Proteome-scale tissue mapping using mass spectrometry based on label-free and multiplexed workflows.

Multiplexed bimolecular profiling of tissue microenvironment, or spatial omics, can provide deep insight into cellular compositions and interactions in both normal and diseased tissues. Proteome-scale tissue mapping, which aims to unbiasedly visualize all the proteins in whole tissue section or region of interest, has attracted significant interest because it holds great potential to directly reveal diagnostic biomarkers and therapeutic targets. While many approaches are available, however, proteome mapping still exhibits significant technical challenges in both protein coverage and analytical throughput. Since many of these existing challenges are associated with mass spectrometry-based protein identification and quantification, we performed a detailed benchmarking study of three protein quantification methods for spatial proteome mapping, including label-free, TMT-MS2, and TMT-MS3. Our study indicates label-free method provided the deepest coverages of ~3500 proteins at a spatial resolution of 50 µm and the largest quantification dynamic range, while TMT-MS2 method holds great benefit in mapping throughput at >125 pixels per day. The evaluation also indicates both label-free and TMT-MS2 provide robust protein quantifications in terms of identifying differentially abundant proteins and spatially co-variable clusters. In the study of pancreatic islet microenvironment, we demonstrated deep proteome mapping not only enables to identify protein markers specific to different cell types, but more importantly, it also reveals unknown or hidden protein patterns by spatial co-expression analysis.

DNA Methylation-Based Assessment of Cell Composition in Human Pancreas and Islets.

Assessment of pancreas cell type composition is crucial to the understanding of the genesis of diabetes. Current approaches use immunodetection of protein markers, for example, insulin as a marker of ß-cells. A major limitation of these methods is that protein content varies in physiological and pathological conditions, complicating the extrapolation to actual cell number. Here, we demonstrate the use of cell type-specific DNA methylation markers for determining the fraction of specific cell types in human islet and pancreas specimens. We identified genomic loci that are uniquely demethylated in specific pancreatic cell types and applied targeted PCR to assess the methylation status of these loci in tissue samples, enabling inference of cell type composition. In islet preparations, normalization of insulin secretion to ß-cell DNA revealed similar ß-cell function in pre-type 1 diabetes (T1D), T1D, and type 2 diabetes (T2D), which was significantly lower than in donors without diabetes. In histological pancreas specimens from recent-onset T1D, this assay showed ß-cell fraction within the normal range, suggesting a significant contribution of ß-cell dysfunction. In T2D pancreata, we observed increased α-cell fraction and normal ß-cell fraction. Methylation-based analysis provides an accurate molecular alternative to immune detection of cell types in the human pancreas, with utility in the interpretation of insulin secretion assays and the assessment of pancreas cell composition in health and disease.

Transcriptional Profile of Human Pancreatic Acinar Ductal Metaplasia.

BACKGROUND AND AIMS: Aberrant acinar to ductal metaplasia (ADM), one of the earliest events involved in exocrine pancreatic cancer development, is typically studied using pancreata from genetically engineered mouse models. METHODS: We used primary, human pancreatic acinar cells from organ donors to evaluate the transcriptional and pathway profiles during the course of ADM. RESULTS: Following 6 days of three-dimensional culture on Matrigel, acinar cells underwent morphological and molecular changes indicative of ADM. mRNA from 14 donors' paired cells (day 0, acinar phenotype and day 6, ductal phenotype) was subjected to whole transcriptome sequencing. Acinar cell specific genes were significantly downregulated in the samples from the day 6 cultures while ductal cell-specific genes were upregulated. Several regulons of ADM were identified including transcription factors with reduced activity (PTF1A, RBPJL, and BHLHA15) and those ductal and progenitor transcription factors with increased activity (HNF1B, SOX11, and SOX4). Cells with the ductal phenotype contained higher expression of genes increased in pancreatic cancer while cells with an acinar phenotype had lower expression of cancer-associated genes. CONCLUSION: Our findings support the relevancy of human in vitro models to study pancreas cancer pathogenesis and exocrine cell plasticity.

Proteome Mapping of the Human Pancreatic Islet Microenvironment Reveals Endocrine-Exocrine Signaling Sphere of Influence.

