Baseline gene signatures of reactogenicity to Ebola vaccination: a machine learning approach across multiple cohorts.

Introduction: The rVSVDG-ZEBOV-GP (Ervebo®) vaccine is both immunogenic and protective against Ebola. However, the vaccine can cause a broad range of transient adverse reactions, from headache to arthritis. Identifying baseline reactogenicity signatures can advance personalized vaccinology and increase our understanding of the molecular factors associated with such adverse events. Methods: In this study, we developed a machine learning approach to integrate prevaccination gene expression data with adverse events that occurred within 14 days post-vaccination. Results and Discussion: We analyzed the expression of 144 genes across 343 blood samples collected from participants of 4 phase I clinical trial cohorts: Switzerland, USA, Gabon, and Kenya. Our machine learning approach revealed 22 key genes associated with adverse events such as local reactions, fatigue, headache, myalgia, fever, chills, arthralgia, nausea, and arthritis, providing insights into potential biological mechanisms linked to vaccine reactogenicity.

Impaired resolution of blood transcriptomes through tuberculosis treatment with diabetes comorbidity.

BACKGROUND: People with diabetes are more likely to develop tuberculosis (TB) and to have poor TB-treatment outcomes than those without. We previously showed that blood transcriptomes in people with TB-diabetes (TB-DM) co-morbidity have excessive inflammatory and reduced interferon responses at diagnosis. It is unknown whether this persists through treatment and contributes to the adverse outcomes. METHODS: Pulmonary TB patients recruited in South Africa, Indonesia and Romania were classified as having TB-DM, TB with prediabetes, TB-related hyperglycaemia or TB-only, based on glycated haemoglobin concentration at TB diagnosis and after 6 months of TB treatment. Gene expression in blood at diagnosis and intervals throughout treatment was measured by unbiased RNA-Seq and targeted Multiplex Ligation-dependent Probe Amplification. Transcriptomic data were analysed by longitudinal mixed-model regression to identify whether genes were differentially expressed between clinical groups through time. Predictive models of TB-treatment response across groups were developed and cross-tested. RESULTS: Gene expression differed between TB and TB-DM patients at diagnosis and was modulated by TB treatment in all clinical groups but to different extents, such that differences remained in TB-DM relative to TB-only throughout. Expression of some genes increased through TB treatment, whereas others decreased: some were persistently more highly expressed in TB-DM and others in TB-only patients. Genes involved in innate immune responses, anti-microbial immunity and inflammation were significantly upregulated in people with TB-DM throughout treatment. The overall pattern of change was similar across clinical groups irrespective of diabetes status, permitting models predictive of TB treatment to be developed. CONCLUSIONS: Exacerbated transcriptome changes in TB-DM take longer to resolve during TB treatment, meaning they remain different from those in uncomplicated TB after treatment completion. This may indicate a prolonged inflammatory response in TB-DM, requiring prolonged treatment or host-directed therapy for complete cure. Development of transcriptome-based biomarker signatures of TB-treatment response should include people with diabetes for use across populations.

Repurposing Tamoxifen as Potential Host-Directed Therapeutic for Tuberculosis.

