MECHANISMS IN ENDOCRINOLOGY: Alternative splicing: the new frontier in diabetes research

Differences in splicing factors may predict type 2 diabetes remission in the CORDIOPREV study

Alternative splicing is a post-transcriptional process resulting in multiple protein isoforms from a single gene. Abnormal splicing may lead to metabolic diseases, including type 2 diabetes mellitus (T2DM). To identify the splicing factor expression that predicts T2DM remission in coronary heart disease (CHD) patients, we identified newly diagnosed T2DM at baseline (n = 190) from the CORDIOPREV study. Patients were classified as Responders (T2DM remission during 5 years without antidiabetic drugs) or non-Responders. Baseline dysregulation in 5 splicing factors (MBNL1, RBM5, hnRNP G/RBMX, CD44, NT5E) distinguished Responders from non-Responders. Adding these factors to clinical variables [AUC = 0.67], insulin resistance, and beta-cell indexes [AUC = 0.76], improved T2DM remission prediction [AUC = 0.80]. Cox regression analysis showed those with higher remission scores had a 2.63-fold increased remission probability. To conclude, a set of splicing factors that contribute to predicting T2DM remission in patients with CHD has been identified. Further research is needed to elucidate these findings' clinical relevance.

Regulation of endocrine cell alternative splicing revealed by single-cell RNA sequencing in type 2 diabetes pathogenesis

The prevalent RNA alternative splicing (AS) contributes to molecular diversity, which has been demonstrated in cellular function regulation and disease pathogenesis. However, the contribution of AS in pancreatic islets during diabetes progression remains unclear. Here, we reanalyze the full-length single-cell RNA sequencing data from the deposited database to investigate AS regulation across human pancreatic endocrine cell types in non-diabetic (ND) and type 2 diabetic (T2D) individuals. Our analysis demonstrates the significant association between transcriptomic AS profiles and cell-type-specificity, which could be applied to distinguish the clustering of major endocrine cell types. Moreover, AS profiles are enabled to clearly define the mature subset of β-cells in healthy controls, which is completely lost in T2D. Further analysis reveals that RNA-binding proteins (RBPs), heterogeneous nuclear ribonucleoproteins (hnRNPs) and FXR1 family proteins are predicted to induce the functional impairment of β-cells through regulating AS profiles. Finally, trajectory analysis of endocrine cells suggests the β-cell identity shift through dedifferentiation and transdifferentiation of β-cells during the progression of T2D. Together, our study provides a mechanism for regulating β-cell functions and suggests the significant contribution of AS program during diabetes pathogenesis.

Effects of myo-inositol on regulating glucose and lipid metabolism and alternative splicing events coexpressed with lncRNAs in the liver tissues of diabetic mice

Objective

Recent studies have shown that gene alternative splicing (AS) and long noncoding RNAs (lncRNAs) are involved in diabetes mellitus (DM) and its complications. Currently, myo-inositol (MI) is considered as effective for the treatment of insulin resistance and lipid metabolism disorders in diabetes patients. We hope to better explore the potential roles of gene AS and lncRNAs in liver glucose and lipid metabolism in diabetes, as well as the effects of myo-inositol treatment, through transcriptome analysis.

Methods

This study analysed glucose and lipid metabolism-related biochemical indicators and liver HE staining in four groups of mice: the control group (Ctrl group), the diabetes group (DM group), the myo-inositol treatment group (MI group), and the metformin treatment group (Met group). The changes in relevant gene-regulated alternative splicing events (RASEs) and lncRNAs were analysed by RNA sequencing of liver tissue, and coexpression analysis and functional enrichment analysis were used to predict the possible lncRNAs and RASEs involved in liver glucose and lipid metabolism.

Result

Metformin and myo-inositol alleviated insulin resistance, lipid metabolism disorders, and hepatic steatosis in diabetic mice. Transcriptome sequencing analysis revealed differential splicing events of genes related to lipid metabolism and differentially expressed lncRNAs (DElncRNAs). Six different lncRNAs and their potentially interacting splicing events were predicted.

Conclusion

The present study revealed novel changes in RASEs and lncRNAs in the livers of diabetic mice following treatment with myo-inositol, which may shed light on the potential mechanisms by which myo-inositol delays and treats the progression of hepatic glucose and lipid metabolism in diabetes.

Acute severe hypoglycemia alters mouse brain microvascular proteome

Hypoglycemia increases the risk related to stroke and neurodegenerative diseases, however, the underlying mechanisms are unclear. For the first time, we studied the effect of a single episode (acute) of severe (ASH) and mild (AMH) hypoglycemia on mouse brain microvascular proteome. After four-hour fasting, insulin was administered (i.p) to lower mean blood glucose in mice and induce ∼30 minutes of ASH (∼30 mg/dL) or AMH (∼75 mg/dL), whereas a similar volume of saline was given to control mice (∼130 mg/dL). Blood glucose was allowed to recover over 60 minutes either spontaneously or by 20% dextrose administration (i.p). Twenty-four hours later, the brain microvessels (BMVs) were isolated, and tandem mass tag (TMT)-based quantitative proteomics was performed using liquid chromatography-mass spectrometry (LC/MS). When compared to control, ASH significantly downregulated 13 proteins (p ≤ 0.05) whereas 23 proteins showed a strong trend toward decrease (p ≤ 0.10). When compared to AMH, ASH significantly induced the expression of 35 proteins with 13 proteins showing an increasing trend. AMH downregulated only 3 proteins. ASH-induced downregulated proteins are involved in actin cytoskeleton maintenance needed for cell shape and migration which are critical for blood-brain barrier maintenance and angiogenesis. In contrast, ASH-induced upregulated proteins are RNA-binding proteins involved in RNA splicing, transport, and stability. Thus, ASH alters BMV proteomics to impair cytoskeletal integrity and RNA processing which are critical for cerebrovascular function.

BCAS2 Participates in Insulin Synthesis and Secretion via mRNA Alternative Splicing in Mice

Insulin secreted by pancreatic β cells is essential for maintaining blood glucose levels. Diabetes is caused primarily by a loss of β cells or impairment of β-cell function. A previous whole-transcriptome analysis of islets from a type 2 diabetes group and a control group showed that a splicing disorder occurred in approximately 25% of splicing events. Breast carcinoma amplified sequence 2 (BCAS2) is a spliceosome component whose function in islet β cells is unclear. Here, we report that knockdown of Bcas2 decreased glucose- and KCl-stimulated insulin secretion in the NIT-1 cell line. Pancreas weight, glucose tolerance, and insulin sensitivity were measured in normal chow-fed Bcas2 f/f-βKO mice, and β-cell mass and islet size were analyzed by immunohistochemistry. Glucose intolerance developed in Bcas2 f/f-βKO mice, but there were no significant differences in pancreas weight, insulin sensitivity, β-cell mass, or islet size. Furthermore, observation of glucose-stimulated insulin secretion and insulin secretion granules in normal chow-fed mice revealed that the insulin level in serum and the number of insulin secretion granules were decreased in Bcas2 f/f-βKO mice. These differences were related to abnormal splicing of Syt7 and Tcf7l2 pre-mRNA. Taken together, these results demonstrate that BCAS2 is involved in alternative splicing during insulin synthesis and secretion.

