Pub Date : 2024-03-01DOI: 10.3389/fsysb.2024.1346076
Jonatan Blais, Julie Jeukens
One of the main challenges in cancer treatment is the selection of treatment resistant clones which leads to the emergence of resistance to previously efficacious therapies. Identifying vulnerabilities in the form of cellular trade-offs constraining the phenotypic possibility space could allow to avoid the emergence of resistance by simultaneously targeting cellular processes that are involved in different alternative phenotypic strategies linked by trade-offs. The Pareto optimality theory has been proposed as a framework allowing to identify such trade-offs in biological data from its prediction that it would lead to the presence of specific geometrical patterns (polytopes) in, e.g., gene expression space, with vertices representing specialized phenotypes. We tested this approach in diffuse large B-cell lymphoma (DLCBL) transcriptomic data. As predicted, there was highly statistically significant evidence for the data forming a tetrahedron in gene expression space, defining four specialized phenotypes (archetypes). These archetypes were significantly enriched in certain biological functions, and contained genes that formed a pattern of shared and unique elements among archetypes, as expected if trade-offs between essential functions underlie the observed structure. The results can be interpreted as reflecting trade-offs between aerobic energy production and protein synthesis, and between immunotolerant and immune escape strategies. Targeting genes on both sides of these trade-offs simultaneously represent potential promising avenues for therapeutic applications.
癌症治疗面临的主要挑战之一是耐药克隆的选择，这导致对以前有效的疗法产生抗药性。以细胞权衡的形式识别限制表型可能性空间的弱点，可以通过同时针对参与由权衡联系在一起的不同替代表型策略的细胞过程来避免抗药性的出现。帕累托最优化理论被认为是一种框架，它可以识别生物数据中的这种权衡，因为它预测在基因表达空间等方面会出现特定的几何模式（多面体），其顶点代表专门的表型。我们在弥漫大 B 细胞淋巴瘤（DLCBL）转录组数据中测试了这种方法。正如预测的那样，数据在基因表达空间中形成了一个四面体，定义了四种特化表型（原型），这在统计学上具有非常显著的证据。这些原型明显富集了某些生物功能，并包含了在原型之间形成共享和独特元素模式的基因，如果基本功能之间的权衡是所观察到的结构的基础，那么就会出现这种情况。这些结果可以解释为反映了有氧能量生产和蛋白质合成之间的权衡，以及免疫耐受和免疫逃逸策略之间的权衡。同时以这些权衡两边的基因为靶标，是治疗应用的潜在可行途径。
{"title":"Pareto task inference analysis reveals cellular trade-offs in diffuse large B-Cell lymphoma transcriptomic data","authors":"Jonatan Blais, Julie Jeukens","doi":"10.3389/fsysb.2024.1346076","DOIUrl":"https://doi.org/10.3389/fsysb.2024.1346076","url":null,"abstract":"One of the main challenges in cancer treatment is the selection of treatment resistant clones which leads to the emergence of resistance to previously efficacious therapies. Identifying vulnerabilities in the form of cellular trade-offs constraining the phenotypic possibility space could allow to avoid the emergence of resistance by simultaneously targeting cellular processes that are involved in different alternative phenotypic strategies linked by trade-offs. The Pareto optimality theory has been proposed as a framework allowing to identify such trade-offs in biological data from its prediction that it would lead to the presence of specific geometrical patterns (polytopes) in, e.g., gene expression space, with vertices representing specialized phenotypes. We tested this approach in diffuse large B-cell lymphoma (DLCBL) transcriptomic data. As predicted, there was highly statistically significant evidence for the data forming a tetrahedron in gene expression space, defining four specialized phenotypes (archetypes). These archetypes were significantly enriched in certain biological functions, and contained genes that formed a pattern of shared and unique elements among archetypes, as expected if trade-offs between essential functions underlie the observed structure. The results can be interpreted as reflecting trade-offs between aerobic energy production and protein synthesis, and between immunotolerant and immune escape strategies. Targeting genes on both sides of these trade-offs simultaneously represent potential promising avenues for therapeutic applications.","PeriodicalId":73109,"journal":{"name":"Frontiers in systems biology","volume":"25 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140086210","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-27DOI: 10.3389/fsysb.2024.1363884
Rahuman S. Malik Sheriff, Hiroki Asari, Henning Hermjakob, Wolfgang Huber, Thomas Quail, Silvia D. M. Santos, Amber M. Smith, Virginie Uhlmann
Mathematical modeling is a pivotal tool for deciphering the complexities of biological systems and their control mechanisms, providing substantial benefits for industrial applications and answering relevant biological questions. BioModels’ Model of the Year 2023 competition was established to recognize and highlight exciting modeling-based research in the life sciences, particularly by non-independent early-career researchers. It further aims to endorse reproducibility and FAIR principles of model sharing among these researchers. We here delineate the competition’s criteria for participation and selection, introduce the award recipients, and provide an overview of their contributions. Their models provide crucial insights into cell division regulation, protein stability, and cell fate determination, illustrating the role of mathematical modeling in advancing biological research.
