Luciana A Castellano, Ryan J McNamara, Horacio M Pallarés, Andrea V Gamarnik, Diego E Alvarez, Ariel A Bazzini
{"title":"Dengue virus preferentially uses human and mosquito non-optimal codons.","authors":"Luciana A Castellano, Ryan J McNamara, Horacio M Pallarés, Andrea V Gamarnik, Diego E Alvarez, Ariel A Bazzini","doi":"10.1038/s44320-024-00052-7","DOIUrl":"10.1038/s44320-024-00052-7","url":null,"abstract":"<p><p>Codon optimality refers to the effect that codon composition has on messenger RNA (mRNA) stability and translation level and implies that synonymous codons are not silent from a regulatory point of view. Here, we investigated the adaptation of virus genomes to the host optimality code using mosquito-borne dengue virus (DENV) as a model. We demonstrated that codon optimality exists in mosquito cells and showed that DENV preferentially uses nonoptimal (destabilizing) codons and avoids codons that are defined as optimal (stabilizing) in either human or mosquito cells. Human genes enriched in the codons preferentially and frequently used by DENV are upregulated during infection, and so is the tRNA decoding the nonoptimal and DENV preferentially used codon for arginine. We found that adaptation during single-host passaging in human or mosquito cells results in the selection of synonymous mutations towards DENV's preferred nonoptimal codons that increase virus fitness. Finally, our analyses revealed that hundreds of viruses preferentially use nonoptimal codons, with those infecting a single host displaying an even stronger bias, suggesting that host-pathogen interaction shapes virus-synonymous codon choice.</p>","PeriodicalId":18906,"journal":{"name":"Molecular Systems Biology","volume":null,"pages":null},"PeriodicalIF":8.5,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11450187/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141748614","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}
Chengyu Zhang, Benjamín J Sánchez, Feiran Li, Cheng Wei Quan Eiden, William T Scott, Ulf W Liebal, Lars M Blank, Hendrik G Mengers, Mihail Anton, Albert Tafur Rangel, Sebastián N Mendoza, Lixin Zhang, Jens Nielsen, Hongzhong Lu, Eduard J Kerkhoven
{"title":"Yeast9: a consensus genome-scale metabolic model for S. cerevisiae curated by the community.","authors":"Chengyu Zhang, Benjamín J Sánchez, Feiran Li, Cheng Wei Quan Eiden, William T Scott, Ulf W Liebal, Lars M Blank, Hendrik G Mengers, Mihail Anton, Albert Tafur Rangel, Sebastián N Mendoza, Lixin Zhang, Jens Nielsen, Hongzhong Lu, Eduard J Kerkhoven","doi":"10.1038/s44320-024-00060-7","DOIUrl":"10.1038/s44320-024-00060-7","url":null,"abstract":"<p><p>Genome-scale metabolic models (GEMs) can facilitate metabolism-focused multi-omics integrative analysis. Since Yeast8, the yeast-GEM of Saccharomyces cerevisiae, published in 2019, has been continuously updated by the community. This has increased the quality and scope of the model, culminating now in Yeast9. To evaluate its predictive performance, we generated 163 condition-specific GEMs constrained by single-cell transcriptomics from osmotic pressure or reference conditions. Comparative flux analysis showed that yeast adapting to high osmotic pressure benefits from upregulating fluxes through central carbon metabolism. Furthermore, combining Yeast9 with proteomics revealed metabolic rewiring underlying its preference for nitrogen sources. Lastly, we created strain-specific GEMs (ssGEMs) constrained by transcriptomics for 1229 mutant strains. Well able to predict the strains' growth rates, fluxomics from those large-scale ssGEMs outperformed transcriptomics in predicting functional categories for all studied genes in machine learning models. Based on those findings we anticipate that Yeast9 will continue to empower systems biology studies of yeast metabolism.</p>","PeriodicalId":18906,"journal":{"name":"Molecular Systems Biology","volume":null,"pages":null},"PeriodicalIF":8.5,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11450192/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141971483","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}
Payam Ghiaci, Paula Jouhten, Nikolay Martyushenko, Helena Roca-Mesa, Jennifer Vázquez, Dimitrios Konstantinidis, Simon Stenberg, Sergej Andrejev, Kristina Grkovska, Albert Mas, Gemma Beltran, Eivind Almaas, Kiran R Patil, Jonas Warringer