Deep Learning for Genomics: From Early Neural Nets to Modern Large Language Models

The data explosion driven by advancements in genomic research, such as high-throughput sequencing techniques, is constantly challenging conventional methods used in genomics. In parallel with the urgent demand for robust algorithms, deep learning has succeeded in various fields such as vision, speech, and text processing. Yet genomics entails unique challenges to deep learning, since we expect a superhuman intelligence that explores beyond our knowledge to interpret the genome from deep learning. A powerful deep learning model should rely on the insightful utilization of task-specific knowledge. In this paper, we briefly discuss the strengths of different deep learning models from a genomic perspective so as to fit each particular task with proper deep learning-based architecture, and we remark on practical considerations of developing deep learning architectures for genomics. We also provide a concise review of deep learning applications in various aspects of genomic research and point out current challenges and potential research directions for future genomics applications. We believe the collaborative use of ever-growing diverse data and the fast iteration of deep learning models will continue to contribute to the future of genomics.

Disease-modifying therapies and features linked to treatment response in type 1 diabetes prevention: a systematic review

BACKGROUND

Type 1 diabetes (T1D) results from immune-mediated destruction of insulin-producing beta cells. Prevention efforts have focused on immune modulation and supporting beta cell health before or around diagnosis; however, heterogeneity in disease progression and therapy response has limited translation to clinical practice, highlighting the need for precision medicine approaches to T1D disease modification.

METHODS

To understand the state of knowledge in this area, we performed a systematic review of randomized-controlled trials with ≥50 participants cataloged in PubMed or Embase from the past 25 years testing T1D disease-modifying therapies and/or identifying features linked to treatment response, analyzing bias using a Cochrane-risk-of-bias instrument.

RESULTS

We identify and summarize 75 manuscripts, 15 describing 11 prevention trials for individuals with increased risk for T1D, and 60 describing treatments aimed at preventing beta cell loss at disease onset. Seventeen interventions, mostly immunotherapies, show benefit compared to placebo (only two prior to T1D onset). Fifty-seven studies employ precision analyses to assess features linked to treatment response. Age, beta cell function measures, and immune phenotypes are most frequently tested. However, analyses are typically not prespecified, with inconsistent methods of reporting, and tend to report positive findings.

CONCLUSIONS

While the quality of prevention and intervention trials is overall high, the low quality of precision analyses makes it difficult to draw meaningful conclusions that inform clinical practice. To facilitate precision medicine approaches to T1D prevention, considerations for future precision studies include the incorporation of uniform outcome measures, reproducible biomarkers, and prespecified, fully powered precision analyses into future trial design.

Gene expression signature predicts rate of type 1 diabetes progression

BACKGROUND

Type 1 diabetes is a complex heterogenous autoimmune disease without therapeutic interventions available to prevent or reverse the disease. This study aimed to identify transcriptional changes associated with the disease progression in patients with recent-onset type 1 diabetes.

METHODS

Whole-blood samples were collected as part of the INNODIA study at baseline and 12 months after diagnosis of type 1 diabetes. We used linear mixed-effects modelling on RNA-seq data to identify genes associated with age, sex, or disease progression. Cell-type proportions were estimated from the RNA-seq data using computational deconvolution. Associations to clinical variables were estimated using Pearson's or point-biserial correlation for continuous and dichotomous variables, respectively, using only complete pairs of observations.

FINDINGS

We found that genes and pathways related to innate immunity were downregulated during the first year after diagnosis. Significant associations of the gene expression changes were found with ZnT8A autoantibody positivity. Rate of change in the expression of 16 genes between baseline and 12 months was found to predict the decline in C-peptide at 24 months. Interestingly and consistent with earlier reports, increased B cell levels and decreased neutrophil levels were associated with the rapid progression.

INTERPRETATION

There is considerable individual variation in the rate of progression from appearance of type 1 diabetes-specific autoantibodies to clinical disease. Patient stratification and prediction of disease progression can help in developing more personalised therapeutic strategies for different disease endotypes.

FUNDING

A full list of funding bodies can be found under Acknowledgments.

Type 1 Diabetes Prevention: a systematic review of studies testing disease-modifying therapies and features linked to treatment response

Background

Type 1 diabetes (T1D) results from immune-mediated destruction of insulin-producing beta cells. Efforts to prevent T1D have focused on modulating immune responses and supporting beta cell health; however, heterogeneity in disease progression and responses to therapies have made these efforts difficult to translate to clinical practice, highlighting the need for precision medicine approaches to T1D prevention.

Methods

To understand the current state of knowledge regarding precision approaches to T1D prevention, we performed a systematic review of randomized-controlled trials from the past 25 years testing disease-modifying therapies in T1D and/or identifying features linked to treatment response, analyzing bias using a Cochrane-risk-of-bias instrument.

Results

We identified 75 manuscripts, 15 describing 11 prevention trials for individuals with increased risk for T1D, and 60 describing treatments aimed at preventing beta cell loss in individuals at disease onset. Seventeen agents tested, mostly immunotherapies, showed benefit compared to placebo (only two prior to T1D onset). Fifty-seven studies employed precision analyses to assess features linked to treatment response. Age, measures of beta cell function and immune phenotypes were most frequently tested. However, analyses were typically not prespecified, with inconsistent methods reporting, and tended to report positive findings.

Conclusions

While the quality of prevention and intervention trials was overall high, low quality of precision analyses made it difficult to draw meaningful conclusions that inform clinical practice. Thus, prespecified precision analyses should be incorporated into the design of future studies and reported in full to facilitate precision medicine approaches to T1D prevention.

Plain Language Summary

Type 1 diabetes (T1D) results from the destruction of insulin-producing cells in the pancreas, necessitating lifelong insulin dependence. T1D prevention remains an elusive goal, largely due to immense variability in disease progression. Agents tested to date in clinical trials work in a subset of individuals, highlighting the need for precision medicine approaches to prevention. We systematically reviewed clinical trials of disease-modifying therapy in T1D. While age, measures of beta cell function, and immune phenotypes were most commonly identified as factors that influenced treatment response, the overall quality of these studies was low. This review reveals an important need to proactively design clinical trials with well-defined analyses to ensure that results can be interpreted and applied to clinical practice.

Circular RNA in autoimmune diseases: special emphasis on regulation mechanism in RA and SLE

BACKGROUND

Autoimmune diseases are diseases caused by tissue damage caused by the body's immune response to autoantibodies. Circular RNAs (CircRNAs) are a kind of special endogenous non-coding RNA that play a biological role by regulating gene transcription.

METHODS

In this work, we searched the PubMed, Web of Science (SCIE), National Science and Technology Library (NSTL), and ScienceDirect Online (SDOL) databases to summarize the impact of circRNAs on autoimmune diseases, especially the results of circRNAs in rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE).

RESULTS

The study on the function of circRNAs and autoimmune diseases further deepened our understanding of the development and pathogenesis of autoimmune diseases. CircRNAs may act as miRNA sponges to regulate biological processes and affect the occurrence and development of autoimmune diseases. CircRNAs are closely related to the pathogenesis of RA and SLE and may become potential biomarkers for the diagnosis and treatment of RA and SLE.

