Biology subjects

Shulman, G.

Publications and source records attributed to Shulman, G..

3 recordsLinked to original sources

bioRxiv2024

Generative whole-brain dynamics models from healthy subjects predict functional alterations in stroke at the level of individual patients

Computational whole-brain models describe the resting activity of each brain region based on a local model, inter-regional functional interactions, and a structural connectome that specifies the strength of inter-regional connections. Strokes damage the healthy structural connectome that forms the backbone of these models and produce large alterations in inter-regional functional interactions. These interactions are typically measured by correlating the timeseries of activity between two brain regions, so-called resting functional connectivity. We show that adding information about the structural disconnections produced by a patients lesion to a whole-brain model previously trained on structural and functional data from a large cohort of healthy subjects predicts the resting functional connectivity of the patient about as well as fitting the model directly to the patients data. Furthermore, the model dynamics reproduce functional connectivity-based measures that are typically abnormal in stroke patients as well as measures that specifically isolate these abnormalities. Therefore, although whole-brain models typically involve a large number of free parameters, the results show that even after fixing those parameters, the model reproduces results from a population very different than the population on which the model was trained. In addition to validating the model, these results show that the model mechanistically captures relationships between the anatomical structure and functional activity of the human brain.

neuroscience↗

bioRxiv2023

Renal Angptl4 is a key fibrogenic molecule in progressive diabetic kidney disease

Angiopoietin-like 4 (ANGPTL4) is the key protein involved in lipoprotein metabolism and has been shown to have diverse effects on tissue protection. In clinical settings, there is a reported association between higher levels of plasma Angptl4 and features of diabetic kidney disease, however, the association between kidney Angptl4 with features of diabetic kidney disease has not been well investigated. We show that both podocyte-and tubule-specific ANGPTL4 are crucial fibrogenic molecules in diabetes. Results from mRNA-array analysis in control (non-fibrotic) and diabetic (fibrotic) kidneys suggest time-dependent emergence of Angplt4 expression. Diabetes accelerates the fibrogenic phenotype in control mice but not in ANGPTL4 mutant mice. The protective effect observed in ANGPTL4 mutant mice is correlated with a reduction in the levels of pro-inflammatory cytokines, epithelial-to-mesenchymal transition, endothelial-to-mesenchymal transition and augmented fatty acid oxidation. Mechanistically, we demonstrate that podocyte-or tubule-secreted Angptl4 interacts with Integrin-{beta}1 and influences the association between dipeptidyl-4 with Integrin-{beta}1 and promotes heterodimerization of transforming growth factor-{beta} receptor 1 (TGF{beta}R1) and TGF{beta}R2 in cultured cells. This in turn results in Smad3 phosphorylation and subsequent downregulation of the expression of genes involved in fatty acid oxidation; these cumulative effects led to the activation of fibrogenic phenotypes. We demonstrate the utility of a targeted pharmacologic therapy that specifically inhibits Angptl4 gene expression in the kidneys and protects diabetic kidneys from proteinuria and fibrosis. Importantly, use of this kidney-specific targeted strategy is beneficial and does not cause any harmful effect suggesting it can be used as a novel drug molecule for treatment of diabetic kidney disease. Taken together, these data demonstrate that podocyte-and tubule-derived Angptl4 is fibrogenic in diabetic kidneys.

cell biology↗

bioRxiv2022

Discovery of phage determinants that confer sensitivity to bacterial immune systems

Over the past few years, numerous anti-phage defense systems have been discovered in bacteria. While the mechanism of defense for some of these systems is understood, a major unanswered question is how these systems sense phage infection. To systematically address this question, we isolated 192 phage mutants that escape 19 different defense systems. In many cases, these escaper phages were mutated in the gene sensed by the defense system, enabling us to map the phage determinants that confer sensitivity to bacterial immunity. Our data identify specificity determinants of diverse retron systems and reveal phage-encoded triggers for multiple abortive infection systems. We find general themes in phage sensing and demonstrate that mechanistically diverse systems have converged to sense either the core replication machinery of the phage, phage structural components, or host takeover mechanisms. Combining our data with previous findings, we formulate key principles on how bacterial immune systems sense phage invaders.

microbiology↗