A comparison of four sputum pre-extraction preparation methods for identifying and characterising Mycobacterium tuberculosis using GCxGC-TOFMS metabolomics

Urinary markers of Mycobacterium tuberculosis and dysbiosis in paediatric tuberculous meningitis cases undergoing treatment

BACKGROUND

The pathogenesis of tuberculous meningitis (TBM) involves infection by Mycobacterium tuberculosis in the meninges and brain. However, recent studies have shown that the immune response and inflammatory processes triggered by TBM can have significant effects on gut microbiota. Disruptions in the gut microbiome have been linked to various systemic consequences, including altered immunity and metabolic dysregulation. Inflammation caused by TBM, antibiotic treatment, and changes in host immunity can all influence the composition of gut microbes. This complex relationship between TBM and the gut microbiome is of great importance in clinical settings. To gain a deeper understanding of the intricate interactions between TBM and the gut microbiome, we report innovative insights into the development of the disease in response to treatment. Ultimately, this could lead to improved outcomes, management strategies and quality of life for individuals affected by TBM.

METHOD

We used a targeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) approach to investigate metabolites associated with gut metabolism in paediatric participants by analysing the urine samples collected from a control group (n = 40), and an experimental group (n = 35) with confirmed TBM, which were subdivided into TBM stage 1 (n = 8), stage 2 (n = 11) and stage 3 (n = 16).

FINDINGS

Our metabolomics investigation showed that, of the 78 initially selected compounds of microbiome origin, eight unique urinary metabolites were identified: 2-methylbutyrlglycine, 3-hydroxypropionic acid, 3-methylcrotonylglycine, 4-hydroxyhippuric acid, 5-hydroxyindoleacetic acid, 5-hydroxyhexanoic acid, isobutyrylglycine, and phenylacetylglutamine as urinary markers of dysbiosis in TBM.

CONCLUSION

These results - which are supported by previous urinary studies of tuberculosis - highlight the importance of gut metabolism and of identifying corresponding microbial metabolites as novel points for the foundation of improved management of TBM patients.

Optimising a urinary extraction method for non-targeted GC-MS metabolomics

Urine is ideal for non-targeted metabolomics, providing valuable insights into normal and pathological cellular processes. Optimal extraction is critical since non-targeted metabolomics aims to analyse various compound classes. Here, we optimised a low-volume urine preparation procedure for non-targeted GC-MS. Five extraction methods (four organic acid [OA] extraction variations and a "direct analysis" [DA] approach) were assessed based on repeatability, metabolome coverage, and metabolite recovery. The DA method exhibited superior repeatability, and achieved the highest metabolome coverage, detecting 91 unique metabolites from multiple compound classes comparatively. Conversely, OA methods may not be suitable for all non-targeted metabolomics applications due to their bias toward a specific compound class. In accordance, the OA methods demonstrated limitations, with lower compound recovery and a higher percentage of undetected compounds. The DA method was further improved by incorporating an additional drying step between two-step derivatization but did not benefit from urease sample pre-treatment. Overall, this study establishes an improved low-volume urine preparation approach for future non-targeted urine metabolomics applications using GC-MS. Our findings contribute to advancing the field of metabolomics and enable efficient, comprehensive analysis of urinary metabolites, which could facilitate more accurate disease diagnosis or biomarker discovery.

The metabolic consequences of HIV/TB co-infection

BACKGROUND

The synergy between the human immunodeficiency virus (HIV) and Mycobacterium tuberculosis during co-infection of a host is well known. While this synergy is known to be driven by immunological deterioration, the metabolic mechanisms that contribute to the associated disease burden experienced during HIV/tuberculosis (TB) co-infection remain poorly understood. Furthermore, while anti-HIV treatments suppress viral replication, these therapeutics give rise to host metabolic disruption and adaptations beyond that induced by only infection or disease.

METHODS

In this study, the serum metabolic profiles of healthy controls, untreated HIV-negative TB-positive patients, untreated HIV/TB co-infected patients, and HIV/TB co-infected patients on antiretroviral therapy (ART), were measured using two-dimensional gas chromatography time-of-flight mass spectrometry. Since no global metabolic profile for HIV/TB co-infection and the effect of ART has been published to date, this pilot study aimed to elucidate the general areas of metabolism affected during such conditions.

RESULTS

HIV/TB co-infection induced significant changes to the host's lipid and protein metabolism, with additional microbial product translocation from the gut to the blood. The results suggest that HIV augments TB synergistically, at least in part, contributing to increased inflammation, oxidative stress, ART-induced mitochondrial damage, and its detrimental effects on gut health, which in turn, affects energy availability. ART reverses these trends to some extent in HIV/TB co-infected patients but not to that of healthy controls.

CONCLUSION

This study generated several new hypotheses that could direct future metabolic studies, which could be combined with other research techniques or methodologies to further elucidate the underlying mechanisms of these changes.

