Cell systems最新文献_第5页

An efficient, not-only-linear correlation coefficient based on clustering. 基于聚类的高效非线性相关系数

Cell systems Pub Date : 2024-09-18 Epub Date: 2024-09-06 DOI: 10.1016/j.cels.2024.08.005

Milton Pividori, Marylyn D Ritchie, Diego H Milone, Casey S Greene

{"title":"An efficient, not-only-linear correlation coefficient based on clustering.","authors":"Milton Pividori, Marylyn D Ritchie, Diego H Milone, Casey S Greene","doi":"10.1016/j.cels.2024.08.005","DOIUrl":"10.1016/j.cels.2024.08.005","url":null,"abstract":"Identifying meaningful patterns in data is crucial for understanding complex biological processes, particularly in transcriptomics, where genes with correlated expression often share functions or contribute to disease mechanisms. Traditional correlation coefficients, which primarily capture linear relationships, may overlook important nonlinear patterns. We introduce the clustermatch correlation coefficient (CCC), a not-only-linear coefficient that utilizes clustering to efficiently detect both linear and nonlinear associations. CCC outperforms standard methods by revealing biologically meaningful patterns that linear-only coefficients miss and is faster than state-of-the-art coefficients such as the maximal information coefficient. When applied to human gene expression data from genotype-tissue expression (GTEx), CCC identified robust linear relationships and nonlinear patterns, such as sex-specific differences, that are undetectable by standard methods. Highly ranked gene pairs were enriched for interactions in integrated networks built from protein-protein interactions, transcription factor regulation, and chemical and genetic perturbations, suggesting that CCC can detect functional relationships missed by linear-only approaches. CCC is a highly efficient, next-generation, not-only-linear correlation coefficient for genome-scale data. A record of this paper's transparent peer review process is included in the supplemental information.","PeriodicalId":93929,"journal":{"name":"Cell systems","volume":" ","pages":"854-868.e3"},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142147119","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

Discovery of therapeutic targets in cancer using chromatin accessibility and transcriptomic data. 利用染色质可及性和转录组数据发现癌症治疗靶点。

Cell systems Pub Date : 2024-09-18 Epub Date: 2024-09-04 DOI: 10.1016/j.cels.2024.08.004

Andre Neil Forbes, Duo Xu, Sandra Cohen, Priya Pancholi, Ekta Khurana

引用次数: 0

Promoter DNA methylation and transcription factor condensation are linked to transcriptional memory in mammalian cells. 启动子 DNA 甲基化和转录因子凝集与哺乳动物细胞的转录记忆有关。

Cell systems Pub Date : 2024-09-18 Epub Date: 2024-09-06 DOI: 10.1016/j.cels.2024.08.007

Shenqi Fan, Liang Ma, Chengzhi Song, Xu Han, Bijunyao Zhong, Yihan Lin

{"title":"Promoter DNA methylation and transcription factor condensation are linked to transcriptional memory in mammalian cells.","authors":"Shenqi Fan, Liang Ma, Chengzhi Song, Xu Han, Bijunyao Zhong, Yihan Lin","doi":"10.1016/j.cels.2024.08.007","DOIUrl":"10.1016/j.cels.2024.08.007","url":null,"abstract":"The regulation of genes can be mathematically described by input-output functions that are typically assumed to be time invariant. This fundamental assumption underpins the design of synthetic gene circuits and the quantitative understanding of natural gene regulatory networks. Here, we found that this assumption is challenged in mammalian cells. We observed that a synthetic reporter gene can exhibit unexpected transcriptional memory, leading to a shift in the dose-response curve upon a second induction. Mechanistically, we investigated the cis-dependency of transcriptional memory, revealing the necessity of promoter DNA methylation in establishing memory. Furthermore, we showed that the synthetic transcription factor's effective DNA binding affinity underlies trans-dependency, which is associated with its capacity to undergo biomolecular condensation. These principles enabled modulating memory by perturbing either cis- or trans-regulation of genes. Together, our findings suggest the potential pervasiveness of transcriptional memory and implicate the need to model mammalian gene regulation with time-varying input-output functions. A record of this paper's transparent peer review process is included in the supplemental information.","PeriodicalId":93929,"journal":{"name":"Cell systems","volume":" ","pages":"808-823.e6"},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142147121","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

Versatile system cores as a conceptual basis for generality in cell and developmental biology. 多功能系统核心是细胞和发育生物学通用性的概念基础。

Cell systems Pub Date : 2024-09-18 Epub Date: 2024-09-04 DOI: 10.1016/j.cels.2024.08.001

