Frontiers in systems biology最新文献

{"title":"Transporter annotations are holding up progress in metabolic modeling","authors":"John Casey, Brian Bennion, Patrik D’haeseleer, Jeffrey Kimbrel, G. Marschmann, Ali Navid","doi":"10.3389/fsysb.2024.1394084","DOIUrl":"https://doi.org/10.3389/fsysb.2024.1394084","url":null,"abstract":"Mechanistic, constraint-based models of microbial isolates or communities are a staple in the metabolic analysis toolbox, but predictions about microbe-microbe and microbe-environment interactions are only as good as the accuracy of transporter annotations. A number of hurdles stand in the way of comprehensive functional assignments for membrane transporters. These include general or non-specific substrate assignments, ambiguity in the localization, directionality and reversibility of a transporter, and the many-to-many mapping of substrates, transporters and genes. In this perspective, we summarize progress in both experimental and computational approaches used to determine the function of transporters and consider paths forward that integrate both. Investment in accurate, high-throughput functional characterization is needed to train the next-generation of predictive tools toward genome-scale metabolic network reconstructions that better predict phenotypes and interactions. More reliable predictions in this domain will benefit fields ranging from personalized medicine to metabolic engineering to microbial ecology.","PeriodicalId":73109,"journal":{"name":"Frontiers in systems biology","volume":"43 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141807065","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}

{"title":"Life’s building blocks: the modular path to multiscale complexity","authors":"Saúl Huitzil, Cristián Huepe","doi":"10.3389/fsysb.2024.1417800","DOIUrl":"https://doi.org/10.3389/fsysb.2024.1417800","url":null,"abstract":"Modularity, the structuring of systems into discrete, interconnected units, is a fundamental organizing principle in biology across multiple scales. Recent progress in understanding the role of modularity as an evolutionary mechanism and a key driver of biological complexity has highlighted its importance in shaping the structure and function of living systems. Here, we propose a unifying framework that identifies the potential evolutionary advantages of modularity in systems ranging from molecular networks to ecologies, such as facilitating evolvability, enhancing robustness, improving information flows, and enabling the emergence of higher-level functions. Our analysis reveals the pervasiveness of modularity in living systems and highlights its crucial role in the evolution of multiscale hierarchies of increasing complexity.","PeriodicalId":73109,"journal":{"name":"Frontiers in systems biology","volume":" 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141830810","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}

{"title":"Coupling quantitative systems pharmacology modelling to machine learning and artificial intelligence for drug development: its pAIns and gAIns","authors":"Núria Folguera-Blasco, Florencia A. T. Boshier, Aydar Uatay, C. Pichardo-Almarza, Massimo Lai, Jacopo Biasetti, Richard Dearden, Megan Gibbs, Holly Kimko","doi":"10.3389/fsysb.2024.1380685","DOIUrl":"https://doi.org/10.3389/fsysb.2024.1380685","url":null,"abstract":"Quantitative Systems Pharmacology (QSP) has become a powerful tool in the drug development landscape. To facilitate its continued implementation and to further enhance its applicability, a symbiotic approach in which QSP is combined with artificial intelligence (AI) and machine learning (ML) seems key. This manuscript presents four case examples where the application of a symbiotic approach could unlock new insights from multidimensional data, including real-world data, potentially leading to breakthroughs in drug development. Besides the remarkable benefits (gAIns) that the symbiosis can offer, it does also carry potential challenges (pAIns) such as how to assess and quantify uncertainty, bias and error. Hence, to ensure a successful implementation, arising pAIns need to be acknowledged and carefully addressed. Successful implementation of the symbiotic QSP and ML/AI approach has the potential to serve as a catalyst, paving the way for a paradigm shift in drug development.","PeriodicalId":73109,"journal":{"name":"Frontiers in systems biology","volume":"37 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141653879","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}