Insights into the Effects of Violating Statistical Assumptions for Dimensionality Reduction for Chemical "-omics" Data with Multiple Explanatory Variables

Biological volatilome analysis is inherently complex due to the considerable number of compounds (i.e., dimensions) and differences in peak areas by orders of magnitude, between and within compounds found within datasets. Traditional volatilome analysis relies on dimensionality reduction techniques which aid in the selection of compounds that are considered relevant to respective research questions prior to further analysis. Currently, compounds of interest are identified using either supervised or unsupervised statistical methods which assume the data residuals are normally distributed and exhibit linearity. However, biological data often violate the statistical assumptions of these models related to normality and the presence of multiple explanatory variables which are innate to biological samples. In an attempt to address deviations from normality, volatilome data can be log transformed. However, whether the effects of each assessed variable are additive or multiplicative should be considered prior to transformation, as this will impact the effect of each variable on the data. If assumptions of normality and variable effects are not investigated prior to dimensionality reduction, ineffective or erroneous compound dimensionality reduction can impact downstream analyses. It is the aim of this manuscript to assess the impact of single and multivariable statistical models with and without the log transformation to volatilome dimensionality reduction prior to any supervised or unsupervised classification analysis. As a proof of concept, Shingleback lizard (Tiliqua rugosa) volatilomes were collected across their species distribution and from captivity and were assessed. Shingleback volatilomes are suspected to be influenced by multiple explanatory variables related to habitat (Bioregion), sex, parasite presence, total body volume, and captive status. This work determined that the exclusion of relevant multiple explanatory variables from analysis overestimates the effect of Bioregion and the identification of significant compounds. The log transformation increased the number of compounds that were identified as significant, as did analyses that assumed that residuals were normally distributed. Among the methods considered in this work, the most conservative form of dimensionality reduction was achieved through analyzing untransformed data using Monte Carlo tests with multiple explanatory variables.

Tuberculosis is associated with sputum metabolome variations, irrespective of patient sex or HIV status: an untargeted GCxGC-TOFMS study

INTRODUCTION

Various studies have identified TB-induced metabolome variations. However, in most of these studies, a large degree of variation exists between individual patients.

OBJECTIVES

To identify differential metabolites for TB, independent of patients' sex or HIV status.

METHODS

Untargeted GCxGC/TOF-MS analyses were applied to the sputum of 31 TB + and 197 TB- individuals. Univariate statistics were used to identify metabolites which are significantly different between TB + and TB- individuals (a) irrespective of HIV status, and (b) with a HIV + status. Comparisons a and b were repeated for (i) all participants, (ii) males only and (iii) females only.

RESULTS

Twenty-one compounds were significantly different between the TB + and TB- individuals within the female subgroup (11% lipids; 10% carbohydrates; 1% amino acids, 5% other and 73% unannotated), and 6 within the male subgroup (20% lipids; 40% carbohydrates; 6% amino acids, 7% other and 27% unannotated). For the HIV + patients (TB + vs. TB-), a total of 125 compounds were significant within the female subgroup (16% lipids; 8% carbohydrates; 12% amino acids, 6% organic acids, 8% other and 50% unannotated), and 44 within the male subgroup (17% lipids; 2% carbohydrates; 14% amino acids related, 8% organic acids, 9% other and 50% unannotated). Only one annotated compound, 1-oleoyl lysophosphaditic acid, was consistently identified as a differential metabolite for TB, irrespective of sex or HIV status. The potential clinical application of this compound should be evaluated further.

CONCLUSIONS

Our findings highlight the importance of considering confounders in metabolomics studies in order to identify unambiguous disease biomarkers.

Novel Potential Diagnostic Serum Biomarkers of Metabolomics in Osteoarticular Tuberculosis Patients: A Preliminary Study

Osteoarticular tuberculosis is one of the extrapulmonary tuberculosis, which is mainly caused by direct infection of Mycobacterium tuberculosis or secondary infection of tuberculosis in other parts. Due to the low specificity of the current detection method, it is leading to a high misdiagnosis rate and subsequently affecting the follow-up treatment and prognosis. Metabolomics is mainly used to study the changes of the body’s metabolites in different states, so it can serve as an important means in the discovery of disease-related metabolic biomarkers and the corresponding mechanism research. Liquid chromatography tandem mass spectrometry (LC-MS/MS) was used to detect and analyze metabolites in the serum with osteoarticular tuberculosis patients, disease controls, and healthy controls to find novel metabolic biomarkers that could be used in the diagnosis of osteoarticular tuberculosis. Our results showed that 68 differential metabolites (p<0.05, fold change>1.0) were obtained in osteoarticular tuberculosis serum after statistical analysis. Then, through the evaluation of diagnostic efficacy, PC[o-16:1(9Z)/18:0], PC[20:4(8Z,11Z,14Z,17Z)/18:0], PC[18:0/22:5(4Z,7Z,10Z,13Z,16Z)], SM(d18:1/20:0), and SM[d18:1/18:1(11Z)] were found as potential biomarkers with high diagnostic efficacy. Using bioinformatics analysis, we further found that these metabolites share many lipid metabolic signaling pathways, such as choline metabolism, sphingolipid signaling, retrograde endocannabinoid signaling, and sphingolipid and glycerophospholipid metabolism; these results suggest that lipid metabolism plays an important role in the pathological process of tuberculosis. This study can provide certain reference value for the study of metabolic biomarkers of osteoarticular tuberculosis and the mechanism of lipid metabolism in osteoarticular tuberculosis and even other tuberculosis diseases.

