System-level strategies for studying the metabolism of Mycobacterium tuberculosis

Sweet spheres: succession and CAZyme expression of marine bacterial communities colonizing a mix of alginate and pectin particles

Polysaccharide particles are important substrates and microhabitats for marine bacteria. However, substrate-specific bacterial dynamics in mixtures of particle types with different polysaccharide composition, as likely occurring in natural habitats, are undescribed. Here, we studied the composition, functional diversity and gene expression of marine bacterial communities colonizing a mix of alginate and pectin particles. Amplicon, metagenome and metatranscriptome sequencing revealed that communities on alginate and pectin particles significantly differed from their free-living counterparts. Unexpectedly, microbial dynamics on alginate and pectin particles were similar, with predominance of amplicon sequence variants (ASVs) from Tenacibaculum, Colwellia, Psychrobium and Psychromonas. Corresponding metagenome-assembled genomes (MAGs) expressed diverse alginate lyases, several colocalized in polysaccharide utilization loci. Only a single, low-abundant MAG showed elevated transcript abundances of pectin-degrading enzymes. One specific Glaciecola ASV dominated the free-living fraction, possibly persisting on particle-derived oligomers through different glycoside hydrolases. Elevated ammonium uptake and metabolism signified nitrogen as an important factor for degrading carbon-rich particles, whereas elevated methylcitrate and glyoxylate cycles suggested nutrient limitation in surrounding waters. The bacterial preference for alginate, whereas pectin primarily served as colonization scaffold, illuminates substrate-driven dynamics within mixed polysaccharide pools. These insights expand our understanding of bacterial niche specialization and the biological carbon pump in macroalgae-rich habitats.

Metabolic fluxes for nutritional flexibility of Mycobacterium tuberculosis

The co-catabolism of multiple host-derived carbon substrates is required by Mycobacterium tuberculosis (Mtb) to successfully sustain a tuberculosis infection. However, the metabolic plasticity of this pathogen and the complexity of the metabolic networks present a major obstacle in identifying those nodes most amenable to therapeutic interventions. It is therefore critical that we define the metabolic phenotypes of Mtb in different conditions. We applied metabolic flux analysis using stable isotopes and lipid fingerprinting to investigate the metabolic network of Mtb growing slowly in our steady-state chemostat system. We demonstrate that Mtb efficiently co-metabolises either cholesterol or glycerol, in combination with two-carbon generating substrates without any compartmentalisation of metabolism. We discovered that partitioning of flux between the TCA cycle and the glyoxylate shunt combined with a reversible methyl citrate cycle is the critical metabolic nodes which underlie the nutritional flexibility of Mtb. These findings provide novel insights into the metabolic architecture that affords adaptability of bacteria to divergent carbon substrates and expand our fundamental knowledge about the methyl citrate cycle and the glyoxylate shunt.

Metabolic profiling of dormant Mycolicibacterium smegmatis cells' reactivation reveals a gradual assembly of metabolic processes

INTRODUCTION

Under gradual acidification of the culture medium mycobacterial cells transit into a specific state characterized by low level of metabolic activity and morphological alterations. This state of non-replicative persistence (dormancy) is directly linked to physiological drug resistance, which complicates the efforts to eradicate the latent forms of TB. In order to find new anti-latent TB compounds, the metabolic processes which may occur in the state of dormancy and during the transition into the active state (reactivation) should be characterized.

OBJECTIVES

In the current study we analyzed the untargeted metabolomic profiles of dormant and reactivating Mycolicibacterium smegmatis cells (a model microorganism, bearing many common physiological traits of MTB), on the global scale level, since the characterization and analysis of the metabolites' dynamics would provide a comprehensive overview on global biochemical responses of the bacteria to stress conditions.

METHODS

The reactivation process was tracked by measuring the value of membrane potential, applying a ratio-metric approach, by the method of flow-cytometry. The crucial timepoints were selected and the bacteria were sampled to LC-MS metabolic profiling.