The global burden of tuberculosis (TB) is aggravated by the continuously increasing emergence of drug resistance, highlighting the need for innovative therapeutic options. The concept of host-directed therapy (HDT) as adjunctive to classical antibacterial therapy with antibiotics represents a novel and promising approach for treating TB. Here, we have focused on repurposing the clinically used anticancer drug tamoxifen, which was identified as a molecule with strong host-directed activity against intracellular Mycobacterium tuberculosis (Mtb). Using a primary human macrophage Mtb infection model, we demonstrate the potential of tamoxifen against drug-sensitive as well as drug-resistant Mtb bacteria. The therapeutic effect of tamoxifen was confirmed in an in vivo TB model based on Mycobacterium marinum infection of zebrafish larvae. Tamoxifen had no direct antimicrobial effects at the concentrations used, confirming that tamoxifen acted as an HDT drug. Furthermore, we demonstrate that the antimycobacterial effect of tamoxifen is independent of its well-known target the estrogen receptor (ER) pathway, but instead acts by modulating autophagy, in particular the lysosomal pathway. Through RNA sequencing and microscopic colocalization studies, we show that tamoxifen stimulates lysosomal activation and increases the localization of mycobacteria in lysosomes both in vitro and in vivo, while inhibition of lysosomal activity during tamoxifen treatment partly restores mycobacterial survival. Thus, our work highlights the HDT potential of tamoxifen and proposes it as a repurposed molecule for the treatment of TB. IMPORTANCE Tuberculosis (TB) is the world's most lethal infectious disease caused by a bacterial pathogen, Mycobacterium tuberculosis. This pathogen evades the immune defenses of its host and grows intracellularly in immune cells, particularly inside macrophages. There is an urgent need for novel therapeutic strategies because treatment of TB patients is increasingly complicated by rising antibiotic resistance. In this study, we explored a breast cancer drug, tamoxifen, as a potential anti-TB drug. We show that tamoxifen acts as a so-called host-directed therapeutic, which means that it does not act directly on the bacteria but helps the host macrophages combat the infection more effectively. We confirmed the antimycobacterial effect of tamoxifen in a zebrafish model for TB and showed that it functions by promoting the delivery of mycobacteria to digestive organelles, the lysosomes. These results support the high potential of tamoxifen to be repurposed to fight antibiotic-resistant TB infections by host-directed therapy.

Leptin mutation and mycobacterial infection lead non-synergistically to a similar metabolic syndrome.

INTRODUCTION: The leptin signaling pathway plays an important role as a key regulator of glucose homeostasis, metabolism control and systemic inflammatory responses. However, the metabolic effects of leptin on infectious diseases, for example tuberculosis (TB), are still little known. OBJECTIVES: In this study, we aim to investigate the role of leptin on metabolism in the absence and presence of mycobacterial infection in zebrafish larvae and mice. METHODS: Metabolites in entire zebrafish larvae and the blood of mice were studied using high-resolution magic-angle-spinning nuclear magnetic resonance (HR-MAS NMR) spectroscopy and mass spectrometry, respectively. For transcriptome studies of zebrafish larvae, deep RNA sequencing was used. RESULTS: The results show that leptin mutation leads to a similar metabolic syndrome as caused by mycobacterial infection in the two species, characterized by the decrease of 11 amine metabolites. In both species, this metabolic syndrome was not aggravated further when the leptin mutant was infected by mycobacteria. Therefore, we conclude that leptin and mycobacterial infection are both impacting metabolism non-synergistically. In addition, we studied the transcriptomes of lepbibl54 mutant zebrafish larvae and wild type (WT) siblings after mycobacterial infection. These studies showed that mycobacteria induced a very distinct transcriptome signature in the lepbibl54 mutant zebrafish compared to WT sibling control larvae. Furthermore, lepbibl55 Tg (pck1:luc1) zebrafish line was constructed and confirmed this difference in transcriptional responses. CONCLUSIONS: Leptin mutation and TB lead non-synergistically to a similar metabolic syndrome. Moreover, different transcriptomic responses in the lepbibl54  mutant and TB can lead to the similar metabolic end states.

Blood transcriptional profiles distinguish different clinical stages of cutaneous leishmaniasis in humans.

Cutaneous leishmaniasis (CL) is a neglected tropical disease with severe morbidity and socioeconomic sequelae. A better understanding of underlying immune mechanisms that lead to different clinical outcomes of CL could inform the rational design of intervention measures. While transcriptomic analyses of CL lesions were recently reported by us and others, there is a dearth of information on the expression of immune-related genes in the blood of CL patients. Herein, we investigated immune-related gene expression in whole blood samples collected from individuals with different clinical stages of CL along with healthy volunteers in an endemic CL region where Leishmania (L.) tropica is prevalent. Study participants were categorized into asymptomatic (LST+) and healthy uninfected (LST-) groups based on their leishmanin skin test (LST). Whole blood PAXgene samples were collected from volunteers, who had healed CL lesions, and patients with active L. tropica cutaneous lesions. Quality RNA extracted from 57 blood samples were subjected to Dual-color reverse-transcription multiplex ligation-dependent probe amplification (dcRT-MLPA) assay for profiling 144 immune-related genes. Results show significant changes in the expression of genes involved in interferon signaling pathway in the blood of active CL patients, asymptomatics and healed individuals. Nonetheless, distinct profiles for several immune-related genes were identified in the healed, the asymptomatic, and the CL patients compared to the healthy controls. Among others, IFI16 and CCL11 were found as immune transcript signatures for the healed and the asymptomatic individuals, respectively. These results warrant further exploration to pinpoint novel blood biomarkers for different clinical stages of CL.

