Biology subjects

Muthuswamy, S.

Publications and source records attributed to Muthuswamy, S..

3 recordsLinked to original sources

bioRxiv2024

Synaptic Organization-Function Relationships of Amygdala Interneurons Supporting Associative Learning

Coordinated activity of basolateral amygdala (BLA) GABAergic interneurons (INs) and glutamatergic principal cells (PCs) is critical for associative learning, however the microcircuit organization-function relationships of distinct IN classes remain uncertain. Here, we show somatostatin (SOM) INs provide inhibition onto, and are excited by, local PCs, whereas vasoactive intestinal peptide (VIP) INs are driven by extrinsic afferents. Parvalbumin (PV) INs inhibit PCs and are activated by local and extrinsic inputs. Thus, SOM and VIP INs exhibit complementary roles in feedback and feedforward inhibition, respectively, while PV INs contribute to both microcircuit motifs. Functionally, each IN subtype reveals unique activity patterns across fear- and extinction learning with SOM and VIP INs showing most divergent characteristics, and PV INs display an intermediate phenotype parallelling synaptic data. Finally, SOM and PV INs dynamically track behavioral state transitions across learning. These data provide insight into the synaptic microcircuit organization-function relationships of distinct BLA IN classes.

neuroscience↗

bioRxiv2021

A multi-tiered map of EMT defines major transition points and identifies vulnerabilities

Epithelial to mesenchymal transition (EMT) is a complex cellular program proceeding through a hybrid E/M state linked to cancer-associated stemness, migration and chemoresistance. Deeper molecular understanding of this dynamic physiological landscape is needed to define events which regulate the transition and entry into and exit from the E/M state. Here, we quantified >60,000 molecules across ten time points and twelve omic layers in human mammary epithelial cells undergoing TGF{beta}-induced EMT. Deep proteomic profiles of whole cells, nuclei, extracellular vesicles, secretome, membrane and phosphoproteome defined state-specific signatures and major transition points. Parallel metabolomics showed metabolic reprogramming preceded changes in other layers, while single-cell RNA sequencing identified transcription factors controlling entry into E/M. Covariance analysis exposed unexpected discordance between the molecular layers. Integrative causal modeling revealed co-dependencies governing entry into E/M that were verified experimentally using combinatorial inhibition. Overall, this dataset provides an unprecedented resource on TGF{beta} signaling, EMT and cancer.

systems biology↗

bioRxiv2019

Pancreatic tumor organoids for modeling in vivo drug response and discovering clinically-actionable biomarkers

Patient-derived models are transforming translational cancer research. It is not clear if the emergence of patient-derived organoid (PDO) models can extend the utility of the widely used patient-derived xenograft (PDX). In addition, the utility of PDO models for serum biomarker discovery is not known. Here, we demonstrate that PDO models recapitulate the genomics, cell biology, glycomics and drug responses observed in PDX models. Furthermore, we demonstrate the applicability of PDO models for identification of N-glycans that are enriched in the glycome of pancreatic ductal adenocarcinoma (PDAC). Surprisingly, among all the glycans observed in PDX and PDOs, a core set of 57 N-glycans represent 50-94% of the relative abundance of all N-glycans detected, suggesting that only a subset of glycans dominate the cell surface landscape in PDAC. In addition, we outline a tumor organoid-based pipeline to identify surface proteins in extracellular vesicles (EV) from media supernatant of PDO cultures. When combined with the affinity-based validation platform, the EV surface proteins discovered in PDOs are effective in differentiating patients with PDAC from those with benign pancreatitis in the clinic, identifying PDO as powerful discovery platform for serum biomarkers. Thus, PDOs extend the utility of the archival collections of PDX models for translational research and function as a powerful platform for identification of clinically-actionable biomarkers in patients blood. Significance statementTumor organoids extend the utility of PDX models as platforms for investigating drug response, glycosylation changes and function as new platforms for discovering blood-based biomarkers

cancer biology↗