NPJ Systems Biology and Applications最新文献_第4页

Cancer mutationscape: revealing the link between modular restructuring and intervention efficacy among mutations. 癌症突变景观：揭示突变中模块重组与干预效果之间的联系。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2024-07-13 DOI: 10.1038/s41540-024-00398-6

Daniel Plaugher, David Murrugarra

{"title":"Cancer mutationscape: revealing the link between modular restructuring and intervention efficacy among mutations.","authors":"Daniel Plaugher, David Murrugarra","doi":"10.1038/s41540-024-00398-6","DOIUrl":"10.1038/s41540-024-00398-6","url":null,"abstract":"There is increasing evidence that biological systems are modular in both structure and function. Complex biological signaling networks such as gene regulatory networks (GRNs) are proving to be composed of subcategories that are interconnected and hierarchically ranked. These networks contain highly dynamic processes that ultimately dictate cellular function over time, as well as influence phenotypic fate transitions. In this work, we use a stochastic multicellular signaling network of pancreatic cancer (PC) to show that the variance in topological rankings of the most phenotypically influential modules implies a strong relationship between structure and function. We further show that induction of mutations alters the modular structure, which analogously influences the aggression and controllability of the disease in silico. We finally present evidence that the impact and location of mutations with respect to PC modular structure directly corresponds to the efficacy of single agent treatments in silico, because topologically deep mutations require deep targets for control.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11246485/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141603990","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Benchmarking and integrating human B-cell receptor genomic and antibody proteomic profiling. 人类 B 细胞受体基因组和抗体蛋白质组剖析的基准和整合。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2024-07-12 DOI: 10.1038/s41540-024-00402-z

Khang Lê Quý, Maria Chernigovskaya, Maria Stensland, Sachin Singh, Jinwoo Leem, Santiago Revale, David A Yadin, Francesca L Nice, Chelsea Povall, Danielle H Minns, Jacob D Galson, Tuula A Nyman, Igor Snapkow, Victor Greiff

{"title":"Benchmarking and integrating human B-cell receptor genomic and antibody proteomic profiling.","authors":"Khang Lê Quý, Maria Chernigovskaya, Maria Stensland, Sachin Singh, Jinwoo Leem, Santiago Revale, David A Yadin, Francesca L Nice, Chelsea Povall, Danielle H Minns, Jacob D Galson, Tuula A Nyman, Igor Snapkow, Victor Greiff","doi":"10.1038/s41540-024-00402-z","DOIUrl":"10.1038/s41540-024-00402-z","url":null,"abstract":"Immunoglobulins (Ig), which exist either as B-cell receptors (BCR) on the surface of B cells or as antibodies when secreted, play a key role in the recognition and response to antigenic threats. The capability to jointly characterize the BCR and antibody repertoire is crucial for understanding human adaptive immunity. From peripheral blood, bulk BCR sequencing (bulkBCR-seq) currently provides the highest sampling depth, single-cell BCR sequencing (scBCR-seq) allows for paired chain characterization, and antibody peptide sequencing by tandem mass spectrometry (Ab-seq) provides information on the composition of secreted antibodies in the serum. Yet, it has not been benchmarked to what extent the datasets generated by these three technologies overlap and complement each other. To address this question, we isolated peripheral blood B cells from healthy human donors and sequenced BCRs at bulk and single-cell levels, in addition to utilizing publicly available sequencing data. Integrated analysis was performed on these datasets, resolved by replicates and across individuals. Simultaneously, serum antibodies were isolated, digested with multiple proteases, and analyzed with Ab-seq. Systems immunology analysis showed high concordance in repertoire features between bulk and scBCR-seq within individuals, especially when replicates were utilized. In addition, Ab-seq identified clonotype-specific peptides using both bulk and scBCR-seq library references, demonstrating the feasibility of combining scBCR-seq and Ab-seq for reconstructing paired-chain Ig sequences from the serum antibody repertoire. Collectively, our work serves as a proof-of-principle for combining bulk sequencing, single-cell sequencing, and mass spectrometry as complementary methods towards capturing humoral immunity in its entirety.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11245537/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141601066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Computational gastronomy: capturing culinary creativity by making food computable. 计算美食：通过使食物可计算来捕捉烹饪创意。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2024-07-08 DOI: 10.1038/s41540-024-00399-5

