Pub Date : 2024-09-13DOI: 10.1101/2024.08.14.607902
Miguel Gonzalez Acera, Jay V Patankar, Lena Erkert, Roodline Cineus, Reyes Gamez Belmonte, Tamara Leupold, Marvin Bubeck, Li-li Bao, Martin Dinkel, Ru Wang, Heidi Limberger, Iris Stolzer, Katharina Gerlach, Fabrizio Mascia, Kristina Koop, Christina Plattner, Gregor Sturm, Benno Weigmann, Claudia Guenther, Stefan Wirtz, Kai Hildner, Anja A Kuehl, Britta Siegmund, Raja Atreya, The IBDome Consortium, Ahmed N Hegazy, Zlatko Trajanoski, Markus F Neurath, Christoph Becker
Inflammatory bowel disease (IBD) is a chronic inflammatory condition of the intestine with a complex and multifaceted pathogenesis. While various animal models exist to study specific disease mechanisms relevant to human IBD, a comprehensive comparative framework linking these to IBD pathophysiology is lacking. In this study, we provide a framework that delineates common and unique features encountered at the transcriptomic level in 13 widely used mouse models, employing both curation-based and statistically correlative analyses. Our comparative transcriptomic analyses between mouse models versus established as well as new patient datasets reveal specific disease mechanisms in IBD. Furthermore, we identify IBD-related pathways, ontologies, and cellular processes that are comparable between mouse models and patient cohorts. Our findings provide a valuable resource for selecting the most appropriate experimental paradigm to model unique features of IBD pathogenesis, allowing analysis at the tissue, cellular, and subcellular levels.
{"title":"Integrated multi-model analysis of intestinal inflammation exposes key molecular features of preclinical and clinical IBD","authors":"Miguel Gonzalez Acera, Jay V Patankar, Lena Erkert, Roodline Cineus, Reyes Gamez Belmonte, Tamara Leupold, Marvin Bubeck, Li-li Bao, Martin Dinkel, Ru Wang, Heidi Limberger, Iris Stolzer, Katharina Gerlach, Fabrizio Mascia, Kristina Koop, Christina Plattner, Gregor Sturm, Benno Weigmann, Claudia Guenther, Stefan Wirtz, Kai Hildner, Anja A Kuehl, Britta Siegmund, Raja Atreya, The IBDome Consortium, Ahmed N Hegazy, Zlatko Trajanoski, Markus F Neurath, Christoph Becker","doi":"10.1101/2024.08.14.607902","DOIUrl":"https://doi.org/10.1101/2024.08.14.607902","url":null,"abstract":"Inflammatory bowel disease (IBD) is a chronic inflammatory condition of the intestine with a complex and multifaceted pathogenesis. While various animal models exist to study specific disease mechanisms relevant to human IBD, a comprehensive comparative framework linking these to IBD pathophysiology is lacking. In this study, we provide a framework that delineates common and unique features encountered at the transcriptomic level in 13 widely used mouse models, employing both curation-based and statistically correlative analyses. Our comparative transcriptomic analyses between mouse models versus established as well as new patient datasets reveal specific disease mechanisms in IBD. Furthermore, we identify IBD-related pathways, ontologies, and cellular processes that are comparable between mouse models and patient cohorts. Our findings provide a valuable resource for selecting the most appropriate experimental paradigm to model unique features of IBD pathogenesis, allowing analysis at the tissue, cellular, and subcellular levels.","PeriodicalId":501213,"journal":{"name":"bioRxiv - Systems Biology","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142202733","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-10DOI: 10.1101/2024.09.06.611749
Sadia Siddika Dima, Gregory T Reeves
Gene regulation by transcription factors (TFs) binding cognate sequences is of paramount importance in development and homeostasis. However, quantitative dose/response relationships between bulk TF concentration and the DNA binding, an event tied to transcriptional activity, remain elusive. Here, we map these relationships during a crucial step in metazoan development: the transcriptional activation of the zygotic genome. In Drosophila, zygotic genome activation (ZGA) begins with the transcription of a handful of genes during the minor wave of ZGA, followed by the major wave when thousands of genes are transcribed. The TF Zelda (Zld) has the ability to bind nucleosomal DNA and subsequently to facilitate the binding of other TFs: the two defining features of a special class of TFs known as pioneer factors. The maternally encoded TF GAGA factor (GAF) also possesses pioneer-like properties. To map the dose/response relationship between nuclear concentration and DNA binding, we performed raster image correlation spectroscopy, a method that can measure concentration and binding of fluorescent molecules. We found that, although Zld concentration increases over time, its DNA binding in the transcriptionally active regions decreases, consistent with its function as an activator for early genes. In contrast, GAF DNA binding is nearly linear with its concentration, which sharply increases during the major wave, implicating it in the major wave. This study provides key insights into the properties of the two factors and puts forward a quantitative approach that can be used for other TFs to study transcriptional regulation.
