How does the immune system recognize what to protect and what to attack This question lies at the heart of new research led by Klaus Ley, MD, founding co-director of the Immunology Center of Georgia at Augusta University. The study sheds light on the delicate balance that keeps the immune system from turning against the body it is meant to protect “The immune system is like the moat around a castle defending against invaders like viruses and bacteria,” said Ley “But when it attacks the castle itself — your own body — you get severe autoimmune diseases like type 1 diabetes and lupus.” The research focused on specific molecules which act as “brakes” on self-reactive T cells — immune cells that would mistakenly target the body’s own tissues By analyzing all of the possible protein fragments that the mouse immune system can recognize and respond to the team found that the self-reactive T cells were not eliminated by the thymus they compared the molecules in self-reactive and foreign-reactive T cells and found that blocking PD-1 and CD73 unleashed a robust immune response to self matching the intensity of the response to foreign invaders like viruses This discovery could have major implications for autoimmune diseases and immunotherapy for cancer and heart disease “Autoimmune diseases occur when the immune system attacks self,” Ley said we often aim to stimulate the immune system to attack cancer cells but this sometimes comes with the tradeoff of triggering autoimmunity.” The study highlights the potential for fine-tuning immune responses by targeting PD-1 and CD73 potentially opening doors to new treatments suppressing these molecules could help treat autoimmune diseases by calming overactive immune responses while blocking them could enhance cancer treatments by boosting the immune attack on tumors The research team used computational analysis to evaluate the entire mouse immune peptidome — a staggering 21 million possible peptides “This work would have been impossible without advanced computing power,” Ley said “We analyzed all possible peptides in mice helping us identify patterns that are relevant to immune responses.” The findings also challenge traditional theories about how the immune system distinguishes self from foreign While the thymus — a small organ behind the breastbone — does help eliminate some self-reactive T cells during development the study showed this is only a minor factor molecules like PD-1 and CD73 play a more significant role in regulating these responses Ley’s mentees has been a great experience for which I am grateful,” Nettersheim said “I am excited about the continuation of our research and feel optimistic that our findings might eventually help to establish strategies for prevention of autoimmunity in patients undergoing cancer immunotherapy and beyond.” the team plans to explore whether these findings hold true in humans and whether the results apply broadly or are specific to certain types of self-antigens One promising avenue involves studying T cells in plaque from patients with atherosclerosis a condition linked to heart attacks and strokes “This research helps us know what to look for,” Ley said “making it easier to identify similar mechanisms in human diseases.” Discoveries at Augusta University are changing and improving the lives of people in Georgia and beyond. Your partnership and support are invaluable as we work to expand our impact Heather Henley is Director of Scientific Communications at the Immunology Center of Georgia part of the Medical College of Georgia at Augusta University Jagwire is your source for news and stories from Augusta University Daily updates highlight the many ways students researchers and clinicians "bring their A games" in classrooms and clinics on four campuses in Augusta and locations across the state of Georgia Metrics details Vaccination with self- and foreign peptides induces weak and strong expansion of antigen-specific CD4+ T cells we used computational analysis of the entire mouse major histocompatibility complex class II peptidome to test how much of the naive CD4+ T cell repertoire specific for self-antigens was shaped by negative selection in the thymus and found that negative selection only partially explained the difference between responses to self and foreign we identified higher expression of programmed cell death protein 1 (PD-1) and CD73 mRNA and protein on self-specific CD4+ T cells compared with foreign-specific CD4+ T cells Pharmacological or genetic blockade of PD-1 and CD73 significantly increased the vaccine-induced expansion of self-specific CD4+ T cells and their transcriptomes were similar to those of foreign-specific CD4+ T cells We concluded that PD-1 and CD73 synergistically limited CD4+ T cell responses to self These observations have implications for the development of tolerogenic vaccines and cancer immunotherapy Prices may be subject to local taxes which are calculated during checkout All new software used to generate the results in this manuscript was written in Python and is available via GitHub at https://github.com/sinkovit/MHCII-processing Multistep pathogenesis of autoimmune disease CD4+ T cell tolerance to tissue-restricted self antigens is mediated by antigen-specific regulatory T cells rather than deletion How autoreactive thymocytes differentiate into regulatory versus effector CD4+ T cells after avoiding clonal deletion CD4+ T cell anergy prevents autoimmunity and generates regulatory T cell precursors Clonal deletion prunes but does not eliminate self-specific αβ CD8+ T lymphocytes CD8 T cell tolerance results from eviction of immature autoreactive cells from the thymus Negative selection—clearing out the bad apples from the T-cell repertoire The self-obsession of T cells: how TCR signaling thresholds affect fate ‘decisions’ and effector function Quantitative impact of thymic selection on Foxp3+ and Foxp3− subsets of self-peptide/MHC class II-specific CD4+ T cells T cell receptor cross-reactivity between similar foreign and self peptides influences naive cell population size and autoimmunity Tolerance is established in polyclonal CD4+ T cells by distinct mechanisms according to self-peptide expression patterns Pathogenic autoimmunity in atherosclerosis evolves from initially protective apolipoprotein B100-reactive CD4+ T-regulatory cells Single-cell T cell receptor sequencing of paired human atherosclerotic plaques and blood reveals autoimmune-like features of expanded effector T cells Khan, A., Roy, P. & Ley, K. Breaking tolerance: the autoimmune aspect of atherosclerosis. Nat. Rev. Immunol. https://doi.org/10.1038/s41577-024-01010-y (2024) Autoimmune regulator (AIRE) deficiency does not affect atherosclerosis and CD4 T cell immune tolerance to apolipoprotein B Nettersheim, F. S. et al. Single-cell transcriptomes and T cell receptors of vaccine-expanded apolipoprotein B-specific T cells. Front. Cardiovasc. 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The ectonucleotidases CD39 and CD73 on T cells: the new pillar of hematological malignancy. Front. Immunol. https://doi.org/10.3389/fimmu.2023.1110325 (2023) Peptide:MHCII tetramer-based cell enrichment for the study of epitope-specific CD4+ T cells Murine cytomegalovirus promotes renal allograft inflammation via Th1/17 cells and IL-17A The diverse functions of the PD1 inhibitory pathway Adenosine mediates functional and metabolic suppression of peripheral and tumor-infiltrating CD8+ T cells Ohta, A. & Sitkovsky, M. Extracellular adenosine-mediated modulation of regulatory T cells. Front. 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Med. https://doi.org/10.1084/jem.20182232 (2020) PD-1+ regulatory T cells amplified by PD-1 blockade promote hyperprogression of cancer Induction of T cell anergy: integration of environmental cues and infectious tolerance Partnering for the major histocompatibility complex class II and antigenic determinant requires flexibility and chaperons High prevalence of low affinity peptide–MHC II tetramer–negative effectors during polyclonal CD4+ T cell responses Low-affinity CD4+ T cells are major responders in the primary immune response Isolation of a structural mechanism for uncoupling T cell receptor sgnaling from peptide-MHC binding Tuning T cell receptor sensitivity through catch bond engineering CD39/CD73/A2AR pathway and cancer immunotherapy Full-length RNA-seq from single cells using Smart-seq2 A sensitive and integrated approach to profile messenger RNA from samples with low cell numbers Metascape provides a biologist-oriented resource for the analysis of systems-level datasets Sinkovits, R. MHC II binding predictions. Figshare https://doi.org/10.6084/m9.figshare.15057975.v1 (2024) Download references Jenkins (Department of Microbiology and Immunology Minneapolis) for providing tetramers and for helpful discussions Peters for help with bioinformatic analyses We thank the flow cytometry and sequencing core facilities at the La Jolla Institute for Immunology for assistance with cell sorting and sequencing We wish to acknowledge the work of expert personnel at the Integrated Genomics Core Sheared Resources at Augusta University Georgia Cancer This work was supported by the German Research Foundation (grant no the Tullie and Rickey Families SPARK Awards for Innovations in Immunology at La Jolla Institute (to F.S.N.) and the National Institutes of Health (grant nos The FACSAria-3 cell sorter and the NovaSeq 6000 system were acquired through the Shared Instrumentation Grant Program (FACSAria II Cell Sorter S10 RR027366; NovaSeq 6000 S10OD025052) decision to publish or preparation of the manuscript These authors contributed equally: Felix Sebastian Nettersheim provided critical collaborative input and supportive data All authors discussed the data and reviewed the manuscript before submission All authors read and approved the final manuscript He receives no compensation from Atherovax No Atherovax funds were used in the present study The other authors declare no competing interests Nature Immunology thanks Stephen Jameson and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available in collaboration with the Nature Immunology team Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations Cells stained with both p6-MHCII-tetramers (a) For random peptides with uniform amino acid distribution and no requirement for MHC-II binding (b) For amino acid distribution in the mouse proteome and no requirement for MHC-II binding (c) For amino acid distribution in the mouse proteome restricted to peptides binding MHC-II at ≤ 1 μM Source data Number of tetramer+ foreign and self peptide-specific CD4+ T cells in naïve (unimmunized and uninfected) in naïve C57BL/6 J mice (a) and C57BL/6 J mice vaccinated (one injection in CFA) with the respective peptides (b). All peptides used in this analysis are listed in Supplementary Table 2 Naïve (a): n = 19 (foreign) and 3 (self); Vaccinated (b): n = 24 (foreign) and 22 (self) Statistical significance was determined by two-sided Mann Whitney test Source data (a) Cumulative flow cytometry plots of p6 and m25 tetramer(same tetramers labeled with PE and APC)-stained CD4+ T cells and total number of m25+CD4+ T cells and p6+CD4+ T cells per mouse in naïve C57BL/6 J mice (n = 9 biological replicates (b) Frequencies of FR4+ CD73+ and PD1+ CD73+ cells among Foxp3−CD44+ m25+CD4+ T cells and p6+CD4+ T cells naïve C57BL/6 J mice (n = 9 biological replicates (c) Frequencies of FR4+ CD73+ and PD1+ CD73+ cells among Foxp3+ m25+CD4+ T cells and p6+CD4+ T cells naïve C57BL/6 J mice (n = 9 biological replicates (a-c) Statistical significance was determined by two-sided paired t test Source data (a) Representative flow cytometry plots of p6+CD4+ T cells costained with PE-tetramer and APC-tetramer in unimmunized (naïve) C57BL/6 J mice C57BL/6 J mice treated with adjuvant (CFA= Complete Freund’s adjuvants) only p6-immunized PD1 KO (B6.Cg-Pdcd1tm1.1Shr/J) mice and p6-immunized CD73 KO (B6.129S1-Nt5etm1Lft/J) mice (b) Frequencies and total numbers of p6+CD4+ T cells in naïve C57BL/6 J mice (n = 10) C57BL/6 J mice treated with adjuvant (CFA) only (n = 5) and fold-change difference in the number of p6+CD4+ T cells in p6-immunized C57BL/6 J mice (n = 10) and p6-immunized CD73 KO mice (n = 7) compared to naive C57BL/6 mice (n = 10) Statistical significance was determined by one-way ANOVA with Tukey’s multiple comparisons test for normally distributed data (p6+CD4+ T cell number and fold change expansion) or Kruskal-Wallis test with Dunn’s multiple comparisons test if data was not normally distributed (p6+CD4+ T cell frequency) Source data (a) Cumulative flow cytometry plots of PD1 (BV605) and CD73 (FITC) expression in p6+CD4+ T cells in non-immunized (naïve) C57BL/6 J mice (n = 5) or in C57BL/6 J mice immunized with p6 in CFA (1x) and treated intraperitoneally (i.p.) with 200 µg of the PD1 blocking antibody 29 F.1A12 (PD1 Ab 20 mg/kg of the small molecule CD73 inhibitor AB680 (CD73 Inh or both (n = 10) every other day for 14 days PD1 was stained with the same antibody clone that was used for in vivo blocking and CD73−PD1− p6+CD4+ T cells (shown as percentage of all p6+CD4+ T cells) in non-immunized (naïve) C57BL/6 J mice and C57BL/6 J mice immunized with p6 in CFA (1x) and treated with PD1 Ab and/or CD73 Inh or left untreated as in a (n = 5 (naïve and p6+CD73Inh) Due to very low cell numbers ( < 10 cells in all but one sample) the frequencies of the unimmunized group could be imprecise Statistical significance was determined by Kruskal-Wallis test with Dunn’s multiple comparisons test Source data (a) Cumulative flow cytometry plots of CD25+ (APC-Cy7) Foxp3+ (BV421) p6+CD4+ Treg cells in C57BL/6 J mice immunized with p6 in CFA (1x) and treated intraperitoneally (i.p.) with 200 µg of the PD1 blocking antibody 29 F.1A12 (PD1 Ab or with the PD1 Ab and 20 mg/kg of the small molecule CD73 inhibitor AB680 (CD73 Inh (b) Frequency of antigen-experienced CD44+CD25+Foxp3+p6+CD4+ Treg cells (shown as percentage of all CD44+p6+CD4+ T cells) in C57BL/6 J mice immunized with p6 in CFA (1x) and treated with PD1 Ab (n = 10) or with PD1 Ab and CD73 Inh (n = 10) or left untreated (n = 9) as in a (c) Frequencies of antigen-experienced CD44+p6+CD4+ T cells expressing the lineage-defining transcription factors Foxp3 (Treg cells) or Gata3 (TH2 cells; shown as percentage of all CD44+p6+CD4+ T cells) in C57BL/6 J mice immunized with p6 in CFA (1x) and treated with PD1 Ab (n = 10) or with PD1 Ab and CD73 Inh (n = 10) or left untreated (n = 9) as in a Statistical significance was determined by one-way ANOVA with Tukey’s multiple comparisons test for normally distributed data (c: RORyt or Kruskal-Wallis test with Dunn’s multiple comparisons test if data was not normally distributed (b Source data (a) Cumulative flow cytometry plots of PD1 (BV605) and CD73 (FITC) expression in m25+CD4+ T cells in C57BL/6 J mice immunized with m25 in CFA (1x) and treated intraperitoneally (i.p.) with 200 µg of the PD1 blocking antibody 29 F.1A12 (PD1 Ab) and 20 mg/kg of the small molecule CD73 inhibitor AB680 (CD73 Inh and CD73−PD1− m25+CD4+ T cells (shown as percentage of all m25+CD4+ T cells) in C57BL/6 J mice immunized with m25 in CFA (1x) and treated with PD1 Ab and CD73 Inh or left untreated as in a (n = 10 mice/group) (c) Cumulative flow cytometry plots of CD25+ (APC-Cy7) Foxp3+ (BV421) m25+CD4+ Treg cells and frequency of antigen-experienced CD44+ CD25+ Foxp3+ m25+CD4+ Treg cells (shown as percentage of all CD44+ m25+CD4+ T cells) in C57BL/6 J mice immunized with m25 in CFA (1x) and treated with PD1 Ab and CD73 Inh or left untreated as in a (n = 10 mice/group) (d) Frequencies of antigen-experienced CD44+ m25+CD4+ T cells expressing the lineage-defining transcription factors Foxp3 (Treg cells) shown as percentage of all CD44+ m25+CD4+ T cells) in C57BL/6 J mice immunized with m25 in CFA (1x) and treated with PD1 Ab and CD73 Inh or left untreated as in a (n = 10 mice/group) Statistical significance was determined by two-sided unpaired t test for normally distributed data (b: PD1+CD73+ d: RORyt and Tbet) or two-sided Mann-Whitney test if data was not normally distributed (b: PD1+CD73− Source data (a) Venn diagram displaying the number of genes that were differentially expressed between p6+CD4+ T cells isolated from p6-immunized C57BL/6 J mice either treated (p6 + PD1Ab/CD73Inh) or not treated (p6) with PD1Ab and CD73 Inh and between m25+CD4+ T cells of m25-immunized C57BL/6 J mice either treated (m25 + PD1Ab/CD73Inh) or not treated (m25) with PD1Ab and CD73 Inh (n = 2 biological replicates per group consisting of pooled samples from 5 mice each) (b) Correlational analysis of the fold changes of all 170 genes that were differentially expressed between p6+CD4+ T cells from p6-immunized C57BL/6 J mice treated and not treated with PD1Ab and CD73 Inh as well as between m25+CD4+ T cells from m25-immunized C57BL/6 J mice treated and not treated with PD1Ab and CD73 Inh (n = 2 biological replicates per group consisting of pooled samples from 5 mice each) Statistical significance was determined by two-sided Pearson’s r test Source data (a) Frequency and (b) total number of p6+CD4+ T cells in draining (para-aortic and inguinal) and non-draining (cervical mesenteric) lymph nodes of C57BL/6 J mice that were immunized (n = 7) or not immunized (n = 4) with p6 Immunized mice received one intramuscular injection of p6 in CFA into both hind limbs 2 weeks prior to euthanasia Statistical significance was determined by two-way ANOVA with Tukey’s multiple comparisons test Source data Differentially expressed genes in p6+CD4+ T cells compared with m25+CD4+ T cells collected from naive (uninfected and unimmunized) C57BL/6J mice Differentially expressed genes in p6+ and m25CD4+ T cells from p6- and m25-immunized C57BL/6J mice that were either untreated or treated with anti-PD1 and CD73 inhibitor Differentially expressed genes between p6+CD4+ T cells from p6-immunized C57BL/6J mice and p6+CD4+ T cells from p6-immunized C57BL/6J mice treated with anti-PD1 and CD73 inhibitor that were coregulated (overlapping) with differentially expressed genes between p6+CD4+ T cells from p6-immunized C57BL/6J mice and m25+CD4+ T cells from m25-immunized C57BL/6J mice Upregulated pathways in p6+CD4+ T cells from p6-immunized C57BL/6J mice treated with anti-PD1 and CD73 inhibitor compared with p6+CD4+ T cells from p6-immunized C57BL/6J mice not treated with anti-PD1 and CD73 inhibitor that were coregulated (overlapping) with upregulated pathways in m25+CD4+ T cells from m25-immunized C57BL/6J mice compared with p6+CD4+ T cells from p6-immunized C57BL/6J mice not treated with anti-PD1 and CD73 inhibitor a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); 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Volume 9 - 2022 | https://doi.org/10.3389/fcvm.2022.1076808 This article is part of the Research TopicAutoimmunity and Cardiovascular DiseaseView all 4 articles Atherosclerotic cardiovascular diseases are the major cause of death worldwide CD4 T cells responding to Apolipoprotein B (ApoB) have been identified as critical disease modulators ApoB-reactive (ApoB+) CD4 T cells are mostly regulatory T cells (Tregs) they may obtain pro-inflammatory features and thus become proatherogenic Evidence from animal studies suggests that vaccination against certain major histocompatibility complex (MHC) II-binding ApoB peptides induces an expansion of ApoB+ Tregs and thus confers atheroprotection in-depth phenotyping of vaccine-expanded ApoB+ T cells has not yet been performed we vaccinated C57BL/6J mice with the ApoB-peptide P6 (ApoB978–993 TGAYSNASSTESASY) and performed single-cell RNA sequencing of tetramer-sorted P6+ T cells P6+ cells were clonally expanded (one major two minor clones) and formed a transcriptional cluster distinct from clusters mainly containing non-expanded P6+ and P6– cells Transcriptomic profiling revealed that most expanded P6+ cells had a strong Treg signature and highly expressed genes mediating suppressive functions some expanded P6+ cells only had a residual Treg signature and expressed genes related to T helper 1 (TH1) cells Modeling the T cell receptor (TCR) and P6:MHC-II interaction showed that only three amino acid residues in the α and β chain contact the P6 peptide in the MHC-II groove and thus determine the specificity of this TCR to P6 Our data begin to reveal the vaccination-induced response to an ApoB epitope in-depth characterization of vaccine-expanded ApoB+ T cells has not been performed Most CD4 T cells express only one αβ heterodimeric TCR per cell. Both TCRα and TCRβ are highly polymorphic, with billions of sequences generated by V(D)J recombination and template-free filling to generate the CDR3 sequences, which are largely responsible for antigen specificity. Single cell RNA sequencing (scRNA-Seq) can be used to assemble paired TCRα and β chains (16–18) Single cell TCR sequences of ApoB-specific CD4 T cells have not been described Here, we combined P6: I-Ab tetramer sorting with Smart-Seq2 scRNA-Seq (single-cell single-well) (19) to obtain full-length transcriptomes and paired TCRα and β chains of P6+ CD4 T cells. This method is more expensive and produces fewer (tens to hundreds) but much better transcriptomes than alternative methods (20, 21) Our data show that immunization with P6 induces oligoclonal expansion of P6+ T cells with a dominating Treg signature We identified upregulation of several genes involved in mediating suppressive functions Our findings are the first full-length transcriptomes and paired α/β TCR sequences from ex vivo T cells specific for an atherosclerosis-related antigen and will help to better understand the autoimmune response in atherosclerosis Seven-week-old C57BL/6J female mice were purchased from The Jackson Laboratory (strain# 000664 Bar Harbor USA) and maintained under specific pathogen-free conditions All animal studies were approved by the local Institutional Animal Care and Use Committee ApoB978–993 (P6: TGAYSNASSTESASY) peptide was purchased from A&A Labs (San Diego Complete (CFA) and incomplete (IFA) Freund’s adjuvants were purchased from SIGMA (St C57BL/6J mice were intramuscularly immunized with 100 μg P6 peptide in 100 μl CFA/PBS (50:50%) at week 0 and 100 μg P6 peptide in 100 μl IFA/PBS (50:50%) at week 2 For each immunization 50 μl were injected into the left and right musculus quadriceps femoris Two weeks after final immunization the inguinal and para-aortic lymph nodes were collected ApoB:MHC monomers were expressed as previously described (11) sequences encoding the antigenic peptide ApoB 978–993 were fused to the N-terminus of the mouse MHC-II (I-Ab) beta chain by a flexible polyglycine linker in the pRMHa-3 expression vector and co-expressed in Drosophila melanogaster S2 cells with the mouse MHC-II (I-Ab) alpha chain and BirA ligase Biotinylated ApoB:MHC monomers were purified from culture supernatants using nickel affinity chromatography followed by an additional purification on a Pierce Monomeric Avidin UltraLink Resin column (Thermo Fisher Scientific USA) and coupled to streptavidin-phycoerythrin (PE) or streptavidin-allophycocyanin (APC) (Prozyme Cell suspensions were prepared from draining (inguinal and para-aortic) lymph nodes Lymph nodes were passed through a 70 μm cell strainer and the cell suspension was filtered once more through a 70 μm strainer before washing (400 × g Cells were counted using trypan blue and a Neubauer chamber CD4 + T cells were enriched by a negative magnetic bead separation followed by anti-mouse biotinylated monoclonal antibodies all obtained from Tonbo Biosciences cat.# 30-0425-M001; and streptavidin-coupled magnetic microbeads (Stem Cell Technologies 20 μl of each antibody and 70 μl magnetic beads were used for each mouse Enriched CD4 + T cells were > 90% pure based on surface expression of TCR-β and CD4 as measured by flow cytometry Isolated CD4 T cells were washed (400 × g 4 min at 4°C) and incubated for 30 min at 37°C and 5% CO2 in 100 μl of 50 nM Dasatinib (Stem Cell Technologies) in RPMI supplemented with 10% FCS (Gemini Bio USA) and 1x Pen/Strep (Thermo Fisher Scientific) 1 μl (equaling a final concentration of 10 nM) of ApoB:MHC-streptavidin-PE and ApoB:MHC-streptavidin-APC tetramer were added for an additional 45 min incubation period the supernatant discarded and resuspended in 100 μl of Live/Dead Aqua (Thermo Scientific Fisher) diluted 1:1,000 in PBS After a 30 min incubation on ice in the dark 100 μl of staining buffer (fetal bovine serum 1:50 diluted in PBS) were added to the samples and cells were washed (400 × g The supernatant was discarded and the cells were resuspended in staining buffer with the following anti-mouse monoclonal antibodies at 1:100 dilution: cat.