Pub Date : 2024-05-17DOI: 10.1371/journal.pcbi.1012124
Alexander Massey, C. Boennec, C. X. Restrepo-Ortiz, Christophe Blanchet, Samuel Alizon, Mircea T. Sofonea
Projects such as the European Covid-19 Forecast Hub publish forecasts on the national level for new deaths, new cases, and hospital admissions, but not direct measurements of hospital strain like critical care bed occupancy at the sub-national level, which is of particular interest to health professionals for planning purposes. We present a sub-national French framework for forecasting hospital strain based on a non-Markovian compartmental model, its associated online visualisation tool and a retrospective evaluation of the real-time forecasts it provided from January to December 2021 by comparing to three baselines derived from standard statistical forecasting methods (a naive model, auto-regression, and an ensemble of exponential smoothing and ARIMA). In terms of median absolute error for forecasting critical care unit occupancy at the two-week horizon, our model only outperformed the naive baseline for 4 out of 14 geographical units and underperformed compared to the ensemble baseline for 5 of them at the 90% confidence level (n = 38). However, for the same level at the 4 week horizon, our model was never statistically outperformed for any unit despite outperforming the baselines 10 times spanning 7 out of 14 geographical units. This implies modest forecasting utility for longer horizons which may justify the application of non-Markovian compartmental models in the context of hospital-strain surveillance for future pandemics.
{"title":"Real-time forecasting of COVID-19-related hospital strain in France using a non-Markovian mechanistic model.","authors":"Alexander Massey, C. Boennec, C. X. Restrepo-Ortiz, Christophe Blanchet, Samuel Alizon, Mircea T. Sofonea","doi":"10.1371/journal.pcbi.1012124","DOIUrl":"https://doi.org/10.1371/journal.pcbi.1012124","url":null,"abstract":"Projects such as the European Covid-19 Forecast Hub publish forecasts on the national level for new deaths, new cases, and hospital admissions, but not direct measurements of hospital strain like critical care bed occupancy at the sub-national level, which is of particular interest to health professionals for planning purposes. We present a sub-national French framework for forecasting hospital strain based on a non-Markovian compartmental model, its associated online visualisation tool and a retrospective evaluation of the real-time forecasts it provided from January to December 2021 by comparing to three baselines derived from standard statistical forecasting methods (a naive model, auto-regression, and an ensemble of exponential smoothing and ARIMA). In terms of median absolute error for forecasting critical care unit occupancy at the two-week horizon, our model only outperformed the naive baseline for 4 out of 14 geographical units and underperformed compared to the ensemble baseline for 5 of them at the 90% confidence level (n = 38). However, for the same level at the 4 week horizon, our model was never statistically outperformed for any unit despite outperforming the baselines 10 times spanning 7 out of 14 geographical units. This implies modest forecasting utility for longer horizons which may justify the application of non-Markovian compartmental models in the context of hospital-strain surveillance for future pandemics.","PeriodicalId":49688,"journal":{"name":"PLoS Computational Biology","volume":"5 11","pages":"e1012124"},"PeriodicalIF":4.3,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140963817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-01DOI: 10.1371/journal.pcbi.1012018
Ava M. Hoffman, Carrie Wright
{"title":"Ten simple rules for teaching an introduction to R","authors":"Ava M. Hoffman, Carrie Wright","doi":"10.1371/journal.pcbi.1012018","DOIUrl":"https://doi.org/10.1371/journal.pcbi.1012018","url":null,"abstract":"","PeriodicalId":49688,"journal":{"name":"PLoS Computational Biology","volume":"19 7","pages":""},"PeriodicalIF":4.3,"publicationDate":"2024-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141052879","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-25DOI: 10.1371/journal.pcbi.1012028
Marc D Singleton, Michael B. Eisen
Intrinsically disordered regions (IDRs) are segments of proteins without stable three-dimensional structures. As this flexibility allows them to interact with diverse binding partners, IDRs play key roles in cell signaling and gene expression. Despite the prevalence and importance of IDRs in eukaryotic proteomes and various biological processes, associating them with specific molecular functions remains a significant challenge due to their high rates of sequence evolution. However, by comparing the observed values of various IDR-associated properties against those generated under a simulated model of evolution, a recent study found most IDRs across the entire yeast proteome contain conserved features. Furthermore, it showed clusters of IDRs with common "evolutionary signatures," i.e. patterns of conserved features, were associated with specific biological functions. To determine if similar patterns of conservation are found in the IDRs of other systems, in this work we applied a series of phylogenetic models to over 7,500 orthologous IDRs identified in the Drosophila genome to dissect the forces driving their evolution. By comparing models of constrained and unconstrained continuous trait evolution using the Brownian motion and Ornstein-Uhlenbeck models, respectively, we identified signals of widespread constraint, indicating conservation of distributed features is mechanism of IDR evolution common to multiple biological systems. In contrast to the previous study in yeast, however, we observed limited evidence of IDR clusters with specific biological functions, which suggests a more complex relationship between evolutionary constraints and function in the IDRs of multicellular organisms.
