{"title":"Enhanced flux potential analysis links changes in enzyme expression to metabolic flux.","authors":"Xuhang Li, Albertha J M Walhout, L Safak Yilmaz","doi":"10.1038/s44320-025-00090-9","DOIUrl":"https://doi.org/10.1038/s44320-025-00090-9","url":null,"abstract":"<p><p>Algorithms that constrain metabolic network models with enzyme levels to predict metabolic activity assume that changes in enzyme levels are indicative of flux variations. However, metabolic flux can also be regulated by other mechanisms such as allostery and mass action. To systematically explore the relationship between fluctuations in enzyme expression and flux, we combine available yeast proteomic and fluxomic data to reveal that flux changes can be best predicted from changes in enzyme levels of pathways, rather than the whole network or only cognate reactions. We implement this principle in an 'enhanced flux potential analysis' (eFPA) algorithm that integrates enzyme expression data with metabolic network architecture to predict relative flux levels of reactions including those regulated by other mechanisms. Applied to human data, eFPA consistently predicts tissue metabolic function using either proteomic or transcriptomic data. Additionally, eFPA efficiently handles data sparsity and noisiness, generating robust flux predictions with single-cell gene expression data. Our approach outperforms alternatives by striking an optimal balance, evaluating enzyme expression at pathway level, rather than either single-reaction or whole-network levels.</p>","PeriodicalId":18906,"journal":{"name":"Molecular Systems Biology","volume":" ","pages":""},"PeriodicalIF":8.5,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143441542","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}
Marco Stock, Corinna Losert, Matteo Zambon, Niclas Popp, Gabriele Lubatti, Eva Hörmanseder, Matthias Heinig, Antonio Scialdone
{"title":"Leveraging prior knowledge to infer gene regulatory networks from single-cell RNA-sequencing data.","authors":"Marco Stock, Corinna Losert, Matteo Zambon, Niclas Popp, Gabriele Lubatti, Eva Hörmanseder, Matthias Heinig, Antonio Scialdone","doi":"10.1038/s44320-025-00088-3","DOIUrl":"https://doi.org/10.1038/s44320-025-00088-3","url":null,"abstract":"<p><p>Many studies have used single-cell RNA sequencing (scRNA-seq) to infer gene regulatory networks (GRNs), which are crucial for understanding complex cellular regulation. However, the inherent noise and sparsity of scRNA-seq data present significant challenges to accurate GRN inference. This review explores one promising approach that has been proposed to address these challenges: integrating prior knowledge into the inference process to enhance the reliability of the inferred networks. We categorize common types of prior knowledge, such as experimental data and curated databases, and discuss methods for representing priors, particularly through graph structures. In addition, we classify recent GRN inference algorithms based on their ability to incorporate these priors and assess their performance in different contexts. Finally, we propose a standardized benchmarking framework to evaluate algorithms more fairly, ensuring biologically meaningful comparisons. This review provides guidance for researchers selecting GRN inference methods and offers insights for developers looking to improve current approaches and foster innovation in the field.</p>","PeriodicalId":18906,"journal":{"name":"Molecular Systems Biology","volume":" ","pages":""},"PeriodicalIF":8.5,"publicationDate":"2025-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143409153","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}
Zhong Yao, Jiyoon Kim, Betty Geng, Jinkun Chen, Victoria Wong, Anna Lyakisheva, Jamie Snider, Marina Rudan Dimlić, Sanda Raić, Igor Stagljar