CONCLUSION

CircRNAs play an important role in the pathogenesis of RA, SLE and other autoimmune diseases, and are expected to provide new biomarkers for the diagnosis and treatment of autoimmune diseases. However, the function and mechanism of circRNAs in autoimmune diseases need more comprehensive research.

Identification of a novel alternatively spliced isoform of the ribosomal uL10 protein

Alternative splicing is one of the key mechanisms extending the complexity of genetic information and at the same time adaptability of higher eukaryotes. As a result, the broad spectrum of isoforms produced by alternative splicing allows organisms to fine-tune their proteome; however, the functions of the majority of alternatively spliced protein isoforms are largely unknown. Ribosomal protein isoforms are one of the groups for which data are limited. Here we report characterization of an alternatively spliced isoform of the ribosomal uL10 protein, named uL10β. The uL10 protein constitutes the core element of the ribosomal stalk structure within the GTPase associated center, which represents the landing platform for translational GTPases - trGTPases. The stalk plays an important role in the ribosome-dependent stimulation of GTP by trGTPases, which confer unidirectional trajectory for the ribosome, allosterically contributing to the speed and accuracy of translation. We have shown that the newly identified uL10β protein is stably expressed in mammalian cells and is primarily located within the nuclear compartment with a minor signal within the cytoplasm. Importantly, uL10β is able to bind to the ribosomal particle, but is mainly associated with 60S and 80S particles; additionally, the uL10β undergoes re-localization into the mitochondria upon endoplasmic reticulum stress induction. Our results suggest a specific stress-related dual role of uL10β, supporting the idea of existence of specialized ribosomes with an altered GTPase associated center.

A seven-transmembrane protein-TM7SF3, resides in nuclear speckles and regulates alternative splicing

The seven-transmembrane superfamily member 3 protein (TM7SF3) is a p53-regulated homeostatic factor that attenuates cellular stress and the unfolded protein response. Here we show that TM7SF3 localizes to nuclear speckles; eukaryotic nuclear bodies enriched in splicing factors. This unexpected location for a trans -membranal protein enables formation of stable complexes between TM7SF3 and pre-mRNA splicing factors including DHX15, LARP7, HNRNPU, RBM14, and HNRNPK. Indeed, TM7SF3 regulates alternative splicing of >330 genes, mainly at the 3'end of introns by directly modulating the activity of splicing factors such as HNRNPK. These effects are observed both in cell lines and primary human pancreatic islets. Accordingly, silencing of TM7SF3 results in differential expression of 1465 genes (about 7% of the human genome); with 844 and 621 genes being up- or down-regulated, respectively. Our findings implicate TM7SF3, as a resident protein of nuclear speckles and suggest a role for seven-transmembrane proteins as regulators of alternative splicing.

The missing heritability in type 1 diabetes

Type 1 diabetes (T1D) is a complex autoimmune disease characterized by an absolute deficiency of insulin. It affects more than 20 million people worldwide and imposes an enormous financial burden on patients. The underlying pathogenic mechanisms of T1D are still obscure, but it is widely accepted that both genetics and the environment play an important role in its onset and development. Previous studies have identified more than 60 susceptible loci associated with T1D, explaining approximately 80%-85% of the heritability. However, most identified variants confer only small increases in risk, which restricts their potential clinical application. In addition, there is still a so-called 'missing heritability' phenomenon. While the gap between known heritability and true heritability in T1D is small compared with that in other complex traits and disorders, further elucidation of T1D genetics has the potential to bring novel insights into its aetiology and provide new therapeutic targets. Many hypotheses have been proposed to explain the missing heritability, including variants remaining to be found (variants with small effect sizes, rare variants and structural variants) and interactions (gene-gene and gene-environment interactions; e.g. epigenetic effects). In the following review, we introduce the possible sources of missing heritability and discuss the existing related knowledge in the context of T1D.

A Humanized Mouse Strain That Develops Spontaneously Immune-Mediated Diabetes

To circumvent the limitations of available preclinical models for the study of type 1 diabetes (T1D), we developed a new humanized model, the YES-RIP-hB7.1 mouse. This mouse is deficient of murine major histocompatibility complex class I and class II, the murine insulin genes, and expresses as transgenes the HLA-A*02:01 allele, the diabetes high-susceptibility HLA-DQ8A and B alleles, the human insulin gene, and the human co-stimulatory molecule B7.1 in insulin-secreting cells. It develops spontaneous T1D along with CD4⁺ and CD8⁺ T-cell responses to human preproinsulin epitopes. Most of the responses identified in these mice were validated in T1D patients. This model is amenable to characterization of hPPI-specific epitopes involved in T1D and to the identification of factors that may trigger autoimmune response to insulin-secreting cells in human T1D. It will allow evaluating peptide-based immunotherapy that may directly apply to T1D in human and complete preclinical model availability to address the issue of clinical heterogeneity of human disease.

Dietary genistein supplementation alters mRNA expression profile and alternative splicing signature in the thymus of chicks with lipopolysaccharide challenge

Genistein is abundant in the soybean products, which exerts prominent effects on immune function. Little information is available about the effect of dietary genistein on thymic transcriptome, especially when suffering from lipopolysaccharide challenge. In this study, 180 one-day-old male broilers were randomly allocated to 3 groups: nonchallenged chicks given a basal diet (CON), and lipopolysaccharide-challenged chicks fed a basal diet (LPS), or lipopolysaccharide-challenged chicks fed a basal diet supplemented with 40 mg/kg genistein (GEN). Lipopolysaccharide injection induced thymocyte apoptosis and inflammatory reactions in the chicks. The results showed dietary genistein significantly reduced the percentage of CD3+ T lymphocytes by 10.04% and CD4+/CD8+ T lymphocyte ratio by 21.88% in the peripheral blood induced by lipopolysaccharide injection (P < 0.05). In addition, genistein significantly reduced the thymus index by 50% and apoptotic index by 12.34% induced by LPS challenge (P < 0.05). Transcriptomic analysis identified 1,926 DEGs (1,014 upregulated and 912 downregulated, P < 0.05) between GEN and LPS groups, which altered the mRNA expression profile and signaling pathways (Toll-like receptor, and NOD-like receptor signaling pathway) in the thymus. Furthermore, 5 splicing (AS) isoforms of the Drosophila Disabled-2 (DAB2) gene were detected, which were significantly upregulated in the GEN group compared with that in the LPS group. In summary, dietary genistein supplementation altered the RNA expression profile and AS signatures in the thymus, and alleviated immune response against lipopolysaccharide challenge.

