Diagnostic 'omics' for active tuberculosis

Clinical metabolomics by NMR revealed serum metabolic signatures for differentiating sarcoidosis from tuberculosis

BACKGROUND

Pulmonary sarcoidosis (SAR) and tuberculosis (TB) are two granulomatous lung-diseases and often pose a diagnostic challenge to a treating physicians.

OBJECTIVE

The present study aims to explore the diagnostic potential of NMR based serum metabolomics approach to differentiate SAR from TB.

MATERIALS AND METHOD

The blood samples were obtained from three study groups: SAR (N = 35), TB (N = 28) and healthy normal subjects (NC, N = 56) and their serum metabolic profiles were measured using 1D 1H CPMG (Carr-Purcell-Meiboom-Gill) NMR spectra recorded at 800 MHz NMR spectrometer. The quantitative metabolic profiles were compared employing a combination of univariate and multivariate statistical analysis methods and evaluated for their diagnostic potential using receiver operating characteristic (ROC) curve analysis.

RESULTS

Compared to SAR, the sera of TB patients were characterized by (a) elevated levels of lactate, acetate, 3-hydroxybutyrate (3HB), glutamate and succinate (b) decreased levels of glucose, citrate, pyruvate, glutamine, and several lipid and membrane metabolites (such as very-low/low density lipoproteins (VLDL/LDL), polyunsaturated fatty acids, etc.).

CONCLUSION

The metabolic disturbances not only found to be well in concordance with various previous reports, these further demonstrated very high sensitivity and specificity to distinguish SAR from TB patients suggesting serum metabolomics analysis can serve as surrogate method in the diagnosis and clinical management of SAR.

Biomarker discovery for tuberculosis using metabolomics

Tuberculosis (TB) is the leading cause of death among infectious diseases, and the ratio of cases in which its pathogen Mycobacterium tuberculosis (Mtb) is drug resistant has been increasing worldwide, whereas latent tuberculosis infection (LTBI) may develop into active TB. Thus it is important to understand the mechanism of drug resistance, find new drugs, and find biomarkers for TB diagnosis. The rapid progress of metabolomics has enabled quantitative metabolite profiling of both the host and the pathogen. In this context, we provide recent progress in the application of metabolomics toward biomarker discovery for tuberculosis. In particular, we first focus on biomarkers based on blood or other body fluids for diagnosing active TB, identifying LTBI and predicting the risk of developing active TB, as well as monitoring the effectiveness of anti-TB drugs. Then we discuss the pathogen-based biomarker research for identifying drug resistant TB. While there have been many reports of potential candidate biomarkers, validations and clinical testing as well as improved bioinformatics analysis are needed to further substantiate and select key biomarkers before they can be made clinically applicable.

Tuberculosis alters immune-metabolic pathways resulting in perturbed IL-1 responses

Tuberculosis (TB) remains a major public health problem and we lack a comprehensive understanding of how Mycobacterium tuberculosis (M. tb) infection impacts host immune responses. We compared the induced immune response to TB antigen, BCG and IL-1β stimulation between latently M. tb infected individuals (LTBI) and active TB patients. This revealed distinct responses between TB/LTBI at transcriptomic, proteomic and metabolomic levels. At baseline, we identified a novel immune-metabolic association between pregnane steroids, the PPARγ pathway and elevated plasma IL-1ra in TB. We observed dysregulated IL-1 responses after BCG stimulation in TB patients, with elevated IL-1ra responses being explained by upstream TNF differences. Additionally, distinct secretion of IL-1α/IL-1β in LTBI/TB after BCG stimulation was associated with downstream differences in granzyme mediated cleavage. Finally, IL-1β driven signalling was dramatically perturbed in TB disease but was completely restored after successful treatment. This study improves our knowledge of how immune responses are altered during TB disease, and may support the design of improved preventive and therapeutic tools, including host-directed strategies.

A protein signature associated with active tuberculosis identified by plasma profiling and network-based analysis

Annually, approximately 10 million people are diagnosed with active tuberculosis (TB), and 1.4 million die of the disease. If left untreated, each person with active TB will infect 10-15 new individuals. The lack of non-sputum-based diagnostic tests leads to delayed diagnoses of active pulmonary TB cases, contributing to continued disease transmission. In this exploratory study, we aimed to identify biomarkers associated with active TB. We assessed the plasma levels of 92 proteins associated with inflammation in individuals with active TB (n = 20), latent TB (n = 14), or healthy controls (n = 10). Using co-expression network analysis, we identified one module of proteins with strong association with active TB. We removed proteins from the module that had low abundance or were associated with non-TB diseases in published transcriptomic datasets, resulting in a 12-protein plasma signature that was highly enriched in individuals with pulmonary and extrapulmonary TB and was further associated with disease severity.

Mass Spectrometry-Based Proteomic and Metabolomic Profiling of Serum Samples for Discovery and Validation of Tuberculosis Diagnostic Biomarker Signature

Tuberculosis (TB) is a transmissible disease listed as one of the 10 leading causes of death worldwide (10 million infected in 2019). A swift and precise diagnosis is essential to forestall its transmission, for which the discovery of effective diagnostic biomarkers is crucial. In this study, we aimed to discover molecular biomarkers for the early diagnosis of tuberculosis. Two independent cohorts comprising 29 and 34 subjects were assayed by proteomics, and 49 were included for metabolomic analysis. All subjects were arranged into three experimental groups—healthy controls (controls), latent TB infection (LTBI), and TB patients. LC-MS/MS blood serum protein and metabolite levels were submitted to univariate, multivariate, and ROC analysis. From the 149 proteins quantified in the discovery set, 25 were found to be differentially abundant between controls and TB patients. The AUC, specificity, and sensitivity, determined by ROC statistical analysis of the model composed of four of these proteins considering both proteomic sets, were 0.96, 93%, and 91%, respectively. The five metabolites (9-methyluric acid, indole-3-lactic acid, trans-3-indoleacrylic acid, hexanoylglycine, and N-acetyl-L-leucine) that better discriminate the control and TB patient groups (VIP > 1.75) from a total of 92 metabolites quantified in both ionization modes were submitted to ROC analysis. An AUC = 1 was determined, with all samples being correctly assigned to the respective experimental group. An integrated ROC analysis enrolling one protein and four metabolites was also performed for the common control and TB patients in the proteomic and metabolomic groups. This combined signature correctly assigned the 12 controls and 12 patients used only for prediction (AUC = 1, specificity = 100%, and sensitivity = 100%). This multiomics approach revealed a biomarker signature for tuberculosis diagnosis that could be potentially used for developing a point-of-care diagnosis clinical test.

Advances in diagnostic tools for respiratory tract infections. From tuberculosis to COVID19: changing paradigms?

Respiratory tract infections (RTI) are one of the commonest reasons for seeking healthcare, but are amongst the most challenging diseases in terms of clinical decision making. Proper and timely diagnosis is critical in order to optimize management and prevent further emergence of antimicrobial resistance by misuse, or overuse of antibiotics. Diagnostic tools for RTI include those involving syndromic and etiological diagnosis: from clinical and radiological features to laboratory methods targeting both pathogen detection and host biomarkers, as well as their combinations in terms of clinical algorithms. They also include tools for predicting severity and monitoring treatment response. Unprecedented milestones have been achieved in the context of the COVID-19 pandemic, involving the most recent applications of diagnostic technologies both at genotypic and phenotypic level, which have changed paradigms in infectious respiratory diseases in terms of why, how and where diagnostics are performed. The aim of this review is to discuss advances in diagnostic tools that impact clinical decision making, surveillance and follow-up of RTI and tuberculosis. If properly harnessed, recent advances in diagnostic technologies, including omics and digital transformation emerge as an unprecedented opportunity to tackle ongoing and future epidemics while handling antimicrobial resistance from a One Health perspective.