Elisa Gallo, Stefano De Renzis, James Sharpe, Roberto Mayor, Jonas Hartmann

{"title":"Versatile system cores as a conceptual basis for generality in cell and developmental biology.","authors":"Elisa Gallo, Stefano De Renzis, James Sharpe, Roberto Mayor, Jonas Hartmann","doi":"10.1016/j.cels.2024.08.001","DOIUrl":"10.1016/j.cels.2024.08.001","url":null,"abstract":"The discovery of general principles underlying the complexity and diversity of cellular and developmental systems is a central and long-standing aim of biology. While new technologies collect data at an ever-accelerating rate, there is growing concern that conceptual progress is not keeping pace. We contend that this is due to a paucity of conceptual frameworks that support meaningful generalizations. This led us to develop the core and periphery (C&P) hypothesis, which posits that many biological systems can be decomposed into a highly versatile core with a large behavioral repertoire and a specific periphery that configures said core to perform one particular function. Versatile cores tend to be widely reused across biology, which confers generality to theories describing them. Here, we introduce this concept and describe examples at multiple scales, including Turing patterning, actomyosin dynamics, multi-cellular morphogenesis, and vertebrate gastrulation. We also sketch its evolutionary basis and discuss key implications and open questions. We propose that the C&P hypothesis could unlock new avenues of conceptual progress in mesoscale biology.","PeriodicalId":93929,"journal":{"name":"Cell systems","volume":" ","pages":"790-807"},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142142059","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

Imputing abundance of over 2,500 surface proteins from single-cell transcriptomes with context-agnostic zero-shot deep ensembles. 利用上下文无关的零点深度集合，从单细胞转录组中推算出 2,500 多种表面蛋白质的丰度。

Cell systems Pub Date : 2024-09-18 Epub Date: 2024-09-06 DOI: 10.1016/j.cels.2024.08.006

Ruoqiao Chen, Jiayu Zhou, Bin Chen

{"title":"Imputing abundance of over 2,500 surface proteins from single-cell transcriptomes with context-agnostic zero-shot deep ensembles.","authors":"Ruoqiao Chen, Jiayu Zhou, Bin Chen","doi":"10.1016/j.cels.2024.08.006","DOIUrl":"10.1016/j.cels.2024.08.006","url":null,"abstract":"Cell surface proteins serve as primary drug targets and cell identity markers. Techniques such as CITE-seq (cellular indexing of transcriptomes and epitopes by sequencing) have enabled the simultaneous quantification of surface protein abundance and transcript expression within individual cells. The published data have been utilized to train machine learning models for predicting surface protein abundance solely from transcript expression. However, the small scale of proteins predicted and the poor generalization ability of these computational approaches across diverse contexts (e.g., different tissues/disease states) impede their widespread adoption. Here, we propose SPIDER (surface protein prediction using deep ensembles from single-cell RNA sequencing), a context-agnostic zero-shot deep ensemble model, which enables large-scale protein abundance prediction and generalizes better to various contexts. Comprehensive benchmarking shows that SPIDER outperforms other state-of-the-art methods. Using the predicted surface abundance of >2,500 proteins from single-cell transcriptomes, we demonstrate the broad applications of SPIDER, including cell type annotation, biomarker/target identification, and cell-cell interaction analysis in hepatocellular carcinoma and colorectal cancer. A record of this paper's transparent peer review process is included in the supplemental information.","PeriodicalId":93929,"journal":{"name":"Cell systems","volume":" ","pages":"869-884.e6"},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11423933/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142147120","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

Environmental modulators of algae-bacteria interactions at scale. 大规模藻类与细菌相互作用的环境调节因素。

Cell systems Pub Date : 2024-09-18 Epub Date: 2024-09-04 DOI: 10.1016/j.cels.2024.08.002

Chandana Gopalakrishnappa, Zeqian Li, Seppe Kuehn

{"title":"Environmental modulators of algae-bacteria interactions at scale.","authors":"Chandana Gopalakrishnappa, Zeqian Li, Seppe Kuehn","doi":"10.1016/j.cels.2024.08.002","DOIUrl":"10.1016/j.cels.2024.08.002","url":null,"abstract":"Interactions between photosynthetic and heterotrophic microbes play a key role in global primary production. Understanding phototroph-heterotroph interactions remains challenging because these microbes reside in chemically complex environments. Here, we leverage a massively parallel droplet microfluidic platform that enables us to interrogate interactions between photosynthetic algae and heterotrophic bacteria in >100,000 communities across ∼525 environmental conditions with varying pH, carbon availability, and phosphorus availability. By developing a statistical framework to dissect interactions in this complex dataset, we reveal that the dependence of algae-bacteria interactions on nutrient availability is strongly modulated by pH and buffering capacity. Furthermore, we show that the chemical identity of the available organic carbon source controls how pH, buffering capacity, and nutrient availability modulate algae-bacteria interactions. Our study reveals the previously underappreciated role of pH in modulating phototroph-heterotroph interactions and provides a framework for thinking about interactions between phototrophs and heterotrophs in more natural contexts.","PeriodicalId":93929,"journal":{"name":"Cell systems","volume":" ","pages":"838-853.e13"},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11412779/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142142058","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

