Metabolic profiles of multidrug resistant and extensively drug resistant Mycobacterium tuberculosis unveiled by metabolomics

Mass spectrometry-based metabolomics for the investigation of antibiotic-bacterial interactions

With the development of analytical technologies especially mass spectrometry, metabolomics is becoming increasingly hot in the field of studying antibiotic-bacterial interactions. On the one hand, metabolomics can reveal metabolic perturbations in bacteria in the presence of antibiotics and expose metabolic mechanisms. On the other hand, through in-depth analysis of bacterial metabolic profiles, biomarkers and bioactive secondary metabolites with great potential as drug precursors can be discovered. This review focuses on the experimental workflow of bacterial metabolomics and its application to study the interaction between bacteria and antibiotics. Metabolomics improves the understanding of antibiotic lethality, reveals metabolic perturbations in antibiotic-resistant bacteria, guides the diagnosis and antibiotic treatment of infectious diseases, and aids in the exploration of antibacterial metabolites in nature. Furthermore, current limitations and directions for future developments in this area are discussed.

Metabolic remodeling by RNA polymerase gene mutations is associated with reduced β-lactam susceptibility in oxacillin-susceptible MRSA

The emergence of oxacillin-susceptible methicillin-resistant Staphylococcus aureus (OS-MRSA) has imposed further challenges to the clinical management of MRSA infections. When exposed to β-lactam antibiotics, these strains can easily acquire reduced β-lactam susceptibility through chromosomal mutations, including those in RNA polymerase (RNAP) genes such as rpoBC, which may then lead to treatment failure. Despite the increasing prevalence of such strains and the apparent challenges they pose for diagnosis and treatment, there is limited information available on the actual mechanisms underlying such chromosomal mutation-related transitions to reduced β-lactam susceptibility, as it does not directly associate with the expression of mecA. This study investigated the cellular physiology and metabolism of six missense mutants with reduced oxacillin susceptibility, each carrying respective mutations on RpoBH929P, RpoBQ645H, RpoCG950R, RpoCG498D, RpiAA64E, and FruBA211E, using capillary electrophoresis-mass spectrometry-based metabolomics analysis. Our results showed that rpoBC mutations caused RNAP transcription dysfunction, leading to an intracellular accumulation of ribonucleotides. These mutations also led to the accumulation of UDP-Glc/Gal and UDP-GlcNAc, which are precursors of UTP-associated peptidoglycan and wall teichoic acid. Excessive amounts of building blocks then contributed to the cell wall thickening of mutant strains, as observed in transmission electron microscopy, and ultimately resulted in decreased susceptibility to β-lactam in OS-MRSA.

IMPORTANCE

The emergence of oxacillin-susceptible methicillin-resistant Staphylococcus aureus (OS-MRSA) strains has created new challenges for treating MRSA infections. These strains can become resistant to β-lactam antibiotics through chromosomal mutations, including those in the RNA polymerase (RNAP) genes such as rpoBC, leading to treatment failure. This study investigated the mechanisms underlying reduced β-lactam susceptibility in four rpoBC mutants of OS-MRSA. The results showed that rpoBC mutations caused RNAP transcription dysfunction, leading to an intracellular accumulation of ribonucleotides and precursors of peptidoglycan as well as wall teichoic acid. This, in turn, caused thickening of the cell wall and ultimately resulted in decreased susceptibility to β-lactam in OS-MRSA. These findings provide insights into the mechanisms of antibiotic resistance in OS-MRSA and highlight the importance of continued research in developing effective treatments to combat antibiotic resistance.

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.

Translating eco-evolutionary biology into therapy to tackle antibiotic resistance

Antibiotic resistance is currently one of the most important public health problems. The golden age of antibiotic discovery ended decades ago, and new approaches are urgently needed. Therefore, preserving the efficacy of the antibiotics currently in use and developing compounds and strategies that specifically target antibiotic-resistant pathogens is critical. The identification of robust trends of antibiotic resistance evolution and of its associated trade-offs, such as collateral sensitivity or fitness costs, is invaluable for the design of rational evolution-based, ecology-based treatment approaches. In this Review, we discuss these evolutionary trade-offs and how such knowledge can aid in informing combination or alternating antibiotic therapies against bacterial infections. In addition, we discuss how targeting bacterial metabolism can enhance drug activity and impair antibiotic resistance evolution. Finally, we explore how an improved understanding of the original physiological function of antibiotic resistance determinants, which have evolved to reach clinical resistance after a process of historical contingency, may help to tackle antibiotic resistance.