RBFOX splicing factors contribute to a broad but selective recapitulation of peripheral tissue splicing patterns in the thymus

Thymic epithelial cells (TEC) control the selection of a T cell repertoire reactive to pathogens but tolerant of self. This process is known to involve the promiscuous expression of virtually the entire protein-coding gene repertoire, but the extent to which TEC recapitulate peripheral isoforms, and the mechanisms by which they do so, remain largely unknown. We performed the first assembly-based transcriptomic census of transcript structures and splicing factor (SF) expression in mouse medullary TEC (mTEC) and 21 peripheral tissues. Mature mTEC expressed 60.1% of all protein-coding transcripts, more than was detected in any of the peripheral tissues. However, for genes with tissue-restricted expression, mTEC produced fewer isoforms than did the relevant peripheral tissues. Analysis of exon inclusion revealed an absence of brain-specific microexons in mTEC. We did not find unusual numbers of novel transcripts in TEC, and we show that Aire, the facilitator of promiscuous gene expression, promotes the generation of long “classical” transcripts (with 5′ and 3′ UTRs) but has only a limited impact on alternative splicing in mTEC. Comprehensive assessment of SF expression in mTEC identified a small set of nonpromiscuously expressed SF genes, among which we confirmed RBFOX to be present with AIRE in mTEC nuclei. Using a conditional loss-of-function approach, we show that Rbfox2 promotes mTEC development and regulates the alternative splicing of promiscuously expressed genes. These data indicate that TEC recommission a small number of peripheral SFs, including members of the RBFOX family, to generate a broad but selective representation of the peripheral splice isoform repertoire.

From Pancreatic β-Cell Gene Networks to Novel Therapies for Type 1 Diabetes

Completion of the Human Genome Project enabled a novel systems- and network-level understanding of biology, but this remains to be applied for understanding the pathogenesis of type 1 diabetes (T1D). We propose that defining the key gene regulatory networks that drive β-cell dysfunction and death in T1D might enable the design of therapies that target the core disease mechanism, namely, the progressive loss of pancreatic β-cells. Indeed, many successful drugs do not directly target individual disease genes but, rather, modulate the consequences of defective steps, targeting proteins located one or two steps downstream. If we transpose this to the T1D situation, it makes sense to target the pathways that modulate the β-cell responses to the immune assault-in relation to signals that may stimulate the immune response (e.g., HLA class I and chemokine overexpression and/or neoantigen expression) or inhibit the invading immune cells (e.g., PDL1 and HLA-E expression)-instead of targeting only the immune system, as it is usually proposed. Here we discuss the importance of a focus on β-cells in T1D, lessons learned from other autoimmune diseases, the "alternative splicing connection," data mining, and drug repurposing to protect β-cells in T1D and then some of the initial candidates under testing for β-cell protection.

Enriched Alternative Splicing in Islets of Diabetes-Susceptible Mice

Dysfunctional islets of Langerhans are a hallmark of type 2 diabetes (T2D). We hypothesize that differences in islet gene expression alternative splicing which can contribute to altered protein function also participate in islet dysfunction. RNA sequencing (RNAseq) data from islets of obese diabetes-resistant and diabetes-susceptible mice were analyzed for alternative splicing and its putative genetic and epigenetic modulators. We focused on the expression levels of chromatin modifiers and SNPs in regulatory sequences. We identified alternative splicing events in islets of diabetes-susceptible mice amongst others in genes linked to insulin secretion, endocytosis or ubiquitin-mediated proteolysis pathways. The expression pattern of 54 histones and chromatin modifiers, which may modulate splicing, were markedly downregulated in islets of diabetic animals. Furthermore, diabetes-susceptible mice carry SNPs in RNA-binding protein motifs and in splice sites potentially responsible for alternative splicing events. They also exhibit a larger exon skipping rate, e.g., in the diabetes gene Abcc8, which might affect protein function. Expression of the neuronal splicing factor Srrm4 which mediates inclusion of microexons in mRNA transcripts was markedly lower in islets of diabetes-prone compared to diabetes-resistant mice, correlating with a preferential skipping of SRRM4 target exons. The repression of Srrm4 expression is presumably mediated via a higher expression of miR-326-3p and miR-3547-3p in islets of diabetic mice. Thus, our study suggests that an altered splicing pattern in islets of diabetes-susceptible mice may contribute to an elevated T2D risk.

A deep learning approach to identify gene targets of a therapeutic for human splicing disorders

Pre-mRNA splicing is a key controller of human gene expression. Disturbances in splicing due to mutation lead to dysregulated protein expression and contribute to a substantial fraction of human disease. Several classes of splicing modulator compounds (SMCs) have been recently identified and establish that pre-mRNA splicing represents a target for therapy. We describe herein the identification of BPN-15477, a SMC that restores correct splicing of ELP1 exon 20. Using transcriptome sequencing from treated fibroblast cells and a machine learning approach, we identify BPN-15477 responsive sequence signatures. We then leverage this model to discover 155 human disease genes harboring ClinVar mutations predicted to alter pre-mRNA splicing as targets for BPN-15477. Splicing assays confirm successful correction of splicing defects caused by mutations in CFTR, LIPA, MLH1 and MAPT. Subsequent validations in two disease-relevant cellular models demonstrate that BPN-15477 increases functional protein, confirming the clinical potential of our predictions.

Consequences for Pancreatic β-Cell Identity and Function of Unregulated Transcript Processing

Mounting evidence suggests a role for alternative splicing (AS) of transcripts in the normal physiology and pathophysiology of the pancreatic β-cell. In the apparent absence of RNA repair systems, RNA decay pathways are likely to play an important role in controlling the stability, distribution and diversity of transcript isoforms in these cells. Around 35% of alternatively spliced transcripts in human cells contain premature termination codons (PTCs) and are targeted for degradation via nonsense-mediated decay (NMD), a vital quality control process. Inflammatory cytokines, whose levels are increased in both type 1 (T1D) and type 2 (T2D) diabetes, stimulate alternative splicing events and the expression of NMD components, and may or may not be associated with the activation of the NMD pathway. It is, however, now possible to infer that NMD plays a crucial role in regulating transcript processing in normal and stress conditions in pancreatic β-cells. In this review, we describe the possible role of Regulated Unproductive Splicing and Translation (RUST), a molecular mechanism embracing NMD activity in relationship to AS and translation of damaged transcript isoforms in these cells. This process substantially reduces the abundance of non-functional transcript isoforms, and its dysregulation may be involved in pancreatic β-cell failure in diabetes.

The RNA-binding profile of the splicing factor SRSF6 in immortalized human pancreatic β-cells

In pancreatic β-cells, the expression of the splicing factor SRSF6 is regulated by GLIS3, a transcription factor encoded by a diabetes susceptibility gene. SRSF6 down-regulation promotes β-cell demise through splicing dysregulation of central genes for β-cells function and survival, but how RNAs are targeted by SRSF6 remains poorly understood. Here, we define the SRSF6 binding landscape in the human pancreatic β-cell line EndoC-βH1 by integrating individual-nucleotide resolution UV cross-linking and immunoprecipitation (iCLIP) under basal conditions with RNA sequencing after SRSF6 knockdown. We detect thousands of SRSF6 bindings sites in coding sequences. Motif analyses suggest that SRSF6 specifically recognizes a purine-rich consensus motif consisting of GAA triplets and that the number of contiguous GAA triplets correlates with increasing binding site strength. The SRSF6 positioning determines the splicing fate. In line with its role in β-cell function, we identify SRSF6 binding sites on regulated exons in several diabetes susceptibility genes. In a proof-of-principle, the splicing of the susceptibility gene LMO7 is modulated by antisense oligonucleotides. Our present study unveils the splicing regulatory landscape of SRSF6 in immortalized human pancreatic β-cells.