{"title":"A split intein and split luciferase-coupled system for detecting protein-protein interactions.","authors":"Zhong Yao, Jiyoon Kim, Betty Geng, Jinkun Chen, Victoria Wong, Anna Lyakisheva, Jamie Snider, Marina Rudan Dimlić, Sanda Raić, Igor Stagljar","doi":"10.1038/s44320-024-00081-2","DOIUrl":"10.1038/s44320-024-00081-2","url":null,"abstract":"<p><p>Elucidation of protein-protein interactions (PPIs) represents one of the most important methods in biomedical research. Recently, PPIs have started to be exploited for drug discovery purposes and have thus attracted much attention from both the academic and pharmaceutical sectors. We previously developed a sensitive method, Split Intein-Mediated Protein Ligation (SIMPL), for detecting binary PPIs via irreversible splicing of the interacting proteins being investigated. Here, we incorporated tripart nanoluciferase (tNLuc) into the system, providing a luminescence signal which, in conjunction with homogenous liquid phase operation, improves the quantifiability and operability of the assay. Using a reference PPI set, we demonstrated an improvement in both sensitivity and specificity over the original SIMPL assay. Moreover, we designed the new SIMPL-tNLuc ('SIMPL2') platform with an inherent modularity allowing for flexible measurement of molecular modulators of target PPIs, including inhibitors, molecular glues and PROTACs. Our results demonstrate that SIMPL2 is a sensitive, cost- and labor-effective tool suitable for high-throughput screening (HTS) in both PPI mapping and drug discovery applications.</p>","PeriodicalId":18906,"journal":{"name":"Molecular Systems Biology","volume":" ","pages":"107-125"},"PeriodicalIF":8.5,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11791039/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142818697","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}
Abel Jansma, Yuelin Yao, Jareth Wolfe, Luigi Del Debbio, Sjoerd V Beentjes, Chris P Ponting, Ava Khamseh
{"title":"High order expression dependencies finely resolve cryptic states and subtypes in single cell data.","authors":"Abel Jansma, Yuelin Yao, Jareth Wolfe, Luigi Del Debbio, Sjoerd V Beentjes, Chris P Ponting, Ava Khamseh","doi":"10.1038/s44320-024-00074-1","DOIUrl":"10.1038/s44320-024-00074-1","url":null,"abstract":"<p><p>Single cells are typically typed by clustering into discrete locations in reduced dimensional transcriptome space. Here we introduce Stator, a data-driven method that identifies cell (sub)types and states without relying on cells' local proximity in transcriptome space. Stator labels the same single cell multiply, not just by type and subtype, but also by state such as activation, maturity or cell cycle sub-phase, through deriving higher-order gene expression dependencies from a sparse gene-by-cell expression matrix. Stator's finer resolution is clear from analyses of mouse embryonic brain, and human healthy or diseased liver. Rather than only coarse-scale labels of cell type, Stator further resolves cell types into subtypes, and these subtypes into stages of maturity and/or cell cycle phases, and yet further into portions of these phases. Among cryptically homogeneous embryonic cells, for example, Stator finds 34 distinct radial glia states whose gene expression forecasts their future GABAergic or glutamatergic neuronal fate. Further, Stator's fine resolution of liver cancer states reveals expression programmes that predict patient survival. We provide Stator as a Nextflow pipeline and Shiny App.</p>","PeriodicalId":18906,"journal":{"name":"Molecular Systems Biology","volume":" ","pages":"173-207"},"PeriodicalIF":8.5,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11790937/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142922177","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}
Kate Sokolina, Saranya Kittanakom, Jamie Snider, Max Kotlyar, Pascal Maurice, Jorge Gandía, Abla Benleulmi-Chaachoua, Kenjiro Tadagaki, Atsuro Oishi, Victoria Wong, Ramy H Malty, Viktor Deineko, Hiroyuki Aoki, Shahreen Amin, Zhong Yao, Xavier Morató, David Otasek, Hiroyuki Kobayashi, Javier Menendez, Daniel Auerbach, Stephane Angers, Natasa Pržulj, Michel Bouvier, Mohan Babu, Francisco Ciruela, Ralf Jockers, Igor Jurisica, Igor Stagljar
