Changes in Transcript, Metabolite, and Antibody Reactivity During the Early Protective Immune Response in Humans to Mycobacterium tuberculosis Infection.

BACKGROUND: Strategies to prevent Mycobacterium tuberculosis (Mtb) infection are urgently required. In this study, we aimed to identify correlates of protection against Mtb infection. METHODS: Two groups of Mtb-exposed contacts of tuberculosis (TB) patients were recruited and classified according to their Mtb infection status using the tuberculin skin test (TST; cohort 1) or QuantiFERON (QFT; cohort 2). A negative reading at baseline with a positive reading at follow-up classified TST or QFT converters and a negative reading at both time points classified TST or QFT nonconverters. Ribonucleic acid sequencing, Mtb proteome arrays, and metabolic profiling were performed. RESULTS: Several genes were found to be differentially expressed at baseline between converters and nonconverters. Gene set enrichment analysis revealed a distinct B-cell gene signature in TST nonconverters compared to converters. When infection status was defined by QFT, enrichment of type I interferon was observed. A remarkable area under the curve (AUC) of 1.0 was observed for IgA reactivity to Rv0134 and an AUC of 0.98 for IgA reactivity to both Rv0629c and Rv2188c. IgG reactivity to Rv3223c resulted in an AUC of 0.96 and was markedly higher compared to TST nonconverters. We also identified several differences in metabolite profiles, including changes in biomarkers of inflammation, fatty acid metabolism, and bile acids. Pantothenate (vitamin B5) was significantly increased in TST nonconverters compared to converters at baseline (q = 0.0060). CONCLUSIONS: These data provide new insights into the early protective response to Mtb infection and possible avenues to interfere with Mtb infection, including vitamin B5 supplementation.Analysis of blood from highly exposed household contacts from The Gambia who never develop latent Mycobacterium tuberculosis infection shows distinct transcriptomic, antibody, and metabolomic profiles compared to those who develop latent tuberculosis infection but prior to any signs of infection

Completeness of tuberculosis case notifications in Germany in 2013–2017: first results of an inventory study

Background Evaluating the completeness of tuberculosis (TB) notification data is important for monitoring of TB surveillance systems. We conducted an inventory study to calculate TB underreporting in Germany in 2013–2017. Methods Acquisition of two pseudonymized case-based data sources (national TB notification data and antibiotic resistance surveillance data) was followed by two-source Capture-recapture (CRC) analysis, as case-based data from a third source was unavailable. Aggregated data on consumption of a key anti-TB drug (pyrazinamide [PZA]) was compared to an estimated need for PZA based on TB notification data to obtain an independent underreporting estimation. Additionally, notified TB incidence was compared to TB rate in an aggregated health insurance fund dataset. Results CRC and PZA-based approaches indicated that between 93 and 97% (CRC) and between 91 and 95% (PZA) of estimated cases were captured in the national TB notification data in the years 2013–2017. Insurance fund dataset did not indicate TB underreporting on the national level in 2017. Conclusions Our results suggest that more than 90% of estimated TB cases are captured within the German TB surveillance system, and accordingly the TB notification rate is likely a good proxy of the diagnosed TB incidence rate. An increase in underreporting and discrepancies however should be further investigated.Peer Reviewe

Vollständigkeit der Tuberkulose-Meldungen in Deutschland in den Jahren 2013 – 2017: Ergebnisse einer Inventurstudie

Für die Evaluation der Qualität von Tuberkulose-Meldesystemen ist die Bewertung der Vollständigkeit der Meldedaten von zentraler Bedeutung, da diese die Basis für eine aussagekräftige Tuberkulose-Surveillance und daraus abgeleitete Maßnahmen sind. Wie das Epidemiologische Bulletin 11/2021 beschreibt, wurde am Robert-Koch-Institut für den Zeitraum 2013-17 eine Inventarstudie zur Schätzung der Tuberkulose-Untererfassung in Deutschland durchgeführt. Das Ergebnis: mit einer Erfassungsquote von über 90% ist die Tuberkulose-Melderate trotz eines leichten Rückgangs innerhalb des untersuchten Zeitraums ein guter Näherungswert für die tatsächliche Tuberkulose-Inzidenz

