Yiping Zou, Jiaqi Luo, Lingxi Chen, Xueying Wang, Wei Liu, Ruo Han Wang, Shuai Cheng Li
{"title":"Identifying T-cell clubs by embracing the local harmony between TCR and gene expressions.","authors":"Yiping Zou, Jiaqi Luo, Lingxi Chen, Xueying Wang, Wei Liu, Ruo Han Wang, Shuai Cheng Li","doi":"10.1038/s44320-024-00070-5","DOIUrl":"10.1038/s44320-024-00070-5","url":null,"abstract":"<p><p>T cell receptors (TCR) and gene expression provide two complementary and essential aspects in T cell understanding, yet their diversity presents challenges in integrative analysis. We introduce TCRclub, a novel method integrating single-cell RNA sequencing data and single-cell TCR sequencing data using local harmony to identify functionally similar T cell groups, termed 'clubs'. We applied TCRclub to 298,106 T cells across seven datasets encompassing various diseases. First, TCRclub outperforms the state-of-the-art methods in clustering T cells on a dataset with over 400 verified peptide-major histocompatibility complex categories. Second, TCRclub reveals a transition from activated to exhausted T cells in cholangiocarcinoma patients. Third, TCRclub discovered the pathways that could intervene in response to anti-PD-1 therapy for patients with basal cell carcinoma by analyzing the pre-treatment and post-treatment samples. Furthermore, TCRclub unveiled different T-cell responses and gene patterns at different severity levels in patients with COVID-19. Hence, TCRclub aids in developing more effective immunotherapeutic strategies for cancer and infectious diseases.</p>","PeriodicalId":18906,"journal":{"name":"Molecular Systems Biology","volume":null,"pages":null},"PeriodicalIF":8.5,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142576294","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Martin Giera, Aries Aisporna, Winnie Uritboonthai, Linh Hoang, Rico J E Derks, Kara M Joseph, Erin S Baker, Gary Siuzdak
{"title":"XCMS-METLIN: data-driven metabolite, lipid, and chemical analysis.","authors":"Martin Giera, Aries Aisporna, Winnie Uritboonthai, Linh Hoang, Rico J E Derks, Kara M Joseph, Erin S Baker, Gary Siuzdak","doi":"10.1038/s44320-024-00063-4","DOIUrl":"10.1038/s44320-024-00063-4","url":null,"abstract":"","PeriodicalId":18906,"journal":{"name":"Molecular Systems Biology","volume":null,"pages":null},"PeriodicalIF":8.5,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11535300/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142291590","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Bradley W Biggs, Morgan N Price, Dexter Lai, Jasmine Escobedo, Yuridia Fortanel, Yolanda Y Huang, Kyoungmin Kim, Valentine V Trotter, Jennifer V Kuehl, Lauren M Lui, Romy Chakraborty, Adam M Deutschbauer, Adam P Arkin
{"title":"High-throughput protein characterization by complementation using DNA barcoded fragment libraries.","authors":"Bradley W Biggs, Morgan N Price, Dexter Lai, Jasmine Escobedo, Yuridia Fortanel, Yolanda Y Huang, Kyoungmin Kim, Valentine V Trotter, Jennifer V Kuehl, Lauren M Lui, Romy Chakraborty, Adam M Deutschbauer, Adam P Arkin","doi":"10.1038/s44320-024-00068-z","DOIUrl":"10.1038/s44320-024-00068-z","url":null,"abstract":"<p><p>Our ability to predict, control, or design biological function is fundamentally limited by poorly annotated gene function. This can be particularly challenging in non-model systems. Accordingly, there is motivation for new high-throughput methods for accurate functional annotation. Here, we used complementation of auxotrophs and DNA barcode sequencing (Coaux-Seq) to enable high-throughput characterization of protein function. Fragment libraries from eleven genetically diverse bacteria were tested in twenty different auxotrophic strains of Escherichia coli to identify genes that complement missing biochemical activity. We recovered 41% of expected hits, with effectiveness ranging per source genome, and observed success even with distant E. coli relatives like Bacillus subtilis and Bacteroides thetaiotaomicron. Coaux-Seq provided the first experimental validation for 53 proteins, of which 11 are less than 40% identical to an experimentally characterized protein. Among the unexpected function identified was a sulfate uptake transporter, an O-succinylhomoserine sulfhydrylase for methionine synthesis, and an aminotransferase. We also identified instances of cross-feeding wherein protein overexpression and nearby non-auxotrophic strains enabled growth. Altogether, Coaux-Seq's utility is demonstrated, with future applications in ecology, health, and engineering.