Rapid changes of mRNA-binding protein levels following glucose and 3-isobutyl-1-methylxanthine stimulation of insulinoma INS-1 cells

Single-nucleus RNA sequencing of human pancreatic islets identifies novel gene sets and distinguishes β-cell subpopulations with dynamic transcriptome profiles

BACKGROUND

Single-cell RNA sequencing (scRNA-seq) provides valuable insights into human islet cell types and their corresponding stable gene expression profiles. However, this approach requires cell dissociation that complicates its utility in vivo. On the other hand, single-nucleus RNA sequencing (snRNA-seq) has compatibility with frozen samples, elimination of dissociation-induced transcriptional stress responses, and affords enhanced information from intronic sequences that can be leveraged to identify pre-mRNA transcripts.

METHODS

We obtained nuclear preparations from fresh human islet cells and generated snRNA-seq datasets. We compared these datasets to scRNA-seq output obtained from human islet cells from the same donor. We employed snRNA-seq to obtain the transcriptomic profile of human islets engrafted in immunodeficient mice. In both analyses, we included the intronic reads in the snRNA-seq data with the GRCh38-2020-A library.

RESULTS

First, snRNA-seq analysis shows that the top four differentially and selectively expressed genes in human islet endocrine cells in vitro and in vivo are not the canonical genes but a new set of non-canonical gene markers including ZNF385D, TRPM3, LRFN2, PLUT (β-cells); PTPRT, FAP, PDK4, LOXL4 (α-cells); LRFN5, ADARB2, ERBB4, KCNT2 (δ-cells); and CACNA2D3, THSD7A, CNTNAP5, RBFOX3 (γ-cells). Second, by integrating information from scRNA-seq and snRNA-seq of human islet cells, we distinguish three β-cell sub-clusters: an INS pre-mRNA cluster (β3), an intermediate INS mRNA cluster (β2), and an INS mRNA-rich cluster (β1). These display distinct gene expression patterns representing different biological dynamic states both in vitro and in vivo. Interestingly, the INS mRNA-rich cluster (β1) becomes the predominant sub-cluster in vivo.

CONCLUSIONS

In summary, snRNA-seq and pre-mRNA analysis of human islet cells can accurately identify human islet cell populations, subpopulations, and their dynamic transcriptome profile in vivo.

The making of insulin in health and disease

The discovery of insulin in 1921 has been one of greatest scientific achievements of the 20th century. Since then, the availability of insulin has shifted the focus of diabetes treatment from trying to keep patients alive to saving and improving the life of millions. Throughout this time, basic and clinical research has advanced our understanding of insulin synthesis and action, both in healthy and pathological conditions. Yet, multiple aspects of insulin production remain unknown. In this review, we focus on the most recent findings on insulin synthesis, highlighting their relevance in diabetes. Graphical abstract.

Effect of prolonged exposure to sublethal concentrations of DDT and DDE on protein expression in human pancreatic beta cells

Pollution of the environment represents one of less explored potential reasons for the worldwide epidemic of type 2 diabetes. One of the most prevalent organochlorine pollutants remains the pesticide DDT and its degradation product DDE. Despite some epidemiologic correlations between levels of DDT and DDE in human organism and the prevalence of diabetes, there is almost no information about the exact targets of these compounds inside pancreatic beta cells. To detect functional areas of pancreatic beta cells that could be affected by exposure to DDT and DDE, we analyzed changes in protein expression in the NES2Y human pancreatic beta cell line exposed to three sublethal concentrations (0.1 μM, 1 μM, 10 μM) of DDT and DDE for 1 month. Protein separation and identification was achieved using high-resolution 2D-electrophoresis, computer analysis and mass spectrometry. With these techniques, four proteins were found downregulated after exposure to 10 μM DDT: three cytoskeletal proteins (cytokeratin 8, cytokeratin 18 and actin) and one protein involved in glycolysis (alpha-enolase). Two proteins were downregulated after exposure to 10 μM DDE: cytokeratin 18 and heterogenous nuclear ribonucleoprotein H1 (HNRH1). These changes correlate with previously described effects of other stress conditions (e.g. exposure to palmitate, hyperglycemia, imidazoline derivative, and cytokines) on protein expression in pancreatic beta cells. We conclude that cytoskeletal proteins and their processing, glucose metabolism, and mRNA processing may represent targets affected by exposure to conditions hostile to pancreatic beta cells, including exposure to DDT and DDE.

Impact of PTBP1 rs11085226 on glucose-stimulated insulin release in adult Danes

BACKGROUND

The variant rs11085226 (G) within the gene encoding polypyrimidine tract binding protein 1 (PTBP1) was reported to associate with reduced insulin release determined by an oral glucose tolerance test (OGTT) as well as an intravenous glucose tolerance test (IVGTT). The aim of the present study was to validate the association of the rs11085226 G-allele of PTBP1 with previously investigated OGTT- and IVGTT-derived diabetes-related metabolic quantitative phenotypes, to conduct exploratory analyses of additional measures of beta-cell function, and to further investigate a potential association with type 2 diabetes.

