Sample preparation procedures utilized in microbial metabolomics: An overview

Physical Laboratory Automation in Synthetic Biology

Synthetic Biology has overcome many of the early challenges facing the field and is entering a systems era characterized by adoption of Design-Build-Test-Learn (DBTL) approaches. The need for automation and standardization to enable reproducible, scalable, and translatable research has become increasingly accepted in recent years, and many of the hardware and software tools needed to address these challenges are now in place or under development. However, the lack of connectivity between DBTL modules and barriers to access and adoption remain significant challenges to realizing the full potential of lab automation. In this review, we characterize and classify the state of automation in synthetic biology with a focus on the physical automation of experimental workflows. Though fully autonomous scientific discovery is likely a long way off, impressive progress has been made toward automating critical elements of experimentation by combining intelligent hardware and software tools. It is worth questioning whether total automation that removes humans entirely from the loop should be the ultimate goal, and considerations for appropriate automation versus total automation are discussed in this light while emphasizing areas where further development is needed in both contexts.

Water-Soluble Pd6L3 Molecular Bowl for Separation of Phenanthrene from a Mixture of Isomeric Aromatic Hydrocarbons

Phenanthrene is a high-value raw material in chemical industries. Separation of phenanthrene from isomeric anthracene continues to be a big challenge in the industry due to their very similar physical properties. Herein, we report the self-assembly of a water-soluble molecular bowl (TB) from a phenothiazine-based unsymmetrical terapyridyl ligand (L) and a cis-blocked 90° Pd(II) acceptor. TB featured an unusual bowl-like topology, with a wide rim diameter and a hydrophobic inner cavity fenced by the aromatic rings of the ligand. The above-mentioned features of TB allow it to bind polyaromatic hydrocarbons in its confined cavity. TB shows a higher affinity for phenanthrene over its isomer anthracene in water, which enables it to separate phenanthrene with ∼93% purity from an equimolar mixture of phenanthrene and anthracene. TB is also able to extract pyrene with around ∼90% purity from an equimolar mixture of coronene, perylene, and pyrene. Moreover, TB can be reused for several cycles without significant degradation in its performance as an extracting agent. This clean strategy of separation of phenanthrene and pyrene from a mixture of hydrophobic hydrocarbons by aqueous extraction is noteworthy.

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.

A model for microbial interactions and metabolomic alterations in Candida glabrata-Staphylococcus epidermidis dual-species biofilms

The fungus Candida glabrata and the bacterium Staphylococcus epidermidis are important biofilm-forming microorganisms responsible of nosocomial infections in patients. In addition to causing single-species disease, these microorganisms are also involved in polymicrobial infections leading to an increased antimicrobial resistance. To expand knowledge about polymicrobial biofilms, in this study we investigate the formation of single- and dual-species biofilms of these two opportunistic pathogens employing several complementary approaches. First, biofilm biomass, biofilm metabolic activity and the microbial composition in single- and dual-species biofilms were assessed and compared. Then, the expression of three genes of C. glabrata and three genes of S. epidermidis positively related to the process of biofilm formation was evaluated. Although S. epidermidis is a stronger biofilm producer than C. glabrata, both biological and genetic data indicate that S. epidermidis growth is inhibited by C. glabrata which dominates the dual-species biofilms. To better understand the mechanisms of the interactions between the two microorganisms, a broad GC-MS metabolomic dataset of extracellular metabolites for planktonic, single- and dual-species biofilm cultures of C. glabrata and S. epidermidis was collected. As demonstrated by Partial Least Squares Discriminant Analysis (PLS-DA) of GC-MS metabolomic data, planktonic cultures, single- and dual-species biofilms can be sharply differentiated from each other by the nature and levels of an assortment of primary and secondary metabolites secreted in the culture medium. However, according to our data, 2-phenylethanol (secreted by C. glabrata) and the synergistically combined antifungal activity of 3-phenyllactic acid and of the cyclic dipeptide cyclo-(l-Pro-l-Trp) (secreted by S. epidermidis) play a major role in the race of the two microorganisms for predominance and survival.

