Yi Qing Lee, Yoon-Mi Choi, Seo-Young Park, Su-Kyung Kim, Minouk Lee, Dongseok Kim, Lokanand Koduru, Meiyappan Lakshmanan, Sangyong Jung, Mi Jin Kim, Yon Ho Choe, Dong-Yup Lee
{"title":"Genome-scale metabolic model-guided systematic framework for designing customized live biotherapeutic products.","authors":"Yi Qing Lee, Yoon-Mi Choi, Seo-Young Park, Su-Kyung Kim, Minouk Lee, Dongseok Kim, Lokanand Koduru, Meiyappan Lakshmanan, Sangyong Jung, Mi Jin Kim, Yon Ho Choe, Dong-Yup Lee","doi":"10.1038/s41540-025-00555-5","DOIUrl":"10.1038/s41540-025-00555-5","url":null,"abstract":"<p><p>For the successful development of live biotherapeutic products (LBPs), which are promising microbiome-based therapeutics, it is required to rigorously evaluate their quality, safety, and efficacy. To this end, we present a model-guided framework where genome-scale metabolic models (GEMs) can be exploited for characterizing LBP candidate strains and their metabolic interactions with adjacent microbiome and host cells at a systems level. In this perspective, we outline a GEM-based strategy for screening, assessment, and design of personalized multi-strain LBPs.</p>","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"73"},"PeriodicalIF":3.5,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12234829/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144584438","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}
M R Patysheva, P S Iamshchikov, A A Fedorenko, O D Bragina, M A Vostrikova, E Y Garbukov, N V Cherdyntseva, E V Denisov, T S Gerashchenko
{"title":"Single-cell transcriptomic profiling of immune landscape in triple-negative breast cancer during neoadjuvant chemotherapy.","authors":"M R Patysheva, P S Iamshchikov, A A Fedorenko, O D Bragina, M A Vostrikova, E Y Garbukov, N V Cherdyntseva, E V Denisov, T S Gerashchenko","doi":"10.1038/s41540-025-00549-3","DOIUrl":"10.1038/s41540-025-00549-3","url":null,"abstract":"<p><p>Triple-negative breast cancer (TNBC) is the most aggressive subtype, typically requiring neoadjuvant chemotherapy (NAC) as an obligatory component of the treatment regimen. Achieving a pathological complete response to NAC is associated with improved long-term outcomes for patients with TNBC. The functional status of the immune system plays a critical role in NAC efficacy. Herein, we presented the investigation of systemic and local immune landscape during the initial course of NAC treatment and identify factors that contribute to chemotherapy resistance of TNBC. Using single-cell RNA sequencing, we demonstrated that the transcriptional profile remained stable in a patient who responded to NAC, while a non-responder exhibited significant dysregulation in the expression of genes involved in stress response, apoptosis, immune cell proliferation, and differentiation within lymphocyte and monocyte populations. During the first course of NAC, circulating cytotoxic CD8 T cells in the non-responder patient overexpressed granzymes B and H, granulysin, and perforin. In contrast, expression of these factors decreased in CD8 T cells within the tumor. Finally, we identified for a first time a signature of myeloid-derived suppressor cells (MDSC) within the S100А<sup>high</sup>MHC<sup>low</sup> monocyte population and calculated an MDSC score for both the responder and the non-responder TNBC patients. An elevated MDSC score in the non-responder was validated using data from an independent cohort of patients with poor NAC response. Our data underscores the importance of immune system functionality in determining chemotherapy efficacy in TNBC.</p>","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"72"},"PeriodicalIF":3.5,"publicationDate":"2025-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12234831/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144584439","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}
Wei He, Matthew D McCoy, Rebecca B Riggins, Robert A Beckman, Chen-Hsiang Yeang
{"title":"Personalized cancer treatment strategies incorporating irreversible and reversible drug resistance mechanisms.","authors":"Wei He, Matthew D McCoy, Rebecca B Riggins, Robert A Beckman, Chen-Hsiang Yeang","doi":"10.1038/s41540-025-00547-5","DOIUrl":"10.1038/s41540-025-00547-5","url":null,"abstract":"<p><p>Despite advances in targeted cancer therapy, the promise of precision medicine has been limited by resistance to these treatments. In this study, we propose a mathematical modelling framework incorporating cellular heterogeneity, genetic evolutionary dynamics, and non-genetic plasticity, accounting for both irreversible and reversible drug resistance. Previously we proposed Dynamic Precision Medicine (DPM), a personalized treatment strategy that designed individualized treatment sequences by simulations of irreversible genetic evolutionary dynamics in a heterogeneous tumor. Here we apply DPM to the joint model of reversible and irreversible drug resistance mechanisms, analyze the simulation results and compare the efficacy of various treatment strategies. The results indicate that this enhanced version of DPM significantly outperforms current personalized medicine treatment approaches. Our results provide insights into cancer treatment strategies for heterogeneous tumors with genetic evolutionary dynamics and non-genetic cellular plasticity, potentially leading to improvements in survival time for cancer patients.</p>","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"70"},"PeriodicalIF":3.5,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12226727/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144560626","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}