{"title":"BioModels’ Model of the Year 2023","authors":"Rahuman S. Malik Sheriff, Hiroki Asari, Henning Hermjakob, Wolfgang Huber, Thomas Quail, Silvia D. M. Santos, Amber M. Smith, Virginie Uhlmann","doi":"10.3389/fsysb.2024.1363884","DOIUrl":"https://doi.org/10.3389/fsysb.2024.1363884","url":null,"abstract":"Mathematical modeling is a pivotal tool for deciphering the complexities of biological systems and their control mechanisms, providing substantial benefits for industrial applications and answering relevant biological questions. BioModels’ Model of the Year 2023 competition was established to recognize and highlight exciting modeling-based research in the life sciences, particularly by non-independent early-career researchers. It further aims to endorse reproducibility and FAIR principles of model sharing among these researchers. We here delineate the competition’s criteria for participation and selection, introduce the award recipients, and provide an overview of their contributions. Their models provide crucial insights into cell division regulation, protein stability, and cell fate determination, illustrating the role of mathematical modeling in advancing biological research.","PeriodicalId":73109,"journal":{"name":"Frontiers in systems biology","volume":"3 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140424979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-15DOI: 10.3389/fsysb.2024.1266279
Ashti M. Shah, R. Zamora, Derek A. Barclay, Jinling Yin, Fayten el-Dehaibi, M. Addorisio, T. Tsaava, A. Tynan, Kevin Tracey, Sangeeta Chavan, Y. Vodovotz
Introduction: The vagus nerve innervates multiple organs, but its role in regulating cross-tissue spread of inflammation is as yet unclear. We hypothesized that the vagus nerve may regulate cross-tissue inflammation via modulation of the putatively neurally regulated chemokine IP-10/CXCL10.Methods: Rate-of-change analysis, dynamic network analysis, and dynamic hypergraphs were used to model intra- and inter-tissue trends, respectively, in inflammatory mediators from mice that underwent either vagotomy or sham surgery.Results: This analysis suggested that vagotomy primarily disrupts the cross-tissue attenuation of inflammatory networks involving IP-10 as well as the chemokines MIG/CXCL9 and CCL2/MCP-1 along with the cytokines IFN-γ and IL-6. Computational analysis also suggested that the vagus-dependent rate of expression of IP-10 and MIG/CXCL9 in the spleen impacts the trajectory of chemokine expression in other tissues. Perturbation of this complex system with bacterial lipopolysaccharide (LPS) revealed a vagally regulated role for MIG in the heart. Further, LPS-stimulated expression of IP-10 was inferred to be vagus-independent across all tissues examined while reducing connectivity to IL-6 and MCP-1, a hypothesis supported by Boolean network modeling.Discussion: Together, these studies define novel spatiotemporal dimensions of vagus-regulated acute inflammation.