转录因子（TF）结合同源序列对基因的调控在发育和稳态中至关重要。然而，大量 TF 浓度与 DNA 结合（一种与转录活性相关的事件）之间的定量剂量/反应关系仍然难以捉摸。在这里，我们绘制了这些关系在后生动物发育过程中的一个关键步骤：子代基因组的转录激活。在果蝇中，子代基因组激活（ZGA）始于 ZGA 小波期间少数基因的转录，随后是数千个基因转录的大波。TF Zelda（Zld）能够与核糖体 DNA 结合，随后促进其他 TF 的结合：这是被称为先驱因子的一类特殊 TF 的两个决定性特征。母体编码的 TF GAGA 因子（GAF）也具有类似先锋因子的特性。为了绘制核浓度与 DNA 结合之间的剂量/反应关系图，我们采用了光栅图像相关光谱法，这种方法可以测量荧光分子的浓度和结合情况。我们发现，虽然Zld的浓度会随着时间的推移而增加，但它在转录活跃区域的DNA结合力却在下降，这与它作为早期基因激活剂的功能是一致的。与此相反，GAF 的 DNA 结合力与其浓度几乎呈线性关系，而其浓度在大波期间急剧增加，这表明它与大波有关。这项研究提供了有关这两种因子特性的重要见解，并提出了一种定量方法，可用于其他 TF 的转录调控研究。
{"title":"Bulk-level maps of pioneer factor binding dynamics during Drosophila maternal-to-zygotic transition","authors":"Sadia Siddika Dima, Gregory T Reeves","doi":"10.1101/2024.09.06.611749","DOIUrl":"https://doi.org/10.1101/2024.09.06.611749","url":null,"abstract":"Gene regulation by transcription factors (TFs) binding cognate sequences is of paramount importance in development and homeostasis. However, quantitative dose/response relationships between bulk TF concentration and the DNA binding, an event tied to transcriptional activity, remain elusive. Here, we map these relationships during a crucial step in metazoan development: the transcriptional activation of the zygotic genome. In Drosophila, zygotic genome activation (ZGA) begins with the transcription of a handful of genes during the minor wave of ZGA, followed by the major wave when thousands of genes are transcribed. The TF Zelda (Zld) has the ability to bind nucleosomal DNA and subsequently to facilitate the binding of other TFs: the two defining features of a special class of TFs known as pioneer factors. The maternally encoded TF GAGA factor (GAF) also possesses pioneer-like properties. To map the dose/response relationship between nuclear concentration and DNA binding, we performed raster image correlation spectroscopy, a method that can measure concentration and binding of fluorescent molecules. We found that, although Zld concentration increases over time, its DNA binding in the transcriptionally active regions decreases, consistent with its function as an activator for early genes. In contrast, GAF DNA binding is nearly linear with its concentration, which sharply increases during the major wave, implicating it in the major wave. This study provides key insights into the properties of the two factors and puts forward a quantitative approach that can be used for other TFs to study transcriptional regulation.","PeriodicalId":501213,"journal":{"name":"bioRxiv - Systems Biology","volume":"31 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142202734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-10DOI: 10.1101/2024.09.05.611398
Kajsa Tunedal, Tino Ebbers, Gunnar Cedersund
Cardiovascular digital twins and mechanistic models can be used to obtain new biomarkers from patient-specific hemodynamic data. However, such model-derived biomarkers are only clinically relevant if the variation between timepoints/patients is smaller than the uncertainty of the biomarkers. Unfortunately, this uncertainty is challenging to calculate, as the uncertainty of the underlying hemodynamic data is largely unknown and has several sources that are not additive or normally distributed. This violates normality assumptions of current methods; implying that also biomarkers have an unknown uncertainty. To remedy these problems, we herein present a method, with attached code, for uncertainty calculation of model-derived biomarkers using non-normal data. First, we estimated all sources of uncertainty, both normal and non-normal, in hemodynamic data used to personalize an existing model; the errors in 4D flow MRI-derived stroke volumes were 5-20% and the blood pressure errors were 0+-8 mmHg. Second, we estimated the resulting model-derived biomarker uncertainty for 100 simulated datasets, sampled from the data distributions, by: 1) combining data uncertainties 2) parameter estimation, 3) profile-likelihood. The true biomarker values were found within a 95% confidence interval in 98% (median) of the cases. This shows both that our estimated data uncertainty is reasonable, and that we can use profile-likelihood despite the non-normality. Finally, we demonstrated that e.g. ventricular relaxation rate has a smaller uncertainty (~10%) than the variation across a clinical cohort (~40%), meaning that these biomarkers have clinical usefulness. Our results take us one step closer to the usage of model-derived biomarkers for cardiovascular patient characterization.
