Biology subjects

Hawn, T. R.

Publications and source records attributed to Hawn, T. R..

9 recordsLinked to original sources

bioRxiv2025

ESX-5 Deletions in Mycobacterium tuberculosis Alter Macrophage Cytokine Signaling and Bacterial Heavy Metal Response

The ESX-5 secretion system is critical for Mycobacterium tuberculosis (Mtb) viability and putatively linked to pathogenesis, but a functional understanding of how it interacts with the host is unknown. ESX-5 is encoded at a single genomic locus with small, paralogous, secreted targets (ESX-5a, 5b, 5c) spaced throughout the genome. To examine host-pathogen interactions of these putative virulence clusters, we made mutant strains lacking these loci and infected primary human macrophages. Surprisingly, all deletion mutants independently reduced cytokine secretion during infection, specific to certain analytes. This defect depended on viable bacteria and was mediated by a post-transcriptional mechanism. In bacterial transcriptomic analyses, each mutant downregulated heavy metal response genes compared to wild type bacteria. Treatment of Mtb with Cu or Cd led to increased ESX-5a and ESX-5c expression, concurrent with increased TNF and IL-6 secretion in macrophages compared to untreated bacilli, indicating a link between ESX-5 expression and cellular cytokine levels.

immunology↗

bioRxiv2025

Human iPSC derived alveolar macrophages reveal macrophage subtype specific functions of itaconate in M. tuberculosis host defense

Mycobacterium tuberculosis (Mtb) must survive within multiple macrophage populations during infection, including alveolar macrophages (AM) and recruited inflammatory macrophages. In mice, itaconate, produced in macrophages by ACOD1 mediated decarboxylation of aconitate, has direct antimicrobial activity, modulates inflammatory cytokines, and is required for resistance to M. tuberculosis (Mtb) infection. The role of itaconate in human macrophages is less clear and whether itaconate mediates distinct effects in macrophage subtypes is unknown. Here, we investigated the role of itaconate in human iPSC-derived macrophages, either induced by GM-CSF to resemble alveolar macrophages (AM-Like cells), or treated with M-CSF to generate control macrophages (MCDM cells). Both types of human macrophages produce substantially less itaconate than mouse macrophages and AM-Ls produced 4-fold less itaconate than MCDMs. Surprisingly, ACOD1 deficient AM-L macrophages, but not MCDM macrophages, were permissive for Mtb growth. Moreover, itaconate functioned to dampen the Mtb induced inflammatory response in MCDMs, but not AM-L macrophages, affecting both the Type I IFN and TNF pathways. These results indicate that itaconate is involved in human macrophage responses to TB, with distinct roles in different macrophage subsets. These results also show that genetically tractable hiPSC-derived macrophages are a robust and versatile model to dissect cellular host pathogen interactions.

immunology↗

bioRxiv2025

Cathepsin Z is a conserved susceptibility factor underlying tuberculosis severity

Tuberculosis (TB) outcomes vary widely, from asymptomatic infection to mortality, yet most animal models do not recapitulate human phenotypic and genotypic variation. The genetically diverse Collaborative Cross mouse panel models distinct facets of TB disease that occur in humans and allows identification of genomic loci underlying clinical outcomes. We previously mapped a TB susceptibility locus on mouse chromosome 2. Here, we identify cathepsin Z (Ctsz) as a lead candidate underlying this TB susceptibility and show that Ctsz ablation leads to increased bacterial burden, CXCL1 overproduction, and decreased survival in mice. Ctsz disturbance within murine macrophages enhances production of CXCL1, a known biomarker of TB severity. From a Ugandan household contact study, we identify significant associations between CTSZ variants and TB disease severity. Finally, we examine patient-derived TB granulomas and report CTSZ localization within granuloma-associated macrophages, placing human CTSZ at the host-pathogen interface. These findings implicate a conserved CTSZ-CXCL1 axis in humans and genetically diverse mice that mediates TB disease severity.

genetics↗

bioRxiv2025

Shared and distinct responses of human and murine alveolar macrophages and monocyte-derived macrophages to Mycobacterium tuberculosis