Metabolomics Strategy Assisted by Transcriptomics Analysis to Identify Potential Biomarkers Associated with Tuberculosis

Purpose

To investigate the dysregulated pathways and identify reliable diagnostic biomarkers for tuberculosis using integrated analysis of metabolomics and transcriptomics.

Methods

Three groups of samples, untargeted metabolomics analysis of healthy controls (HC), latent tuberculosis infection patients (LTBI), and active tuberculosis patients (TB), were analyzed using gas chromatography time-of-flight mass spectrometry (GC-TOF MS) and ultra-high performance liquid chromatography-quantitative mass spectrometry (UHPLC-QE-MS). Both univariate and multivariate and statistical analyses were used to select differential metabolites (DMs) among group comparison, and LASSO regression analysis was employed to discover potential diagnostic biomarkers. Metabolite set enrichment analysis was performed to identify the altered metabolic pathways specifically in patients with TB. Meanwhile, a transcriptomic dataset GSEG4992 was downloaded from the GEO database to explore the differentially expressed genes (DEGs) between TB and HC identified in significantly enriched pathways. Finally, an integrative analysis of DMs and DEGs was performed to investigate the possible molecular mechanisms of TB.

Results

Thirty-three specific metabolites were significantly different between TB and HC, of which 7 (5-hydroxyindoleacetic acid, isoleucyl-isoleucine, heptadecanoic acid, indole acetaldehyde, 5-ethyl-2,4-dimethyloxazole, and 2-hydroxycaproic acid, unknown 71) were chosen as combinational potential biomarkers for TB. The area under the curve (AUC) value of these biomarkers was 0.97 (95% CI: 0.92–1.00). Metabolites set enrichment analysis (MSEA) displayed that there were 3 significantly enriched pathways among all. The genes in 3 significantly enriched pathways were further analyzed, of which 9(ALDH3B1, BCAT1, BCAT2, GLYAT, GOT1, IL4I1, MIF, SDS, SDSL) were expressed differentially. The area under the curve (AUC) values of these DEGs enriched in pathways mostly were greater than 0.8. As a result, a connected network of metabolites and genes in the pathways were established, which provides insights into the credibility of selected metabolites.

Conclusion

The newly identified metabolic biomarkers display a high potential to be developed into a promising tool for TB screening, diagnosis, and therapeutic effect monitoring.

Differential Diagnosis of Latent Tuberculosis Infection and Active Tuberculosis: A Key to a Successful Tuberculosis Control Strategy

As an ancient infectious disease, tuberculosis (TB) is still the leading cause of death from a single infectious agent worldwide. Latent TB infection (LTBI) has been recognized as the largest source of new TB cases and is one of the biggest obstacles to achieving the aim of the End TB Strategy. The latest data indicate that a considerable percentage of the population with LTBI and the lack of differential diagnosis between LTBI and active TB (aTB) may be potential reasons for the high TB morbidity and mortality in countries with high TB burdens. The tuberculin skin test (TST) has been used to diagnose TB for > 100 years, but it fails to distinguish patients with LTBI from those with aTB and people who have received Bacillus Calmette–Guérin vaccination. To overcome the limitations of TST, several new skin tests and interferon-gamma release assays have been developed, such as the Diaskintest, C-Tb skin test, EC-Test, and T-cell spot of the TB assay, QuantiFERON-TB Gold In-Tube, QuantiFERON-TB Gold-Plus, LIAISON QuantiFERON-TB Gold Plus test, and LIOFeron TB/LTBI. However, these methods cannot distinguish LTBI from aTB. To investigate the reasons why all these methods cannot distinguish LTBI from aTB, we have explained the concept and definition of LTBI and expounded on the immunological mechanism of LTBI in this review. In addition, we have outlined the research status, future directions, and challenges of LTBI differential diagnosis, including novel biomarkers derived from Mycobacterium tuberculosis and hosts, new models and algorithms, omics technologies, and microbiota.

M. tuberculosis curli pili (MTP) is associated with alterations in carbon, fatty acid and amino acid metabolism in a THP-1 macrophage infection model

The initial host-pathogen interaction is crucial for the establishment of infection. An improved understanding of the pathophysiology of Mycobacterium tuberculosis (M. tuberculosis) during macrophage infection can aid the development of intervention therapeutics against tuberculosis. M. tuberculosis curli pili (MTP) is a surface located adhesin, involved in the first point-of-contact between pathogen and host. This study aimed to better understand the role of MTP in modulating the intertwined metabolic pathways of M. tuberculosis and its THP-1 macrophage host. Metabolites were extracted from pelleted wet cell mass of THP-1 macrophages infected with M. tuberculosis wild-type V9124 (WT), Δmtp-deletion mutant and the mtp-complemented strains, respectively, via a whole metabolome extraction method using a 1:3:1 ratio of chloroform:methanol:water. Metabolites were detected by two-dimensional gas chromatography time-of-flight mass spectrometry. Significant metabolites were determined through univariate and multivariate statistical tests and online pathway databases. Relative to the WT, a total of nine and ten metabolites were significantly different in the Δmtp and complement strains, respectively. All nine significant metabolites were found in elevated levels in the Δmtp relative to the WT. Additionally, of the ten significant metabolites, eight were detected in lower levels and two were detected in higher levels in the complement relative to the WT. The absence of the MTP adhesin resulted in reduced virulence of M. tuberculosis leading to alterations in metabolites involved in carbon, fatty acid and amino acid metabolism during macrophage infection, suggesting that MTP plays an important role in the modulation of host metabolic activity. These findings support the prominent role of the MTP adhesin as a virulence factor as well as a promising biomarker for possible diagnostic and therapeutic intervention.