{"title":"Uncertainty in cardiovascular digital twins despite non-normal errors in 4D flow MRI: identifying reliable biomarkers such as ventricular relaxation rate","authors":"Kajsa Tunedal, Tino Ebbers, Gunnar Cedersund","doi":"10.1101/2024.09.05.611398","DOIUrl":"https://doi.org/10.1101/2024.09.05.611398","url":null,"abstract":"Cardiovascular digital twins and mechanistic models can be used to obtain new biomarkers from patient-specific hemodynamic data. However, such model-derived biomarkers are only clinically relevant if the variation between timepoints/patients is smaller than the uncertainty of the biomarkers. Unfortunately, this uncertainty is challenging to calculate, as the uncertainty of the underlying hemodynamic data is largely unknown and has several sources that are not additive or normally distributed. This violates normality assumptions of current methods; implying that also biomarkers have an unknown uncertainty. To remedy these problems, we herein present a method, with attached code, for uncertainty calculation of model-derived biomarkers using non-normal data. First, we estimated all sources of uncertainty, both normal and non-normal, in hemodynamic data used to personalize an existing model; the errors in 4D flow MRI-derived stroke volumes were 5-20% and the blood pressure errors were 0+-8 mmHg. Second, we estimated the resulting model-derived biomarker uncertainty for 100 simulated datasets, sampled from the data distributions, by: 1) combining data uncertainties 2) parameter estimation, 3) profile-likelihood. The true biomarker values were found within a 95% confidence interval in 98% (median) of the cases. This shows both that our estimated data uncertainty is reasonable, and that we can use profile-likelihood despite the non-normality. Finally, we demonstrated that e.g. ventricular relaxation rate has a smaller uncertainty (~10%) than the variation across a clinical cohort (~40%), meaning that these biomarkers have clinical usefulness. Our results take us one step closer to the usage of model-derived biomarkers for cardiovascular patient characterization.","PeriodicalId":501213,"journal":{"name":"bioRxiv - Systems Biology","volume":"4 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142202736","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-10DOI: 10.1101/2024.09.05.611487
Jeremy Vicencio, Daisuke Chihara, Matthias Eder, Julie Ahringer, Nicholas Stroustrup
The physiological mechanisms governing health and disease exhibit complex interactions between multiple genes and gene products. To study the dynamics of living systems, researchers need experimental methods capable of producing calibrated, quantitative perturbations in vivo — perturbations that cannot be obtained using classical genetics, RNAi interference, or small molecule drugs. Recently, an auxin-inducible degron (AID) system has been developed to allow targeted degradation of proteins using small-molecule activators, providing spatiotemporal control of protein abundance. However, a better understanding of the biochemical activities of AID system components in their physiological context is needed to design quantitative interventions. Here, we apply engineering approaches to characterize and understand the performance of several AID technologies and then improve this performance in the multicellular animal Caenorhabditis elegans. We 1) develop new technologies that allow for a careful calibration of AID activity for specific purposes; 2) develop new TIR1 enzyme constructs with improved performance over existing constructs; 3) develop an approach to simultaneously and independently degrade target proteins in distinct tissues; and finally, 4) develop an approach for pan-organismal protein degradation by re-engineering the TIR1 enzyme. Taken together, these advances enable new quantitative experimental approaches to study the cellular and systems dynamics of animals.
支配健康和疾病的生理机制表现出多个基因和基因产物之间复杂的相互作用。为了研究生命系统的动力学，研究人员需要能够在体内产生校准、定量扰动的实验方法--这些扰动是经典遗传学、RNAi 干扰或小分子药物无法获得的。最近，人们开发了一种辅助素诱导降解子（AID）系统，利用小分子激活剂对蛋白质进行定向降解，从而实现对蛋白质丰度的时空控制。在这里，我们应用工程学方法来描述和了解几种 AID 技术的性能，然后在多细胞动物秀丽隐杆线虫中改善这种性能。我们：1）开发了新技术，可以针对特定目的仔细校准 AID 活性；2）开发了新的 TIR1 酶构建体，其性能比现有构建体有所提高；3）开发了一种在不同组织中同时独立降解目标蛋白质的方法；最后，4）开发了一种通过重新设计 TIR1 酶实现泛生物体蛋白质降解的方法。总之，这些进展将为研究动物的细胞和系统动态提供新的定量实验方法。
{"title":"Engineering the auxin-inducible degron system for tunable in vivo control of organismal physiology","authors":"Jeremy Vicencio, Daisuke Chihara, Matthias Eder, Julie Ahringer, Nicholas Stroustrup","doi":"10.1101/2024.09.05.611487","DOIUrl":"https://doi.org/10.1101/2024.09.05.611487","url":null,"abstract":"The physiological mechanisms governing health and disease exhibit complex interactions between multiple genes and gene products. To study the dynamics of living systems, researchers need experimental methods capable of producing calibrated, quantitative perturbations <em>in vivo</em> — perturbations that cannot be obtained using classical genetics, RNAi interference, or small molecule drugs. Recently, an auxin-inducible degron (AID) system has been developed to allow targeted degradation of proteins using small-molecule activators, providing spatiotemporal control of protein abundance. However, a better understanding of the biochemical activities of AID system components in their physiological context is needed to design quantitative interventions.\u0000Here, we apply engineering approaches to characterize and understand the performance of several AID technologies and then improve this performance in the multicellular animal <em>Caenorhabditis elegans</em>. We 1) develop new technologies that allow for a careful calibration of AID activity for specific purposes; 2) develop new TIR1 enzyme constructs with improved performance over existing constructs; 3) develop an approach to simultaneously and independently degrade target proteins in distinct tissues; and finally, 4) develop an approach for pan-organismal protein degradation by re-engineering the TIR1 enzyme. Taken together, these advances enable new quantitative experimental approaches to study the cellular and systems dynamics of animals.","PeriodicalId":501213,"journal":{"name":"bioRxiv - Systems Biology","volume":"39 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142202735","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-09DOI: 10.1101/2024.09.05.611545