</p>","PeriodicalId":18906,"journal":{"name":"Molecular Systems Biology","volume":null,"pages":null},"PeriodicalIF":8.5,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11535334/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142391857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Correction of a widespread bias in pooled chemical genomics screens improves their interpretability.","authors":"Lili M Kim, Horia Todor, Carol A Gross","doi":"10.1038/s44320-024-00069-y","DOIUrl":"10.1038/s44320-024-00069-y","url":null,"abstract":"<p><p>Chemical genomics is a powerful and increasingly accessible technique to probe gene function, gene-gene interactions, and antibiotic synergies and antagonisms. Indeed, multiple large-scale pooled datasets in diverse organisms have been published. Here, we identify an artifact arising from uncorrected differences in the number of cell doublings between experiments within such datasets. We demonstrate that this artifact is widespread, show how it causes spurious gene-gene and drug-drug correlations, and present a simple but effective post hoc method for removing its effects. Using several published datasets, we demonstrate that this correction removes spurious correlations between genes and conditions, improving data interpretability and revealing new biological insights. Finally, we determine experimental factors that predispose a dataset for this artifact and suggest a set of experimental and computational guidelines for performing pooled chemical genomics experiments that will maximize the potential of this powerful technique.</p>","PeriodicalId":18906,"journal":{"name":"Molecular Systems Biology","volume":null,"pages":null},"PeriodicalIF":8.5,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11535069/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142350452","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Matteo Mori, Zhongge Zhang, Amir Banaei-Esfahani, Jean-Benoît Lalanne, Hiroyuki Okano, Ben C Collins, Alexander Schmidt, Olga T Schubert, Deok-Sun Lee, Gene-Wei Li, Ruedi Aebersold, Terence Hwa, Christina Ludwig
{"title":"Author Correction: From coarse to fine: the absolute Escherichia coli proteome under diverse growth conditions.","authors":"Matteo Mori, Zhongge Zhang, Amir Banaei-Esfahani, Jean-Benoît Lalanne, Hiroyuki Okano, Ben C Collins, Alexander Schmidt, Olga T Schubert, Deok-Sun Lee, Gene-Wei Li, Ruedi Aebersold, Terence Hwa, Christina Ludwig","doi":"10.1038/s44320-024-00062-5","DOIUrl":"10.1038/s44320-024-00062-5","url":null,"abstract":"","PeriodicalId":18906,"journal":{"name":"Molecular Systems Biology","volume":null,"pages":null},"PeriodicalIF":8.5,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11535196/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142365857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Prediction of the 3D cancer genome from whole-genome sequencing using InfoHiC.","authors":"Yeonghun Lee, Sung-Hye Park, Hyunju Lee","doi":"10.1038/s44320-024-00065-2","DOIUrl":"10.1038/s44320-024-00065-2","url":null,"abstract":"<p><p>The 3D genome prediction in cancer is crucial for uncovering the impact of structural variations (SVs) on tumorigenesis, especially when they are present in noncoding regions. We present InfoHiC, a systemic framework for predicting the 3D cancer genome directly from whole-genome sequencing (WGS). InfoHiC utilizes contig-specific copy number encoding on the SV contig assembly, and performs a contig-to-total Hi-C conversion for the cancer Hi-C prediction from multiple SV contigs. We showed that InfoHiC can predict 3D genome folding from all types of SVs using breast cancer cell line data. We applied it to WGS data of patients with breast cancer and pediatric patients with medulloblastoma, and identified neo topologically associating domains. For breast cancer, we discovered super-enhancer hijacking events associated with oncogenic overexpression and poor survival outcomes. For medulloblastoma, we found SVs in noncoding regions that caused super-enhancer hijacking events of medulloblastoma driver genes (GFI1, GFI1B, and PRDM6). In addition, we provide trained models for cancer Hi-C prediction from WGS at https://github.com/dmcb-gist/InfoHiC , uncovering the impacts of SVs in cancer patients and revealing novel therapeutic targets.</p>","PeriodicalId":18906,"journal":{"name":"Molecular Systems Biology","volume":null,"pages":null},"PeriodicalIF":8.5,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11535030/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142350453","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Andrew J Sweatt, Cameron D Griffiths, Sarah M Groves, B Bishal Paudel, Lixin Wang, David F Kashatus, Kevin A Janes
