Biology subjects

Powers, A. C.

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

15 recordsLinked to original sources

bioRxiv2026

CyclicMPNN: Stable Cyclic Peptide Sequence Generation

AO_SCPLOWBSTRACTC_SCPLOWCyclic peptides are a promising class of therapeutics due to their attractive drug qualities such as increased structural stability, cell permeability, and resistance to proteolytic degradation. With recent advancements in cyclic peptide backbone generation models like CyclicCAE and RFPeptide, generating cyclic peptide backbones can be done more rapidly compared to traditional algorithm or physics based approaches. However, designing energetically favorable cyclic peptide sequences to fit generated backbones using only canonical amino acids is nontrivial. We fine-tuned the state-of-the-art deep learning model for protein sequence design, ProteinMPNN, using a combination of X-ray crystal structures from the Protein Data Bank and in silico generated cyclic peptides. Our approach surpasses ProteinMPNN in cyclic peptide sequence design, producing energetically stable sequences with a higher success rate of folding into the generated cyclic peptide backbones. We show that CyclicMPNN can be used as a motif-inpainting strategy and in de novo sequence design tasks. We propose that CyclicMPNN will enable the rapid design of energetically stable cyclic peptide sequences, increasing the success rate of therapeutic cyclic peptide development.

biochemistry↗

bioRxiv2025

Integrative Spatial Omics for Systems-Level Mapping of Pathological Niches

Spatial omics technologies are a powerful tool for mapping the relationship between cellular organization and molecular distributions in healthy and diseased tissue microenvironments. Here, we describe a novel multimodal pipeline that represents experimental and computational advances for spatiomolecular analysis of tissue samples across molecular classes. This adaptable method integrates matrix-assisted laser desorption/ionization imaging mass spectrometry spatial lipidomics, spatial transcriptomics, protein imaging via multiplexed immunofluorescence microscopy, and histopathological staining to uncover spatiomolecular profiles associated with unique cellular niches and pathological features. We demonstrate the power of this approach using two different complex human disease systems: Alzheimers disease in human brain tissue and type 2 diabetes mellitus in the human pancreas. This work establishes and demonstrates a generalizable framework for multimodal spatial integration, enabling precise mapping of molecular mechanisms that underlie complex tissue pathologies.

systems biology↗

bioRxiv2025

CyclicCAE: A Conformational Autoencoder for Efficient Heterochiral Macrocyclic Backbone Sampling

Peptide macrocycles are a promising therapeutic class. The inclusion of heterochiral and non-natural amino acids allows far more folds and functions to be accessed, but creates challenges for rational design -- particularly for sampling plausible mainchain conformations. We developed a conformational autoencoder called CyclicCAE to rapidly generate energetically favourable macrocycle scaffolds for heterochiral design and structure prediction. Given the absence of large, available macrocycle datasets, we created a custom dataset in silico using physics-based simulation methods. Trained on this, CyclicCAE produces energetically stable mainchain conformations and designable scaffolds more rapidly than the current state-of-the-art method, the Rosetta software suite's Generalized Kinematic Closure (GeneralizedKIC) method. We show that, despite being trained exclusively on synthetic data, CyclicCAE accurately captures the conformations accessible to peptide macrocycles found in the Protein Data Bank, with considerable speed advantages over GeneralizedKIC. We also demonstrate that CyclicCAE enables users to perform energy minimization in isolation or in a target-bound context, to generate structurally similar or diverse outputs by Markov Chain Monte Carlo sampling, and to conduct inpainting with fixed motifs. This method, which we release under a free and open source licence, will accelerate macrocycle design pipelines, speeding the development of peptide therapeutics.

bioengineering↗

bioRxiv2024

Mapping histological and functional maturation of human endocrine pancreas across early postnatal periods

Human endocrine cell differentiation and islet morphogenesis play critical roles in determining islet cell mass and function, but the events and timeline of these processes are incompletely defined. To better understand early human islet cell development and maturation, we collected 115 pediatric pancreata and mapped morphological and spatiotemporal changes from birth through the first ten years of life. Using quantitative analyses and a combination of complementary tissue imaging approaches, including confocal microscopy and whole-slide imaging, we developed an integrated model for endocrine cell formation and islet architecture, including endocrine cell type heterogeneity and abundance, endocrine cell proliferation, and islet vascularization and innervation. We also assessed insulin and glucagon secretory profiles in isolated islet preparations from pediatric donors aged 2 months to 10 years and found a temporal difference in the maturation of insulin secretion compared to glucagon secretion. This comprehensive summary of postnatal and pediatric pancreatic islet development provides a framework for future studies and integration of emerging genetic and genomic data related to islet biology and diabetes risk.

developmental biology↗

bioRxiv2024

Heterogeneous endocrine cell composition defines human islet functional phenotypes

