NPJ Systems Biology and Applications最新文献_第8页

Inferring upstream regulatory genes of FOXP3 in human regulatory T cells from time-series transcriptomic data. 从时间序列转录组数据推断人类调节性 T 细胞中 FOXP3 的上游调控基因

IF 4 2区生物学

NPJ Systems Biology and Applications Pub Date : 2024-05-29 DOI: 10.1038/s41540-024-00387-9

Stefano Magni, Rucha Sawlekar, Christophe M Capelle, Vera Tslaf, Alexandre Baron, Ni Zeng, Laurent Mombaerts, Zuogong Yue, Ye Yuan, Feng Q Hefeng, Jorge Gonçalves

{"title":"Inferring upstream regulatory genes of FOXP3 in human regulatory T cells from time-series transcriptomic data.","authors":"Stefano Magni, Rucha Sawlekar, Christophe M Capelle, Vera Tslaf, Alexandre Baron, Ni Zeng, Laurent Mombaerts, Zuogong Yue, Ye Yuan, Feng Q Hefeng, Jorge Gonçalves","doi":"10.1038/s41540-024-00387-9","DOIUrl":"10.1038/s41540-024-00387-9","url":null,"abstract":"The discovery of upstream regulatory genes of a gene of interest still remains challenging. Here we applied a scalable computational method to unbiasedly predict candidate regulatory genes of critical transcription factors by searching the whole genome. We illustrated our approach with a case study on the master regulator FOXP3 of human primary regulatory T cells (Tregs). While target genes of FOXP3 have been identified, its upstream regulatory machinery still remains elusive. Our methodology selected five top-ranked candidates that were tested via proof-of-concept experiments. Following knockdown, three out of five candidates showed significant effects on the mRNA expression of FOXP3 across multiple donors. This provides insights into the regulatory mechanisms modulating FOXP3 transcriptional expression in Tregs. Overall, at the genome level this represents a high level of accuracy in predicting upstream regulatory genes of key genes of interest.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2024-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11137136/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141175728","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

Mechanisms of cell size regulation in slow-growing Escherichia coli cells: discriminating models beyond the adder. 缓慢生长的大肠杆菌细胞大小调节机制：加法器之外的判别模型。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2024-05-29 DOI: 10.1038/s41540-024-00383-z

César Nieto, César Augusto Vargas-García, Juan Manuel Pedraza, Abhyudai Singh

{"title":"Mechanisms of cell size regulation in slow-growing Escherichia coli cells: discriminating models beyond the adder.","authors":"César Nieto, César Augusto Vargas-García, Juan Manuel Pedraza, Abhyudai Singh","doi":"10.1038/s41540-024-00383-z","DOIUrl":"10.1038/s41540-024-00383-z","url":null,"abstract":"Under ideal conditions, Escherichia coli cells divide after adding a fixed cell size, a strategy known as the adder. This concept applies to various microbes and is often explained as the division that occurs after a certain number of stages, associated with the accumulation of precursor proteins at a rate proportional to cell size. However, under poor media conditions, E. coli cells exhibit a different size regulation. They are smaller and follow a sizer-like division strategy where the added size is inversely proportional to the size at birth. We explore three potential causes for this deviation: degradation of the precursor protein and two models where the propensity for accumulation depends on the cell size: a nonlinear accumulation rate, and accumulation starting at a threshold size termed the commitment size. These models fit the mean trends but predict different distributions given the birth size. To quantify the precision of the models to explain the data, we used the Akaike information criterion and compared them to open datasets of slow-growing E. coli cells in different media. We found that none of the models alone can consistently explain the data. However, the degradation model better explains the division strategy when cells are larger, whereas size-related models (power-law and commitment size) account for smaller cells. Our methodology proposes a data-based method in which different mechanisms can be tested systematically.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":null,"pages":null},"PeriodicalIF":3.5,"publicationDate":"2024-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11137094/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141175730","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

Flexible modeling of regulatory networks improves transcription factor activity estimation. 灵活的调控网络建模改进了转录因子活性估计。

IF 4 2区生物学

NPJ Systems Biology and Applications Pub Date : 2024-05-28 DOI: 10.1038/s41540-024-00386-w

Chen Chen, Megha Padi

{"title":"Flexible modeling of regulatory networks improves transcription factor activity estimation.","authors":"Chen Chen, Megha Padi","doi":"10.1038/s41540-024-00386-w","DOIUrl":"10.1038/s41540-024-00386-w","url":null,"abstract":"Transcriptional regulation plays a crucial role in determining cell fate and disease, yet inferring the key regulators from gene expression data remains a significant challenge. Existing methods for estimating transcription factor (TF) activity often rely on static TF-gene interaction databases and cannot adapt to changes in regulatory mechanisms across different cell types and disease conditions. Here, we present a new algorithm - Transcriptional Inference using Gene Expression and Regulatory data (TIGER) - that overcomes these limitations by flexibly modeling activation and inhibition events, up-weighting essential edges, shrinking irrelevant edges towards zero through a sparse Bayesian prior, and simultaneously estimating both TF activity levels and changes in the underlying regulatory network. When applied to yeast and cancer TF knock-out datasets, TIGER outperforms comparable methods in terms of prediction accuracy. Moreover, our application of TIGER to tissue- and cell-type-specific RNA-seq data demonstrates its ability to uncover differences in regulatory mechanisms. Collectively, our findings highlight the utility of modeling context-specific regulation when inferring transcription factor activities.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2024-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11133322/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141161982","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

