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Biology subjects

Swensen, A. C.

Publications and source records attributed to Swensen, A. C..

2 recordsLinked to original sources

Deletion of carboxypeptidase E in beta cells disrupts proinsulin processing and alters beta cell identity in mice

Carboxypeptidase E (CPE) facilitates the conversion of prohormones into mature hormones and is highly expressed in multiple neuroendocrine tissues. Carriers of CPE mutations have elevated plasma proinsulin and develop severe obesity and hyperglycemia. We aimed to determine whether loss of Cpe in pancreatic beta cells disrupts proinsulin processing and accelerates development of diabetes and obesity in mice. Pancreatic beta cell-specific Cpe knockout mice ({beta}CpeKO; Cpefl/fl x Ins1Cre/+) lack mature insulin granules and have elevated proinsulin in plasma; however, glucose-and KCl-stimulated insulin secretion in {beta}CpeKO islets remained intact. High fat diet-fed {beta}CpeKO mice showed comparable weight gain and glucose tolerance compared to Wt littermates. Notably, beta-cell area was increased in chow-fed {beta}CpeKO mice and beta-cell replication was elevated in {beta}CpeKO islets. Transcriptomic analysis of {beta}CpeKO beta cells revealed elevated glycolysis and Hif1-target gene expression. Upon high glucose challenge, beta cells from {beta}CpeKO mice showed reduced mitochondrial membrane potential, increased reactive oxygen species, reduced MafA, and elevated Aldh1a3 transcript levels. Following multiple low-dose streptozotocin treatment, {beta}CpeKO mice had accelerated hyperglycemia with reduced beta-cell insulin and Glut2 expression. These findings suggest that Cpe and proper proinsulin processing are critical in maintaining beta cell function during the development of diabetes.

physiology↗

A comprehensive urine proteome database generated from patients with various renal conditions and prostate cancer

Urine proteins can serve as viable biomarkers for diagnosing and monitoring various diseases. A comprehensive urine proteome database, generated from a variety of urine samples with different disease conditions, can serve as a reference resource for facilitating discovery of potential urine protein biomarkers. Herein, we present a urine proteome database generated from multiple datasets using 2D LC-MS/MS proteome profiling of urine samples from healthy individuals (HI), renal transplant patients with acute rejection (AR) and stable graft (STA), patients with non-specific proteinuria (NS), and patients with prostate cancer (PC). A total of ~28,000 unique peptides spanning ~2,200 unique proteins were identified with a false discovery rate of <0.5% at the protein level. Over one third of the annotated proteins were plasma membrane proteins and another one third were extracellular proteins according to gene ontology analysis. Ingenuity Pathway Analysis of these proteins revealed 349 potential biomarkers. Surprisingly, 43% (167) of all known cluster of differentiation (CD) proteins were identified in the various human urine samples. Interestingly, following comparisons with five recently published urine proteome profiling studies, which applied similar approaches, there are still ~400 proteins which are unique to this current study. These may represent potential disease-associated proteins. Among them, several proteins such as myoglobin, serpin B3, renin receptor, and periostin have been reported as pathological markers for renal failure and prostate cancer, respectively. Taken together, our data should provide valuable information for future discovery and validation studies of urine protein biomarkers for various diseases.

systems biology↗