Induction of bronchus-associated lymphoid tissue is an early life adaptation for promoting human B cell immunity.

Infants and young children are more susceptible to common respiratory pathogens than adults but can fare better against novel pathogens like severe acute respiratory syndrome coronavirus 2. The mechanisms by which infants and young children mount effective immune responses to respiratory pathogens are unknown. Through investigation of lungs and lung-associated lymph nodes from infant and pediatric organ donors aged 0-13 years, we show that bronchus-associated lymphoid tissue (BALT), containing B cell follicles, CD4+ T cells and functionally active germinal centers, develop during infancy. BALT structures are prevalent around lung airways during the first 3 years of life, and their numbers decline through childhood coincident with the accumulation of memory T cells. Single-cell profiling and repertoire analysis reveals that early life lung B cells undergo differentiation, somatic hypermutation and immunoglobulin class switching and exhibit a more activated profile than lymph node B cells. Moreover, B cells in the lung and lung-associated lymph nodes generate biased antibody responses to multiple respiratory pathogens compared to circulating antibodies, which are mostly specific for vaccine antigens in the early years of life. Together, our findings provide evidence for BALT as an early life adaptation for mobilizing localized immune protection to the diverse respiratory challenges during this formative life stage.

Site-specific development and progressive maturation of human tissue-resident memory T cells over infancy and childhood.

Infancy and childhood are critical life stages for generating immune memory to protect against pathogens; however, the timing, location, and pathways for memory development in humans remain elusive. Here, we investigated T cells in mucosal sites, lymphoid tissues, and blood from 96 pediatric donors aged 0-10 years using phenotypic, functional, and transcriptomic profiling. Our results revealed that memory T cells preferentially localized in the intestines and lungs during infancy and accumulated more rapidly in mucosal sites compared with blood and lymphoid organs, consistent with site-specific antigen exposure. Early life mucosal memory T cells exhibit distinct functional capacities and stem-like transcriptional profiles. In later childhood, they progressively adopt proinflammatory functions and tissue-resident signatures, coincident with increased T cell receptor (TCR) clonal expansion in mucosal and lymphoid sites. Together, our findings identify staged development of memory T cells targeted to tissues during the formative years, informing how we might promote and monitor immunity in children.

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 uncertainty with respect to 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 novel framework for evaluating a dataset's suitability for trajectory inference and quantifying trajectory properties influenced by analysis decisions. Escort evaluates the suitability of trajectory analysis and the combined effects of processing choices using trajectory-specific metrics. Escort navigates single-cell trajectory analysis through these data-driven assessments, reducing uncertainty and much of the decision burden inherent to trajectory inference analyses. 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.

Innate inflammation drives NK cell activation to impair Treg activity.

IL-12 and IL-18 synergize to promote TH1 responses and have been implicated as accelerators of autoimmune pathogenesis in type 1 diabetes (T1D). We investigated the influence of these cytokines on immune cells involved in human T1D progression: natural killer (NK) cells, regulatory T cells (Tregs), and cytotoxic T lymphocytes (CTL). NK cells from T1D patients exhibited higher surface CD226 versus controls and lower CD25 compared to first-degree relatives and controls. Changes in NK cell phenotype towards terminal differentiation were associated with cytomegalovirus (CMV) seropositivity, while possession of IL18RAP, IFIH1, and IL2RA T1D-risk variants impacted NK cell activation as evaluated by immuno-expression quantitative trait loci (eQTL) analyses. IL-12 and IL-18 stimulated NK cells from healthy donors exhibited enhanced specific killing of myelogenous K562 target cells. Moreover, activated NK cells increased expression of NKG2A, NKG2D, CD226, TIGIT and CD25, which enabled competition for IL-2 upon co-culture with Tregs, resulting in Treg downregulation of FOXP3, production of IFNγ, and loss of suppressive function. We generated islet-autoreactive CTL "avatars", which upon exposure to IL-12 and IL-18, upregulated IFNγ and Granzyme-B leading to increased lymphocytotoxicity of a human ß-cell line in vitro. These results support a model for T1D pathogenesis wherein IL-12 and IL-18 synergistically enhance CTL and NK cell cytotoxic activity and disrupt immunoregulation by Tregs.

A global view of T cell metabolism in systemic lupus erythematosus.