Development of Human Cell-Based In Vitro Infection Models to Determine the Intracellular Survival of Mycobacterium avium.

The Mycobacterium avium (Mav) complex accounts for more than 80% of all pulmonary diseases caused by non-tuberculous mycobacteria (NTM) infections, which have an alarming increase in prevalence and vary in different regions, currently reaching 0.3-9.8 per 100,000 individuals. Poor clinical outcomes, as a result of increasing microbial drug resistance and low treatment adherence due to drug-toxicities, emphasize the need for more effective treatments. Identification of more effective treatments, however, appears to be difficult, which may be due to the intracellular life of NTM and concomitant altered drug sensitivity that is not taken into account using traditional drug susceptibility testing screenings. We therefore developed human cell-based in vitro Mav infection models using the human MelJuSo cell line as well as primary human macrophages and a fluorescently labeled Mav strain. By testing a range of multiplicity of infection (MOI) and using flow cytometry and colony-forming unit (CFU) analysis, we found that an MOI of 10 was the most suitable for Mav infection in primary human macrophages, whereas an MOI of 50 was required to achieve similar results in MelJuSo cells. Moreover, by monitoring intracellular bacterial loads over time, the macrophages were shown to be capable of controlling the infection, while MelJuSo cells failed to do so. When comparing the MGIT system with the classical CFU counting assay to determine intracellular bacterial loads, MGIT appeared as a less labor-intensive, more precise, and more objective alternative. Next, using our macrophage Mav infection models, the drug efficacy of the first-line drug rifampicin and the more recently discovered bedaquiline on intracellular bacteria was compared to the activity on extracellular bacteria. The efficacy of the antibiotics inhibiting bacterial growth was significantly lower against intracellular bacteria compared to extracellular bacteria. This finding emphasizes the crucial role of the host cell during infection and drug susceptibility and highlights the usefulness of the models. Taken together, the human cell-based Mav infection models are reliable tools to determine the intracellular loads of Mav, which will enable researchers to investigate host-pathogen interactions and to evaluate the efficacy of (host-directed) therapeutic strategies against Mav.

Transcriptional profiles predict treatment outcome in patients with tuberculosis and diabetes at diagnosis and at two weeks after initiation of anti-tuberculosis treatment.

BACKGROUND: Globally, the tuberculosis (TB) treatment success rate is approximately 85%, with treatment failure, relapse and death occurring in a significant proportion of pulmonary TB patients. Treatment success is lower among people with diabetes mellitus (DM). Predicting treatment outcome early after diagnosis, especially in TB-DM patients, would allow early treatment adaptation for individuals and may improve global TB control. METHODS: Samples were collected in a longitudinal cohort study of adult TB patients from South Africa (n  =  94) and Indonesia (n  =  81), who had concomitant DM (n  =  59), intermediate hyperglycaemia (n  =  79) or normal glycaemia/no DM (n  =  37). Treatment outcome was monitored, and patients were categorized as having a good (cured) or poor (failed, recurrence, died) outcome during treatment and 12 months follow-up. Whole blood transcriptional profiles before, during and at the end of TB treatment were characterized using unbiased RNA-Seq and targeted gene dcRT-MLPA. FINDINGS: We report differences in whole blood transcriptome profiles, which were observed before initiation of treatment and throughout treatment, between patients with a good versus poor TB treatment outcome. An eight-gene and a 22-gene blood transcriptional signature distinguished patients with a good TB treatment outcome from patients with a poor TB treatment outcome at diagnosis (AUC = 0·815) or two weeks (AUC = 0·834) after initiation of TB treatment, respectively. High accuracy was obtained by cross-validating this signature in an external cohort (AUC = 0·749). INTERPRETATION: These findings suggest that transcriptional profiles can be used as a prognostic biomarker for treatment failure and success, even in patients with concomitant DM. FUNDING: The research leading to these results, as part of the TANDEM Consortium, received funding from the European Community's Seventh Framework Programme (FP7/2007-2013 Grant Agreement No. 305279) and the Netherlands Organization for Scientific Research (NWO-TOP Grant Agreement No. 91214038). The research leading to the results presented in the Indian validation cohort was supported by Research Council of Norway Global Health and Vaccination Research (GLOBVAC) projects: RCN 179342, 192534, and 248042, the University of Bergen (Norway).