Ganesh Bagler, Mansi Goel

{"title":"Computational gastronomy: capturing culinary creativity by making food computable.","authors":"Ganesh Bagler, Mansi Goel","doi":"10.1038/s41540-024-00399-5","DOIUrl":"10.1038/s41540-024-00399-5","url":null,"abstract":"Cooking, a quintessential creative pursuit, holds profound significance for individuals, communities, and civilizations. Food and cooking transcend mere sensory pleasure to influence nutrition and public health outcomes. Inextricably linked to culinary and cultural heritage, food systems play a pivotal role in sustainability and the survival of life on our planet. Computational Gastronomy is a novel approach for investigating food through a data-driven paradigm. It offers a systematic, rule-based understanding of culinary arts by scrutinizing recipes for taste, nutritional value, health implications, and environmental sustainability. Probing the art of cooking through the lens of computation will open up a new realm of possibilities for culinary creativity. Amidst the ongoing quest for imitating creativity through artificial intelligence, an interesting question would be, 'Can a machine think like a Chef?' Capturing the experience and creativity of a chef in an AI algorithm presents an exciting opportunity for generating a galaxy of hitherto unseen recipes with desirable culinary, flavor, nutrition, health, and carbon footprint profiles.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11231233/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141559356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

A comprehensive review of computational cell cycle models in guiding cancer treatment strategies. 全面评述用于指导癌症治疗策略的计算细胞周期模型。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2024-07-05 DOI: 10.1038/s41540-024-00397-7

Chenhui Ma, Evren Gurkan-Cavusoglu

{"title":"A comprehensive review of computational cell cycle models in guiding cancer treatment strategies.","authors":"Chenhui Ma, Evren Gurkan-Cavusoglu","doi":"10.1038/s41540-024-00397-7","DOIUrl":"10.1038/s41540-024-00397-7","url":null,"abstract":"This article reviews the current knowledge and recent advancements in computational modeling of the cell cycle. It offers a comparative analysis of various modeling paradigms, highlighting their unique strengths, limitations, and applications. Specifically, the article compares deterministic and stochastic models, single-cell versus population models, and mechanistic versus abstract models. This detailed analysis helps determine the most suitable modeling framework for various research needs. Additionally, the discussion extends to the utilization of these computational models to illuminate cell cycle dynamics, with a particular focus on cell cycle viability, crosstalk with signaling pathways, tumor microenvironment, DNA replication, and repair mechanisms, underscoring their critical roles in tumor progression and the optimization of cancer therapies. By applying these models to crucial aspects of cancer therapy planning for better outcomes, including drug efficacy quantification, drug discovery, drug resistance analysis, and dose optimization, the review highlights the significant potential of computational insights in enhancing the precision and effectiveness of cancer treatments. This emphasis on the intricate relationship between computational modeling and therapeutic strategy development underscores the pivotal role of advanced modeling techniques in navigating the complexities of cell cycle dynamics and their implications for cancer therapy.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11226463/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141538264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Revisiting the evolution of bow-tie architecture in signaling networks. 重新审视信号网络中蝴蝶结结构的演变。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2024-06-29 DOI: 10.1038/s41540-024-00396-8

Thoma Itoh, Yohei Kondo, Kazuhiro Aoki, Nen Saito

{"title":"Revisiting the evolution of bow-tie architecture in signaling networks.","authors":"Thoma Itoh, Yohei Kondo, Kazuhiro Aoki, Nen Saito","doi":"10.1038/s41540-024-00396-8","DOIUrl":"10.1038/s41540-024-00396-8","url":null,"abstract":"Bow-tie architecture is a layered network structure that has a narrow middle layer with multiple inputs and outputs. Such structures are widely seen in the molecular networks in cells, suggesting that a universal evolutionary mechanism underlies the emergence of bow-tie architecture. The previous theoretical studies have implemented evolutionary simulations of the feedforward network to satisfy a given input-output goal and proposed that the bow-tie architecture emerges when the ideal input-output relation is given as a rank-deficient matrix with mutations in network link intensities in a multiplicative manner. Here, we report that the bow-tie network inevitably appears when the link intensities representing molecular interactions are small at the initial condition of the evolutionary simulation, regardless of the rank of the goal matrix. Our dynamical system analysis clarifies the mechanisms underlying the emergence of the bow-tie structure. Further, we demonstrate that the increase in the input-output matrix reduces the width of the middle layer, resulting in the emergence of bow-tie architecture, even when evolution starts from large link intensities. Our data suggest that bow-tie architecture emerges as a side effect of evolution rather than as a result of evolutionary adaptation.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11217396/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141477071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Longitudinal single-cell data informs deterministic modelling of inflammatory bowel disease. 纵向单细胞数据为炎症性肠病的确定性建模提供了信息。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2024-06-24 DOI: 10.1038/s41540-024-00395-9

Christoph Kilian, Hanna Ulrich, Viktor A Zouboulis, Paulina Sprezyna, Jasmin Schreiber, Tomer Landsberger, Maren Büttner, Moshe Biton, Eduardo J Villablanca, Samuel Huber, Lorenz Adlung