{"title":"Highly parallelized laboratory evolution of wine yeasts for enhanced metabolic phenotypes.","authors":"Payam Ghiaci, Paula Jouhten, Nikolay Martyushenko, Helena Roca-Mesa, Jennifer Vázquez, Dimitrios Konstantinidis, Simon Stenberg, Sergej Andrejev, Kristina Grkovska, Albert Mas, Gemma Beltran, Eivind Almaas, Kiran R Patil, Jonas Warringer","doi":"10.1038/s44320-024-00059-0","DOIUrl":"10.1038/s44320-024-00059-0","url":null,"abstract":"<p><p>Adaptive Laboratory Evolution (ALE) of microorganisms can improve the efficiency of sustainable industrial processes important to the global economy. However, stochasticity and genetic background effects often lead to suboptimal outcomes during laboratory evolution. Here we report an ALE platform to circumvent these shortcomings through parallelized clonal evolution at an unprecedented scale. Using this platform, we evolved 10<sup>4</sup> yeast populations in parallel from many strains for eight desired wine fermentation-related traits. Expansions of both ALE replicates and lineage numbers broadened the evolutionary search spectrum leading to improved wine yeasts unencumbered by unwanted side effects. At the genomic level, evolutionary gains in metabolic characteristics often coincided with distinct chromosome amplifications and the emergence of side-effect syndromes that were characteristic of each selection niche. Several high-performing ALE strains exhibited desired wine fermentation kinetics when tested in larger liquid cultures, supporting their suitability for application. More broadly, our high-throughput ALE platform opens opportunities for rapid optimization of microbes which otherwise could take many years to accomplish.</p>","PeriodicalId":18906,"journal":{"name":"Molecular Systems Biology","volume":null,"pages":null},"PeriodicalIF":8.5,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11450223/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142036444","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":"Tissue-aware interpretation of genetic variants advances the etiology of rare diseases.","authors":"Chanan M Argov,Ariel Shneyour,Juman Jubran,Eric Sabag,Avigdor Mansbach,Yair Sepunaru,Emmi Filtzer,Gil Gruber,Miri Volozhinsky,Yuval Yogev,Ohad Birk,Vered Chalifa-Caspi,Lior Rokach,Esti Yeger-Lotem","doi":"10.1038/s44320-024-00061-6","DOIUrl":"https://doi.org/10.1038/s44320-024-00061-6","url":null,"abstract":"Pathogenic variants underlying Mendelian diseases often disrupt the normal physiology of a few tissues and organs. However, variant effect prediction tools that aim to identify pathogenic variants are typically oblivious to tissue contexts. Here we report a machine-learning framework, denoted \"Tissue Risk Assessment of Causality by Expression for variants\" (TRACEvar, https://netbio.bgu.ac.il/TRACEvar/ ), that offers two advancements. First, TRACEvar predicts pathogenic variants that disrupt the normal physiology of specific tissues. This was achieved by creating 14 tissue-specific models that were trained on over 14,000 variants and combined 84 attributes of genetic variants with 495 attributes derived from tissue omics. TRACEvar outperformed 10 well-established and tissue-oblivious variant effect prediction tools. Second, the resulting models are interpretable, thereby illuminating variants' mode of action. Application of TRACEvar to variants of 52 rare-disease patients highlighted pathogenicity mechanisms and relevant disease processes. Lastly, the interpretation of all tissue models revealed that top-ranking determinants of pathogenicity included attributes of disease-affected tissues, particularly cellular process activities. Collectively, these results show that tissue contexts and interpretable machine-learning models can greatly enhance the etiology of rare diseases.","PeriodicalId":18906,"journal":{"name":"Molecular Systems Biology","volume":null,"pages":null},"PeriodicalIF":9.9,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142259216","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}
{"title":"Rescuing error control in crosslinking mass spectrometry.","authors":"Lutz Fischer, Juri Rappsilber","doi":"10.1038/s44320-024-00057-2","DOIUrl":"10.1038/s44320-024-00057-2","url":null,"abstract":"<p><p>Crosslinking mass spectrometry is a powerful tool to study protein-protein interactions under native or near-native conditions in complex mixtures. Through novel search controls, we show how biassing results towards likely correct proteins can subtly undermine error estimation of crosslinks, with significant consequences. Without adjustments to address this issue, we have misidentified an average of 260 interspecies protein-protein interactions across 16 analyses in which we synthetically mixed data of different species, misleadingly suggesting profound biological connections that do not exist. We also demonstrate how data analysis procedures can be tested and refined to restore the integrity of the decoy-false positive relationship, a crucial element for reliably identifying protein-protein interactions.</p>","PeriodicalId":18906,"journal":{"name":"Molecular Systems Biology","volume":null,"pages":null},"PeriodicalIF":8.5,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11368935/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141879114","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}