{"title":"Evolutionary analyses of intrinsically disordered regions reveal widespread signals of conservation.","authors":"Marc D Singleton, Michael B. Eisen","doi":"10.1371/journal.pcbi.1012028","DOIUrl":"https://doi.org/10.1371/journal.pcbi.1012028","url":null,"abstract":"Intrinsically disordered regions (IDRs) are segments of proteins without stable three-dimensional structures. As this flexibility allows them to interact with diverse binding partners, IDRs play key roles in cell signaling and gene expression. Despite the prevalence and importance of IDRs in eukaryotic proteomes and various biological processes, associating them with specific molecular functions remains a significant challenge due to their high rates of sequence evolution. However, by comparing the observed values of various IDR-associated properties against those generated under a simulated model of evolution, a recent study found most IDRs across the entire yeast proteome contain conserved features. Furthermore, it showed clusters of IDRs with common \"evolutionary signatures,\" i.e. patterns of conserved features, were associated with specific biological functions. To determine if similar patterns of conservation are found in the IDRs of other systems, in this work we applied a series of phylogenetic models to over 7,500 orthologous IDRs identified in the Drosophila genome to dissect the forces driving their evolution. By comparing models of constrained and unconstrained continuous trait evolution using the Brownian motion and Ornstein-Uhlenbeck models, respectively, we identified signals of widespread constraint, indicating conservation of distributed features is mechanism of IDR evolution common to multiple biological systems. In contrast to the previous study in yeast, however, we observed limited evidence of IDR clusters with specific biological functions, which suggests a more complex relationship between evolutionary constraints and function in the IDRs of multicellular organisms.","PeriodicalId":49688,"journal":{"name":"PLoS Computational Biology","volume":"90 10","pages":"e1012028"},"PeriodicalIF":4.3,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140654809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-25DOI: 10.1371/journal.pcbi.1012005
Florian E C Blanc, A. Houdusse, Marco Cecchini
Myosin motors use the energy of ATP to produce force and directed movement on actin by a swing of the lever arm. ATP is hydrolysed during the off-actin re-priming transition termed recovery stroke. To provide an understanding of chemo-mechanical transduction by myosin, it is critical to determine how the reverse swing of the lever arm and ATP hydrolysis are coupled. Previous studies concluded that the recovery stroke of myosin II is initiated by closure of the Switch II loop in the nucleotide-binding site. Recently, we proposed that the recovery stroke of myosin VI starts with the spontaneous re-priming of the converter domain to a putative pre-transition state (PTS) intermediate that precedes Switch II closing and ATPase activation. Here, we investigate the transition from the pre-recovery, post-rigor (PR) state to PTS in myosin VI using geometric free energy simulations and the string method. First, our calculations rediscover the PTS state agnostically and show that it is accessible from PR via a low free energy transition path. Second, separate path calculations using the string method illuminate the mechanism of the PR to PTS transition with atomic resolution. In this mechanism, the initiating event is a large movement of the converter/lever-arm region that triggers rearrangements in the Relay-SH1 region and the formation of the kink in the Relay helix with no coupling to the active site. Analysis of the free-energy barriers along the path suggests that the converter-initiated mechanism is much faster than the one initiated by Switch II closure, which supports the biological relevance of PTS as a major on-pathway intermediate of the recovery stroke in myosin VI. Our analysis suggests that lever-arm re-priming and ATP hydrolysis are only weakly coupled, so that the myosin recovery stroke is initiated by thermal fluctuations and stabilised by nucleotide consumption via a ratchet-like mechanism.