METHODS

PTBP1 rs11085226 was genotyped in 20,911 individuals of Danish Caucasian ethnicity ascertained from 9 study samples. Case control analysis was performed on 5,634 type 2 diabetic patients and 11,319 individuals having a normal fasting glucose level as well as 4,641 glucose tolerant controls, respectively. Quantitative trait analyses were performed in up to 13,605 individuals subjected to an OGTT or blood samples obtained after an overnight fast, as well as in 596 individuals subjected to an IVGTT.

RESULTS

Analyses of fasting and OGTT-derived quantitative traits did not show any significant associations with the PTBP1 rs11085226 variant. Meta-analysis of IVGTT-derived quantitative traits showed a nominally significant association between the variant and reduced beta-cell responsiveness to glucose (β = -0.1 mmol · kg(-1) · min(-1); 95% CI: -0.200.20 - -0.024; P = 0.01) assuming a dominant model of inheritance, but failed to replicate a previously reported association with area under the curve (AUC) for insulin. Case control analysis did not show an association of the PTBP1 rs11085226 variant with type 2 diabetes.

CONCLUSIONS

Despite failure to replicate the previously reported associations of PTBP1 rs11085226 with OGTT- and IVGTT-derived measures of beta-cell function, we did find a nominally significant association with reduced beta-cell responsiveness to glucose during an IVGTT, a trait not previously investigated, leaving the potential influence of this variant in PTBP1 on glucose stimulated insulin release open for further investigation. However, the present study does not support the hypothesis that the variant confers risk of type 2 diabetes.

Comparative proteome analysis of two Streptococcus agalactiae strains from cultured tilapia with different virulence

Streptococcus agalactiae is a major piscine pathogen, which causes significant morbidity and mortality among numerous fish species, and results in huge economic losses to aquaculture. Many S. agalactiae strains showing different virulence characteristics have been isolated from infected tilapia in different geographical regions throughout South China in the recent years, including natural attenuated S. agalactiae strain TFJ0901 and virulent S. agalactiae strain THN0901. In the present study, survival of tilapia challenged with S. agalactiae strain TFJ0901 and THN0901 (10(7)CFU/fish) were 93.3% and 13.3%, respectively. Moreover, there are severe lesions of the examined tissues in tilapia infected with strain THN0901, but no significant histopathological changes were observed in tilapia infected with the strain TFJ0901. In order to elucidate the factors responsible for the invasive potential of S. agalactiae between two strains TFJ0901 and THN0901, a comparative proteome analysis was applied to identify the different protein expression profiles between the two strains. 506 and 508 cellular protein spots of S. agalactiae TFJ0901 and THN0901 were separated by two dimensional electrophoresis, respectively. And 34 strain-specific spots, corresponding to 27 proteins, were identified successfully by MALDI-TOF mass spectrometry. Among them, 23 proteins presented exclusively in S. agalactiae TFJ0901 or THN0901, and the other 4 proteins presented in different isomeric forms between TFJ0901 and THN0901. Most of the strain-specific proteins were just involved in metabolic pathways, while 7 of them were presumed to be responsible for the virulence differences of S. agalactiae strain TFJ0901 and THN0901, including molecular chaperone DnaJ, dihydrolipoamide dehydrogenase, thioredoxin, manganese-dependent inorganic pyrophosphatase, elongation factor Tu, bleomycin resistance protein and cell division protein DivIVA. These virulence-associated proteins may contribute to identify new diagnostic markers and help to understand the pathogenesis of S. agalactiae.

Regulation of β-cell function by RNA-binding proteins

β-cells of the pancreatic islets are highly specialized and high-throughput units for the production of insulin, the key hormone for maintenance of glucose homeostasis. Elevation of extracellular glucose and/or GLP-1 levels triggers a rapid upregulation of insulin biosynthesis through the activation of post-transcriptional mechanisms. RNA-binding proteins are emerging as key factors in the regulation of these mechanisms as well as in other aspects of β-cell function and glucose homeostasis at large, and thus may be implicated in the pathogenesis of diabetes. Here we review current research in the field, with a major emphasis on RNA-binding proteins that control biosynthesis of insulin and other components of the insulin secretory granules by modulating the stability and translation of their mRNAs.

Polymorphism rs11085226 in the gene encoding polypyrimidine tract-binding protein 1 negatively affects glucose-stimulated insulin secretion

OBJECTIVE

Polypyrimidine tract-binding protein 1 (PTBP1) promotes stability and translation of mRNAs coding for insulin secretion granule proteins and thereby plays a role in β-cells function. We studied whether common genetic variations within the PTBP1 locus influence insulin secretion, and/or proinsulin conversion.