{"title":"Proteome-wide copy-number estimation from transcriptomics.","authors":"Andrew J Sweatt, Cameron D Griffiths, Sarah M Groves, B Bishal Paudel, Lixin Wang, David F Kashatus, Kevin A Janes","doi":"10.1038/s44320-024-00064-3","DOIUrl":"10.1038/s44320-024-00064-3","url":null,"abstract":"<p><p>Protein copy numbers constrain systems-level properties of regulatory networks, but proportional proteomic data remain scarce compared to RNA-seq. We related mRNA to protein statistically using best-available data from quantitative proteomics and transcriptomics for 4366 genes in 369 cell lines. The approach starts with a protein's median copy number and hierarchically appends mRNA-protein and mRNA-mRNA dependencies to define an optimal gene-specific model linking mRNAs to protein. For dozens of cell lines and primary samples, these protein inferences from mRNA outmatch stringent null models, a count-based protein-abundance repository, empirical mRNA-to-protein ratios, and a proteogenomic DREAM challenge winner. The optimal mRNA-to-protein relationships capture biological processes along with hundreds of known protein-protein complexes, suggesting mechanistic relationships. We use the method to identify a viral-receptor abundance threshold for coxsackievirus B3 susceptibility from 1489 systems-biology infection models parameterized by protein inference. When applied to 796 RNA-seq profiles of breast cancer, inferred copy-number estimates collectively re-classify 26-29% of luminal tumors. By adopting a gene-centered perspective of mRNA-protein covariation across different biological contexts, we achieve accuracies comparable to the technical reproducibility of contemporary proteomics.</p>","PeriodicalId":18906,"journal":{"name":"Molecular Systems Biology","volume":null,"pages":null},"PeriodicalIF":8.5,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11535397/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142350454","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Rajani Kanth Gudipati, Dimos Gaidatzis, Jan Seebacher, Sandra Muehlhaeusser, Georg Kempf, Simone Cavadini, Daniel Hess, Charlotte Soneson, Helge Großhans
{"title":"Deep quantification of substrate turnover defines protease subsite cooperativity.","authors":"Rajani Kanth Gudipati, Dimos Gaidatzis, Jan Seebacher, Sandra Muehlhaeusser, Georg Kempf, Simone Cavadini, Daniel Hess, Charlotte Soneson, Helge Großhans","doi":"10.1038/s44320-024-00071-4","DOIUrl":"https://doi.org/10.1038/s44320-024-00071-4","url":null,"abstract":"<p><p>Substrate specificity determines protease functions in physiology and in clinical and biotechnological applications, yet quantitative cleavage information is often unavailable, biased, or limited to a small number of events. Here, we develop qPISA (quantitative Protease specificity Inference from Substrate Analysis) to study Dipeptidyl Peptidase Four (DPP4), a key regulator of blood glucose levels. We use mass spectrometry to quantify >40,000 peptides from a complex, commercially available peptide mixture. By analyzing changes in substrate levels quantitatively instead of focusing on qualitative product identification through a binary classifier, we can reveal cooperative interactions within DPP4's active pocket and derive a sequence motif that predicts activity quantitatively. qPISA distinguishes DPP4 from the related C. elegans DPF-3 (a DPP8/9-orthologue), and we relate the differences to the structural features of the two enzymes. We demonstrate that qPISA can direct protein engineering efforts like the stabilization of GLP-1, a key DPP4 substrate used in the treatment of diabetes and obesity. Thus, qPISA offers a versatile approach for profiling protease and especially exopeptidase specificity, facilitating insight into enzyme mechanisms and biotechnological and clinical applications.</p>","PeriodicalId":18906,"journal":{"name":"Molecular Systems Biology","volume":null,"pages":null},"PeriodicalIF":8.5,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142522489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Elisabet Frutos-Grilo, Yamile Ana, Javier Gonzalez-de Miguel, Marcel Cardona-I-Collado, Irene Rodriguez-Arce, Luis Serrano
{"title":"Bacterial live therapeutics for human diseases.","authors":"Elisabet Frutos-Grilo, Yamile Ana, Javier Gonzalez-de Miguel, Marcel Cardona-I-Collado, Irene Rodriguez-Arce, Luis Serrano","doi":"10.1038/s44320-024-00067-0","DOIUrl":"https://doi.org/10.1038/s44320-024-00067-0","url":null,"abstract":"<p><p>The genomic revolution has fueled rapid progress in synthetic and systems biology, opening up new possibilities for using live biotherapeutic products (LBP) to treat, attenuate or prevent human diseases. Among LBP, bacteria-based therapies are particularly promising due to their ability to colonize diverse human tissues, modulate the immune system and secrete or deliver complex biological products. These bacterial LBP include engineered pathogenic species designed to target specific diseases, and microbiota species that promote microbial balance and immune system homeostasis, either through local administration or the gut-body axes. This review focuses on recent advancements in preclinical and clinical trials of bacteria-based LBP, highlighting both on-site and long-reaching strategies.</p>","PeriodicalId":18906,"journal":{"name":"Molecular Systems Biology","volume":null,"pages":null},"PeriodicalIF":8.5,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142504457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}