# 104440; TCR-β Alexa Fluor 700 After staining for 30 min on ice in the dark and cells were resuspended in 150 μl staining buffer for sorting with a BD Aria Fusion (BD Biosciences A 70 μm nozzle and medium pressure at 800–1,200 events/s were used to index sort single cells into single wells of a 384-well plate (Thermo Fisher Scientific 90% of the sample volume were used while P6:MHC-negative CD4 T cells were sorted from the remaining 10% Each well contained 4 μl lysis buffer For 1 reaction of lysis buffer 2 μl of diluted RNase inhibitor Thermo Fisher Scientific) and 1 μl of 10 μM Oligo-dT30VN (IdT USA) was diluted 1:20 in 0.2% Triton X-100 (Merck which was diluted in nuclease-free water (Qiagen and centrifuged at 2,000 rpm for 30 s ensuring that all cells were collected in the lysis buffer the plate was incubated for 3 min at 72°C to hybridize the Oligo-dT primer with the mRNA The plate was immediately stored at -80°C until library preparation Single cell libraries were prepared according to the Smart-Seq2-protocol (22, 23) with the following modifications Pre-amplification PCR cycles were increased to 23 to obtain sufficient amounts of cDNA for the sequencing analysis Primer dimers were eliminated by two 0.8x Ampure-XP bead clean ups 0.3–0.5 ng of pre-amplified cDNA were subjected to library preparation with the Nextera XT library preparation kit Barcoded libraries were pooled and sequenced the with a S1 flow cell and a 300-cycle kit on a NovaSeq Illumina platform to obtain 150-bp paired-end reads Quality controls were performed using TapeStation with D5000 high sensitivity tapes (both from Agilent Quantification was performed using Qubit high sensitivity kit (Thermo Fisher Scientific) after PCR preamplification and the PicoGreen assay (Thermo Fisher Scientific) after Nextera XT had been performed Gene body coverage was determined for the upper-middle quartile genes according to QoRTs Mapping rate includes unique as well as multi-mapping reads We used all the reconstructed chains to call TCR clonotypes regardless of productivity or expression level Heatmaps were created using pheatmap (v1.0.12) Chain similarity graph was done using ggraph (v1.0.2) We modeled our TCR sequence by superimposition with the TCRβ chain of YAe62 and manually rebuilt the CDRs where they differed in length and sequence to identify possible contact residues with the ApoB6 peptide The B3K506 (PDB ID 3C5Z) TCRβ chain was slightly more diverse in sequence and was excluded as a template for modeling Common TCR α and β chains among the P6+ and P6– cells green and blue circle) have at least one chain in common amongst themselves A few non-expanded P6+ cells also have some common chains with expanded P6+ cells even though they may not belong to the same clonotype P6– cells mostly do not have chains in common Lines represent at least one common chain between the cells at its termini Line color represents which chain (s) is shared Clonotypes were based on having the exact same reconstructed chains for both productive and non-productive chains Cells with no successful reconstructed chains were not included in this figure Productive α and β chain reconstruction for the P6+ cells (A) Pie charts depicting the frequency of each gene for V and J segment in both productive chains among tetramer+ cells (B) Table listing the reconstructed genes for each productive chain among P6+ cells as well as the size of the clonotype Blank fields represent cases in which the reconstruction algorithm failed to reconstruct a chain Two unexpanded cells were excluded because no productive chains were identified Clonotype calling was based on both productive and non-productive chains Clustering based on transcriptional profiles correlates with clonality This projection is based on the first 8 principal components of the normalized imputed expression data of the highly variable genes Graph-based clustering revealed three major clusters (orange (B) The same UMAP projection but with cells labeled according to their clonotypes Expanded P6+ cells are separated into three clonotypes (orange blue) based on their productive and non-productive TCRα and TCRβ chains Expanded group 3 (blue) cells are separated from the remainder of the expanded P6+ cells Undetermined cells are cells for which TCR information is unavailable whereas the TH2 signature was weaker compared to cluster 2 Cluster 4 was largely populated by unexpanded P6+ cells and contained only one cell from expanded group 1 (orange) These cells showed a weak residual Treg signature and low levels of Rora as well as Ifngr1 Some of these cells expressed the TFH marker genes Slamf6 and Asap1 Hierarchical clustering of the normalized expression heatmap of 38 lineage-defining genes across all P6+ cells Columns were clustered according to Ward’s second clustering criterion Four segments were automatically generated based on the hierarchical clustering All clusters with expanded P6+ cells (clusters 1 (A) Overview of the TCR/I-Ab/ApoB P6 complex with I-Ab in gray TCRα in orange and TCRβ in green (B) Binding of the ApoB P6 peptide in the I-Ab binding groove identifies amino acid residues that are accessible for TCR binding (D) TCRα contact residues highlighted orange and TCRβ residues green The ApoB P6 core peptide is underlined and contact residues are highlighted yellow our data can particularly help to identify P6+ cells in the setting of atherosclerosis almost all (94%) expanded P6+ cells were characterized by high expression of genes known to mediate the suppressive capacity of Tregs These findings are consistent with the idea that Tregs critically contribute to the atheroprotective effect of ApoB-related vaccines The identified candidate genes will help to monitor Treg-related protective immunity during atherogenesis and in response to immunization strategies the majority of expanded P6+ cells co-expressed some markers typical for other TH-lineages Our data may help to guide future studies investigating the role of such co-expression in the context of immunization against ApoB as well as atherogenesis in general Unexpanded P6+ cells exhibited low expression of most lineage-defining genes and might likely represent naïve T cells that have either not encountered P6 or were not sufficiently activated. Some of these cells expressed a TFH profile, led by Slamf6 (69) and Asap1 (70), which is in accordance with a recent report that aortic Tregs can convert into TFH cells (71) Reconstruction of the TCR α and β chain allowed us to model and analyze the interaction between IAb-bound P6 and the most abundant TCR clone (TRAV7D-6 This modeling revealed that only three contiguous amino acid residues determine the TCR specificity for P6 (AGN and RGR in the TCR α and β chain Knowing which features determine the TCR specificity to P6 can be a valuable resource for predicting and evaluating potential cross-reactivities between ApoB and other antigens in future studies our study identifies oligoclonal expansion of CD4 T cells in response to vaccination with ApoB-P6 Most of the clonally expanded cells expressed a clear Treg signature and showed an upregulation of genes involved in mediating the suppressive function The successful reconstruction of TCRα and β in most cells combined with the known peptide epitope defined by sorting with P6:I-Ab tetramer provides complete structural information on an ApoB-specific TCR with peptide-loaded MHC-II Our data is a resource for future studies investigating vaccination strategies with ApoB to modulate proatherogenic autoimmunity The data presented in this study are deposited in the GEO repository and YG wrote the manuscript and prepared the figures TD and MJ contributed to the research materials All authors contributed to the data research and reviewed the manuscript before submission and have read and agreed to the published version of the manuscript This work was supported by the Deutsche Forschungsgemeinschaft (NE 2574/1-1 to FSN and WI 4811/1-1 to HW) and the National Institutes of Health (R01 HL121697 We would like to thank the La Jolla Institute’s Flow Cytometry Facility and Cheryl Kim for excellent assistance in cell sorting We would also like to thank the La Jolla Institute Genomic core facility for sequencing the single cell transcriptomes He received no compensation from Atherovax No Atherovax funds were used in this study The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fcvm.2022.1076808/full#supplementary-material How the immune system shapes atherosclerosis: roles of innate and adaptive immunity Targeting the immune system in atherosclerosis PubMed Abstract | CrossRef Full Text | Google Scholar T cell subsets and functions in atherosclerosis Pathogenic autoimmunity in 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This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) distribution or reproduction in other forums is permitted provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited in accordance with accepted academic practice distribution or reproduction is permitted which does not comply with these terms *Correspondence: Klaus Ley, a2xhdXNAbGppLm9yZw==, a2xleUBhdWd1c3RhLmVkdQ== Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher 94% of researchers rate our articles as excellent or goodLearn more about the work of our research integrity team to safeguard the quality of each article we publish Credit: Credit: Orchestrated in MidJourney by TA 2023 The discovery of a “lost world” of ancient organisms that lived in Earth’s waterways at least 1.6 billion years ago could change our understanding of our earliest ancestors. Known as the ‘Protosterol Biota’ these microscopic creatures are part of a family of organisms called eukaryotes Eukaryotes have a complex cell structure that includes mitochondria known as the “powerhouse” of the cell and a nucleus that acts as the “control and information centre” Modern forms of eukaryotes that inhabit Earth today include fungi animals and single-celled organisms such as amoebae Humans and all other nucleated creatures can trace their ancestral lineage back to the Last Eukaryotic Common Ancestor (LECA) LECA lived more than 1.2 billion years ago. was made by researchers from The Australian National University (ANU) these organisms could have been the first predators on Earth. These ancient creatures were abundant in marine ecosystems across the world and probably shaped ecosystems for much of Earth’s history The researchers say the Protosterol Biota lived at least one billion years before any animal or plant emerged. “Molecular remains of the Protosterol Biota detected in 1.6-billion-year-old rocks appear to be the oldest remnants of our own lineage – they lived even before LECA These ancient creatures were abundant in marine ecosystems across the world and probably shaped ecosystems for much of Earth’s history,” Dr Benjamin Nettersheim who completed his PhD at ANU and is now based at the University of Bremen in Germany “Modern forms of eukaryotes are so powerful and dominant today that researchers thought they should have conquered the ancient oceans on Earth more than a billion years ago. “Scientists have long searched for fossilised evidence of these early eukaryotes but their physical remains are extremely scarce Earth’s ancient oceans rather appeared to be largely a bacterial broth. “One of the greatest puzzles of early evolution scientists have been trying to answer is: why didn’t our highly capable eukaryotic ancestors come to dominate the world’s ancient waterways “Our study flips this theory on its head We show that the Protosterol Biota were hiding in plain sight and were in fact abundant in the world’s ancient oceans and lakes all along Scientists just didn’t know how to look for them – until now.” who made the discovery with Dr Nettersheim said the Protosterol Biota were certainly more complex than bacteria and presumably larger although it’s unknown what they looked like. “We believe they may have been the first predators on Earth hunting and devouring bacteria,” Professor Brocks said. these creatures thrived from about 1.6 billion years ago up until about 800 million years ago. The end of this period in Earth’s evolutionary timeline is known as the ‘Tonian Transformation’ But exactly when the Protosterol Biota went extinct is unknown. “The Tonian Transformation is one of the most profound ecological turning points in our planet’s history,” Professor Brocks said. “Just as the dinosaurs had to go extinct so that our mammal ancestors could become large and abundant perhaps the Protosterol Biota had to disappear a billion years earlier to make space for modern eukaryotes.” the researchers studied fossil fat molecules found inside a 1.6-billion-year-old rock that had formed at the bottom of the ocean near what is now Australia’s Northern Territory The molecules possessed a primordial chemical structure that hinted at the existence of early complex creatures that evolved before LECA and had since gone extinct. we would never have known that the Protosterol Biota existed Early oceans largely appeared to be a bacterial world but our new discovery shows that this probably wasn’t the case,” Dr Nettersheim said. Professor Brocks said: “Scientists had overlooked these molecules for four decades because they do not conform to typical molecular search images.” “But once we knew what we were looking for taken from billion-year-old waterways across the world were also oozing with similar fossil molecules.” Dr Nettersheim completed the analysis as part of his PhD at ANU before accepting a position at the University of Bremen This work involved scientists from Australia 10.1038/s41586-023-06170-w Lost world of complex life and the late rise of the eukaryotic crown are not responsible for the accuracy of news releases posted to EurekAlert by contributing institutions or for the use of any information through the EurekAlert system Copyright © 2025 by the American Association for the Advancement of Science (AAAS) Metrics details Germ cell tumors (GCT) might undergo transformation into a somatic-type malignancy (STM) resulting in a cell fate switch to tumors usually found in somatic tissues such as rhabdomyosarcomas or adenocarcinomas but the molecular and epigenetic mechanisms triggering STM are still enigmatic the tissue-of-origin is under debate and biomarkers are lacking we characterized a unique cohort of STM tissues on mutational epigenetic and protein level using modern and high-throughput methods like TSO assays 850k DNA methylation arrays and mass spectrometry we show that based on DNA methylation and proteome data carcinoma-related STM more closely resemble yolk-sac tumors while sarcoma-related STM resemble teratoma STM harbor mutations in FGF signaling factors (FGF6/23 FGFR1/4) highlighting the corresponding pathway as a therapeutic target and WNT to mediate molecular functions coping with oxidative stress these data might explain the high therapy resistance of STM we identified putative novel biomarkers secreted by STM and DNA methylation at specific CpG dinucleotides treatment guidelines are still missing due to a lack of knowledge about this special group of cancers and their biology the developmental origin and the underlying molecular and (epi)genetic mechanisms of STM formation remain elusive Since specific treatments are still lacking further research on the origin and pathogenesis of STM and the identification of potential therapeutic targets this study characterized the molecular and (epi)genetic features of STM on mutational and proteome level to identify the key processes driving STM formation and related therapy resistance the tissue-of-origin as well as new therapeutic options and novel biomarkers 26 samples were analyzed (10 adenocarcinoma The STM area was highlighted on H&E-stained slides prior to the analysis by a reference pathologist for GCT Only the marked areas were isolated from the FFPE-slides DNA was extracted from 2×5 µm FFPE slices using the InnuPREP FFPE DNA Kit on the InnuPure C16 System (Jena Analytika Germany) according to manufacturer instructions RNA was isolated from 2×5 µm slices using the Maxwell RNA extraction kit (Promega Germany) according to manufacturer’s recommendations DNA and RNA concentrations were measured on the Qubit 3 Fluorometer (ThermoScientific A fold change normalized to controls of > 2 was set as a cut-off value for samples considered to harbor a 12p gain ten samples were analyzed (two adenocarcinoma DNA libraries were prepared using the hybrid capture-based TSO Library Preparation Kit (Illumina USA) following the manufacturer’s instructions (#1000000067621 v00) Library concentrations and peak heights were evaluated on a Tape Station (Agilent Equal amounts of up to eight library samples were pooled and diluted to 4 nM 10 µl of the library pool was mixed in 0.1 M NaOH and incubated for 5 min at RT The library was neutralized and diluted to 20 pMwith 990 µl HT1 To generate 200,000 clusters/mm2 the pool was diluted to 0.6 pM by the addition of 1261 µl HT1 39 µl library (20 pM) and 1 µl PhiX (20 pM) Libraries were sequenced on an Illumina NextSeq 500 instrument The FastQ files were analyzed in CLC Biomedical Workbench (Qiagen) Reads were mapped to hg19 followed by initial variant calling and low-frequency variant calling were performed False-positives were removed based on read quality and forward/reverse balance All variants were checked manually for sequencing artefacts The average coverage was > 500 in all samples; the mutations had at least 50 variant reads 11 samples were analyzed (2 adenocarcinoma DNA was isolated from FFPE tissue using the ReliaPrep™ FFPE gDNA Miniprep System (Promega Germany) according to manufacturer’s instructions 100–500 ng DNA were used for bisulfite conversion with the EZ DNA Methylation Kit (Zymo Research the DNA Clean & Concentrator-5 (Zymo Research) and the Infinium HD FFPE DNA Restore Kit (Illumina) were used to clean and restore the converted DNA the Infinium MethylationEPIC BeadChip (Illumina) was used to evaluate the methylation status of 850,000 CpG sites on an iScan device (Illumina) 11 samples were analyzed (5 adenocarcinoma FFPE tissues were deparaffinized by shaking in 500 µL Xylene for 5 min followed by removal of the solvent and air-dry the residual solvent Tissues were resuspended in 200 µL lysis buffer (300 mM TRIS/HCl shock-frozen in liquid nitrogen and immediately heated for 25 min at 99 °C and 350 rounds per minute (rpm) Samples were ultrasonicated on ice for 20 min with 30 seconds (s) on/off cycles and then shook for 2 hours (h) at 80 °C and 500 rpm followed by a second ultrasonication step After centrifugation for 5 min at 3500 rpm the pellet was resuspended in 100 µL lysis buffer for a second extraction round Supernatants were combined and protein concentration was determined using the Pierce 660 nm Protein Assay (Thermo Fisher Scientific 20 µg total protein were reduced by adding 10 µL 300 mM DTT and shaking for 20 min at 56 °C and 1000 rpm followed by alkylation with the addition of 13 µL 100 mM IAA and incubation for 15 min in the dark 10 µl of a 20 µg/µl bead stock (1:1 Sera-Mag SpeedBeads) were added to each sample ethanol (EtOH) was added to a final concentration of 80% and incubated for 15 min at 20 °C After three rinsing steps with 80% EtOH and one rinsing step with 100% ACN beads were resuspended in 50 mM TEAB buffer and digested with final 1:50 trypsin at 37 °C and 1000 rpm overnight Extra-digestion was carried out by adding trypsin (final 1:50) and shaking at 37 °C and 1000 rpm for 4 h 500 ng of each sample were subjected to LC-MS For the LC-MS acquisition an Orbitrap Fusion Lumos Tribrid Mass Spectrometer coupled to an Ultimate 3000 Rapid Separation liquid chromatography system equipped with an Acclaim PepMap 100 C18 column (75 µm inner diameter 2 mm particle size) as separation column and an Acclaim PepMap 100 C18 column (75 µm inner diameter 2 mm particle size) as trap column (all equipment from Thermo Fisher Scientific) A LC-gradient of 180 min was applied and the MS operated in positive mode with a scan range of 200–2000 m/z at a resolution of 120,000 The capillary temperature was set to 275 °C the normalized AGC target was set to 62.5% and the maximum injection time was 60 ms HCD fragmentations were carried out within a cycle time of 2 s Data were analyzed by Proteome Discoverer (version 2.4.1.15 RAW files were matched against the human Swissprot database (Download: 23.01.2020) and the Maxquant Contaminant database (Download: 20.02.2021) using SequestHT integrated in the LFQ Tribrid processing workflow (Thermo Fisher Scientific) The maximum number of missed cleavages was set to 2 and the peptide length was 6–144 amino acids Precursor mass tolerance was set to 10 ppm and the fragment mass tolerance was 0.6 Dalton All samples were analyzed in a match between run search peptides were ungrouped and filtered to 1% FDR on protein and peptide level and to all proteins identified with ≥ 2 peptides 46 samples were analyzed (7 adenocarcinoma a Pie chart summarizing distribution of the various STM entities analyzed in this study b Clinical parameters of the STM cohort (at diagnosis of STM) from the University Hospital Düsseldorf (Department of Urology) analyzed in this study c Exemplary H&E stainings of each STM entity and IHC staining of typical marker proteins the adenocarcinomas were composed of neoplastic glands with nuclear atypia The proliferation rate (Ki67) was between 30 and 50% The rhabdomysarcomas were composed of spindled rhabdoid cells with pleomorphic nuclei The IHC detected Myogenin+ and Desmin+ cells The carcinomas NOS contained highly atypical cells with pleomorphic nuclei and without any noticeable pattern The IHC detected pan-cytokeratin+ and SALL4− cells The proliferation rate was between 20 and 25% The sarcoma NOS cells were completely pan-cytokeratin- with focal Actin+ cells (without any noticeable pattern) The pleomorphic tumor cells showed a high proliferation rate (> 50%) The angiosarcomas showed anastomosing vascular spaces lined with atypical cells Other parts showed a solid architecture with epithelioid or spindled cells The ENET samples contained small cells with minimal to modest pale eosinophilic cytoplasm and round to oval hyperchromatic nuclei The YST showed a variety of patterns composed of neoplastic glands with prismatic cells a typical arrangement of cells of all three germ layers (ectoderm b Illustration of the tumor mutational burden (TMB; mutations/megabase) and microsatellite instability score (MSI; % unstable) (a) and the ratio of both parameters (b) in STM samples analyzed by the TSO assay c All detected mutations in indicated STM samples Blue dots label mutations found in all samples of a STM subgroup MNV: multiple nucleotide variants; SNV: single nucleotide variants d Overview of drugs targeting found amplified genes/signaling factors a A heatmap including hierarchical clustering and a Pearson’s correlation matrix illustrate similarities and differences in the proteome (abundance > 107) between the various STM groups as well as YST and TER shared and unique proteins (abundance > 107) were identified between the STM entities (b) and compared to YST/TER (c) 363 proteins were found in all analyzed STM entities (b d STRING-based protein-protein-interaction prediction of proteins commonly found in STM entities e DAVID-based GO and KEGG screen for biological processes and functions related to the proteins found exclusively in each STM entity several key molecular functions are shared between STM (ECM interaction although each entity engages different proteins to realize these functions a Distribution of DNA methylation levels (%) across all analyzed CpG dinucleotides b A violin plots illustrates genome-wide distribution of DNA methylation levels C A heatmap and a Pearson’s correlation matrix including hierarchical clustering illustrates and compares DNA methylation data d Distribution of DNA hypo- (< 20%) and hypermethylated (> 80%) CpG dinucleotides across genomic regions/CpG islands Venn diagrams comparing hyper- and hypomethylated CpG dinucleotides in adenocarcinomas (e) and rhabdomyosarcomas (f) with YST and TER g Putative epigenetic biomarkers for adenocarcinomas and/or rhabdomyosarcomas based on the DNA methylation status of single CpG dinucleotides These hypermethylated CpG dinucleotides might serve as epigenetic biomarkers to detect the occurrence of STM we characterized various GCT-related STM subtypes at the mutational DNA methylation and proteome level and compared them to YST and TER The overall mutational burden including amplification fold changes were GCT