{"title":"Predicting chronic responses to calcium channel blockade with a virtual population of African Americans with hypertensive chronic kidney disease","authors":"J. Clemmer, W. Pruett, Robert L. Hester","doi":"10.3389/fsysb.2024.1327357","DOIUrl":"https://doi.org/10.3389/fsysb.2024.1327357","url":null,"abstract":"Chronic kidney disease (CKD) is associated with the progressive loss of functional nephrons and hypertension (HTN). Clinical studies demonstrate calcium channel blocker (CCB) therapy mitigates the decline in renal function in humans with essential HTN. However, there are few long-term clinical studies that determine the impact of CCBs in patients with hypertensive CKD. African Americans (AA) have a higher prevalence of CKD and a faster progression to total kidney failure as compared to the white population but the mechanisms are poorly understood. Both clinical evidence (the African American Study of Kidney Disease and Hypertension, or AASK trial) and experimental studies have demonstrated that CCB may expose glomerular capillaries to high systemic pressures and exacerbate CKD progression. Therefore, using a large physiological model, we set out to replicate the AASK trial findings, predict renal hemodynamic responses and the role of the renin-angiotensin system during CCB antihypertensive therapy in a virtual population, and hypothesize mechanisms underlying those findings. Our current mathematical model, HumMod, is comprised of integrated systems that play an integral role in long-term blood pressure (BP) control such as neural, endocrine, circulatory, and renal systems. Parameters (n = 341) that control these systems were randomly varied and resulted in 1,400 unique models that we define as a virtual population. We calibrated these models to individual patient level data from the AASK trial: BP and glomerular filtration rate (GFR) before and after 3 years of amlodipine (10 mg/day). After calibration, the new virtual population (n = 165) was associated with statistically similar BP and GFR before and after CCB. Baseline factors such as elevated single nephron GFR and low tubuloglomerular feedback were correlated with greater declines in renal function and increased glomerulosclerosis after 3 years of CCB. Blocking the renin-angiotensin system (RAS) in the virtual population decreased glomerular pressure, limited glomerular damage, and further decreased BP (−14 ± 8 mmHg) as compared to CCB alone (−11 ± 9 mmHg). Our simulations echo the potential risk of CCB monotherapy in AA CKD patients and support blockade of the renin angiotensin system as a valuable tool in renal disease treatment when combined with CCB therapy.","PeriodicalId":73109,"journal":{"name":"Frontiers in systems biology","volume":" 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141679000","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}

