Raphael B. M. Aggio

Analytical platform for metabolome analysis of microbial cells using methyl chloroformate derivatization followed by gas chromatography–mass spectrometry

This protocol describes an analytical platform for the analysis of intra- and extracellular metabolites of microbial cells (yeast, filamentous fungi and bacteria) using gas chromatography–mass spectrometry (GC-MS). The protocol is subdivided into sampling, sample preparation, chemical derivatization of metabolites, GC-MS analysis and data processing and analysis. This protocol uses two robust quenching methods for microbial cultures, the first of which, cold glycerol-saline quenching, causes reduced leakage of intracellular metabolites, thus allowing a more reliable separation of intra- and extracellular metabolites with simultaneous stopping of cell metabolism. The second, fast filtration, is specifically designed for quenching filamentous micro-organisms. These sampling techniques are combined with an easy sample-preparation procedure and a fast chemical derivatization reaction using methyl chloroformate. This reaction takes place at room temperature, in aqueous medium, and is less prone to matrix effect compared with other derivatizations. This protocol takes an average of 10 d to complete and enables the simultaneous analysis of hundreds of metabolites from the central carbon metabolism (amino and nonamino organic acids, phosphorylated organic acids and fatty acid intermediates) using an in-house MS library and a data analysis pipeline consisting of two free software programs (Automated Mass Deconvolution and Identification System (AMDIS) and R).

Metab: an R package for high-throughput analysis of metabolomics data generated by GC-MS

MOTIVATION The Automated Mass Spectral Deconvolution and Identification System (AMDIS) is freeware extensively applied in metabolomics. However, datasets processed by AMDIS require extensive data correction, filtering and reshaping to create reliable datasets for further downstream analysis. Performed manually, these processes are laborious and extremely time consuming. Furthermore, manual corrections increase the chance of human error and can introduce additional technical variability to the data. Thus, an automated pipeline for curating GC-MS data is urgently needed. RESULTS We present the Metab R package designed to automate the pipeline for analysis of metabolomics GC-MS datasets processed by AMDIS. AVAILABILITY The Metab package, the AMDIS library and the reference ion library are available at www.metabolomics.auckland.ac.nz/index.php/downloads. CONTACT k.ruggiero@auckland.ac.nz.

Toxin-antitoxin systems of Mycobacterium smegmatis are essential for cell survival.

Background: Mycobacteria harbor a vast array of toxin-antitoxin modules, but their roles remain largely unknown. Results: Deletion of all TA modules in Mycobacterium smegmatis caused a survival defect and alterations in amino acid metabolism. Conclusion: We demonstrate an essential role for TA modules in mycobacterial metabolism and survival. Significance: These results may explain the basis for 88 TA modules in M. tuberculosis where metabolism must be tightly controlled. The role of chromosomal toxin-antitoxin (TA) modules in bacterial physiology remains enigmatic despite their abundance in the genomes of many bacteria. Mycobacterium smegmatis contains three putative TA systems, VapBC, MazEF, and Phd/Doc, and previous work from our group has shown VapBC to be a bona fide TA system. In this study, we show that MazEF and Phd/Doc are also TA systems that are constitutively expressed, transcribed as leaderless transcripts, and subject to autoregulation, and expression of the toxin component leads to growth inhibition that can be rescued by the cognate antitoxin. No phenotype was identified for deletions of the individual TA systems, but a triple deletion strain (ΔvapBC, mazEF, phd/doc), designated ΔTAtriple, exhibited a survival defect in complex growth medium demonstrating an essential role for these TA modules in mycobacterial survival. Transcriptomic analysis revealed no significant differences in gene expression between wild type and the ΔTAtriple mutant under these conditions suggesting that the growth defect was not at a transcriptional level. Metabolomic analysis demonstrated that in response to starvation in complex medium, both the wild type and ΔTAtriple mutant consumed a wide range of amino acids from the external milieu. Analysis of intracellular metabolites revealed a significant difference in the levels of branched-chain amino acids between the wild type and ΔTAtriple mutant, which are proposed to play essential roles in monitoring the nutritional supply and physiological state of the cell and linking catabolic with anabolic reactions. Disruption of this balance in the ΔTAtriple mutant may explain the survival defect in complex growth medium.

Transcriptional and metabolomic consequences of luxS inactivation reveal a metabolic rather than quorum sensing role for LuxS in Lactobacillus reuteri 100-23

Autoinducer-2 (AI-2)-mediated quorum sensing has been extensively studied in relation to the regulation of microbial behavior. There are, however, two potential roles for the AI-2 synthase (LuxS). The first is in the production of AI-2 and the second is as an enzyme in the activated methyl cycle, where it catalyzes the conversion of S-ribosylhomocysteine to homocysteine. The by-product of the reaction catalyzed by LuxS is (S)-4,5-dihydroxy-2,3-pentanedione, which spontaneously forms the furanones known collectively as AI-2. The mammalian gut contains a complex collection of bacterial species so a method of interspecies communication might influence community structure and function. Lactobacillus reuteri 100-23 is an autochthonous inhabitant of the rodent forestomach, where it adheres to the nonsecretory epithelium, forming a biofilm. Microarray comparisons of gene expression profiles of the L. reuteri 100-23 wild type and a luxS mutant under different culture conditions revealed altered transcription of genes encoding proteins associated with cysteine biosynthesis/oxidative stress response, urease activity, and sortase-dependent proteins. Metabolomic analysis showed that the luxS mutation affected cellular levels of fermentation products, fatty acids and amino acids. Cell density-dependent changes (log phase versus stationary phase growth) in gene transcription were not detected, indicating that AI-2 was unlikely to be involved in gene regulation mediated by quorum sensing in L. reuteri 100-23.

Sonic vibration affects the metabolism of yeast cells growing in liquid culture: a metabolomic study

It is undeniable that music and sounds can affect our emotions and mood, but so far the study of physical stimuli provoked by sound on living organisms has been mostly focused on brain and sensorimotor structures rather than cellular metabolism. Using metabolomics, we compared the physiology of yeast cells growing in defined liquid medium exposed to music, high and low frequency sonic vibration and silence. All sonic stimuli tested not only increased the growth rate of the yeast cells by 12% but they also reduced biomass production by 14%. The intra- and extracellular metabolite profiles differed significantly depending on the sonic stimulus applied showing that different metabolic pathways are affected differently by different sound frequency. Therefore, our results clearly demonstrate that sound does affect microbial cell metabolism when growing in liquid culture, opening an entirely new perspective for scientific investigation interfacing acoustics, biophysics and biochemistry.

Analysis of Intracellular Metabolites from Microorganisms: Quenching and Extraction Protocols

Sample preparation is one of the most important steps in metabolome analysis. The challenges of determining microbial metabolome have been well discussed within the research community and many improvements have already been achieved in last decade. The analysis of intracellular metabolites is particularly challenging. Environmental perturbations may considerably affect microbial metabolism, which results in intracellular metabolites being rapidly degraded or metabolized by enzymatic reactions. Therefore, quenching or the complete stop of cell metabolism is a pre-requisite for accurate intracellular metabolite analysis. After quenching, metabolites need to be extracted from the intracellular compartment. The choice of the most suitable metabolite extraction method/s is another crucial step. The literature indicates that specific classes of metabolites are better extracted by different extraction protocols. In this review, we discuss the technical aspects and advancements of quenching and extraction of intracellular metabolite analysis from microbial cells.