Macrophages serve as important sites of bacterial replication and host immune response during Mycobacterium tuberculosis (Mtb) infection with distinct roles for alveolar macrophages (AMs) early in infection and monocyte-derived (MDMs) during later stages of disease. Here, we leverage data from human and mouse models to perform a cross-species analysis of macrophage responses to Mtb infection. Overall, we find that both subsets of human and murine macrophages mount a strong interferon response to Mtb infection. However, AM across both species do not generate as strong a pro-inflammatory response as human MDMs or murine bone marrow-derived macrophages (BMDMs), as characterized by TNFA signaling and inflammatory response pathways. Interestingly, AMs from mice that were previously vaccinated with BCG (scBCG) or from a model of contained TB (coMtb) had Mtb responses that were more similar to human AMs than control mice. We also identify species-specific pathways altered by infection differently in mouse and human macrophages, specifically in pathways related to cholesterol in AMs as well as MYC targets and Hedgehog signaling in MDMs/BMDMs. Lastly, to investigate downstream effects of the macrophage interferon responses, we examine macrophage expression of IL-10, an immunosuppressive cytokine induced by Type I Interferons, and c-Maf, a transcription factor required for IL-10 expression in myeloid cells. We find that c-Maf and IL-10 have significantly lower expression in AMs compared to MDMs in both humans and mice, suggesting one possible mechanism by which AMs mount a stronger interferon response following Mtb infection. Overall, these results highlight the dynamics of innate myeloid responses over the course of Mtb infection and the benefit of a combined analysis across species to reveal conserved and unique responses.

immunology↗

bioRxiv2024

Multi-omic latent variable data integration reveals multicellular structure pathways associated with resistance to tuberculin skin test (TST)/interferon gamma release assay (IGRA) conversion in Uganda

Understanding the mechanisms of early clearance of Mycobacterium tuberculosis (Mtb) may illuminate new therapeutic strategies for tuberculosis (TB). We previously found genetic, epigenetic, and transcriptomic signatures associated with resistance (resister, RSTR) to tuberculin skin test (TST)/interferon gamma release assay (IGRA) conversion among highly exposed TB contacts. We hypothesized that integration of these datasets with multi-omic latent factor methods would detect pathways differentiating RSTR patients from those with latent infection (LTBI) which were not differentiated by individual dataset analyses. We pre-filtered and scaled features with the largest change between LTBI and RSTR groups for 126 patients with data in at least two of five data modalities: single nucleotide polymorphisms (SNP), monocyte RNAseq (baseline and Mtb-stimulated conditions), and monocyte epigenetics (methylation and ATAC-seq). Using multiomic latent factor analysis (MOFA), we generated ten latent factors on the subset of 33 patients with all five datasets available, four of which were different between LTBI and RSTR (FDR < 0.1). Factor 4, which was the most integrated of the significant factors, showed the greatest difference between RSTR and LTBI groups (FDR < 0.001). Three additional latent factor data integration methods also distinguished the RSTR and LTBI groups and identified overlapping features with MOFA. Using pathway analysis and a cluster-based enrichment method, we identified biologic functions associated with latent factors and found that MOFA Factors 2-4 include functions related to cell-cell adhesion, cell shape, and development of multicellular structures. In summary, latent variable integration methods uncovered signatures associated with resistance to TST/IGRA conversion that were not detected within individual dataset analyses and included pathways associated with cellular interactions and multicellular structures. Author SummaryTuberculosis (TB) is a leading cause of preventable death worldwide. Previous research has identified some genetic and molecular patterns that are linked to resistance to TB in people who are highly exposed to the bacterium that causes the disease but do not develop an infection. We took genetic, epigenetic, and gene expression data from people who were not infected after exposure to TB within in their household and compared them with people who did develop a latent form of TB disease after similar exposure. We used a special method to analyze these datasets in an integrated way, rather than separately. This approach revealed four key factors that clearly distinguished between the resistant individuals and those with latent infection. One of these factors, in particular, showed a strong difference. We found that these factors were related to important biological processes such as how cells stick together, their shape, and how they form tissues. This method allowed us to see new patterns in the biological pathways linked to TB resistance that were not evident when looking at each type of data on its own.

genomics↗

bioRxiv2022

MR1-restricted T cell clonotypes are associated with 'resistance' to M.tuberculosis infection

T cells are required for a protective immune response against the human adapted pathogen Mycobacterium tuberculosis (M.tb). We recently described a cohort of Ugandan household contacts of tuberculosis cases that appear to resist M.tb infection (RSTRs) and showed that these individuals harbor IFN-{gamma} independent T cell responses to M.tb-specific peptide antigens. However, T cells also recognize non-protein antigens via antigen presenting systems that are independent of genetic background, leading to their designation as donor-unrestricted T (DURT) cells. We used combinatorial tetramer staining and multi-parameter flow cytometry to comprehensively characterize the association between DURTs and resistance to M.tb infection. We did not observe a difference in peripheral blood frequencies of invariant natural killer T (iNKT) cells, germline encoded mycolyl-reactive (GEM) T cells, or {gamma}{delta} T cells between RSTRs and matched controls with latent M.tb infection (LTBIs). However, we did observe a 1.65-fold increase in frequency of circulating MR1-restricted T (MR1T) cells among RSTRs in comparison with LTBI (p=0.03). Multi-modal single cell RNA-sequencing of 18,251 MR1T cells sorted from a subset of donors revealed 5150 clonotypes that expressed a common transcriptional program, the majority of which were private. Deep sequencing of the TCR- repertoire revealed several DURT clonotypes that were expanded among RSTRs, including at least two MR1T clonotypes. Taken together, our data reveal unexpected donor-specific diversity in the TCR repertoire of human MR1T cells as well as associations between MR1 clonotypes and resistance to M.tb infection.

