Cell SystemsPub Date : 2024-04-17DOI: 10.1016/j.cels.2024.03.005
Andrea L. Higdon, Nathan H. Won, Gloria A. Brar
{"title":"Truncated protein isoforms generate diversity of protein localization and function in yeast","authors":"Andrea L. Higdon, Nathan H. Won, Gloria A. Brar","doi":"10.1016/j.cels.2024.03.005","DOIUrl":"https://doi.org/10.1016/j.cels.2024.03.005","url":null,"abstract":"<p>Genome-wide measurement of ribosome occupancy on mRNAs has enabled empirical identification of translated regions, but high-confidence detection of coding regions that overlap annotated coding regions has remained challenging. Here, we report a sensitive and robust algorithm that revealed the translation of 388 N-terminally truncated proteins in budding yeast—more than 30-fold more than previously known. We extensively experimentally validated them and defined two classes. The first class lacks large portions of the annotated protein and tends to be produced from a truncated transcript. We show that two such cases, Yap5<sup>truncation</sup> and Pus1<sup>truncation</sup>, have condition-specific regulation and distinct functions from their respective annotated isoforms. The second class of truncated protein isoforms lacks only a small region of the annotated protein and is less likely to be produced from an alternative transcript isoform. Many display different subcellular localizations than their annotated counterpart, representing a common strategy for dual localization of otherwise functionally identical proteins.</p><p>A record of this paper’s transparent peer review process is included in the <span>supplemental information</span>.</p>","PeriodicalId":54348,"journal":{"name":"Cell Systems","volume":"56 1","pages":""},"PeriodicalIF":9.3,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140636785","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}
Cell SystemsPub Date : 2024-04-08DOI: 10.1016/j.cels.2024.03.003
Joshua L. Justice, Tavis J. Reed, Brett Phelan, Todd M. Greco, Josiah E. Hutton, Ileana M. Cristea
{"title":"DNA-PK and ATM drive phosphorylation signatures that antagonistically regulate cytokine responses to herpesvirus infection or DNA damage","authors":"Joshua L. Justice, Tavis J. Reed, Brett Phelan, Todd M. Greco, Josiah E. Hutton, Ileana M. Cristea","doi":"10.1016/j.cels.2024.03.003","DOIUrl":"https://doi.org/10.1016/j.cels.2024.03.003","url":null,"abstract":"The DNA-dependent protein kinase, DNA-PK, is an essential regulator of DNA damage repair. DNA-PK-driven phosphorylation events and the activated DNA damage response (DDR) pathways are also components of antiviral intrinsic and innate immune responses. Yet, it is not clear whether and how the DNA-PK response differs between these two forms of nucleic acid stress—DNA damage and DNA virus infection. Here, we define DNA-PK substrates and the signature cellular phosphoproteome response to DNA damage or infection with the nuclear-replicating DNA herpesvirus, HSV-1. We establish that DNA-PK negatively regulates the ataxia-telangiectasia-mutated (ATM) DDR kinase during viral infection. In turn, ATM blocks the binding of DNA-PK and the nuclear DNA sensor IFI16 to viral DNA, thereby inhibiting cytokine responses. However, following DNA damage, DNA-PK enhances ATM activity, which is required for IFN-β expression. These findings demonstrate that the DDR autoregulates cytokine expression through the opposing modulation of DDR kinases.","PeriodicalId":54348,"journal":{"name":"Cell Systems","volume":"23 1","pages":""},"PeriodicalIF":9.3,"publicationDate":"2024-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140610795","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}
Cell SystemsPub Date : 2024-01-09DOI: 10.1016/j.cels.2023.12.006
Neha Cheemalavagu, Karsen E. Shoger, Yuqi M. Cao, Brandon A. Michalides, Samuel A. Botta, James R. Faeder, Rachel A. Gottschalk
{"title":"Predicting gene-level sensitivity to JAK-STAT signaling perturbation using a mechanistic-to-machine learning framework","authors":"Neha Cheemalavagu, Karsen E. Shoger, Yuqi M. Cao, Brandon A. Michalides, Samuel A. Botta, James R. Faeder, Rachel A. Gottschalk","doi":"10.1016/j.cels.2023.12.006","DOIUrl":"https://doi.org/10.1016/j.cels.2023.12.006","url":null,"abstract":"<p><span>The Janus kinase (JAK)-signal transducer and activator of transcription (STAT) pathway integrates complex cytokine signals via a limited number of molecular components, inspiring numerous efforts to clarify the diversity and specificity of STAT transcription factor function. We developed a computational framework to make global cytokine-induced gene predictions from STAT phosphorylation dynamics, modeling macrophage responses to interleukin (IL)-6 and IL-10, which signal through common STATs, but with distinct temporal dynamics and contrasting functions. Our mechanistic-to-machine learning model identified cytokine-specific genes associated with late pSTAT3 time frames and a preferential pSTAT1 reduction upon JAK2 inhibition. We predicted and validated the impact of JAK2 inhibition on gene expression, identifying genes that were sensitive or insensitive to JAK2 variation. Thus, we successfully linked STAT signaling dynamics to gene expression to support future efforts targeting pathology-associated STAT-driven gene sets. This serves as a first step in developing multi-level prediction models to understand and perturb gene expression outputs from signaling systems. A record of this paper’s transparent peer review process is included in the </span><span>supplemental information</span>.