David Deritei, Wardatul Jannat Anamika, Xiaobo Zhou, Edwin K Silverman, Erzsebet Ravasz Regan, Kimberly Glass
A genetic variant near HHIP has been consistently identified as associated with increased risk for Chronic Obstructive Pulmonary Disease (COPD), the third leading cause of death worldwide. However HHIP's role in COPD pathogenesis remains elusive. Canonically, HHIP is a negative regulator of the hedgehog pathway and downstream GLI1 and GLI2 activation. The hedgehog pathway plays an important role in wound healing, specifically in activating transcription factors that drive the epithelial mesenchymal transition (EMT), which in its intermediate state (partial EMT) is necessary for the collective movement of cells closing the wound. Herein, we propose a mechanism to explain HHIP's role in faulty epithelial wound healing, which could contribute to the development of emphysema, a key feature of COPD. Using two different Boolean models compiled from the literature, we show dysfunctional HHIP results in a lack of negative feedback on GLI, triggering a full EMT, where cells become mesenchymal and do not properly close the wound. We validate these Boolean models with experimental evidence gathered from published scientific literature. We also experimentally test if low HHIP expression is associated with EMT at the edge of wounds by using a scratch assay in a human lung epithelial cell line. Finally, we show evidence supporting our hypothesis in bulk and single cell RNA-Seq data from different COPD cohorts. Overall, our analyses suggest that aberrant wound healing due to dysfunctional HHIP, combined with chronic epithelial damage through cigarette smoke exposure, may be a primary cause of COPD-associated emphysema.
{"title":"HHIP's Dynamic Role in Epithelial Wound Healing Reveals a Potential Mechanism of COPD Susceptibility","authors":"David Deritei, Wardatul Jannat Anamika, Xiaobo Zhou, Edwin K Silverman, Erzsebet Ravasz Regan, Kimberly Glass","doi":"10.1101/2024.09.05.611545","DOIUrl":"https://doi.org/10.1101/2024.09.05.611545","url":null,"abstract":"A genetic variant near HHIP has been consistently identified as associated with increased risk for Chronic Obstructive Pulmonary Disease (COPD), the third leading cause of death worldwide. However HHIP's role in COPD pathogenesis remains elusive. Canonically, HHIP is a negative regulator of the hedgehog pathway and downstream GLI1 and GLI2 activation. The hedgehog pathway plays an important role in wound healing, specifically in activating transcription factors that drive the epithelial mesenchymal transition (EMT), which in its intermediate state (partial EMT) is necessary for the collective movement of cells closing the wound. Herein, we propose a mechanism to explain HHIP's role in faulty epithelial wound healing, which could contribute to the development of emphysema, a key feature of COPD. Using two different Boolean models compiled from the literature, we show dysfunctional HHIP results in a lack of negative feedback on GLI, triggering a full EMT, where cells become mesenchymal and do not properly close the wound. We validate these Boolean models with experimental evidence gathered from published scientific literature. We also experimentally test if low HHIP expression is associated with EMT at the edge of wounds by using a scratch assay in a human lung epithelial cell line. Finally, we show evidence supporting our hypothesis in bulk and single cell RNA-Seq data from different COPD cohorts. Overall, our analyses suggest that aberrant wound healing due to dysfunctional HHIP, combined with chronic epithelial damage through cigarette smoke exposure, may be a primary cause of COPD-associated emphysema.","PeriodicalId":501213,"journal":{"name":"bioRxiv - Systems Biology","volume":"10 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142202753","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-08DOI: 10.1101/2024.09.04.611257
Zhenzhen Shi, Shuo Xiao, Qiang Zhang
Background: Endocrine-disrupting chemicals (EDCs) often exhibit nonmonotonic dose-response (NMDR) relationships, posing significant challenges to health risk assessment and regulations. Several molecular mechanisms operating locally in cells have been proposed, including opposing actions via different receptors, mixed-ligand heterodimer formation, and receptor downregulation. Systemic negative feedback regulation of hormone homeostasis, which is a common feature of many endocrine systems, has also been invoked as a mechanism; however, whether and how exactly such global feedback structure may underpin NMDRs is poorly understood. Objectives: We hypothesize that an EDC may compete with the endogenous hormone for receptors (i) at the central site to interfere with the feedback regulation thus altering the physiological hormone level, and (ii) at the peripheral site to disrupt the hormone action; this dual-action may oppose each other, producing nonmonotonic endocrine effects. The