Biology subjects

Boom, W. H.

Publications and source records attributed to Boom, W. H..

9 recordsLinked to original sources

bioRxiv2026

Human memory CD4+ T cells recognize non-infected macrophage bystanders exposed to Mycobacterium tuberculosis-infected cells

Control of Mycobacterium tuberculosis (Mtb) infection requires CD4+ T cell recognition of infected macrophages. However, T cells also colocalize with non-infected macrophages in granulomas. We investigated whether these bystander macrophages present Mtb antigens and shape human CD4+ T cell responses. Using ex vivo co-culture systems, non-infected monocyte-derived macrophages (MDMs) were exposed to Mtb-infected MDMs or infection-conditioned supernatants before co-incubation with autologous memory CD4+ T cells from individuals with latent Mtb infection (LTBI). Bystander macrophages activated memory CD4+ T cells through MHC-II-dependent antigen presentation. Single-cell T cell receptor (TCR) sequencing and TCR-transduced reporter cell lines identified Mtb-specific clonotypes recognizing both infected and bystander macrophages, as well as clonotypes preferentially recognizing infected cells. Strikingly, a subset of TCRs recognized infected but not bystander macrophages. Antigen transfer occurred through soluble Mtb proteins rather than extracellular vesicles. Compared with responses to infected macrophages, bystander macrophages induced attenuated effector responses. These findings reveal antigen-specific recognition of bystander macrophages and suggest that antigens preferentially presented by infected cells may inform TB vaccine design.

immunology↗

bioRxiv2025

Distinct antibody-based signatures and functionality distinguish latent and active pediatric tuberculosis

BackgroundTuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), is among the leading causes of death from an infectious agent among children worldwide. Children represent a particularly vulnerable population due to the greater challenges in diagnosis and the higher risk of progression to severe forms of the disease. However, whether different pediatric outcomes relate to distinct immunologic responses remains incompletely understood. Emerging data suggest that Mtb-specific humoral immune responses represent a correlate of protection against Mtb both following natural infection and vaccination. MethodsTo determine if immune profiles can distinguish children across the spectrum from Mtb infection to TB disease, as well as children with TB from non-TB lower respiratory tract infection, we mapped the humoral immune response across a panel of 4 dozen Mtb antigens across children presenting with symptoms of active TB (ATB), children with evidence of latent TB infection (LTBI) and children exhibiting non-TB lower respiratory tract infection (non-TB LRTI). Using a custom Luminex assay, Mtb-specific antibody subclass/isotype, Fc receptor (FcR) binding profiles, and functions were profiled across the pediatric groups. FindingsA robust humoral immune response was observed in children with active TB compared to non-TB LRTI, marked by a strong IgA response, that exhibited high FcR binding. Conversely, children with LTBI uniquely elicited Mtb-specific antibodies with enhanced opsinophagocytic Fc{gamma}R2A binding, as well as a higher capacity to activate NK cells and neutrophils. InterpretationThere are significant differences in humoral immune profiles across the landscape of pediatric TB, potentially contributing to differential mycobacterial control, and highlighting biomarkers that could guide both diagnostic and therapeutic approaches. FundingUS National Institutes of Health.

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↗

bioRxiv2024

Epigenetic programming of host lipid metabolism associates with resistance to TST/IGRA conversion after exposure to Mycobacterium tuberculosis

Mycobacterium tuberculosis (Mtb) exposure leads to a range of outcomes including clearance, latent TB infection (LTBI), and pulmonary tuberculosis (TB). Some heavily exposed individuals resist tuberculin skin test (TST) and interferon gamma release assay (IGRA) conversion (RSTR), which suggests that they employ IFN{gamma}-independent mechanisms of Mtb control. Here, we compare monocyte epigenetic profiles of RSTR and LTBI from a Ugandan household contact cohort. Chromatin accessibility did not differ between uninfected RSTR and LTBI monocytes. In contrast, methylation significantly differed at 174 CpG sites and across 63 genomic regions. Consistent with previous transcriptional findings in this cohort, differential methylation was enriched in lipid and cholesterol associated pathways including in the genes APOC3, KCNQ1, and PLA2G3. In addition, methylation was enriched in Hippo signaling, which is associated with cholesterol homeostasis and includes CIT and SHANK2. Lipid export and Hippo signaling pathways were also associated with gene expression in response to Mtb in RSTR as well as IFN stimulation in monocyte-derived macrophages (MDMs) from an independent healthy donor cohort. Moreover, serum-derived HDL from RSTR had elevated ABCA1-mediated cholesterol efflux capacity (CEC) compared to LTBI. Our findings suggest that resistance to TST/IGRA conversion is linked to regulation of lipid accumulation in monocytes, which could facilitate early Mtb clearance among RSTR subjects through IFN{gamma}-independent mechanisms. IMPORTANCETuberculosis (TB) remains an enduring global health challenge with millions of deaths and new cases each year. Despite recent advances in TB treatment, we lack an effective vaccine or a durable cure. While heavy exposure to Mycobacterium tuberculosis often results in latent TB latent infection (LTBI), subpopulations exist who are either resistant to infection or contain Mtb with IFN{gamma}-independent mechanisms not indicative of LTBI. These resisters provide an opportunity to investigate mechanisms of TB disease and discover novel therapeutic targets. Here, we compare monocyte epigenetic profiles of RSTR and LTBI from a Ugandan household contact cohort. We identify methylation signatures in host lipid and cholesterol pathways with potential relevance to early TB clearance before the sustained IFN responses indicative of LTBI. This adds to a growing body of literature linking TB disease outcomes to host lipids.

