Biology subjects

Mitchell, R. B.

Publications and source records attributed to Mitchell, R. B..

4 recordsLinked to original sources

bioRxiv2024

Single cell transcriptional analysis of human adenoids identifies molecular features of airway microfold cells

The nasal, oropharyngeal, and bronchial mucosa are primary contact points for airborne pathogens like Mycobacterium tuberculosis (Mtb), SARS-CoV-2, and influenza virus. While mucosal surfaces can function as both entry points and barriers to infection, mucosa-associated lymphoid tissues (MALT) facilitate early immune responses to mucosal antigens. MALT contains a variety of specialized epithelial cells, including a rare cell type called a microfold cell (M cell) that functions to transport apical antigens to basolateral antigen-presenting cells, a crucial step in the initiation of mucosal immunity. M cells have been extensively characterized in the gastrointestinal (GI) tract in murine and human models. However, the precise development and functions of human airway M cells is unknown. Here, using single-nucleus RNA sequencing (snRNA-seq), we generated an atlas of cells from the human adenoid and identified 16 unique cell types representing basal, club, hillock, and hematopoietic lineages, defined their developmental trajectories, and determined cell-cell relationships. Using trajectory analysis, we found that human airway M cells develop from progenitor club cells and express a gene signature distinct from intestinal M cells. Surprisingly, we also identified a heretofore unknown epithelial cell type demonstrating a robust interferon-stimulated gene signature. Our analysis of human adenoid cells enhances our understanding of mucosal immune responses and the role of M cells in airway immunity. This work also provides a resource for understanding early interactions of pathogens with airway mucosa and a platform for development of mucosal vaccines.

immunology↗

bioRxiv2021

Mapping of genotype-by-environment interactions in phenology identifies two cues for flowering in switchgrass (Panicum virgatum)

The timing of vegetative and reproductive growth in plants ("phenological timings") depend on genetic effects (G), environmental (e.g., weather) cues, and their interaction. Here, we measure phenological timings in two highly divergent switchgrass (Panicum virgatum) subpopulations using repeated plantings of cloned individuals at eight sites across the central United States. The timing of vegetative growth for the two subpopulations reversed between their two natural ranges and had strong negative correlations between these regions; in contrast, the timing of flowering was positively correlated between gardens. We expect that these phenotypic correlations consist of polygenic effects on phenology which have distinct patterns of GxE segregating at different mapped loci. Thus, we infer the mixture of ways genetic effects impact phenological timings, such as across common gardens (GxE) or with weather cues (GxWeather). We demonstrate that we can identify genetic variation with GxWeather and assign genetic loci to specific weather-based cues or other patterns. For example, in the Gulf subpopulation, 65% of genetic effects on the timing of vegetative growth covary with daylength 14 days prior to green-up date, and 33% of genetic effects on the timing of flowering covary with cumulative rainfall in the week prior to flowering. However, most variation in genetic effects cannot be attributed to variation in weather variables. Selective breeding for particular alleles at GxWeather loci could alter flowering responsiveness in a photoperiod or rainfall-specific way. More broadly, our approach refines the characterization of genotype-by-environment interactions and can be implemented in any species phenotyped in multiple environments.

genetics↗

bioRxiv2019

Identification of scavenger receptor B1 as the airway microfold cell receptor for Mycobacterium tuberculosis

Mycobacterium tuberculosis (Mtb) can enter the body through multiple routes, including via specialized transcytotic cells called microfold cells (M cell). However, the mechanistic basis for M cell entry remains undefined. Here, we show that M cell transcytosis depends on the Mtb Type VII secretion machine and its major virulence factor EsxA. We identify scavenger receptor B1 (SR-B1) as an EsxA receptor on airway M cells. SR-B1 is required for Mtb binding to and translocation across M cells in mouse and human tissue. Together, our data demonstrate a previously undescribed role for Mtb EsxA in mucosal invasion and identify SR-B1 as the airway M cell receptor for Mtb.

immunology↗

bioRxiv2019

Geographic variation in the genetic basis of resistance to leaf rust in locally adapted ecotypes of the biofuel crop switchgrass (Panicum virgatum)

O_LILocal adaptation is an important process in plant evolution, which can be impacted by differential pathogen pressures along environmental gradients. However, the degree to which pathogen resistance loci vary in effect across space and time is incompletely described. C_LIO_LITo understand how the genetic architecture of resistance varies across time and geographic space, we quantified rust (Puccinia spp.) severity in switchgrass (Panicum virgatum) plantings at eight locations across the central United States for three years and conducted quantitative trait locus (QTL) mapping for rust progression. C_LIO_LIWe mapped several variable QTLs, but two large-effect QTLs which we have named Prr1 and Prr2 were consistently associated with rust severity in multiple sites and years, particularly in northern sites. In contrast, there were numerous small-effect QTLs at southern sites, indicating a genotype-by-environment interaction in rust resistance loci. Interestingly, Prr1 and Prr2 had a strong epistatic interaction, which also varied in strength and direction of effect across space. C_LIO_LIOur results suggest that abiotic factors covarying with latitude interact with the genetic loci underlying plant resistance to control rust infection severity. Further, our results indicate that segregating genetic variation in epistatically interacting loci may play a key role in determining response to infection across geographic space. C_LI

genomics↗