The need for a clinically accessible method with the ability to match protein activity within heterogeneous tissues is currently unmet by existing technologies. Our proteomics sample preparation platform, named microPOTS (Microdroplet Processing in One pot for Trace Samples), can be used to measure relative protein abundance in micron-scale samples alongside the spatial location of each measurement, thereby tying biologically interesting proteins and pathways to distinct regions. However, given the smaller pixel/voxel number and amount of tissue measured, standard mass spectrometric analysis pipelines have proven inadequate. Here we describe how existing computational approaches can be adapted to focus on the specific biological questions asked in spatial proteomics experiments. We apply this approach to present an unbiased characterization of the human islet microenvironment comprising the entire complex array of cell types involved while maintaining spatial information and the degree of the islet's sphere of influence. We identify specific functional activity unique to the pancreatic islet cells and demonstrate how far their signature can be detected in the adjacent tissue. Our results show that we can distinguish pancreatic islet cells from the neighboring exocrine tissue environment, recapitulate known biological functions of islet cells, and identify a spatial gradient in the expression of RNA processing proteins within the islet microenvironment.

Disease progression joint model predicts time to type 1 diabetes onset: Optimizing future type 1 diabetes prevention studies.

Clinical trials seeking type 1 diabetes prevention are challenging in terms of identifying patient populations likely to progress to type 1 diabetes within limited (i.e., short-term) trial durations. Hence, we sought to improve such efforts by developing a quantitative disease progression model for type 1 diabetes. Individual-level data obtained from the TrialNet Pathway to Prevention and The Environmental Determinants of Diabetes in the Young natural history studies were used to develop a joint model that links the longitudinal glycemic measure to the timing of type 1 diabetes diagnosis. Baseline covariates were assessed using a stepwise covariate modeling approach. Our study focused on individuals at risk of developing type 1 diabetes with the presence of two or more diabetes-related autoantibodies (AAbs). The developed model successfully quantified how patient features measured at baseline, including HbA1c and the presence of different AAbs, alter the timing of type 1 diabetes diagnosis with reasonable accuracy and precision (<30% RSE). In addition, selected covariates were statistically significant (p < 0.0001 Wald test). The Weibull model best captured the timing to type 1 diabetes diagnosis. The 2-h oral glucose tolerance values assessed at each visit were included as a time-varying biomarker, which was best quantified using the sigmoid maximum effect function. This model provides a framework to quantitatively predict and simulate the time to type 1 diabetes diagnosis in individuals at risk of developing the disease and thus, aligns with the needs of pharmaceutical companies and scientists seeking to advance therapies aimed at interdicting the disease process.

A genomic data archive from the Network for Pancreatic Organ donors with Diabetes.

The Network for Pancreatic Organ donors with Diabetes (nPOD) is the largest biorepository of human pancreata and associated immune organs from donors with type 1 diabetes (T1D), maturity-onset diabetes of the young (MODY), cystic fibrosis-related diabetes (CFRD), type 2 diabetes (T2D), gestational diabetes, islet autoantibody positivity (AAb+), and without diabetes. nPOD recovers, processes, analyzes, and distributes high-quality biospecimens, collected using optimized standard operating procedures, and associated de-identified data/metadata to researchers around the world. Herein describes the release of high-parameter genotyping data from this collection. 372 donors were genotyped using a custom precision medicine single nucleotide polymorphism (SNP) microarray. Data were technically validated using published algorithms to evaluate donor relatedness, ancestry, imputed HLA, and T1D genetic risk score. Additionally, 207 donors were assessed for rare known and novel coding region variants via whole exome sequencing (WES). These data are publicly-available to enable genotype-specific sample requests and the study of novel genotype:phenotype associations, aiding in the mission of nPOD to enhance understanding of diabetes pathogenesis to promote the development of novel therapies.

Integrated Physiology of the Exocrine and Endocrine Compartments in Pancreatic Diseases: Workshop Proceedings.

