NPJ Systems Biology and Applications最新文献_第9页

MIRO1 mutation leads to metabolic maladaptation resulting in Parkinson's disease-associated dopaminergic neuron loss. MIRO1突变导致代谢失调，导致帕金森病相关多巴胺能神经元丢失。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-04-17 DOI: 10.1038/s41540-025-00509-x

Alise Zagare, Thomas Sauter, Kyriaki Barmpa, Maria Pacheco, Rejko Krüger, Jens Christian Schwamborn, Claudia Saraiva

{"title":"MIRO1 mutation leads to metabolic maladaptation resulting in Parkinson's disease-associated dopaminergic neuron loss.","authors":"Alise Zagare, Thomas Sauter, Kyriaki Barmpa, Maria Pacheco, Rejko Krüger, Jens Christian Schwamborn, Claudia Saraiva","doi":"10.1038/s41540-025-00509-x","DOIUrl":"https://doi.org/10.1038/s41540-025-00509-x","url":null,"abstract":"MIRO1 is a mitochondrial outer membrane protein important for mitochondrial distribution, dynamics and bioenergetics. Over the last decade, evidence has pointed to a link between MIRO1 and Parkinson's disease (PD) pathogenesis. Moreover, a heterozygous MIRO1 mutation (p.R272Q) was identified in a PD patient, from which an iPSC-derived midbrain organoid model was derived, showing MIRO1 mutant-dependent selective loss of dopaminergic neurons. Herein, we use patient-specific iPSC-derived midbrain organoids carrying the MIRO1 p.R272Q mutation to further explore the cellular and molecular mechanisms involved in dopaminergic neuron degeneration. Using single-cell RNA sequencing (scRNAseq) analysis and metabolic modeling we show that the MIRO1 p.R272Q mutation affects the dopaminergic neuron developmental path leading to metabolic deficits and disrupted neuron-astrocyte metabolic crosstalk, which might represent an important pathogenic mechanism leading to their loss.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"37"},"PeriodicalIF":3.5,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12006346/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144011846","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

Single cell RNAseq to identify subpopulations of glial progenitors in iPSC-derived oligodendroglial lineage cultures. 单细胞RNAseq在ipsc衍生的少突胶质谱系培养中鉴定胶质祖细胞亚群。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-04-15 DOI: 10.1038/s41540-025-00515-z

Gabriela J Blaszczyk, Valerio E C Piscopo, Taylor M Goldsmith, Alexandra Chapleau, Julien Sirois, Geneviève Bernard, Jack P Antel, Thomas M Durcan

引用次数: 0

Predicting gene expression changes from chromatin structure modification. 从染色质结构修饰预测基因表达变化。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-04-15 DOI: 10.1038/s41540-025-00510-4

Swayamshree Senapati, Inayat Ullah Irshad, Ajeet K Sharma, Hemant Kumar

{"title":"Predicting gene expression changes from chromatin structure modification.","authors":"Swayamshree Senapati, Inayat Ullah Irshad, Ajeet K Sharma, Hemant Kumar","doi":"10.1038/s41540-025-00510-4","DOIUrl":"https://doi.org/10.1038/s41540-025-00510-4","url":null,"abstract":"Spatial organization of chromatin plays a critical role in gene transcription, but connecting population-averaged HiC data to functional outcomes remains a challenge. We present a computational framework linking HiC contact map to gene transcription. Utilizing a bead-spring polymer model informed by HiC contact maps, we generate an ensemble of 3D conformations for a given genomic locus. These conformations are then coupled to gene transcription levels through a Markov chain model, with transition rates derived from molecular dynamics simulations. The efficacy of this framework is demonstrated by simulating the perturbation of a CTCF-mediated TAD boundary, impacting the expression of sox9 and kcnj2. Our model quantitatively reproduces experimentally observed changes in gene expression, revealing that the increased kcnj2 transcription is a consequence of enhancers within the sox9 TAD becoming accessible upon boundary disruption. Quantifying enhancer impact, our model can also identify functional enhancers. This framework enhances our understanding of the relationship between chromosome spatial architecture and gene regulation.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"34"},"PeriodicalIF":3.5,"publicationDate":"2025-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12000410/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144029977","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

Quantitative cancer-immunity cycle modeling for predicting disease progression in advanced metastatic colorectal cancer. 定量癌症免疫周期模型预测晚期转移性结直肠癌的疾病进展。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-04-13 DOI: 10.1038/s41540-025-00513-1

