Search bioRxivSearch

Biology subjects

Anirikh Chakrabarti

Publications and source records attributed to Anirikh Chakrabarti.

3 recordsLinked to original sources

Cohort Specific Effects of Cereal-bar Supplementation in Overweight Patients With or Without Type 2 Diabetes Mellitus

The importance of gut microbes to metabolic health is becoming more evident and nutrition-based therapies to alter the composition of bacterial communities to manage metabolic disease are an attractive avenue to ameliorate some effects of Western diets. While the composition of gut microbial communities can vary significantly across disease states, it is not well known if these communities have common responses to nutritional interventions. To better understand diet-bacterial community interactions, we collected biological parameters and fecal samples of overweight non-iabetic (OND) and diabetic (OD) individuals before and after daily supplementation of 2.8 g {beta}-lucan on their habitual diet for 30 days. Fecal bacterial communities in an age-atched cohort were measured by sequencing partial 16S rRNA genes and imputed metagenomic content. Unexpectedly, we observed disconnected responses of biological measurements and the bacterial community. Based on average effect size, biological measurements were greater in the OND group while effects on the bacterial community were greatest on the OD cohort, and we suspect these observations are due to the significantly lower alpha diversity in the OD cohort. Our data indicate that responses to cereal-bar supplementation are cohort specific and this should be considered when manipulating the microbiome via diet supplementation.

Microbiology

Mechanistic Modeling and Analysis of the Mammalian Unfolded Protein Response

Cells monitor protein folding by an inbuilt quality-control system in which incorrectly or misfolded folded proteins are tagged for degradation or sent back through a refolding cycle. However, continued accumulation of incorrectly folded proteins triggers the Unfolded Protein Response (UPR), which attempts to re-establish folding homeostasis or commits the cell to apoptosis. In this study, we developed a family of mechanistic models of the mammalian UPR system. An ensemble of models parameters was estimated by minimizing the difference between simulations and experimental measurements using multiobjective optimization. The ensemble of model parameters was validated using cross-validation. Analysis of the model ensemble suggested the three branches of UPR fired simultaneously. However, the importance of each brach was ranked ordered in time; PERK and IRE1 were more important early, while ATF6 was important later in the response. The activity of all three branches as coordinated by the molecular chaperone BiP. Model analysis suggested that BiP feedback was critical to the overall robustness of the system. Removal of any one branch of BiP feedback, destabilized the other branches. On the other hand, removal of all nodes of BiP feedback increased the overall robustness of the system. Thus, while BiP feedback is crucial to allowing the cell to adapt to small perturbations, it also makes the system fragile and susceptible to manipulation.

Systems Biology

Population heterogeneity in the epithelial to mesenchymal transition is controlled by NFAT and phosphorylated Sp1

Epithelial to mesenchymal transition (EMT) is an essential differentiation program during tissue morphogenesis and remodeling. EMT is induced by soluble transforming growth factor {beta} (TGF-{beta}) family members, and restricted by vascular endothelial growth factor family members. While many downstream molecular regulators of EMT have been identified, these have been largely evaluated individually without considering potential crosstalk. In this study, we created an ensemble of dynamic mathematical models describing TGF-{beta} induced EMT to better understand the operational hierarchy of this complex molecular program. We used ordinary differential equations (ODEs) to describe the transcriptional and post-translational regulatory events driving EMT. Model parameters were estimated from multiple data sets using multiobjective optimization, in combination with cross-validation. TGF-{beta} exposure drove the model population toward a mesenchymal phenotype, while an epithelial phenotype was enhanced following vascular endothelial growth factor A (VEGF-A) exposure. Simulations predicted that the transcription factors phosphorylated SP1 and NFAT were master regulators promoting or inhibiting EMT, respectively. Surprisingly, simulations also predicted that a cellular population could exhibit phenotypic heterogeneity (characterized by a significant fraction of the population with both high epithelial and mesenchymal marker expression) if treated simultaneously with TGF-{beta} and VEGF-A. We tested this prediction experimentally in both MCF10A and DLD1 cells and found that upwards of 45% of the cellular population acquired this hybrid state in the presence of both TGF-{beta} and VEGF-A. We experimentally validated the predicted NFAT/Sp1 signaling axis for each phenotype response. Lastly, we found that cells in the hybrid state had significantly different functional behavior when compared to VEGF-A or TGF-{beta} treatment alone. Together, these results establish a predictive mechanistic model of EMT susceptibility, and potentially reveal a novel signaling axis which regulates carcinoma progression through an EMT versus tubulogenesis response.\n\nAuthor SummaryTissue formation and remodeling requires a complex and dynamic balance of interactions between epithelial cells, which reside on the surface, and mesenchymal cells that reside in the tissue interior. During embryonic development, wound healing, and cancer, epithelial cells transform into a mesenchymal cell to form new types of tissues. It is important to understand this process so that it can be controlled to generate beneficial effects and limit pathological differentiation. Much research over the past 20 years has identified many different molecular species that are relevant, but these have mainly been studied one at a time. In this study, we developed and implemented a novel computational strategy to interrogate the key players in this transformation process to identify which are the major bottlenecks. We determined that NFATc1 and pSP1 are essential for promoting epithelial or mesenchymal differentiation, respectively. We then predicted the existence of a partially transformed cell that exhibits both epithelial and mesenchymal characteristics. We found this partial cell type develops a network of invasive but stunted vascular structures that may be a unique cell target for understanding cancer progression and angiogenesis.

Systems Biology