{"title":"Author Correction: Systematic protein-protein interaction mapping for clinically relevant human GPCRs.","authors":"Kate Sokolina, Saranya Kittanakom, Jamie Snider, Max Kotlyar, Pascal Maurice, Jorge Gandía, Abla Benleulmi-Chaachoua, Kenjiro Tadagaki, Atsuro Oishi, Victoria Wong, Ramy H Malty, Viktor Deineko, Hiroyuki Aoki, Shahreen Amin, Zhong Yao, Xavier Morató, David Otasek, Hiroyuki Kobayashi, Javier Menendez, Daniel Auerbach, Stephane Angers, Natasa Pržulj, Michel Bouvier, Mohan Babu, Francisco Ciruela, Ralf Jockers, Igor Jurisica, Igor Stagljar","doi":"10.1038/s44320-024-00080-3","DOIUrl":"10.1038/s44320-024-00080-3","url":null,"abstract":"","PeriodicalId":18906,"journal":{"name":"Molecular Systems Biology","volume":"21 2","pages":"208-209"},"PeriodicalIF":8.5,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11790839/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143123016","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}
Seo Jung Hong, Samuel J Resnick, Sho Iketani, Ji Won Cha, Benjamin Alexander Albert, Christopher T Fazekas, Ching-Wen Chang, Hengrui Liu, Shlomi Dagan, Michael R Abagyan, Pavla Fajtová, Bruce Culbertson, Brooklyn Brace, Eswar R Reddem, Farhad Forouhar, J Fraser Glickman, James M Balkovec, Brent R Stockwell, Lawrence Shapiro, Anthony J O'Donoghue, Yosef Sabo, Joel S Freundlich, David D Ho, Alejandro Chavez
{"title":"A multiplex method for rapidly identifying viral protease inhibitors.","authors":"Seo Jung Hong, Samuel J Resnick, Sho Iketani, Ji Won Cha, Benjamin Alexander Albert, Christopher T Fazekas, Ching-Wen Chang, Hengrui Liu, Shlomi Dagan, Michael R Abagyan, Pavla Fajtová, Bruce Culbertson, Brooklyn Brace, Eswar R Reddem, Farhad Forouhar, J Fraser Glickman, James M Balkovec, Brent R Stockwell, Lawrence Shapiro, Anthony J O'Donoghue, Yosef Sabo, Joel S Freundlich, David D Ho, Alejandro Chavez","doi":"10.1038/s44320-024-00082-1","DOIUrl":"10.1038/s44320-024-00082-1","url":null,"abstract":"<p><p>With current treatments addressing only a fraction of pathogens and new viral threats constantly evolving, there is a critical need to expand our existing therapeutic arsenal. To speed the rate of discovery and better prepare against future threats, we establish a high-throughput platform capable of screening compounds against 40 diverse viral proteases simultaneously. This multiplex approach is enabled by using cellular biosensors of viral protease activity combined with DNA-barcoding technology, as well as several design innovations that increase assay sensitivity and correct for plate-to-plate variation. Among >100,000 compound-target interactions explored within our initial screen, a series of broad-acting inhibitors against coronavirus proteases were uncovered and validated through orthogonal assays. A medicinal chemistry campaign was performed to improve one of the inhibitor's potency while maintaining its broad activity. This work highlights the power of multiplex screening to efficiently explore chemical space at a fraction of the time and costs of previous approaches.</p>","PeriodicalId":18906,"journal":{"name":"Molecular Systems Biology","volume":"21 2","pages":"158-172"},"PeriodicalIF":8.5,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11790949/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143123003","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}
Ralitsa R Madsen, Alix Le Marois, Oliwia N Mruk, Margaritis Voliotis, Shaozhen Yin, Jahangir Sufi, Xiao Qin, Salome J Zhao, Julia Gorczynska, Daniele Morelli, Lindsay Davidson, Erik Sahai, Viktor I Korolchuk, Christopher J Tape, Bart Vanhaesebroeck