Metabolomics and modelling approaches for systems metabolic engineering

Metabolic engineering involves the manipulation of microbes to produce desirable compounds through genetic engineering or synthetic biology approaches. Metabolomics involves the quantitation of intracellular and extracellular metabolites, where mass spectrometry and nuclear magnetic resonance based analytical instrumentation are often used. Here, the experimental designs, sample preparations, metabolite quenching and extraction are essential to the quantitative metabolomics workflow. The resultant metabolomics data can then be used with computational modelling approaches, such as kinetic and constraint-based modelling, to better understand underlying mechanisms and bottlenecks in the synthesis of desired compounds, thereby accelerating research through systems metabolic engineering. Constraint-based models, such as genome scale models, have been used successfully to enhance the yield of desired compounds from engineered microbes, however, unlike kinetic or dynamic models, constraint-based models do not incorporate regulatory effects. Nevertheless, the lack of time-series metabolomic data generation has hindered the usefulness of dynamic models till today. In this review, we show that improvements in automation, dynamic real-time analysis and high throughput workflows can drive the generation of more quality data for dynamic models through time-series metabolomics data generation. Spatial metabolomics also has the potential to be used as a complementary approach to conventional metabolomics, as it provides information on the localization of metabolites. However, more effort must be undertaken to identify metabolites from spatial metabolomics data derived through imaging mass spectrometry, where machine learning approaches could prove useful. On the other hand, single-cell metabolomics has also seen rapid growth, where understanding cell-cell heterogeneity can provide more insights into efficient metabolic engineering of microbes. Moving forward, with potential improvements in automation, dynamic real-time analysis, high throughput workflows, and spatial metabolomics, more data can be produced and studied using machine learning algorithms, in conjunction with dynamic models, to generate qualitative and quantitative predictions to advance metabolic engineering efforts.

Metabolomics for exposure assessment and toxicity effects of occupational pollutants: current status and future perspectives

INTRODUCTION

Work-related exposures to harmful agents or factors are associated with an increase in incidence of occupational diseases. These exposures often represent a complex mixture of different stressors, challenging the ability to delineate the mechanisms and risk factors underlying exposure-disease relationships. The use of omics measurement approaches that enable characterization of biological marker patterns provide internal indicators of molecular alterations, which could be used to identify bioeffects following exposure to a toxicant. Metabolomics is the comprehensive analysis of small molecule present in biological samples, and allows identification of potential modes of action and altered pathways by systematic measurement of metabolites.

OBJECTIVES

The aim of this study is to review the application of metabolomics studies for use in occupational health, with a focus on applying metabolomics for exposure monitoring and its relationship to occupational diseases.

METHODS

PubMed, Web of Science, Embase and Scopus electronic databases were systematically searched for relevant studies published up to 2021.

RESULTS

Most of reviewed studies included worker populations exposed to heavy metals such as As, Cd, Pb, Cr, Ni, Mn and organic compounds such as tetrachlorodibenzo-p-dioxin, trichloroethylene, polyfluoroalkyl, acrylamide, polyvinyl chloride. Occupational exposures were associated with changes in metabolites and pathways, and provided novel insight into the relationship between exposure and disease outcomes. The reviewed studies demonstrate that metabolomics provides a powerful ability to identify metabolic phenotypes and bioeffect of occupational exposures.

CONCLUSION

Continued application to worker populations has the potential to enable characterization of thousands of chemical signals in biological samples, which could lead to discovery of new biomarkers of exposure for chemicals, identify possible toxicological mechanisms, and improved understanding of biological effects increasing disease risk associated with occupational exposure.