</p>","PeriodicalId":54348,"journal":{"name":"Cell Systems","volume":"25 1","pages":""},"PeriodicalIF":9.3,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139409991","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}
Cell SystemsPub Date : 2024-01-09DOI: 10.1016/j.cels.2023.12.005
Robert Kousnetsov, Jessica Bourque, Alexey Surnov, Ian Fallahee, Daniel Hawiger
{"title":"Single-cell sequencing analysis within biologically relevant dimensions","authors":"Robert Kousnetsov, Jessica Bourque, Alexey Surnov, Ian Fallahee, Daniel Hawiger","doi":"10.1016/j.cels.2023.12.005","DOIUrl":"https://doi.org/10.1016/j.cels.2023.12.005","url":null,"abstract":"<p>The currently predominant approach to transcriptomic and epigenomic single-cell analysis depends on a rigid perspective constrained by reduced dimensions and algorithmically derived and annotated clusters. Here, we developed Seqtometry (sequencing-to-measurement), a single-cell analytical strategy based on biologically relevant dimensions enabled by advanced scoring with multiple gene sets (signatures) for examination of gene expression and accessibility across various organ systems. By utilizing information only in the form of specific signatures, Seqtometry bypasses unsupervised clustering and individual annotations of clusters. Instead, Seqtometry combines qualitative and quantitative cell-type identification with specific characterization of diverse biological processes under experimental or disease conditions. Comprehensive analysis by Seqtometry of various immune cells as well as other cells from different organs and disease-induced states, including multiple myeloma and Alzheimer’s disease, surpasses corresponding cluster-based analytical output. We propose Seqtometry as a single-cell sequencing analysis approach applicable for both basic and clinical research.</p>","PeriodicalId":54348,"journal":{"name":"Cell Systems","volume":"94 1","pages":""},"PeriodicalIF":9.3,"publicationDate":"2024-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139410202","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}
Cell SystemsPub Date : 2023-12-28DOI: 10.1016/j.cels.2023.12.001
Sander K. Govers, Manuel Campos, Bhavyaa Tyagi, Géraldine Laloux, Christine Jacobs-Wagner
{"title":"Apparent simplicity and emergent robustness in the control of the Escherichia coli cell cycle","authors":"Sander K. Govers, Manuel Campos, Bhavyaa Tyagi, Géraldine Laloux, Christine Jacobs-Wagner","doi":"10.1016/j.cels.2023.12.001","DOIUrl":"https://doi.org/10.1016/j.cels.2023.12.001","url":null,"abstract":"<p>To examine how bacteria achieve robust cell proliferation across diverse conditions, we developed a method that quantifies 77 cell morphological, cell cycle, and growth phenotypes of a fluorescently labeled <em>Escherichia coli</em> strain and >800 gene deletion derivatives under multiple nutrient conditions. This approach revealed extensive phenotypic plasticity and deviating mutant phenotypes were often nutrient dependent. From this broad phenotypic landscape emerged simple and robust unifying rules (laws) that connect DNA replication initiation, nucleoid segregation, FtsZ ring formation, and cell constriction to specific aspects of cell size (volume, length, or added length) at the population level. Furthermore, completion of cell division followed the initiation of cell constriction after a constant time delay across strains and nutrient conditions, identifying cell constriction as a key control point for cell size determination. Our work provides a population-level description of the governing principles by which <em>E. coli</em> integrates cell cycle processes and growth rate with cell size to achieve its robust proliferative capability.</p><p>A record of this paper’s transparent peer review process is included in the <span>supplemental information</span>.</p>","PeriodicalId":54348,"journal":{"name":"Cell Systems","volume":"194 1","pages":""},"PeriodicalIF":9.3,"publicationDate":"2023-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139071204","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}
Cell SystemsPub Date : 2023-12-12DOI: 10.1016/j.cels.2023.11.007
Bryce M. Connors, Jaron Thompson, Sarah Ertmer, Ryan L. Clark, Brian F. Pfleger, Ophelia S. Venturelli