{"title":"Longitudinal single-cell data informs deterministic modelling of inflammatory bowel disease.","authors":"Christoph Kilian, Hanna Ulrich, Viktor A Zouboulis, Paulina Sprezyna, Jasmin Schreiber, Tomer Landsberger, Maren Büttner, Moshe Biton, Eduardo J Villablanca, Samuel Huber, Lorenz Adlung","doi":"10.1038/s41540-024-00395-9","DOIUrl":"10.1038/s41540-024-00395-9","url":null,"abstract":"Single-cell-based methods such as flow cytometry or single-cell mRNA sequencing (scRNA-seq) allow deep molecular and cellular profiling of immunological processes. Despite their high throughput, however, these measurements represent only a snapshot in time. Here, we explore how longitudinal single-cell-based datasets can be used for deterministic ordinary differential equation (ODE)-based modelling to mechanistically describe immune dynamics. We derived longitudinal changes in cell numbers of colonic cell types during inflammatory bowel disease (IBD) from flow cytometry and scRNA-seq data of murine colitis using ODE-based models. Our mathematical model generalised well across different protocols and experimental techniques, and we hypothesised that the estimated model parameters reflect biological processes. We validated this prediction of cellular turnover rates with KI-67 staining and with gene expression information from the scRNA-seq data not used for model fitting. Finally, we tested the translational relevance of the mathematical model by deconvolution of longitudinal bulk mRNA-sequencing data from a cohort of human IBD patients treated with olamkicept. We found that neutrophil depletion may contribute to IBD patients entering remission. The predictive power of IBD deterministic modelling highlights its potential to advance our understanding of immune dynamics in health and disease.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11196733/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141446646","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Network-driven cancer cell avatars for combination discovery and biomarker identification for DNA damage response inhibitors. 网络驱动的癌细胞化身，用于 DNA 损伤反应抑制剂的组合发现和生物标记物鉴定。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2024-06-21 DOI: 10.1038/s41540-024-00394-w

Orsolya Papp, Viktória Jordán, Szabolcs Hetey, Róbert Balázs, Valér Kaszás, Árpád Bartha, Nóra N Ordasi, Sebestyén Kamp, Bálint Farkas, Jerome Mettetal, Jonathan R Dry, Duncan Young, Ben Sidders, Krishna C Bulusu, Daniel V Veres

{"title":"Network-driven cancer cell avatars for combination discovery and biomarker identification for DNA damage response inhibitors.","authors":"Orsolya Papp, Viktória Jordán, Szabolcs Hetey, Róbert Balázs, Valér Kaszás, Árpád Bartha, Nóra N Ordasi, Sebestyén Kamp, Bálint Farkas, Jerome Mettetal, Jonathan R Dry, Duncan Young, Ben Sidders, Krishna C Bulusu, Daniel V Veres","doi":"10.1038/s41540-024-00394-w","DOIUrl":"10.1038/s41540-024-00394-w","url":null,"abstract":"Combination therapy is well established as a key intervention strategy for cancer treatment, with the potential to overcome monotherapy resistance and deliver a more durable efficacy. However, given the scale of unexplored potential target space and the resulting combinatorial explosion, identifying efficacious drug combinations is a critical unmet need that is still evolving. In this paper, we demonstrate a network biology-driven, simulation-based solution, the Simulated Cell™. Integration of omics data with a curated signaling network enables the accurate and interpretable prediction of 66,348 combination-cell line pairs obtained from a large-scale combinatorial drug sensitivity screen of 684 combinations across 97 cancer cell lines (BAC = 0.62, AUC = 0.7). We highlight drug combination pairs that interact with DNA Damage Response pathways and are predicted to be synergistic, and deep network insight to identify biomarkers driving combination synergy. We demonstrate that the cancer cell 'avatars' capture the biological complexity of their in vitro counterparts, enabling the identification of pathway-level mechanisms of combination benefit to guide clinical translatability.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11192759/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141437264","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Canalization reduces the nonlinearity of regulation in biological networks. 渠化降低了生物网络调节的非线性。

IF 4 2区生物学

NPJ Systems Biology and Applications Pub Date : 2024-06-13 DOI: 10.1038/s41540-024-00392-y