Madison T Wright, Bibek Timalsina, Valeria Garcia Lopez, Jake N Hermanson, Sarah Garcia, Lars Plate
{"title":"Time-resolved interactome profiling deconvolutes secretory protein quality control dynamics.","authors":"Madison T Wright, Bibek Timalsina, Valeria Garcia Lopez, Jake N Hermanson, Sarah Garcia, Lars Plate","doi":"10.1038/s44320-024-00058-1","DOIUrl":"10.1038/s44320-024-00058-1","url":null,"abstract":"<p><p>Many cellular processes are governed by protein-protein interactions that require tight spatial and temporal regulation. Accordingly, it is necessary to understand the dynamics of these interactions to fully comprehend and elucidate cellular processes and pathological disease states. To map de novo protein-protein interactions with time resolution at an organelle-wide scale, we developed a quantitative mass spectrometry method, time-resolved interactome profiling (TRIP). We apply TRIP to elucidate aberrant protein interaction dynamics that lead to the protein misfolding disease congenital hypothyroidism. We deconvolute altered temporal interactions of the thyroid hormone precursor thyroglobulin with pathways implicated in hypothyroidism pathophysiology, such as Hsp70-/90-assisted folding, disulfide/redox processing, and N-glycosylation. Functional siRNA screening identified VCP and TEX264 as key protein degradation components whose inhibition selectively rescues mutant prohormone secretion. Ultimately, our results provide novel insight into the temporal coordination of protein homeostasis, and our TRIP method should find broad applications in investigating protein-folding diseases and cellular processes.</p>","PeriodicalId":18906,"journal":{"name":"Molecular Systems Biology","volume":null,"pages":null},"PeriodicalIF":8.5,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11369088/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141893815","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":"Evolution and stability of complex microbial communities driven by trade-offs.","authors":"Yanqing Huang, Avik Mukherjee, Severin Schink, Nina Catherine Benites, Markus Basan","doi":"10.1038/s44320-024-00051-8","DOIUrl":"10.1038/s44320-024-00051-8","url":null,"abstract":"<p><p>Microbial communities are ubiquitous in nature and play an important role in ecology and human health. Cross-feeding is thought to be core to microbial communities, though it remains unclear precisely why it emerges. Why have multi-species microbial communities evolved in many contexts and what protects microbial consortia from invasion? Here, we review recent insights into the emergence and stability of coexistence in microbial communities. A particular focus is the long-term evolutionary stability of coexistence, as observed for microbial communities that spontaneously evolved in the E. coli long-term evolution experiment (LTEE). We analyze these findings in the context of recent work on trade-offs between competing microbial objectives, which can constitute a mechanistic basis for the emergence of coexistence. Coexisting communities, rather than monocultures of the 'fittest' single strain, can form stable endpoints of evolutionary trajectories. Hence, the emergence of coexistence might be an obligatory outcome in the evolution of microbial communities. This implies that rather than embodying fragile metastable configurations, some microbial communities can constitute formidable ecosystems that are difficult to disrupt.</p>","PeriodicalId":18906,"journal":{"name":"Molecular Systems Biology","volume":null,"pages":null},"PeriodicalIF":8.5,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11369148/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141498464","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}
Johanna Kliche, Leandro Simonetti, Izabella Krystkowiak, Hanna Kuss, Marcel Diallo, Emma Rask, Jakob Nilsson, Norman E Davey, Ylva Ivarsson
{"title":"Proteome-scale characterisation of motif-based interactome rewiring by disease mutations.","authors":"Johanna Kliche, Leandro Simonetti, Izabella Krystkowiak, Hanna Kuss, Marcel Diallo, Emma Rask, Jakob Nilsson, Norman E Davey, Ylva Ivarsson","doi":"10.1038/s44320-024-00055-4","DOIUrl":"10.1038/s44320-024-00055-4","url":null,"abstract":"<p><p>Whole genome and exome sequencing are reporting on hundreds of thousands of missense mutations. Taking a pan-disease approach, we explored how mutations in intrinsically disordered regions (IDRs) break or generate protein interactions mediated by short linear motifs. We created a peptide-phage display library tiling ~57,000 peptides from the IDRs of the human proteome overlapping 12,301 single nucleotide variants associated with diverse phenotypes including cancer, metabolic diseases and neurological diseases. By screening 80 human proteins, we identified 366 mutation-modulated interactions, with half of the mutations diminishing binding, and half enhancing binding or creating novel interaction interfaces. The effects of the mutations were confirmed by affinity measurements. In cellular assays, the effects of motif-disruptive mutations were validated, including loss of a nuclear localisation signal in the cell division control protein CDC45 by a mutation associated with Meier-Gorlin syndrome. The study provides insights into how disease-associated mutations may perturb and rewire the motif-based interactome.