{"title":"Computational inference of chemokine-mediated roles for the vagus nerve in modulating intra- and inter-tissue inflammation","authors":"Ashti M. Shah, R. Zamora, Derek A. Barclay, Jinling Yin, Fayten el-Dehaibi, M. Addorisio, T. Tsaava, A. Tynan, Kevin Tracey, Sangeeta Chavan, Y. Vodovotz","doi":"10.3389/fsysb.2024.1266279","DOIUrl":"https://doi.org/10.3389/fsysb.2024.1266279","url":null,"abstract":"Introduction: The vagus nerve innervates multiple organs, but its role in regulating cross-tissue spread of inflammation is as yet unclear. We hypothesized that the vagus nerve may regulate cross-tissue inflammation via modulation of the putatively neurally regulated chemokine IP-10/CXCL10.Methods: Rate-of-change analysis, dynamic network analysis, and dynamic hypergraphs were used to model intra- and inter-tissue trends, respectively, in inflammatory mediators from mice that underwent either vagotomy or sham surgery.Results: This analysis suggested that vagotomy primarily disrupts the cross-tissue attenuation of inflammatory networks involving IP-10 as well as the chemokines MIG/CXCL9 and CCL2/MCP-1 along with the cytokines IFN-γ and IL-6. Computational analysis also suggested that the vagus-dependent rate of expression of IP-10 and MIG/CXCL9 in the spleen impacts the trajectory of chemokine expression in other tissues. Perturbation of this complex system with bacterial lipopolysaccharide (LPS) revealed a vagally regulated role for MIG in the heart. Further, LPS-stimulated expression of IP-10 was inferred to be vagus-independent across all tissues examined while reducing connectivity to IL-6 and MCP-1, a hypothesis supported by Boolean network modeling.Discussion: Together, these studies define novel spatiotemporal dimensions of vagus-regulated acute inflammation.","PeriodicalId":73109,"journal":{"name":"Frontiers in systems biology","volume":"103 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139834829","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-15DOI: 10.3389/fsysb.2024.1266279
Ashti M. Shah, R. Zamora, Derek A. Barclay, Jinling Yin, Fayten el-Dehaibi, M. Addorisio, T. Tsaava, A. Tynan, Kevin Tracey, Sangeeta Chavan, Y. Vodovotz
Introduction: The vagus nerve innervates multiple organs, but its role in regulating cross-tissue spread of inflammation is as yet unclear. We hypothesized that the vagus nerve may regulate cross-tissue inflammation via modulation of the putatively neurally regulated chemokine IP-10/CXCL10.Methods: Rate-of-change analysis, dynamic network analysis, and dynamic hypergraphs were used to model intra- and inter-tissue trends, respectively, in inflammatory mediators from mice that underwent either vagotomy or sham surgery.Results: This analysis suggested that vagotomy primarily disrupts the cross-tissue attenuation of inflammatory networks involving IP-10 as well as the chemokines MIG/CXCL9 and CCL2/MCP-1 along with the cytokines IFN-γ and IL-6. Computational analysis also suggested that the vagus-dependent rate of expression of IP-10 and MIG/CXCL9 in the spleen impacts the trajectory of chemokine expression in other tissues. Perturbation of this complex system with bacterial lipopolysaccharide (LPS) revealed a vagally regulated role for MIG in the heart. Further, LPS-stimulated expression of IP-10 was inferred to be vagus-independent across all tissues examined while reducing connectivity to IL-6 and MCP-1, a hypothesis supported by Boolean network modeling.Discussion: Together, these studies define novel spatiotemporal dimensions of vagus-regulated acute inflammation.