Pyridoxal phosphate, pyridoxamine phosphate, and folic acid based on ceRNA regulatory network as potential biomarkers for the diagnosis of pulmonary tuberculosis

BACKGROUND

Pulmonary tuberculosis (TB) is a serious disease burden worldwide, and its effective early diagnosis is still facing challenges. Knowledge, acquired from multi-omics integration analysis about the association between different types of differentially expressed molecules in the plasma of TB patients and the disease traits, is anticipated to improve the accuracy of TB diagnosis through the "integrative pattern".

METHODS

In this study, the lncRNA-miRNA-mRNA interaction network was constructed based on the competing endogenous RNA (ceRNA) hypothesis by integrating our previous data sets of lncRNA, mRNA, miRNA, and metabolites. Moreover, the key regulatory axis was established by co-expression analysis and verified at the level of metabolites.

RESULTS

A ceRNA regulatory network consisting of 23 lncRNAs, 10 miRNAs, and 113 mRNAs was constructed. The analysis results suggested that lncRNA (OSBPL10-AS1), miRNA (has-miR-485-5p), and mRNA (SLC23A2) might be involved in the regulation of vitamin metabolism in patients with TB. Metabolite analysis showed that compared with the normal control group, TB patients had abnormal vitamin metabolism, and the expression levels of pyridoxal phosphate, pyridoxamine phosphate, and folic acid were significantly different between the two groups (p < 0.05).

CONCLUSION

Integrated multi-omics analysis showed that vitamin metabolism disorder may be one of the pathological characteristic of TB. OSBPL10-AS1, hsa-miR-485-5p, SLC23A2, pyridoxal phosphate, pyridoxamine phosphate, and folic acid may collectively constitute the "integrative pattern" of multiple biomarkers, which may provide an accurate diagnosis of TB.

Bioprospecting of microbial enzymes: current trends in industry and healthcare

Microbial enzymes have an indispensable role in producing foods, pharmaceuticals, and other commercial goods. Many novel enzymes have been reported from all domains of life, such as plants, microbes, and animals. Nonetheless, industrially desirable enzymes of microbial origin are limited. This review article discusses the classifications, applications, sources, and challenges of most demanded industrial enzymes such as pectinases, cellulase, lipase, and protease. In addition, the production of novel enzymes through protein engineering technologies such as directed evolution, rational, and de novo design, for the improvement of existing industrial enzymes is also explored. We have also explored the role of metagenomics, nanotechnology, OMICs, and machine learning approaches in the bioprospecting of novel enzymes. Overall, this review covers the basics of biocatalysts in industrial and healthcare applications and provides an overview of existing microbial enzyme optimization tools. KEY POINTS: • Microbial bioactive molecules are vital for therapeutic and industrial applications. • High-throughput OMIC is the most proficient approach for novel enzyme discovery. • Comprehensive databases and efficient machine learning models are the need of the hour to fast forward de novo enzyme design and discovery.

Contemporary diagnostics for medically relevant fastidious microorganisms belonging to the genera Anaplasma, Bartonella, Coxiella, Orientia, and Rickettsia

Many of the human infectious pathogens—especially the zoonotic or vector-borne bacteria—are fastidious organisms that are difficult to cultivate because of their strong adaption to the infected host culminating in their near-complete physiological dependence on this environment. These bacterial species exhibit reduced multiplication rates once they are removed from their optimal ecological niche. This fact complicates the laboratory diagnosis of the disease and hinders the detection and further characterization of the underlying organisms, e.g. at the level of their resistance to antibiotics due to their slow growth. Here, we describe the current state of microbiological diagnostics for five genera of human pathogens with a fastidious laboratory lifestyle. For Anaplasma spp., Bartonella spp., Coxiella burnetii, Orientia spp. and Rickettsia spp., we will summarize the existing diagnostic protocols, the specific limitations for implementation of novel diagnostic approaches and the need for further optimization or expansion of the diagnostic armamentarium. We will reflect upon the diagnostic opportunities provided by new technologies including mass spectrometry and next-generation nucleic acid sequencing. Finally, we will review the (im)possibilities of rapidly developing new in vitro diagnostic tools for diseases of which the causative agents are fastidiously growing and therefore hard to detect.

Discovery of serum biomarkers for diagnosis of tuberculosis by NMR metabolomics including cross-validation with a second cohort

Background

Tuberculosis (TB) is a disease with worldwide presence and a major cause of death in several developing countries. Current diagnostic methodologies often lack specificity and sensitivity, whereas a long time is needed to obtain a conclusive result.

Methods

In an effort to develop better diagnostic methods, this study aimed at the discovery of a biomarker signature for TB diagnosis using a Nuclear Magnetic Resonance based metabolomics approach. In this study, we acquired ¹H NMR spectra of blood serum samples of groups of healthy subjects, individuals with latent TB and of patients with pulmonary and extra-pulmonary TB. The resulting data were treated with uni- and multivariate statistical analysis.

Results

Six metabolites (inosine, hypoxanthine, mannose, asparagine, aspartate and glutamate) were validated by an independent cohort, all of them related with metabolic processes described as associated with TB infection.

Conclusion

The findings of the study are according with the WHO Target Product Profile recommendations for a triage test to rule-out active TB.

The aftermath of COVID-19 pandemic on the diagnosis of TB at a tertiary care hospital in India

BACKGROUND

The recent COVID-19 pandemic became a looming catastrophe over global public health and severely disrupted essential healthcare services like tuberculosis (TB). This study estimated the impact of the COVID-19 in the diagnosis of TB, a microbiology laboratory-based overview.

METHOD

This ambispective observational study was conducted at the Department of Microbiology in a tertiary care hospital in South Karnataka from January 2019 to December 2020. A standardized data collection sheet was prepared to collect the month-wise total number of suspected TB and confirmed TB samples. Data were analyzed using EZR 3.4.3 (R, open-source). Categorical variables were expressed in frequency and percentage. The Chi-square test was performed to test the difference in proportions and p < 0.05 indicated statistical significance.

RESULTS

In this study, a significant drop was observed in suspected TB specimens in 2020 compared to 2019, i.e. 54.8% for microscopy, along with 34.2% and 49.7% for Xpert MTB/RIF and MGIT culture respectively. Also, a sharp decline in confirmed TB samples was noted in 2020 with 49%, 43.8%, and 59.7% reduction with microscopy, Xpert MTB/RIF, and MGIT culture respectively, compared to 2019. Another major finding from this study reveals the PTB: EPTB proportion changed from 2.7:1 in 2019 to 2.1:1 in 2020, divulging an overall increase in EPTB sample proportion in 2020 (p = 0.0385).

CONCLUSION

The COVID-19 pandemic adversely impacted the TB diagnostic services, resulting in a significant reduction of active TB case detection. It highlights an urgent need to revise the strategies to control and eliminate TB in this hour of the pandemic crisis.

Combination of Blood Routine Examination and T-SPOT.TB Assay for Distinguishing Between Active Tuberculosis and Latent Tuberculosis Infection

Background

Distinguishing between active tuberculosis (ATB) and latent tuberculosis infection (LTBI) remains challenging.

Methods

Between 2013 and 2019, 2,059 (1,097 ATB and 962 LTBI) and another 883 (372 ATB and 511 LTBI) participants were recruited based on positive T-SPOT.TB (T-SPOT) results from Qiaokou (training) and Caidian (validation) cohorts, respectively. Blood routine examination (BRE) was performed simultaneously. Diagnostic model was established according to multivariate logistic regression.