Human tuberculosis and Mycobacterium tuberculosis complex: A review on genetic diversity, pathogenesis and omics approaches in host biomarkers discovery

Mycobacterium tuberculosis complex (MTBC) refers to a group of mycobacteria encompassing nine members of closely related species that causes tuberculosis in animals and humans. Among the nine members, Mycobacterium tuberculosis (M. tuberculosis) remains the main causative agent for human tuberculosis that results in high mortality and morbidity globally. In general, MTBC species are low in diversity but exhibit distinctive biological differences and phenotypes among different MTBC lineages. MTBC species are likely to have evolved from a common ancestor through insertions/deletions processes resulting in species speciation with different degrees of pathogenicity. The pathogenesis of human tuberculosis is complex and remains poorly understood. It involves multi-interactions or evolutionary co-options between host factors and bacterial determinants for survival of the MTBC. Granuloma formation as a protection or survival mechanism in hosts by MTBC remains controversial. Additionally, MTBC species are capable of modulating host immune response and have adopted several mechanisms to evade from host immune attack in order to survive in humans. On the other hand, current diagnostic tools for human tuberculosis are inadequate and have several shortcomings. Numerous studies have suggested the potential of host biomarkers in early diagnosis of tuberculosis, in disease differentiation and in treatment monitoring. "Multi-omics" approaches provide holistic views to dissect the association of MTBC species with humans and offer great advantages in host biomarkers discovery. Thus, in this review, we seek to understand how the genetic variations in MTBC lead to species speciation with different pathogenicity. Furthermore, we also discuss how the host and bacterial players contribute to the pathogenesis of human tuberculosis. Lastly, we provide an overview of the journey of "omics" approaches in host biomarkers discovery in human tuberculosis and provide some interesting insights on the challenges and directions of "omics" approaches in host biomarkers innovation and clinical implementation.

Neutral Desorption Extractive Electrospray Ionization Mass Spectrometry Analysis Sputum for Non-Invasive Lung Adenocarcinoma Detection

Purpose

Increased use of low-dose spiral computed tomography (LDCT: low-dose computed tomography) screening has contributed to more frequent incidental detection of peripheral lung nodules, part of them were adenocarcinoma, which need to be further evaluated to establish a definitive diagnosis. Here, our primary objective was to evaluate the ambient mass spectrometry (AMS) sputum analysis as a non-invasive lung adenocarcinoma (LAC) diagnosis solution.

Patients and Methods

Neutral desorption extractive electrospray ionization mass spectrometry (ND-EESI-MS) and collision induced dissociation (CID) were used to detect sputum metabolites from 143 spontaneous sputum samples. Partial least squares-discriminant analysis (PLS-DA) was used to refine the biomarker panel, whereas orthogonal PLS-DA (OPLS-DA) was used to operationalize the enhanced biomarker panel for diagnosis.

Results

In this approach, 19 altered metabolites were detected by ND-EESI-MS from 76 cases of LAC and 67 cases of control. Significance testing and receiver operating characteristic (ROC) analysis identified 5 metabolites [hydroxyphenyllactic acid, phytosphingosine, N-nonanoylglycine, sphinganine, S-carboxymethyl-L-cysteine] with p <0.05 and AUC >0.75, respectively. Evaluation of model performance for prediction of LAC resulted in a cross-validation classification accuracy of 87.9%. Metabolic pathway analysis showed that sphingolipid metabolism, fatty acid metabolism, carnitine synthesis and Warburg effect were most impacted in response to disease.

Conclusion

This study indicates that the application of ND-EESI-MS to sputum analysis can be used as a non-invasive detection of peripheral lung nodules. The use of sputum metabolite biomarkers may aid in the development of a further evaluation program for lung adenocarcinoma.

Identification of serum biomarkers for active pulmonary tuberculosis using a targeted metabolomics approach

Although tuberculosis (TB) is a severe health problem worldwide, the current diagnostic methods are far from optimal. Metabolomics is increasingly being used in the study of infectious diseases. We performed metabolome profiling to identify potential biomarkers in patients with active TB. Serum samples from 21 patients with active pulmonary TB, 20 subjects with latent TB infection (LTBI), and 28 healthy controls were analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS) followed by multivariate and univariate analyses. Metabolic profiles indicated higher serum levels of glutamate, sulfoxy methionine, and aspartate and lower serum levels of glutamine, methionine, and asparagine in active TB patients than in LTBI subjects or healthy controls. The ratios between metabolically related partners (glutamate/glutamine, sulfoxy methionine/methionine, and aspartate/asparagine) were also elevated in the active TB group. There was no significant difference in the serum concentration of these metabolites according to the disease extent or risk of relapse in active TB patients. Novel serum biomarkers such as glutamate, sulfoxy methionine, aspartate, glutamine, methionine, and asparagine are potentially useful for adjunctive, rapid, and noninvasive pulmonary TB diagnosis.