objective here is to explore - through computational modeling - how NMDRs may arise through this potential mechanism and the relevant biological variabilities that enable susceptibility to nonmonotonic effects. Methods: We constructed a dynamical model of a generic hypothalamic-pituitary-endocrine (HPE) axis with negative feedback regulation between a pituitary hormone and a terminal effector hormone (EH). The effects of model parameters, including receptor binding affinities and efficacies, on NMDR were examined for EDC agonists and antagonists. Monte Carlo human population simulations were then conducted to systemically explore biological parameter conditions that engender NMDR. Results: When an EDC interferes sufficiently with the central feedback action of EH, the net endocrine effect at the peripheral target site can be opposite to what is expected of an agonist or antagonist at low concentrations. J/U or Bell-shaped NMDRs arise when the EDC has differential binding affinities and/or efficacies, relative to EH, for the peripheral and central receptors. Quantitative relationships between these biological variabilities and associated distributions were discovered, which can distinguish J/U and Bell-shaped NMDRs from monotonic responses. Conclusions: The ubiquitous negative feedback regulation in endocrine systems can act as a universal mechanism for counterintuitive and nonmonotonic effects of EDCs. Depending on key receptor kinetic and signaling properties of EDCs and endogenous hormones, some individuals may be more susceptible to these complex endocrine effects.
{"title":"Interference with Systemic Negative Feedback Regulation as a Potential Mechanism for Nonmonotonic Dose-Responses of Endocrine-Disrupting Chemicals","authors":"Zhenzhen Shi, Shuo Xiao, Qiang Zhang","doi":"10.1101/2024.09.04.611257","DOIUrl":"https://doi.org/10.1101/2024.09.04.611257","url":null,"abstract":"Background: Endocrine-disrupting chemicals (EDCs) often exhibit nonmonotonic dose-response (NMDR) relationships, posing significant challenges to health risk assessment and regulations. Several molecular mechanisms operating locally in cells have been proposed, including opposing actions via different receptors, mixed-ligand heterodimer formation, and receptor downregulation. Systemic negative feedback regulation of hormone homeostasis, which is a common feature of many endocrine systems, has also been invoked as a mechanism; however, whether and how exactly such global feedback structure may underpin NMDRs is poorly understood. Objectives: We hypothesize that an EDC may compete with the endogenous hormone for receptors (i) at the central site to interfere with the feedback regulation thus altering the physiological hormone level, and (ii) at the peripheral site to disrupt the hormone action; this dual-action may oppose each other, producing nonmonotonic endocrine effects. The objective here is to explore - through computational modeling - how NMDRs may arise through this potential mechanism and the relevant biological variabilities that enable susceptibility to nonmonotonic effects. Methods: We constructed a dynamical model of a generic hypothalamic-pituitary-endocrine (HPE) axis with negative feedback regulation between a pituitary hormone and a terminal effector hormone (EH). The effects of model parameters, including receptor binding affinities and efficacies, on NMDR were examined for EDC agonists and antagonists. Monte Carlo human population simulations were then conducted to systemically explore biological parameter conditions that engender NMDR. Results: When an EDC interferes sufficiently with the central feedback action of EH, the net endocrine effect at the peripheral target site can be opposite to what is expected of an agonist or antagonist at low concentrations. J/U or Bell-shaped NMDRs arise when the EDC has differential binding affinities and/or efficacies, relative to EH, for the peripheral and central receptors. Quantitative relationships between these biological variabilities and associated distributions were discovered, which can distinguish J/U and Bell-shaped NMDRs from monotonic responses. Conclusions: The ubiquitous negative feedback regulation in endocrine systems can act as a universal mechanism for counterintuitive and nonmonotonic effects of EDCs. Depending on key receptor kinetic and signaling properties of EDCs and endogenous hormones, some individuals may be more susceptible to these complex endocrine effects.","PeriodicalId":501213,"journal":{"name":"bioRxiv - Systems Biology","volume":"15 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142202738","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-08DOI: 10.1101/2024.09.06.611593
Wyatt Million, Christian R Voolstra, Gabriela Perna, Giulia Puntin, Katherine Rowe, Maren Ziegler