{"title":"Computational inference of chemokine-mediated roles for the vagus nerve in modulating intra- and inter-tissue inflammation","authors":"Ashti M. Shah, R. Zamora, Derek A. Barclay, Jinling Yin, Fayten el-Dehaibi, M. Addorisio, T. Tsaava, A. Tynan, Kevin Tracey, Sangeeta Chavan, Y. Vodovotz","doi":"10.3389/fsysb.2024.1266279","DOIUrl":"https://doi.org/10.3389/fsysb.2024.1266279","url":null,"abstract":"Introduction: The vagus nerve innervates multiple organs, but its role in regulating cross-tissue spread of inflammation is as yet unclear. We hypothesized that the vagus nerve may regulate cross-tissue inflammation via modulation of the putatively neurally regulated chemokine IP-10/CXCL10.Methods: Rate-of-change analysis, dynamic network analysis, and dynamic hypergraphs were used to model intra- and inter-tissue trends, respectively, in inflammatory mediators from mice that underwent either vagotomy or sham surgery.Results: This analysis suggested that vagotomy primarily disrupts the cross-tissue attenuation of inflammatory networks involving IP-10 as well as the chemokines MIG/CXCL9 and CCL2/MCP-1 along with the cytokines IFN-γ and IL-6. Computational analysis also suggested that the vagus-dependent rate of expression of IP-10 and MIG/CXCL9 in the spleen impacts the trajectory of chemokine expression in other tissues. Perturbation of this complex system with bacterial lipopolysaccharide (LPS) revealed a vagally regulated role for MIG in the heart. Further, LPS-stimulated expression of IP-10 was inferred to be vagus-independent across all tissues examined while reducing connectivity to IL-6 and MCP-1, a hypothesis supported by Boolean network modeling.Discussion: Together, these studies define novel spatiotemporal dimensions of vagus-regulated acute inflammation.","PeriodicalId":73109,"journal":{"name":"Frontiers in systems biology","volume":"17 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139775424","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-02DOI: 10.3389/fsysb.2024.1367549
S. Peirce-Cottler, Y. Vodovotz
{"title":"Editorial: Combining mechanistic modeling with machine learning to study multiscale biological processes","authors":"S. Peirce-Cottler, Y. Vodovotz","doi":"10.3389/fsysb.2024.1367549","DOIUrl":"https://doi.org/10.3389/fsysb.2024.1367549","url":null,"abstract":"","PeriodicalId":73109,"journal":{"name":"Frontiers in systems biology","volume":"49 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139810381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-02-02DOI: 10.3389/fsysb.2024.1367549
S. Peirce-Cottler, Y. Vodovotz
{"title":"Editorial: Combining mechanistic modeling with machine learning to study multiscale biological processes","authors":"S. Peirce-Cottler, Y. Vodovotz","doi":"10.3389/fsysb.2024.1367549","DOIUrl":"https://doi.org/10.3389/fsysb.2024.1367549","url":null,"abstract":"","PeriodicalId":73109,"journal":{"name":"Frontiers in systems biology","volume":"15 2-4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139870267","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-29DOI: 10.3389/fsysb.2024.1291612
Alexis Saldivar, Patricia Ruiz-Ruiz, Sergio Revah, C. Zuñiga
Members of the genus Methylacidiphilum are thermoacidophile methanotrophs with optimal growth temperatures between 50°C and 60°C, and pH between 1.0 and 3.0. These microorganisms, as well as other extremophile bacteria, offer an attractive platform for environmental and industrial biotechnology because of their robust operating conditions and capacity to grow using low-cost substrates. In this study, we isolated Methylacidiphilum fumariolicum str. Pic from a crater lake located in the state of Chiapas, Mexico. We sequenced the genome and built a genome-scale metabolic model. The manually curated model contains 667 metabolites, 729 reactions, and 473 genes. Predicted flux distributions using flux balance analysis identified changes in redox trade-offs under methanotrophic and autotrophic conditions (H2+CO2). This was also predicted under heterotrophic conditions (acetone, isopropanol, and propane). Model validation was performed by testing the capacity of the strains to grow using four substrates: CH4, acetone, isopropanol, and LP-Gas. The results suggest that the metabolism of M. fumariolicum str. Pic is limited by the regeneration of redox equivalents such as NAD(P)H and reduced cytochromes.