The structure is the message: Preserving experimental context through tensor decomposition. 结构即信息：通过张量分解保留实验背景。

Cell systems Pub Date : 2024-08-21 DOI: 10.1016/j.cels.2024.07.004

Zhixin Cyrillus Tan, Aaron S Meyer

引用次数: 0

Rationally reprogramming single-cell aging trajectories and lifespan through dynamic modulation of environmental inputs. 通过动态调节环境输入，合理重编程单细胞衰老轨迹和寿命。

Cell systems Pub Date : 2024-08-21 DOI: 10.1016/j.cels.2024.07.008

Matthew Smart, David F Moreno, Murat Acar

引用次数: 0

Deep-learning-based design of synthetic orthologs of SH3 signaling domains. 基于深度学习的 SH3 信号结构域合成同源物设计。

Cell systems Pub Date : 2024-08-21 Epub Date: 2024-08-05 DOI: 10.1016/j.cels.2024.07.005

Xinran Lian, Nikša Praljak, Subu K Subramanian, Sarah Wasinger, Rama Ranganathan, Andrew L Ferguson

引用次数: 0

PanIN and CAF transitions in pancreatic carcinogenesis revealed with spatial data integration. 通过空间数据整合揭示胰腺癌发生过程中的 PanIN 和 CAF 转变。

Cell systems Pub Date : 2024-08-21 Epub Date: 2024-08-07 DOI: 10.1016/j.cels.2024.07.001

Alexander T F Bell, Jacob T Mitchell, Ashley L Kiemen, Melissa Lyman, Kohei Fujikura, Jae W Lee, Erin Coyne, Sarah M Shin, Sushma Nagaraj, Atul Deshpande, Pei-Hsun Wu, Dimitrios N Sidiropoulos, Rossin Erbe, Jacob Stern, Rena Chan, Stephen Williams, James M Chell, Lauren Ciotti, Jacquelyn W Zimmerman, Denis Wirtz, Won Jin Ho, Neeha Zaidi, Elizabeth Thompson, Elizabeth M Jaffee, Laura D Wood, Elana J Fertig, Luciane T Kagohara

{"title":"PanIN and CAF transitions in pancreatic carcinogenesis revealed with spatial data integration.","authors":"Alexander T F Bell, Jacob T Mitchell, Ashley L Kiemen, Melissa Lyman, Kohei Fujikura, Jae W Lee, Erin Coyne, Sarah M Shin, Sushma Nagaraj, Atul Deshpande, Pei-Hsun Wu, Dimitrios N Sidiropoulos, Rossin Erbe, Jacob Stern, Rena Chan, Stephen Williams, James M Chell, Lauren Ciotti, Jacquelyn W Zimmerman, Denis Wirtz, Won Jin Ho, Neeha Zaidi, Elizabeth Thompson, Elizabeth M Jaffee, Laura D Wood, Elana J Fertig, Luciane T Kagohara","doi":"10.1016/j.cels.2024.07.001","DOIUrl":"10.1016/j.cels.2024.07.001","url":null,"abstract":"This study introduces a new imaging, spatial transcriptomics (ST), and single-cell RNA-sequencing integration pipeline to characterize neoplastic cell state transitions during tumorigenesis. We applied a semi-supervised analysis pipeline to examine premalignant pancreatic intraepithelial neoplasias (PanINs) that can develop into pancreatic ductal adenocarcinoma (PDAC). Their strict diagnosis on formalin-fixed and paraffin-embedded (FFPE) samples limited the single-cell characterization of human PanINs within their microenvironment. We leverage whole transcriptome FFPE ST to enable the study of a rare cohort of matched low-grade (LG) and high-grade (HG) PanIN lesions to track progression and map cellular phenotypes relative to single-cell PDAC datasets. We demonstrate that cancer-associated fibroblasts (CAFs), including antigen-presenting CAFs, are located close to PanINs. We further observed a transition from CAF-related inflammatory signaling to cellular proliferation during PanIN progression. We validate these findings with single-cell high-dimensional imaging proteomics and transcriptomics technologies. Altogether, our semi-supervised learning framework for spatial multi-omics has broad applicability across cancer types to decipher the spatiotemporal dynamics of carcinogenesis.","PeriodicalId":93929,"journal":{"name":"Cell systems","volume":" ","pages":"753-769.e5"},"PeriodicalIF":0.0,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11409191/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141908694","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