The Integrated Physiology of the Exocrine and Endocrine Compartments in Pancreatic Diseases workshop was a 1.5-day scientific conference at the National Institutes of Health (Bethesda, MD) that engaged clinical and basic science investigators interested in diseases of the pancreas. This report provides a summary of the proceedings from the workshop. The goals of the workshop were to forge connections and identify gaps in knowledge that could guide future research directions. Presentations were segregated into six major theme areas, including 1) pancreas anatomy and physiology, 2) diabetes in the setting of exocrine disease, 3) metabolic influences on the exocrine pancreas, 4) genetic drivers of pancreatic diseases, 5) tools for integrated pancreatic analysis, and 6) implications of exocrine-endocrine cross talk. For each theme, multiple presentations were followed by panel discussions on specific topics relevant to each area of research; these are summarized here. Significantly, the discussions resulted in the identification of research gaps and opportunities for the field to address. In general, it was concluded that as a pancreas research community, we must more thoughtfully integrate our current knowledge of normal physiology as well as the disease mechanisms that underlie endocrine and exocrine disorders so that there is a better understanding of the interplay between these compartments.

Design and Rationale for the Use of Magnetic Resonance Imaging Biomarkers to Predict Diabetes After Acute Pancreatitis in the Diabetes RElated to Acute Pancreatitis and Its Mechanisms Study: From the Type 1 Diabetes in Acute Pancreatitis Consortium.

ABSTRACT: This core component of the Diabetes RElated to Acute pancreatitis and its Mechanisms (DREAM) study will examine the hypothesis that advanced magnetic resonance imaging (MRI) techniques can reflect underlying pathophysiologic changes and provide imaging biomarkers that predict diabetes mellitus (DM) after acute pancreatitis (AP). A subset of participants in the DREAM study will enroll and undergo serial MRI examinations using a specific research protocol. The aim of the study is to differentiate at-risk individuals from those who remain euglycemic by identifying parenchymal features after AP. Performing longitudinal MRI will enable us to observe and understand the natural history of post-AP DM. We will compare MRI parameters obtained by interrogating tissue properties in euglycemic, prediabetic, and incident diabetes subjects and correlate them with metabolic, genetic, and immunological phenotypes. Differentiating imaging parameters will be combined to develop a quantitative composite risk score. This composite risk score will potentially have the ability to monitor the risk of DM in clinical practice or trials. We will use artificial intelligence, specifically deep learning, algorithms to optimize the predictive ability of MRI. In addition to the research MRI, the DREAM study will also correlate clinical computed tomography and MRI scans with DM development.

Standard Operating Procedures for Biospecimen Collection, Processing, and Storage: From the Type 1 Diabetes in Acute Pancreatitis Consortium.

ABSTRACT: Differences in methods for biospecimen collection, processing, and storage can yield considerable variability and error. Therefore, best practices for standard operating procedures are critical for successful discovery, development, and validation of disease biomarkers. Here, we describe standard operating procedures developed for biospecimen collection during the DREAM (Diabetes RElated to Acute pancreatitis and its Mechanisms) Study within the Type 1 Diabetes in Acute Pancreatitis Consortium. Notably, these protocols were developed using an integrative process based on prior consortium experience and with input from working groups with expertise in immunology, pancreatitis, and diabetes. Publication and adoption consistent biospecimen protocols will inform future studies and allow for better comparisons across different metabolic research efforts.

Pharmacological inhibition and reversal of pancreatic acinar ductal metaplasia.

Pancreatic acinar cells display a remarkable degree of plasticity and can dedifferentiate into ductal-like progenitor cells by a process known as acinar ductal metaplasia (ADM). ADM is believed to be one of the earliest precursor lesions toward the development of pancreatic ductal adenocarcinoma and maintaining the pancreatic acinar cell phenotype suppresses tumor formation. The effects of a novel pStat3 inhibitor (LLL12B) and the histone deacetylase (HDAC) inhibitor trichostatin A (TSA) were investigated using 3-D cultures from p48Cre/+ and p48Cre/+LSL-KrasG12D/+ (KC) mice. LLL12B and TSA inhibited ADM in both KC and p48Cre/+ mouse pancreatic organoids. Furthermore, treatment with LLL12B or TSA on dedifferentiated acini from p48Cre/+ and KC mice that had undergone ADM produced morphologic and gene expression changes that suggest a reversal of ADM. Validation experiments using qRT-PCR (p48Cre/+ and KC) and RNA sequencing (KC) of the LLL12B and TSA treated cultures showed that the ADM reversal was more robust for the TSA treatments. Pathway analysis showed that TSA inhibited Spink1 and PI3K/AKT signaling during ADM reversal. The ability of TSA to reverse ADM was also observed in primary human acinar cultures. We report that pStat3 and HDAC inhibition can attenuate ADM in vitro and reverse ADM in the context of wild-type Kras. Our findings suggest that pharmacological inhibition or reversal of pancreatic ADM represents a potential therapeutic strategy for blocking aberrant ductal reprogramming of acinar cells.