Massimiliano Zanin, Bruno F R Santos, Paul M A Antony, Clara Berenguer-Escuder, Simone B Larsen, Zoé Hanss, Peter A Barbuti, Aidos S Baumuratov, Dajana Grossmann, Christophe M Capelle, Joseph Weber, Rudi Balling, Markus Ollert, Rejko Krüger, Nico J Diederich, Feng Q HeFeng
{"title":"Author Correction: Mitochondria interaction networks show altered topological patterns in Parkinson's disease.","authors":"Massimiliano Zanin, Bruno F R Santos, Paul M A Antony, Clara Berenguer-Escuder, Simone B Larsen, Zoé Hanss, Peter A Barbuti, Aidos S Baumuratov, Dajana Grossmann, Christophe M Capelle, Joseph Weber, Rudi Balling, Markus Ollert, Rejko Krüger, Nico J Diederich, Feng Q HeFeng","doi":"10.1038/s41540-025-00552-8","DOIUrl":"10.1038/s41540-025-00552-8","url":null,"abstract":"","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"71"},"PeriodicalIF":3.5,"publicationDate":"2025-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12229510/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144560625","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}
{"title":"Temporal analysis of doxorubicin-induced cardiac toxicity and hypertrophy.","authors":"Yu-Te Lin, Yi-Ju Lee, Wen-Wei Tseng, Zih-Hua Chen, Huai-Ching Hsieh, Ko-Hong Lin, Jin-Yu Su, An-Chi Wei","doi":"10.1038/s41540-025-00545-7","DOIUrl":"10.1038/s41540-025-00545-7","url":null,"abstract":"<p><p>Doxorubicin (DOX), although effective in treating cancer, has significant cardiac side effects, which limit its clinical utility. In this study, we collected time-course transcriptomics and metabolomics data from the human cardiomyocyte cell line AC16, which we analyzed along with curated public transcriptomics data on DOX-induced toxicity. We developed a multiomics analysis workflow and a computational toolbox, pipeGEM, to integrate RNA-seq data with metabolic models, enabling the simulation of DOX-induced metabolic perturbations at a sample-specific level. Our results revealed that DOX affected mitochondrial damage and mitochondria-to-nucleus retrograde signaling, potentially contributing to the observed cellular enlargement, senescence and metabolic shift. Cardiac cells that survived DOX treatment presented elevated glycolysis, increased pentose phosphate pathway activity, an altered TCA cycle, and modified glutathione and fatty acid metabolism. These findings provide a comprehensive understanding of DOX-induced toxicity and its implications for cardiac hypertrophy, suggesting potential strategies to mitigate side effects while retaining the anticancer efficacy of DOX.</p>","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"67"},"PeriodicalIF":3.5,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12219892/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144541617","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}
{"title":"A supervised machine learning approach with feature selection for sex-specific biomarker prediction.","authors":"Luke Meyer, Danielle Mulder, Joshua Wallace","doi":"10.1038/s41540-025-00523-z","DOIUrl":"10.1038/s41540-025-00523-z","url":null,"abstract":"<p><p>Biomarkers are crucial in aiding in disease diagnosis, prognosis, and treatment selection. Machine learning (ML) has emerged as an effective tool for identifying novel biomarkers and enhancing predictive modelling. However, sex-based bias in ML algorithms remains a concern. This study developed a supervised ML model to predict nine common clinical biomarkers, including triglycerides, BMI, waist circumference, systolic blood pressure, blood glucose, uric acid, urinary albumin-to-creatinine ratio, high-density lipoproteins, and albuminuria. The model's predictions were within 5-10% error of actual values. For predictions within 10% error, the top performing models were waist circumference, albuminuria, BMI, blood glucose and systolic blood pressure, with males scoring higher than females, followed by the combined data set containing sex as an input feature and the combined data without sex as an input feature performing the poorest. This study highlighted the benefits of stratifying data according to sex for ML based models.</p>","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"69"},"PeriodicalIF":3.5,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12219308/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144541615","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}
Helena Braunstein, Alejandra C Ventura, Alejandro Colman-Lerner
{"title":"Modeling the use of transient ligand binding information by AMPA receptors.","authors":"Helena Braunstein, Alejandra C Ventura, Alejandro Colman-Lerner","doi":"10.1038/s41540-025-00546-6","DOIUrl":"10.1038/s41540-025-00546-6","url":null,"abstract":"<p><p>Glutamate mediates fast excitatory neurotransmission through α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid (AMPA)-type glutamate receptors in the central nervous system. Although it is well known that the glutamate affinity for AMPA receptors is submicromolar, ligand-dependent currents are observed only at submillimolar glutamate concentrations, suggesting a non-equilibrium mechanism of dose-dependent signaling. Here, we developed a mathematical model that leverages published reaction rates to demonstrate that AMPA receptors operate within a pre-equilibrium sensing and signaling (PRESS) regime. By functioning before equilibrium binding, AMPARs exploit a transient dynamic range at high ligand concentrations. Our model reveals that fast desensitization is a key transition enabling this PRESS mechanism. Regulators of this desensitization, such as transmembrane AMPAR regulatory proteins TARP, germ cell-specific gene 1-like protein and cornichon homolog auxiliary proteins (CNIH2/3), thus modulate AMPAR dynamic range by modifying the time window in which these receptors may use pre-equilibrium information. We speculate that the use of PRESS by AMPARs helps restrict the postsynaptic area of action of this fast transmission. Other receptors with fast desensitization may also take advantage of PRESS to accurately control dose-dependent responses.</p>","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"68"},"PeriodicalIF":3.5,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12218799/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144541616","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}