Dietary Intervention Modulates the Expression of Splicing Machinery in Cardiovascular Patients at High Risk of Type 2 Diabetes Development: From the CORDIOPREV Study

Type-2 diabetes mellitus (T2DM) has become a major health problem worldwide. T2DM risk can be reduced with healthy dietary interventions, but the precise molecular underpinnings behind this association are still incompletely understood. We recently discovered that the expression profile of the splicing machinery is associated with the risk of T2DM development. Thus, the aim of this work was to evaluate the influence of 3-year dietary intervention in the expression pattern of the splicing machinery components in peripheral blood mononuclear cells (PBMCs) from patients within the CORDIOPREV study. Expression of splicing machinery components was determined in PBMCs, at baseline and after 3 years of follow-up, from all patients who developed T2DM (Incident-T2DM, n = 107) and 108 randomly selected non-T2DM subjects, who were randomly enrolled in two healthy dietary patterns (Mediterranean or low-fat diets). Dietary intervention modulated the expression of key splicing machinery components (i.e., up-regulation of SPFQ/RMB45/RNU6, etc., down-regulation of RNU2/SRSF6) after three years, independently of the type of healthy diet. Some of these changes (SPFQ/RMB45/SRSF6) were associated with key clinical features and were differentially induced in Incident-T2DM patients and non-T2DM subjects. This study reveals that splicing machinery can be modulated by long-term dietary intervention, and could become a valuable tool to screen the progression of T2DM.

Not only cancer: the long non-coding RNA MALAT1 affects the repertoire of alternatively spliced transcripts and circular RNAs in multiple sclerosis

Long non-coding RNAs (lncRNAs) are post-transcriptional and epigenetic regulators, whose implication in neurodegenerative and autoimmune diseases remains poorly understood. We analyzed publicly available microarray data sets to identify dysregulated lncRNAs in multiple sclerosis (MS), a neuroinflammatory autoimmune disease. We found a consistent upregulation in MS of the lncRNA MALAT1 (2.7-fold increase; meta-analysis, P = 1.3 × 10-8; 190 cases, 182 controls), known to regulate alternative splicing (AS). We confirmed MALAT1 upregulation in two independent MS cohorts (1.5-fold increase; P < 0.01; 59 cases, 50 controls). We hence performed MALAT1 overexpression/knockdown in cell lines, demonstrating that its modulation impacts on endogenous expression of splicing factors (HNRNPF and HNRNPH1) and on AS of MS-associated genes (IL7R and SP140). Minigene-based splicing assays upon MALAT1 modulation recapitulated IL7R and SP140 isoform unbalances observed in patients. RNA-sequencing of MALAT1-knockdown Jurkat cells further highlighted MALAT1 role in splicing (approximately 1100 significantly-modulated AS events) and revealed its contribution to backsplicing (approximately 50 differentially expressed circular RNAs). Our study proposes a possible novel role for MALAT1 dysregulation and the consequent AS alteration in MS pathogenesis, based on anomalous splicing/backsplicing profiles of MS-relevant genes.

Graphene quantum dots rescue protein dysregulation of pancreatic β-cells exposed to human islet amyloid polypeptide

The amyloid aggregation of peptides and proteins is a hallmark of neurological disorders and type 2 diabetes. Human islet amyloid polypeptide (IAPP), co-secreted with insulin by pancreatic β-cells, plays dual roles in both glycemic control and the pathology of type 2 diabetes. While IAPP can activate the NLRP3 inflammasome and modulate cellular autophagy, apoptosis and extracellular matrix metabolism, no data is available concerning intracellular protein expression upon exposure to the polypeptide. More surprisingly, how intracellular protein expression is modulated by nanoparticle inhibitors of protein aggregation remains entirely unknown. In this study, we first examined the changing proteomes of βTC6, a pancreatic β-cell line, upon exposure to monomeric, oligomeric and fibrillar IAPP, and detailed cellular protein expression rescued by graphene quantum dots (GQDs), an IAPP inhibitor. We found that 29 proteins were significantly dysregulated by the IAPP species, while majority of these proteins were nucleotide-binding proteins. Collectively, our liquid chromatography tandem-mass spectrometry, fluorescence quenching, helium ion microscopy, cytotoxicity and discreet molecular dynamics simulations data revealed a remarkable capacity of GQDs in regulating aberrant protein expression through H-bonding and hydrophobic interactions, pointing to nanomedicine as a new frontier against human amyloid diseases.

Modulation of the Apoptosis Gene Bcl-x Function Through Alternative Splicing

Apoptosis plays a vital role in cell homeostasis during development and disease. Bcl-x, a member of the Bcl-2 family of proteins, is a mitochondrial transmembrane protein that functions to regulate the intrinsic apoptosis pathway. An alternative splicing (AS) event in exon 2 of Bcl-x results in two isoforms of Bcl-x with antagonistic effects on cell survival: Bcl-xL (long isoform), which is anti-apoptotic, and Bcl-xS (short isoform), which is pro-apoptotic. Bcl-xL is the most abundant Bcl-x protein and functions to inhibit apoptosis by a number of different mechanisms including inhibition of Bax. In contrast, Bcl-xS can directly bind to and inhibit the anti-apoptotic Bcl-xL and Bcl-2 proteins, resulting in the release of the pro-apoptotic Bak. There are multiple splice factors and signaling pathways that influence the Bcl-xL/Bcl-xS splicing ratio, including serine/arginine-rich (SR) proteins, heterogeneous nuclear ribonucleoproteins (hnRNPs), transcription factors, and cytokines. Dysregulation of the AS of Bcl-x has been implicated in cancer and diabetes. In cancer, the upregulation of Bcl-xL expression in tumor cells can result in resistance to chemotherapeutic agents. On the other hand, dysregulation of Bcl-x AS to promote Bcl-xS expression has been shown to be detrimental to pancreatic β-cells in diabetes, resulting in β-cell apoptosis. Therefore, manipulation of the splice factor, transcription factor, and signaling pathways that modulate this splicing event is fast emerging as a therapeutic avenue in the treatment of cancer and diabetes.

MCPIP1 regulates the sensitivity of pancreatic beta-cells to cytokine toxicity

The autoimmune-mediated beta-cell death in type 1 diabetes (T1DM) is associated with local inflammation (insulitis). We examined the role of MCPIP1 (monocyte chemotactic protein–induced protein 1), a novel cytokine-induced antiinflammatory protein, in this process. Basal MCPIP1 expression was lower in rat vs. human islets and beta-cells. Proinflammatory cytokines stimulated MCPIP1 expression in rat and human islets and in insulin-secreting cells. Moderate overexpression of MCPIP1 protected insulin-secreting INS1E cells against cytokine toxicity by a mechanism dependent on the presence of the PIN/DUB domain in MCPIP1. It also reduced cytokine-induced Chop and C/ebpβ expression and maintained MCL-1 expression. The shRNA-mediated suppression of MCPIP1 led to the potentiation of cytokine-mediated NFκB activation and cytokine toxicity in human EndoC-βH1 beta-cells. MCPIP1 expression was very high in infiltrated beta-cells before and after diabetes manifestation in the LEW.1AR1-iddm rat model of human T1DM. The extremely high expression of MCPIP1 in clonal beta-cells was associated with a failure of the regulatory feedback-loop mechanism, ER stress induction and high cytokine toxicity. In conclusion, our data indicate that the expression level of MCPIP1 affects the susceptibility of insulin-secreting cells to cytokines and regulates the mechanism of beta-cell death in T1DM.

