Changes in Mycobacterium tuberculosis-Specific Immunity With Influenza co-infection at Time of TB Diagnosis.

Background: Prior Influenza A viral (IAV) infection has been shown to increase susceptibility to tuberculosis (TB) and TB has also been shown to be a primary cause of death during pandemics, including the Spanish Influenza outbreak of 1918-1919. The majority of data has been obtained from mouse models, thus the aim of this study was to determine the impact of Flu co-infection on host immunity and disease severity in TB patients at diagnosis. Methods: Sputum from 282 patients with active TB were analyzed for presence of FluA/FluB RNA at presentation using multiplex PCR. Sputum RNA was also analyzed for Mycobacterium tuberculosis (Mtb) load using 16S RNA amplification. Supernatants from digested sputum and Mtb antigen-stimulated whole blood were analyzed using multiplex cytokine arrays and PBMC were analyzed for cytokine production from CD4+ T, CD8+ T and Mucosal Associated Invariant T cells (MAITs). Results: 12 (4.3%) of TB patients were found to have FluA or FluB viral RNA present in their sputum at the time of TB diagnosis. The TB/Flu co-infected patients had a significantly higher bacterial load compared to those with TB mono-infection (p = 0.0026). They had lower levels of IL17A in ex vivo sputum (p = 0.0275) and higher MCP-1 (CCL2) levels in the blood following PPD stimulation (p = 0.0267). TB/Flu co-infected subjects had significantly higher IFN-γ+IL-17+CD4+ and IFN-γ+IL-17-CD8+ cells compared to TB mono-infected subjects. Conclusions: These data show that Flu co-infection at time of TB diagnosis is associated with a higher bacterial load and differential cellular and soluble profiles. These findings show for the first time the impact of TB/Flu co-infection in a human cohort and support the potential benefit of Flu vaccination in TB-endemic settings

Perception and knowledge of the effect of climate change on infectious diseases within the general public: A multinational cross-sectional survey-based study

Infectious diseases are emerging and re-emerging due to climate change. Understanding how climate variability affects the transmission of infectious diseases is important for both researchers and the general public. Yet, the widespread knowledge of the general public on this matter is unknown, and quantitative research is still lacking. A survey was designed to assess the knowledge and perception of 1) infectious diseases, 2) climate change and 3) the effect of climate change on infectious diseases. Participants were recruited via convenience sampling, and an anonymous cross-sectional survey with informed consent was distributed to each participant. Descriptive and inferential analyses were performed primarily focusing on the occupational background as well as nationality of participants. A total of 458 individuals participated in this study, and most participants were originally from Myanmar, the Netherlands, Spain, United Kingdom and the United States. Almost half (44%) had a background in natural sciences and had a higher level of knowledge on infectious diseases compared to participants with non-science background (mean score of 12.5 and 11.2 out of 20, respectively). The knowledge of the effect of climate change on infectious diseases was also significantly different between participants with and without a background in natural sciences (13.1 and 11.8 out of 20, respectively). The level of knowledge on various topics was highly correlated with nationality but not associated with age. The general population demonstrated a high awareness and strong knowledge of climate change regardless of their background in natural sciences. This study exposes a knowledge gap in the general public regarding the effect of climate change on infectious diseases, and highlights that different levels of knowledge are observed in groups with differing occupations and nationalities. These results may help to develop awareness interventions for the general public

An easy to use tool for the analysis of subcellular mRNA transcript colocalisation in smFISH data

Single molecule fluorescence in situ hybridisation (smFISH) has become a valuable tool to investigate the mRNA expression of single cells. However, it requires a considerable amount of programming expertise to use currently available open-source analytical software packages to extract and analyse quantitative data about transcript expression. Here, we present FISHtoFigure, a new software tool developed specifically for the analysis of mRNA abundance and co-expression in QuPath-quantified, multi-labelled smFISH data. FISHtoFigure facilitates the automated spatial analysis of transcripts of interest, allowing users to analyse populations of cells positive for specific combinations of mRNA targets without the need for computational image analysis expertise. As a proof of concept and to demonstrate the capabilities of this new research tool, we have validated FISHtoFigure in multiple biological systems. We used FISHtoFigure to identify an upregulation in the expression of Cd4 by T-cells in the spleens of mice infected with influenza A virus, before analysing more complex data showing crosstalk between microglia and regulatory B-cells in the brains of mice infected with Trypanosoma brucei brucei. These analyses demonstrate the ease of analysing cell expression profiles using FISHtoFigure and the value of this new tool in the field of smFISH data analysis

An easy to use tool for the analysis of subcellular mRNA transcript colocalisation in smFISH data

Single molecule fluorescence in situ hybridisation (smFISH) has become a valuable tool to investigate the mRNA expression of single cells. However, it requires a considerable amount of programming expertise to use currently available open-source analytical software packages to extract and analyse quantitative data about transcript expression. Here, we present FISHtoFigure, a new software tool developed specifically for the analysis of mRNA abundance and co-expression in QuPath-quantified, multi-labelled smFISH data. FISHtoFigure facilitates the automated spatial analysis of transcripts of interest, allowing users to analyse populations of cells positive for specific combinations of mRNA targets without the need for computational image analysis expertise. As a proof of concept and to demonstrate the capabilities of this new research tool, we have validated FISHtoFigure in multiple biological systems. We used FISHtoFigure to identify an upregulation in the expression of Cd4 by T-cells in the spleens of mice infected with influenza A virus, before analysing more complex data showing crosstalk between microglia and regulatory B-cells in the brains of mice infected with Trypanosoma brucei brucei. These analyses demonstrate the ease of analysing cell expression profiles using FISHtoFigure and the value of this new tool in the field of smFISH data analysis

