Frontiers in systems biology最新文献

{"title":"An adaptive, negative feedback circuit in a biohybrid device reprograms dynamic networks of systemic inflammation in vivo","authors":"R. Namas, Maxim Mikheev, Jinling Yin, D. Barclay, B. Jefferson, Qi Mi, T. Billiar, R. Zamora, J. Gerlach, Y. Vodovotz","doi":"10.3389/fsysb.2022.926618","DOIUrl":"https://doi.org/10.3389/fsysb.2022.926618","url":null,"abstract":"Introduction: Systemic acute inflammation accompanies and underlies the pathobiology of sepsis but is also central to tissue healing. We demonstrated previously the in vivo feasibility of modulating the key inflammatory mediator tumor necrosis factor-alpha (TNF-α) through the constitutive production and systemic administration of soluble TNF-α receptor (sTNFR) via a biohybrid device. Methods: We have now created multiple, stably transfected human HepG2 cell line variants expressing the mouse NF-κB/sTNFR. In vitro, these cell lines vary with regard to baseline production of sTNFR, but all have ~3.5-fold elevations of sTNFR in response to TNF-α. Results: Both constitutive and TNF-α-inducible sTNFR constructs, seeded into multicompartment, capillary-membrane liver bioreactors could reprogram dynamic networks of systemic inflammation and modulate PaO2, a key physiological outcome, in both endotoxemic and septic rats. Discussion: Thus, Control of TNF-α may drive a new generation of tunable biohybrid devices for the rational reprogramming of acute inflammation.","PeriodicalId":73109,"journal":{"name":"Frontiers in systems biology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47510672","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":"Maintenance of PKMζ-modulated synaptic efficacies despite protein turnover","authors":"N. Aslam","doi":"10.3389/fsysb.2022.933938","DOIUrl":"https://doi.org/10.3389/fsysb.2022.933938","url":null,"abstract":"How can synaptic efficacies be maintained despite the fast turnover of proteins at synapses? Partially, we know that the synthesis of new proteins is essential for the induction of the late, long-lasting phase of long-term potentiation (L-LTP). Recent experiments suggest that the concentration of protein kinase Mζ (PKMζ) is increased during L-LTP and that inhibiting the PKMζ activity during the maintenance phase can effectively reverse L-LTP. Experiments have also shown that phosphorylation is necessary for the activation of PKMζ. However, it is not clear what mechanism maintains the level and activity of PKMζ despite protein turnover and phosphatase activity. Using a mathematical modeling framework, I examine the hypothesis that the activity of PKMζ is sustained through a local switching mechanism. The model for the switching mechanism is motivated by several experimental observations: 1) PKMζ has two phosphorylation sites; one is mediated by another constitutively active kinase, Phosphoinositide-dependent kinase 1 PDK1 (T410) and is essential for its activity, and another is an autophosphorylation site, T560. 2) The phosphorylation of PKMζ increases its stability and the doubly phosphorylated PKMζ has a significantly longer lifetime than the unphosphorylated and singly phosphorylated states of PKMζ. 3) The doubly phosphorylated PKMζ also regulates the new synthesis of PKMζ through a translation feedback loop. The present study implemented a mass action model consistent with these observations. The results show that such a model can be bistable and that L-LTP induction produces an increase in the total amount of PKMζ at active synapses. The increase in PKMζ concentration was maintained through the regulation of new protein synthesis by PKMζ. The results also show that blocking the activity of PKMζ in a dose-dependent manner can effectively abolish the increase in the total amount of PKMζ, which is consistent with the effect that the PKMζ inhibitor zeta inhibitory peptide (ZIP) has experimentally demonstrated. The model is consistent with available experimental results regarding the phosphorylation levels of PKMζ and the temporal aspects of blocking experiments and produces a new prediction.","PeriodicalId":73109,"journal":{"name":"Frontiers in systems biology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43813086","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":"Acute respiratory distress syndrome and acute lung injury in a trauma population with and without long bone fractures","authors":"Julia Larson, H. Robertson, S. Grey, S. Schobel, B. Potter, E. Elster","doi":"10.3389/fsysb.2022.1058603","DOIUrl":"https://doi.org/10.3389/fsysb.2022.1058603","url":null,"abstract":"Introduction: Trauma is the leading cause of death in persons under the age of 45. Recovery in patients who survive initial trauma are frequently complicated by sequelae of injury that increases susceptibility to infection and inflammation. Uncontrolled inflammation can advance into life-threatening organ failure, including acute respiratory distress syndrome (ARDS). Similarities exist between biomarkers established in the etiology of acute respiratory distress syndrome and those identified in the acute inflammatory and healing phase of bone fractures. This