Recombinant BCG-LTAK63 Vaccine Candidate for Tuberculosis Induces an Inflammatory Profile in Human Macrophages.

Tuberculosis (TB) is one of the top 10 leading causes of death worldwide. The recombinant BCG strain expressing the genetically detoxified A subunit of the thermolabile toxin from Escherichia coli (LTAK63) adjuvant (rBCG-LTAK63) has previously been shown to confer superior protection and immunogenicity compared to BCG in a murine TB infection model. To further investigate the immunological mechanisms induced by rBCG-LTAK63, we evaluated the immune responses induced by rBCG-LTAK63, BCG, and Mycobacterium tuberculosis (Mtb) H37Rv strains in experimental infections of primary human M1 and M2 macrophages at the transcriptomic and cytokine secretion levels. The rBCG-LTAK63-infected M1 macrophages more profoundly upregulated interferon-inducible genes such as IFIT3, OAS3, and antimicrobial gene CXCL9 compared to BCG, and induced higher levels of inflammatory cytokines such as IL-12(p70), TNF-ß, and IL-15. The rBCG-LTAK63-infected M2 macrophages more extensively upregulated transcripts of inflammation-related genes, TAP1, GBP1, SLAMF7, TNIP1, and IL6, and induced higher levels of cytokines related to inflammation and tissue repair, MCP-3 and EGF, as compared to BCG. Thus, our data revealed an important signature of immune responses induced in human macrophages by rBCG-LTAK63 associated with increased inflammation, activation, and tissue repair, which may be correlated with a protective immune response against TB.

The effect of cold exposure on circulating transcript levels of immune genes in Dutch South Asian and Dutch Europid men.

OBJECTIVES: Although cold exposure is commonly believed to be causally related to acute viral respiratory infections, its effect on the immune system is largely unexplored. In this study, we determined transcript levels of a large panel of immune genes in blood before and after cold exposure. We included both Dutch Europid and Dutch South Asian men to address whether the immune system is differently regulated in the metabolically vulnerable South Asian population. METHODS: Fasted blood samples were obtained from nonobese Dutch Europid (n = 11; mean age 26 ± 3 y) and Dutch South Asian (n = 12; mean age 28 ± 3 y) men before and directly after short-term (∼2.5 h) mild cold exposure. Transcript levels of 144 immune genes were measured using a dual-color reverse transcriptase multiplex ligation-dependent probe amplification (dcRT-MLPA) assay. RESULTS: Cold exposure acutely upregulated mRNA levels of GNLY (+35%, P < 0.001) and PRF1 (+45%, P < 0.001), which encode cytotoxic proteins, and CCL4 (+8%, P < 0.01) and CCL5 (+5%, P < 0.05), both pro-inflammatory chemokines. At thermoneutrality, mRNA levels of four markers of the nucleotide-binding oligomerization domain (NOD)-like receptor (NLR)-family, involved in inflammasomes, were lower in Dutch South Asians compared to Dutch Europids, namely NLRP2 (-57%, P < 0.05), NLRP7 (-17%, P < 0.05), NLRP10 (-21%, P < 0.05), and NLRC4 (-23%, P < 0.05). CONCLUSIONS: Mild cold exposure acutely increases mRNA levels of genes involved in cytotoxicity of immune cells in blood. In addition, Dutch South Asians display lower circulating mRNA levels of inflammasome genes compared to Dutch Europids.