typically low in STM suggesting that mutations are not a crucial driver of STM formation our data and the correlation to the TCGA GCT cohort suggest that mutations detected in STM arose during formation of STM and are not generally detectable in GCT which might affect drug response (c.215C>G) as well as FGF signaling factors might contribute to the aggressive character of STM by triggering proliferation FGF signaling seems to be a priority target of mutational events mainly small molecule inhibitors and receptor-tyrosine-kinase inhibitors Several completed or ongoing clinical trials screening some of these drugs were found (clinicaltrials.gov); AZD4547: 12 several FGF signaling related therapeutic options for treatment of STM are available and should be screened in follow-up studies and eventually clinical trials to date no drugs targeting the specific mutations found in this study are available a Summary of found mutations common in each STM entity as well as of similarities of STM entities to YST/TER on DNA methylation and proteome level b Summary of molecular and epigenetic processes commonly found in STM entities putatively mediating therapy resistance and interaction with cells of the immune system and the ECM Parts of this figure were generated by biorender.com The clinical data related to our cohort showed that YST (14%) and TER (67%) were the prevalent STM accompanying histology and in 76% of all cases elevated AFP levels were detected These data support the hypothesis that both are tissues-of-origin for the various STM entities 90% of patients received at least three cycles of chemotherapy before diagnosis of a STM suggesting that formation of a STM represents a therapy escape mechanisms for YST/TER cells formation of YST and TER seems to be an escape mechanism itself since mostly YST and TER remain after chemotherapy regimen and are the leading cause of GCT-related death the development of YST or TER from EC under therapy and eventually a STM represents an escalating cascade of escape mechanisms for GCT cells enabling survival found no oncogenic gene fusions in nine patient samples detected distinct DNA methylation patterns for STM (ENET and rhabdomyosarcoma) and GCT samples which is again in line with our 850k array analysis Together with the article published by Wyvekens et al. both studies shed light on the molecular and (epi)genetic features of STM in a unique cohort of patient material providing comprehensive mutation proteome and DNA methylation data as starting point for future studies we show that on a molecular level carcinoma-related STM more closely resemble YST we identified common mutations as well as molecular and epigenetic mechanisms contributing to the therapy resistance of STM we identified new STM biomarkers and therapeutic options to treat STM patients which should be translated into clinical testing Limitations of this study are the relatively small number of samples analyzed for epigenetic and genomic changes in general our cohort represents one of the largest cohorts analyzed in the field but studying more STM cases to confirm and verify our data would be of benefit a molecular and epigenetic similarity between tumor types does not necessarily indicate definitive evolution from a precursor tumor subtype our cohort lacks the primary tumors of each STM patient which would be an important control to recapitulate tumor evolution and STM formation with regard to mutations comparing our findings to TCGA data is only possible for GCT in non-STM context there is a lack of appropriate GCT-related STM model systems cell lines are not available and setting up ex vivo cultures of these rarely occurring STM might be very time challenging and quite hard to organize functional experiments or in vitro drug screenings are limited or not possible although we identified several drugs putatively suitable to target STM setting up clinical trials is also very challenging due to the rarity of the STM phenomenon The datasets and computer code produced in this study are available in the following databases: 850k DNA methylation data: Gene expression omnibus (GSE219033); LC-MS data: ProteomeXchange (PXD039546) Testicular germ-cell tumours in a broader perspective Molecular and epigenetic pathogenesis of germ cell tumors Somatic-type malignancies in testicular germ cell tumors: a clinicopathologic study of 63 cases The 2022 World Health Organization classification of tumours of the urinary system and male genital organs—part a: renal Unusual neoplasms detected in testis cancer patients undergoing post- chemotherapy retroperitoneal lymphadenectomy Management of germ cell tumors with somatic type malignancy: Pathological features Malignant transformation of testicular teratoma: a chemoresistant phenotype Teratoma with malignant transformation in germ cell tumors in men The development of non‐germ cell malignancies within germ cell tumors Teratoma with somatic-type malignant components in germ cell tumors of the testis: a clinicopathologic analysis of 40 cases with outcome correlation Teratoma with somatic-type malignant components of the testis “Somatic-type” malignancies arising from testicular germ cell tumors: a Clinicopathologic study of 124 cases with emphasis on glandular tumors supporting frequent yolk sac tumor origin The pluripotential nature of the mesenchyme-like component of yolk sac tumor Recent developments in the pathology of germ cell tumors The detection of isochromosome i(12p) in malignant germ cell tumours and tumours with somatic malignant transformation by the use of quantitative real-time polymerase chain reaction Extraction and analysis of diagnostically useful proteins from formalin- fixed solid-phase-enhanced sample preparation for proteomics experiments STRING v11: protein–protein association networks with increased coverage supporting functional discovery in genome-wide experimental datasets An interactive tool for comparing lists with Venn’s diagrams EFEMP1 binds the EGF receptor and activates MAPK and Akt pathways in pancreatic carcinoma cells Molecular correlates of male germ cell tumors with overgrowth of components resembling somatic malignancies Download references We thank Anna Pehlke and Olga Dschun for excellent technical assistance DN is supported by the “Deutsche Forschungsgemeinschaft” (NE 1861/8-1) FB is supported by the “Wilhelm-Sander-Stiftung” (2016.041.1/.2/.3) Open Access funding enabled and organized by Projekt DEAL Hanibal Bohnenberger & Philipp Ströbel Medical Faculty and University Hospital Düsseldorf Pailin Pongratanakul & Margaretha Skowron Biological and Medical Research Centre (BMFZ) The authors declare no competing interests The ethics committees of the Heinrich Heine University Düsseldorf and the University Medical Center Göttingen raised no concerns on performing described experiments on used GCT/STM tissues from local biobanks (vote 2020.1247(_1) to DN; vote 20/09/20 to FB Informed consent for use of samples in research was obtained from all subjects Download citation DOI: https://doi.org/10.1038/s41416-023-02425-5 Volume 8 - 2021 | https://doi.org/10.3389/fcvm.2021.812769 This article is part of the Research TopicImmune and Autoimmune Mechanisms in Cardiovascular DiseaseView all 18 articles lipid-driven disease of medium sized arteries which causes myocardial infarction and stroke an adaptive immune response against the plaque-associated autoantigen Apolipoprotein B100 (ApoB) the structural protein component of low-density lipoprotein CD4+ T cells responding to ApoB mainly comprised regulatory T cells which confer immune tolerance and atheroprotection Mice and patients with atherosclerosis harbor increased numbers of proatherogenic ApoB-reactive T-helper cell subsets Given the lack of therapies targeting proatherogenic immunity clarification of the underlying mechanisms is of high clinical relevance where strong autoreactive T cells are eliminated in the process of negative selection we investigated whether the transcription factor autoimmune regulator (AIRE) which controls expression of numerous tissue-restricted self-antigens in the thymus is involved in mediating tolerance to ApoB and whether Aire deficiency might contribute to atherogenesis Mice deficient for Aire were crossbred to apolipoprotein E-deficient mice to obtain atherosclerosis-prone Aire−/− Apoe−/− mice which were fed a regular chow diet (CD) or western-type diet (WD) CD4+ T cells responding to the ApoB peptide p6 were analyzed by flow cytometry We demonstrate that Aire deficiency influences neither generation nor activation of ApoB-reactive T cells and has only minor and overall inconsistent impacts on their phenotype we show that atherosclerotic plaque size is not affected in Aire−/− Apoe−/− compared to Aire+/+ Apoe−/− our data suggests that AIRE is not involved in regulating thymic expression of ApoB or atherosclerosis Alternative mechanisms how ApoB-reactive CD4 T cells are selected in the thymus will have to be investigated Herein we crossed Aire- and apolipoprotein E (Apoe)-deficient (Aire−/− Apoe−/−) mice to test whether lack of AIRE would increase peripheral ApoB-reactive effector T cell numbers and functions and increase atherosclerosis We demonstrate that AIRE-deficiency does neither affect generation of ApoB+ T cells nor their phenotypes and has no impact on atherogenesis pointing toward a dominant role of an alternative central or peripheral mechanism in enabling immune tolerance to ApoB Autoimmune regulator–deficient (Aire−/−) mice on C57BL/6J background were purchased from Jackson Laboratories (cat ME) and crossbred with apolipoprotein E-deficient (Apoe−/−) mice to obtain Aire−/−Apoe−/− mice Mice were housed in a specific pathogen–free environment and fed chow diet (CD) until 10 weeks of age mice were either fed CD or western-type diet (WD) adjusted calories diet with 42% from fat (Harlan Labs Cat #: TD.88137 USA) and remained on CD or WD for 12 weeks until organ collection All animal experiments were conducted in accordance with the institutional guideline for the La Jolla Institute for Immunology animal facility The whole aorta (thoracic and abdominal) was excised and pinned out after paraformaldehyde incubation at room temperature for at least 2 h Atherosclerotic lesions were visualized by Sudan-IV staining and quantified as the percentage Sudan-IV-positive area of the size of the whole aorta Quantification was performed using ImagePro software (Media Cybernetics Cell suspensions were prepared from thymus mesenteric) and incubated with fluorochrome-coupled antibodies against the indicated antigens for 20 min at RT in RPMI-1640 containing 10% rat serum and 10 μg/ml antiCD16/CD32 antibodies to block unspecific Fc-receptor interactions Cells were washed in PBS and fixed in 2% Paraformaldehyde (PFA) for 10 min T-helper cells were identified as CD4+ TCR-β+ Lin− L/D (live/dead dye Transcription factors were stained with a permeabilization/fixation protocol according to the manufacture's recommendations (Thermo Fisher Scientific Tregs were identified as CD4+ Foxp3+ CD25+ TH1 cells were identified as CD4+ Foxp3− T-bet+ TH17 cells were identified as CD4+ Foxp3− RORγt+ TH2 cells were identified as CD4+ Foxp3− T-bet− RORγt− GATA3+ and T follicular helper (TFH) cells were identified as CD4+ T-bet− RORγt− Bcl-6+ T-effector memory subsets were identified as TEM (CD44+ CD62L−) T-central memory cells as TCM (CD44+ and naïve T cells as Tnaïve (CD44− CD62L+) single cell suspensions were prepared from pooled lymph nodes and stained with anti-CD45 (30-F11: Thermo Fisher Scientific) anti-CD4 (RM4–5: Biolegend; San Diego and anti-TCRβ (H57–597: Thermo Fisher Scientific) antibodies the cells were stimulated with cell stimulation cocktail (Thermo Fisher Scientific) and monensin (Thermo Fisher Scientific) for 5 h Dead cells were identified by staining with Ghost Dye UV450 (Tonbo Biosciences) and IC Fixation Buffer (Thermo Fisher Scientific) was used for fixation and permeabilization Samples were acquired with a FACS LSR-II or FACS Fortessa (BD Biosciences all anti-mouse antibodies were purchased from Biolegend (San Diego USA) and used in a final dilution of 1:50 (cytokines/transcription factors/cytoplasmatic proteins) and 1:200 (extracellular markers) Data were analyzed with FlowJo software (Treestar while ApoB:MHC dextramer-APC carried ~12 7 ApoB:MHC monomers and ~9 APC fluorochromes per dextran Non-T cells were identified by fluorochrome-labeled antibodies against CD11b intracellular staining for transcription factors was performed according to the manufacturer's instructions (Thermo Fisher Scientific) Data were analyzed with FlowJo software (Treestar) For calculation of the absolute numbers of ApoB+ T cells leukocyte numbers of enriched CD4+ lymph node T cells were quantified (Hemavet Differences between the groups were evaluated using one-way repeated measures analysis of variance (ANOVA) with a post-hoc Tukey's test P-values < 0.05 were considered statistically significant All statistical analyses were performed using GraphPad Prism 8.4.0 (GraphPad Software Considering that Aire affects thymocytes at the SP stage causes and significance of the observed decrease in DN1 cell counts remain elusive and await confirmation in future studies Thymopoiesis is largely unaffected by AIRE deficiency in male and female Apoe−/− mice (A) Gating scheme for flow-cytometric detection of maturating thymocytes: Double negative (DN) 1 (CD44+CD25−) and DN4 (CD44−CD25−) cells were identified by expression of the surface markers CD44 and CD25 CD4 and CD8 single positive (SP) or double positive (DP) cells were identified as CD44−CD25− cells with expression of CD4 and/or CD8 Regulatory T cells were identified as Foxp3+ CD25+ CD4+ cells and CD25− Treg precursors were identified as Foxp3+ CD25− CD4+ cells (B,C) Quantification of different stages in thymic development in 20-week-old male and female Aire−/−Apoe−/− and Aire−+/+Apoe−/− fed western-type diet for 12 weeks (D) Quantification of thymic CD25− and CD25+ regulatory Tregs Statistical significance was determined by one-way ANOVA with Tukey's multiple comparisons test ***p < 0.001 ****p < 0.0001 whether the gender effect might be overshadowed by the atherosclerotic environment Aire deficiency was associated with an increased neutrophil count in female Apoe−/− mice exposed to a WD and with an increase in eosinophils and decrease in platelets in CD-fed male Apoe−/− mice WD-fed males had a lower proportion of monocytes and CD-fed males had higher relative neutrophil and lower relative lymphocyte counts compared to females these data indicates that Aire deficiency does not induce broad alterations of innate and adaptive immunity these data indicate that AIRE exerts an insignificant effect on the generation and activation of ApoB+ cells in male and female Apoe−/– mice Aire deficiency does not affect generation and activation of ApoB-reactive CD4+ T cells (A) Gating scheme for identification of ApoB+ and ApoB− CD4+ T effector memory (TEM CD44+CD62L+) and naïve T cells (Tnave CD44−CD62L+) by flow-cytometry (B) Absolute counts (left) and frequency (% of CD4+ T cells right) of ApoB+ T cells isolated from lymph nodes of 20-week-old male and female Aire−/−Apoe−/− and Aire−+/+Apoe−/− fed western-type diet for 12 weeks and Tnave ApoB+ and ApoB− T cells Pie charts show the group means of indicated cell types The consistency and relevance of these gender-specific observations are yet unclear and require confirmation in future studies Phenotypes of antigen-experienced ApoB+ T cells are marginally influenced by AIRE deficiency (A) Expression of the transcription factors Foxp3 and RORγt in CD44− ApoB− and CD44+ ApoB+ cells analyzed by flow-cytometry (B,C) Quantification of Foxp3+ and RORγt+ among CD44+ ApoB+ and ApoB− cells isolated from lymph nodes of 20-week-old male and female Aire−/−Apoe−/− and Aire−+/+Apoe−/− fed western-type diet for 12 weeks (D) Quantification of CD4 T cell lineage transcription factors T-bet (TH1) (B,D) Data are expressed as mean ± SD (C) Pie charts show the group means of indicated cell types To determine whether AIRE deficiency affects atherogenesis, we quantified en face atherosclerotic lesions in the aorta. In line with previous data (31), lesion size in Apoe−/– mice fed a WD was higher compared to those fed a CD (Figures 4A,B) Aire deficiency did not influence plaque growth Atherosclerotic lesion size is not influenced by Aire deficiency Representative images quantification of Sudan IV-stained atherosclerotic plaques within the aorta of 20-week-old male and female Aire−/−Apoe−/− and Aire−+/+Apoe−/− mice (A) fed chow diet (n = 6–15 per group) and (B) western-type diet Apoe−/− mice (n = 10–15 per group) Plaque size was calculated as percentage of whole aortic area It can thus not be excluded that thymic expression of some ApoB peptides might be AIRE-dependent we show here that the CD4+ T cell response toward ApoB p6 and atherosclerotic burden was unaffected by AIRE-deficiency The restriction to p6 does not allow direct inferences on the role of Aire in modulating generation or phenotypic alterations of CD4+ T cells responding to other ApoB peptides a clinically relevant effect can almost certainly be excluded since Aire-deficiency had absolutely no influences on atherogenesis Adaptive immunity against ApoB is centrally involved in atherogenesis and specific therapies to modulate this proatherogenic immune responses do not yet exist it is of high clinical relevance to clarify mechanisms of central and/or peripheral immune tolerance to ApoB thymic DCs and B cells in enabling central tolerance to ApoB and the underlying mechanisms of ApoB T cell phenotype switching need to explored in future studies It may thus be interesting to investigate whether IL-4 harbors specific atheroprotective properties in females Further work will be needed to elucidate the confirmability and biological importance of herein-revealed sex-related differences in immune cell composition during atherogenesis this study excludes AIRE as a mediator of central immune tolerance to ApoB and player in atherogenesis Clarification of mechanisms underlying proatherogenic auto-immunity represents a fundamental requirement for development of anti-atherosclerotic immune therapies The original contributions presented in the study are included in the article/Supplementary Material further inquiries can be directed to the corresponding author/s HW and KL conceptualized and supervised the work and provided funding All authors substantially contributed to data research and read and agreed to the published version of the manuscript This research was funded by the Deutsche Forschungsgemeinschaft SFB TRR259 (397484323) and CCRC GRK2407 (360043781 to HW) the Koeln Fortune Program (363/2020 to FN) The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/fcvm.2021.812769/full#supplementary-material Immunity and inflammation in atherosclerosis PubMed Abstract | CrossRef Full Text | Google Scholar PubMed Abstract | CrossRef Full Text | Google Scholar Regulatory CD4+ T cells recognize major histocompatibility complex class II molecule-restricted peptide epitopes of apolipoprotein B Pathogenic autoimmunity in atherosclerosis evolves from initially protective ApoB-reactive CD4 + T-regulatory cells Depletion of FOXP3+ regulatory T cells promotes hypercholesterolemia and atherosclerosis Low levels of circulating CD4+FoxP3+ T cells are associated with an increased risk for development of myocardial infarction but not for stroke doi: 10.1146/ANNUREV-IMMUNOL-042718-041717 Zúñiga-Pflücker JC Positive and negative selection of the T cell repertoire: what thymocytes see (and don't see) Central CD4+ T cell tolerance: deletion versus regulatory T cell differentiation Naturally arising Foxp3-expressing CD25+CD4+ regulatory T cells in immunological tolerance to self and non-self PubMed Abstract | CrossRef Full Text | Google Scholar Projection of an immunological self shadow within the thymus by the aire protein Rapid chromatin repression by Aire provides precise control of immune tolerance caused by mutations in a novel gene featuring two PHD-type zinc-finger domains Aire deficient mice develop multiple features of APECED phenotype and show altered immune response Development of autoimmunity against transcriptionally unrepressed target antigen in the thymus of aire-deficient mice The cellular mechanism of aire control of T cell tolerance Spatial mapping of thymic stromal microenvironments reveals unique features influencing T lymphoid differentiation Promiscuous gene expression in thymic epithelial cells is regulated at multiple levels Population and single-cell genomics reveal the Aire dependency and distribution of self-antigen expression in thymic epithelia Detection of autoreactive CD4 T cells using major histocompatibility complex class II dextramers Aire enforces immune tolerance by directing autoreactive T cells into the regulatory T cell lineage Aire-dependent production of XCL1 mediates medullary accumulation of thymic dendritic cells and contributes to regulatory T cell development Aire-dependent thymic development of tumor-associated regulatory T cells Generation of Foxp3+CD25– regulatory T-cell precursors requires c-rel and IκBNS ApoE-deficient mice develop lesions of all phases of atherosclerosis throughout the arterial tree PubMed Abstract | CrossRef Full Text | Google Scholar CCR5+ T-bet+ FoxP3+ effector CD4 T cells drive atherosclerosis T-bet deficiency reduces atherosclerosis and alters plaque antigen-specific immune responses Atheroprotective vaccination with MHC-II restricted peptides from ApoB-100 Apolipoprotein AI prevents regulatory to follicular helper T cell switching during atherosclerosis Atherosclerosis-driven treg plasticity results in formation of a dysfunctional subset of plastic IFNγ+ Th1/Tregs PubMed Abstract | CrossRef Full Text | Google Scholar Sex bias in CNS autoimmune disease mediated by androgen control of autoimmune regulator Estrogen-mediated downregulation of AIRE influences sexual dimorphism in autoimmune diseases Effects of sex and age on atherosclerosis and autoimmunity in apoE-deficient mice PubMed Abstract | CrossRef Full Text | Google Scholar Consistent production of a higher TH1:TH2 cytokine ratio by stimulated T cells in men compared with women Progesterone favors the development of human T helper cells producing Th2-type cytokines and promotes both IL-4 production and membrane CD30 expression in established Th1 cell clones Ley K and Winkels H (2022) Autoimmune Regulator (AIRE) Deficiency Does Not Affect Atherosclerosis and CD4 T Cell Immune Tolerance to Apolipoprotein B Received: 10 November 2021; Accepted: 21 December 2021; Published: 13 January 2022 Copyright © 2022 Nettersheim, Braumann, Kobiyama, Orecchioni, Vassallo, Miller, Ali, Roy, Saigusa, Wolf, Ley and Winkels. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) *Correspondence: Holger Winkels, aG9sZ2VyLndpbmtlbHNAdWsta29lbG4uZGU= Metrics details The protosteroids reveal an ecologically prominent ‘protosterol biota’ that was widespread and abundant in aquatic environments from at least 1,640 to around 800 million years ago and that probably comprised ancient protosterol-producing bacteria and deep-branching stem-group eukaryotes Modern eukaryotes started to appear in the Tonian period (1,000 to 720 million years ago) fuelled by the proliferation of red algae (rhodophytes) by around 800 million years ago This ‘Tonian transformation’ emerges as one of the most profound ecological turning points in the Earth’s history All processed data generated during this study are included in this published article and its supplementary information files Raw data are available from the corresponding author on reasonable request 1.1-Billion-year-old porphyrins establish a marine ecosystem dominated by bacterial primary producers Integrated genomic and fossil evidence illuminates life’s early evolution and eukaryote origin and Other Essays in Biochemistry 14–36 (Yale Univ On the age of eukaryotes: evaluating evidence from fossils and molecular clocks Estimating the timing of early eukaryotic diversification with multigene molecular clocks A late origin of the extant eukaryotic diversity: divergence time estimates using rare genomic changes Paleobiological perspectives on early eukaryotic evolution Micropaleontology of the lower Mesoproterozoic Roper Group and implications for early eukaryotic evolution sp.: implications for the evolution of sex and the Mesoproterozoic/Neoproterozoic radiation of eukaryotes A one-billion-year-old multicellular chlorophyte Early fungi from the Proterozoic era in Arctic Canada Testate amoebae in the Neoproterozoic Era: evidence from vase-shaped microfossils in the Chuar Group Deciphering the evolutionary history of microbial cyclic triterpenoids The rise of algae in Cryogenian oceans and the emergence of animals Free and kerogen-bound biomarkers from late Tonian sedimentary rocks record abundant eukaryotes in mid-Neoproterozoic marine communities Phylogenomics of sterol synthesis: insights into the origin Variations in the sterane carbon number distributions of marine source rock derived crude oils through geological time Cryogenian evolution of stigmasteroid biosynthesis Lipid taphonomy in the Proterozoic and the effect of microbial mats on biomarker preservation Absence of biomarker evidence for early eukaryotic life from the Mesoproterozoic Roper Group: Searching across a marine redox gradient in mid-Proterozoic habitability Insights into eukaryogenesis from the fossil record Proterozoic ocean chemistry and evolution: a bioinorganic bridge animals and oceanic ventilation: an alternative view The transition from a cyanobacterial to algal world and the emergence of animals Microbial assemblage and paleoenvironmental reconstruction of the 1.3 Ga Velkerri Formation Biomarker evidence for green and purple sulphur bacteria in a stratified Paleoproterozoic sea Distinctive hydrocarbon biomarkers from fossiliferous sediments of the Late Proterozoic Walcott Member Geological alteration of Precambrian steroids mimics early animal signatures Evolution of bacterial steroid biosynthesis and its impact on eukaryogenesis Paleoproterozoic sterol biosynthesis and the rise of oxygen Zhang, X., Paoletti, M., Izon, G., Fournier, G. & Summons, R. 