Interpreting Non-coding Genetic Variation in Multiple Sclerosis Genome-Wide Associated Regions

Multiple sclerosis (MS) is the most common neurological disorder in young adults. Despite extensive studies, only a fraction of MS heritability has been explained, with association studies focusing primarily on protein-coding genes, essentially for the difficulty of interpreting non-coding features. However, non-coding RNAs (ncRNAs) and functional elements, such as super-enhancers (SE), are crucial regulators of many pathways and cellular mechanisms, and they have been implicated in a growing number of diseases. In this work, we searched for possible enrichments in non-coding elements at MS genome-wide associated loci, with the aim to highlight their possible involvement in the susceptibility to the disease. We first reconstructed the linkage disequilibrium (LD) structure of the Italian population using data of 727,478 single-nucleotide polymorphisms (SNPs) from 1,668 healthy individuals. The genomic coordinates of the obtained LD blocks were intersected with those of the top hits identified in previously published MS genome-wide association studies (GWAS). By a bootstrapping approach, we hence demonstrated a striking enrichment of non-coding elements, especially of circular RNAs (circRNAs) mapping in the 73 LD blocks harboring MS-associated SNPs. In particular, we found a total of 482 circRNAs (annotated in publicly available databases) vs. a mean of 194 ± 65 in the random sets of LD blocks, using 1,000 iterations. As a proof of concept of a possible functional relevance of this observation, we experimentally verified that the expression levels of a circRNA derived from an MS-associated locus, i.e., hsa_circ_0043813 from the STAT3 gene, can be modulated by the three genotypes at the disease-associated SNP. Finally, by evaluating RNA-seq data of two cell lines, SH-SY5Y and Jurkat cells, representing tissues relevant for MS, we identified 18 (two novel) circRNAs derived from MS-associated genes. In conclusion, this work showed for the first time that MS-GWAS top hits map in LD blocks enriched in circRNAs, suggesting circRNAs as possible novel contributors to the disease pathogenesis.

Changes in Splicing Machinery Components Influence, Precede, and Early Predict the Development of Type 2 Diabetes: From the CORDIOPREV Study

Background

Type-2 diabetes mellitus (T2DM) is a major health problem with increasing incidence, which severely impacts cardiovascular disease. Because T2DM is associated with altered gene expression and aberrant splicing, we hypothesized that dysregulations in splicing machinery could precede, contribute to, and predict T2DM development.

Methods

A cohort of patients with cardiovascular disease (CORDIOPREV study) and without T2DM at baseline (at the inclusion of the study) was used (n = 215). We determined the expression of selected splicing machinery components in fasting and 4 h-postprandial peripheral blood mononuclear cells (PBMCs, obtained at baseline) from all the patients who developed T2DM during 5-years of follow-up (n = 107 incident-T2DM cases) and 108 randomly selected non-T2DM patients (controls). Serum from incident-T2DM and control patients was used to analyze in vitro the modulation of splicing machinery expression in control PBMCs from an independent cohort of healthy subjects.

Findings

Expression of key splicing machinery components (e.g. RNU2, RNU4 or RNU12) from fasting and 4 h-postprandial PBMCs of incident-T2DM patients was markedly altered compared to non-T2DM controls. Moreover, in vitro treatment of healthy individuals PBMCs with serum from incident-T2DM patients (compared to non-T2DM controls) reduced the expression of splicing machinery elements found down-regulated in incident-T2DM patients PBMCs. Finally, fasting/postprandial levels of several splicing machinery components in the PBMCs of CORDIOPREV patients were associated to higher risk of T2DM (Odds Ratio > 4) and could accurately predict (AUC > 0.85) T2DM development.

Interpretation

Our results reveal the existence of splicing machinery alterations that precede and predict T2DM development in patients with cardiovascular disease.

Fund

ISCIII, MINECO, CIBERObn.

When one becomes many-Alternative splicing in β-cell function and failure

Pancreatic β-cell dysfunction and death are determinant events in type 1 diabetes (T1D), but the molecular mechanisms behind β-cell fate remain poorly understood. Alternative splicing is a post-transcriptional mechanism by which a single gene generates different mRNA and protein isoforms, expanding the transcriptome complexity and enhancing protein diversity. Neuron-specific and certain serine/arginine-rich RNA binding proteins (RBP) are enriched in β-cells, playing crucial roles in the regulation of insulin secretion and β-cell survival. Moreover, alternative exon networks, regulated by inflammation or diabetes susceptibility genes, control key pathways and processes for the correct function and survival of β-cells. The challenge ahead of us is to understand the precise role of alternative splicing regulators and splice variants on β-cell function, dysfunction and death and develop tools to modulate it.

Immune Recognition of β-Cells: Neoepitopes as Key Players in the Loss of Tolerance

Prior to the onset of type 1 diabetes, there is progressive loss of immune self-tolerance, evidenced by the accumulation of islet autoantibodies and emergence of autoreactive T cells. Continued autoimmune activity leads to the destruction of pancreatic β-cells and loss of insulin secretion. Studies of samples from patients with type 1 diabetes and of murine disease models have generated important insights about genetic and environmental factors that contribute to susceptibility and immune pathways that are important for pathogenesis. However, important unanswered questions remain regarding the events that surround the initial loss of tolerance and subsequent failure of regulatory mechanisms to arrest autoimmunity and preserve functional β-cells. In this Perspective, we discuss various processes that lead to the generation of neoepitopes in pancreatic β-cells, their recognition by autoreactive T cells and antibodies, and potential roles for such responses in the pathology of disease. Emerging evidence supports the relevance of neoepitopes generated through processes that are mechanistically linked with β-cell stress. Together, these observations support a paradigm in which neoepitope generation leads to the activation of pathogenic immune cells that initiate a feed-forward loop that can amplify the antigenic repertoire toward pancreatic β-cell proteins.

Splicing in immune cells-mechanistic insights and emerging topics

Differential splicing of mRNAs not only enables regulation of gene expression levels, but also ensures a high degree of gene-product diversity. The extent to which splicing of mRNAs is utilized as a mechanism in immune cells has become evident within the last few years. Still, only a few of these mechanisms have been well studied. In this review, we discuss some of the best-understood mechanisms, for instance the differential splicing of CD45 in T cells, as well as immunoglobulin genes in B cells. Beyond that we provide general mechanistic insights on how, when and where this process takes place and discuss the current knowledge regarding these topics in immune cells. We also highlight some of the reported links to immune-related diseases, genome-wide sequencing studies that revealed thousands of differentially spliced transcripts, as well as splicing studies on immune cells that remain mechanistically not fully understood. We thereby display potential emerging topics for future studies centered on splicing mechanisms in immune cells.