Transcriptomic signatures induced by the Ebola virus vaccine rVSVΔG-ZEBOV-GP in adult cohorts in Europe, Africa, and North America: a molecular biomarker study.

BACKGROUND: A recombinant vesicular stomatitis virus vector expressing the Zaire Ebola virus glycoprotein (rVSVΔG-ZEBOV-GP) vaccine has been reported as safe, immunogenic, and highly protective in a ring vaccination trial. We aimed to identify transcriptomic immune response biomarker signatures induced by vaccination and associated signatures with its immunogenicity and reactogenicity to better understand the potential mechanisms of action of the vaccine. METHODS: 354 healthy adult volunteers were vaccinated in randomised, double-blind, placebo-controlled trials in Europe (Geneva, Switzerland [November, 2014, to January, 2015]) and North America (USA [Dec 5, 2014, to June 23, 2015]), and dose-escalation trials in Africa (Lambaréné, Gabon [November, 2014, to January, 2015], and Kilifi, Kenya [December, 2014, to January, 2015]) using different doses of the recombinant vesicular stomatitis virus vector expressing the Zaire Ebola virus glycoprotein (rVSVΔG-ZEBOV-GP; 3 × 105 to 1 × 108 plaque-forming units [pfu]). Longitudinal transcriptomic responses (days 0, 1, 2, 3, 7, 14, and 28) were measured in whole blood using a targeted gene expression profiling platform (dual-colour reverse-transcriptase multiplex ligation-dependent probe amplification) focusing on 144 immune-related genes. The effect of time and dose on transcriptomic response was also assessed. Logistic regression with lasso regularisation was applied to identify host signatures with optimal discriminatory capability of vaccination at day 1 or day 7 versus baseline, whereas random-effects models and recursive feature elimination combined with regularised logistic regression were used to associate signatures with immunogenicity and reactogenicity. FINDINGS: Our results indicated that perturbation of gene expression peaked on day 1 and returned to baseline levels between day 7 and day 28. The magnitude of the response was dose-dependent, with vaccinees receiving a high dose (≥9 × 106 pfu) of rVSVΔG-ZEBOV-GP exhibiting the largest amplitude. The most differentially expressed genes that were significantly upregulated following vaccination consisted of type I and II interferon-related genes and myeloid cell-associated markers, whereas T cell, natural killer cell, and cytotoxicity-associated genes were downregulated. A gene signature associated with immunogenicity (common to all four cohorts) was identified correlating gene expression profiles with ZEBOV-GP antibody titres and a gene signatures associated with reactogenicity (Geneva cohort) was identified correlating gene expression profiles with an adverse event (ie, arthritis). INTERPRETATION: Collectively, our results identify and cross-validate immune-related transcriptomic signatures induced by rVSVΔG-ZEBOV-GP vaccination in four cohorts of adult participants from different genetic and geographical backgrounds. These signatures will aid in the rational development, testing, and evaluation of novel vaccines and will allow evaluation of the effect of host factors such as age, co-infection, and comorbidity on responses to vaccines. FUNDING: Innovative Medicines Initiative 2 Joint Undertaking.