Single cell and spatial transcriptomic analyses reveal microglia-plasma cell crosstalk in the brain during Trypanosoma brucei infection

Human African trypanosomiasis, or sleeping sickness, is caused by the protozoan parasite Trypanosoma brucei and induces profound reactivity of glial cells and neuroinflammation when the parasites colonise the central nervous system. However, the transcriptional and functional responses of the brain to chronic T. brucei infection remain poorly understood. By integrating single cell and spatial transcriptomics of the mouse brain, we identify that glial responses triggered by infection are readily detected in the proximity to the circumventricular organs, including the lateral and 3rd ventricle. This coincides with the spatial localisation of both slender and stumpy forms of T. brucei. Furthermore, in silico predictions and functional validations led us to identify a previously unknown crosstalk between homeostatic microglia and Cd138+ plasma cells mediated by IL-10 and B cell activating factor (BAFF) signalling. This study provides important insights and resources to improve understanding of the molecular and cellular responses in the brain during infection with African trypanosomes

γδ T cells control murine skin inflammation and subcutaneous adipose wasting during chronic Trypanosoma brucei infection

African trypanosomes colonise the skin to ensure parasite transmission. However, how the skin responds to trypanosome infection remains unresolved. Here, we investigate the local immune response of the skin in a murine model of infection using spatial and single cell transcriptomics. We detect expansion of dermal IL-17A-producing Vγ6+ cells during infection, which occurs in the subcutaneous adipose tissue. In silico cell-cell communication analysis suggests that subcutaneous interstitial preadipocytes trigger T cell activation via Cd40 and Tnfsf18 signalling, amongst others. In vivo, we observe that female mice deficient for IL-17A-producing Vγ6+ cells show extensive inflammation and limit subcutaneous adipose tissue wasting, independently of parasite burden. Based on these observations, we propose that subcutaneous adipocytes and Vγ6+ cells act in concert to limit skin inflammation and adipose tissue wasting. These studies provide new insights into the role of γδ T cell and subcutaneous adipocytes as homeostatic regulators of skin immunity during chronic infection

Changes in Host Cytokine Patterns of TB Patients with Different Bacterial Loads Detected Using 16S rRNA Analysis.

Tuberculosis (TB) has overtaken HIV as the biggest infectious disease killer, with the majority of deaths occurring in sub-Saharan Africa. However it is unknown how differences in bacterial load alter host immune profiles in the sputum and blood of TB patients.16S ribosomal RNA analysis was used to determine bacterial load in sputum samples obtained from 173 patients with active TB (57 pre-treatment and 116 post-treatment). Host analyte concentrations in sputum and Mycobacterium tuberculosis (Mtb) antigen stimulated whole blood assay supernatants were analysed using multiplex cytokine arrays.Multiple logistic regression adjusting for age, sex and HIV status showed highly significant correlation of bacterial load with IL1β, IL2, IL1RA, IL4, IL6, IL8, IL9, IL15, IL17, EOTAX, FGF, IFN-γ, GCSF, MCP1, M1P1α, M1P1β, PDGF, TNFα, VEGF in sputum. With increasing time on treatment, FGF levels in sputum displayed the most significant inverse correlation with reduction in bacterial load.We show that differences in bacterial load correlates with changes in several host biomarkers. These findings have implications for development of tests for TB diagnosis and treatment response

Integrative single cell and spatial transcriptomic analysis reveal reciprocal microglia-plasma cell crosstalk in the mouse brain during chronic Trypanosoma brucei infection

This repository contains the scripts and processed rds necessary for the analysis of the manuscript titled "Integrative single cell and spatial transcriptomic analysis reveal reciprocal microglia-plasma cell crosstalk in the mouse brain during chronic Trypanosoma brucei infection" Abstract: Human African trypanosomiasis, or sleeping sickness, is caused by the protozoan parasite Trypanosoma brucei and induces profound reactivity of glial cells and neuroinflammation when the parasites colonise the central nervous system. However, the transcriptional and functional responses of the brain tochronic T. brucei infection remain poorly understood. By integrating single cell and spatial transcriptomics of the mouse brain, we identified that glial responses triggered by infection are readily detected in the proximity to the circumventricular organs, including the lateral and 3rd ventricle. This coincides with the spatial localisation of both slender and stumpy forms of T. brucei. Furthermore, in silico predictions and functional validations led us to identify a previously unknown crosstalk between homeostatic Cx3cr1+ microglia and Cd138+ plasma cells mediated by IL-10 and B cell activating factor (BAFF) signalling. This study provides important insights and resources to improve understanding of the molecular and cellular responses in the brain during infection with African trypanosomes

Heatmap of cytokine profiles in patients with low and high bacterial loads.

<p>Cytokine levels (pg/ml) for unstimulated (NIL) and sputum supernatants were analysed using a 27-plex cytokine array. Subjects were grouped into those with low bacterial load (below the median of 48059 copies/ml) and high bacterial load (above median). Data were analysed using a Mann-Whitney U-test. NS = not significant. Colour indicates low (blue) to high (red) cytokine levels.</p

Correlation of MBL and host cytokines in blood and sputum.

<p>Bacterial load was analysed for each sputum sample and correlated with host biomarkers (pg/ml) in the same sputum sample and also in Mtb-stimulated and unstimulated blood using a 27-plex cytokine assay. R-values >0.4 are highlighted in yellow and significant p-values in purple. Data were analysed using a Spearman Rank Correlation. Correlation of Time-on treatment with host biomarkers in sputum was also performed.</p