DDX1 regulates alternative splicing and insulin secretion in pancreatic β cells

DEAD-box helicase 1 (DDX1) is a multifunction protein involved in diverse cellular processes including transcription, viral replication, mRNA/miRNA processing, and tRNA splicing. Here, we report a novel function of DDX1 in mRNA alternative splicing in pancreatic β cells. By performing integrated data analysis of high-throughput RNA sequencing (RNA-Seq), and cross-linking and immunoprecipitation coupled with deep sequencing (CLIP-Seq), we identify hundreds of alternative splicing genes that are targeted by DDX1. These DDX1-targeted alternative splicing genes are mainly associated with calcium ion binding, high voltage-gated calcium channel, and transmembrane transporter. Functionally, silencing DDX1 impairs calcium influx and insulin secretion in the pancreatic β cells. These results reveal an important role for DDX1 in the regulation of gene alternative splicing and insulin secretion in pancreatic β cells.

Opportunities and obstacles for deep learning in biology and medicine

Deep learning describes a class of machine learning algorithms that are capable of combining raw inputs into layers of intermediate features. These algorithms have recently shown impressive results across a variety of domains. Biology and medicine are data-rich disciplines, but the data are complex and often ill-understood. Hence, deep learning techniques may be particularly well suited to solve problems of these fields. We examine applications of deep learning to a variety of biomedical problems-patient classification, fundamental biological processes and treatment of patients-and discuss whether deep learning will be able to transform these tasks or if the biomedical sphere poses unique challenges. Following from an extensive literature review, we find that deep learning has yet to revolutionize biomedicine or definitively resolve any of the most pressing challenges in the field, but promising advances have been made on the prior state of the art. Even though improvements over previous baselines have been modest in general, the recent progress indicates that deep learning methods will provide valuable means for speeding up or aiding human investigation. Though progress has been made linking a specific neural network's prediction to input features, understanding how users should interpret these models to make testable hypotheses about the system under study remains an open challenge. Furthermore, the limited amount of labelled data for training presents problems in some domains, as do legal and privacy constraints on work with sensitive health records. Nonetheless, we foresee deep learning enabling changes at both bench and bedside with the potential to transform several areas of biology and medicine.

SRp55 Regulates a Splicing Network That Controls Human Pancreatic β-Cell Function and Survival

Progressive failure of insulin-producing β-cells is the central event leading to diabetes, but the signaling networks controlling β-cell fate remain poorly understood. Here we show that SRp55, a splicing factor regulated by the diabetes susceptibility gene GLIS3, has a major role in maintaining the function and survival of human β-cells. RNA sequencing analysis revealed that SRp55 regulates the splicing of genes involved in cell survival and death, insulin secretion, and c-Jun N-terminal kinase (JNK) signaling. In particular, SRp55-mediated splicing changes modulate the function of the proapoptotic proteins BIM and BAX, JNK signaling, and endoplasmic reticulum stress, explaining why SRp55 depletion triggers β-cell apoptosis. Furthermore, SRp55 depletion inhibits β-cell mitochondrial function, explaining the observed decrease in insulin release. These data unveil a novel layer of regulation of human β-cell function and survival, namely alternative splicing modulated by key splicing regulators such as SRp55, that may cross talk with candidate genes for diabetes.

Emerging roles of RNA-binding proteins in diabetes and their therapeutic potential in diabetic complications

Diabetes is a debilitating health care problem affecting 422 million people around the world. Diabetic patients suffer from multisystemic complications that can cause mortality and morbidity. Recent advancements in high-throughput next-generation RNA-sequencing and computational algorithms led to the discovery of aberrant posttranscriptional gene regulatory programs in diabetes. However, very little is known about how these regulatory programs are mis-regulated in diabetes. RNA-binding proteins (RBPs) are important regulators of posttranscriptional RNA networks, which are also dysregulated in diabetes. Human genetic studies provide new evidence that polymorphisms and mutations in RBPs are linked to diabetes. Therefore, we will discuss the emerging roles of RBPs in abnormal posttranscriptional gene expression in diabetes. Questions that will be addressed are: Which posttranscriptional mechanisms are disrupted in diabetes? Which RBPs are responsible for such changes under diabetic conditions? How are RBPs altered in diabetes? How does dysregulation of RBPs contribute to diabetes? Can we target RBPs using RNA-based methods to restore gene expression profiles in diabetic patients? Studying the evolving roles of RBPs in diabetes is critical not only for a comprehensive understanding of diabetes pathogenesis but also to design RNA-based therapeutic approaches for diabetic complications. WIREs RNA 2018, 9:e1459. doi: 10.1002/wrna.1459 This article is categorized under: RNA in Disease and Development > RNA in Disease RNA Processing > Splicing Regulation/Alternative Splicing Translation > Translation Regulation.

Disease-specific biases in alternative splicing and tissue-specific dysregulation revealed by multitissue profiling of lymphocyte gene expression in type 1 diabetes

Genome-wide association studies (GWAS) have identified multiple, shared allelic associations with many autoimmune diseases. However, the pathogenic contributions of variants residing in risk loci remain unresolved. The location of the majority of shared disease-associated variants in noncoding regions suggests they contribute to risk of autoimmunity through effects on gene expression in the immune system. In the current study, we test this hypothesis by applying RNA sequencing to CD4+, CD8+, and CD19+ lymphocyte populations isolated from 81 subjects with type 1 diabetes (T1D). We characterize and compare the expression patterns across these cell types for three gene sets: all genes, the set of genes implicated in autoimmune disease risk by GWAS, and the subset of these genes specifically implicated in T1D. We performed RNA sequencing and aligned the reads to both the human reference genome and a catalog of all possible splicing events developed from the genome, thereby providing a comprehensive evaluation of the roles of gene expression and alternative splicing (AS) in autoimmunity. Autoimmune candidate genes displayed greater expression specificity in the three lymphocyte populations relative to other genes, with significantly increased levels of splicing events, particularly those predicted to have substantial effects on protein isoform structure and function (e.g., intron retention, exon skipping). The majority of single-nucleotide polymorphisms within T1D-associated loci were also associated with one or more cis-expression quantitative trait loci (cis-eQTLs) and/or splicing eQTLs. Our findings highlight a substantial, and previously underrecognized, role for AS in the pathogenesis of autoimmune disorders and particularly for T1D.

Abnormalities in alternative splicing in diabetes: therapeutic targets

Diabetes mellitus (DM) is a non-communicable, metabolic disorder that affects 416 million individuals worldwide. Type 2 diabetes contributes to a vast 85-90% of the diabetes incidences while 10-15% of patients suffer from type 1 diabetes. These two predominant forms of DM cause a significant loss of functional pancreatic β-cell mass causing different degrees of insulin deficiency, most likely, due to increased β-cell apoptosis. Treatment options involve the use of insulin sensitisers, α-glucosidase inhibitors, and β-cell secretagogues which are often expensive, limited in efficacy and carry detrimental adverse effects. Cost-effective options for treatment exists in the form of herbal drugs, however, scientific validations of these widely used medicinal plants are still underway. Alternative splicing (AS) is a co-ordinated post-transcriptional process in which a single gene generates multiple mRNA transcripts which results in increased amounts of functionally different protein isoforms and in some cases aberrant splicing leads to metabolic disease. In this review, we explore the association of AS with metabolic alterations in DM and the biological significance of the abnormal splicing of some pathogenic diabetes-related genes. An understanding of the molecular mechanism behind abnormally spliced transcripts will aid in the development of new diagnostic, prognostic and therapeutic tools.