Stratification of COVID-19 patients based on quantitative immune-related gene expression in whole blood.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes mild symptoms in the majority of infected individuals, yet in some cases it leads to a life-threatening condition. Determination of early predictive biomarkers enabling risk stratification for coronavirus disease 2019 (COVID-19) patients can inform treatment and intervention strategies. Herein, we analyzed whole blood samples obtained from individuals infected with SARS-CoV-2, varying from mild to critical symptoms, approximately one week after symptom onset. In order to identify blood-specific markers of disease severity status, a targeted expression analysis of 143 immune-related genes was carried out by dual-color reverse transcriptase multiplex ligation-dependent probe amplification (dcRT-MLPA). The clinically well-defined subgroups of COVID-19 patients were compared with healthy controls. The transcriptional profile of the critically ill patients clearly separated from that of healthy individuals. Moreover, the number of differentially expressed genes increased by severity of COVID-19. It was also found that critically ill patients can be distinguished by reduced peripheral blood expression of several genes, which most likely reflects the lower lymphocyte counts. There was a notable predominance of IFN-associated gene expression in all subgroups of COVID-19, which was most profound in critically ill patients. Interestingly, the gene encoding one of the main TNF-receptors, TNFRS1A, had selectively lower expression in mild COVID-19 cases. This report provides added value in understanding COVID-19 disease, and shows potential of determining early immune transcript signatures in the blood of patients with different disease severity. These results can guide further explorations to uncover mechanisms underlying immunity and immunopathology in COVID-19.

Single-cell analysis reveals chemokine-mediated differential regulation of monocyte mechanics.

Monocytes continuously adapt their shapes for proper circulation and elicitation of effective immune responses. Although these functions depend on the cell mechanical properties, the mechanical behavior of monocytes is still poorly understood and accurate physiologically relevant data on basic mechanical properties are lacking almost entirely. By combining several complementary single-cell force spectroscopy techniques, we report that the mechanical properties of human monocyte are strain-rate dependent, and that chemokines can induce alterations in viscoelastic behavior. In addition, our findings indicate that human monocytes are heterogeneous mechanically and this heterogeneity is regulated by chemokine CCL2. The technology presented here can be readily used to reveal mechanical complexity of the blood cell population in disease conditions, where viscoelastic properties may serve as physical biomarkers for disease progression and response to therapy.

Recombinant BCG-LTAK63 vaccine candidate for tuberculosis induces an inflammatory profile in human macrophages

Tuberculosis (TB) is one of the top 10 leading causes of death worldwide. The recombinant BCG strain expressing the genetically detoxified A subunit of the thermolabile toxin from Escherichia coli (LTAK63) adjuvant (rBCG-LTAK63) has previously been shown to confer superior protection and immunogenicity compared to BCG in a murine TB infection model. To further investigate the immunological mechanisms induced by rBCG-LTAK63, we evaluated the immune responses induced by rBCG-LTAK63, BCG, and Mycobacterium tuberculosis (Mtb) H37Rv strains in experimental infections of primary human M1 and M2 macrophages at the transcriptomic and cytokine secretion levels. The rBCG-LTAK63-infected M1 macrophages more profoundly upregulated interferon-inducible genes such as IFIT3, OAS3, and antimicrobial gene CXCL9 compared to BCG, and induced higher levels of inflammatory cytokines such as IL-12(p70), TNF-β, and IL-15. The rBCG-LTAK63-infected M2 macrophages more extensively upregulated transcripts of inflammation-related genes, TAP1, GBP1, SLAMF7, TNIP1, and IL6, and induced higher levels of cytokines related to inflammation and tissue repair, MCP-3 and EGF, as compared to BCG. Thus, our data revealed an important signature of immune responses induced in human macrophages by rBCG-LTAK63 associated with increased inflammation, activation, and tissue repair, which may be correlated with a protective immune response against TB.

Metabolomic and transcriptomic profiling of adult mice and larval zebrafish leptin mutants reveal a common pattern of changes in metabolites and signaling pathways.