肌球蛋白马达利用 ATP 的能量通过杠杆臂的摆动在肌动蛋白上产生力和定向运动。在被称为恢复冲程的脱离肌动蛋白再刺激转换过程中，ATP 会被水解。要了解肌球蛋白的化学机械传导，关键是要确定杠杆臂的反向摆动和 ATP 的水解是如何耦合的。以前的研究认为，肌球蛋白 II 的恢复冲程是由核苷酸结合位点开关 II 环的闭合启动的。最近，我们提出肌球蛋白 VI 的恢复冲程始于转换器结构域自发地重新priming 到假定的过渡前状态（PTS）中间体，该中间体先于 Switch II 闭合和 ATP 酶激活。在这里，我们利用几何自由能模拟和弦法研究了肌球蛋白 VI 从恢复前、支撑后（PR）状态到 PTS 的转变。首先，我们的计算以不可知论的方式重新发现了 PTS 状态，并表明它可以通过低自由能过渡路径从 PR 状态进入。其次，利用弦法进行的单独路径计算以原子分辨率阐明了从 PR 到 PTS 的转变机制。在这一机制中，起始事件是转换器/杠杆臂区域的大幅移动，它引发了中继-SH1 区域的重排，并在中继螺旋中形成了与活性位点无耦合的扭结。对路径自由能垒的分析表明，转换器启动的机制比开关 II 关闭启动的机制要快得多，这支持了 PTS 作为肌球蛋白 VI 恢复冲程的主要路径中间体的生物学相关性。我们的分析表明，杠杆臂再刺激和 ATP 水解只是弱耦合，因此肌球蛋白恢复行程是由热波动启动的，并通过类似棘轮的机制由核苷酸消耗稳定下来。
{"title":"A weak coupling mechanism for the early steps of the recovery stroke of myosin VI: A free energy simulation and string method analysis.","authors":"Florian E C Blanc, A. Houdusse, Marco Cecchini","doi":"10.1371/journal.pcbi.1012005","DOIUrl":"https://doi.org/10.1371/journal.pcbi.1012005","url":null,"abstract":"Myosin motors use the energy of ATP to produce force and directed movement on actin by a swing of the lever arm. ATP is hydrolysed during the off-actin re-priming transition termed recovery stroke. To provide an understanding of chemo-mechanical transduction by myosin, it is critical to determine how the reverse swing of the lever arm and ATP hydrolysis are coupled. Previous studies concluded that the recovery stroke of myosin II is initiated by closure of the Switch II loop in the nucleotide-binding site. Recently, we proposed that the recovery stroke of myosin VI starts with the spontaneous re-priming of the converter domain to a putative pre-transition state (PTS) intermediate that precedes Switch II closing and ATPase activation. Here, we investigate the transition from the pre-recovery, post-rigor (PR) state to PTS in myosin VI using geometric free energy simulations and the string method. First, our calculations rediscover the PTS state agnostically and show that it is accessible from PR via a low free energy transition path. Second, separate path calculations using the string method illuminate the mechanism of the PR to PTS transition with atomic resolution. In this mechanism, the initiating event is a large movement of the converter/lever-arm region that triggers rearrangements in the Relay-SH1 region and the formation of the kink in the Relay helix with no coupling to the active site. Analysis of the free-energy barriers along the path suggests that the converter-initiated mechanism is much faster than the one initiated by Switch II closure, which supports the biological relevance of PTS as a major on-pathway intermediate of the recovery stroke in myosin VI. Our analysis suggests that lever-arm re-priming and ATP hydrolysis are only weakly coupled, so that the myosin recovery stroke is initiated by thermal fluctuations and stabilised by nucleotide consumption via a ratchet-like mechanism.","PeriodicalId":49688,"journal":{"name":"PLoS Computational Biology","volume":"30 3","pages":"e1012005"},"PeriodicalIF":4.3,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140657693","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-24DOI: 10.1371/journal.pcbi.1012066
Jong Hyuk Byun, Hye Seon Jeon, Hwi‐yeol Yun, Jae Kyoung Kim
Target-mediated drug disposition (TMDD) is a phenomenon characterized by a drug's high-affinity binding to a target molecule, which significantly influences its pharmacokinetic profile within an organism. The comprehensive TMDD model delineates this interaction, yet it may become overly complex and computationally demanding in the absence of specific concentration data for the target or its complexes. Consequently, simplified TMDD models employing quasi-steady state approximations (QSSAs) have been introduced; however, the precise conditions under which these models yield accurate results require further elucidation. Here, we establish the validity of three simplified TMDD models: the Michaelis-Menten model reduced with the standard QSSA (mTMDD), the QSS model reduced with the total QSSA (qTMDD), and a first-order approximation of the total QSSA (pTMDD). Specifically, we find that mTMDD is applicable only when initial drug concentrations substantially exceed total target concentrations, while qTMDD can be used for all drug concentrations. Notably, pTMDD offers a simpler and faster alternative to qTMDD, with broader applicability than mTMDD. These findings are confirmed with antibody-drug conjugate real-world data. Our findings provide a framework for selecting appropriate simplified TMDD models while ensuring accuracy, potentially enhancing drug development and facilitating safer, more personalized treatments.