{"title":"Specialty grand challenge: how can we use integrative approaches to understand microbial community dynamics?","authors":"Umer Zeeshan Ijaz, Aqsa Ameer, Farrukh Saleem, Farzana Gul, Ciara Keating, Sundus Javed","doi":"10.3389/fsysb.2024.1432791","DOIUrl":"10.3389/fsysb.2024.1432791","url":null,"abstract":"","PeriodicalId":73109,"journal":{"name":"Frontiers in systems biology","volume":"4 ","pages":"1432791"},"PeriodicalIF":2.3,"publicationDate":"2024-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12342006/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144849996","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PdPANA: phagemid display as peptide array for neutralizing antibodies, an engineered <i>in silico</i> vaccine candidate against COVID-19.","authors":"Javier Uzcátegui, Khaleel Mullah, Daniel Buvat de Virgini, Andrés Mendoza, Rafael Urdaneta, Alejandra Naranjo","doi":"10.3389/fsysb.2024.1309891","DOIUrl":"10.3389/fsysb.2024.1309891","url":null,"abstract":"<p><p>The COVID-19 pandemic has tested the technical, scientific, and industrial resources of all countries worldwide. Faced with the absence of pharmacological strategies against the disease, an effective plan for vaccinating against SARS-CoV-2 has been essential. Due to the lack of production means and necessary infrastructure, only a few nations could adequately confront this pathogen with a production, storage, and distribution scheme in place. This disease has become endemic in many countries, especially in those that are developing, thus necessitating solutions tailored to their reality. In this paper, we propose an <i>in silico</i> method to guide the design towards a thermally stable, universal, efficient, and safe COVID-19 vaccine candidate against SARS-CoV-2 using bioinformatics, immunoinformatics, and molecular modeling approaches for the selection of antigens with higher immunogenic potential, incorporating them into the surface of the M13 phage. Our work focused on using phagemid display as peptide array for neutralizing antibodies (PdPANA). This alternative approach might be useful during the vaccine development process, since it could bring improvements in terms of cost-effectiveness in production, durability, and ease of distribution of the vaccine under less stringent thermal conditions compared to existing methods. Our results suggest that in the heavily glycosylated region of SARS-CoV-2 Spike protein (aa 344-583), from its inter-glycosylated regions, useful antigenic peptides can be obtained to be used in M13 phagemid display system. PdPANA, our proposed method might be useful to overcome the classic shortcoming posed by the phage-display technique (i.e., the time-consuming task of <i>in vitro</i> screening through great sized libraries with non-useful recombinant proteins) and obtain the most ideal recombinant proteins for vaccine design purposes.</p>","PeriodicalId":73109,"journal":{"name":"Frontiers in systems biology","volume":"4 ","pages":"1309891"},"PeriodicalIF":2.3,"publicationDate":"2024-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12341989/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144849995","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Building an Adverse Outcome Pathway network for COVID-19","authors":"P. Nymark, Laure-Alix Clerbaux, Maria-João Amorim, Christos Andronis, Francesca de Bernardi, Gillina F. G. Bezemer, Sandra Coecke, Felicity N. E. Gavins, Daniel Jacobson, E. Lekka, Luigi Margiotta-Casaluci, Marvin Martens, S. Mayasich, Holly M. Mortensen, Young Jun Kim, M. Sachana, Shihori Tanabe, V. Virvilis, Steve W. Edwards, Sabina Halappanavar","doi":"10.3389/fsysb.2024.1384481","DOIUrl":"https://doi.org/10.3389/fsysb.2024.1384481","url":null,"abstract":"The COVID-19 pandemic generated large amounts of data on the disease pathogenesis leading to a need for organizing the vast knowledge in a succinct manner. Between April 2020 and February 2023, the CIAO consortium exploited the Adverse Outcome Pathway (AOP) framework to comprehensively gather and systematically organize published scientific literature on COVID-19 pathology. The project considered 24 pathways relevant for COVID-19 by identifying essential key events (KEs) leading to 19 adverse outcomes observed in patients. While an individual AOP defines causally linked perturbed KEs towards an outcome, building an AOP network visually reflect the interrelatedness of the various pathways and outcomes. In this study, 17 of those COVID-19 AOPs were selected based on quality criteria to computationally derive an AOP network. This primary network highlighted the need to consider tissue specificity and helped to identify missing or redundant elements which were then manually implemented in the final network. Such a network enabled visualization of the complex interactions of the KEs leading to the various outcomes of the multifaceted COVID-19 and confirmed the central role of the inflammatory response in the disease. In addition, this study disclosed the importance of terminology harmonization and of tissue/organ specificity for network building. Furthermore the unequal completeness and quality of information contained in the AOPs highlighted the need for tighter implementation of the FAIR principles to improve AOP findability, accessibility, interoperability and re-usability. Finally, the study underlined that describing KEs specific to SARS-CoV-2 replication and discriminating physiological from pathological inflammation is necessary but requires adaptations to the framework. Hence, based on the challenges encountered, we proposed recommendations relevant for ongoing and future AOP-aligned consortia aiming to build computationally biologically meaningful AOP networks in the context of, but not limited to, viral diseases.","PeriodicalId":73109,"journal":{"name":"Frontiers in systems biology","volume":" 29","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141373398","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}

{"title":"De novo prediction of functional effects of genetic variants from DNA sequences based on context-specific molecular information","authors":"Jiaxin Yang, Sikta Das Adhikari, Hao Wang, Binbin Huang, Wenjie Qi, Yuehua Cui, Jianrong Wang","doi":"10.3389/fsysb.2024.1402664","DOIUrl":"https://doi.org/10.3389/fsysb.2024.1402664","url":null,"abstract":"Deciphering the functional effects of noncoding genetic variants stands as a fundamental challenge in human genetics. Traditional approaches, such as Genome-Wide Association Studies (GWAS), Transcriptome-Wide Association Studies (TWAS), and Quantitative Trait Loci (QTL) studies, are constrained by obscured the underlying molecular-level mechanisms, making it challenging to unravel the genetic basis of complex traits. The advent of Next-Generation Sequencing (NGS) technologies has enabled context-specific genome-wide measurements, encompassing gene expression, chromatin accessibility, epigenetic marks, and transcription factor binding sites, to be obtained across diverse cell types and tissues, paving the way for decoding genetic variation effects directly from DNA sequences only. The de novo predictions of functional effects are pivotal for enhancing our comprehension of transcriptional regulation and its disruptions caused by the plethora of noncoding genetic variants linked to human diseases and traits. This review provides a systematic overview of the state-of-the-art models and algorithms for genetic variant effect predictions, including traditional sequence-based models, Deep Learning models, and the cutting-edge Foundation Models. It delves into the ongoing challenges and prospective directions, presenting an in-depth perspective on contemporary developments in this domain.","PeriodicalId":73109,"journal":{"name":"Frontiers in systems biology","volume":"28 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141272489","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}