BACKGROUND: Leptin plays a critical role in the regulation of metabolic homeostasis. However, the molecular mechanism and cross talks between leptin and metabolic pathways leading to metabolic homeostasis across different species are not clear. This study aims to explore the effects of leptin in mice and zebrafish larvae by integration of metabolomics and transcriptomics. Different metabolomic approaches including mass spectrometry, nuclear magnetic resonance (NMR) and high-resolution magic-angle-spinning NMR spectrometry were used to investigate the metabolic changes caused by leptin deficiency in mutant ob/ob adult mice and lepb-/- zebrafish larvae. For transcriptome studies, deep RNA sequencing was used. RESULTS: Thirteen metabolites were identified as common biomarkers discriminating ob/ob mice and lepb-/- zebrafish larvae from their respective wild type controls: alanine, citrulline, ethanolamine, glutamine, glycine, histidine, isoleucine, leucine, methionine, phenylalanine, putrescine, serine and threonine. Moreover, we also observed that glucose and lipid levels were increased in lepb-/- zebrafish larvae compared to the lepb+/+ group. Deep sequencing showed that many genes involved in proteolysis and arachidonic acid metabolism were dysregulated in ob/ob mice heads and lepb mutant zebrafish larvae compared to their wild type controls, respectively. CONCLUSIONS: Leptin deficiency leads to highly similar metabolic alterations in metabolites in both mice and zebrafish larvae. These metabolic changes show similar features as observed during progression of tuberculosis in human patients, mice and zebrafish larvae. In addition, by studying the transcriptome, we found similar changes in gene regulation related to proteolysis and arachidonic acid metabolism in these two different in vivo models.

Host-directed therapy to combat mycobacterial infections.

Upon infection, mycobacteria, such as Mycobacterium tuberculosis (Mtb) and nontuberculous mycobacteria (NTM), are recognized by host innate immune cells, triggering a series of intracellular processes that promote mycobacterial killing. Mycobacteria, however, have developed multiple counter-strategies to persist and survive inside host cells. By manipulating host effector mechanisms, including phagosome maturation, vacuolar escape, autophagy, antigen presentation, and metabolic pathways, pathogenic mycobacteria are able to establish long-lasting infection. Counteracting these mycobacteria-induced host modifying mechanisms can be accomplished by host-directed therapeutic (HDT) strategies. HDTs offer several major advantages compared to conventional antibiotics: (a) HDTs can be effective against both drug-resistant and drug-susceptible bacteria, as well as potentially dormant mycobacteria; (b) HDTs are less likely to induce bacterial drug resistance; and (c) HDTs could synergize with, or shorten antibiotic treatment by targeting different pathways. In this review, we will explore host-pathogen interactions that have been identified for Mtb for which potential HDTs impacting both innate and adaptive immunity are available, and outline those worthy of future research. We will also discuss possibilities to target NTM infection by HDT, although current knowledge regarding host-pathogen interactions for NTM is limited compared to Mtb. Finally, we speculate that combinatorial HDT strategies can potentially synergize to achieve optimal mycobacterial host immune control.

Human Transcriptomic Response to the VSV-Vectored Ebola Vaccine.

Ebolavirus Disease (EVD) is a severe haemorrhagic fever that occurs in epidemic outbreaks, with a high fatality rate and no specific therapies available. rVSVΔG-ZEBOV-GP (Ervebo®), a live-attenuated recombinant vesicular stomatitis virus vector expressing the glycoprotein G of Zaire Ebolavirus, is the first vaccine approved for prevention of EVD. Both innate and adaptive responses are deemed to be involved in vaccine-induced protection, yet the mechanisms are not fully elucidated. A global transcriptomic approach was used to profile the blood host-response in 51 healthy volunteers enrolled in a phase 1/2 clinical trial. Signatures of the host responses were investigated assessing the enrichment in differentially expressed genes (DEGs) of specific "blood transcription modules" (BTM). Comparison of gene-expression levels showed that vaccination produces a peak of 5469 DEGs at day one, representing 38.6% of the expressed genes. Out of 346 BTMs, 144 were significantly affected by vaccination. Innate immunity pathways were induced from day 1 to day 14. At days 2 and 3, neutrophil modules were downregulated and complement-related modules upregulated. T-cell and cell-cycle associated modules were upregulated at days 7 and 14, while at day 28, no modules remained activated. At day 14, a direct correlation was observed between ZEBOV glycoprotein-specific antibody titres and activation of seven BTMs, including two related to B-cell activation and B cell receptor signalling. Transcriptomic analysis identified an rVSVΔG-ZEBOV-GP-induced signature and demonstrated a direct correlation of blood transcriptomic changes with ZEBOV glycoprotein-specific antibody titres.