Integrated Physiology of the Exocrine and Endocrine Compartments in Pancreatic Diseases: Workshop Proceedings.

ABSTRACT: The "Integrated Physiology of the Exocrine and Endocrine Compartments in Pancreatic Diseases" Workshop was a 1.5-day scientific conference at the National Institutes of Health (Bethesda, MD) that engaged clinical and basic science investigators interested in diseases of the pancreas. This report summarizes the workshop proceedings. The goal of the workshop was to forge connections and identify gaps in knowledge that could guide future research directions. Presentations were segregated into 6 major themes, including (a) Pancreas Anatomy and Physiology; (b) Diabetes in the Setting of Exocrine Disease; (c) Metabolic Influences on the Exocrine Pancreas; (d) Genetic Drivers of Pancreatic Diseases; (e) Tools for Integrated Pancreatic Analysis; and (f) Implications of Exocrine-Endocrine Crosstalk. For each theme, there were multiple presentations followed by panel discussions on specific topics relevant to each area of research; these are summarized herein. Significantly, the discussions resulted in the identification of research gaps and opportunities for the field to address. In general, it was concluded that as a pancreas research community, we must more thoughtfully integrate our current knowledge of the normal physiology as well as the disease mechanisms that underlie endocrine and exocrine disorders so that there is a better understanding of the interplay between these compartments.

Substance Use Affects Type 1 Diabetes Pancreas Pathology: Implications for Future Studies.

Access to human pancreas samples from organ donors has greatly advanced our understanding of type 1 diabetes pathogenesis; however, previous studies have shown that donors have a high rate of substance use, and its impact on pancreatic histopathology in this disease is not well described. One-hundred-thirty-one type 1 diabetes and 111 control organ donor pancreata from persons 12-89 years of age (mean 29.8 ± 15.5 years) within the Network for Pancreatic Organ donors with Diabetes (nPOD) were examined for insulin positivity, insulitis, amyloid staining, acute and chronic pancreatitis, and chronic exocrine changes (acinar atrophy, fibrosis, fatty infiltration, or periductal fibrosis); findings were compared by history of substance use. A secondary analysis compared exocrine pancreatic histopathologic findings in type 1 diabetes versus control organ donors regardless of substance use history. We observed a high but congruent rate of substance use in type 1 diabetes and control organ donors (66.4% and 64% respectively). Among donors with type 1 diabetes (but not controls), islet amyloid (OR 9.96 [1.22, 81.29]) and acute pancreatitis (OR 3.2 [1.06, 9.63]) were more common in alcohol users while chronic exocrine changes (OR 8.86 [1.13, 69.31]) were more common in cocaine users. Substance use impacted the pancreata of donors with type 1 diabetes more than controls. Overall, despite similar rates of substance use, acute pancreatitis (15.3% versus 4.5%, p=0.0061), chronic pancreatitis (29.8% versus 9.9%, p=0.0001), and chronic exocrine changes (73.3% versus 36.9%, p<0.0001) were more common in type 1 diabetes donors than controls. Alcohol and/or cocaine use in type 1 diabetes organ donors increases exocrine pancreas pathology and islet amyloid deposition but does not affect insulitis or insulin positivity. Exocrine pathology in type 1 diabetes donors is common, and further study of the pathophysiology of these changes is needed.

What is a ß cell? - Chapter I in the Human Islet Research Network (HIRN) review series.