Results

Significant differences were observed in all indicators of BRE and T-SPOT assay between ATB and LTBI. Diagnostic model built on BRE showed area under the curve (AUC) of 0.846 and 0.850 for discriminating ATB from LTBI in the training and validation cohorts, respectively. Meanwhile, TB-specific antigens spot-forming cells (SFC) (the larger of early secreted antigenic target 6 and culture filtrate protein 10 SFC in T-SPOT assay) produced lower AUC of 0.775 and 0.800 in the training and validation cohorts, respectively. The diagnostic model based on combination of BRE and T-SPOT showed an AUC of 0.909 for differentiating ATB from LTBI, with 78.03% sensitivity and 90.23% specificity when a cutoff value of 0.587 was used in the training cohort. Application of the model to the validation cohort showed similar performance. The AUC, sensitivity, and specificity were 0.910, 78.23%, and 90.02%, respectively. Furthermore, we also assessed the performance of our model in differentiating ATB from LTBI with lung lesions. Receiver operating characteristic analysis showed that the AUC of established model was 0.885, while a threshold of 0.587 yield a sensitivity of 78.03% and a specificity of 85.69%, respectively.

Conclusions

The diagnostic model based on combination of BRE and T-SPOT could provide a reliable differentiation between ATB and LTBI.

Urine NMR-based TB metabolic fingerprinting for the diagnosis of TB in children

Tuberculosis (TB) is a major cause of morbidity and mortality in children, and early diagnosis and treatment are crucial to reduce long-term morbidity and mortality. In this study, we explore whether urine nuclear magnetic resonance (NMR)-based metabolomics could be used to identify differences in the metabolic response of children with different diagnostic certainty of TB. We included 62 children with signs and symptoms of TB and 55 apparently healthy children. Six of the children with presumptive TB had bacteriologically confirmed TB, 52 children with unconfirmed TB, and 4 children with unlikely TB. Urine metabolic fingerprints were identified using high- and low-field proton NMR platforms and assessed with pattern recognition techniques such as principal components analysis and partial least squares discriminant analysis. We observed differences in the metabolic fingerprint of children with bacteriologically confirmed and unconfirmed TB compared to children with unlikely TB (p = 0.041 and p = 0.013, respectively). Moreover, children with unconfirmed TB with X-rays compatible with TB showed differences in the metabolic fingerprint compared to children with non-pathological X-rays (p = 0.009). Differences in the metabolic fingerprint in children with different diagnostic certainty of TB could contribute to a more accurate characterisation of TB in the paediatric population. The use of metabolomics could be useful to improve the prediction of TB progression and diagnosis in children.

Multi-Omics Approach in the Identification of Potential Therapeutic Biomolecule for COVID-19

COVID-19 is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It has a disastrous effect on mankind due to the contagious and rapid nature of its spread. Although vaccines for SARS-CoV-2 have been successfully developed, the proven, effective, and specific therapeutic molecules are yet to be identified for the treatment. The repurposing of existing drugs and recognition of new medicines are continuously in progress. Efforts are being made to single out plant-based novel therapeutic compounds. As a result, some of these biomolecules are in their testing phase. During these efforts, the whole-genome sequencing of SARS-CoV-2 has given the direction to explore the omics systems and approaches to overcome this unprecedented health challenge globally. Genome, proteome, and metagenome sequence analyses have helped identify virus nature, thereby assisting in understanding the molecular mechanism, structural understanding, and disease propagation. The multi-omics approaches offer various tools and strategies for identifying potential therapeutic biomolecules for COVID-19 and exploring the plants producing biomolecules that can be used as biopharmaceutical products. This review explores the available multi-omics approaches and their scope to investigate the therapeutic promises of plant-based biomolecules in treating SARS-CoV-2 infection.

Multi-Omics Approach in the Identification of Potential Therapeutic Biomolecule for COVID-19

COVID-19 is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It has a disastrous effect on mankind due to the contagious and rapid nature of its spread. Although vaccines for SARS-CoV-2 have been successfully developed, the proven, effective, and specific therapeutic molecules are yet to be identified for the treatment. The repurposing of existing drugs and recognition of new medicines are continuously in progress. Efforts are being made to single out plant-based novel therapeutic compounds. As a result, some of these biomolecules are in their testing phase. During these efforts, the whole-genome sequencing of SARS-CoV-2 has given the direction to explore the omics systems and approaches to overcome this unprecedented health challenge globally. Genome, proteome, and metagenome sequence analyses have helped identify virus nature, thereby assisting in understanding the molecular mechanism, structural understanding, and disease propagation. The multi-omics approaches offer various tools and strategies for identifying potential therapeutic biomolecules for COVID-19 and exploring the plants producing biomolecules that can be used as biopharmaceutical products. This review explores the available multi-omics approaches and their scope to investigate the therapeutic promises of plant-based biomolecules in treating SARS-CoV-2 infection.

Discovery and validation of an NMR-based metabolomic profile in urine as TB biomarker

Despite efforts to improve tuberculosis (TB) detection, limitations in access, quality and timeliness of diagnostic services in low- and middle-income countries are challenging for current TB diagnostics. This study aimed to identify and characterise a metabolic profile of TB in urine by high-field nuclear magnetic resonance (NMR) spectrometry and assess whether the TB metabolic profile is also detected by a low-field benchtop NMR spectrometer. We included 189 patients with tuberculosis, 42 patients with pneumococcal pneumonia, 61 individuals infected with latent tuberculosis and 40 uninfected individuals. We acquired the urine spectra from high and low-field NMR. We characterised a TB metabolic fingerprint from the Principal Component Analysis. We developed a classification model from the Partial Least Squares-Discriminant Analysis and evaluated its performance. We identified a metabolic fingerprint of 31 chemical shift regions assigned to eight metabolites (aminoadipic acid, citrate, creatine, creatinine, glucose, mannitol, phenylalanine, and hippurate). The model developed using low-field NMR urine spectra correctly classified 87.32%, 85.21% and 100% of the TB patients compared to pneumococcal pneumonia patients, LTBI and uninfected individuals, respectively. The model validation correctly classified 84.10% of the TB patients. We have identified and characterised a metabolic profile of TB in urine from a high-field NMR spectrometer and have also detected it using a low-field benchtop NMR spectrometer. The models developed from the metabolic profile of TB identified by both NMR technologies were able to discriminate TB patients from the rest of the study groups and the results were not influenced by anti-TB treatment or TB location. This provides a new approach in the search for possible biomarkers for the diagnosis of TB.

Hematologic alterations and early mortality in a cohort of HIV positive African patients

Introduction

Infection with Human Immunodeficiency Virus (HIV) is highly prevalent worldwide, especially in Sub-Saharan Africa, where anaemia is also widespread. HIV infection is known to be associated with anaemia and various other haematologic alterations, but little data on correlation with immunological and virologic conditions in treatment-naïve patients and impact on mortality are available. Our study aims to investigate hematologic features in HIV-infected individuals in Malawi and Mozambique and assesses possible correlations with early morality.

Material and methods

We conducted a retrospective analysis of baseline data (general details, nutritional status, full blood count and HIV infection progress data) and 12 months follow-up status for HIV+ adult patients in 22 health facilities in Malawi (11 sites) and Mozambique (11 sites) run by DREAM program. Anagraphic details, anthropometric characteristics, full blood count, CD4+ count and Viral Load data were collected from electronical medical records (EMR) for all the HIV-positive, treatment-naïve patients starting care in the sites in the period January 2007 –December 2016. Follow-up status after one year since enrolment in care was also considered. All the data extracted from the EMR were included in a dataset and then analysed. Univariate and multivariate analysis were conducted through logistical regression to investigate associations, and survival analysis analysed in a Cox regression model.

