Cell Systems最新文献_第9页

Instance segmentation of mitochondria in electron microscopy images with a generalist deep learning model trained on a diverse dataset. 利用在不同数据集上训练的通用深度学习模型，对电子显微镜图像中的线粒体进行实例分割。

IF 9.3 1区生物学

Cell Systems Pub Date : 2023-01-18 DOI: 10.1016/j.cels.2022.12.006

Ryan Conrad, Kedar Narayan

引用次数: 0

Epigenetic inheritance of gene silencing is maintained by a self-tuning mechanism based on resource competition. 基因沉默的表观遗传是通过基于资源竞争的自调整机制来维持的。

IF 9.3 1区生物学

Cell Systems Pub Date : 2023-01-18 DOI: 10.1016/j.cels.2022.12.003

Omer Karin, Eric A Miska, Benjamin D Simons

引用次数: 0

Gene-by-gene screen of the unknown proteins encoded on Plasmodium falciparum chromosome 3. 恶性疟原虫3号染色体未知编码蛋白的逐基因筛选。

IF 9.3 1区生物学

Cell Systems Pub Date : 2023-01-18 DOI: 10.1016/j.cels.2022.12.001

Jessica Kimmel, Marius Schmitt, Alexej Sinner, Pascal Wilhelmus Theodorus Christianus Jansen, Sheila Mainye, Gala Ramón-Zamorano, Christa Geeke Toenhake, Jan Stephan Wichers-Misterek, Jakob Cronshagen, Ricarda Sabitzki, Paolo Mesén-Ramírez, Hannah Michaela Behrens, Richárd Bártfai, Tobias Spielmann

{"title":"Gene-by-gene screen of the unknown proteins encoded on Plasmodium falciparum chromosome 3.","authors":"Jessica Kimmel, Marius Schmitt, Alexej Sinner, Pascal Wilhelmus Theodorus Christianus Jansen, Sheila Mainye, Gala Ramón-Zamorano, Christa Geeke Toenhake, Jan Stephan Wichers-Misterek, Jakob Cronshagen, Ricarda Sabitzki, Paolo Mesén-Ramírez, Hannah Michaela Behrens, Richárd Bártfai, Tobias Spielmann","doi":"10.1016/j.cels.2022.12.001","DOIUrl":"https://doi.org/10.1016/j.cels.2022.12.001","url":null,"abstract":"Taxon-specific proteins are key determinants defining the biology of all organisms and represent prime drug targets in pathogens. However, lacking comparability with proteins in other lineages makes them particularly difficult to study. In malaria parasites, this is exacerbated by technical limitations. Here, we analyzed the cellular location, essentiality, function, and, in selected cases, interactome of all unknown non-secretory proteins encoded on an entire P. falciparum chromosome. The nucleus was the most common localization, indicating that it is a hotspot of parasite-specific biology. More in-depth functional studies with four proteins revealed essential roles in DNA replication and mitosis. The mitosis proteins defined a possible orphan complex and a highly diverged complex needed for spindle-kinetochore connection. Structure-function comparisons indicated that the taxon-specific proteins evolved by different mechanisms. This work demonstrates the feasibility of gene-by-gene screens to elucidate the biology of malaria parasites and reveal critical parasite-specific processes of interest as drug targets.","PeriodicalId":54348,"journal":{"name":"Cell Systems","volume":null,"pages":null},"PeriodicalIF":9.3,"publicationDate":"2023-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9544015","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: 6

MitoNet: A generalizable model for segmentation of individual mitochondria within electron microscopy datasets. MitoNet:一个在电子显微镜数据集中分割单个线粒体的通用模型。

IF 9.3 1区生物学

Cell Systems Pub Date : 2023-01-18 DOI: 10.1016/j.cels.2022.12.004

Brian Glancy

引用次数: 0

Improved predictions of antigen presentation and TCR recognition with MixMHCpred2.2 and PRIME2.0 reveal potent SARS-CoV-2 CD8⁺ T-cell epitopes. MixMHCpred2.2和PRIME2.0改进了抗原呈递和TCR识别的预测，揭示了有效的SARS-CoV-2 CD8+ t细胞表位。

IF 9.3 1区生物学

Cell Systems Pub Date : 2023-01-18 DOI: 10.1016/j.cels.2022.12.002

David Gfeller, Julien Schmidt, Giancarlo Croce, Philippe Guillaume, Sara Bobisse, Raphael Genolet, Lise Queiroz, Julien Cesbron, Julien Racle, Alexandre Harari

