Cell Systems最新文献_第2页

DNA-PK and ATM drive phosphorylation signatures that antagonistically regulate cytokine responses to herpesvirus infection or DNA damage DNA-PK 和 ATM 驱动的磷酸化特征可拮抗地调节细胞因子对疱疹病毒感染或 DNA 损伤的反应

IF 9.3 1区生物学

Cell Systems Pub Date : 2024-04-08 DOI: 10.1016/j.cels.2024.03.003

Joshua L. Justice, Tavis J. Reed, Brett Phelan, Todd M. Greco, Josiah E. Hutton, Ileana M. Cristea

引用次数: 0

Predicting gene-level sensitivity to JAK-STAT signaling perturbation using a mechanistic-to-machine learning framework 利用从机制到机器的学习框架预测基因水平对JAK-STAT信号扰动的敏感性

IF 9.3 1区生物学

Cell Systems Pub Date : 2024-01-09 DOI: 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":"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 supplemental information.","PeriodicalId":54348,"journal":{"name":"Cell Systems","volume":null,"pages":null},"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}

引用次数: 0

Single-cell sequencing analysis within biologically relevant dimensions 在生物相关维度内进行单细胞测序分析

IF 9.3 1区生物学

Cell Systems Pub Date : 2024-01-09 DOI: 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":"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.","PeriodicalId":54348,"journal":{"name":"Cell Systems","volume":null,"pages":null},"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}

引用次数: 0

Apparent simplicity and emergent robustness in the control of the Escherichia coli cell cycle 控制大肠杆菌细胞周期的显性简单性和显性稳健性

IF 9.3 1区生物学

Cell Systems Pub Date : 2023-12-28 DOI: 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":"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 Escherichia coli 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 E. coli integrates cell cycle processes and growth rate with cell size to achieve its robust proliferative capability.A record of this paper’s transparent peer review process is included in the supplemental information.","PeriodicalId":54348,"journal":{"name":"Cell Systems","volume":null,"pages":null},"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}

引用次数: 0

Control points for design of taxonomic composition in synthetic human gut communities 设计合成人类肠道群落分类组成的控制点

IF 9.3 1区生物学

Cell Systems Pub Date : 2023-12-12 DOI: 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":"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 supplemental information.","PeriodicalId":54348,"journal":{"name":"Cell Systems","volume":null,"pages":null},"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}

引用次数: 0

Deep learning and CRISPR-Cas13d ortholog discovery for optimized RNA targeting 深度学习和 CRISPR-Cas13d 同源物发现，优化 RNA 靶向

IF 9.3 1区生物学

Cell Systems Pub Date : 2023-12-12 DOI: 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":"Effective and precise mammalian transcriptome engineering technologies are needed to accelerate biological discovery and RNA therapeutics. Despite the promise of programmable CRISPR-Cas13 ribonucleases, their utility has been hampered by an incomplete understanding of guide RNA design rules and cellular toxicity resulting from off-target or collateral RNA cleavage. 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 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.","PeriodicalId":54348,"journal":{"name":"Cell Systems","volume":null,"pages":null},"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}

引用次数: 0

Machine learning analysis of the T cell receptor repertoire identifies sequence features of self-reactivity T细胞受体库的机器学习分析确定了自反应性的序列特征

IF 9.3 1区生物学

Cell Systems Pub Date : 2023-12-06 DOI: 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":"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+ 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 TCRβ sequence sets. This approach revealed that weakly self-reactive T cell populations were enriched for longer CDR3β regions and acidic amino acids. We tested our ML predictions of self-reactivity using retrogenic mice with fixed TCRβ 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 supplemental information.","PeriodicalId":54348,"journal":{"name":"Cell Systems","volume":null,"pages":null},"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}

引用次数: 0

Synthetic symmetry breaking and programmable multicellular structure formation. 合成对称性破坏和可编程多细胞结构形成。

IF 9.3 1区生物学

Cell Systems Pub Date : 2023-09-20 Epub Date: 2023-09-08 DOI: 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":"During development, cells undergo symmetry breaking into differentiated subpopulations that self-organize into complex structures.1,2,3,4,5 However, few tools exist to recapitulate these behaviors in a controllable and coupled manner.6,7,8,9 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.10,11 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.","PeriodicalId":54348,"journal":{"name":"Cell Systems","volume":null,"pages":null},"PeriodicalIF":9.3,"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}

引用次数: 0

The architecture of binding cooperativity between densely bound transcription factors. 紧密结合的转录因子之间结合协同性的结构。

IF 9.3 1区生物学

Cell Systems Pub Date : 2023-09-20 Epub Date: 2023-07-31 DOI: 10.1016/j.cels.2023.06.010

Offir Lupo, Divya Krishna Kumar, Rotem Livne, Michal Chappleboim, Idan Levy, Naama Barkai

引用次数: 2

A proteogenomics data-driven knowledge base of human cancer. 人类癌症的蛋白基因组学数据驱动知识库。

IF 9.3 1区生物学

Cell Systems Pub Date : 2023-09-20 Epub Date: 2023-08-23 DOI: 10.1016/j.cels.2023.07.007

Yuxing Liao, Sara R Savage, Yongchao Dou, Zhiao Shi, Xinpei Yi, Wen Jiang, Jonathan T Lei, Bing Zhang

{"title":"A proteogenomics data-driven knowledge base of human cancer.","authors":"Yuxing Liao, Sara R Savage, Yongchao Dou, Zhiao Shi, Xinpei Yi, Wen Jiang, Jonathan T Lei, Bing Zhang","doi":"10.1016/j.cels.2023.07.007","DOIUrl":"10.1016/j.cels.2023.07.007","url":null,"abstract":"By combining mass-spectrometry-based proteomics and phosphoproteomics with genomics, epi-genomics, and transcriptomics, proteogenomics provides comprehensive molecular characterization of cancer. Using this approach, the Clinical Proteomic Tumor Analysis Consortium (CPTAC) has characterized over 1,000 primary tumors spanning 10 cancer types, many with matched normal tissues. Here, we present LinkedOmicsKB, a proteogenomics data-driven knowledge base that makes consistently processed and systematically precomputed CPTAC pan-cancer proteogenomics data available to the public through ∼40,000 gene-, protein-, mutation-, and phenotype-centric web pages. Visualization techniques facilitate efficient exploration and reasoning of complex, interconnected data. Using three case studies, we illustrate the practical utility of LinkedOmicsKB in providing new insights into genes, phosphorylation sites, somatic mutations, and cancer phenotypes. With precomputed results of 19,701 coding genes, 125,969 phosphosites, and 256 genotypes and phenotypes, LinkedOmicsKB provides a comprehensive resource to accelerate proteogenomics data-driven discoveries to improve our understanding and treatment of human cancer. A record of this paper's transparent peer review process is included in the supplemental information.","PeriodicalId":54348,"journal":{"name":"Cell Systems","volume":null,"pages":null},"PeriodicalIF":9.3,"publicationDate":"2023-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10530292/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10070752","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}

引用次数: 1