Chenghang Li, Yongchang Wei, Jinzhi Lei

{"title":"Quantitative cancer-immunity cycle modeling for predicting disease progression in advanced metastatic colorectal cancer.","authors":"Chenghang Li, Yongchang Wei, Jinzhi Lei","doi":"10.1038/s41540-025-00513-1","DOIUrl":"https://doi.org/10.1038/s41540-025-00513-1","url":null,"abstract":"Patients with advanced metastatic colorectal cancer (mCRC) typically exhibit significant interindividual differences in treatment responses and face poor survival outcomes. To systematically analyze the heterogeneous tumor progression and recurrence observed in advanced mCRC patients, we developed a quantitative cancer-immunity cycle (QCIC) model. The QCIC model employs differential equations to capture the biological mechanisms underlying the cancer-immunity cycle and predicts tumor evolution dynamics under various treatment strategies through stochastic computational methods. We introduce the treatment response index (TRI) to quantify disease progression in virtual clinical trials and the death probability function (DPF) to estimate overall survival. Additionally, we investigate the impact of predictive biomarkers on survival prognosis in advanced mCRC patients, identifying tumor-infiltrating CD8+ cytotoxic T lymphocytes (CTLs) as key predictors of disease progression and the tumor-infiltrating CD4+ Th1/Treg ratio as a significant determinant of survival outcomes. This study presents an approach that bridges the gap between diverse clinical data sources and the generation of virtual patient cohorts, providing valuable insights into interindividual treatment variability and survival forecasting in mCRC patients.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"33"},"PeriodicalIF":3.5,"publicationDate":"2025-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11993626/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144020721","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 mechanism for the emergence of low-dimensional structures in brain dynamics. 脑动力学中低维结构出现的机制。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-04-10 DOI: 10.1038/s41540-025-00499-w

Claudio Runfola, Spase Petkoski, Hiba Sheheitli, Christophe Bernard, Anthony R McIntosh, Viktor Jirsa

{"title":"A mechanism for the emergence of low-dimensional structures in brain dynamics.","authors":"Claudio Runfola, Spase Petkoski, Hiba Sheheitli, Christophe Bernard, Anthony R McIntosh, Viktor Jirsa","doi":"10.1038/s41540-025-00499-w","DOIUrl":"https://doi.org/10.1038/s41540-025-00499-w","url":null,"abstract":"Recent neuroimaging advancements have led to datasets characterized by an overwhelming number of features. Different dimensionality reduction techniques have been employed to uncover low-dimensional manifold representations underlying cognitive functions, while maintaining the fundamental characteristics of the data. These range from linear algorithms to more intricate non-linear methods for manifold extraction. However, the mechanisms responsible for the emergence of these simplified architectures remain a topic of debate. Motivated by concepts from dynamical systems theory, such as averaging and time-scale separation, our study introduces a novel mechanism for the collapse of high dimension brain dynamics onto lower dimensional manifolds. In our framework, fast neuronal activity oscillations average out over time, leading to the resulting dynamics approximating task-related processes occurring at slower time scales. This leads to the emergence of low-dimensional solutions as complex dynamics collapse into slow invariant manifolds. We test this assumption via neural simulations using a simplified model and then enhance the complexity of our simulations by incorporating a large-scale brain network model to mimic realistic neuroimaging signals. We observe in the different cases the convergence of fast oscillatory fluctuations of neuronal activity across time scales that correspond to simulated behavioral configurations. Specifically, by employing various dimensionality reduction techniques and manifold extraction schemes, we observe the reduction of high-dimensional dynamics onto lower-dimensional spaces, revealing emergent low-dimensional solutions. Our findings shed light on the role of frequency and time-scale separation in neuronal activity, proposing and testing a novel theoretical framework for understanding the inner mechanisms governing low-dimensional pattern formation in brain dynamics.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"32"},"PeriodicalIF":3.5,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11985988/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144036807","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

Modeling the dynamics of EMT reveals genes associated with pan-cancer intermediate states and plasticity. EMT动力学建模揭示了与泛癌中间状态和可塑性相关的基因。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-04-10 DOI: 10.1038/s41540-025-00512-2

