Phenotypic characterization of transposon-inserted mutants of Clostridium proteoclasticum B316T using extracellular metabolomics

Sample Preparation in Microbial Metabolomics: Advances and Challenges

Microbial metabolomics has gained significant interest as it reflects the physiological state of microorganisms. Due to the great variability of biological organisms, in terms of physicochemical characteristics and variable range of concentration of metabolites, the choice of sample preparation methods is a crucial step in the metabolomics workflow and will reflect on the quality and reliability of the results generated. The procedures applied to the preparation of microbial samples will vary according to the type of microorganism studied, the metabolomics approach (untargeted or targeted), and the analytical platform of choice. This chapter aims to provide an overview of the sample preparation workflow for microbial metabolomics, highlighting the pre-analytical factors associated with cultivation, harvesting, metabolic quenching, and extraction. Discussions focus on obtaining intracellular and extracellular metabolites. Finally, we introduced advanced sample preparation methods based on automated systems.

Comprehensive analysis of metabolic alterations in Schizochytrium sp. strains with different DHA content

Along with the daily growth of the market requirements for docosahexaenoic acid (DHA) algae oil, a large DHA ingredients are needed to ensure worldwide supply. Undoubtedly a high-productive strain would be the prerequisite for high quality and yield. A comprehensive understanding of the processes of DHA synthesis from glycolysis to the lipid accumulation would be benefit to achieve the final optimization of DHA production. In this study, we comprehensively characterized the metabolic profiles of a Schizochytrium sp. strain, which has higher DHA content and different biomass amino acid composition compared with the wild type to explore the affected pathways and underlying mechanism. Combined with the multivariate statistical analysis, twenty-two differential metabolites were screened as relevant to the discrepancy between two strains. The results showed relatively downregulated glycolysis and saturated fatty acids (SFA) synthesis, and upregulated TCA cycle, amino acids and polyunsaturated fatty acids (PUFA) synthesis in DHA high yield strain. The current study provide a terminal picture of gene regulation from downstream metabolism and demonstrate the advantage of metabolomics in characterizing metabolic status which in turn could provide effective information for the metabolic engineering.

A metabolomic study of the effect of Candida albicans glutamate dehydrogenase deletion on growth and morphogenesis

There are two glutamate dehydrogenases in the pathogenic fungus Candida albicans. One is an NAD⁺-dependent glutamate dehydrogenase (GDH2) and the other is an NADPH-dependent glutamate dehydrogenase (GDH3). These two enzymes are part of the nitrogen and nicotinate/nicotinamide metabolic pathways, which have been identified in our previous studies as potentially playing an important role in C. albicans morphogenesis. In this study, we created single gene knockout mutants of both dehydrogenases in order to investigate whether or not they affect the morphogenesis of C. albicans. The GDH genes were deleted and the phenotypes of the knockout mutants were studied by growth characterisation, metabolomics, isotope labelling experiments, and by quantifying cofactors under various hyphae-inducing conditions. We found that the gdh2/gdh2 mutant was unable to grow on either arginine or proline as a sole carbon and nitrogen source. While the gdh3/gdh3 mutant could grow on these carbon and nitrogen sources, the strain was locked in the yeast morphology in proline-containing medium. We detected different concentrations of ATP, NAD⁺, NADH, NAPD⁺, NADPH, as well as 62 other metabolites, and 19 isotopically labelled metabolites between the mutant and the wild-type strains. These differences were associated with 44 known metabolic pathways. It appears that the disequilibrium of cofactors in the gdh3/gdh3 mutant leads to characteristic proline degradation in the central carbon metabolism. The analysis of the gdh2/gdh2 and the gdh3/gdh3 mutants confirmed our hypothesis that redox potential and nitrogen metabolism are related to filament formation and identified these metabolic pathways as potential drug targets to inhibit morphogenesis.

Metabolite secretion in microorganisms: the theory of metabolic overflow put to the test

INTRODUCTION

Microbial cells secrete many metabolites during growth, including important intermediates of the central carbon metabolism. This has not been taken into account by researchers when modeling microbial metabolism for metabolic engineering and systems biology studies.