</p>","PeriodicalId":18906,"journal":{"name":"Molecular Systems Biology","volume":null,"pages":null},"PeriodicalIF":8.5,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11369174/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141620413","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}
Aidan Flynn, Sebastian M Waszak, Joachim Weischenfeldt
{"title":"Somatic CpG hypermutation is associated with mismatch repair deficiency in cancer.","authors":"Aidan Flynn, Sebastian M Waszak, Joachim Weischenfeldt","doi":"10.1038/s44320-024-00054-5","DOIUrl":"10.1038/s44320-024-00054-5","url":null,"abstract":"<p><p>Somatic hypermutation in cancer has gained momentum with the increased use of tumour mutation burden as a biomarker for immune checkpoint inhibitors. Spontaneous deamination of 5-methylcytosine to thymine at CpG dinucleotides is one of the most ubiquitous endogenous mutational processes in normal and cancer cells. Here, we performed a systematic investigation of somatic CpG hypermutation at a pan-cancer level. We studied 30,191 cancer patients and 103 cancer types and developed an algorithm to identify somatic CpG hypermutation. Across cancer types, we observed the highest prevalence in paediatric leukaemia (3.5%), paediatric high-grade glioma (1.7%), and colorectal cancer (1%). We discovered germline variants and somatic mutations in the mismatch repair complex MutSα (MSH2-MSH6) as genetic drivers of somatic CpG hypermutation in cancer, which frequently converged on CpG sites and TP53 driver mutations. We further observe an association between somatic CpG hypermutation and response to immune checkpoint inhibitors. Overall, our study identified novel cancer types that display somatic CpG hypermutation, strong association with MutSα-deficiency, and potential utility in cancer immunotherapy.</p>","PeriodicalId":18906,"journal":{"name":"Molecular Systems Biology","volume":null,"pages":null},"PeriodicalIF":8.5,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11369196/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141724009","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}
Stefanie Luecke, Xiaolu Guo, Katherine M Sheu, Apeksha Singh, Sarina C Lowe, Minhao Han, Jessica Diaz, Francisco Lopes, Roy Wollman, Alexander Hoffmann
{"title":"Dynamical and combinatorial coding by MAPK p38 and NFκB in the inflammatory response of macrophages.","authors":"Stefanie Luecke, Xiaolu Guo, Katherine M Sheu, Apeksha Singh, Sarina C Lowe, Minhao Han, Jessica Diaz, Francisco Lopes, Roy Wollman, Alexander Hoffmann","doi":"10.1038/s44320-024-00047-4","DOIUrl":"10.1038/s44320-024-00047-4","url":null,"abstract":"<p><p>Macrophages sense pathogens and orchestrate specific immune responses. Stimulus specificity is thought to be achieved through combinatorial and dynamical coding by signaling pathways. While NFκB dynamics are known to encode stimulus information, dynamical coding in other signaling pathways and their combinatorial coordination remain unclear. Here, we established live-cell microscopy to investigate how NFκB and p38 dynamics interface in stimulated macrophages. Information theory and machine learning revealed that p38 dynamics distinguish cytokine TNF from pathogen-associated molecular patterns and high doses from low, but contributed little to information-rich NFκB dynamics when both pathways are considered. This suggests that immune response genes benefit from decoding immune signaling dynamics or combinatorics, but not both. We found that the heterogeneity of the two pathways is surprisingly uncorrelated. Mathematical modeling revealed potential sources of uncorrelated heterogeneity in the branched pathway network topology and predicted it to drive gene expression variability. Indeed, genes dependent on both p38 and NFκB showed high scRNAseq variability and bimodality. These results identify combinatorial signaling as a mechanism to restrict NFκB-AND-p38-responsive inflammatory cytokine expression to few cells.</p>","PeriodicalId":18906,"journal":{"name":"Molecular Systems Biology","volume":null,"pages":null},"PeriodicalIF":8.5,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11297158/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141317837","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}