Results

On the whole, 22.657 patients were included; severe and moderate anaemia were observed in 1.174 (8,2%) and 4.703 (21,9%) patients respectively. Gender, nutritional status, CD4+ count, and viral load (VL) were associated with anaemia, leukopenia, and thrombocytopenia. Among 21.166 fully evaluable patients, 8.494 (40,1%) had at least one cytopenia. Any cytopenia was present in 1/3 of patients with normal nutritional status and less advanced HIV infection, and it wouldn’t be diagnosed in a basic HIV care setting. During the first year of treatment, 1.725 subjects (7,6% of the entire sample) died. Anaemia, lower Red blood cells and platelets counts correlated with mortality in the first year of care, independently by body mass index, haemoglobin, CD4+ count and VL.

Conclusions

Notwithstanding anaemia is known to be associated with HIV infection at diagnosis, full blood count is not routinely performed in many African countries. Our results emphasize that including the study of a broader set of parameters in the routine HIV care services in Sub-Saharan Africa would provide significant clinical information able to predict other alterations and poor outcomes.

Systems Biology Approaches for Therapeutics Development Against COVID-19

Understanding the systems biology approaches for promoting the development of new therapeutic drugs is attaining importance nowadays. The threat of COVID-19 outbreak needs to be vanished for global welfare, and every section of research is focusing on it. There is an opportunity for finding new, quick, and accurate tools for developing treatment options, including the vaccine against COVID-19. The review at this moment covers various aspects of pathogenesis and host factors for exploring the virus target and developing suitable therapeutic solutions through systems biology tools. Furthermore, this review also covers the extensive details of multiomics tools i.e., transcriptomics, proteomics, genomics, lipidomics, immunomics, and in silico computational modeling aiming towards the study of host-virus interactions in search of therapeutic targets against the COVID-19.

Pediatric Tuberculosis: The Impact of "Omics" on Diagnostics Development

Tuberculosis (TB) is a major public health concern for all ages. However, the disease presents a larger challenge in pediatric populations, partially owing to the lack of reliable diagnostic standards for the early identification of infection. Currently, there are no biomarkers that have been clinically validated for use in pediatric TB diagnosis. Identification and validation of biomarkers could provide critical information on prognosis of disease, and response to treatment. In this review, we discuss how the “omics” approach has influenced biomarker discovery and the advancement of a next generation rapid point-of-care diagnostic for TB, with special emphasis on pediatric disease. Limitations of current published studies and the barriers to their implementation into the field will be thoroughly reviewed within this article in hopes of highlighting future avenues and needs for combating the problem of pediatric tuberculosis.

Long Noncoding RNA and Predictive Model To Improve Diagnosis of Clinically Diagnosed Pulmonary Tuberculosis

Clinically diagnosed pulmonary tuberculosis (PTB) patients lack microbiological evidence of Mycobacterium tuberculosis, and misdiagnosis or delayed diagnosis often occurs as a consequence. We investigated the potential of long noncoding RNAs (lncRNAs) and corresponding predictive models to diagnose these patients. We enrolled 1,764 subjects, including clinically diagnosed PTB patients, microbiologically confirmed PTB cases, non-TB disease controls, and healthy controls, in three cohorts (screening, selection, and validation).

Clinically diagnosed pulmonary tuberculosis (PTB) patients lack microbiological evidence of Mycobacterium tuberculosis, and misdiagnosis or delayed diagnosis often occurs as a consequence. We investigated the potential of long noncoding RNAs (lncRNAs) and corresponding predictive models to diagnose these patients. We enrolled 1,764 subjects, including clinically diagnosed PTB patients, microbiologically confirmed PTB cases, non-TB disease controls, and healthy controls, in three cohorts (screening, selection, and validation). Candidate lncRNAs differentially expressed in blood samples of the PTB and healthy control groups were identified by microarray and reverse transcription-quantitative PCR (qRT-PCR) in the screening cohort. Logistic regression models were developed using lncRNAs and/or electronic health records (EHRs) from clinically diagnosed PTB patients and non-TB disease controls in the selection cohort. These models were evaluated by area under the concentration-time curve (AUC) and decision curve analyses, and the optimal model was presented as a Web-based nomogram, which was evaluated in the validation cohort. Three differentially expressed lncRNAs (ENST00000497872, n333737, and n335265) were identified. The optimal model (i.e., nomogram) incorporated these three lncRNAs and six EHRs (age, hemoglobin, weight loss, low-grade fever, calcification detected by computed tomography [CT calcification], and interferon gamma release assay for tuberculosis [TB-IGRA]). The nomogram showed an AUC of 0.89, a sensitivity of 0.86, and a specificity of 0.82 in differentiating clinically diagnosed PTB cases from non-TB disease controls of the validation cohort, which demonstrated better discrimination and clinical net benefit than the EHR model. The nomogram also had a discriminative power (AUC, 0.90; sensitivity, 0.85; specificity, 0.81) in identifying microbiologically confirmed PTB patients. lncRNAs and the user-friendly nomogram could facilitate the early identification of PTB cases among suspected patients with negative M. tuberculosis microbiological evidence.

Potential anti-TB investigational compounds and drugs with repurposing potential in TB therapy: a conspectus

The latest WHO report estimates about 1.6 million global deaths annually from TB, which is further exacerbated by drug-resistant (DR) TB and comorbidities with diabetes and HIV. Exiguous dosing, incomplete treatment course, and the ability of the tuberculosis bacilli to tolerate and survive current first-line and second-line anti-TB drugs, in either their latent state or active state, has resulted in an increased prevalence of multidrug-resistant (MDR), extensively drug-resistant (XDR), and totally drug-resistant TB (TDR-TB). Although a better understanding of the TB microanatomy, genome, transcriptome, proteome, and metabolome, has resulted in the discovery of a few novel promising anti-TB drug targets and diagnostic biomarkers of late, no new anti-TB drug candidates have been approved for routine therapy in over 50 years, with only bedaquiline, delamanid, and pretomanid recently receiving tentative regulatory approval. Considering this, alternative approaches for identifying possible new anti-TB drug candidates, for effectively eradicating both replicating and non-replicating Mycobacterium tuberculosis, are still urgently required. Subsequently, several antibiotic and non-antibiotic drugs with known treatment indications (TB targeted and non-TB targeted) are now being repurposed and/or derivatized as novel antibiotics for possible use in TB therapy. Insights gathered here reveal that more studies focused on drug-drug interactions between licensed and potential lead anti-TB drug candidates need to be prioritized. This write-up encapsulates the most recent findings regarding investigational compounds with promising anti-TB potential and drugs with repurposing potential in TB therapy.

Multiplex PCR Based Urinary Tract Infection (UTI) Analysis Compared to Traditional Urine Culture in Identifying Significant Pathogens in Symptomatic Patients

OBJECTIVE

To evaluate whether multiplex PCR-based molecular testing is noninferior to urine culture for detection of bacterial infections in symptomatic patients.

METHODS

Retrospective record review of 582 consecutive elderly patients presenting with symptoms of lower urinary tract infection (UTI) was conducted. All patients had traditional urine cultures and PCR molecular testing run in parallel.

RESULTS

A total of 582 patients (mean age 77; range 60-95) with symptoms of lower UTI had both urine cultures and diagnostic PCR between March and July 2018. PCR detected uropathogens in 326 patients (56%, 326/582), while urine culture detected pathogens in 217 patients (37%, 217/582). PCR and culture agreed in 74% of cases (431/582): both were positive in 34% of cases (196/582) and both were negative in 40% of cases (235/582). However, PCR and culture disagreed in 26% of cases (151/582): PCR was positive while culture was negative in 22% of cases (130/582), and culture was positive while PCR was negative in 4% of cases (21/582). Polymicrobial infections were reported in 175 patients (30%, 175/582), with PCR reporting 166 and culture reporting 39. Further, polymicrobial infections were identified in 67 patients (12%, 67/582) in which culture results were negative. Agreement between PCR and urine culture for positive cultures was 90%, exceeding the noninferiority threshold of 85% (95% conflict of interest 85.7%-93.6%).

