Frontiers in systems biology最新文献

{"title":"Clonal abundance patterns in hematopoiesis: Mathematical modeling and parameter estimation.","authors":"Yunbei Pan, Maria R D'Orsogna, Min Tang, Thomas Stiehl, Tom Chou","doi":"10.3389/fsysb.2023.893366","DOIUrl":"10.3389/fsysb.2023.893366","url":null,"abstract":"<p><p>Hematopoiesis has been studied <i>via</i> stem cell labeling using barcodes, viral integration sites (VISs), or <i>in situ</i> methods. Subsequent proliferation and differentiation preserve the tag identity, thus defining a clone of mature cells across multiple cell type or lineages. By tracking the population of clones, measured within samples taken at discrete time points, we infer physiological parameters associated with a hybrid stochastic-deterministic mathematical model of hematopoiesis. We analyze clone population data from Koelle et al. (Koelle et al., 2017) and compare the states of clones (mean and variance of their abundances) and the state-space density of clones with the corresponding quantities predicted from our model. Comparing our model to the tagged granulocyte populations, we find parameters (stem cell carrying capacity, stem cell differentiation rates, and the proliferative potential of progenitor cells, and sample sizes) that provide reasonable fits in three out of four animals. Even though some observed features cannot be quantitatively reproduced by our model, our analyses provides insight into how model parameters influence the underlying mechanisms in hematopoiesis. We discuss additional mechanisms not incorporated in our model.</p>","PeriodicalId":73109,"journal":{"name":"Frontiers in systems biology","volume":" ","pages":"893366"},"PeriodicalIF":2.3,"publicationDate":"2023-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12342013/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48293055","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":"Application of perturbation gene expression profiles in drug discovery-From mechanism of action to quantitative modelling.","authors":"Bence Szalai, Dániel V Veres","doi":"10.3389/fsysb.2023.1126044","DOIUrl":"10.3389/fsysb.2023.1126044","url":null,"abstract":"<p><p>High dimensional characterization of drug targets, compound effects and disease phenotypes are crucial for increased efficiency of drug discovery. High-throughput gene expression measurements are one of the most frequently used data acquisition methods for such a systems level analysis of biological phenotypes. RNA sequencing allows genome wide quantification of transcript abundances, recently even on the level of single cells. However, the correct, mechanistic interpretation of transcriptomic measurements is complicated by the fact that gene expression changes can be both the cause and the consequence of altered phenotype. Perturbation gene expression profiles, where gene expression is measured after a genetic or chemical perturbation, can help to overcome these problems by directly connecting the causal perturbations to their gene expression consequences. In this Review, we discuss the main large scale perturbation gene expression profile datasets, and their application in the drug discovery process, covering mechanisms of action identification, drug repurposing, pathway activity analysis and quantitative modelling.</p>","PeriodicalId":73109,"journal":{"name":"Frontiers in systems biology","volume":" ","pages":"1126044"},"PeriodicalIF":2.3,"publicationDate":"2023-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12341996/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42861344","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":"Editorial: Systems biology, women in science 2021/22: Data and model integration.","authors":"María Rodríguez Martínez, Angelyn Lao, Leda Torres","doi":"10.3389/fsysb.2023.1134055","DOIUrl":"10.3389/fsysb.2023.1134055","url":null,"abstract":"","PeriodicalId":73109,"journal":{"name":"Frontiers in systems biology","volume":" ","pages":"1134055"},"PeriodicalIF":2.3,"publicationDate":"2023-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12342034/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46875487","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":"What can go wrong when observations are not independently and identically distributed: A cautionary note on calculating correlations on combined data sets from different experiments or conditions.","authors":"Edoardo Saccenti","doi":"10.3389/fsysb.2023.1042156","DOIUrl":"10.3389/fsysb.2023.1042156","url":null,"abstract":"<p><p>In the scientific literature data analysis results are often presented when samples from different experiments or different conditions, technical replicates or times series are merged to increase the sample size before calculating the correlation coefficient. This way of proceeding violates two basic assumptions underlying the use of the correlation coefficient: sampling from one population and independence of the observations (independence of errors). Since correlations are used to measure and infer associations between biological entities, this has tremendous implications on the reliability of scientific results, as the violation of these assumption leads to wrong and biased results. In this technical note, I review some basic properties of the Pearson's correlation coefficient and illustrate some exemplary problems with simulated and experimental data, taking a didactic approach with the use of supporting graphical examples.