Roberta Maria Lorenzi, Fulvia Palesi, Claudia Casellato, Claudia A M Gandini Wheeler-Kingshott, Egidio D'Angelo
{"title":"Region-specific mean field models enhance simulations of local and global brain dynamics.","authors":"Roberta Maria Lorenzi, Fulvia Palesi, Claudia Casellato, Claudia A M Gandini Wheeler-Kingshott, Egidio D'Angelo","doi":"10.1038/s41540-025-00543-9","DOIUrl":"10.1038/s41540-025-00543-9","url":null,"abstract":"<p><p>Brain dynamics can be simulated using virtual brain models, in which a standard mathematical representation of oscillatory activity is usually adopted for all cortical and subcortical regions. However, some brain regions have specific microcircuit properties that are not recapitulated by standard oscillators. Moreover, magnetic resonance imaging (MRI)-based connectomes may not be able to capture local circuit connectivity. Region-specific models incorporating computational properties of local neurons and microcircuits have recently been generated using the mean field (MF) approach and proposed to impact large-scale brain dynamics. Here, we have used a MF of the cerebellar cortex to generate a mesoscopic model of the whole cerebellum featuring a prewired connectivity of multiple cerebellar cortical areas with deep cerebellar nuclei. This multi-node cerebellar MF was then used to substitute the corresponding standard oscillators and build up a cerebellar mean field virtual brain (cMF-TVB) for a group of healthy human subjects. Simulations revealed that electrophysiological and fMRI signals generated by the cMF-TVB significantly improved the fitness of local and global dynamics with respect to a homogeneous model made solely of standard oscillators. The cMF-TVB reproduced the rhythmic oscillations and coherence typical of the cerebellar circuit and allowed to correlate electrophysiological and functional MRI signals to specific neuronal populations. In aggregate, region-specific models based on MF and pre-wired circuit connectivity can significantly improve virtual brain simulations, fostering the generation of effective brain digital twins that could be used for physiological studies and clinical applications.</p>","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"66"},"PeriodicalIF":3.5,"publicationDate":"2025-06-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12187921/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144485215","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}
{"title":"Automated model refinement using perturbation-observation pairs.","authors":"Kyu Hyong Park, Jordan C Rozum, Réka Albert","doi":"10.1038/s41540-025-00532-y","DOIUrl":"10.1038/s41540-025-00532-y","url":null,"abstract":"<p><p>In modeling signal transduction networks, it is common to manually integrate experimental evidence through a process that involves trial and error constrained by domain knowledge. We implement a genetic algorithm-based workflow (boolmore) to streamline Boolean model refinement. Boolmore adjusts the functions of the model to enhance agreement with a corpus of curated perturbation-observation pairs. It leverages existing mechanistic knowledge to automatically limit the search space to biologically plausible models. We demonstrate boolmore's effectiveness in a published plant signaling model that exemplifies the challenges of manual model construction and refinement. The refined models surpass the accuracy gain achieved over two years of manual revision and yield new, testable predictions. By automating the laborious task of model validation and refinement, this workflow is a step towards fast, fully automated, and reliable model construction.</p>","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"65"},"PeriodicalIF":3.5,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12170832/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144310236","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}
Gianmarco Rasi, Elena Emili, Jessica M Conway, Nicola Cotugno, Paolo Palma
{"title":"Mathematical modeling and mechanisms of HIV latency for personalized anti latency therapies.","authors":"Gianmarco Rasi, Elena Emili, Jessica M Conway, Nicola Cotugno, Paolo Palma","doi":"10.1038/s41540-025-00538-6","DOIUrl":"10.1038/s41540-025-00538-6","url":null,"abstract":"<p><p>Combination antiretroviral therapy controls human immunodeficiency virus-1 (HIV) but cannot eradicate latent proviruses in immune cells, which reactivate upon treatment interruption. Anti-latency therapies like \"shock-and-kill\" are being developed but are yet to succeed due to the complexity of latency mechanisms. This review discusses recent advances in understanding HIV latency via mathematical modeling, covering key regulatory factors and models to predict latency reversal, highlighting gaps to guide future therapeutic approaches.</p>","PeriodicalId":19345,"journal":{"name":"NPJ Systems Biology and Applications","volume":"11 1","pages":"64"},"PeriodicalIF":3.5,"publicationDate":"2025-06-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12162841/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144285823","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}