{"title":"Improved predictions of antigen presentation and TCR recognition with MixMHCpred2.2 and PRIME2.0 reveal potent SARS-CoV-2 CD8+ T-cell epitopes.","authors":"David Gfeller, Julien Schmidt, Giancarlo Croce, Philippe Guillaume, Sara Bobisse, Raphael Genolet, Lise Queiroz, Julien Cesbron, Julien Racle, Alexandre Harari","doi":"10.1016/j.cels.2022.12.002","DOIUrl":"https://doi.org/10.1016/j.cels.2022.12.002","url":null,"abstract":"The recognition of pathogen or cancer-specific epitopes by CD8+ T cells is crucial for the clearance of infections and the response to cancer immunotherapy. This process requires epitopes to be presented on class I human leukocyte antigen (HLA-I) molecules and recognized by the T-cell receptor (TCR). Machine learning models capturing these two aspects of immune recognition are key to improve epitope predictions. Here, we assembled a high-quality dataset of naturally presented HLA-I ligands and experimentally verified neo-epitopes. We then integrated these data in a refined computational framework to predict antigen presentation (MixMHCpred2.2) and TCR recognition (PRIME2.0). The depth of our training data and the algorithmic developments resulted in improved predictions of HLA-I ligands and neo-epitopes. Prospectively applying our tools to SARS-CoV-2 proteins revealed several epitopes. TCR sequencing identified a monoclonal response in effector/memory CD8+ T cells against one of these epitopes and cross-reactivity with the homologous peptides from other coronaviruses.","PeriodicalId":54348,"journal":{"name":"Cell Systems","volume":null,"pages":null},"PeriodicalIF":9.3,"publicationDate":"2023-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9200122","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: 9

The in silico lab: Improving academic code using lessons from biology. 计算机实验室:利用生物学的经验改进学术代码。

IF 9.3 1区生物学

Cell Systems Pub Date : 2023-01-18 DOI: 10.1016/j.cels.2022.11.006

Jason Y Cain, Jessica S Yu, Neda Bagheri

引用次数: 0

Multi-omic integration reveals cell-type-specific regulatory networks of insulin resistance in distinct ancestry populations. 多组学整合揭示了不同血统人群胰岛素抵抗的细胞类型特异性调控网络。

IF 9.3 1区生物学

Cell Systems Pub Date : 2023-01-18 Epub Date: 2023-01-10 DOI: 10.1016/j.cels.2022.12.005

Peng Xu, Minghui Wang, Neeraj K Sharma, Mary E Comeau, Martin Wabitsch, Carl D Langefeld, Mete Civelek, Bin Zhang, Swapan K Das

{"title":"Multi-omic integration reveals cell-type-specific regulatory networks of insulin resistance in distinct ancestry populations.","authors":"Peng Xu, Minghui Wang, Neeraj K Sharma, Mary E Comeau, Martin Wabitsch, Carl D Langefeld, Mete Civelek, Bin Zhang, Swapan K Das","doi":"10.1016/j.cels.2022.12.005","DOIUrl":"10.1016/j.cels.2022.12.005","url":null,"abstract":"Our knowledge of the cell-type-specific mechanisms of insulin resistance remains limited. To dissect the cell-type-specific molecular signatures of insulin resistance, we performed a multiscale gene network analysis of adipose and muscle tissues in African and European ancestry populations. In adipose tissues, a comparative analysis revealed ethnically conserved cell-type signatures and two adipocyte subtype-enriched modules with opposite insulin sensitivity responses. The modules enriched for adipose stem and progenitor cells as well as immune cells showed negative correlations with insulin sensitivity. In muscle tissues, the modules enriched for stem cells and fibro-adipogenic progenitors responded to insulin sensitivity oppositely. The adipocyte and muscle fiber-enriched modules shared cellular-respiration-related genes but had tissue-specific rearrangements of gene regulations in response to insulin sensitivity. Integration of the gene co-expression and causal networks further pinpointed key drivers of insulin resistance. Together, this study revealed the cell-type-specific transcriptomic networks and signaling maps underlying insulin resistance in major glucose-responsive tissues. 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":"2023-01-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9852073/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9973480","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

Periodic spatial patterning with a single morphogen. 具有单一形态源的周期性空间图案。

IF 9.3 1区生物学

Cell Systems Pub Date : 2022-12-21 DOI: 10.1016/j.cels.2022.11.001

Sheng Wang, Jordi Garcia-Ojalvo, Michael B Elowitz

引用次数: 0

Distinct gene programs underpinning disease tolerance and resistance in influenza virus infection. 流感病毒感染中支持疾病耐受性和耐药性的独特基因程序。