Metabolite Profiling: A Tool for the Biochemical Characterisation of Mycobacterium sp

Over the last decades, the prevalence of drug-resistance in Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis, has increased. These findings have rekindled interest in elucidating the unique adaptive molecular and biochemistry physiology of Mycobacterium. The use of metabolite profiling independently or in combination with other levels of "-omic" analyses has proven an effective approach to elucidate key physiological/biochemical mechanisms associated with Mtb throughout infection. The following review discusses the use of metabolite profiling in the study of tuberculosis, future approaches, and the technical and logistical limitations of the methodology.

The application of metabolomics toward pulmonary tuberculosis research

In the quest to identify novel biomarkers for pulmonary tuberculosis (TB), high-throughput systems biology approaches such as metabolomics has become increasingly widespread. Such biomarkers have not only successfully been used for better disease characterization, but have also provided new insights toward the future development of improved diagnostic and therapeutic approaches. In this review, we give a summary of the metabolomics studies done to date, with a specific focus on those investigating various aspects of pulmonary TB, and the infectious agent responsible, Mycobacterium tuberculosis. These studies, done on a variety of sample matrices, including bacteriological culture, sputum, blood, urine, tissue, and breath, are discussed in terms of their intended research outcomes or future clinical applications. Additionally, a summary of the research model, sample cohort, analytical apparatus and statistical methods used for biomarker identification in each of these studies, is provided.

Advances in the application of comprehensive two-dimensional gas chromatography in metabolomics

Due to excellent separation capacity for complex mixtures of chemicals, comprehensive two-dimensional gas chromatography (GC × GC) is being utilized with increasing frequency for metabolomics analyses. This review describes recent advances in GC × GC method development for metabolomics, organismal sampling techniques compatible with GC × GC, metabolomic discoveries made using GC × GC, and recommendations and best practices for collecting and reporting GC × GC metabolomics data.

Opportunities for green microextractions in comprehensive two-dimensional gas chromatography / mass spectrometry-based metabolomics - A review

Microextractions have become an attractive class of techniques for metabolomics. The most popular technique is solid-phase microextraction that revolutionized the field of modern sample preparation in the early nineties. Ever since this milestone, microextractions have taken on many principles and formats comprising droplets, fibers, membranes, needles, and blades. Sampling devices may be customized to impart exhaustive or equilibrium-based characteristics to the extraction method. Equilibrium-based approaches may rely on additional methods for calibration, such as diffusion-based or on-fiber kinetic calibration to improve bioanalysis. In addition, microextraction-based methods may enable minimally invasive sampling protocols and measure the average free concentration of analytes in heterogeneous multiphasic biological systems. On-fiber derivatization has evidenced new opportunities for targeted and untargeted analysis in metabolomics. All these advantages have highlighted the potential of microextraction techniques for in vivo and on-site sampling and sample preparation, while many opportunities are still available for laboratory protocols. In this review, we outline and discuss some of the most recent applications using microextractions techniques for comprehensive two-dimensional gas chromatography-based metabolomics, including potential research opportunities.

Altered phosphatidylcholines expression in sputum for diagnosis of non-small cell lung cancer

Non–small cell lung cancer (NSCLC) is a leading cause of cancer mortality worldwide, and early diagnosis needs to be improved. We examined whether neutral desorption extractive electrospray ionization mass spectrometry (ND-EESI-MS) could be used to detect sputum lipids expression changes to enable earlier diagnosis. Overall, 167 NSCLC patients and 140 controls were enrolled. The main peaks in the sputum of patients with NSCLC patients differed from controls (83.3% of total variability), and the signals were not associated with pathological type, TNM stage or smoking history. The relative abundance of peaks at m/z734, m/ z756, m/z772, m/z782, m/z798 and m/z803 reliably distinguished NSCLC sputum from control. Collision-induced dissociation confirmed that m/z734, m/z756, and m/z772 represented [DPPC + H]⁺, [DPPC + Na]⁺, and [DPPC + K]⁺, respectively, and m/z782, m/z798, and m/z803 represented sphingomyelin, phosphatidylglycerol, and phosphatidylglycerolphosphate, respectively. The relative abundance of DPPC was clearly lower in NSCLC sputum than in control, and the relative abundances of phosphatidylglycerol and phosphatidylglycerolphosphate were higher in NSCLC sputum than in control. The detection of changes in sputum lipids with ND-EESI-MS may be a noninvasive, radiation-free, relatively inexpensive, repeatable, and efficient method for diagnosis of NSCLC.