immunology↗

bioRxiv2023

HIV co-infection is associated with reduced Mycobacterium tuberculosis transmissibility in sub-Saharan Africa

Persons living with HIV are known to be at increased risk of developing tuberculosis (TB) disease upon infection with Mycobacterium tuberculosis (Mtb). However, it has remained unclear how HIV co-infection affects subsequent Mtb transmission from these patients. Here, we customized a Bayesian phylodynamic framework to estimate the effects of HIV co-infection on the Mtb transmission dynamics from sequence data. We applied our model to four Mtb genomic datasets collected in sub-Saharan African countries with a generalized HIV epidemic. Our results confirm that HIV co-infection is a strong risk factor for developing active TB. Additionally, we demonstrate that HIV co-infection is associated with a reduced effective reproductive number for TB. Stratifying the population by CD4+ T-cell count yielded similar results, suggesting that, in this context, CD4+ T-cell count is not a better predictor of Mtb transmissibility than HIV infection status. Together, our genome-based analyses complement observational household studies, and firmly establish the negative association between HIV co-infection and Mtb transmissibility. Author summaryMany sub-Saharan African countries have seen a considerable rise in TB incidence since the introduction of HIV, suggesting a strong interaction between HIV and TB epidemics. HIV infection is recognized as an important risk factor for developing TB, but the contribution of HIV-infected TB patients to further Mtb transmission is poorly understood. In this study, we analyzed four sets of Mtb genomic sequences collected in different countries, including sequences from HIV-negative and HIV-positive TB patients. We applied a phylodynamic model to these sequences, aimed at inferring transmission dynamics within and between different host populations. While our findings support that HIV is a strong risk factor for TB, we show that HIV-positive TB patients generate a significantly lower number of secondary TB cases than HIV-negative patients. This suggests that HIV-positive patients often act as sinks in Mtb transmission chains, while HIV-negative patients are a major source of transmission.

microbiology↗

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↗

bioRxiv2021

TLR2 on CD4+ and CD8+ T cells promotes late control of Mycobacterium tuberculosis infection

Although a role for TLR2 on T cells has been indicated in prior studies, in vivo stimulation of TLR2 on T cells by Mtb and its impact on Mtb infection has not been tested. Furthermore, it is not known if the enhanced susceptibility to Mtb of Tlr2 gene knockout (ko) mice is due to its role in macrophages, on T cells or both. To address TLR2 on T cells, we generated Tlr2fl/flxCd4cre/cre mice, which lack expression of TLR2 on both CD4 and CD8 T cells, to study the in vivo role of TLR2 on T cells after aerosol infection with virulent Mtb. Deletion of TLR2 in CD4+ and CD8+ T cells reduces their ability to be co-stimulated by TLR2 ligands for cytokine production. These include both pro-(IFN-{gamma}, TNF-) and anti-inflammatory cytokines (IL-10). Deletion of TLR2 in T cells did not affect early control but did result in decreased late control of Mtb in the lungs of infected mice. This suggests that T cell co-stimulation by mycobacterial TLR2 ligands in vivo is important for control of infection during the chronic phase of Mtb infection in the lung.

immunology↗

bioRxiv2019

Interaction between host genes and M. tuberculosis lineage can affect tuberculosis severity: evidence for co-evolution

Genetic studies of both the human host and Mycobacterium tuberculosis (MTB) demonstrate independent association with tuberculosis (TB) risk. However, neither explains a large portion of disease risk or severity. Based on studies in other infectious diseases and animal models of TB, we hypothesized that the genomes of the two interact to modulate risk of developing active TB or increasing the severity of disease, when present. We examined this hypothesis in our TB household contact study in Kampala, Uganda, in which there were 3 MTB lineages of which L4-Ugandan (L4.6) is the most recent. TB severity, measured using the Bandim TBscore, was modeled as a function of host SNP genotype, MTB lineage, and their interaction, within two independent cohorts of TB cases, N=113 and 122. No association was found between lineage and severity, but association between multiple polymorphisms in IL12B and TBscore was replicated in two independent cohorts (most significant rs3212227, combined p=0.0006), supporting previous associations of IL12B with TB susceptibility. We also observed significant interaction between a single nucleotide polymorphism (SNP) in SLC11A1 and the L4-Ugandan lineage in both cohorts (rs17235409, meta p=0.0002). Interestingly, the presence of the L4-Uganda lineage in the presence of the ancestral human allele associated with more severe disease. These findings demonstrate that IL12B is associated with severity of TB in addition to susceptibility, and that the association between TB severity and human genetics can be due to an interaction between genes in the two species, providing evidence of host-pathogen coevolution in TB.\n\nAUTHOR SUMMARYSusceptibility to tuberculosis (TB) is affected by genetic variation in both the human host and the causative bacterium, Mycobacterium tuberculosis. However, prior studies of the genetics of each species have not explained a large part of TB risk. The possibility exists that risk can be better estimated from patterns of variation in two species as a unit, such that some combinations provide increased risk, or in the presence of TB, increased disease severity. We hypothesized that alleles in the two species that have co-existed for long periods are more likely to reduce disease severity so as to promote prolonged co-occurrence. We tested this by studying TB severity in two patient cohorts from Uganda for which paired MTB-human DNA were available. We examined severity, as measured by the Bandim TBscore, and assessed whether there was an interaction between MTB lineage and SNPs in the host with this metric. Our results indicate that the most recent TB lineage (L4.6/Uganda) when found together with an ancestral allele in SLC11A1 resulted in more severe disease. This finding is consistent with the conclusion that MTB and human have coevolved to modulate TB severity.

evolutionary biology↗