CONCLUSION

Multiplex PCR is noninferior to urine culture for detection and identification of bacteria. Further investigation may show that the accuracy and speed of PCR to diagnose UTI can significantly improve patient outcomes.

Recent and emerging technologies for the rapid diagnosis of infection and antimicrobial resistance

The rise in antimicrobial resistance (AMR) is predicted to cause 10 million deaths per year by 2050 unless steps are taken to prevent this looming crisis. Microbiological culture is the gold standard for the diagnosis of bacterial/fungal pathogens and antimicrobial resistance and takes 48 hours or longer. Hence, antibiotic prescriptions are rarely based on a definitive diagnosis and patients often receive inappropriate treatment. Rapid diagnostic tools are urgently required to guide appropriate antimicrobial therapy, thereby improving patient outcomes and slowing AMR development. We discuss new technologies for rapid infection diagnosis including: sample-in-answer-out PCR-based tests, BioFire FilmArray and Curetis Unyvero; rapid susceptibility tests, Accelerate Pheno and microfluidic tests; and sequencing-based approaches, focusing on targeted and clinical metagenomic nanopore sequencing.

Mycobacterium tuberculosis strain H37Rv Electrochemical Sensor Mediated by Aptamer and AuNPs-DNA

The accurate and rapid detection of Mycobacterium tuberculosis ( M. tuberculosis) is essential for the effective treatment of tuberculosis. In this article, we propose an electrochemical sensor to detect M. tuberculosis reference strain H37Rv. The sensor contains an H37Rv aptamer and oligonucleotides modified with gold nanoparticles (AuNPs-DNA). An H37Rv aptamer screened by our laboratory was used as the recognition probe. The change in frequency shift mediated by AuNPs-DNA in the presence of H37Rv was detected using a multichannel series piezoelectric quartz crystal (MSPQC) system. Three oligonucleotides modified with gold nanoparticles were designed. These oligonucleotides contained 12, 12, and 13 bases that hybridized with the 37-nt H37Rv aptamer. H37Rv aptamer was immobilized on the gold electrode surface by Au-S bonds. A conductive-layer was then formed by sequential hybridization of the aptamer with the three designed AuNPs-DNAs. When H37Rv was present, it specifically bound to the aptamer, resulting in the detachment of AuNPs-DNA from the electrode. The conductive layer was thereby replaced by a nonconductive complex of aptamer and bacteria. These changes were monitored by the MSPQC system. The proposed sensor is rapid, specific and sensitive, the detection time was 2 h. The detection limit was 100 cfu/mL. This sensor would be of great benefit for the early clinical diagnosis of tuberculosis.

Metabolomics applied to maternal and perinatal health: a review of new frontiers with a translation potential

The prediction or early diagnosis of maternal complications is challenging mostly because the main conditions, such as preeclampsia, preterm birth, fetal growth restriction, and gestational diabetes mellitus, are complex syndromes with multiple underlying mechanisms related to their occurrence. Limited advances in maternal and perinatal health in recent decades with respect to preventing these disorders have led to new approaches, and "omics" sciences have emerged as a potential field to be explored. Metabolomics is the study of a set of metabolites in a given sample and can represent the metabolic functioning of a cell, tissue or organism. Metabolomics has some advantages over genomics, transcriptomics, and proteomics, as metabolites are the final result of the interactions of genes, RNAs and proteins. Considering the recent "boom" in metabolomic studies and their importance in the research agenda, we here review the topic, explaining the rationale and theory of the metabolomic approach in different areas of maternal and perinatal health research for clinical practitioners. We also demonstrate the main exploratory studies of these maternal complications, commenting on their promising findings. The potential translational application of metabolomic studies, especially for the identification of predictive biomarkers, is supported by the current findings, although they require external validation in larger datasets and with alternative methodologies.

Integrating exosomal microRNAs and electronic health data improved tuberculosis diagnosis

Background Tuberculosis (TB) is difficult to diagnose under complex clinical conditions as electronic health records (EHRs) are often inadequate in making an affirmative diagnosis. As exosomal miRNAs emerged as promising biomarkers, we investigated the potential of using exosomal miRNAs and EHRs in TB diagnosis.

Methods

A total of 370 individuals, including pulmonary tuberculosis (PTB), tuberculous meningitis (TBM), non-TB disease controls and healthy state controls, were enrolled. Exosomal miRNAs were profiled in the exploratory cohort using microarray and miRNA candidates were selected in the selection cohort using qRT-PCR. EHRs and follow-up information of the patients were collected accordingly. miRNAs and EHRs were used to develop diagnostic models for PTB and TBM in the selection cohort with the Support Vector Machine (SVM) algorithm. These models were further evaluated in an independent testing cohort.

Findings

Six exosomal miRNAs (miR-20a, miR-20b, miR-26a, miR-106a, miR-191, miR-486) were differentially expressed in the TB patients. Three SVM models, "EHR+miRNA", "miRNA only" and "EHR only" were compared, and "EHR + miRNA" model achieved the highest diagnostic efficacy, with an AUC up to 0.97 (95% CI 0.80–0.99) in TBM and 0.97 (0.87–0.99) in PTB, respectively. However, "EHR only" model only showed an AUC of 0.67 (0.46–0.83) in TBM. After 2-month anti-tuberculosis therapy, overexpressed miRNAs presented a decreased expression trend (p= 4.80 × 10⁻⁵).

Interpretation

Our results showed that the combination of exosomal miRNAs and EHRs could potentially improve clinical diagnosis of TBM and PTB.

Fund

Funds for the Central Universities, the National Natural Science Foundation of China.

Tuberculosis in the 21th century: Current status of diagnostic methods

Tuberculosis is an infectious bacterial disease with a high mortality rate worldwide constituting a serious public health problem. The diagnostic methods commonly used by health professionals are slow and expensive and the results may take about sixty days which will cause a delay in administrating the most proper treatment to the patient, as well as increase health care costs and infection transmission possibility. Patients infected simultaneously with human immunodeficiency virus and Mycobacterium tuberculosis are a constant and worrying challenge for the scientific community which will research and develop new methods of diagnosis, new drugs and new therapies. Nowadays there are new tuberculosis diagnosis methods and some of which are already in clinical trial phases. These methods have high sensitivity, but do not replace the microbiological examination for isolation and culture of Mycobacterium spp. However, in clinical practice, microbiological, imaging, clinical and epidemiological data integration provide the best diagnosis and treatment possible. Consequently, throughout this paper, the different methods of diagnosis of human tuberculosis with its advantages and disadvantages will be covered, describing new omics and ultra-fast methods to increase knowledge and obtain a rapid diagnosis of tuberculosis.

High-resolution plasma metabolomics analysis to detect Mycobacterium tuberculosis-associated metabolites that distinguish active pulmonary tuberculosis in humans

Introduction

Pulmonary tuberculosis (TB) is a major worldwide health problem that lacks robust blood-based biomarkers for detection of active disease. High-resolution metabolomics (HRM) is an innovative method to discover low-abundance metabolites as putative blood biomarkers to detect TB disease, including those known to be produced by the causative organism, Mycobacterium tuberculosis (Mtb).

Methods

We used HRM profiling to measure the plasma metabolome for 17 adults with active pulmonary TB disease and 16 of their household contacts without active TB. We used a suspect screening approach to identify metabolites previously described in cell culture studies of Mtb based on retention time and accurate mass matches.