MATERIALS AND METHODS

The uptake of metabolites by microorganisms is well studied, but our knowledge of how and why they secrete different intracellular compounds is poor. The secretion of metabolites by microbial cells has traditionally been regarded as a consequence of intracellular metabolic overflow.

CONCLUSIONS

Here, we provide evidence based on time-series metabolomics data that microbial cells eliminate some metabolites in response to environmental cues, independent of metabolic overflow. Moreover, we review the different mechanisms of metabolite secretion and explore how this knowledge can benefit metabolic modeling and engineering.

Extracellular Microbial Metabolomics: The State of the Art

Microorganisms produce and secrete many primary and secondary metabolites to the surrounding environment during their growth. Therefore, extracellular metabolites provide important information about the changes in microbial metabolism due to different environmental cues. The determination of these metabolites is also comparatively easier than the extraction and analysis of intracellular metabolites as there is no need for cell rupture. Many analytical methods are already available and have been used for the analysis of extracellular metabolites from microorganisms over the last two decades. Here, we review the applications and benefits of extracellular metabolite analysis. We also discuss different sample preparation protocols available in the literature for both types (e.g., metabolites in solution and in gas) of extracellular microbial metabolites. Lastly, we evaluate the authenticity of using extracellular metabolomics data in the metabolic modelling of different industrially important microorganisms.

Mutation-based selection and analysis of Komagataeibacter hansenii HDM1-3 for improvement in bacterial cellulose production

AIMS

A low yield of bacterial cellulose (BC) always results from an excessive accumulation of organic acids. Screening and the selection of bacterial mutants with a low accumulation of organic acids is an efficient approach for improving BC production.

METHODS AND RESULTS

In combination with the proton suicide method (medium containing NaBr-NaBrO₃ ), diethyl sulphate chemical mutagenesis coupled with ⁶⁰ Co-γ irradiation treatment were performed for the screening and selection of desired mutant lines with a high yield of BC. Two high-yield strains, Br-3 and Co-5, as well as a low-yield strain, Br-12, were obtained. Amplified fragment length polymorphism (AFLP) was applied to explore the differences between the mutant lines and the wild type. For the Br-12 line, three specific fragments were verified, corresponding to TonB-dependent transport (TBDT), exopolysaccharides output protein (PePr) and an unknown gene. For Co-5, two specific fragments were matched, acsD and UDP-galactose-4-epimerase. In addition, metabolic analysis for the mutant lines indicated that BC production may be limited by excessive accumulation of organic acids in the fermentation. The limitation would be resolved by the cross-talk of genes involved in BC biosynthesis.

CONCLUSIONS

Reduced organic acid by-products from glucose in bypasses were found to be responsible for the high-yield BC synthesis in Komagataeibacter hansenii mutant strains.

SIGNIFICANCE AND IMPACT OF THE STUDY

The metabolic process was varied by mutagenesis-induced gene disruption of the metabolic products. A new idea was provided for the targeted screening and characterization of mutants in the future.

Behavior and target site selection of conjugative transposon Tn916 in two different strains of toxigenic Clostridium difficile

The insertion sites of the conjugative transposon Tn916 in the anaerobic pathogen Clostridium difficile were determined using Illumina Solexa high-throughput DNA sequencing of Tn916 insertion libraries in two different clinical isolates: 630ΔE, an erythromycin-sensitive derivative of 630 (ribotype 012), and the ribotype 027 isolate R20291, which was responsible for a severe outbreak of C. difficile disease. A consensus 15-bp Tn916 insertion sequence was identified which was similar in both strains, although an extended consensus sequence was observed in R20291. A search of the C. difficile 630 genome showed that the Tn916 insertion motif was present 100,987 times, with approximately 63,000 of these motifs located in genes and 35,000 in intergenic regions. To test the usefulness of Tn916 as a mutagen, a functional screen allowed the isolation of a mutant. This mutant contained Tn916 inserted into a gene involved in flagellar biosynthesis.