Metabolomic profiling of Campylobacter jejuni with resistance gene ermB by ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry and tandem quadrupole mass spectrometry

The metabolome changes of Campylobacter jejuni with resistant gene ermB remain unclear. Here, we described an untargeted metabolomic workflow based on ultra-high performance liquid chromatography-quadrupole time-of-flight mass spectrometry to investigate the metabolites perturbations mediated by ermB in C. jejuni. After optimization of extractants and chromatographic conditions, the combination of 100% methanol extraction with a 12 min gradient by C18 column was adopted for untargeted metabolomic profiling in reversed phase separation. Meanwhile, 60% methanol extraction followed by a 14 min separation using hydrophilic interaction chromatography column was suitable to complementally expand the metabolite coverage of C. jejuni. Multivariate statistical analysis was performed by means of orthogonal projection to latent structures-discriminant analysis to select metabolic features. The selected features were further confirmed by ultra-high performance liquid chromatography-tandem quadrupole mass spectrometry. A total of thirty-six differential metabolites between the susceptible strain (C. jejuni NCTC 11168) and resistant stain (C. jejuni NCTC 11168 with ermB) were identified. These pivotal metabolites were primarily participated in biological processes as cell signaling, membrane integrity/stability, fuel and energy source/storage and nutrient. The biofilm formation capability of resistant strain was inferior to that of susceptible strain, confirming the influence of ermB on membrane integrity/stability of C. jejuni. Our findings revealed important metabolic regulatory pathways associated with resistant C. jejuni with ermB.

Headspace solid-phase microextraction coupled to comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry for the analysis of aerosol from tobacco heating product

A method involving headspace solid-phase microextraction (HS-SPME) and comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry (GC×GC-TOFMS) was developed and optimised to elucidate the volatile composition of the particulate phase fraction of aerosol produced by tobacco heating products (THPs). Three SPME fiber types were studied in terms of extraction capacity and precision measurements. Divinylbenzene polydimethylsiloxane appeared as the most efficient coating for these measurements. A central composite design of experiment was utilised for the optimization of the extraction conditions. Qualitative and semi-quantitative analysis of the headspace above THP aerosol condensate was carried out using optimised extraction conditions. Semi-quantitative analyses of detected constituents were performed by assuming that their relative response factors to the closest internal standard (itR) were equal to 1. Using deconvoluted mass spectral data (library similarity and reverse match >750) and linear retention indices (match window of ±15 index units), 205 peaks were assigned to individual compounds, 82 of which (including 43 substances previously reported to be present in tobacco) have not been reported previously in tobacco aerosol. The major volatile fraction of the headspace contained ketones, alcohols, aldehydes, alicyclic hydrocarbons alkenes, and alkanes. The method was further applied to compare the volatiles from the particulate phase of aerosol composition of THP with that of reference cigarette smoke and showed that the THP produced a less complex chemical mixture. This new method showed good efficiency and precision for the peak areas and peak numbers from the volatile fraction of aerosol particulate phase for both THP and reference cigarettes.

Early diagnosis and effective treatment regimens are the keys to tackle antimicrobial resistance in tuberculosis (TB): A report from Euroscicon's international TB Summit 2016

To say that tuberculosis (TB) has regained a strong foothold in the global human health and wellbeing scenario would be an understatement. Ranking alongside HIV/AIDS as the top reason for mortality due to a single infectious disease, the impact of TB extends far into socio-economic context worldwide. As global efforts led by experts and political bodies converge to mitigate the predicted outcome of growing antimicrobial resistance, the academic community of students, practitioners and researchers have mobilised to develop integrated, inter-disciplinary programmes to bring the plans of the former to fruition. Enabling this crucial requirement for unimpeded dissemination of scientific discovery was the TB Summit 2016, held in London, United Kingdom. This report critically discusses the recent breakthroughs made in diagnostics and treatment while bringing to light the major hurdles in the control of the disease as discussed in the course of the 3-day international event. Conferences and symposia such as these are the breeding grounds for successful local and global collaborations and therefore must be supported to expand the understanding and outreach of basic science research.

Metabolomics biomarkers for tuberculosis diagnostics: current status and future objectives

Numerous studies have contributed to our current understanding of the complex biology of pulmonary tuberculosis and subsequently provided solutions to its control or eradication. Metabolomics, a newcomer to the Omics research domain, has significantly contributed to this understanding by identifying biomarkers originating from the disease-associated metabolome adaptations of both the microbe and host. These biomarkers have shed light on previously unknown disease mechanisms, many of which have been implemented toward the development of improved diagnostic strategies. In this review, we will discuss the role that metabolomics has played in tuberculosis research to date, with a specific focus on new biomarker identification, and how these have contributed to improved disease characterization and diagnostics, and their potential clinical applications.