Results

The association of relative metabolite abundance in active TB disease subjects compared to their household contacts predicted three Mtb-associated metabolites that were significantly increased in the active TB patients based on accurate mass matches: phosphatidylglycerol (PG) (16:0_18:1), lysophosphatidylinositol (Lyso-PI) (18:0) and acylphosphatidylinositol mannoside (Ac1PIM1) (56:1) (p<0.001 for all). These three metabolites provided excellent classification accuracy for active TB disease (AUC = 0.97). Ion dissociation spectra (tandem MS/MS) supported the identification of PG (16:0_18:1) and Lyso-PI (18:0) in the plasma of patients with active TB disease, though the identity of Ac1PIM1 could not be definitively confirmed.

Conclusions

Presence of the Mtb-associated lipid metabolites PG (16:0_18:1) and Lyso-PI (18:0) in plasma accurately identified patients with active TB disease. Consistency of in vitro and in vivo data suggests suitability for exploring these in future studies for possible development as TB disease biomarkers.

RNA Sequencing (RNA-Seq) Reveals Extremely Low Levels of Reticulocyte-Derived Globin Gene Transcripts in Peripheral Blood From Horses (Equus caballus) and Cattle (Bos taurus)

RNA-seq has emerged as an important technology for measuring gene expression in peripheral blood samples collected from humans and other vertebrate species. In particular, transcriptomics analyses of whole blood can be used to study immunobiology and develop novel biomarkers of infectious disease. However, an obstacle to these methods in many mammalian species is the presence of reticulocyte-derived globin mRNAs in large quantities, which can complicate RNA-seq library sequencing and impede detection of other mRNA transcripts. A range of supplementary procedures for targeted depletion of globin transcripts have, therefore, been developed to alleviate this problem. Here, we use comparative analyses of RNA-seq data sets generated from human, porcine, equine, and bovine peripheral blood to systematically assess the impact of globin mRNA on routine transcriptome profiling of whole blood in cattle and horses. The results of these analyses demonstrate that total RNA isolated from equine and bovine peripheral blood contains very low levels of globin mRNA transcripts, thereby negating the need for globin depletion and greatly simplifying blood-based transcriptomic studies in these two domestic species.

Incipient and Subclinical Tuberculosis: a Clinical Review of Early Stages and Progression of Infection

Tuberculosis (TB) is the leading infectious cause of mortality worldwide, due in part to a limited understanding of its clinical pathogenic spectrum of infection and disease. Historically, scientific research, diagnostic testing, and drug treatment have focused on addressing one of two disease states: latent TB infection or active TB disease. Recent research has clearly demonstrated that human TB infection, from latent infection to active disease, exists within a continuous spectrum of metabolic bacterial activity and antagonistic immunological responses. This revised understanding leads us to propose two additional clinical states: incipient and subclinical TB. The recognition of incipient and subclinical TB, which helps divide latent and active TB along the clinical disease spectrum, provides opportunities for the development of diagnostic and therapeutic interventions to prevent progression to active TB disease and transmission of TB bacilli. In this report, we review the current understanding of the pathogenesis, immunology, clinical epidemiology, diagnosis, treatment, and prevention of both incipient and subclinical TB, two emerging clinical states of an ancient bacterium.

Nano-biosensing approaches on tuberculosis: Defy of aptamers

Tuberculosis is a major global health problem caused by the bacterium Mycobacterium tuberculosis (Mtb) complex. According to WHO reports, 53 million TB patients died from 2000 to 2016. Therefore, early diagnosis of the disease is of great importance for global health care programs. The restrictions of traditional methods have encouraged the development of innovative methods for rapid, reliable, and cost-effective diagnosis of tuberculosis. In recent years, aptamer-based biosensors or aptasensors have drawn great attention to sensitive and accessible detection of tuberculosis. Aptamers are small short single-stranded molecules of DNA or RNA that fold to a unique form and bind to targets. Once combined with nanomaterials, nano-scale aptasensors provide powerful analytical platforms for diagnosing of tuberculosis. Various groups designed and studied aptamers specific for the whole cells of M. tuberculosis, mycobacterial proteins and IFN-γ for early diagnosis of TB. Advantages such as high specificity and strong affinity, potential for binding to a larger variety of targets, increased stability, lower costs of synthesis and storage requirements, and lower probability of contamination make aptasensors pivotal alternatives for future TB diagnostics. In recent years, the concept of SOMAmer has opened new horizons in high precision detection of tuberculosis biomarkers. This review article provides a description of the research progresses of aptamer-based and SOMAmer-based biosensors and nanobiosensors for the detection of tuberculosis.

Mass spectrometry-based metabolomics for tuberculosis meningitis

Tuberculosis meningitis (TBM) is a prevalent form of extra-pulmonary tuberculosis that causes substantial morbidity and mortality. Diagnosis of TBM is difficult because of the limited sensitivity of existing laboratory techniques. A metabolomics approach can be used to investigate the sets of metabolites of both bacteria and host, and has been used to clarify the mechanisms underlying disease development, and identify metabolic changes, leadings to improved methods for diagnosis, treatment, and prognostication. Mass spectrometry (MS) is a major analysis platform used in metabolomics, and MS-based metabolomics provides wide metabolite coverage, because of its high sensitivity, and is useful for the investigation of Mycobacterium tuberculosis (Mtb) and related diseases. It has been used to investigate TBM diagnosis; however, the processes involved in the MS-based metabolomics approach are complex and flexible, and often consist of several steps, and small changes in the methods used can have a huge impact on the final results. Here, the process of MS-based metabolomics is summarized and its applications in Mtb and Mtb-related diseases discussed. Moreover, the current status of TBM metabolomics is described.

Cerebral tryptophan metabolism and outcome of tuberculous meningitis: an observational cohort study

BACKGROUND

Immunopathology contributes to the high mortality of tuberculous meningitis, but the biological pathways involved are mostly unknown. We aimed to compare cerebrospinal fluid (CSF) and serum metabolomes of patients with tuberculous meningitis with that of controls without tuberculous meningitis, and assess the link between metabolite concentrations and mortality.

METHODS

In this observational cohort study at the Hasan Sadikin Hospital (Bandung, Indonesia) we measured 425 metabolites using liquid chromatography-mass spectrometry in CSF and serum from 33 HIV-negative Indonesian patients with confirmed or probable tuberculous meningitis and 22 control participants with complete clinical data between March 12, 2009, and Oct 27, 2013. Associations of metabolite concentrations with survival were validated in a second cohort of 101 patients from the same centre. Genome-wide single nucleotide polymorphism typing was used to identify tryptophan quantitative trait loci, which were used for survival analysis in a third cohort of 285 patients.

FINDINGS

Concentrations of 250 (70%) of 351 metabolites detected in CSF were higher in patients with tuberculous meningitis than in controls, especially in those who died during follow-up. Only five (1%) of the 390 metobolites detected in serum differed between patients with tuberculous meningitis and controls. CSF tryptophan concentrations showed a pattern different from most other CSF metabolites; concentrations were lower in patients who survived compared with patients who died (9-times) and to controls (31-times). The association of low CSF tryptophan with patient survival was confirmed in the validation cohort (hazard ratio 0·73; 95% CI 0·64-0·83; p<0·0001; per each halving). 11 genetic loci predictive for CSF tryptophan concentrations in tuberculous meningitis were identified (p<0·00001). These quantitative trait loci predicted survival in a third cohort of 285 HIV-negative patients in a prognostic index including age and sex, also after correction for possible confounders (p=0·0083).

INTERPRETATION

Cerebral tryptophan metabolism, which is known to affect Mycobacterium tuberculosis growth and CNS inflammation, is important for the outcome of tuberculous meningitis. CSF tryptophan concentrations in tuberculous meningitis are under strong genetic influence, probably contributing to the variable outcomes of tuberculous meningitis. Interventions targeting tryptophan metabolism could improve outcomes of tuberculous meningitis.