Enhancing mass spectrometry imaging accessibility using convolutional autoencoders for deriving hypoxia-associated peptides from tumors. 利用卷积自动编码器提高质谱成像的可及性，从肿瘤中提取缺氧相关肽。

IF 4 2区生物学

NPJ Systems Biology and Applications Pub Date : 2024-05-27 DOI: 10.1038/s41540-024-00385-x

Verena Bitto, Pia Hönscheid, María José Besso, Christian Sperling, Ina Kurth, Michael Baumann, Benedikt Brors

{"title":"Enhancing mass spectrometry imaging accessibility using convolutional autoencoders for deriving hypoxia-associated peptides from tumors.","authors":"Verena Bitto, Pia Hönscheid, María José Besso, Christian Sperling, Ina Kurth, Michael Baumann, Benedikt Brors","doi":"10.1038/s41540-024-00385-x","DOIUrl":"10.1038/s41540-024-00385-x","url":null,"abstract":"Mass spectrometry imaging (MSI) allows to study cancer's intratumoral heterogeneity through spatially-resolved peptides, metabolites and lipids. Yet, in biomedical research MSI is rarely used for biomarker discovery. Besides its high dimensionality and multicollinearity, mass spectrometry (MS) technologies typically output mass-to-charge ratio values but not the biochemical compounds of interest. Our framework makes particularly low-abundant signals in MSI more accessible. We utilized convolutional autoencoders to aggregate features associated with tumor hypoxia, a parameter with significant spatial heterogeneity, in cancer xenograft models. We highlight that MSI captures these low-abundant signals and that autoencoders can preserve them in their latent space. The relevance of individual hyperparameters is demonstrated through ablation experiments, and the contribution from original features to latent features is unraveled. Complementing MSI with tandem MS from the same tumor model, multiple hypoxia-associated peptide candidates were derived. Compared to random forests alone, our autoencoder approach yielded more biologically relevant insights for biomarker discovery.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2024-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11130291/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141158991","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

Extending PROXIMAL to predict degradation pathways of phenolic compounds in the human gut microbiota. 扩展 PROXIMAL 预测人类肠道微生物群中酚类化合物的降解途径。

IF 4 2区生物学

NPJ Systems Biology and Applications Pub Date : 2024-05-27 DOI: 10.1038/s41540-024-00381-1

Francesco Balzerani, Telmo Blasco, Sergio Pérez-Burillo, Luis V Valcarcel, Soha Hassoun, Francisco J Planes

{"title":"Extending PROXIMAL to predict degradation pathways of phenolic compounds in the human gut microbiota.","authors":"Francesco Balzerani, Telmo Blasco, Sergio Pérez-Burillo, Luis V Valcarcel, Soha Hassoun, Francisco J Planes","doi":"10.1038/s41540-024-00381-1","DOIUrl":"10.1038/s41540-024-00381-1","url":null,"abstract":"Despite significant advances in reconstructing genome-scale metabolic networks, the understanding of cellular metabolism remains incomplete for many organisms. A promising approach for elucidating cellular metabolism is analysing the full scope of enzyme promiscuity, which exploits the capacity of enzymes to bind to non-annotated substrates and generate novel reactions. To guide time-consuming costly experimentation, different computational methods have been proposed for exploring enzyme promiscuity. One relevant algorithm is PROXIMAL, which strongly relies on KEGG to define generic reaction rules and link specific molecular substructures with associated chemical transformations. Here, we present a completely new pipeline, PROXIMAL2, which overcomes the dependency on KEGG data. In addition, PROXIMAL2 introduces two relevant improvements with respect to the former version: i) correct treatment of multi-step reactions and ii) tracking of electric charges in the transformations. We compare PROXIMAL and PROXIMAL2 in recovering annotated products from substrates in KEGG reactions, finding a highly significant improvement in the level of accuracy. We then applied PROXIMAL2 to predict degradation reactions of phenolic compounds in the human gut microbiota. The results were compared to RetroPath RL, a different and relevant enzyme promiscuity method. We found a significant overlap between these two methods but also complementary results, which open new research directions into this relevant question in nutrition.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2024-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11130242/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141159009","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 negative feedback loop underlies the Warburg effect. 负反馈回路是沃伯格效应的基础。

IF 4 2区生物学

NPJ Systems Biology and Applications Pub Date : 2024-05-24 DOI: 10.1038/s41540-024-00377-x

Alok Jaiswal, Raghvendra Singh

引用次数: 0

Comparative analysis of metabolic models of microbial communities reconstructed from automated tools and consensus approaches. 通过自动工具和共识方法重建的微生物群落代谢模型的比较分析。