immunology↗

bioRxiv2022

kimma: flexible linear mixed effects modeling with kinship for RNA-seq data

We introduce kimma (Kinship In Mixed Model Analysis), an open-source R package for flexible linear mixed effects modeling of RNA-seq including covariates, weights, random effects, covariance matrices, and fit metrics. In simulated datasets, kimma detects differentially expressed genes (DEGs) with similar specificity, sensitivity, and computational time as limma unpaired and dream paired models. Unlike other software, kimma supports covariance matrices as well as fit metrics like AIC. Utilizing genetic kinship covariance, kimma revealed that kinship impacts model fit and DEG detection in a related cohort. Thus, kimma equals or outcompetes current DEG pipelines in sensitivity, computational time, and model complexity.

bioinformatics↗

bioRxiv2022

Peripheral blood T-cell deficiency and hyperinflammatory monocyte responses associate with MAC lung disease

RationaleAlthough nontuberculous mycobacterial (NTM) disease is a growing problem, available treatments are suboptimal and diagnostic tools are inadequate. Immunological mechanisms of susceptibility to NTM disease are poorly understood. ObjectiveTo understand NTM pathogenesis, we evaluated innate and antigen-specific adaptive immune responses to Mycobacterium avium complex (MAC) in individuals with MAC lung disease (MACDZ). MethodsWe synthesized 15mer MAC-, NTM-, or MAC/Mtb-specific peptides and stimulated peripheral blood mononuclear cells (PBMC) with pools of these peptides. We measured T-cell responses by cytokine production, expression of surface markers, and analysis of global gene expression in 27 MACDZ individuals and 32 healthy controls. We also analyzed global gene expression in Mav-infected and uninfected peripheral blood monocytes from 17 MACDZ and 17 healthy controls. Measurements and Main ResultsWe were unable to detect T-cell responses against the peptide libraries or Mav lysate that has increased reactivity in MACDZ subjects compared to controls. T-cell responses to non-mycobacteria derived antigens were preserved. MACDZ individuals had a lower frequency of Th1 and Th1* T-cell populations. By contrast, global gene expression analysis demonstrated upregulation of proinflammatory pathways in uninfected and Mav-infected monocytes derived from MACDZ subjects compared to controls. ConclusionsPeripheral blood T-cell responses to Mycobacterial antigens and the frequency of Th1 and Th1* cell populations are diminished in individuals with MAC disease. In contrast, MACDZ subjects had hyperinflammatory monocyte responses. Together, these data suggest a novel immunologic defect which underlies MAC pathogenesis and includes concurrent innate and adaptive dysregulation.

immunology↗

bioRxiv2021

Tracking SARS-CoV-2 Spike Protein Mutations in the United States (2020/01 - 2021/03) Using a Statistical Learning Strategy

The emergence and establishment of SARS-CoV-2 variants of interest (VOI) and variants of concern (VOC) highlight the importance of genomic surveillance. We propose a statistical learning strategy (SLS) for identifying and spatiotemporally tracking potentially relevant Spike protein mutations. We analyzed 167,893 Spike protein sequences from US COVID-19 cases (excluding 21,391 sequences from VOI/VOC strains) deposited at GISAID from January 19, 2020 to March 15, 2021. Alignment against the reference Spike protein sequence led to the identification of viral residue variants (VRVs), i.e., residues harboring a substitution compared to the reference strain. Next, generalized additive models were applied to model VRV temporal dynamics, to identify VRVs with significant and substantial dynamics (false discovery rate q-value <0.01; maximum VRV proportion > 10% on at least one day). Unsupervised learning was then applied to hierarchically organize VRVs by spatiotemporal patterns and identify VRV-haplotypes. Finally, homology modelling was performed to gain insight into potential impact of VRVs on Spike protein structure. We identified 90 VRVs, 71 of which have not previously been observed in a VOI/VOC, and 35 of which have emerged recently and are durably present. Our analysis identifies 17 VRVs [~]91 days earlier than their first corresponding VOI/VOC publication. Unsupervised learning revealed eight VRV-haplotypes of 4 VRVs or more, suggesting two emerging strains (B1.1.222 and B.1.234). Structural modeling supported potential functional impact of the D1118H and L452R mutations. The SLS approach equally monitors all Spike residues over time, independently of existing phylogenic classifications, and is complementary to existing genomic surveillance methods.

genomics↗