Soumyadeep Sarkar

Dr. Soumyadeep Sarkar

orcid

Research Focus & Metrics

Academic Career Length

5Years (2022-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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28 November 2023 in Scientific Data
Verified
Journal Article
Open access
PDF file
MVMilene C. Vallejo
Milene C. Vallejo
SSSoumyadeep Sarkar
Soumyadeep Sarkar
EEEmily C. Elliott
Emily C. Elliott
HHHayden R. Henry
Hayden R. Henry
SPSamantha M. Powell
Samantha M. Powell
ENErnesto Nakayasu
Ernesto Nakayasu
Extracellular vesicles play major roles in cell-to-cell communication and are excellent biomarker candidates. However, studying plasma extracellular vesicles is challenging due to contaminants. Here, we performed a proteomics meta-analysis of public data to refine the plasma EV composition by separating EV proteins and contaminants into different clusters. We obtained two clusters with a total of 1717 proteins that were depleted of known contaminants and enriched in EV markers with independently validated 71% true-positive. These clusters had 133 clusters of differentiation (CD) antigens and were enriched with proteins from cell-to-cell communication and signaling. We compared our data with the proteins deposited in PeptideAtlas, making our refined EV protein list a resource for mechanistic and biomarker studies. As a use case example for this resource, we validated the type 1 diabetes biomarker proplatelet basic protein in EVs and showed that it regulates apoptosis of β cells and macrophages, two key players in the disease development. Our approach provides a refinement of the EV composition and a resource for the scientific community.

9 February 2022 in Expert Opinion on Therapeutic Targets
Verified
Journal Article
Closed access
SSSoumyadeep Sarkar
Soumyadeep Sarkar
JMJohn Melchior
John Melchior
HHHayden R. Henry
Hayden R. Henry
FSFarooq Syed
Farooq Syed
Raghavendra MirmiraRaghavendra Mirmira
Raghavendra Mirmira
TMTom Metz
Tom Metz
Current treatment for type 1 diabetes (T1D) is centered around insulin supplementation to manage the effects of pancreatic β cell loss. GDF15 is a potential preventative therapy against T1D progres...

18 June 2024 in Journal of Clinical Investigation
Verified
Journal Article
Open access
PDF file
CMCharanya Muralidharan
Charanya Muralidharan
FHFei Huang
Fei Huang
JEJacob R. Enriquez
Jacob R. Enriquez
JWJiayi E. Wang
Jiayi E. Wang
JNJennifer B. Nelson
Jennifer B. Nelson
Raghavendra MirmiraRaghavendra Mirmira
Raghavendra Mirmira
Preventing the onset of autoimmune type 1 diabetes (T1D) is feasible through pharmacological interventions that target molecular stress–responsive mechanisms. Cellular stresses, such as nutrient deficiency, viral infection, or unfolded proteins, trigger the integrated stress response (ISR), which curtails protein synthesis by phosphorylating eukaryotic translation initiation factor-2α (eIF2α). In T1D, maladaptive unfolded protein response (UPR) in insulin-producing β cells renders these cells susceptible to autoimmunity. We found that inhibition of the eIF2α kinase PKR-like ER kinase (PERK), a common component of the UPR and ISR, reversed the mRNA translation block in stressed human islets and delayed the onset of diabetes, reduced islet inflammation, and preserved β cell mass in T1D-susceptible mice. Single-cell RNA-Seq of islets from PERK-inhibited mice showed reductions in the UPR and PERK signaling pathways and alterations in antigen-processing and presentation pathways in β cells. Spatial proteomics of islets from these mice showed an increase in the immune checkpoint protein programmed death-ligand 1 (PD-L1) in β cells. Golgi membrane protein 1, whose levels increased following PERK inhibition in human islets and EndoC-βH1 human β cells, interacted with and stabilized PD-L1. Collectively, our studies show that PERK activity enhances β cell immunogenicity and that inhibition of PERK may offer a strategy for preventing or delaying the development of T1D.

2 September 2023 in Expert Opinion on Therapeutic Targets
Verified
Journal Article
Open access
ILIvo Díaz Ludovico
Ivo Díaz Ludovico
SSSoumyadeep Sarkar
Soumyadeep Sarkar
EEEmily Elliott
Emily Elliott
SVSuvi M. Virtanen
Suvi M. Virtanen
IEIris Erlund
Iris Erlund
ENErnesto Nakayasu
Ernesto Nakayasu
Type 1 diabetes (T1D) is an autoimmune disease in which pro-inflammatory and cytotoxic signaling drive the death of the insulin-producing β cells. This complex signaling is regulated in part by fatty acids and their bioproducts, making them excellent therapeutic targets. We provide an overview of the fatty acid actions on β cells by discussing how they can cause lipotoxicity or regulate inflammatory response during insulitis. We also discuss how diet can affect the availability of fatty acids and disease development. Finally, we discuss development avenues that need further exploration. Fatty acids, such as hydroxyl fatty acids, ω-3 fatty acids and their downstream products, are druggable candidates that promote protective signaling. Inhibitors and antagonists of enzymes and receptors of arachidonic acid and free fatty acids, along with their derived metabolites, which cause pro-inflammatory and cytotoxic responses, have the potential to be developed as therapeutic targets also. Further, because diet is the main source of fatty acid intake in humans, balancing protective and pro-inflammatory/cytotoxic fatty acid levels through dietary therapy may have beneficial effects, delaying T1D progression. Therefore, therapeutic interventions targeting fatty acid signaling hold potential as avenues to treat T1D.