A metabolomics investigation of the function of the ESX-1 gene cluster in mycobacteria

The ESX-1 gene cluster, encoding the Type-VII secretion (T7S) system and its virulence associated proteins, ESAT-6 and CFP-10, is thought to be responsible for the transport of extracellular proteins across the hydrophobic and highly impermeable, cell envelope of Mycobacterium, and is involved in virulence in Mycobacterium tuberculosis, the causative agent of tuberculosis. Using a GCxGC-TOFMS metabolomics approach, a M. smegmatis ESX-1 knock-out strain (ΔESX-1_ms) was compared to that of the M. smegmatis wild-type parent strain, and the metabolite markers due to the presence or absence of the ESX-1 gene cluster were identified. A general increase in specific metabolites in the ΔESX-1_ms, confirmed the roles previously described for ESX-1 in mycolic acid biosynthesis and cell wall integrity. However, a number of other metabolite markers identified indicates ESX-1 has an additional role the in cell envelope structure, altering the levels of antioxidants and energy metabolism. Furthermore, the metabolome profiles correlated with the metabolomic variation observed when comparing a hyper- and hypo-virulent Beijing strain of M. tuberculosis, suggesting that the pathways which modulate virulence in M. tuberculosis are also influenced by ESX-1, reaffirming the previously described association of ESX-1 with virulence and cell envelope biogenesis.

Metabolomics: Applications and Promise in Mycobacterial Disease

Until recently, the study of mycobacterial diseases was trapped in culture-based technology that is more than a century old. The use of nucleic acid amplification is changing this, and powerful new technologies are on the horizon. Metabolomics, which is the study of sets of metabolites of both the bacteria and host, is being used to clarify mechanisms of disease, and can identify changes leading to better diagnosis, treatment, and prognostication of mycobacterial diseases. Metabolomic profiles are arrays of biochemical products of genes in their environment. These complex patterns are biomarkers that can allow a more complete understanding of cell function, dysfunction, and perturbation than genomics or proteomics. Metabolomics could herald sweeping advances in personalized medicine and clinical trial design, but the challenges in metabolomics are also great. Measured metabolite concentrations vary with the timing within a condition, the intrinsic biology, the instruments, and the sample preparation. Metabolism profoundly changes with age, sex, variations in gut microbial flora, and lifestyle. Validation of biomarkers is complicated by measurement accuracy, selectivity, linearity, reproducibility, robustness, and limits of detection. The statistical challenges include analysis, interpretation, and description of the vast amount of data generated. Despite these drawbacks, metabolomics provides great opportunity and the potential to understand and manage mycobacterial diseases.

Canonical pathways, networks and transcriptional factor regulation by clinical strains of Mycobacterium tuberculosis in pulmonary alveolar epithelial cells

Limited knowledge exists on pathways, networks and transcriptional factors regulated within epithelial cells by diverse Mycobacterium tuberculosis genotypes. This study aimed to elucidate these mechanisms induced in A549 epithelial cells by dominant clinical strains in KwaZulu-Natal, South Africa. RNA for sequencing was extracted from epithelial cells at 48 h post-infection with 5 strains at a multiplicity of infection of approximately 10:1. Bioinformatics analysis performed with the RNA-Seq Tuxedo pipeline identified differentially expressed genes. Changes in pathways, networks and transcriptional factors were identified using Ingenuity Pathway Analysis (IPA). The interferon signalling and hepatic fibrosis/hepatic stellate cell activation pathways were among the top 5 canonical pathways in all strains. Hierarchical clustering for enrichment of cholesterol biosynthesis and immune associated pathways revealed similar patterns for Beijing and Unique; F15/LAM4/KZN and F11; and, F28 and H37Rv strains, respectively. However, the induction of top scoring networks varied among the strains. Among the transcriptional factors, only EHL, IRF7, PML, STAT1, STAT2 and VDR were induced by all clinical strains. Activation of the different pathways, networks and transcriptional factors revealed in the current study may be an underlying mechanism that results in the differential host response by clinical strains of M. tuberculosis.

New insights into the survival mechanisms of rifampicin-resistant Mycobacterium tuberculosis

OBJECTIVES

Rifampicin is considered the most important antibiotic for treating TB, but unfortunately Mycobacterium tuberculosis is rapidly developing resistance to this drug. Despite the fervent research efforts to date, TB is still a major global problem, and hence new approaches are necessary to better characterize this disease, especially the mechanisms relating to drug resistance.

METHODS

Using a two-dimensional GC-coupled time-of-flight MS metabolomics approach, the most important metabolite markers characterizing rifampicin-resistant M. tuberculosis were identified.

RESULTS

The metabolite markers identified indicate instability in rifampicin-resistant M. tuberculosis mRNA, induced by the rpoB mutation. This results in a total depletion of aconitic acid, due to a shift in aconitase functionality towards mRNA binding and stability, and away from energy production and growth, and a subsequent increased dependency on alternative energy sources, fatty acids in particular. A number of other metabolic changes were observed, confirming an additional survival response for maintaining/remodelling the cell wall.

CONCLUSIONS

This study shows the value of a metabolomics approach to biological investigations in a quest to better understand disease-causing organisms and their tolerance to existing medications, which would in the future undoubtedly assist in the development of alternative treatment approaches.