Dinoflagellates of the family Symbiodiniaceae are main symbionts of diverse marine animals. A large diversity of Symbiodiniaceae also occur beyond the bounds of their multicellular hosts, occupying environmental niches on coral reefs. The link between spatial diversity at ecosystem scale to microhabitats of Symbiodiniaceae within the coral holobiont are largely unknown. Using ITS2 amplicon sequencing, we compared Symbiodiniaceae communities across four environments (seawater, near-reef and distant sediments, and turf algae mats) and two coral microhabitats (tissue and mucus) on a coral reef in the Red Sea. Analysis of ITS2 sequences revealed that coral and environmental habitats were both dominated by the genera Symbiodinium, Cladocopium, and Durusdinium, but environmental habitats additionally harbored Fugacium, Gerakladium, and Halluxium. Each environmental habitat harbored a distinct Symbiodiniaceae community, with 14-27 % exclusive ITS2 sequences. Nonetheless, 17 ITS2 sequences were shared among all habitat types and were variants defining nearly half of the ITS2 type profiles used to further resolve Symbiodiniaceae identity of coral-based communities. Tissues and surface mucus layers of 49 coral colonies from 17 genera had largely identical Symbiodiniaceae communities. Together with the large difference between environmental Symbiodiniaceae communities and those in the mucus, our results indicate a clear barrier between host-associated and environmental Symbiodiniaceae communities marked by only few shared complete type profiles under normal conditions. It remains to be determined how Symbiodiniaceae community dynamics between coral microhabitats and environmental reservoirs change during coral bleaching events. Monitoring coral colonies after mucus sampling confirmed its suitability for repeated long-term monitoring of coral-associated Symbiodiniaceae communities.
{"title":"Resolving Symbiodiniaceae diversity across coral microhabitats and reef niches","authors":"Wyatt Million, Christian R Voolstra, Gabriela Perna, Giulia Puntin, Katherine Rowe, Maren Ziegler","doi":"10.1101/2024.09.06.611593","DOIUrl":"https://doi.org/10.1101/2024.09.06.611593","url":null,"abstract":"Dinoflagellates of the family Symbiodiniaceae are main symbionts of diverse marine animals. A large diversity of Symbiodiniaceae also occur beyond the bounds of their multicellular hosts, occupying environmental niches on coral reefs. The link between spatial diversity at ecosystem scale to microhabitats of Symbiodiniaceae within the coral holobiont are largely unknown. Using ITS2 amplicon sequencing, we compared Symbiodiniaceae communities across four environments (seawater, near-reef and distant sediments, and turf algae mats) and two coral microhabitats (tissue and mucus) on a coral reef in the Red Sea. Analysis of ITS2 sequences revealed that coral and environmental habitats were both dominated by the genera Symbiodinium, Cladocopium, and Durusdinium, but environmental habitats additionally harbored Fugacium, Gerakladium, and Halluxium. Each environmental habitat harbored a distinct Symbiodiniaceae community, with 14-27 % exclusive ITS2 sequences. Nonetheless, 17 ITS2 sequences were shared among all habitat types and were variants defining nearly half of the ITS2 type profiles used to further resolve Symbiodiniaceae identity of coral-based communities. Tissues and surface mucus layers of 49 coral colonies from 17 genera had largely identical Symbiodiniaceae communities. Together with the large difference between environmental Symbiodiniaceae communities and those in the mucus, our results indicate a clear barrier between host-associated and environmental Symbiodiniaceae communities marked by only few shared complete type profiles under normal conditions. It remains to be determined how Symbiodiniaceae community dynamics between coral microhabitats and environmental reservoirs change during coral bleaching events. Monitoring coral colonies after mucus sampling confirmed its suitability for repeated long-term monitoring of coral-associated Symbiodiniaceae communities.","PeriodicalId":501213,"journal":{"name":"bioRxiv - Systems Biology","volume":"9 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142202739","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-07DOI: 10.1101/2024.09.03.611067
Samantha N Piekos, Oren Barak, Andrew Baumgartner, Tianjiao Chu, W Tony Parks, Jennifer Hadlock, Leroy Hood, Nathan Price, Yoel Sadovsky
The placenta is essential for a healthy pregnancy, and placental pathology can endanger both maternal and fetal health. Placental function is affected by dynamic, complex, and interconnected molecular, cellular, and environmental events; therefore, we need a systems biology approach to study disease in normal physiological placenta function. We use placental multiomics (short and bulk transcriptomics, untargeted metabolomics, and targeted proteomics) paired with clinical data and placental histopathology reports from 321 placentas across multiple obstetric conditions: fetal growth restriction (FGR), FGR with pregnancy-related hypertension (FGR+HDP), preeclampsia (PE), and spontaneous preterm delivery (PTD). We first performed cellular deconvolution to estimate cell type numbers from bulk transcriptomes: FGR+HDP placentas were the most different from control placentas driven by a higher estimated number of extravillous trophoblast (p<0.0001). Next, we evaluated the impact of fetal sex and gestational age on analyte levels, adjusting for these confounders. We then generated obstetric condition-specific correlation networks and identified communities of related analytes associated with physiology and disease. We demonstrated how network connectivity and its disruption in disease can be used to identify signatures unique to a clinical outcome. We examined a community defined in control placentas for which the most connected node was miR-365a-3p in contrast to the corresponding community in FGR+HDP placentas for which the most connected node was hypoxia-induced miR-210-3p. From this community, we identified a signature containing mRNA transcripts implicated in placental dysfunction (e.g. FLT1, FSTL3, HTRA4, LEP, and PHYHIP). This signature distinguishes between FGR+HDP placentas and placentas of differing clinical outcomes in high-dimensional space. These findings illustrate the power of systems biology-driven interomics network analysis in a single tissue type, laying the groundwork for future multi-tissue studies.