MeiLu McDermott, Riddhee Mehta, Evanthia T Roussos Torres, Adam L MacLean

{"title":"Modeling the dynamics of EMT reveals genes associated with pan-cancer intermediate states and plasticity.","authors":"MeiLu McDermott, Riddhee Mehta, Evanthia T Roussos Torres, Adam L MacLean","doi":"10.1038/s41540-025-00512-2","DOIUrl":"https://doi.org/10.1038/s41540-025-00512-2","url":null,"abstract":"Epithelial-mesenchymal transition (EMT) is a cell state transition co-opted by cancer that drives metastasis via stable intermediate states. Here we study EMT dynamics to identify marker genes of highly metastatic intermediate cells via mathematical modeling with single-cell RNA sequencing (scRNA-seq) data. Across multiple tumor types and stimuli, we identified genes consistently upregulated in EMT intermediate states, many previously unrecognized as EMT markers. Bayesian parameter inference of a simple EMT mathematical model revealed tumor-specific transition rates, providing a framework to quantify EMT progression. Consensus analysis of differential expression, RNA velocity, and model-derived dynamics highlighted SFN and NRG1 as key regulators of intermediate EMT. Independent validation confirmed SFN as an intermediate state marker. Our approach integrates modeling and inference to identify genes associated with EMT dynamics, offering biomarkers and therapeutic targets to modulate tumor-promoting cell state transitions driven by EMT.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"31"},"PeriodicalIF":3.5,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11986130/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144021011","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

Understanding therapeutic tolerance through a mathematical model of drug-induced resistance. 通过药物诱导耐药的数学模型了解治疗耐受性。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-04-10 DOI: 10.1038/s41540-025-00511-3

Jana L Gevertz, James M Greene, Samantha Prosperi, Natacha Comandante-Lou, Eduardo D Sontag

{"title":"Understanding therapeutic tolerance through a mathematical model of drug-induced resistance.","authors":"Jana L Gevertz, James M Greene, Samantha Prosperi, Natacha Comandante-Lou, Eduardo D Sontag","doi":"10.1038/s41540-025-00511-3","DOIUrl":"https://doi.org/10.1038/s41540-025-00511-3","url":null,"abstract":"There is growing recognition that phenotypic plasticity enables cancer cells to adapt to various environmental conditions. An example of this adaptability is the ability of an initially sensitive population of cancer cells to acquire resistance and persist in the presence of therapeutic agents. Understanding the implications of this drug-induced resistance is essential for predicting transient and long-term tumor dynamics subject to treatment. This paper introduces a mathematical model of drug-induced resistance which provides excellent fits to time-resolved in vitro experimental data. From observational data of total numbers of cells, the model unravels the relative proportions of sensitive and resistance subpopulations and quantifies their dynamics as a function of drug dose. The predictions are then validated using data on drug doses that were not used when fitting parameters. Optimal control techniques are then utilized to discover dosing strategies that could lead to better outcomes as quantified by lower total cell volume.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"30"},"PeriodicalIF":3.5,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11982405/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144003027","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

Exploring cell-to-cell variability and functional insights through differentially variable gene analysis. 通过差异变量基因分析探索细胞间的可变性和功能见解。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-03-20 DOI: 10.1038/s41540-025-00507-z

Victoria Gatlin, Shreyan Gupta, Selim Romero, Robert S Chapkin, James J Cai

{"title":"Exploring cell-to-cell variability and functional insights through differentially variable gene analysis.","authors":"Victoria Gatlin, Shreyan Gupta, Selim Romero, Robert S Chapkin, James J Cai","doi":"10.1038/s41540-025-00507-z","DOIUrl":"10.1038/s41540-025-00507-z","url":null,"abstract":"Single-cell RNA sequencing (scRNA-seq) has revolutionized our understanding of cellular variability by capturing gene expression profiles of individual cells. The importance of cell-to-cell variability in determining and shaping cell function has been widely appreciated. Nevertheless, differential expression (DE) analysis remains a cornerstone method in analytical practice. Current computational analyses overlook the rich information encoded by variability within the single-cell gene expression data by focusing exclusively on mean expression. To offer a deeper understanding of cellular systems, there is a need for approaches to assess data variability rather than just the mean. Here we present spline-DV, a statistical framework for differential variability (DV) analysis using scRNA-seq data. The spline-DV method identifies genes exhibiting significantly increased or decreased expression variability among cells derived from two experimental conditions. Case studies show that DV genes identified using spline-DV are representative and functionally relevant to tested cellular conditions, including obesity, fibrosis, and cancer.","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"29"},"PeriodicalIF":3.5,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11926233/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143670326","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

Plant cold acclimation and its impact on sensitivity of carbohydrate metabolism. 植物冷驯化及其对碳水化合物代谢敏感性的影响。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-03-19 DOI: 10.1038/s41540-025-00505-1

Stephan O Adler, Anastasia Kitashova, Ana Bulović, Thomas Nägele, Edda Klipp

引用次数: 0

A molecular systems architecture of neuromuscular junction in amyotrophic lateral sclerosis. 肌萎缩性侧索硬化症神经肌肉连接处的分子系统结构。

IF 3.5 2区生物学

NPJ Systems Biology and Applications Pub Date : 2025-03-17 DOI: 10.1038/s41540-025-00501-5

V A Shiva Ayyadurai, Prabhakar Deonikar, Roger D Kamm

引用次数: 0