Biology subjects

Queiroz, A.

Publications and source records attributed to Queiroz, A..

5 recordsLinked to original sources

bioRxiv2026

Early tuberculosis treatment remodels blood mRNA and small RNA, and a baseline host signature is associated with early culture conversion

Tuberculosis (TB) treatment monitoring relies on sputum-based microbiological assays, which are slow and provide limited insight into the host response. Blood-based biomarkers could offer rapid and minimally invasive treatment monitoring. We performed an integrative multi-omics analysis of paired whole-blood samples collected at baseline and four weeks after treatment initiation across three South African cohorts. A meta-analysis combined RNA sequencing data from GSE89403 (86 pairs) and a prospective cohort (11 pairs), with directional concordance assessed in an independent microarray cohort, GSE31348 (27 pairs). In the prospective cohort, small RNA sequencing profiled microRNAs (miRNAs) and tRNA-derived fragments (tRFs). In GSE89403 (n = 76), a k-top scoring pairs signature (EARLY5) was developed using leave-one-out cross-validation to predict week-4 sputum culture conversion from baseline samples. The meta-analysis identified 63 concordantly regulated genes. These changes reflected attenuation of neutrophil, inflammatory and complement programs, and deconvolution showed decreased neutrophils with increased T-cell and NK-cell populations. Seven miRNAs and eight nuclear-encoded tRFs changed during treatment, including erythroid-associated miR-144, with computationally identified candidate interactions involving complement genes. EARLY5 identified participants who converted by week 4 with a cross-validated AUC of 0.76 and remained associated with conversion after adjustment for baseline bacterial burden in logistic regression and performed comparably to existing TB signatures. Early TB treatment induces coordinated remodeling of blood mRNA and small RNA profiles. Baseline host transcriptional profiles were associated with early culture conversion after accounting for bacterial burden, supporting further evaluation in independent cohorts.

immunology↗

bioRxiv2025

Two distinct cytokine response clusters identified in healthcare workers with apparent resistance to infection with Mycobacterium tuberculosis despite sustained occupational exposure

IntroductionEvidence exists that some individuals resist ("Resisters") Mycobacterium tuberculosis (Mtb) infection despite sustained exposure, but the protective mechanisms involved are not fully understood. We investigated immune responses induced by ex vivo stimulation of peripheral blood mononuclear cells (PBMC) with live Mtb in Resisters compared to those with latent TB infection (LTBI). MethodsHIV-uninfected healthcare workers working in high TB exposure healthcare facilities for over 5 years were screened for Mtb sensitization using the interferon-gamma release assay (IGRA) and the tuberculin skin test (TST). We identified Resisters (TST<10mm and IGRA<0.35 IU/mL, n=129) and those with LTBI (TST[≥]10mm and IGRA[≥]0.35 IU/mL n=145). We selected a subset of extreme resisters (TST=0mm and IGRA<0.2 IU/mL; n=26) and extreme LTBI (TST[≥]15mm and IGRA[≥]1 IU/mL; n=24) for these analyses. Blood was collected and PBMC isolated and cultured with live H37Rv Mtb for 18 hours. Supernatants were collected and used for measuring 65 secreted analytes by Luminex. We also evaluated cell-associated cytokine expression by CD4 T cells and monocytes in these participants using flow cytometry. ResultsUsing the feature selection in R, we identified a set of 4 cytokines: IL-17A, MCP-1, IL-8, and MDC, which collectively classified extreme Resisters from extreme LTBI with an area-under-the-curve (AUC) of 0.67 (0.54-0.85). Focusing only on the extreme Resisters, and using hierarchical clustering, participants in this group segregated into two main clusters (Resister_c1 and Resister_c2). Further analyses identified 37 cytokines that were significantly higher and 15 cytokines that were lower in Resister_c2 compared with Resister_c1. A set of 5 cytokines (TRAIL, MIP-1{beta}, Fractalkine, GRO- and IL-1) collectively classified these two clusters with an AUC of 1 (1-1). CD4 T cell and monocyte responses to Mtb did not significantly differ between the two clusters. ConclusionsMtb-specific immune responses segregate extreme Resisters into two distinct clusters in individuals with apparent resistance to Mtb infection and may allow discrimination of individuals with true resistance from those with infection but have alternative immune responses not detected by IGRA and TST.

immunology↗

bioRxiv2021

CD4 T cells are rapidly depleted from tuberculosis granulomas following acute SIV co-infection