{"title":"Genome-scale flux balance analysis reveals redox trade-offs in the metabolism of the thermoacidophile Methylacidiphilum fumariolicum under auto-, hetero-and methanotrophic conditions","authors":"Alexis Saldivar, Patricia Ruiz-Ruiz, Sergio Revah, C. Zuñiga","doi":"10.3389/fsysb.2024.1291612","DOIUrl":"https://doi.org/10.3389/fsysb.2024.1291612","url":null,"abstract":"Members of the genus Methylacidiphilum are thermoacidophile methanotrophs with optimal growth temperatures between 50°C and 60°C, and pH between 1.0 and 3.0. These microorganisms, as well as other extremophile bacteria, offer an attractive platform for environmental and industrial biotechnology because of their robust operating conditions and capacity to grow using low-cost substrates. In this study, we isolated Methylacidiphilum fumariolicum str. Pic from a crater lake located in the state of Chiapas, Mexico. We sequenced the genome and built a genome-scale metabolic model. The manually curated model contains 667 metabolites, 729 reactions, and 473 genes. Predicted flux distributions using flux balance analysis identified changes in redox trade-offs under methanotrophic and autotrophic conditions (H2+CO2). This was also predicted under heterotrophic conditions (acetone, isopropanol, and propane). Model validation was performed by testing the capacity of the strains to grow using four substrates: CH4, acetone, isopropanol, and LP-Gas. The results suggest that the metabolism of M. fumariolicum str. Pic is limited by the regeneration of redox equivalents such as NAD(P)H and reduced cytochromes.","PeriodicalId":73109,"journal":{"name":"Frontiers in systems biology","volume":"1 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140489025","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-22DOI: 10.3389/fsysb.2023.1283341
Christian T. Michael, Sayed A. Almohri, J. Linderman, Denise E. Kirschner
Computational models of disease progression have been constructed for a myriad of pathologies. Typically, the conceptual implementation for pathology-related in silico intervention studies has been ad hoc and similar in design to experimental studies. We introduce a multi-scale interventional design (MID) framework toward two key goals: tracking of disease dynamics from within-body to patient to population scale; and tracking impact(s) of interventions across these same spatial scales. Our MID framework prioritizes investigation of impact on individual patients within virtual pre-clinical trials, instead of replicating the design of experimental studies. We apply a MID framework to develop, organize, and analyze a cohort of virtual patients for the study of tuberculosis (TB) as an example disease. For this study, we use HostSim: our next-generation whole patient-scale computational model of individuals infected with Mycobacterium tuberculosis. HostSim captures infection within lungs by tracking multiple granulomas, together with dynamics occurring with blood and lymph node compartments, the compartments involved during pulmonary TB. We extend HostSim to include a simple drug intervention as an example of our approach and use our MID framework to quantify the impact of treatment at cellular and tissue (granuloma), patient (lungs, lymph nodes and blood), and population scales. Sensitivity analyses allow us to determine which features of virtual patients are the strongest predictors of intervention efficacy across scales. These insights allow us to identify patient-heterogeneous mechanisms that drive outcomes across scales.
{"title":"A framework for multi-scale intervention modeling: virtual cohorts, virtual clinical trials, and model-to-model comparisons","authors":"Christian T. Michael, Sayed A. Almohri, J. Linderman, Denise E. Kirschner","doi":"10.3389/fsysb.2023.1283341","DOIUrl":"https://doi.org/10.3389/fsysb.2023.1283341","url":null,"abstract":"Computational models of disease progression have been constructed for a myriad of pathologies. Typically, the conceptual implementation for pathology-related in silico intervention studies has been ad hoc and similar in design to experimental studies. We introduce a multi-scale interventional design (MID) framework toward two key goals: tracking of