RESULTS

Reactivation of these cells after 60 days of storage revealed that this process proceeds in two stages: (I) a period, which lasts for 10 h and is characterized by a constant CFU number, unchangeable cell size, a minuscule increase of respiratory activity and a noticeable increase in membrane potential value, indicating the onset of the first metabolic processes during this time interval; the second phase (10-26 h) is characterized by acceleration of endogenous respiration, changes in the size of the cells and it finishes with the beginning of cells division. Analysis of the changes in the relative abundances of KEGG-annotated metabolites revealed that a significant number of metabolites, such as stearic acid, glycerol, D-glucose, trehalose-6-phosphate decrease their concentrations over the reactivation time, whereas in contrast, such metabolites as dodecanoic acid, mycobactin S, and other compounds of PG/AG biosynthesis are synthesized during reactivation. Differential analysis of metabolic profiles disclosed the activation of a number of metabolic pathways at the early reactivation stage: biosynthesis of secondary metabolites, purine and pyrimidine metabolism, glycerophospholipid and fatty acids metabolism etc. CONCLUSION: The data obtained indicate, despite the long-term storage of dormant cells in a state of minimal metabolic activity, according to metabolic profiling, they still retained a large number of metabolites. In the process of reactivation, the incremental stochastic assembly of the complete metabolic pathways occurs.

Biphasic cellular adaptations and ecological implications of Alteromonas macleodii degrading a mixture of algal polysaccharides

Algal polysaccharides are an important bacterial nutrient source and central component of marine food webs. However, cellular and ecological aspects concerning the bacterial degradation of polysaccharide mixtures, as presumably abundant in natural habitats, are poorly understood. Here, we contextualize marine polysaccharide mixtures and their bacterial utilization in several ways using the model bacterium Alteromonas macleodii 83-1, which can degrade multiple algal polysaccharides and contributes to polysaccharide degradation in the oceans. Transcriptomic, proteomic and exometabolomic profiling revealed cellular adaptations of A. macleodii 83-1 when degrading a mix of laminarin, alginate and pectin. Strain 83-1 exhibited substrate prioritization driven by catabolite repression, with initial laminarin utilization followed by simultaneous alginate/pectin utilization. This biphasic phenotype coincided with pronounced shifts in gene expression, protein abundance and metabolite secretion, mainly involving CAZymes/polysaccharide utilization loci but also other functional traits. Distinct temporal changes in exometabolome composition, including the alginate/pectin-specific secretion of pyrroloquinoline quinone, suggest that substrate-dependent adaptations influence chemical interactions within the community. The ecological relevance of cellular adaptations was underlined by molecular evidence that common marine macroalgae, in particular Saccharina and Fucus, release mixtures of alginate and pectin-like rhamnogalacturonan. Moreover, CAZyme microdiversity and the genomic predisposition towards polysaccharide mixtures among Alteromonas spp. suggest polysaccharide-related traits as an ecophysiological factor, potentially relating to distinct 'carbohydrate utilization types' with different ecological strategies. Considering the substantial primary productivity of algae on global scales, these insights contribute to the understanding of bacteria-algae interactions and the remineralization of chemically diverse polysaccharide pools, a key step in marine carbon cycling.

Emerging drugs and drug targets against tuberculosis

Mycobacterium tuberculosis (M. tuberculosis), the causative agent of tuberculosis, uses various tactics to resist on antibiotics and evade host immunity. To control tuberculosis, antibiotics with novel mechanisms of action are urgently needed. Emerging new antibiotics and underlying novel drug targets are summarized in this paper.

Overcoming drug resistance through in silico prediction

Prediction tools are commonly used in pre-clinical research to assist target selection, to optimize drug potency or to predict the pharmacological profile of drug candidates. In silico prediction and overcoming drug resistance is a new opportunity that creates a high interest in pharmaceutical research. This review presents two main in silico strategies to meet this challenge: a structure-based approach to study the influence of mutations on the drug-target interaction and a system-biology approach to identify resistance pathways for a given drug. In silico screening of synergies between therapeutic and resistant pathways through biological network analysis is an example of technique to escape drug resistance. Structure-based drug design and in silico system biology are complementary approaches to reach few objectives at once: increase efficiency, reduce toxicity and overcoming drug resistance.