Claus Kadelka, David Murrugarra

{"title":"Canalization reduces the nonlinearity of regulation in biological networks.","authors":"Claus Kadelka, David Murrugarra","doi":"10.1038/s41540-024-00392-y","DOIUrl":"10.1038/s41540-024-00392-y","url":null,"abstract":"Biological networks, such as gene regulatory networks, possess desirable properties. They are more robust and controllable than random networks. This motivates the search for structural and dynamical features that evolution has incorporated into biological networks. A recent meta-analysis of published, expert-curated Boolean biological network models has revealed several such features, often referred to as design principles. Among others, the biological networks are enriched for certain recurring network motifs, the dynamic update rules are more redundant, more biased, and more canalizing than expected, and the dynamics of biological networks are better approximable by linear and lower-order approximations than those of comparable random networks. Since most of these features are interrelated, it is paramount to disentangle cause and effect, that is, to understand which features evolution actively selects for, and thus truly constitute evolutionary design principles. Here, we compare published Boolean biological network models with different ensembles of null models and show that the abundance of canalization in biological networks can almost completely explain their recently postulated high approximability. Moreover, an analysis of random N-K Kauffman models reveals a strong dependence of approximability on the dynamical robustness of a network.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2024-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11176187/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141317923","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

interFLOW: maximum flow framework for the identification of factors mediating the signaling convergence of multiple receptors. interFLOW：用于识别介导多种受体信号汇聚的因素的最大流量框架。

IF 4 2区生物学

NPJ Systems Biology and Applications Pub Date : 2024-06-10 DOI: 10.1038/s41540-024-00391-z

Ron Sheinin, Koren Salomon, Eilam Yeini, Shai Dulberg, Ayelet Kaminitz, Ronit Satchi-Fainaro, Roded Sharan, Asaf Madi

{"title":"interFLOW: maximum flow framework for the identification of factors mediating the signaling convergence of multiple receptors.","authors":"Ron Sheinin, Koren Salomon, Eilam Yeini, Shai Dulberg, Ayelet Kaminitz, Ronit Satchi-Fainaro, Roded Sharan, Asaf Madi","doi":"10.1038/s41540-024-00391-z","DOIUrl":"10.1038/s41540-024-00391-z","url":null,"abstract":"Cell-cell crosstalk involves simultaneous interactions of multiple receptors and ligands, followed by downstream signaling cascades working through receptors converging at dominant transcription factors, which then integrate and propagate multiple signals into a cellular response. Single-cell RNAseq of multiple cell subsets isolated from a defined microenvironment provides us with a unique opportunity to learn about such interactions reflected in their gene expression levels. We developed the interFLOW framework to map the potential ligand-receptor interactions between different cell subsets based on a maximum flow computation in a network of protein-protein interactions (PPIs). The maximum flow approach further allows characterization of the intracellular downstream signal transduction from differentially expressed receptors towards dominant transcription factors, therefore, enabling the association between a set of receptors and their downstream activated pathways. Importantly, we were able to identify key transcription factors toward which the convergence of multiple receptor signaling pathways occurs. These identified factors have a unique role in the integration and propagation of signaling following specific cell-cell interactions.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2024-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11164912/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141301140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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

Low-frequency ERK and Akt activity dynamics are predictive of stochastic cell division events. 低频 ERK 和 Akt 活性动态可预测随机细胞分裂事件。

IF 4 2区生物学

NPJ Systems Biology and Applications Pub Date : 2024-06-04 DOI: 10.1038/s41540-024-00389-7

Jamie J R Bennett, Alan D Stern, Xiang Zhang, Marc R Birtwistle, Gaurav Pandey

{"title":"Low-frequency ERK and Akt activity dynamics are predictive of stochastic cell division events.","authors":"Jamie J R Bennett, Alan D Stern, Xiang Zhang, Marc R Birtwistle, Gaurav Pandey","doi":"10.1038/s41540-024-00389-7","DOIUrl":"10.1038/s41540-024-00389-7","url":null,"abstract":"Understanding the dynamics of intracellular signaling pathways, such as ERK1/2 (ERK) and Akt1/2 (Akt), in the context of cell fate decisions is important for advancing our knowledge of cellular processes and diseases, particularly cancer. While previous studies have established associations between ERK and Akt activities and proliferative cell fate, the heterogeneity of single-cell responses adds complexity to this understanding. This study employed a data-driven approach to address this challenge, developing machine learning models trained on a dataset of growth factor-induced ERK and Akt activity time courses in single cells, to predict cell division events. The most predictive models were developed by applying discrete wavelet transforms (DWTs) to extract low-frequency features from the time courses, followed by using Ensemble Integration, a data integration and predictive modeling framework. The results demonstrated that these models effectively predicted cell division events in MCF10A cells (F-measure=0.524, AUC=0.726). ERK dynamics were found to be more predictive than Akt, but the combination of both measurements further enhanced predictive performance. The ERK model`s performance also generalized to predicting division events in RPE cells, indicating the potential applicability of these models and our data-driven methodology for predicting cell division across different biological contexts. Interpretation of these models suggested that ERK dynamics throughout the cell cycle, rather than immediately after growth factor stimulation, were associated with the likelihood of cell division. Overall, this work contributes insights into the predictive power of intra-cellular signaling dynamics for cell fate decisions, and highlights the potential of machine learning approaches in unraveling complex cellular behaviors.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11150372/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141248354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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