Evaluation and optimization of analytical procedure and sample preparation for polar Streptomyces albus J1074 metabolome profiling

Metabolomics is an essential discipline in omics technology that promotes research on the biology of microbial systems. Streptomyces albus J1074 is a model organism used in fundamental research and industrial microbiology. Nevertheless, a comprehensive and standardized method for analyzing the metabolome of S. albus J1074 is yet to be developed. Thus, we comprehensively evaluated and optimized the analytical procedure and sample preparation for profiling polar metabolites using hydrophilic interaction liquid chromatography (HILIC) coupled with high-resolution mass spectrometry (HRMS). We systematically examined the HILIC columns, quenching solutions, sample-to-quenching ratios, and extraction methods. Then, the optimal protocol was used to investigate the dynamic intracellular polar metabolite profile of the engineered S. albus J1074 strains during spinosad (spinosyn A and spinosyn D) fermentation. A total of 3648 compounds were detected, and 83 metabolites were matched to the standards. The intracellular metabolomic profiles of engineered S. albus J1074 strains (ADE-AP and OE3) were detected; furthermore, their metabolomes in different stages were analyzed to reveal the reasons for their differences in their spinosad production, as well as the current metabolic limitation of heterologous spinosad production in S. albus J1074. The HILIC-HRMS method is a valuable tool for investigating polar metabolomes, and provides a reference methodology to study other Streptomyces metabolomes.

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A HILIC-HRMS method was developed for polar metabolome profiling.

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Sample preparation protocol for Streptomyces albus J1074 intracellular metabolites was studied for the first time.

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This study revealed the possible reasons for different production of spinosad of engineered S. albus J1074 strains.

Metabolic Plasticity of Candida albicans in Response to Different Environmental Conditions

The ubiquitous commensal Candida albicans, part of the human microbiota, is an opportunistic pathogen able to cause a wide range of diseases, from cutaneous mycoses to life-threatening infections in immunocompromised patients. Candida albicans adapts to different environments and survives long-time starvation. The ability to switch from yeast to hyphal morphology under specific environmental conditions is associated with its virulence. Using hydrogen nuclear magnetic resonance spectroscopy, we profiled the intracellular and extracellular metabolome of C. albicans kept in water, yeast extract–peptone–dextrose (YPD), and M199 media, at selected temperatures. Experiments were carried out in hypoxia to mimic a condition present in most colonized niches and fungal infection sites. Comparison of the intracellular metabolites measured in YPD and M199 at 37 °C highlighted differences in specific metabolic pathways: (i) alanine, aspartate, glutamate metabolism, (ii) arginine and proline metabolism, (iii) glycerolipid metabolism, attributable to the diverse composition of the media. Moreover, we hypothesized that the subtle differences in the M199 metabolome, observed at 30 °C and 37 °C, are suggestive of modifications propaedeutic to a subsequent transition from yeast to hyphal form. The analysis of the metabolites’ profiles of C. albicans allows envisaging a molecular model to better describe its ability to sense and adapt to environmental conditions.

Bacterial Metabolomics: Sample Preparation Methods

Metabolomics is a comprehensive analysis of metabolites existing in biological systems. As one of the important "omics" tools, the approach has been widely employed in various fields in helping to better understand the complex cellular metabolic states and changes. Bacterial metabolomics has gained a significant interest as bacteria serve to provide a better subject or model at systems level. The approach in metabolomics is categorized into untargeted and targeted which serves different paradigms of interest. Nevertheless, the bottleneck in metabolomics has been the sample or metabolite preparation method. A custom-made method and design for a particular species or strain of bacteria might be necessary as most studies generally refer to other bacteria or even yeast and fungi that may lead to unreliable analysis. The paramount aspect of metabolomics design comprises sample harvesting, quenching, and metabolite extraction procedures. Depending on the type of samples and research objective, each step must be at optimal conditions which are significantly important in determining the final output. To date, there are no standardized nor single designated protocols that have been established for a specific bacteria strain for untargeted and targeted approaches. In this paper, the existing and current developments of sample preparation methods of bacterial metabolomics used in both approaches are reviewed. The review also highlights previous literature of optimized conditions used to propose the most ideal methods for metabolite preparation, particularly for bacterial cells. Advantages and limitations of methods are discussed for future improvement of bacterial metabolomics.