Neglected diseases prioritized in Brazil under the perspective of metabolomics: A review

This review article compiles in a critical manner literature publications regarding seven neglected diseases (ND) prioritized in Brazil (Chagas disease, dengue, leishmaniasis, leprosy, malaria, schistosomiasis, and tuberculosis) under the perspective of metabolomics. Both strategies, targeted and untargeted metabolomics, were considered in the compilation. The majority of studies focused on biomarker discovery for diagnostic purposes, and on the search of novel or alternative therapies against the ND under consideration, although temporal progression of the infection at metabolic level was also addressed. Tuberculosis, followed by schistosomiasis, malaria and leishmaniasis are the diseases that received larger attention in terms of number of publications. Dengue and leprosy were the least studied and Chagas disease received intermediate attention. NMR and HPLC-MS technologies continue to predominate among the analytical platforms of choice in the metabolomic studies of ND. A plethora of metabolites were identified in the compiled studies, with expressive predominancy of amino acids, organic acids, carbohydrates, nucleosides, lipids, fatty acids, and derivatives.

Rapid diagnosis of TB using GC-MS and chemometrics

The search continues for a rapid diagnostic test for TB that has high sensitivity and specificity and is useable in sophisticated environments and in deprived regions with poor infrastructure. We discuss here the modern bioanalytical techniques that can be used to discover biomarkers of infection with Mycobacterium tuberculosis, focusing on techniques using GC. We will also discuss the use of GC-MS to identify volatile organic compounds in the headspace of bacterial culture or in samples of breath, serum or urine. Biomarkers discovered in the 'clean' environment of culture may differ from those in patients. A number of biomarkers have been found in patients, with little consistency in the various studies to date. Reproducibility is difficult; the impressive results found initially with a few patients are rarely repeatable when a larger sample series is tested. Mycobacterial lipids offer promise for distinguishing M. tuberculosis from nontuberculous mycobacteria directly in sputum.

The use of functional genomics in conjunction with metabolomics for Mycobacterium tuberculosis research

Tuberculosis (TB), caused by Mycobacterium tuberculosis, is a fatal infectious disease, resulting in 1.4 million deaths globally per annum. Over the past three decades, genomic studies have been conducted in an attempt to elucidate the functionality of the genome of the pathogen. However, many aspects of this complex genome remain largely unexplored, as approaches like genomics, proteomics, and transcriptomics have failed to characterize them successfully. In turn, metabolomics, which is relatively new to the “omics” revolution, has shown great potential for investigating biological systems or their modifications. Furthermore, when these data are interpreted in combination with previously acquired genomics, proteomics and transcriptomics data, using what is termed a systems biology approach, a more holistic understanding of these systems can be achieved. In this review we discuss how metabolomics has contributed so far to characterizing TB, with emphasis on the resulting improved elucidation of M. tuberculosis in terms of (1) metabolism, (2) growth and replication, (3) pathogenicity, and (4) drug resistance, from the perspective of systems biology.

An altered Mycobacterium tuberculosis metabolome induced by katG mutations resulting in isoniazid resistance

The most common form of drug resistance found in tuberculosis (TB)-positive clinical samples is monoresistance to isoniazid. Various genomics and proteomics studies to date have investigated this phenomenon; however, the exact mechanisms relating to how this occurs, as well as the implications of this on the TB-causing organisms function and structure, are only partly understood. Considering this, we followed a metabolomics research approach to identify potential new metabolic pathways and metabolite markers, which when interpreted in context would give a holistic explanation for many of the phenotypic characteristics associated with a katG mutation and the resulting isoniazid resistance in Mycobacterium tuberculosis. In order to achieve these objectives, gas chromatography-time of flight mass spectrometry (GCxGC-TOFMS)-generated metabolite profiles from two isoniazid-resistant strains were compared to a wild-type parent strain. Principal component analyses showed clear differentiation between the groups, and the metabolites best describing the separation between these groups were identified. It is clear from the data that due to a mutation in the katG gene encoding catalase, the isoniazid-resistant strains experience increased susceptibility to oxidative stress and have consequently adapted to this by upregulating the synthesis of a number of compounds involved in (i) increased uptake and use of alkanes and fatty acids as a source of carbon and energy and (ii) the synthesis of a number of compounds directly involved in reducing oxidative stress, including an ascorbic acid degradation pathway, which to date hasn't been proposed to exist in these organisms.

New sputum metabolite markers implicating adaptations of the host to Mycobacterium tuberculosis, and vice versa

In this study, a metabolomics research approach was used to identify new tuberculosis (TB) markers from sputum, in an attempt to better characterise the disease as well as the metabolic response of the host to Mycobacterium tuberculosis infection. After GCxGC-TOFMS analyses, various multivariate and univariate statistical methods were implemented to identify those compounds best describing the variation between the TB-positive and TB-negative patient groups. The interpretation of these new metabolite markers led to a number of new hypotheses, including: 1) support of the previously proposed citramalate cycle in M. tuberculosis; 2) the interaction of this cycle with an up-regulated glyoxylate cycle during pulmonary M. tuberculosis infection; 3) the increased utilisation of fatty acids and glutamate as alternative carbon sources by M. tuberculosis during pulmonary infection; 4) an alternative mechanism by which the host produces hydrogen peroxide via glucose oxidation, in order to eliminate the bacterial infection; 5) inhibition of the ETC due to pronounced oxidative stress during an active TB disease state, resulting in increased concentrations of various neurotransmitters and other metabolites previously associated with an inborn error of metabolism (MADD/GA type II); and 6) elevated concentrations of neurotransmitters associated with a number of previously described symptoms of TB.