FUNDING

Royal Dutch Academy of Arts and Sciences; Netherlands Foundation for Scientific Research; Radboud University; National Academy of Sciences; Ministry of Research, Technology, and Higher Education, Indonesia; European Research Council; and PEER-Health.

Type I Interferons in the Pathogenesis of Tuberculosis: Molecular Drivers and Immunological Consequences

Tuberculosis (TB) remains a major global health threat. Urgent needs in the fight against TB include improved and innovative treatment options for drug-sensitive and -resistant TB as well as reliable biological indicators that discriminate active from latent disease and enable monitoring of treatment success or failure. Prominent interferon (IFN) inducible gene signatures in TB patients and animal models of Mycobacterium tuberculosis infection have drawn significant attention to the roles of type I IFNs in the host response to mycobacterial infections. Here, we review recent developments in the understanding of the innate immune pathways that drive type I IFN responses in mycobacteria-infected host cells and the functional consequences for the host defense against M. tuberculosis, with a view that such insights might be exploited for the development of targeted host-directed immunotherapies and development of reliable biomarkers.

Discovery and Validation of a Six-Marker Serum Protein Signature for the Diagnosis of Active Pulmonary Tuberculosis

New non-sputum biomarker tests for active tuberculosis (TB) diagnostics are of the highest priority for global TB control. We performed in-depth proteomic analysis using the 4,000-plex SOMAscan assay on 1,470 serum samples from seven countries where TB is endemic. All samples were from patients with symptoms and signs suggestive of active pulmonary TB that were systematically confirmed or ruled out for TB by culture and clinical follow-up. HIV coinfection was present in 34% of samples, and 25% were sputum smear negative. Serum protein biomarkers were identified by stability selection using L1-regularized logistic regression and by Kolmogorov-Smirnov (KS) statistics. A naive Bayes classifier using six host response markers (HR6 model), including SYWC, kallistatin, complement C9, gelsolin, testican-2, and aldolase C, performed well in a training set (area under the sensitivity-specificity curve [AUC] of 0.94) and in a blinded verification set (AUC of 0.92) to distinguish TB and non-TB samples. Differential expression was also highly significant (P < 10⁻²⁰) for previously described TB markers, such as IP-10, LBP, FCG3B, and TSP4, and for many novel proteins not previously associated with TB. Proteins with the largest median fold changes were SAA (serum amyloid protein A), NPS-PLA2 (secreted phospholipase A2), and CA6 (carbonic anhydrase 6). Target product profiles (TPPs) for a non-sputum biomarker test to diagnose active TB for treatment initiation (TPP#1) and for a community-based triage or referral test (TPP#2) have been published by the WHO. With 90% sensitivity and 80% specificity, the HR6 model fell short of TPP#1 but reached TPP#2 performance criteria. In conclusion, we identified and validated a six-marker signature for active TB that warrants diagnostic development on a patient-near platform.

Diagnosis of Tuberculosis in HIV Co-infected Individuals: Current Status, Challenges and Opportunities for the Future

Tuberculosis (TB) remains one of the most important causes of death among people co-infected with human immunodeficiency virus (HIV). The diagnosis of TB remains challenging in HIV co-infected individuals, due to a high frequency of smear-negative disease and high rates of extrapulmonary TB. Accurate, ease of use and rapid diagnosis of active TB are critical to the World Health Organization (WHO) End TB Strategy by 2050. Traditional laboratory techniques do not provide rapid and accurate results to effectively manage HIV co-infected patients. Over the last decade, molecular methods have provided significant steps in the fight against TB. However, many HIV co-infected patients do not have access to these molecular diagnostic tests. Given the costs closely related with confirming a TB diagnosis in HIV patients, an overtreatment for TB is used in this patient population. Nowadays, an estimated US $8 billion a year is required to provide TB treatment, which is very high compared with making an important strategy to improve the current diagnostic tests. This review focuses on current advances in diagnosing active TB with an emphasis on the diagnosis of HIV-associated TB. Also discussed are the main challenges that need to be overcome for improving an adequate initial diagnosis of active TB in HIV-positive patients.

Evaluation of pathogen-specific biomarkers for the diagnosis of tuberculosis in white-tailed deer (Odocoileus virginianus)

OBJECTIVE To develop a noninvasive biomarker-based detection system specific for Mycobacterium bovis for monitoring infection in wild animals. SAMPLE Serum samples from 8 experimentally infected yearling white-tailed deer (Odocoileus virginianus) and 3 age-matched control deer and from 393 Minnesota Department of Natural Resources hunter-harvested white-tailed deer in northwest Minnesota. PROCEDURES 8 yearling deer were inoculated with 2 × 10⁸ CFUs of virulent M bovis strain 1315 (day 0), and sera were obtained on days 0, 19, 48, and 60; sera were obtained from 3 uninoculated control deer on those same days. Sera from these deer and 9 M bovis-positive hunter-harvested deer were tested for 3 Mycobacterium-specific biomarkers (MB1895c, MB2515c, and polyketide synthase 5) by use of an indirect ELISA. That same ELISA was used to test sera obtained from 384 exposed noninfected deer in northwest Minnesota from 2007 through 2010, concurrent with an outbreak of tuberculosis involving cattle and deer in that region. RESULTS ELISA results revealed that tuberculosis infection could be detected as early as 48 days after inoculation in experimentally infected deer. Results for 384 deer sera revealed that prevalence of tuberculosis decreased over the 4-year period. CONCLUSIONS AND CLINICAL RELEVANCE Results suggested that the prevalence of tuberculosis in Minnesota deer decreased after 2009 but tuberculosis may have persisted (as subclinical disease) at extremely low levels, as indicated by the presence of low concentrations of circulating biomarkers. Biomarker-based diagnostic tests may offer a specific approach for early identification of M bovis infection.

Diagnosis of opportunistic infections: HIV co-infections - tuberculosis

PURPOSE OF REVIEW

Tuberculosis (TB) incidence has declined ∼1.5% annually since 2000, but continued to affect 10.4 million individuals in 2015, with 1/3 remaining undiagnosed or underreported. The diagnosis of TB among those co-infected with HIV is challenging as TB remains the leading cause of death in such individuals. Accurate and rapid diagnosis of active TB will avert mortality in both adults and children, reduce transmission, and assist in timeous decisions for antiretroviral therapy initiation. This review describes advances in diagnosing TB, especially among HIV co-infected individuals, highlights national program's uptake, and impact on patient care.

RECENT FINDINGS

The TB diagnostic landscape has been transformed over the last 5 years. Molecular diagnostics such as Xpert MTB/RIF, which simultaneously detects Mycobacterium tuberculosis (MTB) resistance to rifampicin, has revolutionized TB control programs. WHO endorsed the use of Xpert MTB/RIF in 2010 for use in HIV/TB co-infected patients, and later in 2013 for use as the initial diagnostic test for all adults and children with signs and symptoms of pulmonary TB. Line probe assays (LPAs) are recommended for the detection of rifampicin and isoniazid resistance in sputum smear-positive specimens and mycobacterial cultures. A second-line line probe assay has been recommended for the diagnosis of extensively drug-resistant (XDR)-TB Assays such as the urine lateral flow (LF)-lipoarabinomannan (LAM), can be used at the point of care (POC) and have a niche role to supplement the diagnosis of TB in seriously ill HIV-infected, hospitalized patients with low CD4 cell counts of less than 100 cells/μl. Polyvalent platforms such as the m2000 (Abbott Molecular) and GeneXpert (Cepheid) offer potential for integration of HIV and TB testing services. While the Research and Development (R&D) pipeline appears to be rich at first glance, there are actually few leads for true POC tests that would allow for earlier TB diagnosis or rapid, comprehensive drug susceptibility testing, especially when considering the very high attrition rates observed between biomarker discovery and product market entry.