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isotopic signatures Testing biomarker syngeneity of evaporites from Neoproterozoic and Cambrian strata Assessing biomarker syngeneity using branched alkanes with quaternary carbon (BAQCs) and other plastic contaminants Tailing of chromatographic peaks in GC–MS caused by interaction of halogenated solvents with the ion source Application of tetracyclic polyprenoids as indicators of input from fresh-brackish water environments climate and the chemical evolution of a 1400 million year old tropical marine setting Sufficient oxygen for animal respiration 1,400 million years ago Download references acknowledges funding support from Australian Research Council grants DP160100607 acknowledge funding support from the Centre National de la Recherche Scientifique and the Université de Strasbourg acknowledges doctoral and postdoctoral fellowships by the Australian National University and the Central Research and Development Fund of the University of Bremen publishes with the permission of the Executive Director Edwards and the organic geochemistry team at Geoscience Australia (GA) for oil samples from the National Collection; and the Geological Survey of Western Australia (GSWA) the Northern Territory Geological Survey (NTGS) These authors contributed equally: Jochen J MARUM–Center for Marine Environmental Sciences and Faculty of Geosciences GFZ German Research Center for Geosciences interpreted the data and wrote the paper with contributions from C.H conducted pyrolysis and ring-opening experiments conducted RuO4 oxidation experiments and assisted with compound identification conceived the project and compiled data and figures reviewer(s) for their contribution to the peer review of this work Chemical structures in purple and cyan are biogenic precursors Structures in black are fossil lipids detected in mid-Proterozoic sedimentary rocks and generated in pyrolysis experiments of the respective biolipids Green arrows signify biosynthetic reactions black dashed arrows point to products of diagenesis (and laboratory pyrolysis) Note that the dashed arrows do not imply direct product-precursor relationships as diagenetic reactions commonly involve numerous intermediates and complex reaction networks ‘x,4,24-Me3TAS’ signifies a TAS methylated at C-4 M/z 412 to 300 partial ion chromatograms of cyclosterane and successive side-chain cleavage products ‘x’ indicate absence or low concentration of pseudohomologs indicative of side-chain branching positions Total ion current (TIC) of the saturated hydrocarbon fraction of the biodegraded oil highlighting the biodegradation resistance of the two cyclosterane isomers k1 and k2 ‘~’ marks truncated signal of internal standard Mass spectra of the cyclosterane side-chain cleavage products See text for explanation of red and blue dashed lines Juxtaposition of the mass spectra of cyclosterane isomer k2 (upper panel) and cycloartane from the NIST 95 library (lower panel) (the mass spectrum of k1 is not shown as it is nearly identical to k2) Suggested major MS fragmentation of hypothetical cyclosterane structure I and cycloartane Note that 8β(H),9α(H)-lanostane l4 co-elutes with TTP2 but that its presence can be recognized by an elevated TTP2 peak or a shoulder trailing the peak The chromatograms are identified by MRM precursor → product transitions and relative signal heights in % relative to the highest signal Mass spectra of signals labelled in (a) to (e) a1 to a4 are chromatographic signal identifiers for geological bitumens and A1 to A4 identifiers for corresponding authentic standards and pyrolysis products Ancient bitumen chromatograms are in black 375 and 361 mass chromatograms identifying isomers of C28 C29 and C30 DAL generated through pyrolysis of cycloartenol C29 and C30 DAL of sample 14B211 from the 725 Ma Kanpa Fm showing an immature isomer distribution (20S << 20R) C29 and C30 DAL of sample B03162c from the 1,640 Ma Barney Creek Fm with a mature isomer distribution (20S ≈ 20R) b1 to b10 are chromatographic signal identifiers for geological bitumens and B1 to B10 identifiers for pyrolysis products of authentic standards in blue and B1 to B10 identifiers for pyrolysis products of cycloartenol Vertical labels ‘13 Aug 18 35’ are unique identifiers for individual GC-MS experiments Signals marked ‘x’ are from coeluting compounds Relative abundance data of all aromatic steroids protosteroids and hopanoids used to assemble Figs including a key to the colours and reference to individual compounds identified in Extended Data Figs Also included is methylphenanthrene-based thermal maturity data Relative abundance data of all saturated steranes protosteranes and hopanes used to assemble Fig and references to data taken from the literature Characterization of all samples analysed in this study from the Palaeoproterozoic to the Cenozoic sample depths and a brief description of lithology Download citation DOI: https://doi.org/10.1038/s41586-023-06170-w a shareable link is not currently available for this article European Journal for Philosophy of Science (2025) Sign up for the Nature Briefing newsletter — what matters in science Metrics details Single-cell RNA-sequencing (scRNA-Seq) is widely used to characterize immune cell populations mRNA levels correlate poorly with expression of surface proteins which are well established to define immune cell types CITE-Seq (cellular indexing of transcriptomes and epitopes by sequencing) utilizes oligonucleotide-tagged antibodies to simultaneously analyze surface phenotypes and transcriptomes Considering the high costs of adding surface phenotyping to scRNA-Seq we aimed to determine which of 188 tested CITE-Seq antibodies can detect their antigens on human peripheral blood mononuclear cells (PBMCs) a commonly interrogated cell population in immunology and find the optimal concentration for staining The recommended concentration was optimal for 76 antibodies whereas staining quality of 7 antibodies improved when the concentration was doubled 33 and 8 antibodies still worked well when the concentration was reduced to 1/5 or 1/25 64 antigens were not detected at any antibody concentration Optimizing the antibody panel by removing antibodies not able to detect their target antigens and adjusting concentrations of the remaining antibodies will improve the analysis and may reduce costs our data are a resource for building an informative and cost-effective panel of CITE-Seq antibodies and use them at their optimal concentrations in future CITE-seq experiments on human PBMCs it is beneficial to analyze cell surface phenotype along with transcriptomes which were developed by Stoeckius and colleagues at the New York Genome Center and Peterson et al at the Merck Department for Translational Medicine Both methods detect surface proteins through utilization of oligonucleotide-tagged antibodies Such antibodies have become commercially available for the 10 × Genomics Chromium™ (BioLegend® TotalSeq™) and BD® Rhapsody™ scRNA-Seq systems (BD® AbSeq) Adding cell surface phenotype assessment to scRNA-Seq is informative The main cost drivers are the antibody pools the extra PCR steps required for library preparation and the labor cost for cell washing and counting a CITE-Seq experiment using the 10 × Genomics system and their 137plex TotalSeq™ human universal antibody cocktail costs around $3000 per sample This amount does not include labor costs and consists of around $1000 each for reagents Addition of more antibodies increases the costs even further Although antibodies are titrated by the manufacturer using flow cytometry almost no data are available on titration using actual oligonucleotide-tagged antibodies There should be a relationship between the antibody signal detected by flow cytometry and by sequencing but this relationship is not necessarily one of identity To maximally benefit from surface phenotype assessment it is necessary to optimize the antibody panels for the intended purpose to include only target antigens expressed on the interrogated cells to ensure that the antibodies used actually work and to find their optimal concentration in actual CITE-Seq experiments We clustered the five major cell types in PBMCs [CD4 T cells which are independent of antibody concentration to map all cells at all concentrations in the same UMAP we interrogated and analyzed the signal and background for each antibody at each concentration We demonstrate which (of the 188 tested) TotalSeq™ antibodies are capable of staining human PBMCs and which concentrations enable sufficient staining quality these data can be a valuable resource for designing future CITE-Seq experiments on human PBMCs We first called the five major cell types using the following gating scheme (Fig. S1): Classical monocytes (CM): CD3−CD19−CD14+CD16− Natural killer (NK) cells: CD3−CD19−CD14−CD56+ suggesting that these concentrations were insufficient to saturate many antibodies Major cell type identification at different antibody concentrations (A–D) Major cell types detected by antibodies at the indicated concentrations were projected on a unified UMAP in which all cells are clustered by transcriptomes Major cell type clusters were clearly separated at all concentrations although antibody dilution reduced the number of identified cells (E) Percentage of correctly identified major cells at different antibody concentrations in relation to 1 × Proportions of all major cell types in relation to the total number of cells detected were calculated for each concentration and normalized to the proportions of detected cells at the recommended concentration (1 ×) Target antigen expression in major cell types (A) Total number of detectable target antigens at different antibody concentrations (B) Average number of antigens detected at different concentrations in each cell type Statistical significance was determined by one-way ANOVA with Tukey’s multiple comparisons test Exemplary feature plots. Expression of exemplary surface antigens (CD19, CD4, CD8, CD14, and CD56) at each of the four concentrations plotted on a unified UMAP, in which all cells, stained with any of the four antibody concentrations, are clustered by transcriptomes. Centered log-ratio (CLR) normalized expression levels in a low dimensional space are indicated by color (scaled between 1 and 3 as indicated by the scale bar; yellow = low to red = high expression). Dose-responses of all thresholded antibodies Centered log-ratio (CLR) normalized expression levels in all cell types and at all antibody concentrations are displayed as a colored heatmap Antibodies are clustered depending on the cell type in which the expression was highest (from top to bottom: B cells Average expression values of the 10 most abundant differentially expressed genes (one versus all other comparison) in each of the major cell types at all antibody concentrations are displayed as dot plots The centered log-ratio (CLR) normalized average gene expression is indicated by color intensity and the fraction of cells expressing an antigen is indicated by the size of the dots The top 10 B cell antigens are shown on the left and natural killer (NK) cell antigens (left to right) Potential benefits from antibody panel optimization (A) Distribution of optimal antibody concentrations The lowest concentration enabling good staining quality was regarded optimal (B) Calculation of the total antibody amount utilized in the optimized 128plex panel (middle) and the commercially available 137plex TotalSeq™ C human universal cocktail (right) in relation to the tested 192plex panel (left) there is sparse data on titration of CITE-Seq antibodies CITE-Seq facilitates the use of large antibody panels and antibody staining intensity strongly influences sequencing costs From an economic perspective it is thus highly relevant to determine optimal dilutions which can be defined as the lowest concentrations enabling sufficient staining quality Such favorable characteristics include (1) easy accessibility without any need for surgical interventions (2) no need for enzymatic digestion or mechanical separation (3) availability from patients in many large cohort studies (4) ready availability from healthy individuals that can be used as controls (5) long-term stability on liquid nitrogen and (6) a high potential to be used as biomarkers in clinical practice PBMCs collected in clinical trials allow correlating experimental findings with clinical outcome data and to thus achieve high translational potential Considering that CITE-Seq of human PBMCs represents a powerful technology to study immune responses in health and disease an antibody panel that enables optimal staining quality at the lowest possible cost can be an important resource for future research we reveal that about one third of 188 tested CITE-Seq antibodies were not able to detect their target antigens it remains unknown whether the target antigens were not expressed in any PBMCs or whether some of these antibodies were technical failures (antibody not working) About one third of the remaining antibodies could be used at lower than recommended concentrations without loss of staining quality Performance of only a few antibodies improved after doubling the concentration Utilization of an optimized antibody panel only including the 124 working antibodies at optimal concentrations and isotype controls would reduce the total antibody amount needed by almost 50% this reduction comes without compromising staining quality; our proposed strategy actually improves the performance of the panel The manufacturer could use this data to optimize their universal antibody cocktail for human PBMCs our findings can help to optimize custom panels designed by customers although the actual cost savings would depend on the individual composition of the panel they revealed that dilution of many antibodies did not impair their performance Reducing staining volume only affected antibodies used at low concentrations and targeting highly expressed antigens since the number of antigens present in the sample might then exceed the total number of antibody molecules (loss of saturation) this effect was counteracted by reducing the cell count they did not use a lyophilized antibody cocktail but titrated each antibody individually using starting concentrations (1 ×) which were based on previous experience epitope abundance or vendor recommendation and a fourfold dilution (0.25 ×) of these concentrations They also established and validated an adjusted antibody panel which yielded higher signal-to-noise ratio and was substantially cheaper compared to the 1 × concentration Titrating antibodies individually based on a-priori information facilitates a more targeted determination of optimal dilutions and offers the opportunity to directly validate the adjusted panel (as was done by Buus and colleagues) For practical reasons of relevance to daily lab operation we titrated a lyophilized TotalSeq™ C antibody cocktail rather than individual antibodies (1) Individual titrations of large antibody panels by future customers are infeasible due to high experimental and labor costs (2) We assumed that titrating the whole panel based on the recommended concentrations would be most useful for enabling adjustments of concentrations We acknowledge several limitations of our study: (1) Our findings only apply to human PBMCs and (2) our data does not allow to differentiate whether an antibody was not working as intended or whether its target antigen was just not expressed in the major cell types present in PBMCs (NK cells antibodies not able to detect their antigens in our study can be discarded from a panel specifically designed for application in PBMCs unless analysis of very rare cell populations after enrichment by sorting is intended Utilization of CITE-Seq antibodies in other tissues or such rare cell types would require validation and titration in these particular cell populations This is common practice in titration studies because multiple samples are associated with higher experimental costs (4) some antigens that were not detectable in our sample could potentially be expressed by PBMCs in the setting of diseases or after stimulation (e.g with endotoxins or superantigens such as LPS or SEB) this resource for building an informative and cost-effective panel of TotalSeq™ C antibodies and use them at their optimal concentrations improves future CITE-seq experiments on human PBMCs This panel includes 4 isotype controls and 124 of 188 tested antibodies of which 76 are used at the recommended concentration and 7 are used at the double concentration This optimized panel utilizes a substantially lower amount of antibodies while increasing overall staining quality compared to currently available antibody panels This study was approved by the Institutional Review Board at the La Jolla Institute for Immunology (LJI) and all experiments were performed in accordance with the guidelines of this committee and the Declaration of Helsinki Written informed consent was obtained from all participants A blood sample from one healthy adult donor was collected through the La Jolla Institute for Immunology’s in-house Normal Blood Donor Program (NBDP) All participants of the NBDP must not have a history of any chronic infectious disease recent surgery or organ/tissue transplantation must not be pregnant/breast-feeding or weigh below 50 kg and must not take any cardiac or anticoagulant/antiplatelet drugs and Hepatitis C was confirmed by diagnostic blood tests Venous blood samples were collected into heparin-coated tubes and centrifuged at 400×g for 10 min at RT to remove platelet rich plasma PBMCs were isolated by Ficoll Paque (Sigma Aldrich) density-gradient centrifugation and resuspended in CryoStor® CS10 (Stemcell) a serum-free and animal component-free cryopreservation medium containing 10% DMSO PBMC-containing vials were cooled down in Mr Frosty™ Freezing Containers (ThermoFisher Sientific™) and subsequently cryopreserved on liquid nitrogen until used PBMC-containing tubes were filled with RPMI-1640 solution supplemented with 10% fetal bovine serum (FBS) and thawed in a 37 °C water bath Cells were counted and centrifuged at 400 rcf for 5 min at room temperature (RT) the pellets were resuspended in 1 ml phosphate-buffered saline (PBS) with 0.04% w/v bovine serum albumin (BSA) and centrifuged at 400 rcf for 5 min Pellets were again resuspended in 1 × PBS with 0.04% w/v BSA to achieve a target concentration of 1000 cells/µl Cells were counted again and volume was adjusted to obtain the target cell concentration 106 cells (1 ml) each were transferred to four different microcentrifuge tubes resuspended with 50 µl chilled PBS + 1% w/v BSA and then incubated with 5 µl Fc receptor blocking solution (BioLegend® Human TruStain FcX™) at 4 °C for 10 min The 192plex antibody mix (including 188 antibodies and 4 isotype controls) was prepared to achieve the concentration recommended by the manufacturer (1 ×) two times the recommended concentration (2 ×) and one fifth (0.2 ×) as well as one twenty-fifth (0.04x) of the recommended concentration in the same total staining volume (10 µl) and 0.04 ×) was added to one of the four tubes which were filled up with PBS + 1% w/v BSA to a total volume of 100 µl incubated for 30 min at 4 °C and washed in PBS + 0.04% w/v BSA Cells stained with any of the four antibody concentrations (one million cells each) were then hashtagged by incubation in 100 µl Cell Multiplexing Oligo (10 × Genomics) for 5 min at RT and washed three times with PBS + 1% BSA at 4 °C (total volume 2 ml) volume adjusted to obtain the target cell concentration (1000 cells/µl) and pooled in one tube 16.5 µl of the cell suspension were incubated with the 10 × Genomics Master Mix for a targeted cell recovery of 10,000 cells loaded onto a Chromium Next GEM Chip (10 × Genomics) and further steps of library preparation were performed according to the Chromium Next GEM Single Cell 5’ Protocol A median of 1670 genes were detected per cell based on UMI (unique molecular identifier) counts The transcriptome data was log normalized and the antibody data was CLR (centered log-ratio) normalized The margin was set to 2 (column-wise) to normalize for differences in ADT depth across cells Prior to calling thresholds for each antibody biaxial plots were used to gate the major cell populations: B cells Figure S4 summarizes the removal of cells during quality control and cell type calling ridge plots were used to set the thresholds for each of the other antibodies at each concentration (2 × We used the UMAP (Uniform Manifold Approximation and Projection) dimensionality reduction algorithm to project the identified cell populations for the samples in a 2D space The first 25 principal components from PCA (principal component analysis) were used to run the UMAP algorithm we used Seurat’s default Louvain clustering algorithm with the default resolution parameter and random seed set to 42 to ensure reproducibility Cells were clustered by the log normalized transcriptome data PBMCs were thawed in a 37 °C water bath and washed with cold FACS buffer (PBS w/o Ca/Mg Viability and cell concentration were determined by trypan blue dye exclusion using a hemocytometer About 1.5 million cells were resuspended in a staining master mix containing anti-human Fc-Block (Biolegend™ USA) and fluorochrome-coupled antibodies (Biolegend™ Fc-block at 1:75 and antibodies were used at a final dilution of 1:100 Stained cells were washed with cold FACS buffer and fixed in 100 µl eBioscience™ IC Fixation Buffer (Invitrogen™ Single color-stained beads (UltraComp eBeads™ Invitrogen) were used for compensation control Data was acquired on a BD LSR II flow cytometer (BD® Biosciences USA) and analyzed with FlowJo software (FlowJo LLC The datasets generated and analyzed during the current study are available in the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) repository Single-cell RNA sequencing to explore immune cell heterogeneity Revolutionizing immunology with single-cell RNA sequencing Single-cell RNA sequencing in cancer: Applications Meta-analysis of leukocyte diversity in atherosclerotic mouse aortas Heterogeneity of immune cells in human atherosclerosis revealed by scRNA-Seq Guidelines for the use of flow cytometry and cell sorting in immunological studies (second edition) Systems-level immunomonitoring from acute to recovery phase of severe COVID-19 Williams, J. W. et al. Single Cell RNA sequencing in atherosclerosis research. Circ. Res. 1, 1112–1126. https://doi.org/10.1161/CIRCRESAHA.119.315940 (2020) Single-cell immune landscape of human atherosclerotic plaques Atlas of the immune cell repertoire in mouse atherosclerosis defined by single-cell RNA-sequencing and mass cytometry Single-cell RNA-seq reveals the transcriptional landscape and heterogeneity of aortic macrophages in murine atherosclerosis Microanatomy of the human atherosclerotic plaque by single-cell transcriptomics Adventitial cell atlas of wt (wild type) and ApoE (apolipoprotein E)-deficient mice defined