Trends and challenges of multi-drug resistance in childhood tuberculosis

Drug-resistant tuberculosis (DR-TB) in children is a growing global health concern, This review provides an overview of the current epidemiology of childhood TB and DR-TB, including prevalence, incidence, and mortality. We discuss the challenges in diagnosing TB and DR-TB in children and the limitations of current diagnostic tools. We summarize the challenges associated with treating multi-drug resistance TB in childhood, including limitations of current treatment options, drug adverse effects, prolonged regimens, and managing and monitoring during treatment. We highlight the urgent need for improved diagnosis and treatment of DR-TB in children. The treatment of children with multidrug-resistant tuberculosis will be expanded to include the evaluation of new drugs or new combinations of drugs. Basic research is needed to support the technological development of biomarkers to assess the phase of therapy, as well as the urgent need for improved diagnostic and treatment options.

Metabolomic analysis of Mycobacterium tuberculosis reveals metabolic profiles for identification of drug-resistant tuberculosis

The detection of pre-extensively (pre-XDR) and extensively drug-resistant tuberculosis (XDR-TB) is challenging. Drug-susceptibility tests for some anti-TB drugs, especially ethambutol (ETH) and ethionamide (ETO), are problematic due to overlapping thresholds to differentiate between susceptible and resistant phenotypes. We aimed to identify possible metabolomic markers to detect Mycobacterium tuberculosis (Mtb) strains causing pre-XDR and XDR-TB. The metabolic patterns of ETH- and ETO-resistant Mtb isolates were also investigated. Metabolomics of 150 Mtb isolates (54 pre-XDR, 63 XDR-TB and 33 pan-susceptible; pan-S) were investigated. Metabolomics of ETH and ETO phenotypically resistant subgroups were analyzed using UHPLC-ESI-QTOF-MS/MS. Orthogonal partial least-squares discriminant analysis revealed distinct separation in all pairwise comparisons among groups. Two metabolites (meso-hydroxyheme and itaconic anhydride) were able to differentiate the pre-XDR and XDR-TB groups from the pan-S group with 100% sensitivity and 100% specificity. In comparisons of the ETH and ETO phenotypically resistant subsets, sets of increased (ETH = 15, ETO = 7) and decreased (ETH = 1, ETO = 6) metabolites specific for the resistance phenotype of each drug were found. We demonstrated the potential for metabolomics of Mtb to differentiate among types of DR-TB as well as between isolates that were phenotypically resistant to ETO and ETH. Thus, metabolomics might be further applied for DR-TB diagnosis and patient management.

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.

The Role of Amino Acids in Tuberculosis Infection: A Literature Review

Recently, there was an abundance of studies being conducted on the metabolomic profiling of tuberculosis patients. Amino acids are critical metabolites for the immune system, as they might contribute to providing nutrients for the host intracellular pathway. In tuberculosis, several amino acids play important roles in both the mycobacteria infection mechanism and the host. Individual studies showed how the dynamics of metabolite products that result from interactions between Mycobacterium tuberculosis (Mtb) and the host play important roles in different stages of infection. In this review, we focus on the dynamics of amino-acid metabolism and identify the prominent roles of amino acids in the diagnostics and treatment of tuberculosis infection. Online resources, including PubMed, ScienceDirect, Scopus, and Clinical Key, were used to search for articles with combination keywords of amino acids and TB. The inclusion criteria were full-text articles in English published in the last 10 years. Most amino acids were decreased in patients with active TB compared with those with latent TB and healthy controls. However, some amino acids, including leucine, isoleucine, valine, phenylalanine, aspartate, and glutamate, were found to be at higher levels in TB patients. Additionally, the biomarkers of Mtb infection included the ratios of kynurenine to tryptophan, phenylalanine to histidine, and citrulline to arginine. Most amino acids were present at different levels in different stages of infection and disease progression. The search for additional roles played by those metabolomic biomarkers in each stage of infection might facilitate diagnostic tools for staging TB infection.