{"title":"Placental Network Differences Among Obstetric Syndromes Identified With An Integrated Multiomics Approach","authors":"Samantha N Piekos, Oren Barak, Andrew Baumgartner, Tianjiao Chu, W Tony Parks, Jennifer Hadlock, Leroy Hood, Nathan Price, Yoel Sadovsky","doi":"10.1101/2024.09.03.611067","DOIUrl":"https://doi.org/10.1101/2024.09.03.611067","url":null,"abstract":"The placenta is essential for a healthy pregnancy, and placental pathology can endanger both maternal and fetal health. Placental function is affected by dynamic, complex, and interconnected molecular, cellular, and environmental events; therefore, we need a systems biology approach to study disease in normal physiological placenta function. We use placental multiomics (short and bulk transcriptomics, untargeted metabolomics, and targeted proteomics) paired with clinical data and placental histopathology reports from 321 placentas across multiple obstetric conditions: fetal growth restriction (FGR), FGR with pregnancy-related hypertension (FGR+HDP), preeclampsia (PE), and spontaneous preterm delivery (PTD). We first performed cellular deconvolution to estimate cell type numbers from bulk transcriptomes: FGR+HDP placentas were the most different from control placentas driven by a higher estimated number of extravillous trophoblast (p<0.0001). Next, we evaluated the impact of fetal sex and gestational age on analyte levels, adjusting for these confounders. We then generated obstetric condition-specific correlation networks and identified communities of related analytes associated with physiology and disease. We demonstrated how network connectivity and its disruption in disease can be used to identify signatures unique to a clinical outcome. We examined a community defined in control placentas for which the most connected node was miR-365a-3p in contrast to the corresponding community in FGR+HDP placentas for which the most connected node was hypoxia-induced miR-210-3p. From this community, we identified a signature containing mRNA transcripts implicated in placental dysfunction (e.g. FLT1, FSTL3, HTRA4, LEP, and PHYHIP). This signature distinguishes between FGR+HDP placentas and placentas of differing clinical outcomes in high-dimensional space. These findings illustrate the power of systems biology-driven interomics network analysis in a single tissue type, laying the groundwork for future multi-tissue studies.","PeriodicalId":501213,"journal":{"name":"bioRxiv - Systems Biology","volume":"93 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142202737","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-07DOI: 10.1101/2024.09.04.611211
Eduardo D. Sontag, Jana L. Gevertz, James Greene, Natacha Comandante-Lou, Samantha Prosperi
There is growing recognition that phenotypic plasticity enables cancer cells to adapt to various environmental conditions. An example of this adaptability is the persistence of an initially sensitive population of cancer cells in the presence of therapeutic agents. Understanding the implications of this drug-induced resistance is essential for predicting transient and long-term tumor tumor dynamics subject to treatment. This paper introduces a mathematical model of this phenomenon of drug-induced resistance which provides excellent fits to time-resolved in vitro experimental data. From observational data of total numbers of cells, the model unravels the relative proportions of sensitive and resistance subpopulations, and quantifies their dynamics as a function of drug dose. The predictions are then validated using data on drug doses which were not used when fitting parameters. The model is then used, in conjunction with optimal control techniques, in order to discover dosing strategies that might lead to better outcomes as quantified by lower total cell volume.