Molecular mechanisms of ROS production and oxidative stress in diabetes

Oxidative stress and chronic inflammation are known to be associated with the development of metabolic diseases, including diabetes. Oxidative stress, an imbalance between oxidative and antioxidative systems of cells and tissues, is a result of over production of oxidative-free radicals and associated reactive oxygen species (ROS). One outcome of excessive levels of ROS is the modification of the structure and function of cellular proteins and lipids, leading to cellular dysfunction including impaired energy metabolism, altered cell signalling and cell cycle control, impaired cell transport mechanisms and overall dysfunctional biological activity, immune activation and inflammation. Nutritional stress, such as that caused by excess high-fat and/or carbohydrate diets, promotes oxidative stress as evident by increased lipid peroxidation products, protein carbonylation and decreased antioxidant status. In obesity, chronic oxidative stress and associated inflammation are the underlying factors that lead to the development of pathologies such as insulin resistance, dysregulated pathways of metabolism, diabetes and cardiovascular disease through impaired signalling and metabolism resulting in dysfunction to insulin secretion, insulin action and immune responses. However, exercise may counter excessive levels of oxidative stress and thus improve metabolic and inflammatory outcomes. In the present article, we review the cellular and molecular origins and significance of ROS production, the molecular targets and responses describing how oxidative stress affects cell function including mechanisms of insulin secretion and action, from the point of view of possible application of novel diabetic therapies based on redox regulation.

The Characterization of GSDMB Splicing and Backsplicing Profiles Identifies Novel Isoforms and a Circular RNA That Are Dysregulated in Multiple Sclerosis

Abnormalities in alternative splicing (AS) are emerging as recurrent features in autoimmune diseases (AIDs). In particular, a growing body of evidence suggests the existence of a pathogenic association between a generalized defect in splicing regulatory genes and multiple sclerosis (MS). Moreover, several studies have documented an unbalance in alternatively-spliced isoforms in MS patients possibly contributing to the disease etiology. In this work, using a combination of PCR-based techniques (reverse-transcription (RT)-PCR, fluorescent-competitive, real-time, and digital RT-PCR assays), we investigated the alternatively-spliced gene encoding Gasdermin B, GSDMB, which was repeatedly associated with susceptibility to asthma and AIDs. The in-depth characterization of GSDMB AS and backsplicing profiles led us to the identification of an exonic circular RNA (ecircRNA) as well as of novel GSDMB in-frame and out-of-frame isoforms. The non-productive splicing variants were shown to be downregulated by the nonsense-mediated mRNA decay (NMD) in human cell lines, suggesting that GSDMB levels are significantly modulated by NMD. Importantly, both AS isoforms and the identified ecircRNA were significantly dysregulated in peripheral blood mononuclear cells of relapsing-remitting MS patients compared to controls, further supporting the notion that aberrant RNA metabolism is a characteristic feature of the disease.

Neuron-enriched RNA-binding Proteins Regulate Pancreatic Beta Cell Function and Survival

Pancreatic beta cell failure is the central event leading to diabetes. Beta cells share many phenotypic traits with neurons, and proper beta cell function relies on the activation of several neuron-like transcription programs. Regulation of gene expression by alternative splicing plays a pivotal role in brain, where it affects neuronal development, function, and disease. The role of alternative splicing in beta cells remains unclear, but recent data indicate that splicing alterations modulated by both inflammation and susceptibility genes for diabetes contribute to beta cell dysfunction and death. Here we used RNA sequencing to compare the expression of splicing-regulatory RNA-binding proteins in human islets, brain, and other human tissues, and we identified a cluster of splicing regulators that are expressed in both beta cells and brain. Four of them, namely Elavl4, Nova2, Rbox1, and Rbfox2, were selected for subsequent functional studies in insulin-producing rat INS-1E, human EndoC-βH1 cells, and in primary rat beta cells. Silencing of Elavl4 and Nova2 increased beta cell apoptosis, whereas silencing of Rbfox1 and Rbfox2 increased insulin content and secretion. Interestingly, Rbfox1 silencing modulates the splicing of the actin-remodeling protein gelsolin, increasing gelsolin expression and leading to faster glucose-induced actin depolymerization and increased insulin release. Taken together, these findings indicate that beta cells share common splicing regulators and programs with neurons. These splicing regulators play key roles in insulin release and beta cell survival, and their dysfunction may contribute to the loss of functional beta cell mass in diabetes.

Transcriptome sequencing of gingival biopsies from chronic periodontitis patients reveals novel gene expression and splicing patterns

BACKGROUND

Periodontitis is the most common chronic inflammatory disease caused by complex interaction between the microbial biofilm and host immune responses. In the present study, high-throughput RNA sequencing was utilized to systemically and precisely identify gene expression profiles and alternative splicing.

METHODS

The pooled RNAs of 10 gingival tissues from both healthy and periodontitis patients were analyzed by deep sequencing followed by computational annotation and quantification of mRNA structures.

RESULTS

The differential expression analysis designated 400 up-regulated genes in periodontitis tissues especially in the pathways of defense/immunity protein, receptor, protease, and signaling molecules. The top 10 most up-regulated genes were CSF3, MAFA, CR2, GLDC, SAA1, LBP, MME, MMP3, MME-AS1, and SAA4. The 62 down-regulated genes in periodontitis were mainly cytoskeletal and structural proteins. The top 10 most down-regulated genes were SERPINA12, MT4, H19, KRT2, DSC1, PSORS1C2, KRT27, LCE3C, AQ5, and LCE6A. The differential alternative splicing analysis revealed unique transcription variants in periodontitis tissues. The EDB exon was predominantly included in FN1, while exon 2 was mostly skipped in BCL2A1.

CONCLUSIONS

These findings using RNA sequencing provide novel insights into the pathogenesis mechanism of periodontitis in terms of gene expression and alternative splicing.

Neoantigens and Microenvironment in Type 1 Diabetes: Lessons from Antitumor Immunity

Type 1 diabetes (T1D) is characterized by the selective and progressive destruction of insulin-producing beta cells by the immune system. An incomplete thymic selection against self-reactive islet antigens partly explains how these T cells reach the periphery and become diabetogenic. Increasing evidence suggest that beta cells themselves also participate to their own demise by generating neoepitopes that could be recognized by the immune surveillance machinery. In this regard, these T cells eradicate self-tissue by mechanisms analogous to a classical antitumor response. Cancer immunotherapy has exploited mutations and transcriptional and translational errors to trigger a specific antitumor response. In this opinion article, we aim at merging insight in antitumor immunology and autoimmunity to reveal processes that had previously been ignored to create beta cell-specific neoantigens.