Contribution and Future of High-Throughput Transcriptomics in Battling Tuberculosis.

While Tuberculosis (TB) infection remains a serious challenge worldwide, big data and "omic" approaches have greatly contributed to the understanding of the disease. Transcriptomics have been used to tackle a wide variety of queries including diagnosis, treatment evolution, latency and reactivation, novel target discovery, vaccine response or biomarkers of protection. Although a powerful tool, the elevated cost and difficulties in data interpretation may hinder transcriptomics complete potential. Technology evolution and collaborative efforts among multidisciplinary groups might be key in its exploitation. Here, we discuss the main fields explored in TB using transcriptomics, and identify the challenges that need to be addressed for a real implementation in TB diagnosis, prevention and therapy.

An RNA-seq Based Machine Learning Approach Identifies Latent Tuberculosis Patients With an Active Tuberculosis Profile.

A better understanding of the response against Tuberculosis (TB) infection is required to accurately identify the individuals with an active or a latent TB infection (LTBI) and also those LTBI patients at higher risk of developing active TB. In this work, we have used the information obtained from studying the gene expression profile of active TB patients and their infected -LTBI- or uninfected -NoTBI- contacts, recruited in Spain and Mozambique, to build a class-prediction model that identifies individuals with a TB infection profile. Following this approach, we have identified several genes and metabolic pathways that provide important information of the immune mechanisms triggered against TB infection. As a novelty of our work, a combination of this class-prediction model and the direct measurement of different immunological parameters, was used to identify a subset of LTBI contacts (called TB-like) whose transcriptional and immunological profiles are suggestive of infection with a higher probability of developing active TB. Validation of this novel approach to identifying LTBI individuals with the highest risk of active TB disease merits further longitudinal studies on larger cohorts in TB endemic areas.

Identification of candidate host serum and saliva biomarkers for a better diagnosis of active and latent tuberculosis infection.

In our work, we aim to identify new candidate host biomarkers to discriminate between active TB patients (n = 28), latent infection (LTBI; n = 27) and uninfected (NoTBI; n = 42) individuals. For that, active TB patients and their contacts were recruited that donated serum and saliva samples. A multiplex assay was performed to study the concentration of different cytokines, chemokines and growth factors. Proteins with significant differences between groups were selected and logistic regression and the area under the ROC curve (AUC) was used to assess the diagnostic accuracy. The best marker combinations that discriminate active TB from NoTBI contacts were [IP-10 + IL-7] in serum and [Fractalkine + IP-10 + IL-1α + VEGF] in saliva. Best discrimination between active TB and LTBI was achieved using [IP-10 + BCA-1] in serum (AUC = 0.83) and IP-10 in saliva (p = 0.0007; AUC = 0.78). The levels of TNFα (p = 0.003; AUC = 0.73) in serum and the combination of [Fractalkine+IL-12p40] (AUC = 0.83) in saliva, were able to differentiate between NoTBI and LTBI contacts. In conclusion, different individual and combined protein markers could help to discriminate between active TB and both uninfected and latently-infected contacts. The most promising ones include [IP-10 + IL-7], [IP-10 + BCA-1] and TNFα in serum and [Fractalkine + IP-10 + IL-1α + VEGF], IP-10 and [Fractalkine+IL-12p40] in saliva.

Multi-parameter flow cytometry immunophenotyping distinguishes different stages of tuberculosis infection.