IF 9.3 1区生物学

Cell Systems Pub Date : 2022-12-21 DOI: 10.1016/j.cels.2022.11.004

Ofir Cohn, Gal Yankovitz, Naama Peshes-Yaloz, Yael Steuerman, Amit Frishberg, Rachel Brandes, Michal Mandelboim, Jennifer R Hamilton, Tzachi Hagai, Ido Amit, Mihai G Netea, Nir Hacohen, Fuad A Iraqi, Eran Bacharach, Irit Gat-Viks

{"title":"Distinct gene programs underpinning disease tolerance and resistance in influenza virus infection.","authors":"Ofir Cohn, Gal Yankovitz, Naama Peshes-Yaloz, Yael Steuerman, Amit Frishberg, Rachel Brandes, Michal Mandelboim, Jennifer R Hamilton, Tzachi Hagai, Ido Amit, Mihai G Netea, Nir Hacohen, Fuad A Iraqi, Eran Bacharach, Irit Gat-Viks","doi":"10.1016/j.cels.2022.11.004","DOIUrl":"https://doi.org/10.1016/j.cels.2022.11.004","url":null,"abstract":"When challenged with an invading pathogen, the host-defense response is engaged to eliminate the pathogen (resistance) and to maintain health in the presence of the pathogen (disease tolerance). However, the identification of distinct molecular programs underpinning disease tolerance and resistance remained obscure. We exploited transcriptional and physiological monitoring across 33 mouse strains, during in vivo influenza virus infection, to identify two host-defense gene programs-one is associated with hallmarks of disease tolerance and the other with hallmarks of resistance. Both programs constitute generic responses in multiple mouse and human cell types. Our study describes the organizational principles of these programs and validates Arhgdia as a regulator of disease-tolerance states in epithelial cells. We further reveal that the baseline disease-tolerance state in peritoneal macrophages is associated with the pathophysiological response to injury and infection. Our framework provides a paradigm for the understanding of disease tolerance and resistance at the molecular level.","PeriodicalId":54348,"journal":{"name":"Cell Systems","volume":null,"pages":null},"PeriodicalIF":9.3,"publicationDate":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10602341","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

Multi-objective optimization identifies a specific and interpretable COVID-19 host response signature. 多目标优化识别特定且可解释的COVID-19宿主反应特征。

IF 9.3 1区生物学

Cell Systems Pub Date : 2022-12-21 DOI: 10.1016/j.cels.2022.11.008

Antonio Cappuccio, Daniel G Chawla, Xi Chen, Aliza B Rubenstein, Wan Sze Cheng, Weiguang Mao, Thomas W Burke, Ephraim L Tsalik, Elizabeth Petzold, Ricardo Henao, Micah T McClain, Christopher W Woods, Maria Chikina, Olga G Troyanskaya, Stuart C Sealfon, Steven H Kleinstein, Elena Zaslavsky

{"title":"Multi-objective optimization identifies a specific and interpretable COVID-19 host response signature.","authors":"Antonio Cappuccio, Daniel G Chawla, Xi Chen, Aliza B Rubenstein, Wan Sze Cheng, Weiguang Mao, Thomas W Burke, Ephraim L Tsalik, Elizabeth Petzold, Ricardo Henao, Micah T McClain, Christopher W Woods, Maria Chikina, Olga G Troyanskaya, Stuart C Sealfon, Steven H Kleinstein, Elena Zaslavsky","doi":"10.1016/j.cels.2022.11.008","DOIUrl":"https://doi.org/10.1016/j.cels.2022.11.008","url":null,"abstract":"The identification of a COVID-19 host response signature in blood can increase the understanding of SARS-CoV-2 pathogenesis and improve diagnostic tools. Applying a multi-objective optimization framework to both massive public and new multi-omics data, we identified a COVID-19 signature regulated at both transcriptional and epigenetic levels. We validated the signature's robustness in multiple independent COVID-19 cohorts. Using public data from 8,630 subjects and 53 conditions, we demonstrated no cross-reactivity with other viral and bacterial infections, COVID-19 comorbidities, or confounders. In contrast, previously reported COVID-19 signatures were associated with significant cross-reactivity. The signature's interpretation, based on cell-type deconvolution and single-cell data analysis, revealed prominent yet complementary roles for plasmablasts and memory T cells. Although the signal from plasmablasts mediated COVID-19 detection, the signal from memory T cells controlled against cross-reactivity with other viral infections. This framework identified a robust, interpretable COVID-19 signature and is broadly applicable in other disease contexts. 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":"2022-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10602369","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: 2