BACKGROUND: The pancreatic ß cell, as the sole source of the vital hormone insulin, has been under intensive study for more than a century. Given the potential of newly created insulin-producing cells as a treatment or even cure of type 1 diabetes (T1D) and possibly in severe cases of type 2 diabetes (T2D), multiple academic and commercial laboratories are working to derive surrogate glucose-responsive, insulin-producing cells. SCOPE OF REVIEW: The recent development of advanced phenotyping technologies, including molecular, epigenomic, histological, or functional, have greatly improved our understanding of the critical properties of human ß cells. Using this information, here we summarize the salient features of normal, fully functional adult human ß cells, and propose minimal criteria for what should rightfully be termed 'ß cells' as opposed to insulin-producing but not fully-functional surrogates that we propose should be referred to as 'ß-like' cells or insulin-producing cells. MAJOR CONCLUSIONS: Clear criteria can be established to differentiate fully functional, mature ß cells from 'ß-like' surrogates. In addition, we outline important knowledge gaps that must be addressed to enable a greater understanding of the ß cell.

Pancreas Optical Clearing and 3-D Microscopy in Health and Diabetes.

Although first described over a hundred years ago, tissue optical clearing is undergoing renewed interest due to numerous advances in optical clearing methods, microscopy systems, and three-dimensional (3-D) image analysis programs. These advances are advantageous for intact mouse tissues or pieces of human tissues because samples sized several millimeters can be studied. Optical clearing methods are particularly useful for studies of the neuroanatomy of the central and peripheral nervous systems and tissue vasculature or lymphatic system. Using examples from solvent- and aqueous-based optical clearing methods, the mouse and human pancreatic structures and networks will be reviewed in 3-D for neuro-insular complexes, parasympathetic ganglia, and adipocyte infiltration as well as lymphatics in diabetes. Optical clearing with multiplex immunofluorescence microscopy provides new opportunities to examine the role of the nervous and circulatory systems in pancreatic and islet functions by defining their neurovascular anatomy in health and diabetes.

Islet sympathetic innervation and islet neuropathology in patients with type 1 diabetes.

Dysregulation of glucagon secretion in type 1 diabetes (T1D) involves hypersecretion during postprandial states, but insufficient secretion during hypoglycemia. The sympathetic nervous system regulates glucagon secretion. To investigate islet sympathetic innervation in T1D, sympathetic tyrosine hydroxylase (TH) axons were analyzed in control non-diabetic organ donors, non-diabetic islet autoantibody-positive individuals (AAb), and age-matched persons with T1D. Islet TH axon numbers and density were significantly decreased in AAb compared to T1D with no significant differences observed in exocrine TH axon volume or lengths between groups. TH axons were in close approximation to islet α-cells in T1D individuals with long-standing diabetes. Islet RNA-sequencing and qRT-PCR analyses identified significant alterations in noradrenalin degradation, α-adrenergic signaling, cardiac ß-adrenergic signaling, catecholamine biosynthesis, and additional neuropathology pathways. The close approximation of TH axons at islet α-cells supports a model for sympathetic efferent neurons directly regulating glucagon secretion. Sympathetic islet innervation and intrinsic adrenergic signaling pathways could be novel targets for improving glucagon secretion in T1D.

Exocrine Pancreatic Enzymes Are a Serological Biomarker for Type 1 Diabetes Staging and Pancreas Size.

Exocrine pancreas abnormalities are increasingly recognized as features of type 1 diabetes. We previously reported reduced serum trypsinogen levels and in a separate study, smaller pancreata at and before disease onset. We hypothesized that three pancreas enzymes (amylase, lipase, and trypsinogen) might serve as serological biomarkers of pancreas volume and risk for type 1 diabetes. Amylase, lipase, and trypsinogen were measured from two independent cohorts, together comprising 800 serum samples from single-autoantibody-positive (1AAb+) and multiple-AAb+ (≥2AAb+) subjects, individuals with recent-onset or established type 1 diabetes, their AAb-negative (AAb-) first-degree relatives, and AAb- control subjects. Lipase and trypsinogen were significantly reduced in ≥2AAb+, recent-onset, and established type 1 diabetes subjects versus control subjects and 1AAb+, while amylase was reduced only in established type 1 diabetes. Logistic regression models demonstrated trypsinogen plus lipase (area under the receiver operating characteristic curve [AUROC] = 81.4%) performed equivalently to all three enzymes (AUROC = 81.4%) in categorizing ≥2AAb+ versus 1AAb+ subjects. For cohort 2 (n = 246), linear regression demonstrated lipase and trypsinogen levels could individually and collectively serve as indicators of BMI-normalized relative pancreas volume (RPVBMI, P < 0.001), previously measured by MRI. Serum lipase and trypsinogen levels together provide the most sensitive serological biomarker of RPVBMI and may improve disease staging in pretype 1 diabetes.

