Cell systems最新文献_第10页

Sustainable protein regeneration in encapsulated materials. 封装材料中的可持续蛋白质再生。

Cell systems Pub Date : 2024-03-20 DOI: 10.1016/j.cels.2024.02.004

Sourik Dey, Shrikrishnan Sankaran

引用次数: 0

What can recent methodological advances help us understand about protein and genome evolution? 最新的方法论进展能帮助我们了解蛋白质和基因组进化的哪些方面？

Cell systems Pub Date : 2024-03-20 DOI: 10.1016/j.cels.2024.02.006

引用次数: 0

Widespread alteration of protein autoinhibition in human cancers. 人类癌症中蛋白质自身抑制的广泛改变。

Cell systems Pub Date : 2024-03-20 Epub Date: 2024-02-15 DOI: 10.1016/j.cels.2024.01.009

Jorge A Holguin-Cruz, Jennifer M Bui, Ashwani Jha, Dokyun Na, Jörg Gsponer

引用次数: 0

Clonal differences underlie variable responses to sequential and prolonged treatment. 克隆差异是对连续和长期治疗产生不同反应的原因。

Cell systems Pub Date : 2024-03-20 Epub Date: 2024-02-23 DOI: 10.1016/j.cels.2024.01.011

Dylan L Schaff, Aria J Fasse, Phoebe E White, Robert J Vander Velde, Sydney M Shaffer

{"title":"Clonal differences underlie variable responses to sequential and prolonged treatment.","authors":"Dylan L Schaff, Aria J Fasse, Phoebe E White, Robert J Vander Velde, Sydney M Shaffer","doi":"10.1016/j.cels.2024.01.011","DOIUrl":"10.1016/j.cels.2024.01.011","url":null,"abstract":"Cancer cells exhibit dramatic differences in gene expression at the single-cell level, which can predict whether they become resistant to treatment. Treatment perpetuates this heterogeneity, resulting in a diversity of cell states among resistant clones. However, it remains unclear whether these differences lead to distinct responses when another treatment is applied or the same treatment is continued. In this study, we combined single-cell RNA sequencing with barcoding to track resistant clones through prolonged and sequential treatments. We found that cells within the same clone have similar gene expression states after multiple rounds of treatment. Moreover, we demonstrated that individual clones have distinct and differing fates, including growth, survival, or death, when subjected to a second treatment or when the first treatment is continued. By identifying gene expression states that predict clone survival, this work provides a foundation for selecting optimal therapies that target the most aggressive resistant clones within a tumor. A record of this paper's transparent peer review process is included in the supplemental information.","PeriodicalId":93929,"journal":{"name":"Cell systems","volume":" ","pages":"213-226.e9"},"PeriodicalIF":0.0,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11003565/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139944788","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Convolutions are competitive with transformers for protein sequence pretraining. 在蛋白质序列预训练方面，卷积与变换器具有竞争性。

Cell systems Pub Date : 2024-03-20 Epub Date: 2024-02-29 DOI: 10.1016/j.cels.2024.01.008

Kevin K Yang, Nicolo Fusi, Alex X Lu

{"title":"Convolutions are competitive with transformers for protein sequence pretraining.","authors":"Kevin K Yang, Nicolo Fusi, Alex X Lu","doi":"10.1016/j.cels.2024.01.008","DOIUrl":"10.1016/j.cels.2024.01.008","url":null,"abstract":"Pretrained protein sequence language models have been shown to improve the performance of many prediction tasks and are now routinely integrated into bioinformatics tools. However, these models largely rely on the transformer architecture, which scales quadratically with sequence length in both run-time and memory. Therefore, state-of-the-art models have limitations on sequence length. To address this limitation, we investigated whether convolutional neural network (CNN) architectures, which scale linearly with sequence length, could be as effective as transformers in protein language models. With masked language model pretraining, CNNs are competitive with, and occasionally superior to, transformers across downstream applications while maintaining strong performance on sequences longer than those allowed in the current state-of-the-art transformer models. Our work suggests that computational efficiency can be improved without sacrificing performance, simply by using a CNN architecture instead of a transformer, and emphasizes the importance of disentangling pretraining task and model architecture. A record of this paper's transparent peer review process is included in the supplemental information.","PeriodicalId":93929,"journal":{"name":"Cell systems","volume":" ","pages":"286-294.e2"},"PeriodicalIF":0.0,"publicationDate":"2024-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140013789","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Retrospective identification of cell-intrinsic factors that mark pluripotency potential in rare somatic cells. 在罕见体细胞中回溯鉴定标志多能潜能的细胞内在因子。

Cell systems Pub Date : 2024-02-21 Epub Date: 2024-02-08 DOI: 10.1016/j.cels.2024.01.001

Naveen Jain, Yogesh Goyal, Margaret C Dunagin, Christopher J Cote, Ian A Mellis, Benjamin Emert, Connie L Jiang, Ian P Dardani, Sam Reffsin, Miles Arnett, Wenli Yang, Arjun Raj