OBJECTIVES: To identify new potential host biomarkers in blood to discriminate between active TB patients, uninfected (NoTBI) and latently infected contacts (LTBI). METHODS: A blood cell count was performed to study parent leukocyte populations. Peripheral blood mononuclear cells (PBMCs) were isolated and a multi-parameter flow cytometry assay was conducted to study the distribution of basal and Mycobacterium tuberculosis (Mtb)-stimulated lymphocytes. Differences between groups and the area under the ROC curve (AUC) were investigated to assess the diagnostic accuracy. RESULTS: Active TB patients presented higher Monocyte-to-lymphocyte and Neutrophil-to-lymphocyte ratios than LTBI and NoTBI contacts (p<0.0001; AUC>0.8). Lymphocyte subsets with differences (p >0.05; AUC >0.7) between active TB and both contact groups include the basal distribution of Th1/Th2 ratio, Th1-Th17, CD4+ Central Memory (TCM) or MAIT cells. Expression of CD154 is increased in Mtb-activated CD4+ TCM and Effector Memory T cells in active TB and LTBI compared to NoTBI. In CD4+T cells, expression of CD154 showed a higher accuracy than IFNγ to discriminate Mtb-specific activation. CONCLUSIONS: We identified different cell subsets with potential use in tuberculosis diagnosis. Among them, distribution of CD4 TCM cells and their expression of CD154 after Mtb-activation are the most promising candidates.

Serum proteomics of active tuberculosis patients and contacts reveals unique processes activated during Mycobacterium tuberculosis infection.

Tuberculosis (TB) is the most lethal infection among infectious diseases. The specific aim of this study was to establish panels of serum protein biomarkers representative of active TB patients and their household contacts who were either infected (LTBI) or uninfected (EMI-TB Discovery Cohort, Pontevedra Region, Spain). A TMT (Tamdem mass tags) 10plex-based quantitative proteomics study was performed in quintuplicate containing a total of 15 individual serum samples per group. Peptides were analyzed in an LC-Orbitrap Elite platform, and raw data were processed using Proteome Discoverer 2.1. A total of 418 proteins were quantified. The specific protein signature of active TB patients was characterized by an accumulation of proteins related to complement activation, inflammation and modulation of immune response and also by a decrease of a small subset of proteins, including apolipoprotein A and serotransferrin, indicating the importance of lipid transport and iron assimilation in the progression of the disease. This signature was verified by the targeted measurement of selected candidates in a second cohort (EMI-TB Verification Cohort, Maputo Region, Mozambique) by ELISA and nephelometry techniques. These findings will aid our understanding of the complex metabolic processes associated with TB progression from LTBI to active disease.

Changes in the Immune Phenotype and Gene Expression Profile Driven by a Novel Tuberculosis Nanovaccine: Short and Long-Term Post-immunization.

Deciphering protection mechanisms against Mycobacterium tuberculosis (Mtb) remains a critical challenge for the development of new vaccines and therapies. We analyze the phenotypic and transcriptomic profile in lung of a novel tuberculosis (TB) nanoparticle-based boosting mucosal vaccine Nano-FP1, which combined to BCG priming conferred enhanced protection in mice challenged with low-dose Mtb. We analyzed the vaccine profile and efficacy at short (2 weeks), medium (7 weeks) and long term (11 weeks) post-vaccination, and compared it to ineffective Nano-FP2 vaccine. We observed several changes in the mouse lung environment by both nanovaccines, which are lost shortly after boosting. Additional boosting at long-term (14 weeks) recovered partially cell populations and transcriptomic profile, but not enough to enhance protection to infection. An increase in both total and resident memory CD4 and CD8 T cells, but no pro-inflammatory cytokine levels, were correlated with better protection. A unique gene expression pattern with differentially expressed genes revealed potential pathways associated to the immune defense against Mtb. Our findings provide an insight into the critical immune responses that need to be considered when assessing the effectiveness of a novel TB vaccine.

High-resolution quantitative proteomics applied to the study of the specific protein signature in the sputum and saliva of active tuberculosis patients and their infected and uninfected contacts.