{"title":"Validity conditions of approximations for a target-mediated drug disposition model: A novel first-order approximation and its comparison to other approximations.","authors":"Jong Hyuk Byun, Hye Seon Jeon, Hwi‐yeol Yun, Jae Kyoung Kim","doi":"10.1371/journal.pcbi.1012066","DOIUrl":"https://doi.org/10.1371/journal.pcbi.1012066","url":null,"abstract":"Target-mediated drug disposition (TMDD) is a phenomenon characterized by a drug's high-affinity binding to a target molecule, which significantly influences its pharmacokinetic profile within an organism. The comprehensive TMDD model delineates this interaction, yet it may become overly complex and computationally demanding in the absence of specific concentration data for the target or its complexes. Consequently, simplified TMDD models employing quasi-steady state approximations (QSSAs) have been introduced; however, the precise conditions under which these models yield accurate results require further elucidation. Here, we establish the validity of three simplified TMDD models: the Michaelis-Menten model reduced with the standard QSSA (mTMDD), the QSS model reduced with the total QSSA (qTMDD), and a first-order approximation of the total QSSA (pTMDD). Specifically, we find that mTMDD is applicable only when initial drug concentrations substantially exceed total target concentrations, while qTMDD can be used for all drug concentrations. Notably, pTMDD offers a simpler and faster alternative to qTMDD, with broader applicability than mTMDD. These findings are confirmed with antibody-drug conjugate real-world data. Our findings provide a framework for selecting appropriate simplified TMDD models while ensuring accuracy, potentially enhancing drug development and facilitating safer, more personalized treatments.","PeriodicalId":49688,"journal":{"name":"PLoS Computational Biology","volume":"59 11","pages":"e1012066"},"PeriodicalIF":4.3,"publicationDate":"2024-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140665957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-22DOI: 10.1371/journal.pcbi.1012054
Florian G. Pflug, Simon Haendeler, Christopher Esk, Dominik Lindenhofer, Jurgen Knoblich, A. von Haeseler
Neural organoids model the development of the human brain and are an indispensable tool for studying neurodevelopment. Whole-organoid lineage tracing has revealed the number of progenies arising from each initial stem cell to be highly diverse, with lineage sizes ranging from one to more than 20,000 cells. This high variability exceeds what can be explained by existing stochastic models of corticogenesis and indicates the existence of an additional source of stochasticity. To explain this variability, we introduce the SAN model which distinguishes Symmetrically diving, Asymmetrically dividing, and Non-proliferating cells. In the SAN model, the additional source of stochasticity is the survival time of a lineage's pool of symmetrically dividing cells. These survival times result from neutral competition within the sub-population of all symmetrically dividing cells. We demonstrate that our model explains the experimentally observed variability of lineage sizes and derive the quantitative relationship between survival time and lineage size. We also show that our model implies the existence of a regulatory mechanism which keeps the size of the symmetrically dividing cell population constant. Our results provide quantitative insight into the clonal composition of neural organoids and how it arises. This is relevant for many applications of neural organoids, and similar processes may occur in other developing tissues both in vitro and in vivo.