SUMMARY

In this review, we describe diagnostic strategies specifically for HIV and TB co-infected individuals. Molecular diagnostics in particular within the past 5 years have revolutionized and 'disrupted' this field. They lend themselves to integration of services with platforms capable of polyvalent testing. Impact on patient care is, however, still debatable. What has been highlighted is the need for health system strengthening and for true POC testing that can be used in active case finding.

Meta-analysis of host response networks identifies a common core in tuberculosis

Tuberculosis remains a major global health challenge worldwide, causing more than a million deaths annually. To determine newer methods for detecting and combating the disease, it is necessary to characterise global host responses to infection. Several high throughput omics studies have provided a rich resource including a list of several genes differentially regulated in tuberculosis. An integrated analysis of these studies is necessary to identify a unified response to the infection. Such data integration is met with several challenges owing to platform dependency, patient heterogeneity, and variability in the extent of infection, resulting in little overlap among different datasets. Network-based approaches offer newer alternatives to integrate and compare diverse data. In this study, we describe a meta-analysis of host's whole blood transcriptomic profiles that were integrated into a genome-scale protein-protein interaction network to generate response networks in active tuberculosis, and monitor their behaviour over treatment. We report the emergence of a highly active common core in disease, showing partial reversals upon treatment. The core comprises 380 genes in which STAT1, phospholipid scramblase 1 (PLSCR1), C1QB, OAS1, GBP2 and PSMB9 are prominent hubs. This network captures the interplay between several biological processes including pro-inflammatory responses, apoptosis, complement signalling, cytoskeletal rearrangement, and enhanced cytokine and chemokine signalling. The common core is specific to tuberculosis, and was validated on an independent dataset from an Indian cohort. A network-based approach thus enables the identification of common regulators that characterise the molecular response to infection, providing a platform-independent foundation to leverage maximum insights from available clinical data.

Unbiased Identification of Blood-based Biomarkers for Pulmonary Tuberculosis by Modeling and Mining Molecular Interaction Networks

Efficient diagnosis of tuberculosis (TB) is met with multiple challenges, calling for a shift of focus from pathogen-centric diagnostics towards identification of host-based multi-marker signatures. Transcriptomics offer a list of differentially expressed genes, but cannot by itself identify the most influential contributors to the disease phenotype. Here, we describe a computational pipeline that adopts an unbiased approach to identify a biomarker signature. Data from RNA sequencing from whole blood samples of TB patients were integrated with a curated genome-wide molecular interaction network, from which we obtain a comprehensive perspective of variations that occur in the host due to TB. We then implement a sensitive network mining method to shortlist gene candidates that are most central to the disease alterations. We then apply a series of filters that include applicability to multiple publicly available datasets as well as additional validation on independent patient samples, and identify a signature comprising 10 genes - FCGR1A, HK3, RAB13, RBBP8, IFI44L, TIMM10, BCL6, SMARCD3, CYP4F3 and SLPI, that can discriminate between TB and healthy controls as well as distinguish TB from latent tuberculosis and HIV in most cases. The signature has the potential to serve as a diagnostic marker of TB.

Blood transcriptomic diagnosis of pulmonary and extrapulmonary tuberculosis

BACKGROUND. Novel rapid diagnostics for active tuberculosis (TB) are required to overcome the time delays and inadequate sensitivity of current microbiological tests that are critically dependent on sampling the site of disease. Multiparametric blood transcriptomic signatures of TB have been described as potential diagnostic tests. We sought to identify the best transcript candidates as host biomarkers for active TB, extend the evaluation of their specificity by comparison with other infectious diseases, and to test their performance in both pulmonary and extrapulmonary TB.

METHODS. Support vector machine learning, combined with feature selection, was applied to new and previously published blood transcriptional profiles in order to identify the minimal TB‑specific transcriptional signature shared by multiple patient cohorts including pulmonary and extrapulmonary TB, and individuals with and without HIV-1 coinfection.

RESULTS. We identified and validated elevated blood basic leucine zipper transcription factor 2 (BATF2) transcript levels as a single sensitive biomarker that discriminated active pulmonary and extrapulmonary TB from healthy individuals, with receiver operating characteristic (ROC) area under the curve (AUC) scores of 0.93 to 0.99 in multiple cohorts of HIV-1–negative individuals, and 0.85 in HIV-1–infected individuals. In addition, we identified and validated a potentially novel 4-gene signature comprising CD177, haptoglobin, immunoglobin J chain, and galectin 10 that discriminated active pulmonary and extrapulmonary TB from other febrile infections, giving ROC AUCs of 0.94 to 1.

CONCLUSIONS. Elevated blood BATF2 transcript levels provide a sensitive biomarker that discriminates active TB from healthy individuals, and a potentially novel 4-gene transcriptional signature differentiates between active TB and other infectious diseases in individuals presenting with fever.

FUNDING. MRC, Wellcome Trust, Rosetrees Trust, British Lung Foundation, NIHR.

Blood BATF2 transcripts provide a single biomarker for active tuberculosis and a novel four-gene transcriptional signature differentiates active TB from other infectious diseases with fever.

Analytical pitfalls and challenges in clinical metabolomics

Metabolomics-based strategies have become an integral part of modern clinical research, allowing for a better understanding of pathophysiological conditions and disease mechanisms, as well as providing innovative tools for more adequate diagnostic and prognosis approaches. Metabolomics is considered an essential tool in precision medicine, which aims for personalized prevention and tailor-made treatments. Nevertheless, multiple pitfalls may be encountered in clinical metabolomics during the entire workflow, hampering the quality of the data and, thus, the biological interpretation. This review describes the challenges underlying metabolomics-based experiments, discussing step by step the potential pitfalls of the analytical process, including study design, sample collection, storage, as well as preparation, chromatographic and electrophoretic separation, detection and data analysis. Moreover, it offers practical solutions and strategies to tackle these challenges, ensuring the generation of high-quality data.

Driving the Way to Tuberculosis Elimination: The Essential Role of Fundamental Research

Tuberculosis has impacted human health for millennia. The World Health Organization estimated that, in 2014, 9.6 million people developed tuberculosis and 1.5 million people died from the disease. In May 2014, the World Health Assembly endorsed the new "End TB Strategy" that presents a pathway to tuberculosis elimination. The strategy outlines 3 areas of emphasis, one of which is intensified research and innovation. In this article we highlight the essential role for fundamental tuberculosis research in the future of tuberculosis diagnostics, treatment, and prevention. To maximize the impact of fundamental research, we must foster collaboration among all stakeholders engaged in tuberculosis research and control to facilitate open dialogue to assure that critical gaps in outcome-oriented science are identified and addressed. We present here a framework for future discussions among scientists, physicians, research and development specialists, and public health managers for the reinforcement of national and international strategies toward tuberculosis elimination.

Uniting to end the TB epidemic: advances in disease control from prevention to better diagnosis and treatment

Tuberculosis is a major global cause of morbidity and mortality. Despite recent advances in containing the epidemic, several challenges continue to slow progress towards elimination including the continuing impact of drug resistant disease, and the lack of appropriate tools. Curtailing the transmission of tuberculosis remains a challenge especially in high burden countries. New developments in measuring correlates of protection are urgently needed to support the evaluation of vaccines. Similarly, despite progress in molecular diagnostics, better tools are required to identify resistance to antibiotics in multi and extensively drug resistant tuberculosis. Whole Genome Sequencing may lead to the next generation of assays to rapidly detect resistance and evaluate transmission. Advances on shortening treatment are hampered by the lack of a biomarker of cure which obviates the current long wait for relapses in trials. New research is urgently needed to support development of new vaccines and better diagnostics tools and shorter treatment for drug sensitive and resistant tuberculosis.