Our goal was to establish panels of protein biomarkers that are characteristic of patients with microbiologically confirmed pulmonary tuberculosis (TB) and their contacts, including latent TB-infected (LTBI) and uninfected patients. Since the first pathogen-host contact occurs in the oral and nasal passages the saliva and sputum were chosen as the biological fluids to be studied. Quantitative shotgun proteomics was performed using a LTQ-Orbitrap-Elite platform. For active TB patients, both fluids exhibited a specific accumulation of proteins that were related to complement activation, inflammation and modulation of immune response. In the saliva of TB patients, a decrease of in proteins related to glucose and lipid metabolism was detected. In contrast, the sputum of uninfected contacts presented a specific proteomic signature that was composed of proteins involved in the perception of bitter taste, defense against pathogens and innate immune response, suggesting that those are key events during the initial entry of the pathogen in the host. SIGNIFICANCE: This is the first study to compare the saliva and sputum from active TB patients and their contacts. Our findings strongly suggest that TB patients show not only an activation of processes that are related to complement activation and modulation of inflammation but also an imbalance in carbohydrate and lipid metabolism. In addition, those individuals who do not get infected after direct exposure to the pathogen display a typical proteomic signature in the sputum, which is a reflection of the secretion from the nasal and oral mucosa, the first immunological barriers that M. tuberculosis encounters in the host. Thus, this result indicates the importance of the processes related to the innate immune response in fighting the initial events of the infection.

Genomic structure and expression of immunoglobulins in Squamata.

The Squamata order represents a major evolutionary reptile lineage, yet the structure and expression of immunoglobulins in this order has been scarcely studied in detail. From the genome sequences of four Squamata species (Gekko japonicus, Ophisaurus gracilis, Pogona vitticeps and Ophiophagus hannah) and RNA-seq datasets from 18 other Squamata species, we identified the immunoglobulins present in these animals as well as the tissues in which they are found. All Squamata have at least three immunoglobulin classes; namely, the immunoglobulins M, D, and Y. Unlike mammals, however, we provide evidence that some Squamata lineages possess more than one Cµ gene which is located downstream from the Cδ gene. The existence of two evolutionary lineages of immunoglobulin Y is shown. Additionally, it is demonstrated that while all Squamata species possess the λ light chain, only Iguanidae species possess the κ light chain.

Amphibians have immunoglobulins similar to ancestral IgD and IgA from Amniotes.

We studied the immunoglobulin genes from either the genomes or RNAs of amphibians. In particular, we obtained data from one frog genome (Nanorana parkeri) and three transcriptomes of the Caudata order (Andrias davidianus, Notophthalmus viridescens and Cynops pyrrhogaster). Apart from the immunoglobulins IgM and IgY previously described, we identified several IgD related immunoglobulins. The species N. parkeri, N. viridescens and C. pyrrhogaster have two IgD genes, while Andrias davidianus has three such genes. The three Caudata species have long IgD immunoglobulins similar to IgD of reptiles, and could be an ancient relic from the common ancestor of IgD of all mammals and reptiles. We also found two IgA isotypes. The results suggest that one of the IgA may be the ancestor of IgA in crocodiles and birds, while the other could be the ancestor IgA found in mammals. These results provide information that could help understand the evolution of immunoglobulins in terrestrial vertebrates.

Tratamiento de la depresión con maprotilina en dosis única: un estudio abierto / Treatment of depresion with single doses of maprotiline: an open study

El presente ensayo, consistió en un estudio abierto, no comparativo de los efectos clínicos de 75 mgrs. de Maprotilina, en pacientes con Depresión Neurótica y en Reacciones Depresivas de Adaptación, cuya intensidad no hacía necesaria la hospitalización. El control de los pacientes, se realizó en la Consulta Externa del Servicio de Psiquiatría del Hospital Vargas de Caracas. Los autores evaluaron a los pacientes semanalmente, a partir del inicio del tratamiento. Para cuantificar los cambios ocurridos, se utilizó la Escola de Hamilton para depresión y un protocolo que contiene datos relativos a la evolución clínica, tratamientos previos, exploraciones cardiovasculares y de laboratorio, datos biográficos y escalas de evaluación para el médico y el paciente, que incluye el control de efectos colaterales atribuibles al medicamento. Al final del ensayo, casi las tres cuartas partes de la muestra presentó mejoría marcada en tanto que los restantes lo hicieron levemente. Se presentaron efectos secundarios leves en seis pacientes, que desaparecieron después de la segunda semana de tratamiento