{"title":"Oncogenic PIK3CA corrupts growth factor signaling specificity.","authors":"Ralitsa R Madsen, Alix Le Marois, Oliwia N Mruk, Margaritis Voliotis, Shaozhen Yin, Jahangir Sufi, Xiao Qin, Salome J Zhao, Julia Gorczynska, Daniele Morelli, Lindsay Davidson, Erik Sahai, Viktor I Korolchuk, Christopher J Tape, Bart Vanhaesebroeck","doi":"10.1038/s44320-024-00078-x","DOIUrl":"10.1038/s44320-024-00078-x","url":null,"abstract":"<p><p>Technical limitations have prevented understanding of how growth factor signals are encoded in distinct activity patterns of the phosphoinositide 3-kinase (PI3K)/AKT pathway, and how this is altered by oncogenic pathway mutations. We introduce a kinetic, single-cell framework for precise calculations of PI3K-specific information transfer for different growth factors. This features live-cell imaging of PI3K/AKT activity reporters and multiplexed CyTOF measurements of PI3K/AKT and RAS/ERK signaling markers over time. Using this framework, we found that the PIK3CA<sup>H1047R</sup> oncogene was not a simple, constitutive activator of the pathway as often presented. Dose-dependent expression of PIK3CA<sup>H1047R</sup> in human cervical cancer and induced pluripotent stem cells corrupted the fidelity of growth factor-induced information transfer, with preferential amplification of epidermal growth factor receptor (EGFR) signaling responses compared to insulin-like growth factor 1 (IGF1) and insulin receptor signaling. PIK3CA<sup>H1047R</sup> did not only shift these responses to a higher mean but also enhanced signaling heterogeneity. We conclude that oncogenic PIK3CA<sup>H1047R</sup> corrupts information transfer in a growth factor-dependent manner and suggest new opportunities for tuning of receptor-specific PI3K pathway outputs for therapeutic benefit.</p>","PeriodicalId":18906,"journal":{"name":"Molecular Systems Biology","volume":" ","pages":"126-157"},"PeriodicalIF":8.5,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11791070/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142872589","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}
Tomer Milo, Shiraz Nir Halber, Moriya Raz, Dor Danan, Avi Mayo, Uri Alon
{"title":"Hormone circuit explains why most HPA drugs fail for mood disorders and predicts the few that work.","authors":"Tomer Milo, Shiraz Nir Halber, Moriya Raz, Dor Danan, Avi Mayo, Uri Alon","doi":"10.1038/s44320-024-00083-0","DOIUrl":"https://doi.org/10.1038/s44320-024-00083-0","url":null,"abstract":"<p><p>Elevated cortisol in chronic stress and mood disorders causes morbidity including metabolic and cardiovascular diseases. There is therefore interest in developing drugs that lower cortisol by targeting its endocrine pathway, the hypothalamic-pituitary-adrenal (HPA) axis. However, several promising HPA-modulating drugs have failed to reduce long-term cortisol in mood disorders, despite effectiveness in other hypercortisolism conditions such as Cushing's syndrome. The reasons for these failures remain unclear. Here, we use a mathematical model of the HPA axis to demonstrate that the pituitary and adrenal glands compensate for drug effects by adjusting their functional mass, a feedback mechanism absent in Cushing tumors. Our systematic in silico analysis identifies two interventions targeting corticotropin-releasing hormone (CRH) as effective for lowering long-term cortisol. Other targets either fail due to gland mass compensation or harm other aspects of the HPA axis. We propose CRH-neutralizing antibodies and CRH-synthesis inhibitors as potential targets for reducing long-term cortisol in mood disorders and chronic stress. More generally, this study indicates that understanding the slow compensatory mechanisms in endocrine axes can be crucial to prioritize drug targets.</p>","PeriodicalId":18906,"journal":{"name":"Molecular Systems Biology","volume":" ","pages":""},"PeriodicalIF":8.5,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143029179","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}
