bioRxiv Science⌕ Search

Biology subjects

Raha, S.

Publications and source records attributed to Raha, S..

5 recordsLinked to original sources

Defining a hypoxic exposure paradigm for modelling preeclampsia-associated syncytiotrophoblast dysfunction in human blastocyst-derived placental stem cells

Introduction: Preeclampsia (PE) is a hypertensive pregnancy disorder in which placental dysfunction is thought to play a central role. Although hypoxia is widely used to model PE-associated syncytiotrophoblast (ST) dysfunction in vitro, considerable variability in oxygen control conditions and hypoxic exposure paradigms has limited standardization across studies. This study aimed to establish physiologically relevant oxygen control conditions and identify a hypoxic exposure paradigm that consistently recapitulates characteristic features of PE-associated ST dysfunction. Methods: Human blastocyst-derived trophoblast stem cells were differentiated into STs and exposed to physiological (8% O2), atmospheric (21% O2), or hypoxic (1% O2) conditions for 24 or 48 h. Angiogenic and apoptotic marker expression, cell death, and mitochondrial stress were assessed. Results: Compared with atmospheric oxygen, 8% O2 reduced cell death and more closely reflected physiological ST conditions. Acute hypoxia (24 h) induced a robust PE-like phenotype in STs characterized by induction of anti-angiogenic markers, sFlt-1 and sEng, reduced expression of the pro-angiogenic factor PlGF, and increased cell death, apoptotic signalling and mitochondrial stress. Notably, induction of several of these markers was attenuated or reversed following prolonged hypoxic exposure. Conclusions: These findings identify 8% O2 as a physiologically relevant control condition for modelling PE-associated ST dysfunction relative to 21% O2, and demonstrate that 24 h of severe hypoxia more consistently reproduces key molecular and cellular features of PE than prolonged hypoxia. This work establishes a framework for modelling hypoxia-induced ST dysfunction while highlighting the importance of oxygen control conditions and hypoxic exposure duration when modeling PE in vitro.

cell biology↗

Placental transcriptomics reveals alterations in metabolic and transport gene programs following prenatal cannabis smoke exposure

Background: Prenatal cannabis use is increasing, yet the effects of inhaled cannabis smoke on placental molecular function remain poorly defined. Objective: To characterize placental transcriptomic alterations following prenatal cannabis smoke exposure using a physiologically relevant murine inhalation model. Methods: Timed-pregnant CD-1 mice were exposed to cannabis cigarette smoke or room air from embryonic day (E)6.5 to 18.5. Placentae were collected at E18.5 for microarray-based transcriptomic profiling. Differential gene expression was assessed using fetal sex adjusted linear models and false discovery rate correction. Gene set variation and ranked pathway enrichment were performed to evaluate compartment-associated and biological transcriptional programs. Selected genes were validated by quantitative PCR. Results: Large-scale transcriptomic profiles revealed no clear visual clustering by exposure; however, 23 genes were differentially expressed (FDR <0.05, |log2 fold change| > 0.5). Labyrinth-associated transcriptional signatures were reduced, whereas junctional-associated signatures were increased in exposed placentae. Pathway analyses revealed negative enrichment of fatty acid metabolism, bioenergetic, and transmembrane transport pathways, alongside positive enrichment of RNA processing and transcriptional-regulatory pathways. Quantitative PCR confirmed altered expression of multiple transport-related genes. Electron transport chain-associated gene expression was altered despite preserved placental respiratory measurements. Conclusions: Prenatal cannabis smoke exposure is associated with subtle yet coordinated placental transcriptional alterations involving metabolic, transport-associated, and gene-regulatory pathways, alongside compartment-associated transcriptional shifts. These findings provide insight into placental responses to whole cannabis smoke exposure and identify pathways that may contribute to altered placental function during pregnancy.

physiology↗

Prenatal cannabis smoke exposure alters placental development in a murine model of pregnancy

Cannabis use during pregnancy continues to increase with smoking remaining the most common mode of consumption. While clinical studies highlight an association between prenatal cannabis use and adverse pregnancy outcomes, less is known about placental outcomes, even though many of the reported pregnancy outcomes are thought to be mediated via placental dysfunction. Here, we established a mouse model of gestational cannabis smoke exposure to investigate the impacts on fetal outcomes and placental structure and function. Pregnant CD1 mice were exposed daily to {Delta}9-tetrahydrocannabinol (THC)-dominant cannabis smoke (12-14% THC, 0-2% CBD) or filtered air from embryonic day (E)6.5 to E18.5 or parturition. Cannabinoid analyses in cannabis smoke-exposed, paired maternal and fetal livers revealed total THC and 11-Nor-9-carboxy-THC (THCA) concentrations of 135.95 {+/-} 13.60 ng/g and 30.84 {+/-} 4.68 ng/g, respectively. Moreover, Cyp1a1, a smoke-inducible enzyme, was induced by 4-fold in cannabis smoke-exposed placentae. No changes in offspring body weights were observed; however, there was a marked decrease in the brain-to-body weight ratio of exposed postnatal day 1 (PND1) offspring. Placentae from exposed dams were significantly reduced in size, with altered zonation marked by a significantly decreased junctional zone and increased labyrinth zone. Key trophoblast differentiation markers (Tfap2c, Tpbpa, Pcdh12) and placental endocrine regulators (Pl2, Igf1r) were significantly downregulated following cannabis smoke exposure in placentas. Furthermore, transcript levels of placental nutrient and vascularization markers, Glut1, Vegfa and Pparg were significantly decreased in cannabis smoke-exposed placentas. By employing a physiologically relevant platform of prenatal cannabis exposure in vivo we demonstrate the adverse effects of prenatal cannabis smoke exposure on placental structure and function as well as on fetal brain growth.