29 September 2022 in bioRxiv
Verified
Preprint
Open access
PDF file
MVMilene C. Vallejo
Milene C. Vallejo
SSSoumyadeep Sarkar
Soumyadeep Sarkar
EEEmily C. Elliott
Emily C. Elliott
HHHayden R. Henry
Hayden R. Henry
FHFei Huang
Fei Huang
ENErnesto Nakayasu
Ernesto Nakayasu
Extracellular vesicles (EVs) play important roles in cell-to-cell communication and are potential biomarkers as they carry markers of their derived tissues and disease signatures. However, obtaining pure EV preparations from biofluids is challenging due to contaminants with similar physicochemical properties. Here, we performed a meta-analysis of plasma EV proteomics data deposited in public repositories to refine the protein composition of EVs and investigate potential roles in type 1 diabetes development. With the concept that each purification method yields different proportions of distinct contaminants, we grouped proteins into clusters based on their abundance profiles. This allowed us to separate clusters with classical EV markers, such as CD9, CD40, C63 and CD81, from clusters of well-known contaminants, such as serum albumin, apolipoproteins and components of the complement and coagulation pathways. Two clusters containing a total of 1720 proteins combined were enriched with EV markers and depleted in common contaminants; therefore, they were considered to contain bona fide EV components. As possible origins of plasma EVs, these clusters had markers of tissues such as spleen, liver, brain, lungs, pancreas, and blood/immune cells. These clusters were also enriched in cell surface markers CD antigens, and proteins from cell-to-cell communication and signaling pathways, such as chemokine signaling and antigen presentation. We also show that the EV component and type 1 diabetes biomarker, platelet basic protein (PPBP/CXCL7) regulates apoptosis in both beta and macrophage cell lines. Overall, our meta-analysis refined the composition of plasma EVs, reinforcing a primary function as messengers for cell-to-cell communication and signaling. Furthermore, this analysis identifies optimal avenues to target EVs for development of disease biomarkers.

22 February 2023 in medRxiv
Verified
Preprint
Open access
PDF file
SSSoumyadeep Sarkar
Soumyadeep Sarkar
EEEmily C. Elliott
Emily C. Elliott
HHHayden R. Henry
Hayden R. Henry
ILIvo Díaz Ludovico
Ivo Díaz Ludovico
JMJohn Melchior
John Melchior
ENErnesto Nakayasu
Ernesto Nakayasu
Aims Type 1 diabetes (T1D) results from an autoimmune attack of the pancreatic β cells that progresses to dysglycemia and symptomatic hyperglycemia. Current biomarkers to track this evolution are limited, with development of islet autoantibodies marking the onset of autoimmunity and metabolic tests used to detect dysglycemia. Therefore, additional biomarkers are needed to better track disease initiation and progression. Multiple clinical studies have used proteomics to identify biomarker candidates. However, most of the studies were limited to the initial candidate identification, which needs to be further validated and have assays developed for clinical use. Here we curate these studies to help prioritize biomarker candidates for validation studies and to obtain a broader view of processes regulated during disease development. Methods This systematic review was registered with Open Science Framework (DOI 10.17605/OSF.IO/N8TSA). Using PRISMA guidelines, we conducted a systematic search of proteomics studies of T1D in the PubMed to identify putative protein biomarkers of the disease. Studies that performed mass spectrometry-based untargeted/targeted proteomic analysis of human serum/plasma of control, pre-seroconversion, post-seroconversion, and/or T1D-diagnosed subjects were included. For unbiased screening, 3 reviewers screened all the articles independently using the pre-determined criteria. Results A total of 13 studies met our inclusion criteria, resulting in the identification of 251 unique proteins, with 27 (11%) being identified across 3 or more studies. The circulating protein biomarkers were found to be enriched in complement, lipid metabolism, and immune response pathways, all of which are found to be dysregulated in different phases of T1D development. We found a subset of 3 proteins (C3, KNG1 & CFAH), 6 proteins (C3, C4A, APOA4, C4B, A2AP & BTD) and 7 proteins (C3, CLUS, APOA4, C6, A2AP, C1R & CFAI) have consistent regulation between multiple studies in samples from individuals at pre-seroconversion, post-seroconversion and post-diagnosis compared to controls, respectively, making them strong candidates for clinical assay development. Conclusions Biomarkers analyzed in this systematic review highlight alterations in specific biological processes in T1D, including complement, lipid metabolism, and immune response pathways, and may have potential for further use in the clinic as prognostic or diagnostic assays.