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Walsh, C. M.

Publications and source records attributed to Walsh, C. M..

5 recordsLinked to original sources

Neutrophils promote CXCR3-dependent itch in the development of atopic dermatitis

Chronic itch remains a highly prevalent disorder with limited treatment options. Most chronic itch diseases are thought to be driven by both the nervous and immune systems, but the fundamental molecular and cellular interactions that trigger the development of itch and the acute-to-chronic itch transition remain unknown. Here, we show that skin-infiltrating neutrophils are key initiators of itch in atopic dermatitis, the most prevalent chronic itch disorder. Neutrophil depletion significantly attenuated itch-evoked scratching in a mouse model of atopic dermatitis. Neutrophils were also required for several key hallmarks of chronic itch, including skin hyperinnervation, enhanced expression of itch signaling molecules, and upregulation of inflammatory cytokines, activity-induced genes, and markers of neuropathic itch. Finally, we demonstrate that neutrophils are required for induction of CXCL10, a ligand of the CXCR3 receptor that promotes itch via activation of sensory neurons, and we find that that CXCR3 antagonism attenuates chronic itch.

immunology

Mutations that improve the efficiency of a weak-link enzyme are rare compared to adaptive mutations elsewhere in the genome

New enzymes often evolve by amplification and divergence of genes encoding enzymes with a weak ability to provide a new function. Experimental studies to date have followed the evolutionary trajectory of an amplified gene, but have not addressed other mutations in the genome when fitness is limited by an evolving gene. We have adapted Escherichia coli in which an enzymes weak secondary activity has been recruited to serve an essential function. While the gene encoding the \"weak-link\" enzyme amplified in all eight populations, mutations improving the new activity occurred in only one. This beneficial allele quickly swept the amplified array, displacing the parental allele. Most adaptive mutations, however, occurred elsewhere in the genome. We have identified the mechanisms by which three of the classes of mutations increase fitness. These mutations may be detrimental once a new enzyme has evolved, and require reversion or compensation, leading to permanent changes in the genome.

evolutionary biology

A global survey of mycobacterial diversity in soil

Mycobacterium is a diverse bacterial genus ubiquitous in many soil and aquatic environments. Members of this genus have been associated with human and other animal diseases, including the nontuberculous mycobacteria (NTM), which are of growing relevance to public health worldwide. Although soils are often considered an important source of environmentally-acquired NTM infections, the biodiversity and ecological preferences of soil mycobacteria remain largely unexplored across contrasting climates and ecosystem types. Using a culture-independent approach by combining 16S rRNA marker gene sequencing with mycobacterial-specific hsp65 gene sequencing, we analyzed the diversity, distributions, and environmental preferences of soil-dwelling mycobacteria in 143 soil samples collected from across the globe. The surveyed soils harbored highly diverse mycobacterial communities that span the full-extent of the known mycobacterial phylogeny, with most soil mycobacteria belonging to previously undescribed lineages. While the genus Mycobacterium tended to have higher relative abundances in cool, wet, and acidic soil environments, several individual mycobacterial clades had contrasting environmental preferences. We identified the environmental preferences of many mycobacterial clades, including the clinically-relevant M. avium complex that was more commonly detected in wet and acidic soils. However, most of the soil mycobacteria detected were not closely related to known pathogens, calling into question previous assumptions about the general importance of soil as a source of NTM infections. Together this work provides novel insights into the diversity, distributions and ecological preferences of soil mycobacteria, and lays the foundation for future efforts to link mycobacterial phenotypes to their distributions. ImportanceMycobacteria are common inhabitants of soil, and while most members of the bacterial genus are innocuous, some mycobacteria can cause environmentally-acquired infections of humans and other animals. Human infections from nontuberculous mycobacteria (NTM) are increasingly prevalent worldwide, and some areas appear to be hotspots for NTM disease. While exposure to soil is frequently implicated as an important mode of NTM transmission, the diversity, distributions and ecological preferences of soil mycobacteria remain poorly understood. We analyzed 143 soils from across the globe and found that the genus Mycobacterium and lineages within the genus often exhibited predictable preferences for specific environmental conditions. Soils harbor large amounts of previously-undescribed mycobacterial diversity, and lineages that include known pathogens were rarely detected in soil. Together these findings suggest that soil is an unlikely source of many mycobacterial infections. The biogeographical patterns we documented lend insight into the ecology of this important group of soil-dwelling bacteria.

microbiology

Optical Metabolic Imaging of Heterogeneous Drug Response in Pancreatic Cancer Patient Organoids

New tools are needed to match pancreatic cancer patients with effective treatments. Patient-derived organoids offer a high-throughput platform to personalize treatments and discover novel therapies. Currently, methods to evaluate drug response in organoids are limited because they cannot be completed in a clinically relevant time frame, only evaluate response at one time point, and most importantly, overlook cellular heterogeneity. In this study, non-invasive optical metabolic imaging (OMI) of cellular heterogeneity in organoids was evaluated as a predictor of clinical treatment response. Organoids were generated from fresh patient tissue samples acquired during surgery and treated with the same drugs as the patient's prescribed adjuvant treatment. OMI measurements of heterogeneity in response to this treatment were compared to later patient response, specifically to the time to recurrence following surgery. OMI was sensitive to patient-specific treatment response in as little as 24 hours. OMI distinguished subpopulations of cells with divergent and dynamic responses to treatment in living organoids without the use of labels or dyes. OMI of organoids agreed with long-term therapeutic response in patients. With these capabilities, OMI could serve as a sensitive high-throughput tool to identify optimal therapies for individual pancreatic cancer patients, and to develop new effective therapies that address cellular heterogeneity in pancreatic cancer.

bioengineering

Label-free Method for Classification of T cell Activation

T cells have a range of cytotoxic and immune-modulating functions, depending on activation state and subtype. However, current methods to assess T cell function use exogenous labels that often require cell permeabilization, which is limiting for time-course studies of T cell activation and non-destructive quality control of immunotherapies. Label-free optical imaging is an attractive solution. Here, we use autofluorescence imaging of NAD(P)H and FAD, co-enzymes of metabolism, to quantify optical imaging endpoints in quiescent and activated T cells. Machine learning classification models were developed for label-free, non-destructive determination of T cell activation state. T cells were isolated from the peripheral blood of human donors, and a subset were activated with a tetrameric antibody against CD2/CD3/CD28 surface ligands. NAD(P)H and FAD autofluorescence intensity and lifetime of the T cells were imaged using a multiphoton fluorescence lifetime microscope. Significant differences in autofluorescence imaging end-points were observed between quiescent and activated T cells. Feature selection methods revealed that the contribution of the short NAD(P)H lifetime (1) is the most important feature for classification of activation state, across multiple donors and T cell subsets. Logistic regression models achieved 97-99% accuracy for classification of T cell activation from the autofluorescence imaging endpoints. Additionally, autofluorescence imaging revealed NAD(P)H and FAD autofluorescence differences between CD3+CD8+ and CD3+CD4+ T cells, and random forest models of the autofluorescence imaging endpoints achieved 97+% accuracy for four-group classification of quiescent and activated CD3+CD8+ and CD3+CD4+ T cells. Altogether these results indicate that autofluorescence imaging of NAD(P)H and FAD is a powerful method for label-free, non-destructive determination of T cell activation and subtype, which could have important applications for the treatment of cancer, autoimmune, infectious, and other diseases.

bioengineering