Effect of cultivation media and temperature on metabolite profiles of three nematicidal Bacillus species

Globally, root-knot nematode (RKN) infestations cause great financial losses. Although agrochemicals are used to manage these pests, there is increased interest in using biocontrol agents based on natural antagonistic microorganisms, such as Bacillus. These nematicidal bacteria demonstrate antagonism towards RKN through different modes of action, including specialised metabolite production. The aim of this study was to compare metabolite profiles of nematicidal Bacillus species and assess the influence of cultivation conditions on these profiles. Two hyphenated metabolomics platforms, gas chromatography-mass spectrometry (GC-MS) and liquid chromatography coupled to quadrupole time-of-flight mass spectrometry (LC-QTOF-MS), were employed to profile and compare metabolite features produced during the cultivation of three nematicidal Bacillus species (Bacillus firmus, B. cereus and B. soli) in complex Luria-Bertani broth (LB) and a simpler minimal broth (MB), at three different temperatures (25, 30 and 37°C). Cultivation in complex LB as opposed to simpler MB resulted in the production of more statistically significant metabolite features. Selected temperatures in this study did not have a significant influence on metabolite profiles. Moreover, media-specific influences outweighed temperature-specific influences on metabolite profiles. Results from this study are a valuable first step in establishing suitable cultivation conditions for the production of Bacillus metabolites of interest.

Metabolomic analyses on microbial primary and secondary oxidative stress responses

Food safety is veryimportant in our daily life. In food processing or disinfection, microorganisms are commonly exposed to oxidative stress perturbations. However, microorganisms can adapt and respond to physicochemical interventions, leading to difficulty and complexity for food safety assurance. Therefore, understanding the response mechanisms of microbes and providing an overview of the responses under oxidative stress conditions are beneficial for ensuring food safety for the industry. The current review takes the metabolomics approach to reveal small metabolite signatures and key pathway alterations during oxidative stress at the molecular and technical levels. These alterations are involved in primary oxidative stress responses due to inactivation treatments such as using hypochlorite (HOCl), hydrogen peroxide (H₂ O₂ ), electrolyzed water (EW), irradiation, pulsed light (PL), electron beam (EB), and secondary oxidative stress responses due to exposures to excessive conditions such as heat, pressure, acid, and alkaline. Details on the putative origin of exogenous or endogenous reactive oxygen species (ROS) are discussed, with particular attention paid to their effects on lipid, amino acid, nucleotide, and carbohydrate metabolism. In addition, mechanisms on counteracting oxidative stresses, stabilization of cell osmolality as well as energy provision for microbes to survive are also discussed.

GC-MS-Based Metabolomics Study of Single- and Dual-Species Biofilms of Candida albicans and Klebsiella pneumoniae

Candida albicans and Klebsiella pneumoniae frequently co-exist within the human host as a complex biofilm community. These pathogens are of interest because their association is also related to significantly increased morbidity and mortality in hospitalized patients. With the aim of highlighting metabolic shifts occurring in the dual-species biofilm, an untargeted GC-MS-based metabolomics approach was applied to single and mixed biofilms of C. albicans and K. pneumoniae. Metabolomic results showed that among the extracellular metabolites identified, approximately 40 compounds had significantly changed relative abundance, mainly involving central carbon, amino acid, vitamin, and secondary metabolisms, such as serine, leucine, arabitol, phosphate, vitamin B6, cyclo-(Phe-Pro), trehalose, and nicotinic acid. The results were related to the strict interactions between the two species and the different microbial composition in the early and mature biofilms.