Stefanie Höfer, Larissa Frasch, Sarah Brajkovic, Kerstin Putzker, Joe Lewis, Hendrik Schürmann, Valentina Leone, Amirhossein Sakhteman, Matthew The, Florian P Bayer, Julian Müller, Firas Hamood, Jens T Siveke, Maximilian Reichert, Bernhard Kuster
{"title":"Gemcitabine and ATR inhibitors synergize to kill PDAC cells by blocking DNA damage response.","authors":"Stefanie Höfer, Larissa Frasch, Sarah Brajkovic, Kerstin Putzker, Joe Lewis, Hendrik Schürmann, Valentina Leone, Amirhossein Sakhteman, Matthew The, Florian P Bayer, Julian Müller, Firas Hamood, Jens T Siveke, Maximilian Reichert, Bernhard Kuster","doi":"10.1038/s44320-025-00085-6","DOIUrl":"https://doi.org/10.1038/s44320-025-00085-6","url":null,"abstract":"<p><p>The DNA-damaging agent Gemcitabine (GEM) is a first-line treatment for pancreatic cancer, but chemoresistance is frequently observed. Several clinical trials investigate the efficacy of GEM in combination with targeted drugs, including kinase inhibitors, but the experimental evidence for such rationale is often unclear. Here, we phenotypically screened 13 human pancreatic adenocarcinoma (PDAC) cell lines against GEM in combination with 146 clinical inhibitors and observed strong synergy for the ATR kinase inhibitor Elimusertib in most cell lines. Dose-dependent phosphoproteome profiling of four ATR inhibitors following DNA damage induction by GEM revealed a strong block of the DNA damage response pathway, including phosphorylated pS468 of CHEK1, as the underlying mechanism of drug synergy. The current work provides a strong rationale for why the combination of GEM and ATR inhibition may be useful for the treatment of PDAC patients and constitutes a rich phenotypic and molecular resource for further investigating effective drug combinations.</p>","PeriodicalId":18906,"journal":{"name":"Molecular Systems Biology","volume":" ","pages":""},"PeriodicalIF":8.5,"publicationDate":"2025-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143008697","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}
{"title":"Epigenetic modifications and metabolic gene mutations drive resistance evolution in response to stimulatory antibiotics.","authors":"Hui Lin, Donglin Wang, Qiaojuan Wang, Jie Mao, Lutong Yang, Yaohui Bai, Jiuhui Qu","doi":"10.1038/s44320-025-00087-4","DOIUrl":"https://doi.org/10.1038/s44320-025-00087-4","url":null,"abstract":"<p><p>The antibiotic resistance crisis, fueled by misuse and bacterial evolution, is a major global health threat. Traditional perspectives tie resistance to drug target mechanisms, viewing antibiotics as mere growth inhibitors. New insights revealed that low-dose antibiotics may also serve as signals, unexpectedly promoting bacterial growth. Yet, the development of resistance under these conditions remains unknown. Our study investigated resistance evolution under stimulatory antibiotics and uncovered new genetic mechanisms of resistance linked to metabolic remodeling. We documented a shift from a fast, reversible mechanism driven by methylation in central metabolic pathways to a slower, stable mechanism involving mutations in key metabolic genes. Both mechanisms contribute to a metabolic profile transition from glycolysis to rapid gluconeogenesis. In addition, our findings demonstrated that rising environmental temperatures associated with metabolic evolution accelerated this process, increasing the prevalence of metabolic gene mutations, albeit with a trade-off in interspecific fitness. These findings expand beyond the conventional understanding of resistance mechanisms, proposing a broader metabolic mechanism within the selective window of stimulatory sub-MIC antibiotics, particularly in the context of climate change.</p>","PeriodicalId":18906,"journal":{"name":"Molecular Systems Biology","volume":" ","pages":""},"PeriodicalIF":8.5,"publicationDate":"2025-01-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143008695","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}
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