Phenotyping and genotyping initiatives within the Integrated Islet Distribution Program (IIDP), the largest source of human islets for research in the U.S., provide standardized assessment of islet preparations distributed to researchers, enabling the integration of multiple data types. Data from islets of the first 299 organ donors without diabetes, analyzed using this pipeline, highlights substantial heterogeneity in islet cell composition associated with hormone secretory traits, sex, reported race and ethnicity, genetically predicted ancestry, and genetic risk for type 2 diabetes (T2D). While and {beta} cell composition influenced insulin and glucagon secretory traits, the abundance of {delta} cells showed the strongest association with insulin secretion and was also associated with the genetic risk score (GRS) for T2D. These findings have important implications for understanding mechanisms underlying diabetes heterogeneity and islet dysfunction and may provide insight into strategies for personalized medicine and {beta} cell replacement therapy.

physiology↗

bioRxiv2024

Interruption of glucagon signaling augments islet non-alpha cell proliferation in SLC7A2- and mTOR-dependent manners

ObjectiveDysregulated glucagon secretion and inadequate functional beta cell mass are hallmark features of diabetes. While glucagon receptor (GCGR) antagonism ameliorates hyperglycemia and elicits beta cell regeneration in pre-clinical models of diabetes, it also promotes alpha and delta cell hyperplasia. We sought to investigate the mechanism by which loss of glucagon action impacts pancreatic islet non-alpha cells, and the relevance of these observations in a human islet context. MethodsWe used zebrafish, rodents, and transplanted human islets comprising six different models of interrupted glucagon signaling to examine their impact on delta and beta cell proliferation and mass. We also used models with global deficiency of the cationic amino acid transporter, SLC7A2, and mTORC1 inhibition via rapamycin, to determine whether amino acid-dependent nutrient sensing was required for islet non-alpha cell growth. ResultsInhibition of glucagon signaling stimulated delta cell proliferation in mouse and transplanted human islets, and in mouse islets. This was rapamycin-sensitive and required SLC7A2. Likewise, gcgr deficiency augmented beta cell proliferation via SLC7A2- and mTORC1-dependent mechanisms in zebrafish and promoted cell cycle engagement in rodent beta cells but was insufficient to drive a significant increase in beta cell mass in mice. ConclusionOur findings demonstrate that interruption of glucagon signaling augments islet non-alpha cell proliferation in zebrafish, rodents, and transplanted human islets in a manner requiring SLC7A2 and mTORC1 activation. An increase in delta cell mass may be leveraged for future beta cell regeneration therapies relying upon delta cell reprogramming.

cell biology↗

bioRxiv2023

Pancreatic islet α cell function and proliferation requires the arginine transporter SLC7A2

Interrupting glucagon signaling decreases gluconeogenesis and the fractional extraction of amino acids by liver from blood resulting in lower glycemia. The resulting hyperaminoacidemia stimulates cell proliferation and glucagon secretion via a liver- cell axis. We hypothesized that cells detect and respond to circulating amino acids levels via a unique amino acid transporter repertoire. We found that Slc7a2ISLC7A2 is the most highly expressed cationic amino acid transporter in cells with its expression being three-fold greater in than {beta} cells in both mouse and human. Employing cell culture, zebrafish, and knockout mouse models, we found that the cationic amino acid arginine and SLC7A2 are required for cell proliferation in response to interrupted glucagon signaling. Ex vivo and in vivo assessment of islet function in Slc7a2-/- mice showed decreased arginine-stimulated glucagon and insulin secretion. We found that arginine activation of mTOR signaling and induction of the glutamine transporter SLC38A5 was dependent on SLC7A2, showing that boths role in cell proliferation is dependent on arginine transport and SLC7A2. Finally, we identified single nucleotide polymorphisms in SLC7A2 associated with HbA1c. Together, these data indicate a central role for SLC7A2 in amino acid-stimulated cell proliferation and islet hormone secretion.

physiology↗

bioRxiv2023

Redox Regulation of m6A Methyltransferase METTL3 in Human β-cells Controls the Innate Immune Response in Type 1 Diabetes