{"title":"Understanding therapeutic tolerance through a mathematical model of drug-induced resistance","authors":"Eduardo D. Sontag, Jana L. Gevertz, James Greene, Natacha Comandante-Lou, Samantha Prosperi","doi":"10.1101/2024.09.04.611211","DOIUrl":"https://doi.org/10.1101/2024.09.04.611211","url":null,"abstract":"There is growing recognition that phenotypic plasticity enables cancer cells to adapt to various environmental conditions. An example of this adaptability is the persistence of an initially sensitive population of cancer cells in the presence of therapeutic agents. Understanding the implications of this drug-induced resistance is essential for predicting transient and long-term tumor tumor dynamics subject to treatment. This paper introduces a mathematical model of this phenomenon of drug-induced resistance which provides excellent fits to time-resolved <em>in vitro</em> experimental data. From observational data of total numbers of cells, the model unravels the relative proportions of sensitive and resistance subpopulations, and quantifies their dynamics as a function of drug dose. The predictions are then validated using data on drug doses which were not used when fitting parameters. The model is then used, in conjunction with optimal control techniques, in order to discover dosing strategies that might lead to better outcomes as quantified by lower total cell volume.","PeriodicalId":501213,"journal":{"name":"bioRxiv - Systems Biology","volume":"35 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142202740","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-07DOI: 10.1101/2024.09.05.609098
Riddhiman K Garge, Valerie Lynch, Rose Fields, Silvia Casadei, Sabrina Best, Jeremy Stone, Matthew Snyder, Chris D McGann, Jay Shendure, Lea M Starita, Nobuhiko Hamazaki, Devin K. Schweppe
Gastrulation is the highly coordinated process by which the early embryo breaks symmetry, establishes germ layers and a body plan, and sets the stage for organogenesis. As early mammalian development is challenging to study in vivo, stem cell-derived models have emerged as powerful surrogates, e.g. human and mouse gastruloids. However, although single cell RNA-seq (scRNA-seq) and high-resolution imaging have been extensively applied to characterize such in vitro embryo models, a paucity of measurements of protein dynamics and regulation leaves a major gap in our understanding. Here, we sought to address this by applying quantitative proteomics to human and mouse gastruloids at four key stages of their differentiation (naïve ESCs, primed ESCs, early gastruloids, late gastruloids). To the resulting data, we perform network analysis to map the dynamics of expression of macromolecular protein complexes and biochemical pathways, including identifying cooperative proteins that associate with them. With matched RNA-seq and phosphosite data from these same stages, we investigate pathway-, stage- and species-specific aspects of translational and post-translational regulation, e.g. finding peri-gastrulation stages of human and mice to be discordant with respect to the mitochondrial transcriptome vs. proteome, and nominating novel kinase-substrate relationships based on phosphosite dynamics. Finally, we leverage correlated dynamics to identify conserved protein networks centered around congenital disease genes. Altogether, our data (https://gastruloid.brotmanbaty.org/) and analyses showcase the potential of intersecting in vitro embryo models and proteomics to advance our understanding of early mammalian development in ways not possible through transcriptomics alone.
{"title":"The proteomic landscape and temporal dynamics of mammalian gastruloid development","authors":"Riddhiman K Garge, Valerie Lynch, Rose Fields, Silvia Casadei, Sabrina Best, Jeremy Stone, Matthew Snyder, Chris D McGann, Jay Shendure, Lea M Starita, Nobuhiko Hamazaki, Devin K. Schweppe","doi":"10.1101/2024.09.05.609098","DOIUrl":"https://doi.org/10.1101/2024.09.05.609098","url":null,"abstract":"Gastrulation is the highly coordinated process by which the early embryo breaks symmetry, establishes germ layers and a body plan, and sets the stage for organogenesis. As early mammalian development is challenging to study <em>in vivo</em>, stem cell-derived models have emerged as powerful surrogates, e.g. human and mouse gastruloids. However, although single cell RNA-seq (scRNA-seq) and high-resolution imaging have been extensively applied to characterize such <em>in vitro</em> embryo models, a paucity of measurements of protein dynamics and regulation leaves a major gap in our understanding. Here, we sought to address this by applying quantitative proteomics to human and mouse gastruloids at four key stages of their differentiation (naïve ESCs, primed ESCs, early gastruloids, late gastruloids). To the resulting data, we perform network analysis to map the dynamics of expression of macromolecular protein complexes and biochemical pathways, including identifying cooperative proteins that associate with them. With matched RNA-seq and phosphosite data from these same stages, we investigate pathway-, stage- and species-specific aspects of translational and post-translational regulation, <em>e.g.</em> finding peri-gastrulation stages of human and mice to be discordant with respect to the mitochondrial transcriptome vs. proteome, and nominating novel kinase-substrate relationships based on phosphosite dynamics. Finally, we leverage correlated dynamics to identify conserved protein networks centered around congenital disease genes. Altogether, our data (https://gastruloid.brotmanbaty.org/) and analyses showcase the potential of intersecting <em>in vitro</em> embryo models and proteomics to advance our understanding of early mammalian development in ways not possible through transcriptomics alone.","PeriodicalId":501213,"journal":{"name":"bioRxiv - Systems Biology","volume":"734 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142202744","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}
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