Impaired metabolism is recognized as an important contributor to pathogenicity of T cells in Systemic Lupus Erythematosus (SLE). Over the last two decades, we have acquired significant knowledge about the signaling and transcriptomic programs related to metabolic rewiring in healthy and SLE T cells. However, our understanding of metabolic network activity derives largely from studying metabolic pathways in isolation. Here, we argue that enzymatic activities are necessarily coupled through mass and energy balance constraints with in-built network-wide dependencies and compensation mechanisms. Therefore, metabolic rewiring of T cells in SLE must be understood in the context of the entire network, including changes in metabolic demands such as shifts in biomass composition and cytokine secretion rates as well as changes in uptake/excretion rates of multiple nutrients and waste products. As a way forward, we suggest cell physiology experiments and integration of orthogonal metabolic measurements through computational modeling towards a comprehensive understanding of T cell metabolism in lupus.

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.

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+.

Impaired islet function and normal exocrine enzyme secretion occur with low inter-regional variation in type 1 diabetes.

Histopathological heterogeneity in the human pancreas is well documented; however, functional evidence at the tissue level is scarce. Herein, we investigate in situ glucose-stimulated islet and carbachol-stimulated acinar cell secretion across the pancreas head (PH), body (PB), and tail (PT) regions in donors without diabetes (ND; n = 15), positive for one islet autoantibody (1AAb+; n = 7), and with type 1 diabetes (T1D; <14 months duration, n = 5). Insulin, glucagon, pancreatic amylase, lipase, and trypsinogen secretion along with 3D tissue morphometrical features are comparable across regions in ND. In T1D, insulin secretion and beta-cell volume are significantly reduced within all regions, while glucagon and enzymes are unaltered. Beta-cell volume is lower despite normal insulin secretion in 1AAb+, resulting in increased volume-adjusted insulin secretion versus ND. Islet and acinar cell secretion in 1AAb+ are consistent across the PH, PB, and PT. This study supports low inter-regional variation in pancreas slice function and, potentially, increased metabolic demand in 1AAb+.

Inhibition of CD226 Co-Stimulation Suppresses Diabetes Development in the NOD Mouse by Augmenting Tregs and Diminishing Effector T Cell Function.

Aims/hypothesis: Immunotherapeutics targeting T cells are crucial for inhibiting autoimmune disease progression proximal to disease onset in type 1 diabetes. A growing number of T cell-directed therapeutics have demonstrated partial therapeutic efficacy, with anti-CD3 (α-CD3) representing the only regulatory agency-approved drug capable of slowing disease progression through a mechanism involving the induction of partial T cell exhaustion. There is an outstanding need to augment the durability and effectiveness of T cell targeting by directly restraining proinflammatory T helper type 1 (Th1) and type 1 cytotoxic CD8+ T cell (Tc1) subsets, while simultaneously augmenting regulatory T cell (Treg) activity. Here, we present a novel strategy for reducing diabetes incidence in the NOD mouse model using a blocking monoclonal antibody targeting the type 1 diabetes-risk associated T cell co-stimulatory receptor, CD226. Methods: Female NOD mice were treated with anti-CD226 between 7-8 weeks of age and then monitored for diabetes incidence and therapeutic mechanism of action. Results: Compared to isotype-treated controls, anti-CD226 treated NOD mice showed reduced insulitis severity at 12 weeks and decreased disease incidence at 30 weeks. Flow cytometric analysis performed five weeks post-treatment demonstrated reduced proliferation of CD4+ and CD8+ effector memory T cells in spleens of anti-CD226 treated mice. Phenotyping of pancreatic Tregs revealed increased CD25 expression and STAT5 phosphorylation following anti-CD226, with splenic Tregs displaying augmented suppression of CD4+ T cell responders in vitro. Anti-CD226 treated mice exhibited reduced frequencies of islet-specific glucose-6-phosphatase catalytic subunit related protein (IGRP)-reactive CD8+ T cells in the pancreas, using both ex vivo tetramer staining and single-cell T cell receptor sequencing (scTCR-seq) approaches. 51Cr-release assays demonstrated reduced cell-mediated lysis of beta-cells by anti-CD226-treated autoreactive cytotoxic T lymphocytes. Conclusions/interpretation: CD226 blockade reduces T cell cytotoxicity and improves Treg function, representing a targeted and rational approach for restoring immune regulation in type 1 diabetes.

Low-Dose Antithymocyte Globulin: A Pragmatic Approach to Treating Stage 2 Type 1 Diabetes.