Type 1 Diabetes (T1D) is characterized by autoimmune-mediated destruction of insulin-producing {beta}-cells. Several observations have renewed interest in the innate immune system as an initiator of the disease process against {beta}-cells. Here, we show that N6-Methyladenosine (m6A) is an adaptive {beta}-cell safeguard mechanism that accelerates mRNA decay of the 2-5-oligoadenylate synthetase (OAS) genes to control the antiviral innate immune response at T1D onset. m6A writer methyltransferase 3 (METTL3) levels increase drastically in human and mouse {beta}-cells at T1D onset but rapidly decline with disease progression. Treatment of human islets and EndoC-{beta}H1 cells with pro-inflammatory cytokines interleukin-1 {beta} and interferon mimicked the METTL3 upregulation seen at T1D onset. Furthermore, m6A-sequencing revealed the m6A hypermethylation of several key innate immune mediators including OAS1, OAS2, and OAS3 in human islets and EndoC-{beta}H1 cells challenged with cytokines. METTL3 silencing in human pseudoislets or EndoC-{beta}H1 cells enhanced OAS levels by increasing its mRNA stability upon cytokine challenge. Consistently, in vivo gene therapy, to prolong Mettl3 overexpression specifically in {beta}-cells, delayed diabetes progression in the non-obese diabetic (NOD) mouse model of T1D by limiting the upregulation of Oas pointing to potential therapeutic relevance. Mechanistically, the accumulation of reactive oxygen species blocked METTL3 upregulation in response to cytokines, while physiological levels of nitric oxide promoted its expression in human islets. Furthermore, for the first time to our knowledge, we show that the cysteines in position C276 and C326 in the zinc finger domain of the METTL3 protein are sensitive to S-nitrosylation (SNO) and are significant for the METTL3 mediated regulation of OAS mRNA stability in human {beta}-cells in response to cytokines. Collectively, we report that m6A regulates human and mouse {beta}-cells to control the innate immune response during the onset of T1D and propose targeting METTL3 to prevent {beta}-cell death in T1D.

molecular biology↗

bioRxiv2023

AnnoSpat annotates cell types and quantifies cellular arrangements from spatial proteomics

Cellular composition and anatomical organization influence normal and aberrant organ functions. Emerging spatial single-cell proteomic assays such as Image Mass Cytometry (IMC) and Co-Detection by Indexing (CODEX) have facilitated the study of cellular composition and organization by enabling high-throughput measurement of cells and their localization directly in intact tissues. However, annotation of cell types and quantification of their relative localization in tissues remain challenging. To address these unmet needs, we developed AnnoSpat (Annotator and Spatial Pattern Finder) that uses neural network and point process algorithms to automatically identify cell types and quantify cell-cell proximity relationships. Our study of data from IMC and CODEX show the superior performance of AnnoSpat in rapid and accurate annotation of cell types compared to alternative approaches. Moreover, the application of AnnoSpat to type 1 diabetic, non-diabetic autoantibody-positive, and non-diabetic organ donor cohorts recapitulated known islet pathobiology and showed differential dynamics of pancreatic polypeptide (PP) cell abundance and CD8+ T cells infiltration in islets during type 1 diabetes progression.

bioinformatics↗

bioRxiv2022

Improving stem cell-derived pancreatic islets using single-cell multiome-inferred regulomes

Pancreatic islet cells derived from human pluripotent stem cells hold great promise for modeling and treating diabetes. Differences between stem cell-derived and primary islets remain, but molecular insights to inform improvements are limited. Here, we acquire single-cell transcriptomes and accessible chromatin profiles during in vitro islet differentiation and pancreas from childhood and adult donors for comparison. We delineate major cell types, define their regulomes, and describe spatiotemporal gene regulatory relationships between transcription factors. CDX2 emerged as a regulator of enterochromaffin-like cells, which we show resemble a transient, previously unrecognized, CDX2+ pre-{beta}-cell population in fetal pancreas, arguing against a proposed non-pancreatic origin. Furthermore, we observe insufficient activation of signal-dependent transcriptional programs during in vitro {beta}-cell maturation and identify sex hormones as drivers of {beta}-cell proliferation in childhood. Altogether, our analysis provides a comprehensive understanding of cell fate acquisition in stem cell-derived islets and a framework for manipulating cell identities and maturity.

cell biology↗

bioRxiv2021

RFX6-mediated dysregulation defines human β cell dysfunction in early type 2 diabetes

A hallmark of type 2 diabetes (T2D), a major cause of world-wide morbidity and mortality, is dysfunction of insulin-producing pancreatic islet {beta} cells1-3. T2D genome-wide association studies (GWAS) have identified hundreds of signals, mostly in the non-coding genome and overlapping {beta} cell regulatory elements, but translating these into biological mechanisms has been challenging4-6. To identify early disease-driving events, we performed single cell spatial proteomics, sorted cell transcriptomics, and assessed islet physiology on pancreatic tissue from short-duration T2D and control donors. Here, through integrative analyses of these diverse modalities, we show that multiple gene regulatory modules are associated with early-stage T2D {beta} cell-intrinsic defects. One notable example is the transcription factor RFX6, which we show is a highly connected {beta} cell hub gene that is reduced in T2D and governs a gene regulatory network associated with insulin secretion defects and T2D GWAS variants. We validated the critical role of RFX6 in {beta} cells through direct perturbation in primary human islets followed by physiological and single nucleus multiome profiling, which showed reduced dynamic insulin secretion and large-scale changes in the {beta} cell transcriptome and chromatin accessibility landscape. Understanding the molecular mechanisms of complex, systemic diseases necessitates integration of signals from multiple molecules, cells, organs, and individuals and thus we anticipate this approach will be a useful template to identify and validate key regulatory networks and master hub genes for other diseases or traits with GWAS data.