{"title":"Control points for design of taxonomic composition in synthetic human gut communities","authors":"Bryce M. Connors, Jaron Thompson, Sarah Ertmer, Ryan L. Clark, Brian F. Pfleger, Ophelia S. Venturelli","doi":"10.1016/j.cels.2023.11.007","DOIUrl":"https://doi.org/10.1016/j.cels.2023.11.007","url":null,"abstract":"<p>Microbial communities offer vast potential across numerous sectors but remain challenging to systematically control. We develop a two-stage approach to guide the taxonomic composition of synthetic microbiomes by precisely manipulating media components and initial species abundances. By combining high-throughput experiments and computational modeling, we demonstrate the ability to predict and design the diversity of a 10-member synthetic human gut community. We reveal that critical environmental factors governing monoculture growth can be leveraged to steer microbial communities to desired states. Furthermore, systematically varied initial abundances drive variation in community assembly and enable inference of pairwise inter-species interactions via a dynamic ecological model. These interactions are overall consistent with conditioned media experiments, demonstrating that specific perturbations to a high-richness community can provide rich information for building dynamic ecological models. This model is subsequently used to design low-richness communities that display low or high temporal taxonomic variability over an extended period. A record of this paper’s transparent peer review process is included in the <span>supplemental information</span>.</p>","PeriodicalId":54348,"journal":{"name":"Cell Systems","volume":"3 1","pages":""},"PeriodicalIF":9.3,"publicationDate":"2023-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138572885","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}
Cell SystemsPub Date : 2023-12-12DOI: 10.1016/j.cels.2023.11.006
Jingyi Wei, Peter Lotfy, Kian Faizi, Sara Baungaard, Emily Gibson, Eleanor Wang, Hannah Slabodkin, Emily Kinnaman, Sita Chandrasekaran, Hugo Kitano, Matthew G. Durrant, Connor V. Duffy, April Pawluk, Patrick D. Hsu, Silvana Konermann
{"title":"Deep learning and CRISPR-Cas13d ortholog discovery for optimized RNA targeting","authors":"Jingyi Wei, Peter Lotfy, Kian Faizi, Sara Baungaard, Emily Gibson, Eleanor Wang, Hannah Slabodkin, Emily Kinnaman, Sita Chandrasekaran, Hugo Kitano, Matthew G. Durrant, Connor V. Duffy, April Pawluk, Patrick D. Hsu, Silvana Konermann","doi":"10.1016/j.cels.2023.11.006","DOIUrl":"https://doi.org/10.1016/j.cels.2023.11.006","url":null,"abstract":"<p><span><span>Effective and precise mammalian transcriptome engineering technologies are needed to accelerate biological discovery and </span>RNA therapeutics. Despite the promise of programmable CRISPR-Cas13 </span>ribonucleases<span><span>, their utility has been hampered by an incomplete understanding of guide RNA design rules and cellular toxicity resulting from off-target or collateral </span>RNA cleavage<span>. Here, we quantified the performance of over 127,000 RfxCas13d (CasRx) guide RNAs and systematically evaluated seven machine learning models to build a guide efficiency prediction algorithm orthogonally validated across multiple human cell types. Deep learning model interpretation revealed preferred sequence motifs<span> and secondary features for highly efficient guides. We next identified and screened 46 novel Cas13d orthologs, finding that DjCas13d achieves low cellular toxicity and high specificity—even when targeting abundant transcripts in sensitive cell types, including stem cells and neurons. Our Cas13d guide efficiency model was successfully generalized to DjCas13d, illustrating the power of combining machine learning with ortholog discovery to advance RNA targeting in human cells.</span></span></span></p>","PeriodicalId":54348,"journal":{"name":"Cell Systems","volume":"24 1","pages":""},"PeriodicalIF":9.3,"publicationDate":"2023-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138572889","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}
Cell SystemsPub Date : 2023-12-06DOI: 10.1016/j.cels.2023.11.004
Johannes Textor, Franka Buytenhuijs, Dakota Rogers, Ève Mallet Gauthier, Shabaz Sultan, Inge M.N. Wortel, Kathrin Kalies, Anke Fähnrich, René Pagel, Heather J. Melichar, Jürgen Westermann, Judith N. Mandl
{"title":"Machine learning analysis of the T cell receptor repertoire identifies sequence features of self-reactivity","authors":"Johannes Textor, Franka Buytenhuijs, Dakota Rogers, Ève Mallet Gauthier, Shabaz Sultan, Inge M.N. Wortel, Kathrin Kalies, Anke Fähnrich, René Pagel, Heather J. Melichar, Jürgen Westermann, Judith N. Mandl","doi":"10.1016/j.cels.2023.11.004","DOIUrl":"https://doi.org/10.1016/j.cels.2023.11.004","url":null,"abstract":"<p>The T cell receptor (TCR) determines specificity and affinity for both foreign and self-peptides presented by the major histocompatibility complex (MHC). Although the strength of TCR interactions with self-pMHC impacts T cell function, it has been challenging to identify TCR sequence features that