Biology subjects

Vander Heiden, J. A.

Publications and source records attributed to Vander Heiden, J. A..

4 recordsLinked to original sources

bioRxiv2024

Dermatopontin-expressing fibroblasts mediate an essential skin macrophage niche

Fibroblasts are present in all tissues and are crucial for maintaining tissue homeostasis. We previously identified fibroblasts marked by Dermatopontin (Dpt) but their role in supporting macrophage homeostasis remains unclear. Here, we generated novel mesenchymal lineage-restricted genetic tools to target Dpt expressing fibroblasts and elucidate their role in supporting skin macrophages. Transcriptional profiling, flow cytometry, and in situ hybridization uncovered two broad populations of F4/80-expressing skin macrophages, denoted by high expression of CD206 and CD64 (CD206hiCD64+), or CD11c. Targeted depletion of Dpt+ fibroblasts resulted in a profound loss of both macrophage populations. Conditional deletion of colony-stimulating factor-1 (Csf1) in Dpt+ fibroblasts revealed that CD206hiCD64+, and not CD11c+, macrophages are acutely dependent on fibroblast-derived Csf1, consistent with their higher expression of the Csf1 receptor. Following Csf1 deletion in Dpt+ fibroblasts, loss of CD206hiCD64+ macrophages were observed across the dermis, dermal white adipose tissue (dWAT), and adventitia, accompanied by a modest upregulation of fibroblast-related and extracellular matrix (ECM) genes and structural changes to the skin. Alterations to the skin network upon loss of fibroblast-derived Csf1 and CD206hiCD64+ macrophages led to a significant delay in wound healing. We also demonstrate the CSF1-CSF1R signaling pathway is functionally relevant in human systemic sclerosis, or scleroderma, as elevated levels of CSF1 produced by fibroblasts and an increased abundance of macrophages both correlate with disease severity. Our findings demonstrate the role of Dpt+ fibroblasts in regulating a Csf1-dependent macrophage niche in skin and orchestrating responses in injury and disease.

immunology↗

bioRxiv2023

Scalable querying of human cell atlases via a foundational model reveals commonalities across fibrosis-associated macrophages

Single-cell RNA-seq (scRNA-seq) studies have profiled over 100 million human cells across diseases, developmental stages, and perturbations to date. A singular view of this vast and growing expression landscape could help reveal novel associations between cell states and diseases, discover cell states in unexpected tissue contexts, and relate in vivo cells to in vitro models. However, these require a common, scalable representation of cell profiles from across the body, a general measure of their similarity, and an efficient way to query these data. Here, we present SCimilarity, a metric learning framework to learn and search a unified and interpretable representation that annotates cell types and instantaneously queries for a cell state across tens of millions of profiles. We demonstrate SCimilarity on a 22.7 million cell corpus assembled across 399 published scRNA-seq studies, showing accurate integration, annotation and querying. We experimentally validated SCimilarity by querying across tissues for a macrophage subset originally identified in interstitial lung disease, and showing that cells with similar profiles are found in other fibrotic diseases, tissues, and a 3D hydrogel system, which we then repurposed to yield this cell state in vitro. SCimilarity serves as a foundational model for single cell gene expression data and enables researchers to query for similar cellular states across the entire human body, providing a powerful tool for generating novel biological insights from the growing Human Cell Atlas.

bioinformatics↗

bioRxiv2019

sumrep: a summary statistic framework for immune receptor repertoire comparison and model validation

The adaptive immune system generates an incredible diversity of antigen receptors for B and T cells to keep dangerous pathogens at bay. The DNA sequences coding for these receptors arise by a complex recombination process followed by a series of productivity-based filters, as well as affinity maturation for B cells, giving considerable diversity to the circulating pool of receptor sequences. Although these datasets hold considerable promise for medical and public health applications, the complex structure of the resulting adaptive immune receptor repertoire sequencing (AIRR-seq) datasets makes analysis difficult. In this paper we introduce sumrep, an R package that efficiently performs a wide variety of repertoire summaries and comparisons, and show how sumrep can be used to perform model validation. We find that summaries vary in their ability to differentiate between datasets, although many are able to distinguish between covariates such as donor, timepoint, and cell type for BCR and TCR repertoires. We show that deletion and insertion lengths resulting from V(D)J recombination tend to be more discriminative characterizations of a repertoire than summaries that describe the amino acid composition of the CDR3 region. We also find that state-of-the-art generative models excel at recapitulating gene usage and recombination statistics in a given experimental repertoire, but struggle to capture many physiochemical properties of real repertoires.

immunology↗

bioRxiv2019

Repertoire-wide phylogenetic models of B cell molecular evolution reveal evolutionary signatures of aging and vaccination

In order to produce effective antibodies, B cells undergo rapid somatic hypermutation (SHM) and selection for binding affinity to antigen via a process called affinity maturation. The similarities between this process and evolution by natural selection have led many groups to use evolutionary and phylogenetic methods to characterize the development of immunological memory, vaccination, and other processes that depend on affinity maturation. However, these applications are limited by several features of affinity maturation that violate assumptions in standard phylogenetic models. Further, most phylogenetic models are designed to be applied to individual lineages comprising genetically diverse sequences, while B cell repertoires often consist of hundreds to thousands of separate low-diversity lineages. Here, we introduce a hierarchical phylogenetic framework that incorporates the unique features of SHM, and integrates information from all lineages in a repertoire to more precisely estimate model parameters. We demonstrate the power of this approach by characterizing previously un-described phenomena in affinity maturation. First, we find evidence consistent with age related changes in SHM hot-and cold-spot motifs. Second, we identify a consistent relationship between increased tree length and signs of increased negative selection, apparent in the repertoires of both healthy subjects and those undergoing active immune responses. This suggests that B cell lineages shift towards negative selection over time as a general feature of affinity maturation. Our study provides a framework for undertaking repertoire-wide phylogenetic testing of SHM hypotheses, and provides a new means of charactering the process of mutation and selection during affinity maturation.

immunology↗