神经器官模拟人脑的发育，是研究神经发育不可或缺的工具。对整个器官组织进行的系谱追踪显示，每个初始干细胞产生的后代数量高度多样化，系谱大小从一个细胞到超过20,000个细胞不等。这种高变异性超出了现有的皮质发生随机模型所能解释的范围，表明还存在一个额外的随机性来源。为了解释这种变异性，我们引入了 SAN 模型，该模型区分了对称潜行细胞、非对称分裂细胞和非增殖细胞。在 SAN 模型中，随机性的额外来源是一个系的对称分裂细胞池的存活时间。这些存活时间来自所有对称分裂细胞亚群内部的中性竞争。我们证明，我们的模型可以解释实验观察到的品系大小的变化，并推导出存活时间与品系大小之间的定量关系。我们还证明，我们的模型意味着存在一种调节机制，它能使对称分裂细胞群的大小保持恒定。我们的研究结果提供了对神经器官组织克隆组成及其产生方式的定量洞察。这与神经器官组织的许多应用相关，类似的过程也可能发生在体外和体内的其他发育组织中。
{"title":"Neutral competition explains the clonal composition of neural organoids.","authors":"Florian G. Pflug, Simon Haendeler, Christopher Esk, Dominik Lindenhofer, Jurgen Knoblich, A. von Haeseler","doi":"10.1371/journal.pcbi.1012054","DOIUrl":"https://doi.org/10.1371/journal.pcbi.1012054","url":null,"abstract":"Neural organoids model the development of the human brain and are an indispensable tool for studying neurodevelopment. Whole-organoid lineage tracing has revealed the number of progenies arising from each initial stem cell to be highly diverse, with lineage sizes ranging from one to more than 20,000 cells. This high variability exceeds what can be explained by existing stochastic models of corticogenesis and indicates the existence of an additional source of stochasticity. To explain this variability, we introduce the SAN model which distinguishes Symmetrically diving, Asymmetrically dividing, and Non-proliferating cells. In the SAN model, the additional source of stochasticity is the survival time of a lineage's pool of symmetrically dividing cells. These survival times result from neutral competition within the sub-population of all symmetrically dividing cells. We demonstrate that our model explains the experimentally observed variability of lineage sizes and derive the quantitative relationship between survival time and lineage size. We also show that our model implies the existence of a regulatory mechanism which keeps the size of the symmetrically dividing cell population constant. Our results provide quantitative insight into the clonal composition of neural organoids and how it arises. This is relevant for many applications of neural organoids, and similar processes may occur in other developing tissues both in vitro and in vivo.","PeriodicalId":49688,"journal":{"name":"PLoS Computational Biology","volume":"5 4","pages":"e1012054"},"PeriodicalIF":4.3,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140672772","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-22DOI: 10.1371/journal.pcbi.1012029
Bingxian Xu, D. Hwangbo, Sumit Saurabh, C. Rosensweig, Ravi Allada, William L. Kath, Rosemary Braun
The circadian clock is an evolutionarily-conserved molecular oscillator that enables species to anticipate rhythmic changes in their environment. At a molecular level, the core clock genes induce circadian oscillations in thousands of genes in a tissue-specific manner, orchestrating myriad biological processes. While previous studies have investigated how the core clock circuit responds to environmental perturbations such as temperature, the downstream effects of such perturbations on circadian regulation remain poorly understood. By analyzing bulk-RNA sequencing of Drosophila fat bodies harvested from flies subjected to different environmental conditions, we demonstrate a highly condition-specific circadian transcriptome: genes are cycling in a temperature-specific manner, and the distributions of their phases also differ between the two conditions. Further employing a reference-based gene regulatory network (Reactome), we find evidence of increased gene-gene coordination at low temperatures and synchronization of rhythmic genes that are network neighbors. We report that the phase differences between cycling genes increase as a function of geodesic distance in the low temperature condition, suggesting increased coordination of cycling on the gene regulatory network. Our results suggest a potential mechanism whereby the circadian clock mediates the fly's response to seasonal changes in temperature.