predict T cell fate. To discern patterns distinguishing TCRs from naive CD4<sup>+</sup> T cells with low versus high self-reactivity, we used data from 42 mice to train a machine learning (ML) algorithm that identifies population-level differences between TCR<em>β</em> sequence sets. This approach revealed that weakly self-reactive T cell populations were enriched for longer CDR3<em>β</em> regions and acidic amino acids. We tested our ML predictions of self-reactivity using retrogenic mice with fixed TCR<em>β</em> sequences. Extrapolating our analyses to independent datasets, we predicted high self-reactivity for regulatory T cells and slightly reduced self-reactivity for T cells responding to chronic infections. Our analyses suggest a potential trade-off between TCR repertoire diversity and self-reactivity. A record of this paper’s transparent peer review process is included in the <span>supplemental information</span>.</p>","PeriodicalId":54348,"journal":{"name":"Cell Systems","volume":"63 1","pages":""},"PeriodicalIF":9.3,"publicationDate":"2023-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138539110","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}
Cell SystemsPub Date : 2023-09-20Epub Date: 2023-09-08DOI: 10.1016/j.cels.2023.08.001
Noreen Wauford, Akshay Patel, Jesse Tordoff, Casper Enghuus, Andrew Jin, Jack Toppen, Melissa L Kemp, Ron Weiss
{"title":"Synthetic symmetry breaking and programmable multicellular structure formation.","authors":"Noreen Wauford, Akshay Patel, Jesse Tordoff, Casper Enghuus, Andrew Jin, Jack Toppen, Melissa L Kemp, Ron Weiss","doi":"10.1016/j.cels.2023.08.001","DOIUrl":"10.1016/j.cels.2023.08.001","url":null,"abstract":"<p><p>During development, cells undergo symmetry breaking into differentiated subpopulations that self-organize into complex structures.<sup>1</sup><sup>,</sup><sup>2</sup><sup>,</sup><sup>3</sup><sup>,</sup><sup>4</sup><sup>,</sup><sup>5</sup> However, few tools exist to recapitulate these behaviors in a controllable and coupled manner.<sup>6</sup><sup>,</sup><sup>7</sup><sup>,</sup><sup>8</sup><sup>,</sup><sup>9</sup> Here, we engineer a stochastic recombinase genetic switch tunable by small molecules to induce programmable symmetry breaking, commitment to downstream cell fates, and morphological self-organization. Inducers determine commitment probabilities, generating tunable subpopulations as a function of inducer dosage. We use this switch to control the cell-cell adhesion properties of cells committed to each fate.<sup>10</sup><sup>,</sup><sup>11</sup> We generate a wide variety of 3D morphologies from a monoclonal population and develop a computational model showing high concordance with experimental results, yielding new quantitative insights into the relationship between cell-cell adhesion strengths and downstream morphologies. We expect that programmable symmetry breaking, generating precise and tunable subpopulation ratios and coupled to structure formation, will serve as an integral component of the toolbox for complex tissue and organoid engineering.</p>","PeriodicalId":54348,"journal":{"name":"Cell Systems","volume":" ","pages":"806-818.e5"},"PeriodicalIF":9.0,"publicationDate":"2023-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10919224/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10188701","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":"The architecture of binding cooperativity between densely bound transcription factors.","authors":"Offir Lupo, Divya Krishna Kumar, Rotem Livne, Michal Chappleboim, Idan Levy, Naama Barkai","doi":"10.1016/j.cels.2023.06.010","DOIUrl":"10.1016/j.cels.2023.06.010","url":null,"abstract":"<p><p>The binding of transcription factors (TFs) along genomes is restricted to a subset of sites containing their preferred motifs. TF-binding specificity is often attributed to the co-binding of interacting TFs; however, apart from specific examples, this model remains untested. Here, we define dependencies among budding yeast TFs that localize to overlapping promoters by profiling the genome-wide consequences of co-depleting multiple TFs. We describe unidirectional interactions, revealing Msn2 as a central factor allowing TF binding at its target promoters. By contrast, no case of mutual cooperation was observed. Particularly, Msn2 retained binding at its preferred promoters upon co-depletion of fourteen similarly bound TFs. Overall, the consequences of TF co-depletions were moderate, limited to a subset of promoters, and failed to explain the role of regions outside the DNA-binding domain in directing TF-binding preferences. Our results call for re-evaluating the role of cooperative interactions in directing TF-binding preferences.</p>","PeriodicalId":54348,"journal":{"name":"Cell Systems","volume":" ","pages":"732-745.e5"},"PeriodicalIF":9.3,"publicationDate":"2023-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9974704","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}