Bioorthogonal Correlative Light-Electron Microscopy of Mycobacterium tuberculosis in Macrophages Reveals the Effect of Antituberculosis Drugs on Subcellular Bacterial Distribution.

Bioorthogonal correlative light-electron microscopy (B-CLEM) can give a detailed overview of multicomponent biological systems. It can provide information on the ultrastructural context of bioorthogonal handles and other fluorescent signals, as well as information about subcellular organization. We have here applied B-CLEM to the study of the intracellular pathogen Mycobacterium tuberculosis (Mtb) by generating a triply labeled Mtb through combined metabolic labeling of the cell wall and the proteome of a DsRed-expressing Mtb strain. Study of this pathogen in a B-CLEM setting was used to provide information about the intracellular distribution of the pathogen, as well as its in situ response to various clinical antibiotics, supported by flow cytometric analysis of the bacteria, after recovery from the host cell (ex cellula). The RNA polymerase-targeting drug rifampicin displayed the most prominent effect on subcellular distribution, suggesting the most direct effect on pathogenicity and/or viability, while the cell wall synthesis-targeting drugs isoniazid and ethambutol effectively rescued bacterial division-induced loss of metabolic labels. The three drugs combined did not give a more pronounced effect but rather an intermediate response, whereas gentamicin displayed a surprisingly strong additive effect on subcellular distribution.

Erratum: Author Correction: Rapid dose-dependent Natural Killer (NK) cell modulation and cytokine responses following human rVSV-ZEBOV Ebolavirus vaccination.

[This corrects the article DOI: 10.1038/s41541-020-0179-4.].

An alternative model for type I interferon induction downstream of human TLR2.

Surface-exposed Toll-like receptors (TLRs) such as TLR2 and TLR4 survey the extracellular environment for pathogens. TLR activation initiates the production of various cytokines and chemokines, including type I interferons (IFN-I). Downstream of TLR4, IFNß secretion is only vigorously triggered in macrophages when the receptor undergoes endocytosis and switches signaling adaptor; surface TLR4 engagement predominantly induces proinflammatory cytokines via the signaling adaptor MyD88. It is unclear whether this dichotomy is generally applicable to other TLRs, cell types, or differentiation states. Here, we report that diverse TLR2 ligands induce an IFN-I response in human monocyte-like cells, but not in differentiated macrophages. This TLR2-dependent IFN-I signaling originates from the cell surface and depends on MyD88; it involves combined activation of the transcription factors IRF3 and NF-κB, driven by the kinases TBK1 and TAK1-IKKß, respectively. TLR2-stimulated monocytes produced modest IFNß levels that caused productive downstream signaling, reflected by STAT1 phosphorylation and expression of numerous interferon-stimulated genes. Our findings reveal that the outcome of TLR2 signaling includes an IFN-I response in human monocytes, which is lost upon macrophage differentiation, and differs mechanistically from IFN-I-induction through TLR4. These findings point to molecular mechanisms tailored to the differentiation state of a cell and the nature of receptors activated to control and limit TLR-triggered IFN-I responses.

Combining host-derived biomarkers with patient characteristics improves signature performance in predicting tuberculosis treatment outcomes.

Tuberculosis (TB) is a global health concern. Treatment is prolonged, and patients on anti-TB therapy (ATT) often experience treatment failure for various reasons. There is an urgent need to identify signatures for early detection of failure and initiation of a treatment switch.We investigated how gene biomarkers and/or basic patient characteristics could be used to define signatures for treatment outcomes in Indian adult pulmonary-TB patients treated with standard ATT. Using blood samples at baseline, a 12-gene signature combined with information on gender, previously-diagnosed TB, severe thinness, smoking and alcohol consumption was highly predictive of treatment failure at 6 months. Likewise a 4-protein biomarker signature combined with the same patient characteristics was almost as highly predictive of treatment failure. Combining biomarkers and basic patient characteristics may be useful for predicting and hence identification of treatment failure at an early stage of TB therapy.