Transposition of Tn916 in the four replicons of the Butyrivibrio proteoclasticus B316(T) genome

The rumen bacterium Butyrivibrio proteoclasticus B316(T) has a 4.4-Mb genome composed of four replicons (approximately 3.55 Mb, 361, 302 and 186 kb). Mutagenesis of B316(T) was performed with the broad host-range conjugative transposon Tn916 to screen for functionally important characteristics. The insertion sites of 123 mutants containing a single copy of Tn916 were identified and corresponded to 53 different insertion points, of which 18 (34.0%), representing 39 mutants (31.7%), were in ORFs and 12 were where transposition occurred in both directions (top and bottom DNA strand). Up to eight mutants from several independent conjugation experiments were found to have the same integration site. Although transposition occurred in all four replicons, the number of specific insertion sites, transposition frequency and the average intertransposon distance between insertions varied between the four replicons. In silico analysis of the 53 insertion sites was used to model a target consensus sequence for Tn916 integration into B316(T) . A search of the B316(T) genome using the modelled target consensus sequence (up to two mismatches) identified 39 theoretical Tn916 insertion sites (19 coding, 20 noncoding), of which nine corresponded to Tn916 insertions identified in B316(T) mutants during our conjugation experiments.

Pathway Activity Profiling (PAPi): from the metabolite profile to the metabolic pathway activity

MOTIVATION

Metabolomics is one of the most recent omics-technologies and uses robust analytical techniques to screen low molecular mass metabolites in biological samples. It has evolved very quickly during the last decade. However, metabolomics datasets are considered highly complex when used to relate metabolite levels to metabolic pathway activity. Despite recent developments in bioinformatics, which have improved the quality of metabolomics data, there is still no straightforward method capable of correlating metabolite level to the activity of different metabolic pathways operating within the cells. Thus, this kind of analysis still depends on extremely laborious and time-consuming processes.

RESULTS

Here, we present a new algorithm Pathway Activity Profiling (PAPi) with which we are able to compare metabolic pathway activities from metabolite profiles. The applicability and potential of PAPi was demonstrated using a previously published data from the yeast Saccharomyces cerevisiae. PAPi was able to support the biological interpretations of the previously published observations and, in addition, generated new hypotheses in a straightforward manner. However, PAPi is time consuming to perform manually. Thus, we also present here a new R-software package (PAPi) which implements the PAPi algorithm and facilitates its usage to quickly compare metabolic pathways activities between different experimental conditions. Using the identified metabolites and their respective abundances as input, the PAPi package calculates pathways' Activity Scores, which represents the potential metabolic pathways activities and allows their comparison between conditions. PAPi also performs principal components analysis and analysis of variance or t-test to investigate differences in activity level between experimental conditions. In addition, PAPi generates comparative graphs highlighting up- and down-regulated pathway activity.

AVAILABILITY

These datasets are available in http://www.4shared.com/file/hTWyndYU/extra.html and http://www.4shared.com/file/VbQIIDeu/intra.html. PAPi package is available in: http://www.4shared.com/file/s0uIYWIg/PAPi_10.html

CONTACT

s.villas-boas@auckland.ac.nz

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

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).

Metabolic profiling strategy of Caenorhabditis elegans by whole-organism nuclear magnetic resonance

In this study, we present a methodology for metabotyping of C. elegans using 1H high resolution magic angle spinning (HRMAS) whole-organism nuclear magnetic resonance (NMR). We demonstrate and characterize the robustness of our metabolic phenotyping method, discriminating wild-type N2 from mutant sod-1(tm776) animals, with the latter being an otherwise silent mutation, and we identify and quantify several confounding effects to establish guidelines to ensure optimal quality of the raw data across time and space. We monitor the sample stability under experimental conditions and examine variations arising from effects that can potentially confuse the biological interpretation or prevent the automation of the protocol, including sample culture (breeding of the worms by two biologists), sample preparation (freezing), NMR acquisition (acquisition by different spectroscopists, acquisition in different facilities), and the effect of the age of the animals. When working with intact model organisms, some of these exogenous effects are shown to be significant and therefore require control through experimental design and sample randomization.