{"title":"Retrospective identification of cell-intrinsic factors that mark pluripotency potential in rare somatic cells.","authors":"Naveen Jain, Yogesh Goyal, Margaret C Dunagin, Christopher J Cote, Ian A Mellis, Benjamin Emert, Connie L Jiang, Ian P Dardani, Sam Reffsin, Miles Arnett, Wenli Yang, Arjun Raj","doi":"10.1016/j.cels.2024.01.001","DOIUrl":"10.1016/j.cels.2024.01.001","url":null,"abstract":"Pluripotency can be induced in somatic cells by the expression of OCT4, KLF4, SOX2, and MYC. Usually only a rare subset of cells reprogram, and the molecular characteristics of this subset remain unknown. We apply retrospective clone tracing to identify and characterize the rare human fibroblasts primed for reprogramming. These fibroblasts showed markers of increased cell cycle speed and decreased fibroblast activation. Knockdown of a fibroblast activation factor identified by our analysis increased the reprogramming efficiency. We provide evidence for a unified model in which cells can move into and out of the primed state over time, explaining how reprogramming appears deterministic at short timescales and stochastic at long timescales. Furthermore, inhibiting the activity of LSD1 enlarged the pool of cells that were primed for reprogramming. Thus, even homogeneous cell populations can exhibit heritable molecular variability that can dictate whether individual rare cells will reprogram or not.","PeriodicalId":93929,"journal":{"name":"Cell systems","volume":" ","pages":"109-133.e10"},"PeriodicalIF":0.0,"publicationDate":"2024-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10940218/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139713514","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Mapping combinatorial expression perturbations to growth in Escherichia coli. 绘制组合表达扰动与大肠杆菌生长的关系图。

Cell systems Pub Date : 2024-02-21 DOI: 10.1016/j.cels.2024.01.006

J Scott P McCain

引用次数: 0

A top variant identification pipeline for protein engineering. 用于蛋白质工程的顶级变异识别管道。

Cell systems Pub Date : 2024-02-21 DOI: 10.1016/j.cels.2024.01.010

Hui Chen, Zhike Lu, Lijia Ma

引用次数: 0

Simple visualization of submicroscopic protein clusters with a phase-separation-based fluorescent reporter. 利用基于相分离的荧光报告器实现亚显微蛋白质团簇的简单可视化。

Cell systems Pub Date : 2024-02-21 Epub Date: 2024-02-08 DOI: 10.1016/j.cels.2024.01.005

Thomas R Mumford, Diarmid Rae, Emily Brackhahn, Abbas Idris, David Gonzalez-Martinez, Ayush Aditya Pal, Michael C Chung, Juan Guan, Elizabeth Rhoades, Lukasz J Bugaj

{"title":"Simple visualization of submicroscopic protein clusters with a phase-separation-based fluorescent reporter.","authors":"Thomas R Mumford, Diarmid Rae, Emily Brackhahn, Abbas Idris, David Gonzalez-Martinez, Ayush Aditya Pal, Michael C Chung, Juan Guan, Elizabeth Rhoades, Lukasz J Bugaj","doi":"10.1016/j.cels.2024.01.005","DOIUrl":"10.1016/j.cels.2024.01.005","url":null,"abstract":"Protein clustering plays numerous roles in cell physiology and disease. However, protein oligomers can be difficult to detect because they are often too small to appear as puncta in conventional fluorescence microscopy. Here, we describe a fluorescent reporter strategy that detects protein clusters with high sensitivity called CluMPS (clusters magnified by phase separation). A CluMPS reporter detects and visually amplifies even small clusters of a binding partner, generating large, quantifiable fluorescence condensates. We use computational modeling and optogenetic clustering to demonstrate that CluMPS can detect small oligomers and behaves rationally according to key system parameters. CluMPS detected small aggregates of pathological proteins where the corresponding GFP fusions appeared diffuse. CluMPS also detected and tracked clusters of unmodified and tagged endogenous proteins, and orthogonal CluMPS probes could be multiplexed in cells. CluMPS provides a powerful yet straightforward approach to observe higher-order protein assembly in its native cellular context. A record of this paper's transparent peer review process is included in the supplemental information.","PeriodicalId":93929,"journal":{"name":"Cell systems","volume":" ","pages":"166-179.e7"},"PeriodicalIF":0.0,"publicationDate":"2024-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10947474/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139713515","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A continuous epistasis model for predicting growth rate given combinatorial variation in gene expression and environment. 在基因表达和环境组合变化的情况下，预测生长率的连续外显模型。

Cell systems Pub Date : 2024-02-21 Epub Date: 2024-02-09 DOI: 10.1016/j.cels.2024.01.003

Ryan M Otto, Agata Turska-Nowak, Philip M Brown, Kimberly A Reynolds

{"title":"A continuous epistasis model for predicting growth rate given combinatorial variation in gene expression and environment.","authors":"Ryan M Otto, Agata Turska-Nowak, Philip M Brown, Kimberly A Reynolds","doi":"10.1016/j.cels.2024.01.003","DOIUrl":"10.1016/j.cels.2024.01.003","url":null,"abstract":"Quantifying and predicting growth rate phenotype given variation in gene expression and environment is complicated by epistatic interactions and the vast combinatorial space of possible perturbations. We developed an approach for mapping expression-growth rate landscapes that integrates sparsely sampled experimental measurements with an interpretable machine learning model. We used mismatch CRISPRi across pairs and triples of genes to create over 8,000 titrated changes in E. coli gene expression under varied environmental contexts, exploring epistasis in up to 22 distinct environments. Our results show that a pairwise model previously used to describe drug interactions well-described these data. The model yielded interpretable parameters related to pathway architecture and generalized to predict the combined effect of up to four perturbations when trained solely on pairwise perturbation data. We anticipate this approach will be broadly applicable in optimizing bacterial growth conditions, generating pharmacogenomic models, and understanding the fundamental constraints on bacterial gene expression. A record of this paper's transparent peer review process is included in the supplemental information.","PeriodicalId":93929,"journal":{"name":"Cell systems","volume":" ","pages":"134-148.e7"},"PeriodicalIF":0.0,"publicationDate":"2024-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10885703/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139716697","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0