{"title":"Temperature-driven coordination of circadian transcriptional regulation.","authors":"Bingxian Xu, D. Hwangbo, Sumit Saurabh, C. Rosensweig, Ravi Allada, William L. Kath, Rosemary Braun","doi":"10.1371/journal.pcbi.1012029","DOIUrl":"https://doi.org/10.1371/journal.pcbi.1012029","url":null,"abstract":"The circadian clock is an evolutionarily-conserved molecular oscillator that enables species to anticipate rhythmic changes in their environment. At a molecular level, the core clock genes induce circadian oscillations in thousands of genes in a tissue-specific manner, orchestrating myriad biological processes. While previous studies have investigated how the core clock circuit responds to environmental perturbations such as temperature, the downstream effects of such perturbations on circadian regulation remain poorly understood. By analyzing bulk-RNA sequencing of Drosophila fat bodies harvested from flies subjected to different environmental conditions, we demonstrate a highly condition-specific circadian transcriptome: genes are cycling in a temperature-specific manner, and the distributions of their phases also differ between the two conditions. Further employing a reference-based gene regulatory network (Reactome), we find evidence of increased gene-gene coordination at low temperatures and synchronization of rhythmic genes that are network neighbors. We report that the phase differences between cycling genes increase as a function of geodesic distance in the low temperature condition, suggesting increased coordination of cycling on the gene regulatory network. Our results suggest a potential mechanism whereby the circadian clock mediates the fly's response to seasonal changes in temperature.","PeriodicalId":49688,"journal":{"name":"PLoS Computational Biology","volume":"50 7","pages":"e1012029"},"PeriodicalIF":4.3,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140676072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-18DOI: 10.1371/journal.pcbi.1012013
Kamil Wołos, L. Pstras, M. Debowska, Wojciech Dabrowski, Dorota Siwicka-Gieroba, Jan Poleszczuk
Cardiovascular diseases are the leading cause of death globally, making the development of non-invasive and simple-to-use tools that bring insights into the state of the cardiovascular system of utmost importance. We investigated the possibility of using peripheral pulse wave recordings to estimate stroke volume (SV) and subject-specific parameters describing the selected properties of the cardiovascular system. Peripheral pressure waveforms were recorded in the radial artery using applanation tonometry (SphygmoCor) in 35 hemodialysis (HD) patients and 14 healthy subjects. The pressure waveforms were then used to estimate subject-specific parameters of a mathematical model of pulse wave propagation coupled with the elastance-based model of the left ventricle. Bioimpedance cardiography measurements (PhysioFlow) were performed to validate the model-estimated SV. Mean absolute percentage error between the simulated and measured pressure waveforms was 4.0% and 2.8% for the HD and control group, respectively. We obtained a moderate correlation between the model-estimated and bioimpedance-based SV (r = 0.57, p<0.05, and r = 0.58, p<0.001, for the control group and HD patients, respectively). We also observed a correlation between the estimated end-systolic elastance of the left ventricle and the peripheral systolic pressure in both HD patients (r = 0.84, p<0.001) and the control group (r = 0.70, p<0.01). These preliminary results suggest that, after additional validation and possibly further refinement to increase accuracy, the proposed methodology could support non-invasive assessment of stroke volume and selected heart function parameters and vascular properties. Importantly, the proposed method could be potentially implemented in the existing devices measuring peripheral pressure waveforms.