IF 4 2区生物学

NPJ Systems Biology and Applications Pub Date : 2024-05-23 DOI: 10.1038/s41540-024-00384-y

Yunli Eric Hsieh, Kshitij Tandon, Heroen Verbruggen, Zoran Nikoloski

{"title":"Comparative analysis of metabolic models of microbial communities reconstructed from automated tools and consensus approaches.","authors":"Yunli Eric Hsieh, Kshitij Tandon, Heroen Verbruggen, Zoran Nikoloski","doi":"10.1038/s41540-024-00384-y","DOIUrl":"10.1038/s41540-024-00384-y","url":null,"abstract":"Genome-scale metabolic models (GEMs) of microbial communities offer valuable insights into the functional capabilities of their members and facilitate the exploration of microbial interactions. These models are generated using different automated reconstruction tools, each relying on different biochemical databases that may affect the conclusions drawn from the in silico analysis. One way to address this problem is to employ a consensus reconstruction method that combines the outcomes of different reconstruction tools. Here, we conducted a comparative analysis of community models reconstructed from three automated tools, i.e. CarveMe, gapseq, and KBase, alongside a consensus approach, utilizing metagenomics data from two marine bacterial communities. Our analysis revealed that these reconstruction approaches, while based on the same genomes, resulted in GEMs with varying numbers of genes and reactions as well as metabolic functionalities, attributed to the different databases employed. Further, our results indicated that the set of exchanged metabolites was more influenced by the reconstruction approach rather than the specific bacterial community investigated. This observation suggests a potential bias in predicting metabolite interactions using community GEMs. We also showed that consensus models encompassed a larger number of reactions and metabolites while concurrently reducing the presence of dead-end metabolites. Therefore, the usage of consensus models allows making full and unbiased use from aggregating genes from the different reconstructions in assessing the functional potential of microbial communities.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2024-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11116368/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141088139","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

Comprehensive molecular interaction map of TGFβ induced epithelial to mesenchymal transition in breast cancer. TGFβ诱导乳腺癌上皮细胞向间质转化的综合分子相互作用图。

IF 4 2区生物学

NPJ Systems Biology and Applications Pub Date : 2024-05-17 DOI: 10.1038/s41540-024-00378-w

Sai Bhavani Gottumukkala, Trivadi Sundaram Ganesan, Anbumathi Palanisamy

{"title":"Comprehensive molecular interaction map of TGFβ induced epithelial to mesenchymal transition in breast cancer.","authors":"Sai Bhavani Gottumukkala, Trivadi Sundaram Ganesan, Anbumathi Palanisamy","doi":"10.1038/s41540-024-00378-w","DOIUrl":"10.1038/s41540-024-00378-w","url":null,"abstract":"Breast cancer is one of the prevailing cancers globally, with a high mortality rate. Metastatic breast cancer (MBC) is an advanced stage of cancer, characterised by a highly nonlinear, heterogeneous process involving numerous singling pathways and regulatory interactions. Epithelial-mesenchymal transition (EMT) emerges as a key mechanism exploited by cancer cells. Transforming Growth Factor-β (TGFβ)-dependent signalling is attributed to promote EMT in advanced stages of breast cancer. A comprehensive regulatory map of TGFβ induced EMT was developed through an extensive literature survey. The network assembled comprises of 312 distinct species (proteins, genes, RNAs, complexes), and 426 reactions (state transitions, nuclear translocations, complex associations, and dissociations). The map was developed by following Systems Biology Graphical Notation (SBGN) using Cell Designer and made publicly available using MINERVA ( http://35.174.227.105:8080/minerva/?id=Metastatic_Breast_Cancer_1 ). While the complete molecular mechanism of MBC is still not known, the map captures the elaborate signalling interplay of TGFβ induced EMT-promoting MBC. Subsequently, the disease map assembled was translated into a Boolean model utilising CaSQ and analysed using Cell Collective. Simulations of these have captured the known experimental outcomes of TGFβ induced EMT in MBC. Hub regulators of the assembled map were identified, and their transcriptome-based analysis confirmed their role in cancer metastasis. Elaborate analysis of this map may help in gaining additional insights into the development and progression of metastatic breast cancer.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":null,"pages":null},"PeriodicalIF":4.0,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11101644/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140958661","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 multi-omics approach for biomarker discovery in neuroblastoma: a network-based framework 发现神经母细胞瘤生物标记物的多组学方法：基于网络的框架

IF 4 2区生物学

NPJ Systems Biology and Applications Pub Date : 2024-05-17 DOI: 10.1038/s41540-024-00371-3

Rahma Hussein, Ahmed M. Abou-Shanab, Eman Badr

引用次数: 0

Comprehensive molecular interaction map of TGFβ induced epithelial to mesenchymal transition in breast cancer TGFβ 诱导乳腺癌上皮细胞向间质转化的综合分子相互作用图谱

IF 4 2区生物学

NPJ Systems Biology and Applications Pub Date : 2024-05-17 DOI: 10.1038/s41540-024-00378-w

Sai Bhavani Gottumukkala, T. S. Ganesan, A. Palanisamy

引用次数: 0