Sample pooling for SARS-CoV-2 RT-PCR screening.

OBJECTIVE: To evaluate the efficacy of sample pooling compared to the individual analysis for the diagnosis of coronavirus disease 2019 (COVID-19) by using different commercial platforms for nucleic acid extraction and amplification. METHODS: A total of 3519 nasopharyngeal samples received at nine Spanish clinical microbiology laboratories were processed individually and in pools (342 pools of ten samples and 11 pools of nine samples) according to the existing methodology in place at each centre. RESULTS: We found that 253 pools (2519 samples) were negative and 99 pools (990 samples) were positive; with 241 positive samples (6.85%), our pooling strategy would have saved 2167 PCR tests. For 29 pools (made out of 290 samples), we found discordant results when compared to their correspondent individual samples, as follows: in 22 of 29 pools (28 samples), minor discordances were found; for seven pools (7 samples), we found major discordances. Sensitivity, specificity and positive and negative predictive values for pooling were 97.10% (95% confidence interval (CI), 94.11-98.82), 100%, 100% and 99.79% (95% CI, 99.56-99.90) respectively; accuracy was 99.80% (95% CI, 99.59-99.92), and the kappa concordant coefficient was 0.984. The dilution of samples in our pooling strategy resulted in a median loss of 2.87 (95% CI, 2.46-3.28) cycle threshold (Ct) for E gene, 3.36 (95% CI, 2.89-3.85) Ct for the RdRP gene and 2.99 (95% CI, 2.56-3.43) Ct for the N gene. CONCLUSIONS: We found a high efficiency of pooling strategies for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA testing across different RNA extraction and amplification platforms, with excellent performance in terms of sensitivity, specificity and positive and negative predictive values.

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.

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.

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.

Procalcitonin and neopterin correlation with aetiology and severity of pneumonia.

OBJECTIVE: Clinical outcome of pneumonia depends on a multifaceted treatment approach. Not only diagnostic methods but also early indicators of the degree of inflammatory response can aid in therapeutic decisions. The objective was to evaluate the usefulness of procalcitonin and neopterin in distinguishing among aetiologies as well as severity in patients with pneumonia. PATIENTS: A total of one hundred sixteen patients with clinical, radiographic and microbiological diagnosis of pneumonia were grouped by aetiology, pneumonia severity index, and by the presence of unilobar or multilobar radiographic pulmonary infiltrates. Procalcitonin and neopterin were measured by immunoassays. RESULTS: Patients with pneumococcal pneumonia presented elevated procalcitonin and neopterin levels, being higher in bacteraemic than in non-bacteraemic pneumonia. Patients with Legionella pneumonia presented elevated neopterin levels and slightly elevated procalcitonin levels. Patients with tuberculosis and Pneumocystis jirovecii pneumonia presented elevated neopterin and low or not detectable procalcitonin. Procalcitonin and neopterin levels were increased in high-risk classes of pneumonia severity index. Both parameters yielded significant correlation to the radiographic extent and also to young age. CONCLUSIONS: Procalcitonin and neopterin levels vary depending on age, aetiology and severity of pneumonia. Together with clinical and microbiological data, combined measurement can help to identify patients who might benefit from additional therapies.

Catalase-peroxidase activity has no influence on virulence in a murine model of tuberculosis.

The capacity to generate a chronic and persistent infection in the experimental murine model of tuberculosis induced aerogenically by a low-dose inoculum was determined in eight isoniazid-resistant clinical strains of Mycobacterium tuberculosis showing different catalase-peroxidase (C-P) activities. Determination of bacillary concentration in lung and spleen and the percentage of pulmonary parenchyma occupied by granulomas were monitored. Data showed no relation between the lack of C-P activity and the ability to develop a persistent infection, highlighting the potential of C-P negative strains to spread through the community.

Widespread bronchogenic dissemination makes DBA/2 mice more susceptible than C57BL/6 mice to experimental aerosol infection with Mycobacterium tuberculosis.

We have used the murine model of aerosol-induced experimental tuberculosis to assess the effects of four clinical isolates and a reference strain of Mycobacterium tuberculosis on resistant C57BL/6 mice and susceptible DBA/2 mice. Histological studies and detection of 25 cytokines potentially involved in the infection were carried out. DBA/2 mice showed higher concentrations of bacilli in bronchoalveolar lavage fluid and lung tissue. Furthermore, these mice evidenced a larger granulomatous infiltration in the parenchyma due to an increased rate of emigration of infected foamy macrophages from the granulomas to the neighboring pulmonary alveolar spaces. The better control of bacillary concentrations and pulmonary infiltration observed in C57BL/6 mice from week 3 postinfection could result from their higher RANTES, ICAM-1, and gamma interferon (IFN-gamma) mRNA levels. On the other hand, the higher MIP-2 and MCP-3 mRNA levels seen in DBA/2 mice would result in stronger lung recruitment of macrophages and neutrophils. Additionally, DBA/2 mice showed increased inducible nitric oxide synthase expression, induced by the larger number of foamy macrophages, at weeks 18 and 22. This increment was a consequence of phagocytosed bacillary debris, was independent of IFN-gamma expression, and could exert only a bacteriostatic effect. The results of the study suggest that DBA/2 mice are more susceptible than C57BL/6 mice to M. tuberculosis infection due to a higher bronchial dissemination of bacilli inside poorly activated foamy macrophages.