Unraveling transcript-based variability of host responses to Tuberculosis

Jedes Jahr treten weltweit über zehn Millionen Fälle von Tuberkulose (TB) auf. Die Weltgesundheitsorganisation (WHO) schätzt, dass ein Drittel der Weltbevölkerung mit dem Erreger Mycobacterium tuberculosis (Mtb) infiziert ist. Bei fünf bis zehn Prozent aller latent Infizierten bricht Tuberkulose im Laufe des Lebens aus. Dennoch sind bereits 100 Jahre seit der Entdeckung von Mtb vergangen, ohne dass die entscheidenden Faktoren für den unterschiedlichen Infektionsverlauf bekannt wären. In dieser Arbeit untersuche ich die unterschiedlichen Reaktionen auf eine Tuberkuloseinfektion in verschiedenen Wirten. In meinem ersten Ansatz habe ich öffentlich zugängliche Transkriptom-Datensätze von Tuberkulosepatienten und gesunden Probanden ausgewertet. Mit Hilfe der Gensatzanreicherungs-Analyse (eng. Gene Set Enrichment Analysis, GSEA) habe ich die Transkriptionsprofile von Tuberkulosepatienten betrachtet. Das besondere Augenmerk lag hierbei auf der Interferon (IFN)-Signalkaskade, die für den Krankheitsverlauf von besonderer Bedeutung ist. In dieser Arbeit zeige ich zunächst, dass Patienten ohne eine IFN-Signatur in der untersuchten Kohorte vorkommen und widme mich im Anschluss der Frage, ob diese Patienten einen anderen Phänotypus haben als jene mit einer starken IFN-Antwort. Indem ich nur Patienten ohne IFN-Antwort betrachte, werden Mechanismen deutlich, die allen Patientengruppen gemein sind, aber vorher von der starken IFN-Signatur überlagert wurden. Ich belege in dieser Arbeit, dass eine starke IFN-Regulation auch mit einer ausgeprägten Lungenpathologie in Tuberkulosepatienten einhergeht. Passend hierzu weisen auch gesunde Probanden nach Verabreichung des Impfstoffs FLUAD® einen erhöhten Blutwert IFN-induzierter Zytokine auf. Mit Hilfe maschinellen Lernens konnte ich Transkriptomsignaturen der Patienten mit bzw. ohne IFN-Antwort identifizieren und vergleichen. Im zweiten Ansatz widme ich mich den unterschiedlichen Transkriptionsantworten auf Mtb-Infektionen in humanen Kohorten und zwei verschiedenen Mausmodellen. Der humanen und der murinen Immunantwort auf Infektionen unterliegen gravierende Unterschiede. Trotzdem sind einige Elemente des Immunsystems in beiden Arten konserviert. In dieser Arbeit präsentiere ich einen neuen Ansatz der Datenintegration, der die Identifizierung von übereinstimmenden und nicht übereinstimmenden Regulationselementen der Genexpression in heterogenen Datensätzen ermöglicht. Die Analyse basiert auf öffentlich zugänglichen sowie de-novo-generierten Datensätzen, zu denen ich durch wissenschaftliche Kollaborationen meiner Kollegen in der Abteilung Immunologie sowie der zentralen Einheit Microarray des Max-Planck-Instituts für Infektionsbiologie, Zugang erhalten habe. Des Weiteren liegt ein Schwerpunkt auf der vergleichenden Analyse humaner und muriner Transkriptionsantworten auf Tuberkulose in Vollblut und Makrophagen. Die erhaltenen Ergebnisse weisen auf einen signifikanten Unterschied in der Regulierung der angeborenen sowie der erworbenen Immunität in Mensch und Maus als Reaktion auf eine Mtb-Infektion hin. In dieser Arbeit charakterisiere ich die unterschiedliche Regulierung von T-Zell bezogenen Genen, die mit unterschiedlich ausgeprägten Phänotypen bei stark oder schwach TB-anfälligen Mausstämmen korrespondiert. Darüber hinaus habe ich den 21. Tag nach einer Tuberkuloseinfektion in Mäusen als Zeitpunkt ermittelt, der die Transkriptionsantworten in den untersuchten humanen Kohorten am besten widerspiegelt. Die angewandten Ansätze erleichtern die Auswahl des am besten geeigneten Tiermodells für die Erforschung der humanen Immunantwort auf eine ausgewählte Krankheit und liefern die Basis für ein besseres Verständnis der unterschiedlichen Krankheitsverläufe in Mtb-infizierten Patienten.Over 10 million tuberculosis (TB) cases are being reported annually and the World Health Organization (WHO) estimates that up to the 1/3 of the world population is infected with Mycobacterium tuberculosis (Mtb). Between 5 and 10% of the latently infected individuals develop TB during their lifetime. Yet, despite over 100 years of research since Mtb has been identified, we are not able to define all the factors which are responsible for the different infection outcomes in the hosts. In this thesis I investigate the variability in the response to TB presented by different hosts. In one approach, I collect publicly available transcriptomic datasets from TB patients and healthy donors. Using Gene Set Enrichment Analysis (GSEA) I examine transcriptional profiles of individuals with TB. In particular, focus is brought to interferon (IFN) signaling which has been previously described as crucial for the disease outcome. I show that patients lacking IFN signature are present in the studied cohorts and investigate whether these patients present different phenotype than patients with strong regulation of IFN responses. Moreover, by focusing on patients lacking IFN response I try to unearth mechanisms present in all patient groups but dominated by the signal of IFN response. I show that strong regulation of IFN genes is related to severe pathology in the lungs of TB patients and that it is reflected by the levels of IFN-inducible cytokines in blood of healthy volunteers after vaccination with FLUAD® vaccine. Using Machine Learning (ML) methods, I identify and compare transcriptomic signatures of the patients presenting and lacking the IFN response. In the second approach I study the differences in the transcriptional responses to Mtb infection in human cohorts and two different mouse models. The immunity in infection, inflammation and malignancy differs markedly in man and mouse. Nevertheless, there are elements of immune system which have been conserved between the species. I propose a novel data integration approach which identifies concordant and discordant elements of gene expression regulation in heterologous datasets. The analysis is based on publicly available as well as novel experimental data acquired thanks to collaboration with my colleagues from the Department of Immunology and Microarray Core Facility of Max Planck Institute for Infection Biology (MPIIB). Additionally, I focus on the comparison of human and murine transcriptional responses to TB in whole blood (WB) and in macrophages. The results indicate profound differences between regulation of innate and adaptive immunity in man and mouse upon Mtb infection. I characterize differential regulation of T-cell related genes corresponding to the differences in phenotype between TB high and low susceptible mouse strains and identify the time point of 21 days p.i. of mice as best reflection of transcriptional responses in the studied human cohorts. The implemented approaches facilitate the choice of an appropriate animal model for studies of the human immune response to a particular disease and provide the basis for better understanding of differences in the outcomes of Mtb infection in individual hosts