Image-Based Machine Learning Algorithms for Disease Characterization in the Human Type 1 Diabetes Pancreas.

Emerging data suggest that type 1 diabetes affects not only the ß-cell-containing islets of Langerhans, but also the surrounding exocrine compartment. Using digital pathology, machine learning algorithms were applied to high-resolution, whole-slide images of human pancreata to determine whether the tissue composition in individuals with or at risk for type 1 diabetes differs from those without diabetes. Transplant-grade pancreata from organ donors were evaluated from 16 nondiabetic autoantibody-negative controls, 8 nondiabetic autoantibody-positive subjects with increased type 1 diabetes risk, and 19 persons with type 1 diabetes (0 to 12 years' duration). HALO image analysis algorithms were implemented to compare architecture of the main pancreatic duct as well as cell size, density, and area of acinar, endocrine, ductal, and other nonendocrine, nonexocrine tissues. Type 1 diabetes was found to affect exocrine area, acinar cell density, and size, whereas the type of difference correlated with the presence or absence of insulin-positive cells remaining in the pancreas. These changes were not observed before disease onset, as indicated by modeling cross-sectional data from pancreata of autoantibody-positive subjects and those diagnosed with type 1 diabetes. These data provide novel insights into anatomic differences in type 1 diabetes pancreata and demonstrate that machine learning can be adapted for the evaluation of disease processes from cross-sectional data sets.

Expression of SARS-CoV-2 Entry Factors in the Pancreas of Normal Organ Donors and Individuals with COVID-19.

Diabetes is associated with increased mortality from severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). Given literature suggesting a potential association between SARS-CoV-2 infection and diabetes induction, we examined pancreatic expression of angiotensin-converting enzyme 2 (ACE2), the key entry factor for SARS-CoV-2 infection. Specifically, we analyzed five public scRNA-seq pancreas datasets and performed fluorescence in situ hybridization, western blotting, and immunolocalization for ACE2 with extensive reagent validation on normal human pancreatic tissues across the lifespan, as well as those from coronavirus disease 2019 (COVID-19) cases. These in silico and ex vivo analyses demonstrated prominent expression of ACE2 in pancreatic ductal epithelium and microvasculature, but we found rare endocrine cell expression at the mRNA level. Pancreata from individuals with COVID-19 demonstrated multiple thrombotic lesions with SARS-CoV-2 nucleocapsid protein expression that was primarily limited to ducts. These results suggest SARS-CoV-2 infection of pancreatic endocrine cells, via ACE2, is an unlikely central pathogenic feature of COVID-19-related diabetes.

Designing a bioelectronic treatment for Type 1 diabetes: targeted parasympathetic modulation of insulin secretion.

The pancreas is a visceral organ with exocrine functions for digestion and endocrine functions for maintenance of blood glucose homeostasis. In pancreatic diseases such as Type 1 diabetes, islets of the endocrine pancreas become dysfunctional and normal regulation of blood glucose concentration ceases. In healthy individuals, parasympathetic signaling to islets via the vagus nerve, triggers release of insulin from pancreatic ß-cells and glucagon from α-cells. Using electrical stimulation to augment parasympathetic signaling may provide a way to control pancreatic endocrine functions and ultimately control blood glucose. Historical data suggest that cervical vagus nerve stimulation recruits many visceral organ systems. Simultaneous modulation of liver and digestive function along with pancreatic function provides differential signals that work to both raise and lower blood glucose. Targeted pancreatic vagus nerve stimulation may provide a solution to minimizing off-target effects through careful electrode placement just prior to pancreatic insertion.