study investigates the impact of long bone fractures on the development of acute respiratory distress syndrome where it is hypothesized that patients with long bone fractures would have different biomarker profiles and increased development of lung injury compared to patients without long bone fractures. Methods: This is a retrospective data analysis of patients from an observational data repository from three trauma centers. Trauma patients with and without long bone fractures were matched and analyzed for the presence of known biomarkers of acute respiratory distress syndrome and for the development of acute respiratory distress syndrome. Results: There were no differences in overall acute respiratory distress syndrome development or hospital outcomes, however long bone fracture patients had a 2.35-fold higher hazard ratio of acute respiratory distress syndrome in the first 10 hospital days. There was a statistically significant increase in the levels of IL-6 in patients with long bone fractures (p = .0007). Structural equations modeling demonstrated that IL-6 was positively influenced by long bone fractures and IL-8. Conclusion: The presence of long bone fractures did not result in differences in the overall development of acute respiratory distress syndrome or hospital outcomes, though was found to have an increased hazard ratio for acute respiratory distress syndrome development in the first 10 days. Further research is needed to better characterize the relationship between varying cytokine profiles and the development of acute respiratory distress syndrome in a trauma population.","PeriodicalId":73109,"journal":{"name":"Frontiers in systems biology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45127706","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":"Computational design of custom therapeutic cells to correct failing human cardiomyocytes.","authors":"Andrew Tieu, Katherine G Phillips, Kevin D Costa, Joshua Mayourian","doi":"10.3389/fsysb.2023.1102467","DOIUrl":"https://doi.org/10.3389/fsysb.2023.1102467","url":null,"abstract":"Background: Myocardial delivery of non-excitable cells—namely human mesenchymal stem cells (hMSCs) and c-kit+ cardiac interstitial cells (hCICs)—remains a promising approach for treating the failing heart. Recent empirical studies attempt to improve such therapies by genetically engineering cells to express specific ion channels, or by creating hybrid cells with combined channel expression. This study uses a computational modeling approach to test the hypothesis that custom hypothetical cells can be rationally designed to restore a healthy phenotype when coupled to human heart failure (HF) cardiomyocytes. Methods: Candidate custom cells were simulated with a combination of ion channels from non-excitable cells and healthy human cardiomyocytes (hCMs). Using a genetic algorithm-based optimization approach, candidate cells were accepted if a root mean square error (RMSE) of less than 50% relative to healthy hCM was achieved for both action potential and calcium transient waveforms for the cell-treated HF cardiomyocyte, normalized to the untreated HF cardiomyocyte. Results: Custom cells expressing only non-excitable ion channels were inadequate to restore a healthy cardiac phenotype when coupled to either fibrotic or non-fibrotic HF cardiomyocytes. In contrast, custom cells also expressing cardiac ion channels led to acceptable restoration of a healthy cardiomyocyte phenotype when coupled to fibrotic, but not non-fibrotic, HF cardiomyocytes. Incorporating the cardiomyocyte inward rectifier K+ channel was critical to accomplishing this phenotypic rescue while also improving single-cell action potential metrics associated with arrhythmias, namely resting membrane potential and action potential duration. The computational approach also provided insight into the rescue mechanisms, whereby heterocellular coupling enhanced cardiomyocyte L-type calcium current and promoted calcium-induced calcium release. Finally, as a therapeutically translatable strategy, we simulated delivery of hMSCs and hCICs genetically engineered to express the cardiomyocyte inward rectifier K+ channel, which decreased action potential and calcium transient RMSEs by at least 24% relative to control hMSCs and hCICs, with more favorable single-cell arrhythmia metrics. Conclusion: Computational modeling facilitates exploration of customizable engineered cell therapies. Optimized cells expressing cardiac ion channels restored healthy action potential and calcium handling phenotypes in fibrotic HF cardiomyocytes and improved single-cell arrhythmia metrics, warranting further experimental validation studies of the proposed custom therapeutic cells.","PeriodicalId":73109,"journal":{"name":"Frontiers in systems biology","volume":"3 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9894098/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9230767","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":"Batch Correction and Harmonization of -Omics Datasets with a Tunable Median Polish of Ratio.","authors":"Eric B Dammer,&nbsp;Nicholas T Seyfried,&nbsp;Erik C B