by single-cell RNA sequencing Transcriptome analysis reveals nonfoamy rather than foamy plaque macrophages are proinflammatory in atherosclerotic murine models Single-cell analysis of fate-mapped macrophages reveals heterogeneity during atherosclerosis progression and regression Vallejo, J. et al. Combined protein and transcript single cell RNA sequencing in human peripheral blood mononuclear cells. BioRxiv https://doi.org/10.1101/2020.09.10.292086 (2021) Global quantification of mammalian gene expression control On the dependency of cellular protein levels on mRNA abundance Simultaneous epitope and transcriptome measurement in single cells Multiplexed quantification of proteins and transcripts in single cells Temporally integrated single cell RNA sequencing analysis of PBMC from experimental and natural primary human DENV-1 infections Multiplexed enrichment and genomic profiling of peripheral blood cells reveal subset-specific immune signatures Single-cell analysis of Crohn’s disease lesions identifies a pathogenic cellular module associated with resistance to anti-TNF therapy Integrated single-cell analysis of multicellular immune dynamics during hyperacute HIV-1 infection Broad immune activation underlies shared set point signatures for vaccine responsiveness in healthy individuals and disease activity in patients with lupus Deep single-cell RNA sequencing data of individual T cells from treatment-naïve colorectal cancer patients Single-cell sequencing of peripheral mononuclear cells reveals distinct immune response landscapes of COVID-19 and influenza patients Relevance of antibody validation for flow cytometry Titration of fluorochrome-conjugated antibodies for labeling cell surface markers on live cells Mosallaei, M. et al. PBMCs: A new source of diagnostic and prognostic biomarkers. Arch. Physiol. Biochem. https://doi.org/10.1080/13813455.2020.1752257 (2020) Improving oligo-conjugated antibody signal in multimodal single-cell analysis DoubletFinder: Doublet detection in single-cell RNA sequencing data using artificial nearest neighbors Normalizing and denoising protein expression data from droplet-based single cell profiling dittoSeq: Universal user-friendly single-cell and bulk RNA sequencing visualization toolkit Download references This study was supported by the Deutsche Forschungsgemeinschaft (NE 2574/1-1 to FSN) and the National Institutes of Health (R01 HL115232 to KL) Faculty of Medicine and University Hospital Cologne Centro Nacional de Investigaciones Cardiovasculares designed and supervised the study and provided funding Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations Download citation DOI: https://doi.org/10.1038/s41598-022-24371-7 Metrics details Fossilized lipids offer a rare glimpse into ancient ecosystems 2-Methylhopanes in sedimentary rocks were once used to infer the importance of cyanobacteria as primary producers throughout geological history the discovery of hopanoid C-2 methyltransferase (HpnP) in Alphaproteobacteria led to the downfall of this molecular proxy we re-examined the distribution of HpnP in a new phylogenetic framework including recently proposed candidate phyla and re-interpreted a revised geological record of 2-methylhopanes based on contamination-free samples We show that HpnP was probably present in the last common ancestor of cyanobacteria while the gene appeared in Alphaproteobacteria only around 750 million years ago (Ma) A subsequent rise of sedimentary 2-methylhopanes around 600 Ma probably reflects the expansion of Alphaproteobacteria that coincided with the rise of eukaryotic algae—possibly connected by algal dependency on microbially produced vitamin B12 Our findings re-establish 2-methylhopanes as cyanobacterial biomarkers before 750 Ma and thus as a potential tool to measure the importance of oxygenic cyanobacteria as primary producers on early Earth Our study illustrates how genetics can improve the diagnostic value of biomarkers and refine the reconstruction of early ecosystems thereby framing the environmental context that is crucially needed for better understanding the evolution of increasingly complex life These inferences ultimately led to much uncertainty debate and a questionable utility of ecological proxies involving 2-methylhopanoids our molecular data were combined with new analyses of sedimentary 2-methylhopanes to provide an integrated account of 2-methylhopane production through Earth history characterization of early-diverging HpnP homologues from other bacterial phyla may provide important information about the functional evolution of radical SAM methyltransferases towards HpnP This suggests that the HGT events at the root of those sub-clades are ancient and the bacterial lineages that mediated those transfers (but were not necessarily producing 2-methylhopaonids themselves) are long extinct Whereas HpnP sequences from Alphaproteobacteria and Cyanobacteria dominate our dataset the evolutionary pattern seen in the two clades is distinct Alphaproteobacterial sequences come from a sporadic number of sub-clades while cyanobacterial sequences largely mirror the species tree suggesting HpnP was inherited vertically in crown-group cyanobacteria These observed patterns are described in more detail below we infer that HpnP was horizontally transferred to Alphaproteobacteria only after the divergence of Hyphomicrobiales Solid lines in the HpnP tree indicate that they are consistent with the species tree Dashed lines indicate that they are not consistent with the species tree and thus the presence of HGT is inferred by Notung Filled black circles indicate that the node support is >85% for both maximum likelihood inference and Bayesian inference (node support is shown only for major clades) Filled grey circles indicate that the node support is above the same threshold for one of the two inferences The scale bar represents 0.1 amino acid replacements per site per unit evolutionary time Understanding the evolutionary timeline of HpnP in individual phyla allows constraining the source of 2-methylhopanoids at different geological times HpnP in additional bacteria suggests that Cyanobacteria was not the only lineage capable of producing 2-methylhopanoids HpnP appears only sporadically in those additional lineages possibly reflecting relatively recent HGT events or limited microbial sampling the presence of these proteins at the base of the HpnP tree could represent long branch attraction of proteins that are dissimilar from the better sampled clades (Cyanobacteria and Alphaproteobacteria)—perhaps representing a divergent function—or they could represent ancestry from an extinct lineage with an ancestral form of HpnP that was not necessarily involved in 2-methylhopanoid production as implied for deltaproteobacterial HpnP homologues We currently do not have enough data to adjudicate between these competing interpretations cyanobacteria are the most likely source of fossilized 2-methylhopanoids before the evolution of HpnP-containing Alphaproteobacteria (Hyphomicrobiales) In contrast to previous findings, the revised 2-MHI record exhibits consistently low relative 2-methylhopane abundances until the end of the Snowball Earth glaciations around 635 Ma (2-MHI < 2.4%; n = 93; average = 0.96%) (Fig. 4b) An initial increase to 5.4% is observed in the early Ediacaran ( ~ 620 Ma) and followed by multiple episodes of large fluctuations While the 2-MHI in the Ediacaran and Phanerozoic can be extremely high for individual formations (up to 24%) the averaged values over geological time units remain moderate at ~5% it is likely that the Ediacaran increase of the 2-MHI reflects the expansion of HpnP-containing Alphaproteobacteria In view of enhanced alphaproteobacterial 2-methylhopanoid production going back to the Ediacaran it is likely that HpnP-containing Alphaproteobacteria were responsible for modulating the 2-MHI throughout the Phanerozoic The once suggested association of 2-methylhopanoids with cyanobacteria—a highly important proxy tool for our understanding of Earth system evolution and oxygen dynamics in the geological past—has been constantly debated Both Cyanobacteria and Alphaproteobacteria can biosynthesize 2-methylhopanoids and thus sedimentary 2-methylhopanes are not a diagnostic biomarker for a single taxonomic group We show that such ambiguities can be refined by adding a genetic perspective The phylogenetic tree topology of HpnP in Cyanobacteria suggests that HpnP was probably present in the common ancestor of crown-group cyanobacteria whereas according to molecular clock analyses alphaproteobacterial lineages acquired HpnP after 750 Ma This finding re-establishes the utility of 2-methylhopanes as a biomarker for cyanobacteria in pre-Ediacaran rocks enabling us to measure the importance of HpnP-containing oxygenic cyanobacteria in the geological past 2-methylhopanes in post-Cryogenian oceans reflect additional signals from heterotrophic 2-methylhopanoid producers—Alphaproteobacteria The synchronization between the 2-MHI increase during the Ediacaran and the ecological expansion of HpnP-containing Alphaproteobacteria and eukaryotic algae may not be coincidental involving a vitamin B12-based mutualistic relationship between Alphaproteobacteria and algae and enhanced reworking of algal biomass by Alphaproteobacteria in increasingly oxygenated marine environments Our study demonstrates the strength of combining the geological record of fossil hydrocarbon biomarkers with genetic analyses to gain insights into ancient ecosystems and provides an important precedent for refining our understanding of biomarker utility throughout Earth’s history These sequences were excluded from the subsequent analyses The phylum currently contains only metagenomic samples, and thus the same species tree construction as performed for cyanobacteria was not possible. Instead, a species tree was constructed by concatenating three ribosomal proteins L2, L3 and L4 (Supplementary Table 1) The best substitution model was also determined by IQ-TREE The topology of the rokubacterial HpnP tree was compared with the generated species tree using NOTUNG v2.9 (DTL model) To minimize uncertainty due to contamination Precambrian samples in our dataset consist mostly of our newly analysed samples except for Ediacaran oil samples that are highly organic rich and difficult to substantially adulterate through contamination overprint Saturated fractions were eluted with 1.5 dead volumes n-hexane on a microcolumn of annealed (300 °C D4-C29 αααR-ethylcholestane (D4; Chiron Laboratories AS) was added to the saturate fraction before gas chromatography-mass spectroscopy (GC–MS) analyses with an Agilent 6890 gas chromatograph equipped with a 60 m DB-5 MS capillary column (0.25 mm i.d. 0.25 µm film thickness; Agilent Technologies) coupled to a Micromass Autospec Premier double sector mass spectrometer (Waters Corporation) Hopanes were analysed with M+ (412 for C30 hopanes)→ m/z 191 and methylhopanes with M+→ m/z 205 multiple reaction monitoring transitions 2-Methylhopane peak assignment was based on the retention time and the comparison with the Australian Geological Survey Organisation standard C31 2-methylhopane elutes just before C30 αβ hopane on the chromatogram Aliquots (1 mg) of diplopterol (courtesy of P Sigma-Aldrich) were transferred to glass tubes flame sealed at one end (Duran tubes were evacuated to ≤300 mTorr and flame sealed with a gas torch After pyrolysis in an oven at 300 °C for 24 h cracked open and the active carbon was transferred with sequential solvent rinses of n-hexane DCM and methanol onto a small silica plug in a 4 ml solid phase extraction glass tube and subsequently extracted with about 10 ml n-hexane Once solvents were evaporated under a stream of N2 the pyrolysate was applied onto a silica gel microcolumn (about 500 mg in a glasswool-plugged Pasteur pipette) and the saturated hydrocarbon fraction was eluted with 1.5 dead volumes n-hexane followed by GC–MS analysis Pyrolysates were analysed on a Thermo Quantum XLS Ultra triple-quadrupole MS coupled to a Thermo Trace GC Ultra fitted with a VF-1 MS column (40 m Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article All data needed to evaluate the conclusions in the paper are present in the paper and/or Supplementary Information Additional and raw data and used sample material related to this paper may be requested from the authors The data and code used to execute cyanobacterial species tree constructions are available at https://github.com/David-Gold/2022_HpnP Devonian rise in atmospheric oxygen correlated to the radiations of terrestrial plants and large predatory fish Late-Neoproterozoic deep-ocean oxygenation and the rise of animal life in Treatise on Geochemistry 2nd edn (eds Holland Lipid biomarkers for the reconstruction of deep-time environmental conditions Hopanoids as functional analogues of cholesterol in bacterial membranes Hopanoid lipids: from membranes to plant–bacteria interactions 2-Methylhopanoids as biomarkers for cyanobacterial oxygenic photosynthesis N2-fixing cyanobacteria supplied nutrient N for Cretaceous oceanic anoxic events Microbial response to limited nutrients in shallow water immediately after the end-Permian mass extinction Changing perspectives in marine nitrogen fixation Bacteriohopanepolyols across environmental gradients in Lake Vanda 2-Methylhopanoids are maximally produced in akinetes of Nostoc punctiforme: geobiological implications in Evolution of Primary Producers in the Sea (eds Falkowski Two episodes of microbial change coupled with Permo/Triassic faunal mass extinction Identification of a methylase required for 2-methylhopanoid production and implications for the interpretation of sedimentary hopanes Diverse capacity for 2-methylhopanoid production correlates with a specific ecological niche Phylogenetic analysis of HpnP reveals the origin of 2-methylhopanoid production in Alphaproteobacteria Origin and evolution of polycyclic triterpene synthesis The planetary biology of cytochrome P450 aromatases The occurrence of 2-methylhopanoids in modern bacteria and the geological record Vitamin B12-dependent biosynthesis ties amplified 2-methylhopanoid production during oceanic anoxic events to nitrification Rokubacteria: genomic giants among the uncultured bacterial phyla Hopanoid lipids may facilitate aerobic nitrogen fixation in the ocean Biosynthesis of 2-methylbacteriohopanepolyols by an anoxygenic phototroph Pheno- and genotyping of hopanoid production in Acidobacteria Biosynthesis of hopanoids by sulfate-reducing bacteria (genus Desulfovibrio) Anaerobic ammonium-oxidizing bacteria: unique microorganisms with exceptional properties 1.1-billion-year-old porphyrins establish a marine ecosystem dominated by bacterial primary producers Evolutionary timeline and genomic plasticity underlying the lifestyle diversity in rhizobiales Biomarker evidence for green and purple sulphur bacteria in a stratified Palaeoproterozoic sea Lipid biomarkers in Hamelin pool microbial mats and stromatolites Diversity of cyanobacterial biomarker genes from the stromatolites of Shark Bay Microbial mats in terminal Proterozoic siliciclastics; Ediacaran death masks Role of microorganisms in the evolution of animals and plants: the hologenome theory of evolution How mutualisms arise in phytoplankton communities: building eco-evolutionary principles for aquatic microbes Algae acquire vitamin B12 through a symbiotic relationship with bacteria Uneven distribution of cobamide biosynthesis and dependence in bacteria predicted by comparative genomics Two distinct pools of B12 analogs reveal community interdependencies in the ocean Gapped BLAST and PSI-BLAST: a new generation of protein database search programs MUSCLE: multiple sequence alignment with high accuracy and high throughput IQ-TREE 2: new models and efficient methods for phylogenetic inference in the genomic era MRBAYES: Bayesian inference of phylogenetic trees Entrez programming utilities help. National Center for Biotechnology Information https://www.ncbi.nlm.nih.gov/books/NBK25501/ (2010) OrthoFinder: phylogenetic orthology inference for comparative genomics FASconCAT-G: extensive functions for multiple sequence alignment preparations concerning phylogenetic studies A hybrid micro–macroevolutionary approach to gene tree reconstruction Diverse chromatic acclimation processes regulating phycoerythrocyanin and rod-shaped phycobilisome in cyanobacteria The Archean origin of oxygenic photosynthesis and extant cyanobacterial lineages Download references Edwards and the organic geochemistry team at Geoscience Australia for oil samples from the National Collection and the Geological Survey of Western Australia Schaeffer (University of Strasbourg) for providing the diplopterol educt employed in the pyrolysis experiments and R Tarozo (Max Planck Institute for Biogeochemistry) and J Hope (The Australian National University) for assistance with GC–MS This work was supported by DFG Priority programme 2237 and the Helmholtz Society to C.H.; Agouron geobiology postdoctoral fellowship to Y.H.; postdoctoral fellowship provided by the Central Research and Development Fund of the University of Bremen to B.J.N.; National Science Foundation grant 2044871 to D.A.G.; Australian Research Council grants DP160100607 DP170100556 and DP200100004 to J.J.B.; and National Institutes of Health grant R01AR069137 Human Frontier Science Program grant RGP0041 National Science Foundation grant 2032315 and Department of Defense grant MURI W911NF-16-1-0372 to E.A.G Open access funding provided by Helmholtz-Zentrum Potsdam Deutsches GeoForschungsZentrum - GFZ GFZ German Research Centre for Geosciences MARUM Center for Marine Environmental Sciences and Department of Geosciences Department of Earth and Planetary Sciences performed genetic data collection and analyses performed biomarker data collection and analyses All authors participated in data interpretation edited the draft and agreed to the published version of the paper Nature Ecology & Evolution thanks the anonymous reviewers for their contribution to the peer review of this work. Peer reviewer reports are available Dashed lines indicate that they are not consistent with the species tree and thus the presence of HGT is inferred by Notung Filled black circles indicate that the node support is >85% (node support is shown only for major clades) 2-MHI values were calculated for the Paleoproterozoic LV09001 drill core from the McArthur Basin in Northern Australia ( ~ 1.64 Ga) (see also Supplementary Note 6) Representative chromatograms for non-methylated hopanes (C30 diahopanes C30 & C31 hopanes) and methylhopanes (2α and 3β) are shown (478.2 m depth) C31 2-methylhopane elutes just prior to C30 αβ-hopane on a DB-5 MS capillary column Chromatograms are annotated by Metastable Reaction Monitoring (MRM) precursor → products pairs Percentages provide relative heights of the largest peaks in the chromatograms References (Supplementary Table 7 references included) and captions for Tables 1–7 Maximum likelihood HpnP tree data for Supplementary Fig Bayesian HpnP tree data for Supplementary Fig Maximum likelihood HpnP-like protein tree data for Supplementary Fig Multiple sequence alignment data for Supplementary Fig Download citation DOI: https://doi.org/10.1038/s41559-023-02223-5 International Journal of Earth Sciences (2025) Sign up for the Nature Briefing: Microbiology newsletter — what matters in microbiology research Metrics details Matters Arising to this article was published on 25 November 2019 The dawn of animals remains one of the most mysterious milestones in the evolution of life The fossil lipids 24-isopropylcholestane and 26-methylstigmastane are considered diagnostic for demosponges—arguably the oldest group of living animals The widespread occurrence and high relative abundance of these biomarkers in Ediacaran sediments from 635–541 million years (Myr) ago have been viewed as evidence for the rise of animals to ecological importance approximately 100 Myr before their rapid Cambrian radiation Here we show that the biosynthesis of 24-isopropylcholestane and 26-methylstigmastane precursors is common among early-branching unicellular Rhizaria—heterotrophic protists that play an important role in trophic cycling and carbon export in the modern ocean Negating these hydrocarbons as sponge biomarkers our study places the oldest evidence for animals closer to the Cambrian Explosion Cambrian silica hexactine spicules that are approximately 535 Myr old now represent the oldest diagnostic sponge remains whereas approximately 558-Myr-old Dickinsonia and Kimberella (Ediacara biota) provide the most reliable evidence for the emergence of animals The proliferation of predatory protists may have been responsible for much of the ecological changes during the late Neoproterozoic the establishment of complex trophic relationships and the oxygenation of shallow-water habitats required for the subsequent ascent of macroscopic animals The data required to assess the interpretations made in this paper are included in the Supplementary Information Additional (raw) data are available from the corresponding authors upon reasonable request Co-evolution of eukaryotes and ocean oxygenation in the Neoproterozoic era Giving the early fossil record of sponges a squeeze Early sponge evolution: a review and phylogenetic framework The Cambrian conundrum: early divergence and later ecological success in the early history of animals Estimating metazoan divergence times with a molecular clock Uncertainty in the timing of origin of animals and the limits of precision in molecular timescales A molecular timescale of eukaryote evolution and the rise of complex multicellular life Fossil steroids record the appearance of Demospongiae during the Cryogenian period Demosponge steroid biomarker 26-methylstigmastane provides evidence for Neoproterozoic animals Origin of petroleum in the Neoproterozoic–Cambrian South Oman salt basin Sterol and genomic analyses validate the sponge biomarker hypothesis Identification of 24-n-propylidenecholesterol in a member of the Foraminifera Deep relationships of Rhizaria revealed by phylogenomics: a farewell to Haeckel’s Radiolaria Plankton networks driving carbon export in the oligotrophic ocean Possible early foraminiferans in post-Sturtian (716−635 Ma) cap carbonates Bayesian relaxed clock estimation of divergence times in foraminifera Radiolaria: major exporters of organic carbon to the deep ocean Ancient steroids establish the Ediacaran fossil Dickinsonia as one of the earliest animals and microRNAs suggest a 200‐Myr missing Precambrian fossil record of siliceous sponge spicules Prospects for sterane preservation in sponge fossils from museum collections and the utility of sponge biomarkers for molecular clocks in Evolution of Primary Producers in the Sea 405–430 (Elsevier Sterols in red and green algae: quantification and relevance for the interpretation of geologic steranes Molecular fossils from organically preserved Ediacara biota reveal cyanobacterial origin for Beltanelliformis The effects of marine eukaryote evolution on phosphorus carbon and oxygen cycling across the Proterozoic–Phanerozoic transition in Microbial Ecology of the Oceans 2nd edn (ed Phagotrophy by a flagellate selects for colonial prey: a possible origin of multicellularity Patterns of distribution in the Ediacaran biotas: facies versus biogeography and evolution The origin of animals: can molecular clocks and the fossil record be reconciled Sponge spicules from the lower Cambrian in the Yanjiahe Formation South China: the earliest biomineralizing sponge record A crown-group demosponge from the early Cambrian Sirius Passet biota Volume 2: Biomarkers and Isotopes in Petroleum Exploration and Earth History (Cambridge Univ in Quantifying the Evolution of Early Life 355–401 (Springer Download references van Maldegem for discussions and reference samples; M Reymond for assistance in sourcing specimens; and S This study was principally funded by the Max Planck Society (to C.H and R.S.) and the Agouron Institute (Geobiology fellowship to B.J.N.) We also acknowledge the US National Science Foundation (grant nos Swiss National Science Foundation (grant no the French National Research Agency (grant no IMPEKAB ANR-15-CE02-001 to F.N.) and Australian Research Council (grant nos MARUM—Center for Marine Environmental Sciences Uppsala BioCentre Linnean Centre for Plant Biology Swedish University of Agricultural Sciences Adaptation and Diversity in Marine Environment (AD2M) Laboratory Ecology of Marine Plankton team Station Biologique de Roscoff Leibniz Centre for Tropical Marine Research (ZMT) collected some specimens