{"title":"Surface-displayed silicatein-α enzyme in bioengineered <i>E. coli</i> enables biocementation and silica mineralization.","authors":"Toriana N Vigil, Nikolas K Schwendeman, Melanie L M Grogger, Victoria L Morrison, Margaret C Warner, Nathaniel B Bone, Morgan T Vance, David C Morris, Kristi McElmurry, Bryan W Berger, J Jordan Steel","doi":"10.3389/fsysb.2024.1377188","DOIUrl":"10.3389/fsysb.2024.1377188","url":null,"abstract":"<p><p>Biocementation is an exciting biomanufacturing alternative to common cement, which is a significant contributor of CO₂ greenhouse gas production. In nature biocementation processes are usually modulated via ureolytic microbes, such as <i>Sporosarcina pasteurii,</i> precipitating calcium carbonate to cement particles together, but these ureolytic reactions also produce ammonium and carbonate byproducts, which may have detrimental effects on the environment. As an alternative approach, this work examines biosilicification via surface-displayed silicatein-α in bio-engineered <i>E. coli</i> as an <i>in vivo</i> biocementation strategy. The surface-display of silicatein-α with ice nucleation protein is a novel protein fusion combination that effectively enables biosilicification, which is the polymerization of silica species in solution, from the surface of <i>E. coli</i> bacterial cells. Biosilicification with silicatein-α produces biocementation products with comparable compressive strength as <i>S. pasteurii.</i> This biosilicification approach takes advantage of the high silica content found naturally in sand and does not produce the ammonium and carbonate byproducts of ureolytic bacteria, making this a more environmentally friendly biocementation strategy.</p>","PeriodicalId":73109,"journal":{"name":"Frontiers in systems biology","volume":"4 ","pages":"1377188"},"PeriodicalIF":2.3,"publicationDate":"2024-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12341959/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144849998","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Elucidating a genomic signature associated with behavioral and executive function after moderate to severe pediatric TBI: a systems biology informed approach","authors":"B. Kurowski, A. Treble-Barna, Valentina Pilipenko, Lisa J. Martin, Anil G. Jegga, Aimee E Miley, Nanhua Zhang, Anthony Fabio, Ranjit S. Chima, Anna-Lynne R. Adlam, Kenneth Kaufman, Michael J Bell, Sue R Beers, Stephen R. Wisniewski, Shari L. Wade","doi":"10.3389/fsysb.2024.1293265","DOIUrl":"https://doi.org/10.3389/fsysb.2024.1293265","url":null,"abstract":"Introduction: There is significant unexplained variability in behavioral and executive functioning after pediatric traumatic brain injury (TBI). Prior research indicates that there are likely genetic contributions; however, current research is limited. The purpose of this study is to use a systems biology informed approach to characterize the genomic signature related to behavioral and executive functioning ∼12 months after moderate through severe TBI in children.Methods: Participants were from two prospective cohorts of children with severe TBI (Cohort #1) and moderate-severe TBI and an orthopedic injury (OI) group (Cohort #2). Participants included 196 children (n = 72 and n = 124 total from each respective cohort), ranging in age between 0–17 years at the time of injury. In total, 86 children had severe TBI, 49 had moderate TBI, and 61 had an OI. Global behavioral functioning assessed via the Child Behavior Checklist and executive function assessed via the Behavioral Rating Inventory of Executive Function at ∼ 12 months post injury served as outcomes. To test for a genomic signature, we compared the number of nominally significant (p < 0.05) polymorphisms associated with the outcomes in our systems biology identified genes to a set 10,000 permutations using control genes (e.g., not implicated by systems biology). We used the ToppFun application from Toppgene Suite to identify enriched biologic processes likely to be associated with behavioral and executive function outcomes.Results: At 12 months post injury, injury type (TBI vs OI) by polymorphism interaction was significantly enriched in systems biology selected genes for behavioral and executive function outcomes, suggesting these genes form a genomic signature. Effect sizes of the associations from our genes of interest ranged from .2–.5 for the top 5% of variants. Systems biology analysis of the variants associated with the top 5% effect sizes indicated enrichment in several specific biologic processes and systems.Discussion: Findings indicate that a genomic signature may explain heterogeneity of behavioral and executive outcomes after moderate and severe TBI. This work provides the foundation for constructing genomic signatures and integrating systems biology and genetic information into future recovery, prognostic, and treatment algorithms.","PeriodicalId":73109,"journal":{"name":"Frontiers in systems biology","volume":"26 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140658194","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}