Johnson","doi":"10.3389/fsysb.2023.1092341","DOIUrl":"https://doi.org/10.3389/fsysb.2023.1092341","url":null,"abstract":"<p><p>Large scale -omics datasets can provide new insights into normal and disease-related biology when analyzed through a systems biology framework. However, technical artefacts present in most -omics datasets due to variations in sample preparation, batching, platform settings, personnel, and other experimental procedures prevent useful analyses of such data without prior adjustment for these technical factors. Here, we demonstrate a tunable median polish of ratio (TAMPOR) approach for batch effect correction and agglomeration of multiple, multi-batch, site-specific cohorts into a single analyte abundance data matrix that is suitable for systems biology analyses. We illustrate the utility and versatility of TAMPOR through four distinct use cases where the method has been applied to different proteomic datasets, some of which contain a specific defect that must be addressed prior to analysis. We compare quality control metrics and sources of variance before and after application of TAMPOR to show that TAMPOR is effective at removing batch effects and other unwanted sources of variance in -omics data. We also show how TAMPOR can be used to harmonize -omics datasets even when the data are acquired using different analytical approaches. TAMPOR is a powerful and flexible approach for cleaning and harmonization of -omics data prior to downstream systems biology analysis.</p>","PeriodicalId":73109,"journal":{"name":"Frontiers in systems biology","volume":"3 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10137904/pdf/nihms-1893744.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9404662","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":"Understanding multimorbidity requires sign-disease networks and higher-order interactions, a perspective.","authors":"Cillian Hourican,&nbsp;Geeske Peeters,&nbsp;René Melis,&nbsp;Thomas M Gill,&nbsp;Marcel Olde Rikkert,&nbsp;Rick Quax","doi":"10.3389/fsysb.2023.1155599","DOIUrl":"10.3389/fsysb.2023.1155599","url":null,"abstract":"<p><strong>Background: </strong>Count scores, disease clustering, and pairwise associations between diseases remain ubiquitous in multimorbidity research despite two major shortcomings: they yield no insight into plausible mechanisms underlying multimorbidity, and they ignore higher-order interactions such as effect modification.</p><p><strong>Objectives: </strong>We argue that two components are currently missing but vital to develop novel multimorbidity metrics. Firstly, networks should be constructed which consists simultaneously of signs, symptoms, and diseases, since only then could they yield insight into plausible shared biological mechanisms underlying diseases.Secondly, learning pairwise associations is insufficient to fully characterize the correlations in a system. That is, synergistic (e.g., cooperative or antagonistic) effects are widespread in complex systems, where two or more elements combined give a larger or smaller effect than the sum of their individual effects. It can even occur that pairs of symptoms have no pairwise associations whatsoever, but in combination have a significant association. Therefore, higher-order interactions should be included in networks used to study multimorbidity, resulting in so-called hypergraphs.</p><p><strong>Methods: </strong>We illustrate our argument using a synthetic Bayesian Network model of symptoms, signs and diseases, composed of pairwise and higher-order interactions. We simulate network interventions on both individual and population levels and compare the ground-truth outcomes with the predictions from pairwise associations.</p><p><strong>Conclusion: </strong>We find that, when judged purely from the pairwise associations, interventions can have unexpected 'side-effects' or the most opportune intervention could be missed. The hypergraph uncovers links missed in pairwise networks, giving a more complete overview of sign and disease associations.</p>","PeriodicalId":73109,"journal":{"name":"Frontiers in systems biology","volume":"3 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10557993/pdf/nihms-1932390.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41160751","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":"Alzheimer's Disease Protein Relevance Analysis Using Human and Mouse Model Proteomics Data.","authors":"Cathy Shi, W Kirby Gottschalk, Carol A Colton, Sayan Mukherjee, Michael W Lutz","doi":"10.3389/fsysb.2023.1085577","DOIUrl":"10.3389/fsysb.2023.1085577","url":null,"abstract":"<p><p>The principles governing genotype-phenotype relationships are still emerging(1-3), and detailed translational as well as transcriptomic information is required to understand complex phenotypes, such as the pathogenesis of Alzheimer's disease. For this reason, the proteomics of Alzheimer disease (AD) continues to be studied extensively. Although comparisons between data obtained from humans and mouse models have been reported, approaches that specifically address the between-species statistical comparisons are understudied. Our study investigated