METHODS

We genotyped 1,502 healthy German subjects for four tagging single nucleotide polymorphisms (SNPs) within the PTBP1 locus (rs351974, rs11085226, rs736926, and rs123698) covering 100% of genetic variation with an r(2)≥0.8. The subjects were metabolically characterized by an oral glucose tolerance test with insulin, proinsulin, and C-peptide measurements. A subgroup of 320 subjects also underwent an IVGTT.

RESULTS

PTBP1 SNP rs11085226 was nominally associated with lower insulinogenic index and lower cleared insulin response in the OGTT (p≤0.04). The other tested SNPs did not show any association with the analyzed OGTT-derived secretion parameters. In the IVGTT subgroup, SNP rs11085226 was accordingly associated with lower insulin levels within the first ten minutes following glucose injection (p = 0.0103). Furthermore, SNP rs351974 was associated with insulin levels in the IVGTT (p = 0.0108). Upon interrogation of MAGIC HOMA-B data, our rs11085226 result was replicated (MAGIC p = 0.018), but the rs351974 was not.

CONCLUSIONS

We conclude that common genetic variation in PTBP1 influences glucose-stimulated insulin secretion. This underlines the importance of PTBP1 for beta cell function in vivo.

Proteomics in pancreatic cancer research

In this review, we give an overview of the actual role of proteomic technologies in the study of pancreatic cancers (PCs). We describe PC proteomics on the basis of sample origins, i.e. tissues, body fluids, and PC cell lines. As regards PC tissues, we report the identification of a number of candidate biomarkers of precursor lesions that may allow early diagnosis of this neoplasia. Moreover, we describe cytoskeletal and hypoxia-regulated proteins that confirm the involvement of cytoskeleton modifications and metabolism adaptations in carcinogenesis. We also discuss the most important biomarkers identified by proteomic analysis involved in local invasion and distant metastasis, and in the cross-talk between pancreatic tumor and the surrounding stroma. Furthermore, we report novel candidate biomarkers identified in serum, plasma, and pancreatic juice of cancer patients compared with cancer-free controls. Proteomic alterations in PC cell line models as compared to normal controls and studies on cell lines treated with drugs or new agents to understand their mechanism of pharmacological action or the onset of drug resistance are also presented. Finally, we discuss the recent improvements obtained in classical 2-DE and high-throughput proteomic strategies able to allow the overcoming of relevant proteomic drawbacks.

Islet protein profiling

Islet protein profiling is defined as generation of extended protein expression data sets from islets or islet cells. Islets from rodent control and animal models of type 1 and type 2 diabetes mellitus and healthy humans and insulin- and glucagon-producing cell lines have been used. Protein profiling entails separation, differential expression determination, identification and expression analysis. Protein/peptide separation is either gel-based or by chromatography. Differential expression is based on comparison of visualized spots/proteins between gels or by sample labelling in gel-free systems. Identification of proteins is made by tryptic fragmentation of proteins, fragment mass determination and mass comparison with protein databases. Analysis of expression data sets interprets the complex protein changes into cellular mechanisms to generate hypotheses. The importance of such protein expression sets to elucidate islet cellular events is evidenced by the observation that only about 50% of the differentially expressed proteins and transcripts showed concordance when measured in parallel. Using protein profiling, different areas related to islet dysfunction in type 1 and type 2 diabetes mellitus have been addressed, including dysfunction induced by elevated levels of glucose and fatty acids and cytokines. Because islets from individuals with type 1 or type 2 diabetes mellitus have not yet been protein profiled, islets from rat (BB-DP) and mouse (NOD, ob/ob, MKR) models of the disease have been used, and mechanisms responsible for islet dysfunction delineated offering avenues of intervention.

Role and therapeutic potential of microRNAs in diabetes

The discovery in mammalian cells of hundreds of small RNA molecules, called microRNAs, with the potential to modulate the expression of the majority of the protein-coding genes has revolutionized many areas of biomedical research, including the diabetes field. MicroRNAs function as translational repressors and are emerging as key regulators of most, if not all, physiological processes. Moreover, alterations in the level or function of microRNAs are associated with an increasing number of diseases. Here, we describe the mechanisms governing the biogenesis and activities of microRNAs. We present evidence for the involvement of microRNAs in diabetes mellitus, by outlining the contribution of these small RNA molecules in the control of pancreatic beta-cell functions and by reviewing recent studies reporting changes in microRNA expression in tissues isolated from diabetes animal models. MicroRNAs hold great potential as therapeutic targets. We describe the strategies developed for the delivery of molecules mimicking or blocking the function of these tiny regulators of gene expression in living animals. In addition, because changes in serum microRNA profiles have been shown to occur in association with different human diseases, we also discuss the potential use of microRNAs as blood biomarkers for prevention and management of diabetes.