disease dynamics from within-body to patient to population scale; and tracking impact(s) of interventions across these same spatial scales. Our MID framework prioritizes investigation of impact on individual patients within virtual pre-clinical trials, instead of replicating the design of experimental studies. We apply a MID framework to develop, organize, and analyze a cohort of virtual patients for the study of tuberculosis (TB) as an example disease. For this study, we use HostSim: our next-generation whole patient-scale computational model of individuals infected with Mycobacterium tuberculosis. HostSim captures infection within lungs by tracking multiple granulomas, together with dynamics occurring with blood and lymph node compartments, the compartments involved during pulmonary TB. We extend HostSim to include a simple drug intervention as an example of our approach and use our MID framework to quantify the impact of treatment at cellular and tissue (granuloma), patient (lungs, lymph nodes and blood), and population scales. Sensitivity analyses allow us to determine which features of virtual patients are the strongest predictors of intervention efficacy across scales. These insights allow us to identify patient-heterogeneous mechanisms that drive outcomes across scales.","PeriodicalId":73109,"journal":{"name":"Frontiers in systems biology","volume":"17 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139609220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-08DOI: 10.3389/fsysb.2023.1260315
Angelo Lucia, Korkut Uygun
The current clinical standard of Static Cold Storage (SCS) which involves preservation on ice (about +4°C) in a hypoxic state limits storage to a few hours for metabolically active tissues such as the liver and the heart. This period of hypoxia during can generate superoxide and other free radicals from purine metabolism, a well-established component of ischemia/reperfusion injury (IRI). Machine perfusion is at the cutting edge of organ preservation, which provides a functional, oxygenated preservation modality that can avoid/attenuate IRI. In clinical application, perfusion usually follows a period of SCS. This presentation of oxygen following hypoxia can lead to superoxide and hydrogen peroxide generation, but machine perfusion also allows manipulation of the temperature profiles and supply of antioxidant treatments, which could be used to minimize such issues. However, metabolomic data is difficult to gather, and there are currently no mathematical models present to allow rational design of experiments or guide clinical practice. In this article, the effects of a gradual warming temperature policy and glutathione supplementation to minimize oxidative stress are studied. An optimal gradual warming temperature policy for mid-thermic machine perfusion of a liver metabolic model is determined using a combination of Nash Equilibrium and Monte Carlo optimization. Using this optimal gradual warming temperature policy, minimum GSH requirements to maintain hydrogen peroxide concentrations in the normal region are calculated using a different Monte Carlo optimization methodology. In addition, the dynamic behavior of key metabolites and cofactors are determined. Results show that the minimum GSH requirement increases and that the ratio of GSH/GSSG decreases with increasing hydrogen peroxide concentration. In addition, at high concentrations of hydrogen peroxide it is shown that cytochrome C undergoes dysfunction leading to a decrease in useful oxygen consumption and ATP synthesis from the electron transport chain and an overall reduction in the energy charge for the liver cells.
目前的临床标准是静态冷藏（SCS），即在缺氧状态下置于冰上（约 +4°C）保存，这就将肝脏和心脏等代谢活跃组织的保存时间限制在几小时之内。这一时期的缺氧会产生超氧化物和其他来自嘌呤代谢的自由基，这是缺血/再灌注损伤（IRI）的一个公认组成部分。机器灌注是器官保存的最前沿技术，它提供了一种功能性氧合保存方式，可以避免/减轻 IRI。在临床应用中，灌注通常是在一段时间的 SCS 之后进行。缺氧后氧气的出现会导致超氧化物和过氧化氢的产生，但机器灌注还可以控制温度曲线和提供抗氧化剂治疗，从而最大限度地减少此类问题。然而，代谢组学数据很难收集，目前也没有数学模型来合理设计实验或指导临床实践。本文研究了逐渐升温的温度策略和补充谷胱甘肽对减少氧化应激的影响。采用纳什均衡和蒙特卡洛优化相结合的方法，确定了肝脏代谢模型中期热机灌注的最佳渐进升温温度策略。利用这种最佳渐进升温温度策略，采用不同的蒙特卡洛优化方法计算了将过氧化氢浓度维持在正常区域的最低 GSH 要求。此外，还确定了关键代谢物和辅助因子的动态行为。结果表明，随着过氧化氢浓度的增加，最低 GSH 需求量增加，GSH/GSSG 比率降低。此外，在高浓度的过氧化氢条件下，细胞色素 C 会发生功能障碍，导致电子传递链的有用耗氧量和 ATP 合成减少，肝细胞的能量负荷总体下降。