the performance of two statistical methods for identification of proteins and biological pathways associated with Alzheimer's disease for cross-species comparisons, taking specific data analysis challenges into account, including collinearity, dimensionality reduction and cross-species protein matching. We used a human dataset from a well-characterized cohort followed for over 22 years with proteomic data available. For the mouse model, we generated proteomic data from whole brains of CVN-AD and matching control mouse models. We used these analyses to determine the reliability of a mouse model to forecast significant proteomic-based pathological changes in the brain that may mimic pathology in human Alzheimer's disease. Compared with LASSO regression, partial least squares discriminant analysis provided better statistical performance for the proteomics analysis. The major biological finding of the study was that extracellular matrix proteins and integrin-related pathways were dysregulated in both the human and mouse data. This approach may help inform the development of mouse models that are more relevant to the study of human late-onset Alzheimer's disease.</p>","PeriodicalId":73109,"journal":{"name":"Frontiers in systems biology","volume":"3 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10467016/pdf/nihms-1925280.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10226757","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":"Erratum: Research-driven education: An introductory course to systems and synthetic biology","authors":"Frontiers Production Office","doi":"10.3389/fsysb.2022.1114700","DOIUrl":"https://doi.org/10.3389/fsysb.2022.1114700","url":null,"abstract":"","PeriodicalId":73109,"journal":{"name":"Frontiers in systems biology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49460013","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":"A brief account on enzyme mining using metagenomic approach","authors":"Tithi Patel, Hiral G. Chaudhari, Vimalkumar S. Prajapati, Swati R. Patel, Vaibhavkumar N Mehta, N. Soni","doi":"10.3389/fsysb.2022.1046230","DOIUrl":"https://doi.org/10.3389/fsysb.2022.1046230","url":null,"abstract":"Metagenomics is an approach for directly analyzing the genomes of microbial communities in the environment. The use of metagenomics to investigate novel enzymes is critical because it allows researchers to acquire data on microbial diversity, with a 99% success rate, and different kinds of genes encode an enzyme that has yet to be found. Basic metagenomic approaches have been created and are widely used in numerous studies. To promote the success of the advance research, researchers, particularly young researchers, must have a fundamental understanding of metagenomics. As a result, this review was conducted to provide a thorough insight grasp of metagenomics. It also covers the application and fundamental methods of metagenomics in the discovery of novel enzymes, focusing on recent studies. Moreover, the significance of novel biocatalysts anticipated from varied microbial metagenomes and their relevance to future research for novel industrial applications, the ramifications of Next-Generation Sequencing (NGS), sophisticated bio-informatic techniques, and the prospects of the metagenomic approaches are discussed. The current study additionally explores metagenomic research on enzyme exploration, specifically for key enzymes like lipase, protease, and cellulase of microbial origin.","PeriodicalId":73109,"journal":{"name":"Frontiers in systems biology","volume":"2 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41465046","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":"Genome-wide association studies of viral infections—A short guide to a successful experimental and statistical analysis","authors":"A. Butković, S. Elena","doi":"10.3389/fsysb.2022.1005758","DOIUrl":"https://doi.org/10.3389/fsysb.2022.1005758","url":null,"abstract":"Genome-wide association studies (GWAS) have been gaining popularity over the last decade as they provide new insights into the genetic architecture of many disease-related traits. GWAS is based on the common disease common variant hypothesis, allowing identification of alleles associated with susceptibility and symptomatology of most common infectious diseases, such as AIDS, common cold, flu, and many others. It depends on the natural variation in a host population which can help identify genetic variants responsible for virus disease-related traits. Considering the prevalence of viruses in the ecosystem and their societal burden, identification of potential resistance loci or therapeutic targets is of great interest. Here, we highlight the most important points necessary for a successful GWAS of viral infectious diseases, focusing on the study design and various statistical methods used. Finally, we exemplify this application with studies done with human immunodeficiency virus type 1 and turnip mosaic virus.","PeriodicalId":73109,"journal":{"name":"Frontiers in systems biology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43563882","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}