Mycobacterium tuberculosis metabolism

Metabolism underpins the physiology and pathogenesis of Mycobacterium tuberculosis. However, although experimental mycobacteriology has provided key insights into the metabolic pathways that are essential for survival and pathogenesis, determining the metabolic status of bacilli during different stages of infection and in different cellular compartments remains challenging. Recent advances-in particular, the development of systems biology tools such as metabolomics-have enabled key insights into the biochemical state of M. tuberculosis in experimental models of infection. In addition, their use to elucidate mechanisms of action of new and existing antituberculosis drugs is critical for the development of improved interventions to counter tuberculosis. This review provides a broad summary of mycobacterial metabolism, highlighting the adaptation of M. tuberculosis as specialist human pathogen, and discusses recent insights into the strategies used by the host and infecting bacillus to influence the outcomes of the host-pathogen interaction through modulation of metabolic functions.

Drug resistance to Mycobacterium tuberculosis: from the traditional Chinese view to modern systems biology

The pathogen, Mycobacterium tuberculosis (M. tuberculosis) is a well-evolved, organized pathogen that has developed drug resistance, specifically multidrug resistance (MDR) and extensive drug resistance (XDR). This review primarily summarizes the mechanisms of drug resistance by M. tuberculosis according to the traditional Chinese view. The traditional Chinese view of drug resistance includes: the physical barrier of the cell wall; mutations relating to current anti-TB agents; drug efflux pumps; and drug stress, including the SOS response systems, the mismatch repair systems and the toxin-antitoxin systems. In addition, this review addresses the integrated systems biology of genomics, transcriptomics, proteomics, metabolomics and interactomics. Development of the various levels of systems biology has enabled determination of the anatomy of bacteria. Finally, the current review proposes that further investigation regarding the population of individuals with a high drug metabolic speed is vital to further understand drug resistance in M. tuberculosis.

Sample preparation of Mycobacterium tuberculosis extracts for nuclear magnetic resonance metabolomic studies

Mycobacterium tuberculosis is a major cause of mortality in human beings on a global scale. The emergence of both multi- (MDR) and extensively-(XDR) drug-resistant strains threatens to derail current disease control efforts. Thus, there is an urgent need to develop drugs and vaccines that are more effective than those currently available. The genome of M. tuberculosis has been known for more than 10 years, yet there are important gaps in our knowledge of gene function and essentiality. Many studies have since used gene expression analysis at both the transcriptomic and proteomic levels to determine the effects of drugs, oxidants, and growth conditions on the global patterns of gene expression. Ultimately, the final response of these changes is reflected in the metabolic composition of the bacterium including a few thousand small molecular weight chemicals. Comparing the metabolic profiles of wild type and mutant strains, either untreated or treated with a particular drug, can effectively allow target identification and may lead to the development of novel inhibitors with anti-tubercular activity. Likewise, the effects of two or more conditions on the metabolome can also be assessed. Nuclear magnetic resonance (NMR) is a powerful technology that is used to identify and quantify metabolic intermediates. In this protocol, procedures for the preparation of M. tuberculosis cell extracts for NMR metabolomic analysis are described. Cell cultures are grown under appropriate conditions and required Biosafety Level 3 containment, harvested, and subjected to mechanical lysis while maintaining cold temperatures to maximize preservation of metabolites. Cell lysates are recovered, filtered sterilized, and stored at ultra-low temperatures. Aliquots from these cell extracts are plated on Middlebrook 7H9 agar for colony-forming units to verify absence of viable cells. Upon two months of incubation at 37 °C, if no viable colonies are observed, samples are removed from the containment facility for downstream processing. Extracts are lyophilized, resuspended in deuterated buffer and injected in the NMR instrument, capturing spectroscopic data that is then subjected to statistical analysis. The procedures described can be applied for both one-dimensional (1D) H NMR and two-dimensional (2D) H-(13)C NMR analyses. This methodology provides more reliable small molecular weight metabolite identification and more reliable and sensitive quantitative analyses of cell extract metabolic compositions than chromatographic methods. Variations of the procedure described following the cell lysis step can also be adapted for parallel proteomic analysis.