Biology subjects

Brusko, M. A.

Publications and source records attributed to Brusko, M. A..

5 recordsLinked to original sources

bioRxiv2024

Impaired islet function with normal exocrine enzyme secretion is consistent across the head, body, and tail pancreas regions in type 1 diabetes

Histopathological heterogeneity in human pancreas has been well documented; however, functional evidence at the tissue level is scarce. Herein we investigated in situ glucose-stimulated islet and carbachol-stimulated acinar cell secretion across the pancreas head (PH), body (PB), and tail (PT) regions in no diabetes (ND, n=15), single islet autoantibody-positive (1AAb+, n=7), and type 1 diabetes donors (T1D, <14 months duration, n=5). Insulin, glucagon, pancreatic amylase, lipase, and trypsinogen secretion along with 3D tissue morphometrical features were comparable across the regions in ND. In T1D, insulin secretion and beta-cell volume were significantly reduced within all regions, while glucagon and enzymes were unaltered. Beta-cell volume was lower despite normal insulin secretion in 1AAb+, resulting in increased volume-adjusted insulin secretion versus ND. Islet and acinar cell secretion in 1AAb+ were consistent across PH, PB and PT. This study supports low inter-regional variation in pancreas slice function and potentially, increased metabolic demand in 1AAb+.

pathology↗

bioRxiv2023

Data-driven selection of analysis decisions in single-cell RNA-seq trajectory inference

Single-cell RNA sequencing (scRNA-seq) experiments have become instrumental in developmental and differentiation studies, enabling the profiling of cells at a single or multiple time-points to uncover subtle variations in expression profiles reflecting underlying biological processes. Benchmarking studies have compared many of the computational methods used to reconstruct cellular dynamics, however researchers still encounter challenges in their analysis due to uncertainties in selecting the most appropriate methods and parameters. Even among universal data processing steps used by trajectory inference methods such as feature selection and dimension reduction, trajectory methods performances are highly dataset-specific. To address these challenges, we developed Escort, a framework for evaluating a datasets suitability for trajectory inference and quantifying trajectory properties influenced by analysis decisions. Escort navigates single-cell trajectory analysis through data-driven assessments, reducing uncertainty and much of the decision burden associated with trajectory inference. Escort is implemented in an accessible R package and R/Shiny application, providing researchers with the necessary tools to make informed decisions during trajectory analysis and enabling new insights into dynamic biological processes at single-cell resolution.

bioinformatics↗

bioRxiv2023

Characterizing cell-type spatial relationships across length scales in spatially resolved omics data

Spatially resolved omics (SRO) technologies enable the identification of cell types while preserving their organization within tissues. Application of such technologies offers the opportunity to delineate cell-type spatial relationships, particularly across different length scales, and enhance our understanding of tissue organization and function. To quantify such multi-scale cell-type spatial relationships, we developed CRAWDAD, Cell-type Relationship Analysis Workflow Done Across Distances, as an open-source R package with source code and additional documentation at https://jef.works/CRAWDAD/. To demonstrate the utility of such multi-scale characterization, recapitulate expected cell-type spatial relationships, and evaluate against other cell-type spatial analyses, we applied CRAWDAD to various simulated and real SRO datasets of diverse tissues assayed by diverse SRO technologies. We further demonstrate how such multi-scale characterization enabled by CRAWDAD can be used to compare cell-type spatial relationships across multiple samples. Finally, we applied CRAWDAD to SRO datasets of the human spleen to identify consistent as well as patient and sample-specific cell-type spatial relationships. In general, we anticipate such multi-scale analysis of SRO data enabled by CRAWDAD will provide useful quantitative metrics to facilitate the identification, characterization, and comparison of cell-type spatial relationships across axes of interest.

bioinformatics↗

bioRxiv2023

Human immune phenotyping reveals accelerated aging in type 1 diabetes

The composition of immune cells in peripheral blood is dramatically remodeled throughout the human lifespan, as environmental exposures shape the proportion and phenotype of cellular subsets. These dynamic shifts complicate efforts to identify disease-associated immune signatures in type 1 diabetes (T1D), which is variable in age of onset and rate of {beta}-cell decline. Herein, we conducted standardized flow cytometric immune profiling on peripheral blood from a cross-sectional cohort of T1D participants (n=240), their first-degree relatives (REL, n=310), those at increased risk with two or more islet autoantibodies (RSK, n=24), and autoantibody negative healthy controls (CTR, n=252). We constructed an immune-age predictive model in healthy subjects and developed an interactive data visualization portal (ImmScape; https://ufdiabetes.shinyapps.io/ImmScape/). When applied to the T1D cohort, this model revealed accelerated immune aging (p<0.001) as well as phenotypic signatures of disease after age correction. Of 192 investigated flow cytometry and complete blood count readouts, 46 were significantly associated with age only, 25 with T1D only, and 23 with both age and T1D. Phenotypes associated with T1D after age-correction were predictive of T1D status (AUROC=82.3%). Phenotypes associated with accelerated aging in T1D included increased CXCR3+ and PD-1+ frequencies in naive and memory T cell subsets, despite reduced PD-1 expression levels (mean fluorescence intensity) on memory T cells. Additionally, quantitative trait locus analysis linked an increase in HLA-DR expression on monocytes with the T1D-associated HLA-DR4/DQ8 genotype, regardless of clinical group. Our findings demonstrate advanced immune aging in T1D and highlight disease-associated phenotypes for biomarker monitoring and therapeutic interventions. One Sentence SummaryPeripheral blood characterization reveals accelerated immune-age and age-adjusted proinflammatory immune phenotypes in type 1 diabetes.

immunology↗

bioRxiv2021

Galectin-anchored indoleamine 2,3-dioxygenase suppresses local inflammation

Summary paragraphChronic inflammation underlies the onset, progression and associated pain of numerous diseases.(1) Current anti-inflammatory treatments administered systemically are associated with moderate-to-severe side effects, while locally administered drugs have short-lived efficacy, and neither approach successfully modifies the underlying causality of disease.(2) We report a new way to locally modulate inflammation by fusing the enzyme indoleamine 2,3-dioxygenase 1 (IDO) to galectin-3 (Gal3). A general regulator of inflammation(3), IDO is immunosuppressive(4), catabolizing the essential amino acid tryptophan into kynurenine.(5) Recently we demonstrated that extracellular exogenous IDO regulates innate immune cell function(6), and envisioned delivering IDO into specific tissues would provide control of inflammation. However, proteins problematically diffuse away from local injection sites. Addressing this, we recently established that fusion to Gal3 anchors enzymes to tissues(7) via binding to extracellular glycans. Fusion protein IDO-Gal3 was retained in injected tissues and joints for up to a week or more, where it suppressed local inflammation in rodent models of endotoxin-induced inflammation, psoriasis, periodontal disease and osteoarthritis. Amelioration of local inflammation, disease progression and inflammatory pain were concomitant with homeostatic preservation of tissues without global immune suppression. Thus, IDO-Gal3 presents a new concept of anchoring immunomodulatory enzymes for robust control of focal inflammation in multiple disease settings.

bioengineering↗