OBJECTIVE: Low-dose antithymocyte globulin (ATG) (2.5 mg/kg) preserves C-peptide and reduces HbA1c in new-onset stage 3 type 1 diabetes, yet efficacy in delaying progression from stage 2 to stage 3 has not been evaluated. RESEARCH DESIGN AND METHODS: Children (n = 6) aged 5-14 years with stage 2 type 1 diabetes received off-label, low-dose ATG. HbA1c, C-peptide, continuous glucose monitoring, insulin requirements, and side effects were followed for 18-48 months. RESULTS: Three subjects (50%) remained diabetes free after 1.5, 3, and 4 years of follow-up, while three developed stage 3 within 1-2 months after therapy. Eighteen months posttreatment, even disease progressors demonstrated near-normal HbA1c (5.1% [32 mmol/mol], 5.6% [38 mmol/mol], and 5.3% [34 mmol/mol]), time in range (93%, 88%, and 98%), low insulin requirements (0.17, 0.18, and 0.34 units/kg/day), and robust C-peptide 90 min after mixed meal (1.3 ng/dL, 2.3 ng/dL, and 1.4 ng/dL). CONCLUSIONS: These observations support additional prospective studies evaluating ATG in stage 2 type 1 diabetes.

Human γδ T cells in diverse tissues exhibit site-specific maturation dynamics across the life span.

During ontogeny, γδ T cells emerge from the thymus and directly seed peripheral tissues for in situ immunity. However, their functional role in humans has largely been defined from blood. Here, we analyzed the phenotype, transcriptome, function, and repertoire of human γδ T cells in blood and mucosal and lymphoid tissues from 176 donors across the life span, revealing distinct profiles in children compared with adults. In early life, clonally diverse Vδ1 subsets predominate across blood and tissues, comprising naïve and differentiated effector and tissue repair functions, whereas cytolytic Vδ2 subsets populate blood, spleen, and lungs. With age, Vδ1 and Vδ2 subsets exhibit clonal expansions and elevated cytolytic signatures, which are disseminated across sites. In adults, Vδ2 cells predominate in blood, whereas Vδ1 cells are enriched across tissues and express residency profiles. Thus, antigenic exposures over childhood drive the functional evolution and tissue compartmentalization of γδ T cells, leading to age-dependent roles in immunity.

TRANSCRIPTOMIC DIFFERENCES IN PERIPHERAL MONOCYTE POPULATIONS IN SEPTIC PATIENTS BASED ON OUTCOME.

ABSTRACT: Postsepsis early mortality is being replaced by survivors who experience either a rapid recovery and favorable hospital discharge or the development of chronic critical illness with suboptimal outcomes. The underlying immunological response that determines these clinical trajectories remains poorly defined at the transcriptomic level. As classical and nonclassical monocytes are key leukocytes in both the innate and adaptive immune systems, we sought to delineate the transcriptomic response of these cell types. Using single-cell RNA sequencing and pathway analyses, we identified gene expression patterns between these two groups that are consistent with differences in TNF-α production based on clinical outcome. This may provide therapeutic targets for those at risk for chronic critical illness in order to improve their phenotype/endotype, morbidity, and long-term mortality.

The post-septic peripheral myeloid compartment reveals unexpected diversity in myeloid-derived suppressor cells.

Introduction: Sepsis engenders distinct host immunologic changes that include the expansion of myeloid-derived suppressor cells (MDSCs). These cells play a physiologic role in tempering acute inflammatory responses but can persist in patients who develop chronic critical illness. Methods: Cellular Indexing of Transcriptomes and Epitopes by Sequencing and transcriptomic analysis are used to describe MDSC subpopulations based on differential gene expression, RNA velocities, and biologic process clustering. Results: We identify a unique lineage and differentiation pathway for MDSCs after sepsis and describe a novel MDSC subpopulation. Additionally, we report that the heterogeneous response of the myeloid compartment of blood to sepsis is dependent on clinical outcome. Discussion: The origins and lineage of these MDSC subpopulations were previously assumed to be discrete and unidirectional; however, these cells exhibit a dynamic phenotype with considerable plasticity.

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 dataset's 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.

Human immune phenotyping reveals accelerated aging in type 1 diabetes.

