Proteomic predictors of individualized nutrient-specific insulin secretion in health and disease.

Population level variation and molecular mechanisms behind insulin secretion in response to carbohydrate, protein, and fat remain uncharacterized despite ramifications for personalized nutrition. Here, we define prototypical insulin secretion dynamics in response to the three macronutrients in islets from 140 cadaveric donors, including those diagnosed with type 2 diabetes. While islets from the majority of donors exhibited the expected relative response magnitudes, with glucose being highest, amino acid moderate, and fatty acid small, 9% of islets stimulated with amino acid and 8% of islets stimulated with fatty acids had larger responses compared with high glucose. We leveraged this insulin response heterogeneity and used transcriptomics and proteomics to identify molecular correlates of specific nutrient responsiveness, as well as those proteins and mRNAs altered in type 2 diabetes. We also examine nutrient-responsiveness in stem cell-derived islet clusters and observe that they have dysregulated fuel sensitivity, which is a hallmark of functionally immature cells. Our study now represents the first comparison of dynamic responses to nutrients and multi-omics analysis in human insulin secreting cells. Responses of different people's islets to carbohydrate, protein, and fat lay the groundwork for personalized nutrition. ONE-SENTENCE SUMMARY: Deep phenotyping and multi-omics reveal individualized nutrient-specific insulin secretion propensity.

HumanIslets: An integrated platform for human islet data access and analysis.

Comprehensive molecular and cellular phenotyping of human islets can enable deep mechanistic insights for diabetes research. We established the Human Islet Data Analysis and Sharing (HI-DAS) consortium to advance goals in accessibility, usability, and integration of data from human islets isolated from donors with and without diabetes at the Alberta Diabetes Institute (ADI) IsletCore. Here we introduce HumanIslets.com , an open resource for the research community. This platform, which presently includes data on 547 human islet donors, allows users to access linked datasets describing molecular profiles, islet function and donor phenotypes, and to perform various statistical and functional analyses at the donor, islet and single-cell levels. As an example of the analytic capacity of this resource we show a dissociation between cell culture effects on transcript and protein expression, and an approach to correct for exocrine contamination found in hand-picked islets. Finally, we provide an example workflow and visualization that highlights links between type 2 diabetes status, SERCA3b Ca 2+ -ATPase levels at the transcript and protein level, insulin secretion and islet cell phenotypes. HumanIslets.com provides a growing and adaptable set of resources and tools to support the metabolism and diabetes research community.

A genome-wide CRISPR screen identifies CALCOCO2 as a regulator of beta cell function influencing type 2 diabetes risk.

Identification of the genes and processes mediating genetic association signals for complex diseases represents a major challenge. As many of the genetic signals for type 2 diabetes (T2D) exert their effects through pancreatic islet-cell dysfunction, we performed a genome-wide pooled CRISPR loss-of-function screen in a human pancreatic beta cell line. We assessed the regulation of insulin content as a disease-relevant readout of beta cell function and identified 580 genes influencing this phenotype. Integration with genetic and genomic data provided experimental support for 20 candidate T2D effector transcripts including the autophagy receptor CALCOCO2. Loss of CALCOCO2 was associated with distorted mitochondria, less proinsulin-containing immature granules and accumulation of autophagosomes upon inhibition of late-stage autophagy. Carriers of T2D-associated variants at the CALCOCO2 locus further displayed altered insulin secretion. Our study highlights how cellular screens can augment existing multi-omic efforts to support mechanistic understanding and provide evidence for causal effects at genome-wide association studies loci.

Muscle stem cells and fibro-adipogenic progenitors in female pelvic floor muscle regeneration following birth injury.

Pelvic floor muscle (PFM) injury during childbirth is a key risk factor for pelvic floor disorders that affect millions of women worldwide. Muscle stem cells (MuSCs), supported by the fibro-adipogenic progenitors (FAPs) and immune cells, are indispensable for the regeneration of injured appendicular skeletal muscles. However, almost nothing is known about their role in PFM regeneration following birth injury. To elucidate the role of MuSCs, FAPs, and immune infiltrate in this context, we used radiation to perturb cell function and followed PFM recovery in a validated simulated birth injury (SBI) rat model. Non-irradiated and irradiated rats were euthanized at 3,7,10, and 28 days post-SBI (dpi). Twenty-eight dpi, PFM fiber cross-sectional area (CSA) was significantly lower and the extracellular space occupied by immune infiltrate was larger in irradiated relative to nonirradiated injured animals. Following SBI in non-irradiated animals, MuSCs and FAPs expanded significantly at 7 and 3 dpi, respectively; this expansion did not occur in irradiated animals at the same time points. At 7 and 10 dpi, we observed persistent immune response in PFMs subjected to irradiation compared to non-irradiated injured PFMs. CSA of newly regenerated fibers was also significantly smaller following SBI in irradiated compared to non-irradiated injured PFMs. Our results demonstrate that the loss of function and decreased expansion of MuSCs and FAPs after birth injury lead to impaired PFM recovery. These findings form the basis for further studies focused on the identification of novel therapeutic targets to counteract postpartum PFM dysfunction and the associated pelvic floor disorders.

Zmiz1 is required for mature ß-cell function and mass expansion upon high fat feeding.

OBJECTIVE: Identifying the transcripts which mediate genetic association signals for type 2 diabetes (T2D) is critical to understand disease mechanisms. Studies in pancreatic islets support the transcription factor ZMIZ1 as a transcript underlying a T2D GWAS signal, but how it influences T2D risk is unknown. METHODS: ß-Cell-specific Zmiz1 knockout (Zmiz1ßKO) mice were generated and phenotypically characterised. Glucose homeostasis was assessed in Zmiz1ßKO mice and their control littermates on chow diet (CD) and high fat diet (HFD). Islet morphology and function were examined by immunohistochemistry and in vitro islet function was assessed by dynamic insulin secretion assay. Transcript and protein expression were assessed by RNA sequencing and Western blotting. In islets isolated from genotyped human donors, we assessed glucose-dependent insulin secretion and islet insulin content by static incubation assay. RESULTS: Male and female Zmiz1ßKO mice were glucose intolerant with impaired insulin secretion, compared with control littermates. Transcriptomic profiling of Zmiz1ßKO islets identified over 500 differentially expressed genes including those involved in ß-cell function and maturity, which we confirmed at the protein level. Upon HFD, Zmiz1ßKO mice fail to expand ß-cell mass and become severely diabetic. Human islets from carriers of the ZMIZ1-linked T2D-risk alleles have reduced islet insulin content and glucose-stimulated insulin secretion. CONCLUSIONS: ß-Cell Zmiz1 is required for normal glucose homeostasis. Genetic variation at the ZMIZ1 locus may influence T2D-risk by reducing islet mass expansion upon metabolic stress and the ability to maintain a mature ß-cell state.