心血管疾病是导致全球死亡的主要原因，因此开发能深入了解心血管系统状态的无创且简单易用的工具至关重要。我们研究了使用外周脉搏波记录来估算每搏量（SV）和描述心血管系统选定特性的特定受试者参数的可能性。我们使用眼压计（SphygmoCor）记录了 35 名血液透析（HD）患者和 14 名健康受试者桡动脉的外周压力波形。然后利用压力波形估算脉搏波传播数学模型和基于弹性的左心室模型的特定受试者参数。生物阻抗心动图测量（PhysioFlow）对模型估计的 SV 进行了验证。对于 HD 组和对照组，模拟压力波形和测量压力波形之间的平均绝对百分比误差分别为 4.0% 和 2.8%。模型估计的 SV 与基于生物阻抗的 SV 之间存在中度相关性（对照组和 HD 患者的相关性分别为 r = 0.57，p<0.05；r = 0.58，p<0.001）。我们还观察到，HD 患者（r = 0.84，p<0.001）和对照组（r = 0.70，p<0.01）的左心室收缩末期弹性估计值与外周收缩压之间存在相关性。这些初步结果表明，经过进一步验证和可能的进一步改进以提高准确性后，所建议的方法可支持对卒中量和选定的心脏功能参数及血管特性进行无创评估。重要的是，建议的方法有可能在现有的外周压力波形测量设备中实施。
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Pub Date : 2024-04-17DOI: 10.1371/journal.pcbi.1011562
Scott Boebinger, Aiden M. Payne, Giovanni Martino, Kennedy Kerr, Jasmine L Mirdamadi, J. L. McKay, Michael R Borich, Lena H Ting
The role of the cortex in shaping automatic whole-body motor behaviors such as walking and balance is poorly understood. Gait and balance are typically mediated through subcortical circuits, with the cortex becoming engaged as needed on an individual basis by task difficulty and complexity. However, we lack a mechanistic understanding of how increased cortical contribution to whole-body movements shapes motor output. Here we use reactive balance recovery as a paradigm to identify relationships between hierarchical control mechanisms and their engagement across balance tasks of increasing difficulty in young adults. We hypothesize that parallel sensorimotor feedback loops engaging subcortical and cortical circuits contribute to balance-correcting muscle activity, and that the involvement of cortical circuits increases with balance challenge. We decomposed balance-correcting muscle activity based on hypothesized subcortically- and cortically-mediated feedback components driven by similar sensory information, but with different loop delays. The initial balance-correcting muscle activity was engaged at all levels of balance difficulty. Its onset latency was consistent with subcortical sensorimotor loops observed in the lower limb. An even later, presumed, cortically-mediated burst of muscle activity became additionally engaged as balance task difficulty increased, at latencies consistent with longer transcortical sensorimotor loops. We further demonstrate that evoked cortical activity in central midline areas measured using electroencephalography (EEG) can be explained by a similar sensory transformation as muscle activity but at a delay consistent with its role in a transcortical loop driving later cortical contributions to balance-correcting muscle activity. These results demonstrate that a neuromechanical model of muscle activity can be used to infer cortical contributions to muscle activity without recording brain activity. Our model may provide a useful framework for evaluating changes in cortical contributions to balance that are associated with falls in older adults and in neurological disorders such as Parkinson's disease.
{"title":"Precise cortical contributions to sensorimotor feedback control during reactive balance.","authors":"Scott Boebinger, Aiden M. Payne, Giovanni Martino, Kennedy Kerr, Jasmine L Mirdamadi, J. L. McKay, Michael R Borich, Lena H Ting","doi":"10.1371/journal.pcbi.1011562","DOIUrl":"https://doi.org/10.1371/journal.pcbi.1011562","url":null,"abstract":"The role of the cortex in shaping automatic whole-body motor behaviors such as walking and balance is poorly understood. Gait and balance are typically mediated through subcortical circuits, with the cortex becoming engaged as needed on an individual basis by task difficulty and complexity. However, we lack a mechanistic understanding of how increased cortical contribution to whole-body movements shapes motor output. Here we use reactive balance recovery as a paradigm to identify relationships between hierarchical control mechanisms and their engagement across balance tasks of increasing difficulty in young adults. We hypothesize that parallel sensorimotor feedback loops engaging subcortical and cortical circuits contribute to balance-correcting muscle activity, and that the involvement of cortical circuits increases with balance challenge. We decomposed balance-correcting muscle activity based on hypothesized subcortically- and cortically-mediated feedback components driven by similar sensory information, but with different loop delays. The initial balance-correcting muscle activity was engaged at all levels of balance difficulty. Its onset latency was consistent with subcortical sensorimotor loops observed in the lower limb. An even later, presumed, cortically-mediated burst of muscle activity became additionally engaged as balance task difficulty increased, at latencies consistent with longer transcortical sensorimotor loops. We further demonstrate that evoked cortical activity in central midline areas measured using electroencephalography (EEG) can be explained by a similar sensory transformation