cell biology↗

bioRxiv2021

Combinatorial transcription factor profiles predict mature and functional human islet α and β cells

Islet-enriched transcription factors (TFs) exert broad control over cellular processes in pancreatic and {beta} cells and changes in their expression are associated with developmental state and diabetes. However, the implications of heterogeneity in TF expression across islet cell populations are not well understood. To define this TF heterogeneity and its consequences for cellular function, we profiled >40,000 cells from normal human islets by scRNA-seq and stratified and {beta} cells based on combinatorial TF expression. Subpopulations of islet cells co-expressing ARX/MAFB ( cells) and MAFA/MAFB ({beta} cells) exhibited greater expression of key genes related to glucose sensing and hormone secretion relative to subpopulations expressing only one or neither TF. Moreover, all subpopulations were identified in native pancreatic tissue from multiple donors. By Patch-seq, MAFA/MAFB co-expressing {beta} cells showed enhanced electrophysiological activity. Thus, these results indicate combinatorial TF expression in islet and {beta} cells predicts highly functional, mature subpopulations.

genomics↗

bioRxiv2020

SARS-CoV-2 Cell Entry Factors ACE2 and TMPRSS2 are Expressed in the Pancreas but Not in Islet Endocrine Cells

Summary/AbstractReports of new-onset diabetes and diabetic ketoacidosis in individuals with COVID-19 have led to the hypothesis that SARS-CoV-2, the virus that causes COVID-19, is directly cytotoxic to pancreatic islet {beta} cells. This would require binding and entry of SARS-CoV-2 into host {beta} cells via cell surface co-expression of ACE2 and TMPRSS2, the putative receptor and effector protease, respectively. To define ACE2 and TMPRSS2 expression in the human pancreas, we examined six transcriptional datasets from primary human islet cells and assessed protein expression by immunofluorescence in pancreata from donors with and without diabetes. ACE2 and TMPRSS2 transcripts were low or undetectable in pancreatic islet endocrine cells as determined by bulk or single cell RNA sequencing, and neither protein was detected in or {beta} cells from these donors. Instead, ACE2 protein was expressed in the islet and exocrine tissue microvasculature and also found in a subset of pancreatic ducts, whereas TMPRSS2 protein was restricted to ductal cells. The absence of significant ACE2 and TMPRSS2 co-expression in islet endocrine cells reduces the likelihood that SARS-CoV-2 directly infects pancreatic islet {beta} cells through these cell entry proteins.

cell biology↗

bioRxiv2020

Pancreatlas: a comprehensive and interactive image atlas of the human pancreas in health and disease

Human tissue phenotyping generates complex spatial information from numerous imaging modalities, yet images typically become static figures for publication and original data and metadata are rarely available. While comprehensive image maps exist for some organs, most resources have limited support for multiplexed imaging or have non-intuitive user interfaces. Therefore, we built a Pancreatlas resource that integrates several technologies into a novel interface, allowing users to access richly annotated web pages, drill down to individual images, and deeply explore data online. The current version of Pancreatlas contains over 800 unique images acquired by whole-slide scanning, confocal microscopy, and imaging mass cytometry, and is available at https://www.pancreatlas.org. To create this human pancreas-specific biological imaging resource, we developed a React-based web application and Python-based application programming interface, collectively called Flexible Framework for Integrating and Navigating Data (FFIND), which can be adapted beyond Pancreatlas to meet countless imaging or other structured data management needs.

cell biology↗

bioRxiv2019

Human pseudoislet system enables detection of differences in G-protein-coupled-receptor signaling pathways between α and β cells

G-protein-coupled-receptors (GPCRs) modulate insulin secretion from {beta} cells and glucagon secretion from cells. Here, we developed an integrated approach to study the function of primary human islet cells using genetically modified pseudoislets that resemble native islets across multiple parameters. We studied the Gi and Gq GPCR pathways by expressing the designer receptors exclusively activated by designer drugs (DREADDs) hM4Di or hM3Dq. Activation of Gi signaling reduced insulin and glucagon secretion, while activation of Gq signaling stimulated glucagon secretion but had both stimulatory and inhibitory effects on insulin secretion. Further, we developed a microperifusion system that allowed synchronous acquisition of GCaMP6f biosensor signal and hormone secretory profiles and showed that the dual effects for Gq signaling occur through changes in intracellular Ca2+. By combining pseudoislets with a microfluidic system, we co-registered intracellular signaling dynamics and hormone secretion and demonstrated differences in GPCR signaling pathways between human {beta} and cells.

cell biology↗