{"title":"Metabolic perturbation studies using a Nash Equilibrium model of liver machine perfusion: modeling oxidative stress and effect of glutathione supplementation","authors":"Angelo Lucia, Korkut Uygun","doi":"10.3389/fsysb.2023.1260315","DOIUrl":"https://doi.org/10.3389/fsysb.2023.1260315","url":null,"abstract":"The current clinical standard of Static Cold Storage (SCS) which involves preservation on ice (about +4°C) in a hypoxic state limits storage to a few hours for metabolically active tissues such as the liver and the heart. This period of hypoxia during can generate superoxide and other free radicals from purine metabolism, a well-established component of ischemia/reperfusion injury (IRI). Machine perfusion is at the cutting edge of organ preservation, which provides a functional, oxygenated preservation modality that can avoid/attenuate IRI. In clinical application, perfusion usually follows a period of SCS. This presentation of oxygen following hypoxia can lead to superoxide and hydrogen peroxide generation, but machine perfusion also allows manipulation of the temperature profiles and supply of antioxidant treatments, which could be used to minimize such issues. However, metabolomic data is difficult to gather, and there are currently no mathematical models present to allow rational design of experiments or guide clinical practice. In this article, the effects of a gradual warming temperature policy and glutathione supplementation to minimize oxidative stress are studied. An optimal gradual warming temperature policy for mid-thermic machine perfusion of a liver metabolic model is determined using a combination of Nash Equilibrium and Monte Carlo optimization. Using this optimal gradual warming temperature policy, minimum GSH requirements to maintain hydrogen peroxide concentrations in the normal region are calculated using a different Monte Carlo optimization methodology. In addition, the dynamic behavior of key metabolites and cofactors are determined. Results show that the minimum GSH requirement increases and that the ratio of GSH/GSSG decreases with increasing hydrogen peroxide concentration. In addition, at high concentrations of hydrogen peroxide it is shown that cytochrome C undergoes dysfunction leading to a decrease in useful oxygen consumption and ATP synthesis from the electron transport chain and an overall reduction in the energy charge for the liver cells.","PeriodicalId":73109,"journal":{"name":"Frontiers in systems biology","volume":"31 15","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139444914","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-01Epub Date: 2024-04-29DOI: 10.3389/fsysb.2024.1372995
Sogand Schafer, Kaige Chen, Leyuan Ma
Crosstalk between dendritic cells (DCs) and T cells plays a crucial role in modulating immune responses in natural and pathological conditions. DC-T cell crosstalk is achieved through contact-dependent (i.e., immunological synapse) and contact-independent mechanisms (i.e., cytokines). Activated DCs upregulate co-stimulatory signals and secrete proinflammatory cytokines to orchestrate T cell activation and differentiation. Conversely, activated T helper cells "license" DCs towards maturation, while regulatory T cells (Tregs) silence DCs to elicit tolerogenic immunity. Strategies to efficiently modulate the DC-T cell crosstalk can be harnessed to promote immune activation for cancer immunotherapy or immune tolerance for the treatment of autoimmune diseases. Here, we review the natural crosstalk mechanisms between DC and T cells. We highlight bioengineering approaches to modulate DC-T cell crosstalk, including conventional vaccines, synthetic vaccines, and DC-mimics, and key seminal studies leveraging these approaches to steer immune response for the treatment of cancer and autoimmune diseases.
树突状细胞（DC）和 T 细胞之间的串联在调节自然和病理条件下的免疫反应中起着至关重要的作用。DC-T细胞之间的串联是通过依赖接触的机制（即免疫突触）和不依赖接触的机制（即细胞因子）实现的。活化的 DC 上调共刺激信号并分泌促炎细胞因子，以协调 T 细胞的活化和分化。相反，活化的 T 辅助细胞会 "许可 "DC 走向成熟，而调节性 T 细胞（Tregs）则会抑制 DC 以激发耐受性免疫。有效调节DC-T细胞串扰的策略可用于促进癌症免疫疗法的免疫激活或治疗自身免疫性疾病的免疫耐受。在此，我们回顾了 DC 和 T 细胞之间的天然串联机制。我们重点介绍了调节直流-T 细胞串联的生物工程方法，包括传统疫苗、合成疫苗和直流模拟物，以及利用这些方法引导免疫反应以治疗癌症和自身免疫性疾病的重要开创性研究。
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