Rational development of mycobacteria cell factory for advancing the steroid biomanufacturing

Steroidal resource occupies a vital proportion in the pharmaceutical industry attributing to their important therapeutic effects on fertility, anti-inflammatory and antiviral activities. Currently, microbial transformation from phytosterol has become the dominant strategy of steroidal drug intermediate synthesis that bypasses the traditional chemical route. Mycobacterium sp. serve as the main industrial microbial strains that are capable of introducing selective functional modifications of steroidal intermediate, which has become an indispensable platform for steroid biomanufacturing. By reviewing the progress in past two decades, the present paper concentrates mainly on the microbial rational modification aspects that include metabolic pathway editing, key enzymes engineering, material transport pathway reinforcement, toxic metabolic intermediates removal and byproduct reconciliation. In addition, progress on omics analysis and direct genetic manipulation are summarized and classified that may help reform the industrial hosts with more efficiency. The paper provides an insightful present for steroid biomanufacturing especially on the current trends and prospects of mycobacteria.

Screening of Microbial Fermentation Products for Anti-M. tuberculosis Activity

Simple Summary

M. tuberculosis (M.tb) is the main pathogen of tuberculosis (TB). The emergence of multidrug-resistant (MDR) and extensively drug-resistant (XDR) M.tb has brought new challenges to the treatment of TB. Therefore, finding new materials for the development of natural anti-TB drugs is crucial to the prevention and treatment of TB. In order to discover new anti-TB drug materials, we isolated microorganisms from the soil and tested the anti-M.tb activity of their fermentation products. The results showed that the four fermentation products had anti-M.tb activities in vitro and in intracellular bacteria. The qPCR results showed that the four fermentation products down-regulated some growth-essential gene expression of M.tb. Thus, we speculated that the fermentation product may exert its anti-M.tb effect by down-regulating the expression of the essential genes of M.tb.

Abstract

Tuberculosis (TB), caused by M. tuberculosis (M.tb), is the leading infectious cause of mortality worldwide. The emergence of drug-resistant M.tb has made the control of TB more difficult. In our study, we investigated the ability of microorganism fermentation products from the soil to inhibit M.tb. We successfully identified four fermentation products (Micromonospora chokoriensis, Micromonospora purpureochromogenes, Micromonospora profundi, Streptomyces flavofungini) that inhibited the growth of M.tb in vitro and in intracellular bacteria at 25 μg/mL MIC. Importantly, the fermentation products decreased some essential gene expression levels for M.tb growth. Our data provide the possibility that microbial fermentation products have potential development value for anti-M.tb drugs.

GLO1 Contributes to the Drug Resistance of Escherichia coli Through Inducing PER Type of Extended-Spectrum β-Lactamases

Background

Escherichia coli-associated antimicrobial resistance (AMR) issue so far needs urgent considerations. This study aims to screen the potent genes associated with extended-spectrum β-lactamases (ESBLs) in drug-resistant Escherichia coli and elucidate the specific drug-resistant mechanism.

Methods

Clinical ESBLs-EC samples were obtained based on the microbial identification, and the whole genome was sequenced. In combination with the significantly enriched pathways, several differently expressed genes were screened and verified by RT-PCR. Furthermore, through knocking out glyoxalase 1 (GLO1) gene and transfecting overexpressed plasmids, the potential relationship between GLO1 and ESBLs was then investigated. Lastly, the concentrations of β-lactamases in bacteria and supernatant from different groups were examined by enzyme-linked immunosorbent assay (ELISA).

Results

After successful isolation and identification of ESBLs-EC, the whole genome and eighteen differential metabolic pathways were analyzed to select differently expressed genes, including add, deoD, guaD, speG, GLO1, VNN1, etc. RT-PCR results showed that there were no differences in these genes between the standard bacteria and susceptible Escherichia coli. Remarkably, the relative levels of four genes including speG, Hdac10, GLO1 and Ppcdc were significantly increased in ESBLs-EC in comparison with susceptible strains, whereas other gene expression was decreased. Further experiments utilizing gene knockout and overexpression strains confirmed the role of GLO1. At last, a total of 10 subtypes of β-lactamases were studied using ELISA, including BES-, CTX-M1-, CTX-M2-, OXA1-, OXA2-, OXA10-, PER-, SHV-, TEM-, and VEB-ESBLs, and results demonstrated that GLO1 gene expression only affected PER-β-lactamases but had no effects on other β-lactamases.