Gene Set Enrichment Analysis Reveals Individual Variability in Host Responses in Tuberculosis Patients

Group-aggregated responses to tuberculosis (TB) have been well characterized on a molecular level. However, human beings differ and individual responses to infection vary. We have combined a novel approach to individual gene set analysis (GSA) with the clustering of transcriptomic profiles of TB patients from seven datasets in order to identify individual molecular endotypes of transcriptomic responses to TB. We found that TB patients differ with respect to the intensity of their hallmark interferon (IFN) responses, but they also show variability in their complement system, metabolic responses and multiple other pathways. This variability cannot be sufficiently explained with covariates such as gender or age, and the molecular endotypes are found across studies and populations. Using datasets from a Cynomolgus macaque model of TB, we revealed that transcriptional signatures of different molecular TB endotypes did not depend on TB progression post-infection. Moreover, we provide evidence that patients with molecular endotypes characterized by high levels of IFN responses (IFN-rich), suffered from more severe lung pathology than those with lower levels of IFN responses (IFN-low). Harnessing machine learning (ML) models, we derived gene signatures classifying IFN-rich and IFN-low TB endotypes and revealed that the IFN-low signature allowed slightly more reliable overall classification of TB patients from non-TB patients than the IFN-rich one. Using the paradigm of molecular endotypes and the ML-based predictions allows more precisely tailored treatment regimens, predicting treatment-outcome with higher accuracy and therefore bridging the gap between conventional treatment and precision medicine.Peer Reviewe