physiology↗

A Consensus Model of Glucose-Stimulated Insulin Secretion in the Pancreatic beta-Cell

The pancreas plays a critical role in maintaining glucose homeostasis through the secretion of hormones from the islets of Langerhans. Glucose-stimulated insulin secretion (GSIS) by the pancreatic {beta}-cell is the main mechanism for reducing elevated plasma glucose. Here we present a systematic modeling workflow for the development of kinetic pathway models using the Systems Biology Markup Language (SBML). Steps include retrieval of information from databases, curation of experimental and clinical data for model calibration and validation, integration of heterogeneous data including absolute and relative measurements, unit normalization, data normalization, and model annotation. An important factor was the reproducibility and exchangeability of the model, which allowed the use of various existing tools. The workflow was applied to construct the first consensus model of GSIS in the pancreatic {beta}-cell based on experimental and clinical data from 39 studies spanning 50 years of pancreatic, islet, and {beta}-cell research in humans, rats, mice, and cell lines. The model consists of detailed glycolysis and equations for insulin secretion coupled to cellular energy state (ATP/ADP ratio). Key findings of our work are that in GSIS there is a glucose-dependent increase in almost all intermediates of glycolysis. This increase in glycolytic metabolites is accompanied by an increase in energy metabolites, especially ATP and NADH. One of the few decreasing metabolites is ADP, which, in combination with the increase in ATP, results in a large increase in ATP/ADP ratios in the {beta}-cell with increasing glucose. Insulin secretion is dependent on ATP/ADP, resulting in glucose-stimulated insulin secretion. The observed glucose-dependent increase in glycolytic intermediates and the resulting change in ATP/ADP ratios and insulin secretion is a robust phenomenon observed across data sets, experimental systems and species. Model predictions of the glucose-dependent response of glycolytic intermediates and insulin secretion are in good agreement with experimental measurements. Our model predicts that factors affecting ATP consumption, ATP formation, hexokinase, phosphofructokinase, and ATP/ADP-dependent insulin secretion have a major effect on GSIS. In conclusion, we have developed and applied a systematic modeling workflow for pathway models that allowed us to gain insight into key mechanisms in GSIS in the pancreatic {beta}-cell.

systems biology↗

A graph-based framework for multi-scale modeling of physiological transport

Trillions of chemical reactions occur in the human body every second, where the generated products are not only consumed locally but also transported to various locations in a systematic manner to sustain homeostasis. Current solutions to model these biological phenomena are restricted in computability and scalability due to the use of continuum approaches where it is practically impossible to encapsulate the complexity of the physiological processes occurring at diverse scales. Here we present a discrete modeling framework defined on an interacting graph that offers the flexibility to model multiscale systems by translating the physical space into a metamodel. We discretize the graph-based metamodel into functional units composed of well-mixed volumes with vascular and cellular subdomains; the operators defined over these volumes define the transport dynamics. We predict glucose drift governed by advective-dispersive transport in the vascular subdomains of an islet vasculature and cross-validate the flow and concentration fields with finite-element based COMSOL simulations. Vascular and cellular subdomains are coupled to model the nutrient exchange occurring in response to the gradient arising out of reaction and perfusion dynamics. The application of our framework for modeling biologically relevant test systems shows how our approach can assimilate both multi-omics data from in vitro - in vivo studies and vascular topology from imaging studies for examining the structure-function relationship of complex vasculatures. The framework can advance simulation of whole-body networks at user-defined levels and is expected to find major use in personalized medicine and drug discovery. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=199 SRC="FIGDIR/small/460337v2_ufig1.gif" ALT="Figure 1"> View larger version (41K): org.highwire.dtl.DTLVardef@1b872b4org.highwire.dtl.DTLVardef@72b98borg.highwire.dtl.DTLVardef@1f35f29org.highwire.dtl.DTLVardef@ecba45_HPS_FORMAT_FIGEXP M_FIG C_FIG

systems biology↗