Conclusion

SpeG, Hdac10, GLO1 and Ppcdc might be associated with the drug-resistant mechanism of Escherichia coli. Of note, this study firstly addressed the role of GLO1 in the drug resistance of ESBLs-EC, and this effect may be mediated by increasing PER-β-lactamases.

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.

Using Omics to Study Leprosy, Tuberculosis, and Other Mycobacterial Diseases

Mycobacteria are members of the Actinomycetales order, and they are classified into one family, Mycobacteriaceae. More than 20 mycobacterial species cause disease in humans. The Mycobacterium group, called the Mycobacterium tuberculosis complex (MTBC), has nine closely related species that cause tuberculosis in animals and humans. TB can be detected worldwide and one-fourth of the world's population is contaminated with tuberculosis. According to the WHO, about two million dies from it, and more than nine million people are newly infected with TB each year. Mycobacterium tuberculosis (M. tuberculosis) is the most potential causative agent of tuberculosis and prompts enormous mortality and morbidity worldwide due to the incompletely understood pathogenesis of human tuberculosis. Moreover, modern diagnostic approaches for human tuberculosis are inefficient and have many lacks, while MTBC species can modulate host immune response and escape host immune attacks to sustain in the human body. "Multi-omics" strategies such as genomics, transcriptomics, proteomics, metabolomics, and deep sequencing technologies could be a comprehensive strategy to investigate the pathogenesis of mycobacterial species in humans and offer significant discovery to find out biomarkers at the early stage of disease in the host. Thus, in this review, we attempt to understand an overview of the mission of "omics" approaches in mycobacterial pathogenesis, including tuberculosis, leprosy, and other mycobacterial diseases.

Dissecting Host-Pathogen Interactions in TB Using Systems-Based Omic Approaches

Tuberculosis (TB) is a devastating infectious disease that kills over a million people every year. There is an increasing burden of multi drug resistance (MDR) and extensively drug resistance (XDR) TB. New and improved therapies are urgently needed to overcome the limitations of current treatment. The causative agent, Mycobacterium tuberculosis (Mtb) is one of the most successful pathogens that can manipulate host cell environment for adaptation, evading immune defences, virulence, and pathogenesis of TB infection. Host-pathogen interaction is important to establish infection and it involves a complex set of processes. Metabolic cross talk between the host and pathogen is a facet of TB infection and has been an important topic of research where there is growing interest in developing therapies and drugs that target these interactions and metabolism of the pathogen in the host. Mtb scavenges multiple nutrient sources from the host and has adapted its metabolism to survive in the intracellular niche. Advancements in systems-based omic technologies have been successful to unravel host-pathogen interactions in TB. In this review we discuss the application and usefulness of omics in TB research that provides promising interventions for developing anti-TB therapies.

Antibiotic resistance: Time of synthesis in a post-genomic age

Antibiotic resistance has been highlighted by international organizations, including World Health Organization, World Bank and United Nations, as one of the most relevant global health problems. Classical approaches to study this problem have focused in infected humans, mainly at hospitals. Nevertheless, antibiotic resistance can expand through different ecosystems and geographical allocations, hence constituting a One-Health, Global-Health problem, requiring specific integrative analytic tools. Antibiotic resistance evolution and transmission are multilayer, hierarchically organized processes with several elements (from genes to the whole microbiome) involved. However, their study has been traditionally gene-centric, each element independently studied. The development of robust-economically affordable whole genome sequencing approaches, as well as other -omic techniques as transcriptomics and proteomics, is changing this panorama. These technologies allow the description of a system, either a cell or a microbiome as a whole, overcoming the problems associated with gene-centric approaches. We are currently at the time of combining the information derived from -omic studies to have a more holistic view of the evolution and spread of antibiotic resistance. This synthesis process requires the accurate integration of -omic information into computational models that serve to analyse the causes and the consequences of acquiring AR, fed by curated databases capable of identifying the elements involved in the acquisition of resistance. In this review, we analyse the capacities and drawbacks of the tools that are currently in use for the global analysis of AR, aiming to identify the more useful targets for effective corrective interventions.