COVID-19: cross-border contact tracing in Germany, February to April 2020

Since January 2020, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has rapidly spread to become a global pandemic [1]. Active case finding, early detection and isolation of cases and their contacts are essential for breaking transmission chains. A modelling study showed that 70% of contacts should be traced in order to control the outbreak, assuming a baseline reproduction rate of 2.5 [2]. Early warning systems for the serious cross-border spread of infectious pathogens include the International Health Regulations (IHR) 2005 and the Early Warning and Response System (EWRS) for the European Union/European Economic Area (EU/EEA) countries [3,4]. Within Germany, communication channels have been established in accordance with the German Infection Protection Act (Infektionsschutzgesetz; IfSG). Cross-border contact tracing at the national level is operated by the Robert Koch Institute (RKI), the federal public health institute in Germany. The first cases of coronavirus disease 2019 (COVID-19) in Germany occurred in Bavaria at the end of January 2020 [5]. The first SARS-CoV-2 cluster also led to cross-border contacts and exposures on flights since close contacts and suspected cases travelled to Austria and Spain after exposure. This required intensive international communication to identify and share the information on contacts with the responsible health authorities. An international communication and contact tracing team (RKI IC-Team) was rapidly created in the RKI COVID-19 Emergency Operations Centre (EOC) including members of all units of the department for infectious disease epidemiology and other departments at the RKI. The core task of the team was to collect and communicate information on confirmed COVID-19 cases and their contacts to other countries in the event of cross-border relevance. In addition, incoming information on German citizens exposed abroad was communicated through the federal state health authorities to the responsible local health authorities in Germany. The spread of SARS-CoV-2 in Germany triggered the introduction of various measures: (i) mass gatherings with more than 1,000 participants were banned after calendar week 10, (ii) schools and public places were closed in several federal states, (iii) physical distancing measures of at least 1.5 m to another person were recommended, (iv) it was recommended to cancel non-essential travel and (v) quarantine measures for travellers from high risk areas entering Germany were introduced in calendar week 15. Because of the federal structure in Germany, the measures and their implementation varied between the states. This work aimed to describe the extent and course of activities resulting from information on COVID-19 exposure events with a cross-border context. Further, we discuss the challenges experienced and possible workflow improvements.Peer Reviewe

Efficacy Testing of H56 cDNA Tattoo Immunization against Tuberculosis in a Mouse Model

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), remains a global threat. The only approved vaccine against TB, Mycobacterium bovis bacillus Calmette–Guérin (BCG), provides insufficient protection and, being a live vaccine, can cause disseminated disease in immunocompromised individuals. Previously, we found that intradermal cDNA tattoo immunization with cDNA of tetanus toxoid fragment C domain 1 fused to cDNA of the fusion protein H56, comprising the Mtb antigens Ag85B, ESAT-6, and Rv2660c, induced antigen-specific CD8+ T cell responses in vivo. As cDNA tattoo immunization would be safer than a live vaccine in immunocompromised patients, we tested the protective efficacy of intradermal tattoo immunization against TB with H56 cDNA, as well as with H56_E, a construct optimized for epitope processing in a mouse model. As Mtb antigens can be used in combination with BCG to boost immune responses, we also tested the protective efficacy of heterologous prime-boost, using dermal tattoo immunization with H56_E cDNA to boost BCG immunization in mice. Dermal H56 and H56_E cDNA immunization induced H56-specific CD4+ and CD8+ T cell responses and Ag85B-specific IgG antibodies, but did not reduce bacterial loads, although immunization with H56_E ameliorated lung pathology. Both subcutaneous and intradermal immunization with BCG resulted in broad cellular immune responses, with increased frequencies of CD4+ T effector memory cells, T follicular helper cells, and germinal center B cells, and resulted in reduced bacterial loads and lung pathology. Heterologous vaccination with BCG/H56_E cDNA induced increased H56-specific CD4+ and CD8+ T cell cytokine responses compared to vaccination with BCG alone, and lung pathology was significantly decreased in BCG/H56_E cDNA immunized mice compared to unvaccinated controls. However, bacterial loads were not decreased after heterologous vaccination compared to BCG alone. CD4+ T cells responding to Ag85B- and ESAT-6-derived epitopes were predominantly IFN-γ+TNF-α+ and TNF-α+IL-2+, respectively. In conclusion, despite inducing appreciable immune responses to Ag85B and ESAT-6, intradermal H56 cDNA tattoo immunization did not substantially enhance the protective effect of BCG under the conditions tested

The Henna pigment Lawsone activates the Aryl Hydrocarbon Receptor and impacts skin homeostasis

As a first host barrier, the skin is constantly exposed to environmental insults that perturb its integrity. Tight regulation of skin homeostasis is largely controlled by the aryl hydrocarbon receptor (AhR). Here, we demonstrate that Henna and its major pigment, the naphthoquinone Lawsone activate AhR, both in vitro and in vivo. In human keratinocytes and epidermis equivalents, Lawsone exposure enhances the production of late epidermal proteins, impacts keratinocyte differentiation and proliferation, and regulates skin inflammation. To determine the potential use of Lawsone for therapeutic application, we harnessed human, murine and zebrafish models. In skin regeneration models, Lawsone interferes with physiological tissue regeneration and inhibits wound healing. Conversely, in a human acute dermatitis model, topical application of a Lawsone-containing cream ameliorates skin irritation. Altogether, our study reveals how a widely used natural plant pigment is sensed by the host receptor AhR, and how the physiopathological context determines beneficial and detrimental outcomes.publishersversionpublishe

The Henna pigment Lawsone activates the Aryl Hydrocarbon Receptor and impacts skin homeostasis (vol 9, 10878, 2019)

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