</p>","PeriodicalId":73109,"journal":{"name":"Frontiers in systems biology","volume":" ","pages":"1042156"},"PeriodicalIF":2.3,"publicationDate":"2023-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12341968/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47028841","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":"Quantitative systems modeling approaches towards model-informed drug development: Perspective through case studies","authors":"Meghna Verma, Louis Gall, J. Biasetti, G. D. Di Veroli, C. Pichardo-Almarza, M. Gibbs, Holly Kimko","doi":"10.3389/fsysb.2022.1063308","DOIUrl":"https://doi.org/10.3389/fsysb.2022.1063308","url":null,"abstract":"Quantitative systems pharmacology (QSP) modeling has become an increasingly popular approach impacting our understanding of disease mechanisms and helping predict patients’ treatment responses to facilitate study design or development go/no-go decisions. In this paper, we highlight the notable contributions and opportunities that QSP approaches are to offer during the drug development process by sharing three examples that have facilitated internal decisions. The barriers to successful applications and the factors that facilitate the success of the modeling approach is discussed.","PeriodicalId":73109,"journal":{"name":"Frontiers in systems biology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42829618","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":"scMODD: A model-driven algorithm for doublet identification in single-cell RNA-sequencing data","authors":"Xinye Zhao, Alexander Du, Peng-Chao Qiu","doi":"10.3389/fsysb.2022.1082309","DOIUrl":"https://doi.org/10.3389/fsysb.2022.1082309","url":null,"abstract":"Single-cell RNA sequencing (scRNA-seq) data often contain doublets, where a doublet manifests as 1 cell barcode that corresponds to combined gene expression of two or more cells. Existence of doublets can lead to spurious biological interpretations. Here, we present single-cell MOdel-driven Doublet Detection (scMODD), a model-driven algorithm to detect doublets in scRNA-seq data. ScMODD achieved similar performance compared to existing doublet detection algorithms which are primarily data-driven, showing the promise of model-driven approach for doublet detection. When implementing scMODD in simulated and real scRNA-seq data, we tested both the negative binomial (NB) model and the zero-inflated negative binomial (ZINB) model to serve as the underlying statistical model for scRNA-seq count data, and observed that incorporating zero inflation did not improve detection performance, suggesting that consideration of zero inflation is not necessary in the context of doublet detection in scRNA-seq.","PeriodicalId":73109,"journal":{"name":"Frontiers in systems biology","volume":"37 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41295868","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":"Systems biology of asphalt pollutants and their human molecular targets","authors":"Eran Rozewski, Omran Taqi, E. Fini, Nastassja A. Lewinski, J. Klein-Seetharaman","doi":"10.3389/fsysb.2022.928962","DOIUrl":"https://doi.org/10.3389/fsysb.2022.928962","url":null,"abstract":"More than 90% of all the roads in the United States are covered with asphalt, despite hundreds of scientific studies demonstrating the detrimental effect of asphalt on human health. Asphalt is a complex mixture of thousands of compounds. Here, we not only review studies of the effects of asphalt on human health, but go a step further by taking a novel view of these health effects from a systems biology perspective. In particular, we propose an analogy to protein-protein interaction networks, which can be within species and across species when looking at host-pathogen interactions. While in the former, all nodes are of the same type (e.g., human proteins), in the latter nodes can be of different types, such as human proteins and pathogen proteins. To build a corresponding network of interactions between different nodes for asphalt, we retrieved the literature studying the molecular targets of identified components in asphalt and their corresponding cellular biomarkers. Using this approach, we show that a complex trans pollutant-human target network appears in which multiple health effects can be triggered through interactions of multiple pollutant molecules with multiple human targets. We envision that the insights gained from this analysis may assist future efforts at regulating the use of asphalt.","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":"47331715","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":"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}