The proportions and phenotypes of immune cell subsets in peripheral blood undergo continual and dramatic remodeling throughout the human life span, which complicates efforts to identify disease-associated immune signatures in type 1 diabetes (T1D). We conducted cross-sectional flow cytometric immune profiling on peripheral blood from 826 individuals (stage 3 T1D, their first-degree relatives, those with ≥2 islet autoantibodies, and autoantibody-negative unaffected controls). We constructed an immune age predictive model in unaffected participants and observed accelerated immune aging in T1D. We used generalized additive models for location, shape, and scale to obtain age-corrected data for flow cytometry and complete blood count readouts, which can be visualized in our interactive portal (ImmScape); 46 parameters were significantly associated with age only, 25 with T1D only, and 23 with both age and T1D. Phenotypes associated with accelerated immunological aging in T1D included increased CXCR3+ and programmed cell death 1-positive (PD-1+) frequencies in naive and memory T cell subsets, despite reduced PD-1 expression levels on memory T cells. Phenotypes associated with T1D after age correction were predictive of T1D status. Our findings demonstrate advanced immune aging in T1D and highlight disease-associated phenotypes for biomarker monitoring and therapeutic interventions.

Suppression of local inflammation via galectin-anchored indoleamine 2,3-dioxygenase.

The treatment of chronic inflammation with systemically administered anti-inflammatory treatments is associated with moderate-to-severe side effects, and the efficacy of locally administered drugs is short-lived. Here we show that inflammation can be locally suppressed by a fusion protein of the immunosuppressive enzyme indoleamine 2,3-dioxygenase 1 (IDO) and galectin-3 (Gal3). Gal3 anchors IDO to tissue, limiting the diffusion of IDO-Gal3 away from the injection site. In rodent models of endotoxin-induced inflammation, psoriasis, periodontal disease and osteoarthritis, the fusion protein remained in the inflamed tissues and joints for about 1 week after injection, and the amelioration of local inflammation, disease progression and inflammatory pain in the animals were concomitant with homoeostatic preservation of the tissues and with the absence of global immune suppression. IDO-Gal3 may serve as an immunomodulatory enzyme for the control of focal inflammation in other inflammatory conditions.

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.

Membrane marker selection for segmenting single cell spatial proteomics data.

The ability to profile spatial proteomics at the single cell level enables the study of cell types, their spatial distribution, and interactions in several tissues and conditions. Current methods for cell segmentation in such studies rely on known membrane or cell boundary markers. However, for many tissues, an optimal set of markers is not known, and even within a tissue, different cell types may express different markers. Here we present RAMCES, a method that uses a convolutional neural network to learn the optimal markers for a new sample and outputs a weighted combination of the selected markers for segmentation. Testing RAMCES on several existing datasets indicates that it correctly identifies cell boundary markers, improving on methods that rely on a single marker or those that extend nuclei segmentations. Application to new spatial proteomics data demonstrates its usefulness for accurately assigning cell types based on the proteins expressed in segmented cells.

Infant T cells are developmentally adapted for robust lung immune responses through enhanced T cell receptor signaling.

Infants require coordinated immune responses to prevent succumbing to multiple infectious challenges during early life, particularly in the respiratory tract. The mechanisms by which infant T cells are functionally adapted for these responses are not well understood. Here, we demonstrated using an in vivo mouse cotransfer model that infant T cells generated greater numbers of lung-homing effector cells in response to influenza infection compared with adult T cells in the same host, due to augmented T cell receptor (TCR)­mediated signaling. Mouse infant T cells showed increased sensitivity to low antigen doses, originating at the interface between T cells and antigen-bearing accessory cells­through actin-mediated mobilization of signaling molecules to the immune synapse. This enhanced signaling was also observed in human infant versus adult T cells. Our findings provide a mechanism for how infants control pathogen load and dissemination, which is important for designing developmentally targeted strategies for promoting immune responses at this vulnerable life stage.

geneBasis: an iterative approach for unsupervised selection of targeted gene panels from scRNA-seq.

scRNA-seq datasets are increasingly used to identify gene panels that can be probed using alternative technologies, such as spatial transcriptomics, where choosing the best subset of genes is vital. Existing methods are limited by a reliance on pre-existing cell type labels or by difficulties in identifying markers of rare cells. We introduce an iterative approach, geneBasis, for selecting an optimal gene panel, where each newly added gene captures the maximum distance between the true manifold and the manifold constructed using the currently selected gene panel. Our approach outperforms existing strategies and can resolve cell types and subtle cell state differences.