The HIV-mediated decline in circulating CD4 T cells correlates with increased the risk of active tuberculosis (TB)1-4. However, HIV/Mycobacterium tuberculosis (Mtb) co-infected individuals also have an increased incidence of TB prior to loss of CD4 T cells in blood3,5, raising the possibility that HIV co-infection leads to disruption of CD4 T cell responses at the site of lung infection before they are observed systemically. Here we used a rhesus macaque model of SIV/Mtb co-infection to study the early effects of acute SIV infection on CD4 T cells in pulmonary Mtb granulomas. Two weeks after SIV co-infection CD4 T cells were dramatically depleted from granulomas, before significant bacterial outgrowth, disease reactivation as measured by PET-CT imaging, or CD4 T cell loss in blood, airways, and lymph nodes. Mtb-specific CD4 T cells, CCR5-expressing, in granulomas were preferentially depleted by SIV infection. Moreover, CD4 T cells were preferentially depleted from the granuloma core and lymphocyte cuff relative to B cell-rich regions, and live imaging of granuloma explants showed that SIV co-infection reduced T cell motility. Thus, Mtb-specific CD4 T cells in pulmonary granulomas may be decimated before many patients even experience the first symptoms of acute HIV infection.

immunology↗

bioRxiv2019

Systems biology analysis of publicly available transcriptomic data reveals a critical link between AKR1B10 gene expression, smoking and occurrence of lung cancer

BackgroundCigarette smoking is associated with increased risk of developing respiratory diseases and various types of cancer. Early identification of such unfavorable outcomes in patients who smoke is critical for optimizing personalized medical care.\n\nMethodsHere, we perform a comprehensive analysis using Systems Biology tools of publicly available data from a total of six transcriptomic studies, which examined different specimens of lung tissue and/or cells of smokers and nonsmokers to identify potential markers associated with lung cancer.\n\nResultsExpression level of twenty-two genes was capable of classifying smokers from non-smokers. A machine learning algorithm revealed that AKR1B10 was the most informative gene among the 22 DEGs accounting for the classification of the clinical groups. AKR1B10 expression was higher in smokers compared to non-smokers in datasets examining small and large airway epithelia, but not in the data from a study of sorted alveolar macrophages. We next tested whether AKR1B10 expression could be useful in identification of cancer tissue in patients who were not exposed to smoking. AKR1B10 expression was substantially higher in lung cancer specimens compared to matched healthy tissue obtained from nonsmoking individuals (accuracy: 80%, p<0.0001). Finally, we searched the expression of 11 single nucleotide polymorphisms (SNPs) of AKR1B10 worldwide. We found that the SNP rs782881 was the most frequent mutant allele in the majority of continents. Africa was the continent which exhibited higher frequency of SNPs associated with lower AKR1B10 expression and displayed lower lung cancer incidence and deaths attributable to tobacco.\n\nConclusionThe systematic analysis of transcriptomic studies performed here revealed a potential critical link between AKR1B10 expression, smoking and occurrence of lung cancer.

genomics↗

bioRxiv2019

Rainfall and other meteorological factors as drivers of urban transmission of leptospirosis

BackgroundLeptospirosis is an important public health problem affecting vulnerable urban slum populations in developing country settings. However, the complex interaction of meteorological factors driving the temporal trends of leptospirosis remain incompletely understood.\n\nMethods and findingsFrom 1996 to 2010, we investigated the association between the weekly incidence of leptospirosis and climatic variables in the city of Salvador, Brazil by using a dynamic generalized linear model that accounted for time lags, overall trend and seasonal variation. Our model showed an increase of leptospirosis cases associated with rainfall, lower temperature and higher humidity. There was a lag of one-to-two weeks between weekly values for significant meteorological variables and leptospirosis incidence. Independent of the season, a weekly cumulative rainfall of 20 mm increased the risk of the leptospirosis by 10% compared to a week without rain. Finally, over the 14 year study period the incidence of leptospirosis decreased significantly by four fold (12.8 versus 3.6 per 100,000 people), independently of variations in climate.\n\nConclusionsStrategies to control leptospirosis should focus on avoiding contact with contaminated sources of Leptospira as well as on increasing awareness in the population and health professionals within the short time window after both low-level and extreme rainfall events. Increased leptospirosis incidence was restricted to one-to-two weeks after those events suggesting that infectious Leptospira survival may be limited to short time intervals.\n\nAuthor SummaryTo determine the role of meteorological variables, seasonal variation and temporal trends in the incidence of leptospirosis, we investigated the time series of leptospirosis incidence amongst residents of Salvador, Brazil, from 1996 to 2010. Exploratory and confirmatory statistical methods detected associations between meteorological factors and disease incidence. Results showed the importance of extreme meteorological conditions, particularly rainfall, as short-term predictors of leptospirosis incidence. In addition, we found a long-term decreasing trend of in disease incidence over the observation period.

epidemiology↗