and analysed all other samples wrote the manuscript with input from all authors Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations Supplementary Methods and Supplementary Text Download citation DOI: https://doi.org/10.1038/s41559-019-0806-5 Rocks hundreds of metres beneath the Australian Outback have yielded clues to a lost world of primitive microbes that once populated the world’s oceans and might have eventually given rise to modern plants and animals doi: https://doi.org/10.1038/d41586-023-01847-8 Read the related News & Views: ‘The long infancy of sterol biosynthesis’ Nature https://doi.org/10.1038/s41586-023-06170-w (2023) Download references Picuris Pueblo oral history and genomics reveal continuity in US Southwest Punic people were genetically diverse with almost no Levantine ancestors A pangenome reference of wild and cultivated rice author and TV presenter who traced continents through fossils A wetter ancient Arabia could have enabled easier intercontinental species dispersal A Jurassic acanthocephalan illuminates the origin of thorny-headed worms Powerful protein editors offer new ways of probing living cells A DNA-gated molecular guard controls bacterial Hailong anti-phage defence Structural basis of lipid transfer by a bridge-like lipid-transfer protein HT is an interdisciplinary research institute created and supported by the Italian government whose aim is to develop innovative strategies to pr.. UNIL is a leading international teaching and research institution with over 5,000 employees and 17,000 students split between its Dorigny campus Department of Energy and Environmental Materials and advance cancer research in a leading translational institute Olivia Newton-John Cancer Research Institute We are seeking a tenure-track associate professor to promote interdisciplinary research in nanoprobe life sciences or related interdisciplinary field Metrics details Quantum heat engines are subjected to quantum fluctuations related to their discrete energy spectra Such fluctuations question the reliable operation of thermal machines in the quantum regime we realize an endoreversible quantum Otto cycle in the large quasi-spin states of Cesium impurities immersed in an ultracold Rubidium bath Endoreversible machines are internally reversible and irreversible losses only occur via thermal contact We employ quantum control to regulate the direction of heat transfer that occurs via inelastic spin-exchange collisions We further use full-counting statistics of individual atoms to monitor quantized heat exchange between engine and bath at the level of single quanta and additionally evaluate average and variance of the power output We optimize the performance as well as the stability of the quantum heat engine large power output and small power output fluctuations We employ this system and techniques to evaluate and optimize the performance as well as the stability of the quantum heat engine a Individual laser-cooled Cs atoms (green) are immersed in an ultracold Rb cloud (orange); both are confined in a common optical dipole trap (DT) External magnetic fields and microwave (MW) radiation implement the power strokes of the quantum heat engine and distinguish the high- from the low-energy bath The inset shows typical mF-resolved fluorescence images of single Cs atoms for t = tB = 300 ms after initialization The position of the bath cloud is indicated in orange with a width of 4σ b The experimental Otto cycle consists of a heating stage during which average heat 〈QH〉 is absorbed and a power stroke induced by an adiabatic change of the magnetic field A microwave field then switches the bath from high to low energy The cycle is further completed by a cooling step during which average heat 〈QC〉 is released and an additional power stroke when the magnetic field is adiabatically brought back to its initial value c The heat transfer between the Cs atom (engine) and a Rb (bath) atom occurs via inelastic spin-exchange collisions a single quantum of spin associated with a certain energy quantum is exchanged Spin polarization of the Rb atoms and spin-conservation in individual collisions allow only up to six exo- or endothermal processes d Owing to the difference of atomic Landé factors between Cs and Rb the quantum heat engine (green) absorbs heat 〈QH〉 and releases heat 〈QC〉 (to produce work 〈W〉) The lost energy is irreversibly dissipated during an average of ten elastic collisions and is described by a heat leak 〈QL〉 from the high-energy bath The spin polarization of the Rb atoms distinguishes a high-energy bath for mRb = −1 from a low-energy bath for mRb = +1 Control over the internal Rb state accordingly permits to either increase or decrease the energy of the quasi-spin of the engine Heat exchange automatically stops after six spin-exchange collisions because then the highest/lowest energy state has been reached One collision transfers the colliding Rb atom to the $|{F}_{\text{Rb}}=1,{m}_{F,\text{Rb}}=0\rangle$ state Owing to the massive imbalance between the Rb and Cs atom numbers (NRb/NCs > 1000) the probability of a second collision with the same Rb atom is indeed vanishingly small The Cs machine is first driven by up to six spin-exchange collisions into energetically higher states (at magnetic field B1) absorbing average heat 〈QH〉 in time τH = tB Mean work 〈WBC〉 is then performed by adiabatically decreasing the magnetic field to B2 in τ = tC − tB = 10 ms This time is much longer than the inverse energy splitting ΔE of the quasi-spin states fast enough to avoid unwanted spin-exchange collisions The engine is subsequently brought into contact with the low-energy bath by flipping the spins of the Rb bath using microwave (MW) sweeps The Cs engine is accordingly driven by up to six spin-exchange collisions into energetically lower states Work 〈WDA〉 is further performed by adiabatically increasing the magnetic field back to B1 in τ = tA − tD = 10 ms The Rb spins are finally flipped to their initial state with other microwave sweeps During the heating (AB) and cooling (CD) steps of the quantum Otto cycle (center) The average population dynamics of the individual engine levels are shown in green extracted from the full-counting statistics are indicated for a cooling (blue) and b heating (red) as a function of the respective times τC and τH solid lines are a prediction of a microscopic model (Methods) the population dynamics shows the transition from an initially spin-polarized engine state via a state of many populated mF levels to a spin-polarized state of the other extreme spin state The inversion of an initially fully polarized population ($|{m}_{F,\text{Cs}}=3\rangle \leftrightarrow |{m}_{F,\text{Cs}}=-3\rangle$) requires some hundreds of milliseconds Error bars show statistical uncertainty of ± 1σ standard deviation We first characterize the performance of the quantum Otto engine by evaluating its efficiency given by13 we consider the average power of the quantum heat engine which reads We use the heat counting statistics to track its time evolution in Fig. 3b We observe that the power (blue dots) increases with the number of inelastic collisions and reaches a maximum ${\left\langle P\right\rangle }_{\max }/{k}_{\text{B}}=30$ nK/ms The corresponding number of inelastic collisions responsible for the heat exchange is almost 12 collisions total (6 spin-exchange collisions for the heating process and 6 for the cooling) This maximum nearly coincides with full population inversion between these two processes ($|{m}_{F,\text{Cs}}=3\rangle \leftrightarrow |{m}_{F,\text{Cs}}=-3\rangle$) Good agreement with a theoretical model (red solid line) is observed (Methods) the energy transfer with the atomic bath is optimal in the sense that it exchanges the maximum energy of six quanta in exactly six spin-exchange collisions as a consequence of the precise control of the spin states of machine and bath The value of ${\left\langle P\right\rangle }_{\max }$ may be further optimized by enhancing the magnetic field difference as well as the collision rate and the collision cross-section by controlling the temperature or density of the Rb gas but this regime is not seen experimentally due to experimental imperfections a Rb microwave spectra for extraction of the magnetic fields B1 and B2 Center illustrates the engine cycle and the corresponding Zeeman energy splitting of a Rb bath atom Red lines correspond to the theory curves and blue dots are experimental data These measurements yielding magnetic fields B1 = 346.5 ± 0.2 mG and B2 = 31.6 ± 0.1 mG Measured spectra confirm similar magnetic fields for B and C b Corresponding microwave transition scheme in the Rb ground-state hyperfine manifold The magnetic field changes extracting work of the engine have to be adiabatic The adiabaticity condition writes $\dot{{\omega }_{\text{lar}}}/{\omega }_{\text{lar}\,}^{2}\ll 1$ where ${\omega }_{\text{lar}}=| {g}_{F}^{\text{Rb}}| {\mu }_{\text{B}}B/\hslash$ is the Larmor frequency the populations pn are constant during the isentropic processes (B → C and D → A) we also compute the mean number of spin collisions Nspin within a cycle duration t = tD in two steps we calculate the time-averaged collision rate as the sum of time-averaged collision rates during heating (exothermal spin collisions) and cooling (endothermal spin collisions) as we integrate these rates during the heating and cooling to obtain the number of collisions within cycle time t as the inital and final Cs states before and after a cycle have to be the equal Owing to preservation of populations during adiabatic strokes we can further use ${p}_{n}^{\,\text{D}}={p}_{n}^{\text{A}\,}$ and ${p}_{n}^{\,\text{B}}={p}_{n}^{\text{C}\,}$ yielding the expression for the dissipated heat divided by the energy provided by the high-energy bath Using ${p}_{n}^{\,\text{D}}={p}_{n}^{\text{A}\,}$ ${p}_{n}^{\,\text{B}}={p}_{n}^{\text{C}\,}$ and γ = λ/κ The internal efficiency of the engine is computed as the ratio of the produced work ∣〈W〉∣ and the heat absorbed by the machine 〈QH〉: It corresponds to the efficiency without a leak (γ = 1) To extract the fluctuations of the engine, Eq. (4), we calculate the mean power, Eq. (3) The cycle time τcycle = tD is experimentally controlled and we assume that it is a fixed parameter not adding further fluctuations to the power-output fluctuations we can restrict the calculation to the fluctuations σW of work 〈W〉 as ${\sigma }_{W}^{2}=\langle {W}^{2}\rangle -{\langle W\rangle }^{2}$ The work is given by the difference of energy absorbed by and rejected from the engine ∣〈W〉∣ = 〈QH〉 − ∣〈QC〉∣ The averages and variances of heat absorbed or rejected depend on the energy differences at the different points during the cycle $E({t}_{i},{B}_{j})={\sum }_{n}{p}_{n}^{i}({t}_{i})\ n\lambda {B}_{j}$ can be computed from the measured populations $\{{p}_{n}^{i}\}$ of level n at point i = A D during the cycle and the magnetic field Bj(j = 1 the fluctuations ${\sigma }_{Q}^{2}$ of heat 〈Q〉 exchanged when changing the engine’s probability distribution from point i to point f at a magnetic field Bj reads The data that support the plots and findings of this study are available from the corresponding author upon reasonable request Current trends in finite-time thermodynamics efficiency and constancy in steady-state heat engines Cycling tames power fluctuations near optimum efficiency Denzler, T. & Lutz, E. Power fluctuations in a finite-time quantum Carnot engine. Preprint at https://arxiv.org/abs/2007.01034 (2020) Spin heat engine coupled to a harmonic-oscillator flywheel Single-atom energy-conversion device with a quantum load Experimental demonstration of quantum effects in the operation of microscopic heat engines Efficiency of a quantum otto heat engine operating under a reservoir at effective negative temperatures Experimental characterization of a spin quantum heat engine Tailored single-atom collisions at ultra-low energies Discrete four-stroke quantum heat engine exploring the origin of friction Irreversible work and inner friction in quantum thermodynamic processes and counting statistics in quantum systems Quantum energy exchange and refrigeration: a full-counting statistics approach Advances in Atomic Physics (World Scientific Single-atom quantum probes for ultracold gases boosted by nonequilibrium spin dynamics Dissipative endoreversible engine with given efficiency Efficiency of heat engines coupled to nonequilibrium reservoirs Nanoscale heat engine beyond the Carnot limit Squeezed thermal reservoirs as a resource for a nanomechanical engine beyond the Carnot limit Thermodynamics of non-Markovian reservoirs and heat engines An out-of-equilibrium non-Markovian quantum heat engine Beyond optical molasses: 3D raman sideband cooling of atomic cesium to high phase-space density Precision measurement of the 87Rb tune-out wavelength in the hyperfine ground state F = 1 at 790 nm Quantum spin dynamics of individual neutral impurities coupled to a Bose-Einstein condensate Introduction to Experiments and Theory (Springer Download references Tiemann for providing us with the scattering cross-sections underlying our numerical model Anglin for helpful comments on the manuscript This work was funded by Deutsche Forschungsgemeinschaft via Sonderforschungsbereich (SFB) SFB/TRR185 (Project No These authors contributed equally: Quentin Bouton Department of Physics and Research Center OPTIMAS conceived the experiment and supervised the project contributed to the microscopic numerical model provided the theoretical thermodynamic explanation All authors contributed to analysis and interpretation of the data Peer review information Nature Communications thanks the anonymous reviewers for their contribution to the peer review of this work Reprints and permissions Download citation DOI: https://doi.org/10.1038/s41467-021-22222-z but they have proposed that the lost creatures were tiny predators that hunted said bacteria The discovery fills in a large gap in the history of complex Researchers from the Australian National University and elsewhere found evidence of the so-called “Protosterol Biota” inside a 1.6-billion-year-old sedimentary rock recovered from the bottom of the ocean near what is now Australia’s Northern Territory Read More: What Are the Oldest Fossils in the World? they found fossilized fat molecules that held evidence of the biota like a microscopic time capsule Scientists had previously overlooked the tiny “protosteroids” because of their unusual configuration “Once we knew what we were looking for, we discovered that dozens of other rocks, taken from billion-year-old waterways across the world, were also oozing with similar fossil molecules,” says Jochen Brocks, a professor of geobiology, in a press release Along with researcher Benjamin Nettersheim Brocks has proposed that the organisms were larger than the bacteria they consumed and served as the world’s first predators The creatures would have thrived from about 1.6 billion years ago until 800 million years ago the time of the “Tonian Transformation.” This is when more complex life forms “Just as the dinosaurs had to go extinct so that our mammal ancestors could become large and abundant,” Brocks says “perhaps the Protosterol Biota had to disappear a billion years earlier to make space for modern eukaryotes.” The discovery extends the family tree of complex life back beyond the Last Eukaryotic Common Ancestor (LECA) another little understood organism that lived more than 1.2 billion years ago but Nettersheim says Protosterol Biota stand as even earlier figures in the human lineage Scientists have long searched for early eukaryotes and wondered why the early oceans appeared to have been one big “bacterial broth,” Brocks says “One of the greatest puzzles of early evolution scientists have been trying to answer is why didn’t our highly capable eukaryotic ancestors come to dominate the world’s ancient waterways “we show that the Protosterol Biota were hiding in plain sight and were in fact abundant in the world’s ancient oceans and lakes all along.” Read More: Oldest Fossil Fungi Hints at Early ‘Modern’ Life Register or Log In Want more?Keep reading for as low as $1.99 Subscribe Save up to 40% off the cover price when you subscribe to Discover magazine and fungi—is one of biology’s biggest mysteries A new discovery helps reveal these evolutionary roots The origin of organisms with complex cells is one of the most crucial parts of life’s evolutionary story and if complex cells had not developed on Earth While the oldest confirmed fossils of eukaryotes are about one billion years old, the organisms may have had a long-hidden prehistory, according to a new study of chemicals preserved in ancient rocks This chemical evidence suggests there were complex cells 1.6 billion years ago and possibly even earlier The tell-tale chemicals from these cells are the breakdown products of fatty molecules in their membranes. They had gone unnoticed until now because they are not the exact ones found in modern cells. “They are very primordial,” says Benjamin Nettersheim a geochemist at the University of Bremen in Germany and an author of the new study Nettersheim’s team found traces of these fatty molecules in a range of ancient rocks including Australia’s Barney Creek Formation The findings suggest primitive eukaryotes were widespread between about 1.6 billion and 800 million years ago comprising what the scientists have called a “lost world” of early complex life “It’s really quite substantial and really does change how we view the evidence for biomarkers and eukaryotic evolution,” says Emily Mitchell at the University of Cambridge in the United Kingdom who studies the early evolution of animals but was not involved in the study The oldest cellular organisms are bacteria and archaea Their cells are small and have few internal structures while eukaryotic cells are much bigger and contain structures such as a nucleus and the sausage-shaped mitochondria that produces energy Bacteria and archaea arose at least 3.5 billion years ago the origin of eukaryotes remains one of the biggest mysteries in biology It seems to have happened between one and two billion years ago A useful marker is the Last Eukaryotic Common Ancestor (LECA): the most recent species from which all modern eukaryotes are descended Genetics research suggests LECA lived at least 1.2 billion years ago Tracking how eukaryotes arose and evolved from such early fossils has proven difficult. So Nettersheim and his colleagues set out to find another line of evidence that would help tie down the eukaryote story. The researchers focused on chemicals called lipids, which include all fats and oils. Specifically, they targeted sterols: a group of lipids that are found in the outer membranes of eukaryotic cells. “Almost all eukaryotes produce sterols,” says Nettersheim. Probably the most famous sterol is cholesterol, which plays a major role in human biology. Over time, sterols break down into chemicals called steranes. Finding steranes in ancient rocks is good evidence that the place was once home to eukaryotes. Steranes are plentiful in rocks from the last 800 million years, but they have not been detected in older rocks. On face value, this looks like evidence that there were few eukaryotes before 800 million years ago, which flies in the face of the fossil and genetic evidence. However, Nettersheim and his colleagues have found another way to look at it. They reasoned that early eukaryotes might not have made the same kind of sterols as modern eukaryotes. Instead, the team focused on sterols that today only function as intermediate steps in the reaction pathways of cells. These, they suggest, were once the main sterols used by early eukaryotes, until later organisms found ways to convert them into different molecules, perhaps with more specialised properties. but they produced lipids that are now intermediates,” says Nettersheim This approach enables researchers to look at the “evolutionary development or precursors” of sterols, says Paul Strother a palaeobotanist at Boston College in Massachusetts The team determined what molecules these primordial sterols would decay into Then they searched ancient rocks for those breakdown products Previously the chemical record suggested a late origin of eukaryotes while the microfossil and genetic evidence indicated an earlier one Now the chemical record has been extended back in time and the three largely align “When very independent lines start matching up then you know that you’ve probably got a very accurate record,” says Mitchell Eukaryotes first evolve at least 1.6 billion years ago possibly as early as two billion years ago They use the primordial sterols in their outer membranes A crucial step occurs where some eukaryotes evolve to use modern sterols But pushing back the origin of eukaryotes to at least 1.6 billion years ago creates a new question: Why did it take so long for complex animals One possibility is that complex multicellular organisms evolved earlier than is generally thought. For example, a 2019 study claimed to have found fossil sponges, one of the earliest animal groups, in rocks from 890 million years ago This would push back the origin of animals by 350 million years Nettersheim says the fossils are “not really convincing,” because some single-celled eukaryotes can produce similar-looking structures Nettersheim’s team suggests instead that the early eukaryotes dominated prehistoric ecosystems and modern eukaryotes could only flourish and diversify when this earlier population died out Modern sterols help eukaryotes adjust to stresses like dehydration and cold shock so it may be that the more developed cells were better suited to survive a period of environmental stress A possible cause may be conditions called Snowball Earth: a series of episodes in which Earth’s climate cooled considerably “Potentially the entire Earth was frozen or at least very cold,” says Nettersheim Snowball Earth episodes occurred during the Cryogenian Period between about 720 and 635 million years ago Modern sterols could have helped certain eukaryotes survive while others died—and once the glaciation eased the surviving eukaryotes diversified into plants and animals “We think this might have been one of the pre-adaptations that helped the modern eukaryotes attain ecological importance,” says Nettersheim “It seems like a reasonable suggestion,” says Mitchell pointing out that we have so few early eukaryotes preserved that any new discovery could upend the story these paradigms are somewhat fragile,” he says Similarly, in 2021 Strother and his colleagues described another billion-year-old eukaryote called Bicellum brasieri, found in the Scottish Highlands. This one was multicellular, and what’s more, it had two distinct cell types: a precursor to the tissues and organs of later animals and plants. “If at one billion we’re having these kinds of morphological complexity, that would kind of indicate maybe stuff was happening earlier than 800 million,” he says. Paleontologists have detected abundant protosteroids — traces of ancient life forms — in 1.6-billion-year-old sedimentary rocks that had formed at the bottom of the ocean near what is now Australia’s Northern Territory Eukaryotic life appears to have flourished surprisingly late in the history of Earth This view is based on the low diversity of diagnostic eukaryotic fossils in marine sediments of mid-Proterozoic age (around 1.6 billion to 800 million years ago) and an absence of steranes the molecular fossils of eukaryotic membrane sterols This scarcity of eukaryotic remains is difficult to reconcile with molecular clocks that suggest that LECA had already emerged between around 1.2 and more than 1.8 billion years ago must have been preceded by stem-group eukaryotic forms by several hundred million years report the discovery of abundant protosteroids in sedimentary rocks of mid-Proterozoic age “All living eukaryotes evolved from the Last Eukaryotic Common Ancestor (LECA) that lived between around 1.2 billion and more than 1.8 billion years ago,” said University of Bremen paleontologist Benjamin Nettersheim and colleagues “LECA and all its descendants form the crown of the eukaryotic tree including algae “Yet, the domain Eukarya has a much deeper prehistory “The genome and cell structure of living descendants provide only limited insights into the evolution of LECA’s ancestors and almost nothing is known about their abundance “To study the hundreds of millions of years of hidden eukaryote evolution and ecology we have to search for fossil and chemical remains directly in the geological record.” In their research, the scientists detected chemical