as muscle activity but at a delay consistent with its role in a transcortical loop driving later cortical contributions to balance-correcting muscle activity. These results demonstrate that a neuromechanical model of muscle activity can be used to infer cortical contributions to muscle activity without recording brain activity. Our model may provide a useful framework for evaluating changes in cortical contributions to balance that are associated with falls in older adults and in neurological disorders such as Parkinson's disease.","PeriodicalId":49688,"journal":{"name":"PLoS Computational Biology","volume":"170 4","pages":"e1011562"},"PeriodicalIF":4.3,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140693413","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-17DOI: 10.1371/journal.pcbi.1012016
Satyaki Roy, S. Sheikh, T. Furey
Network inference is used to model transcriptional, signaling, and metabolic interactions among genes, proteins, and metabolites that identify biological pathways influencing disease pathogenesis. Advances in machine learning (ML)-based inference models exhibit the predictive capabilities of capturing latent patterns in genomic data. Such models are emerging as an alternative to the statistical models identifying causative factors driving complex diseases. We present CoVar, an ML-based framework that builds upon the properties of existing inference models, to find the central genes driving perturbed gene expression across biological states. Unlike differentially expressed genes (DEGs) that capture changes in individual gene expression across conditions, CoVar focuses on identifying variational genes that undergo changes in their expression network interaction profiles, providing insights into changes in the regulatory dynamics, such as in disease pathogenesis. Subsequently, it finds core genes from among the nearest neighbors of these variational genes, which are central to the variational activity and influence the coordinated regulatory processes underlying the observed changes in gene expression. Through the analysis of simulated as well as yeast expression data perturbed by the deletion of the mitochondrial genome, we show that CoVar captures the intrinsic variationality and modularity in the expression data, identifying key driver genes not found through existing differential analysis methodologies.
网络推断用于模拟基因、蛋白质和代谢物之间的转录、信号和代谢相互作用，从而确定影响疾病发病机制的生物通路。基于机器学习（ML）的推理模型取得的进展显示了捕捉基因组数据中潜在模式的预测能力。这些模型正在成为确定复杂疾病致病因素的统计模型的替代方案。我们提出的 CoVar 是一种基于 ML 的框架，它以现有推理模型的特性为基础，用于寻找驱动跨生物状态基因表达扰动的中心基因。与捕捉不同条件下单个基因表达变化的差异表达基因（DEGs）不同，CoVar 侧重于识别表达网络交互图谱发生变化的变异基因，从而深入了解疾病发病机制等调控动态的变化。随后，它从这些变异基因的近邻中找到核心基因，这些基因是变异活动的核心，影响着观察到的基因表达变化背后的协调调控过程。通过分析模拟数据和线粒体基因组缺失扰动的酵母表达数据，我们发现 CoVar 能够捕捉表达数据的内在变异性和模块性，识别出现有差异分析方法无法发现的关键驱动基因。
{"title":"CoVar: A generalizable machine learning approach to identify the coordinated regulators driving variational gene expression.","authors":"Satyaki Roy, S. Sheikh, T. Furey","doi":"10.1371/journal.pcbi.1012016","DOIUrl":"https://doi.org/10.1371/journal.pcbi.1012016","url":null,"abstract":"Network inference is used to model transcriptional, signaling, and metabolic interactions among genes, proteins, and metabolites that identify biological pathways influencing disease pathogenesis. Advances in machine learning (ML)-based inference models exhibit the predictive capabilities of capturing latent patterns in genomic data. Such models are emerging as an alternative to the statistical models identifying causative factors driving complex diseases. We present CoVar, an ML-based framework that builds upon the properties of existing inference models, to find the central genes driving perturbed gene expression across biological states. Unlike differentially expressed genes (DEGs) that capture changes in individual gene expression across conditions, CoVar focuses on identifying variational genes that undergo changes in their expression network interaction profiles, providing insights into changes in the regulatory dynamics, such as in disease pathogenesis. Subsequently, it finds core genes from among the nearest neighbors of these variational genes, which are central to the variational activity and influence the coordinated regulatory processes underlying the observed changes in gene expression. Through the analysis of simulated as well as yeast expression data perturbed by the deletion of the mitochondrial genome, we show that CoVar captures the intrinsic variationality and modularity in the expression data, identifying key driver genes not found through existing differential analysis methodologies.","PeriodicalId":49688,"journal":{"name":"PLoS Computational Biology","volume":" 12","pages":"e1012016"},"PeriodicalIF":4.3,"publicationDate":"2024-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140690733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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