traces of the so-called Protosterol Biota in 1.6-billion-year-old rocks of the Barney Creek Formation in northern Australia “These ancient creatures were abundant in marine ecosystems across the world and probably shaped ecosystems for much of Earth’s history,” Dr “The Protosterol Biota were certainly more complex than bacteria and presumably larger although it’s unknown what they looked like,” added Australian National University’s Professor Jochen Brocks “We believe they may have been the first predators on Earth these creatures thrived from about 1.6 billion years ago up until about 800 million years ago The end of this period in Earth’s evolutionary timeline is known as the ‘Tonian Transformation,’ when more advanced nucleated organisms But exactly when the Protosterol Biota went extinct is unknown “The Tonian Transformation is one of the most profound ecological turning points in our planet’s history,” Professor Brocks said “Just as the dinosaurs had to go extinct so that our mammal ancestors could become large and abundant perhaps the Protosterol Biota had to disappear a billion years earlier to make space for modern eukaryotes.” The team’s findings appear in the journal Nature own shares in or receive funding from any company or organisation that would benefit from this article and have disclosed no relevant affiliations beyond their academic appointment Australian National University provides funding as a member of The Conversation AU View all partners and they may stand at the root of all complex animal life on Earth Scientists study the evolution of the earliest sponges to learn about the conditions that led life to develop from single-celled amoeba-like creatures to the large mobile and even intelligent animals that surround us today Exactly when and how animals emerged on our planet is a subject of fierce debate among scientists While the most ancient sponge fossils ever found are around 540 million years old some have argued that fossil molecules dating from 635 million years ago are evidence of earlier animal life The oldest fossil remnants of sponges that can be recognised in ancient rocks are around 540 million years old and date to the early Cambrian period. But there are yet older fossils of animals that belong to the biota of the Ediacara period Among the enigmatic Ediacaran creatures that lived up to 40 million years before the “Cambrian explosion” of complex life was an oval-shaped organism called Dickinsonia It could exceed one meter in size and its segmented body is popularly depicted as something like a quilted air-mattress A recent study detected fossil cholesterol Cholesterol is a characteristic animal fat so this suggests that Dickinsonia really was a genuine animal rather than a fungus or something else But even older than these cholesterol traces found in body fossils are fossilised organic molecules found alone. In 2009, a team of scientists discovered molecules called sterols in 635 million-year-old sediments in Oman on the Arabian Peninsula that once was the bottom of an inland sea the only organisms that were known to produce similar sterols were specific sponges Here was the long-sought earliest evidence for animals in the world the fossil “sponge sterols” were found in rocks of this age around the globe suggesting that these animals were very abundant This exciting discovery suggested that the ancient fat recovered from rocks in Oman represented some of the first recognisable traces that animals left on our planet But do ancient fat signatures alone really suffice to reconstruct early animal evolution interpretation of fossil sterols from million-year-old rocks may not be as straightforward as comparing it to the sterols of living organisms its remains settle on the bottom of the ocean They get buried deeper and deeper as sediment builds up most knowledge about organisms of the past gets erased by these changes The most informative parts of the molecules are also the most fragile and they disappear over time to leave behind a more generic We wondered whether other changes might occur as well potentially producing molecules that look like fossil sterols of modern sponges but actually have nothing to do with animals we approached this question from different ends One study headed by Lennart van Maldegem and Benjamin Nettersheim focused on sterol molecules preserved in sediments up to 800 million years old It was thought that these molecules might extend the geological record of animals even deeper into Earth’s history than the famous Oman signatures the study uncovered a significant connection between some of the sponge-associated molecules and compounds known to be generated through geological alterations indicating that they shared the same origin we then carried out laboratory experiments to simulate the effect of geological heating on particular molecules produced by algae The resulting molecular signatures were surprisingly similar to those of the ancient rocks So the fossil fat provides interesting insights into the molecular make-up of early algae but unfortunately does not illuminate early animal evolution The second study but between 500 million and 650 million years ago they dominated oceans all over the world By heating green algal molecules in the laboratory – similar to what happens to molecules in rocks – this study showed that some of the most common sterols of green algae can be easily altered into sponge-like molecules This indicates that also the ancient Oman signature may represent sterols that were originally produced by primitive algae and subsequently altered by geological processes It turns out that even ancient fat can be deceptive our two studies demonstrate that sponge-associated molecules in ancient rocks are not a tell-tale sign of animals they were most likely generated by the remains of common algae exposed to geological heating These results should now finally settle the long-lasting debate surrounding the oldest molecular traces of early animals There currently is no evidence that sponge-like animals conquered the oceans before 540 million years ago when the first unambiguous fossils of sponges and most other groups of animals start to appear in the geological record The earliest evidence for animals on Earth is now the 558 million-years-old Dickinsonia and other Ediacaran animals labeled as the “Protosterol Biota,” belong to a broad family of life known as eukaryotes eukaryotes exhibit a more intricate cell structure Their cells house vital components such as mitochondria famously dubbed the “powerhouse” of the cell and a nucleus serving as the “control and information center.” Eukaryotes of today have adopted various forms – fungi and single-celled organisms like amoebae are some of the examples trace their ancestry back to the Last Eukaryotic Common Ancestor (LECA) an organism that existed more than 1.2 billion years ago However, this recent discovery, which was published in the journal Nature, unveils that the Protosterol Biota thrived even before LECA. Scientists from Australian National University (ANU) propose that these organisms might have been the Earth’s inaugural predators a former PhD student at ANU now at the University of Bremen in Germany noted that these ancient beings were quite prolific in marine ecosystems around the world “Molecular remains of the Protosterol Biota detected in 1.6-billion-year-old rocks appear to be the oldest remnants of our own lineage – they lived even before LECA.” “Scientists have long searched for fossilised evidence of these early eukaryotes but their physical remains are extremely scarce,” explained Dr “Our study flips this theory on its head We show that the Protosterol Biota were hiding in plain sight and were in fact abundant in the world’s ancient oceans and lakes all along.” Further elucidating on the nature of these ancient organisms who collaborated with Dr Nettersheim on this discovery suggests that the Protosterol Biota were certainly more intricate and probably larger than bacteria “We believe they may have been the first predators on Earth hunting and devouring bacteria,” said Professor Brocks. the reign of these creatures began around 1.6 billion years ago and lasted until about 800 million years ago This was a period in Earth’s evolutionary timeline that culminated in the “Tonian Transformation.” During this significant juncture more advanced nucleated organisms such as fungi and algae began to prosper “The Tonian Transformation is one of the most profound ecological turning points in our planet’s history,” said Professor Brocks “Just as the dinosaurs had to go extinct so that our mammal ancestors could become large and abundant perhaps the Protosterol Biota had to disappear a billion years earlier to make space for modern eukaryotes.” The scientists made this groundbreaking discovery by studying fossil fat molecules tucked away inside a 1.6-billion-year-old rock that had formed at the bottom of the ocean near present-day Australia’s Northern Territory suggested the presence of early complex creatures that evolved before LECA and had since vanished but our new discovery shows that this probably wasn’t the case,” said Dr These fossil molecules have been overlooked for decades as they did not fit the typical molecular search parameters used by scientists. “Scientists had overlooked these molecules for four decades because they do not conform to typical molecular search images,” said Professor Brocks “But once we knew what we were looking for were also oozing with similar fossil molecules.” who undertook this analysis as a part of his PhD at ANU before moving to the University of Bremen This seminal work involved a multinational collaboration that brought together scientists from Australia This remarkable discovery of the Protosterol Biota revealing an unknown chapter of Earth’s evolutionary narrative is a testament to the boundless scope of scientific exploration. As we delve deeper into the mysteries of the past we gain valuable insights that help shape our understanding of the present and foresee the trajectory of life’s future evolution The story of our ancient ancestors might be far from complete but this discovery serves as a fascinating new piece of the puzzle Life on Earth started at least 3.5 billion years ago as evidenced by the discovery of fossils of microscopic organisms in rocks of that age. The very first lifeforms were likely simple was characterized by a lack of oxygen in the Earth’s atmosphere and high levels of volcanic activity Among the earliest forms of life were prokaryotes single-celled organisms that lack a nucleus or other membrane-bound organelles The prokaryotes include bacteria and archaea two domains of life that are still present today. capable of surviving in harsh environments such as hydrothermal vents and acidic springs which were common during Earth’s early history Life remained microscopic and single-celled for billions of years a significant evolutionary leap occurred: the emergence of eukaryotes. These are organisms with complex cells that have a nucleus and other membrane-bound organelles The first eukaryotes were likely single-celled but they represented a significant increase in biological complexity The invention of photosynthesis by cyanobacteria transformed the Earth’s atmosphere by filling it with oxygen The rise of oxygen levels in the atmosphere allowed for the evolution of more complex These strange creatures bore little resemblance to modern animals and many of them belonged to groups that have since gone extinct. It wasn’t until the Cambrian explosion that the ancestors of most modern animal groups emerged This event was characterized by a rapid increase in biodiversity and complexity the journey of life on Earth began with simple evolved into the complex web of biodiversity we see today This ongoing process of evolution continues to shape life on our planet Image Credit: Orchestrated in MidJourney by TA 2023 Check us out on EarthSnap, a free app brought to you by Eric Ralls and Earth.com Metrics details This article has been updated Cancer/testis-antigens (CTAs) are specifically expressed in human malignancies and testis tissue but their molecular functions are poorly understood CTAs serve as regulators of gene expression as well as targets for immune-based therapies The CTA PRAME is expressed in various cancers antagonises retinoic acid signalling and is regulated by DNA methylation and histone acetylation We analysed the molecular function of the CTA PRAME in primordial germ cells (PGC) and testicular germ cell cancers (GCC) GCCs arise from a common precursor lesion termed germ cell neoplasia in situ (GCNIS) which itself is thought to originate from a defective PGC GCNIS cells eventually develop into unipotent seminomas or totipotent embryonal carcinomas (ECs) which are capable of differentiation into teratomas like the master regulator of PGCs SOX17 expressed in human PGCs shRNA-mediated knockdown of PRAME in seminomatous TCam-2 cells left SOX17 levels unchanged but resulted in downregulation of pluripotency- and PGC-related genes (LIN28 whereas somatic and germ cell differentiation markers were upregulated PRAME seems to act downstream of SOX17 by mediating the regulation of the germ cell differentiation and pluripotency programme Endoderm differentiation is triggered in somatic cells by SOX17 PRAME represses this programme and modulates SOX17 to function as a PGC-master regulator knockdown of PRAME in TCam-2 cells did not render the cells sensitive towards retinoic acid despite the fact that PRAME has been described to antagonise retinoic acid signalling we demonstrate that in non-seminomas PRAME expression is silenced by DNA methylation which can be activated by formation of euchromatin via histone-deacetylase-inhibitors We identified the CTA PRAME as a downstream factor of SOX17 and LIN28 in regulating pluripotency and suppressing somatic/germ cell differentiation in PGC GCNIS and seminoma cells are not prone to spontaneous differentiation seminomas and PGCs PRAME expression correlates to SOX17 expression we reasoned that expression of PRAME is a general feature of PGC GCNIS and seminomas and its function might be linked to SOX17 we further speculate that PRAME might be required for RA resistance of PGCs/seminomas we analysed molecular function of PRAME and its link to SOX17 in PGC and GCC biology we correlated PRAME expression to DNA methylation and RA responsiveness and analysed how histone deacetylation affects PRAME expression in GCC cell lines The ethics commitee of the Rheinische Friedrich-Wilhelms-Universität Bonn approved the analyses of formalin fixed paraffin-embedded type-II GCC tissues in context of this study No personal patient data will be collected or stored 100 nM β-mercaptoethanol) at 37 °C and 5% CO2 All tumours were classified according to the WHO classification based on their histology Samples were examined by frozen section to assure a significant tumour cellularity Only TFAP2C-positive/SOX2-negative seminomas and SOX2-positive ECs were analysed DNA was isolated by phenol/chloroform/isoamylalcohol Bulk proteins were isolated by RIPA buffer whereas nuclear and cytoplasmic proteins were separately isolated by the ‘Nuclear Extract Kit’ (Active Motif Colorimetric analysis of band/expression intensities was performed by Image Lab software (BioRad) 70 μg of total protein was loaded onto the array and incubated at 4 °C overnight Each sample was analysed in three biological replicates 1 × 105 GCC cells were treated for 8 days (d) with 20 μ M RA (Sigma-Aldrich as well as for 16 h with 10 nM romidepsin (Celgene for 24 with 1 μ M VPA and for 24 h with 20 nM TSA (all from Sigma-Aldrich) Corresponding solvents were used as controls The PRAME shRNA oligonucleotides (Table 2) were cloned into the pSUPER.retro.puro-vector (OligoEngine USA) according to the pSUPER RNAi System manual A shRNA against the GFP sequence was used as unspecific control A plasmid coding for GFP (pRP-GFP) was utilised to monitor the infection efficiency Retroviral particles were produced in 1.2 × 106 HEK293 cells by transfecting 2 μg of the retroviral PRAME shRNA plasmid 2 μg pCMV-gag-pol-plasmid and 220 ng pCMV-VSV-G-plasmid via the calcium phosphate method sterile filtered and applied to the target cells Stable shRNA-expressing cells were selected by adding 0.5 mg ml−1 puromycin every second day for 1 week Chromatin-immunoprecipation followed by sequencing (ChIP-seq) analysis was performed by Active Motif (Carlsbad USA) in context of a different study and was re-analysed in this study with regard to PRAME including Drosophila DNA as spike-in control were used as input control The ChIP-seq data are publically available via GEO (GSE78262) we found the CTAs PRAME and XAGE1 strongly expressed in GCNIS/seminomas PRAME expression in GCC tissues and cell lines (A) Correlation of SOX2 and SOX17 expression to PRAME expression in normal adult testis tissue (NATT) and indicated GCC tissues (B) qRT–PCR analysis of PRAME expression in indicated GCC tissues and corresponding cell lines as well as fibroblasts (Fibro) and Sertoli cells (Sert) (C) Western blot analysis of PRAME expression in seminoma and EC tissues as well as GCC cell lines and human fibroblasts (D) Pie diagrams summarising cellular localisation of PRAME in seminoma and EC tissues as determined by IHC (E) IHC staining of PRAME in seminomas and ECs (F) Western blot analysis of PRAME expression in the nuclear and cytoplasmic extract of TCam-2 cells Efficient separation of nuclear and cytoplasmic fraction was demonstrated by OCT3/4 and β-actin detection Sem=seminomas; EC=embryonal carcinoma; Cc=choriocarcinoma a more prominent signal was detected in the nucleus in western blotting the antibody is able to specifically detect PRAME but IHC staining is biased by detection of additional unspecific signals in the cytoplasm PRAME shRNA-mediated knockdown in TCam-2 cells (A) Detection of a GFP signal in nearly all pRP-GFP-infected TCam-2 (pRP-GFP) demonstrates high transduction efficiency PRAME-knockdown cells (PRAME shRNA 1) show a change in morphology C) qRT–PCR and western blot analysis of PRAME expression in PRAME shRNA-infected and puromycin-selected TCam-2 cells GFP shRNA-infected and empty vector-infected TCam-2 served as controls In order to reveal the molecular effects of a PRAME knockdown we performed expression microarray analyses knockdown of PRAME might render TCam-2 cells sensitive toward RA PRDM14 and ZSCAN10) are downregulated upon PRAME knockdown suggesting that PRAME normally contributes to maintenance of the pluripotency programme in TCam-2 cells These findings suggest that PRAME shRNA cells initiate differentiation into the somatic lineage Furthermore, knockdown of PRAME led to upregulation of genes associated with reproductive development and germ cell differentiation (CCND1, DMRT1, OSR1, TP63, SPRY4), indicating that PRAME suppresses this programme (Supplementary Data S1D) our data demonstrate that in TCam-2 PRAME supports the pluripotency network and suppresses a somatic and germ cell differentiation process including RA-signalling-related genes CYP26A1 which were also upregulated in RA-treated PRAME shRNA cells These findings demonstrate that a PRAME knockdown does not sensitise TCam-2 cells towards a RA-induced differentiation process although upregulation of RA-response genes like RARB demonstrated a cellular response toward RA The deregulations in expression of pluripotency/PGC factors were also detected by our microarray analysis, but expression intensities were slightly below our set significance threshold. Nevertheless, the same trend in downregulation of pluripotency factors was found (Supplementary Figure S3D) Upon PRAME knockdown expression of SOX17 did not change significantly and markers for germ cell and somatic differentiation were upregulated This demonstrates that expression of SOX17 does not depend on PRAME PRAME is required to maintain PGC-state in repressing somatic and further germ cell differentiation in TCam-2 Furthermore, our analysis of the PRAME shRNA cells pointed at a regulatory link between PRAME and the RNA-binding protein LIN28A. By Co-IP analysis using either a LIN28A or a PRAME antibody, we demonstrated that indeed PRAME and LIN28A interact with each other (Figure 3F) the influence of PRAME on the pluripotency programme is at least in part a result of the interaction with LIN28A maybe by binding and guiding LIN28A to its target RNAs knockdown of PRAME leads to an increase in MAPK signalling our DAVID analysis predicted enrichment of genes associated with regulation of kinase activity/phosphorylation and by microarray analysis we found upregulation of marker genes associated with ERK1/2/P38-MAPK signalling TGFB1 as well as the negative regulators of MAPK signalling Epigenetic regulation of PRAME expression by DNA methylation and histone acetylation (A) Illustration of pan-H3ac ChIP-seq data in TCam-2 and genomic features of the PRAME locus in the Genome Browser (B) Sodium-bisulfite sequencing of the PRAME promotor in GCC tissues and corresponding cell lines as well as during in vivo reprogramming of TCam-2 to an EC-like state (C) qRT–PCR analysis of PRAME expression in HDI (romidepsin)-treated GCC cell lines Fold change (romidepsin-treated versus solvent control) is indicated above bars (D) Western blot analysis of PRAME and pan-Histone H3 acetylation (pan-H3ac) in selected HDI-treated samples (E) qRT–PCR analysis of PRAME expression in HDI (SAHA PRAME expression inversely correlates to the DNA methylation status of the PRAME promoter in GCNIS/seminomas and ECs suggesting that PRAME expression is silenced by DNA methylation in non-seminomas PRAME expression can be restored in non-seminomatous GCC cell lines by inhibition of HDACs formation of euchromatin around the PRAME locus seems to override the repressive DNA methylation mark leading to de-repression of PRAME expression we analysed expression of the CTA PRAME in human testicular GCCs and corresponding cell lines and demonstrated that PRAME is expressed in PGCs/GCNIS/seminomas and is absent in ECs Knocking down PRAME in seminomatous TCam-2 leads to downregulation of pluripotency and PGC markers the cells displayed increased cell size and appeared as big flat roundish cells indicative of differentiation Expression microarray analyses revealed upregulation of genes suggestive for endodermal/mesodermal and germ cell differentiation in seminomas (and probably in human PGCs) expression of PRAME leads to a fixation of the PGC fate by suppressing germ cell and somatic differentiation These data suggest that in seminomas SOX17 is able to bind the canonical motif and thus SOX17 can replace SOX2 in the pluripotency cluster This indicates that SOX17 is upstream of PRAME in the cascade of PGC genes knockdown of PRAME results in downregulation of pluripotency/PGC factors (LIN28A TFAP2C) and upregulation of genes indicative for germ cell differentiation This suggests that PRAME expression leads to a fixation of the SOX17-induced PGC fate lowering the levels of PRAME led to upregulation of endoderm markers PRAME seems required for binding of the SOX17/OCT3/4 dimers to pluripotency markers Reduction of PRAME leads to alteration in binding-site selection allowing (as demonstrated in murine embryonic stem cells) the SOX17/OCT3/4 dimers to bind to somatic differentiation genes a knockdown of PRAME leads to increased activity of MAPK signalling (ERK1/2 It is known that repression of MAPK signalling by MEK inhibition is required to maintain ES cells in pluripotency and repress somatic differentiation It remains to be elucidated whether PRAME itself represses MAPK signalling or whether the upregulation of MAPK signals is a secondary process due to the upregulation of somatic differentiation markers Treatment of the PRAME-knockdown TCam-2 cells with RA had no considerable effect on expression of pluripotency and PGC markers suggesting that RA has little role in PRAME-knockdown-induced reduction of pluripotency and loss of a seminoma-like cell state the RA-metabolising enzyme CYP26A1 was strongly upregulated which might catabolise RA to excreted oxoderivatives (4-OH RA This leads to the suppression of RA-induced differentiation We found that PRAME expression inversely correlated to DNA methylation in the PRAME promoter and that in non-seminomatous cell lines repressed PRAME expression can be restored by HDI treatment seminomas respond very well to DNA-damaging treatments In future experiments it would be of interest to find out if PRAME has a role in this sensitivity and if restoring PRAME expression by HDI treatment in (chemotherapy-resistant) non-seminomas might re-sensitise these cells towards a treatment with DNA-damaging agents Model of the cellular mechanisms of PRAME (B) A knockdown of PRAME leads to suppression of pluripotency- and PGC-associated factors whereas expression of somatic and germ cell differentiation markers is induced via binding of SOX17/OCT3/4 to compressed binding motifs This paper was modified 12 months after initial publication to switch to Creative Commons licence terms Stanton LW (2013) Oct4 switches partnering from Sox2 to Sox17 to reinterpret the enhancer code and specify endoderm Skakkebaek NE (2016) Germ cell neoplasia in situ (GCNIS): evolution of the current nomenclature for testicular pre-invasive germ cell malignancy Buettner R (2007) Genome-wide expression profiling reveals new insights into pathogenesis and progression of testicular germ cell tumors Looijenga LHJ (2008) Differential expression of SOX17 and SOX2 in germ cells and stem cells has biological and clinical implications Schorle H (2008) TCam-2 but not JKT-1 cells resemble seminoma in cell culture Bernards R (2005) The human tumor antigen PRAME is a dominant repressor of retinoic acid receptor signaling Qiao J (2015) The transcriptome and DNA methylome landscapes of human primordial germ cells Hide W (2008) Genome-wide analysis of cancer/testis gene expression Lempicki RA (2009) Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources Surani MA (2015) SOX17 is a critical specifier of human primordial germ cell fate Schorle H (2011a) NANOG promoter methylation and expression correlation during normal and malignant human germ cell development Schorle H (2011b) The seminoma cell line TCam-2 is sensitive to HDAC inhibitor depsipeptide but tolerates various other chemotherapeutic drugs and loss of NANOG expression EGF and FGF4 synergistically induce differentiation of the seminoma cell line TCam-2 into a cell type resembling mixed non-seminoma Schorle H (2013) Analysis of TET expression/activity and 5mC oxidation during normal and malignant germ cell development Schorle H (2015) BMP inhibition in seminomas initiates acquisition of pluripotency via NODAL signaling resulting in reprogramming to an embryonal carcinoma Schorle H (2012) Establishment of a versatile seminoma model indicates cellular plasticity of germ cell tumor cells Fischer M (2004) The tumor-associated antigen PRAME is universally expressed in high-stage neuroblastoma and associated with poor outcome Looijenga LH (2005a) Testicular germ-cell tumours in a broader perspective Looijenga LHJ (2005b) Testicular germ-cell tumours in a broader perspective Schorle H (2013) Transcription factor TFAP2C regulates major programs required for murine fetal germ cell maintenance and haploinsufficiency predisposes to teratomas in male mice Saluz HP (2007) Hypomethylation of PRAME is responsible for its aberrant overexpression in human malignancies Royer-Pokora B (2008) Characteristics of testicular dysgenesis syndrome and decreased expression of SRY and SOX9 in Frasier syndrome Leffers H (2009) Analysis of gene expression profiles of microdissected cell populations indicates that testicular carcinoma in situ is an arrested gonocyte Mahdavi V (1978) The induction of differentiation in teratocarcinoma stem cells by retinoic acid Mering von C (2015) STRING v10: protein-protein interaction networks Surani MA (2015) A unique gene regulatory network resets the human germline epigenome for development a gene encoding an antigen recognized on a human melanoma by cytolytic T cells Bernards R (2002) A gene-expression signature as a predictor of survival in breast cancer Hadjantonakis A-K (2014) SOX17 links gut endoderm morphogenesis and germ layer segregation Stanton LW (2007) Zfp206 is a transcription factor that controls pluripotency of embryonic stem cells Whitehurst AW (2014) Cause and consequence of cancer/testis antigen activation in cancer Yu L (2013) Increased PRAME-specific CTL killing of acute myeloid leukemia cells by either a novel histone deacetylase inhibitor chidamide alone or combined treatment with decitabine Hughes TR (2006) Zfp206 regulates ES cell gene expression and differentiation Download references Barbara Reddemann and Alena Heimsoeth for technical assistance Romidepsin was provided by Gloucester Pharmaceuticals (Celgene Institute of Clinical Chemistry and Clinical Pharmacology The authors declare no conflict of interest This work is published under the standard license to publish agreement After 12 months the work will become freely available and the license terms will switch to a Creative Commons Attribution-NonCommercial-Share Alike 4.0 Unported License Supplementary Information accompanies this paper on British Journal of Cancer website From twelve months after its original publication, this work is licensed under the Creative Commons Attribution-NonCommercial-Share Alike 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/4.0/ Download citation ANU/Midjourney by TA 2023The molecular remains of a microbe called protosterol biota appeared within the Barney Creek Formation in Australia’s Northern Territory — and those traces could hold information on the origin of complex life on Earth A paper published June 7 in the journal Nature describes biomarkers from the ancient forebearer protosterol biota which formed at the bottom of the ancient ocean contains protosterol biota traces that date as far back as 1.64 billion years ago The work points to the possibility that these ancient creatures were abundant in marine ecosystems and had a heavy hand in shaping the planet’s history The biomarker discovery in the Australian rocks might be critical to the study of life on Earth because the 1.64 billion year old protosterol biota biomarkers may constitute what remains of our earliest known ancestors He studied and sampled rock cores of the 1.64 billion year old Barney Creek Formation in Australia The finding pushes back the understanding of eukaryotic life — most lifeforms that aren’t bacteria or similar microbes — by a half-billion years This has consequences for our understanding of eukaryotic life eukaryotic microbes would have also been abundant in the time before the Last Common Eukaryotic Ancestor — the organism that gave rise to complex life as we know it The molecular traces in the rocks are as close to a fossil for these microbes as scientists can get Although they are thought to have lived on Earth for about 2 billion years only their byproducts would signal that they existed A team of researchers led by the Australian National University (ANU) made the incredible findings. Jochen Brocks suggests that these traces were always around They were first predicted by Nobel laureate Konrad Bloch almost three decades ago although Bloch concluded that not even the biomarkers would survive the passage of time One big question now is, when did Protosterol Biota go extinct? “Just as the dinosaurs had to go extinct so that our mammal ancestors could become large and abundant, perhaps the Protosterol Biota had to disappear a billion years earlier to make space for modern eukaryotes,” Brocks says in an announcement from ANU Metrics details Protamines are arginine-rich DNA-binding proteins that replace histones in elongating spermatids This leads to hypercondensation of chromatin and ensures physiological sperm morphology protamine-1 (Prm1) and protamine-2 (Prm2) are expressed in a species-specific ratio alterations of this PRM1/PRM2 ratio is associated with subfertility By applying CRISPR/Cas9 mediated gene-editing in oocytes heterozygous males remained fertile with sperm displaying normal head morphology and motility DNA-hypercondensation and acrosome formation was severely impaired the sperm displayed severe membrane defects resulting in immotility lack of Prm2 leads not only to impaired histone to protamine exchange and disturbed DNA-hypercondensation but also to severe membrane defects resulting in immotility previous attempts using a regular gene-targeting approach failed to establish Prm2-deficient mice This was due to the fact that already chimeric animals generated with Prm2+/− ES cells were sterile the Prm2-deficient mouse lines established here clearly demonstrate that mice tolerate loss of one Prm2 allele As such they present an ideal model for further studies on protamine function and chromatin organization in murine sperm chimeras generated by injecting ES cells heterozygous for one allele of either protamine gene resulted in infertility Prm2-deficient mouse lines could not be established hampering further experiments dealing with Protamine function We demonstrate that mice heterozygous for Prm2 are fertile with normal sperm morphology and motility whereas Prm2-null mice are infertile due to a complete loss of sperm motility and abnormal sperm head morphology CRISPR/Cas9-mediated generation of Prm2-deficient mice (a) Schematic representation of the Prm2 gene locus and targeting sites of designed gRNAs Intended target sites of gRNAs were amplified by PCR from genomic DNA of gene-edited E14TG2a ES cells Wildtype and gene-edited PCR products were denaturated and re-annealed Surveyor nuclease mediated cleavage of mismatched PCR products (highlighted by arrowheads) confirmed functionality of gRNAs (c,d) Genotyping of offsprings by PCR and Surveyor assay identified 4/10 animals to be mutant as indicated by asterisks (PCR) and pluses (Surveyor) Sequence analysis of genomic DNA from #10 revealed that the CRISPR/Cas9-mediated gene-editing resulted in four different alleles This suggests that gene-editing took place at the 2-cell-stage Alleles with deletions of 97 bp and 101 bp were separated by back-crossing with C57BL/6 wildtype mice Knockout validation and fertility analysis (a) Schematic representation of established Prm2-deficient mouse lines Prm2Δ97bp and Prm2Δ101bp Blue triangle marks cleavage site within the premature PRM2 protein (b) Mating statistics of Prm2-deficient males and females Successful mating of Prm2−/− males with wildtype females was indicated by presence of a vaginal plug at 0.5 dpc (c) Relative expression of Prm2 mRNA in murine testis of wildtype (d) Immunohistochemical staining of PRM2 on testicular sections of wildtype (e) Immunoblot against PRM2 following acid urea gel electrophoresis of basic nuclear proteins isolated from epididymal sperm of Prm2Δ97bp or Prm2Δ101bp mice the amount of protein loaded from Prm2-deficient samples were doubled compared to samples from wildtype and heterozygous animals Coomassie-Brilliant-Blue staining (CBB) served as loading control The antibody detects mature PRM2 as well as its precursor forms (pP2-a Morphological testes and sperm analysis (c) HE staining of testicular sections from wildtype (d) Transmission electron micrographs (TEM) of stage XII seminiferous epithelium as indicated by meiotic spermatocytes (stars) showing step 12 elongating spermatids Note homogeneously condensed chromatin in wildtype in contrast to heterogeneously condensed fine-grained chromatin in the Prm2-deficient mutant whereas formation of the acrosome and manchette as well as head shape did not differ (e) TEMs of step 16 elongated spermatids prior to sperm release detachment of acrosome (arrow) and attachment of the flagellum to the head (arrowhead) in knockout sperm (g) Quantification of epididymal sperm chromatin integrity (h) Prm2−/− but not Prm2+/− sperm showed morphological defects in the acrosome and head-tail conjunction The acrosome was labeled using PNA-FITC (green) (i) Agarose gel electrophoresis of sperm genomic DNA (j,k) Sperm damage analysis referring to SCSA (a) Tracks for freely swimming wildtype Prm2+/+ and heterozygous Prm2+/− sperm Sperm were tethered with their heads to a glass surface and the flagellar waveform was analyzed (c) Changes in the intracellular Ca2+ concentration in Prm2+/+ Sperm have been loaded with CAL520-AM and stimulated with K8.6 (blue) Experiments have been measured using the stopped-flow technique and Prm2−/− sperm was tested using fluorescence microscopy low levels of fluorescence could also indicate that the intracellular Ca2+ concentration in Prm2-deficient sperm is extremely low this can be excluded since treatment with ionomycin did not evoke a Ca2+ response Together with the results obtained by transmission electron microscopy (TEM) this suggests that Prm2-deficient sperm have severe plasma membrane defects Effects of Prm2-deficiency on histone-to-protamine exchange dynamics for western blot analysis the basic proteins like the protamines were isolated from precipitated DNA The fact that we could detect PRM1 in PRM2-deficient sperm suggests that PRM1 is incorporated into sperm chromatin independent of PRM2 we used CRISPR/Cas9 gene-editing to generate Prm2-deficient mice to investigate the role of PRM2 in controlling chromatin hypercondensation and fertility We demonstrate that Prm2-heterozygous mice remain fertile with sperm being morphologically and functionally indistinguishable from wildtype sperm lack of Prm2 causes infertility with severe defects in sperm head morphology and sperm motility qRT-PCR clearly demonstrates that expression of Prm1 is maintained in Prm2+/− males while only a mild decrease in protein level is observed Further, the hypothesis that physiological PRM2 protein levels are required for proper incorporation of PRM1 into sperm chromatin has to be re-visited29 since sperm of Prm2+/− and Prm2−/− males displays certain degrees of DNA-hypercondensation indicative for DNA-protamine interaction the Prm2Δ97 and Prm2Δ101 alleles were backcrossed with wildtype mice which might have affected loci on other chromosomes This clearly indicates that deletion of one Prm2 allele does not affect male reproductive performance in mice The typical apical hook-like structure of sperm heads and intact sperm motility further suggests that sperm physiology and morphology are not affected strong sperm DNA degradation observed in Prm2-deficient animals most likely prohibits successful reproduction This indicates that mice might be able to tolerate changes in the PRM1/2 ratio to some extent This would be in contrast to the situation in humans where changes of the PRM1/2 ratio are associated with reduced fertility the elevated levels of histones detected in such animals that remain bound to sperm chromatin might compensate for the lower total amount of protamines Whereas the reason for the defect in chromatin packaging is obvious the molecular mechanisms underlying the ultrastructural change in acrosomal cap formation and attachment to the nucleus need to be addressed in further studies a robust and reliable model for functional studies on protamine-induced chromatin hypercondensation during spermiogenesis These mice allow for a detailed investigation of basic regulatory mechanisms of haploid gene expression in sperm Shedding light on these molecular mechanisms is an absolute requirement for a better understanding of aberrant protamine expression in subfertile men All animal experiments were conducted according to German law of animal protection and in agreement with the approval of the local institutional animal care committees (Landesamt für Natur E14Tg2a mES cells (kind gift of Christof Niehrs Germany) were maintained on gelatinized cell culture dishes with standard ES cell medium at 37 °C and 7.5% CO2 3 × 105 cells per well were seeded onto a gelatinized 12-well-plate in media without antibiotics After 3 h cells were transfected with a 3:1 ratio of pX330: Lipofectamine2000 according to the manufacturers’ protocol (Thermo Fisher Scientific 8 h later media was changed to ES media to remove DNA-Lipofectamine complexes Products were denaturated by heating to 95 °C for 10 min re-annealed by stepwise cooling to room temperature (RT) and analyzed using the ‘SURVEYOR Mutation Detection Kit’ (Transgenomic Surviving zygotes were cultured in KSOM medium for 3 days Developing blastocysts were transferred into the uteri of pseudo-pregnant foster mice Mouse monoclonal antibodies anti-PRM1 (Hup1N) and anti-PRM2 (Hup2B) (Briar Patch Biosciences Secondary polyclonal antibodies were used as follows: rabbit anti-mouse HRP 1:1.000 (Dako Sperm were isolated by multiple incisions of the cauda followed by a swim-out in modified TYH medium65 or M2 medium Sperm count was determined using a Neubauer hemocytometer sexually mature males with an age of 2–5 months were used Animals were derived from intercrosses of the F1 generation Equal protein loading was validated by staining with Coomassie Brillant Blue G-250 Membranes were blocked in 3% nonfat dry milk powder in Tris-buffered saline with Tween20 (TBST) for 2 h at RT and probed with primary (overnight at 4 °C) and secondary (1 h at RT) antibodies in blocking solution Chemiluminescent signals were detected using ChemiDoc MP Imaging System (BioRad) after incubation of the membrane with PierceSuper Signal West Pico chemiluminescent substrate (Perbio Germany) or Westar Supernova substrate (7Bioscience sections were washed in 0.02 M PBS (pH 7.4) boiled for 20 min in sodium citrate buffer treated for 20 min with 3% H2O2 in methanol and blocked for 20 min with 5% bovine serum albumin (BSA) in PBS Incubation with the primary antibody was performed overnight at 4 °C with biotinylated goat-anti-mouse secondary antibody (DAKO) and the Vectastain ABC Kit (Vector Laboratories Immunoreaction was visualized using AEC (DAKO) sections were counterstained with hematoxylin and covered with glycerin gelatin Testis and epididymis perfused with PBS buffer (0.1 M) including 0.25% heparin followed by Yellow-Fix (2% paraformaldehyde 0.02% picric acid mixed with 2% glutaraldehyde just before usage) via the heart were immersion-fixed in Yellow-Fix for 24 h at 4 °C Smaller samples rinsed in PBS buffer (0.1 M) were then immersion-fixed in 1% osmium tetroxide at 4 °C for 2 h and rinsed in buffer again the tissue was dehydrated and embedded in Epon Ultrathin-sections were picked up on grids stained with lead-citrate (0.2%) and examined with a Zeiss EM 109 (Zeiss Data acquisition was performed with a data acquisition pad (PCI-6221; National Instruments Ca2+ signals are depicted as the percent change in fluorescence (ΔF) with respect to the mean of the first three data points recorded immediately after mixing (F0) when a stable fluorescence signal was observed The control (buffer) ΔF/F0 signal was subtracted from compound-induced signals Sperm were dried and fixed in 4% paraformaldehyde/PBS for 20 min sperm were incubated for 40 min with blocking buffer (0.5% Triton X-100 and 5% ChemiBLOCKER (Merck Millipore Sigma Aldrich) and MitoTracker Red CMXRos (1:2000 Thermo Fisher) were diluted in blocking buffer containing 0.5 mg/ml DAPI (Life Technologies) and incubated for 1 h Pictures were taken on a confocal microscope (FV1000; Olympus) Sperm motility was studied in shallow observation chambers (depth 150 μm) using an inverted microscope (IX71; Olympus) equipped as described previously65 cells were tethered to the glass surface by adjusting the BSA concentration in the buffer from 3 to 0.3 mg/ml Cells that had their head attached to the glass surface and had a free beating flagellum were selected for imaging Images were collected at 200 frames per second using a CMOS camera (Dimax; PCO Quantification of the flagellar beat was performed using custom-made programs written in Java The program identified a point on the flagellum 25 μm apart from the center of the mouse head within every time frame The flagellar beat parameters were determined within a time window of 1 s after each frame The first point in this time window was chosen as reference point and the distance between the successive points found on the flagellum and the reference point was monitored This distance varied in a sinusoid-like manner in time and the beat frequency was determined as the maxima in the Fourier spectrum Error bars represent standard deviation (SD) Statistical significance was determined by two-tailed Significance was assumed for p-values < 0.05 (*p < 0.05; **p < 0.005; ***p < 0.001) Re-visiting the Protamine-2 locus: deletion Chromatin and epigenetic regulation of animal development 1839 A model for the structure of chromatin in mammalian sperm Isolation and partial characterization of a basic protein from bovine sperm heads DNA packaging and organization in mammalian spermatozoa: comparison with somatic cells Identification of the Elemental Packing Unit of DNA in Mammalian Sperm Cells by Atomic Force Microscopy Biochemical and Biophysical Research Communications 193 Transcriptional and translational regulation of gene expression in haploid spermatids Function of sperm chromatin structural elements in fertilization and development Isolation and amino-acid sequence analysis of human sperm protamines P1 and P2 Both P1 and P2 protamine genes are expressed in mouse The protamine family of sperm nuclear proteins Mapping of PRM1 to human chromosome 16 and tight linkage of Prm-1 and Prm-2 on mouse chromosome 16 Conservation of the PRM1 –> PRM2 –> TNP2 domain Amino-acid sequences of two forms of protamine P2 Mouse protamine 2 is synthesized as a precursor whereas mouse protamine 1 is not Protamine 1: Protamine 2 stoichiometry in the sperm of eutherian mammals* The lack of protamine 2 (P2) in boar and bull spermatozoa is due to mutations within the P2 gene Expression of the rat protamine 2 gene is suppressed at the level of transcription and translation Aberrant protamine 1/protamine 2 ratios in sperm of infertile human males Detection of P2 precursors in the sperm cells of infertile patients who have reduced protamine P2 levels DNA Integrity Is Compromised in Protamine-Deficient Human Sperm DNA integrity and other sperm parameters in infertile patients Protamine 1 to protamine 2 ratio correlates with dynamic aspects of DNA fragmentation in human sperm Both protamine-1 to protamine-2 mRNA ratio and Bcl2 mRNA content in testicular spermatids and ejaculated spermatozoa discriminate between fertile and infertile men Decreased protamine-1 transcript levels in testes from infertile men The impact of sperm protamine deficiency and sperm DNA damage on human male fertility: a systematic review and meta-analysis The sperm protamine mRNA ratio as a clinical parameter to estimate the fertilizing potential of men taking part in an ART programme Sperm protamine 1/protamine 2 ratios are related to in vitro fertilization pregnancy rates and predictive of fertilization ability Effect of protamine-2 deficiency on ICSI 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1-deficient mice Proceedings of the National Academy of Sciences of the United States of America 97 Teratozoospermia in mice lacking the transition protein 2 (Tnp2) Sexual selection on protamine and transition nuclear protein expression in mouse species Selective constraints on protamine 2 in primates and rodents The effects of protamine deficiency on ultrastructure of human sperm nucleus Generation of mutant mice by pronuclear injection of circular plasmid expressing Cas9 and single guided RNA DNA targeting specificity of RNA-guided Cas9 nucleases Multiplex Genome Engineering Using CRISPR/Cas Systems Genome engineering using the CRISPR-Cas9 system NANOG promoter methylation and expression correlation during normal and malignant human germ cell development Analysis of TET expression/activity and 5mC oxidation during normal and malignant germ cell development Controlling fertilization and cAMP signaling in sperm by optogenetics Rapid Analysis of Mammalian Sperm Nuclear Proteins High resolution acrylamide gel electrophoresis of histones Archives of Biochemistry and Biophysics 130 IS Transmission of modified nucleosomes from the mouse male germline to the zygote and subsequent remodeling of paternal chromatin Sperm chromatin structure assay: its clinical use for detecting sperm DNA fragmentation in male infertility and comparisons with other techniques Development of a novel CASA system based on open source software for characterization of zebrafish sperm motility parameters Download references This study was supported by a grant from the Deutsche Forschungsgemeinschaft (DFG) to HS (SCH 503/15-1) and KS (STE 892/14-1) DW was further supported by the Bonn Excellence Cluster for “ImmunoSensation” Susi Schubert-Porth and Susi Steiner for excellent technical assistance Minerva Max Planck Research Group - Molecular Physiology Center of Advanced European Studies and Research Biomedical Research Center of the Justus-Liebig University generated and analyzed gene-edited mice (qRT-PCR recorded and analyzed sperm motility parameters were major contributors in writing the manuscript The authors declare no competing financial interests Download citation Nature Structural & Molecular Biology (2023)