Impact of the Peptide WMR-K on Dual-Species Biofilm Candida albicans/Klebsiella pneumoniae and on the Untargeted Metabolomic Profile

In recent years, the scientific community has focused on the development of new antibiotics to address the difficulties linked to biofilm-forming microorganisms and drug-resistant infections. In this respect, synthetic antimicrobial peptides (AMPs) are particularly regarded for their therapeutic potential against a broad spectrum of pathogens. In this work, the antimicrobial and antibiofilm activities of the peptide WMR-K towards single and dual species cultures of Candida albicans and Klebsiella pneumoniae were investigated. We found minimum inhibitory concentration (MIC) values for WMR-K of 10 µM for K. pneumoniae and of 200 µM for C. albicans. Furthermore, sub-MIC concentrations of peptide showed an in vitro inhibition of biofilm formation of mono and polymicrobial systems and also a good biofilm eradication even if higher concentrations of it are needed. In order to provide additional evidence for the effect of the examined peptide, a study of changes in extracellular metabolites excreted and/or uptaken from the culture medium (metabolomic footprinting) in the poly-microbial association of C. albicans and K. pneumoniae in presence and absence of WMR-K was performed. Comparing to the untreated dual species biofilm culture, the metabolomic profile of the WMR-K treated culture appears significantly altered. The differentially expressed compounds are mainly related to the primary metabolic pathways, including amino acids, trehalose, pyruvic acid, glycerol and vitamin B6.

Editing of the Proteolytic System of Lactococcus lactis Increases Its Bioactive Potential

Large-scale mass spectrometry-based peptidomics for bioactive-peptide discovery is relatively unexplored because of challenges in intracellular peptide extraction and small-peptide identification. Here, we present an analytical pipeline for large-scale intracellular peptidomics of Lactococcus lactis It entails an optimized sample preparation protocol for L. lactis, used as an "enzyme complex" to digest β-casein, an extraction method for its intracellular peptidome, and a peptidomics data analysis and visualization procedure. In addition, we proofread the publicly available bioactive-peptide databases and obtained an optimized database of bioactive peptides derivable from bovine β-casein. We used the pipeline to examine cultures of L. lactis MG1363 and a set of 6 isogenic multiple peptidase mutants incubated with β-casein. We observed a clearly strain-dependent accumulation of peptides with several bioactivities, such as angiotensin-converting enzyme (ACE)-inhibitory, dipeptidyl peptidase 4 (DPP-IV)-inhibitory, and immunoregulatory functions. The results suggest that both the number of different bioactive peptides and the bioactivity diversity can be increased by editing the proteolytic system of L. lactis This comprehensive pipeline offers a model for discovery of bioactive peptides in combination with other proteins and might be applicable to other bacteria.IMPORTANCE Lactic acid bacteria (LAB) are very important for the production of safe and healthy human and animal fermented foods and feed and, increasingly more, in the functional food industry. The intracellular peptidomes of LAB are promising reservoirs of bioactive peptides. We show here that targeted genetic engineering of the peptide degradation pathway allows steering the composition of the peptide pool of the LAB Lactococcus lactis and production of peptides with interesting bioactivities. Our work could be used as a guideline for modifying proteolytic systems in other LAB to further explore their potential as cell peptide factories.

Recent advances in the application of metabolomics for food safety control and food quality analyses

As one of the omics fields, metabolomics has unique advantages in facilitating the understanding of physiological and pathological activities in biology, physiology, pathology, and food science. In this review, based on developments in analytical chemistry tools, cheminformatics, and bioinformatics methods, we highlight the current applications of metabolomics in food safety, food authenticity and quality, and food traceability. Additionally, the combined use of metabolomics with other omics techniques for "foodomics" is comprehensively described. Finally, the latest developments and advances, practical challenges and limitations, and requirements related to the application of metabolomics are critically discussed, providing new insight into the application of metabolomics in food analysis.

Metabolomic applications for understanding complex tripartite plant-microbes interactions: Strategies and perspectives

Phytopathogens from the Alternaria sp., Fusarium sp., Penicillium sp., and Pseudomonas sp. and their toxigenic metabolites - alternariol, fumonisin, citrinin, and coronatine respectively, negatively impact crop yields and sales by eliciting plant diseases and/or causing human and veterinary toxicoses upon the consumption of contaminated food. These phytopathogens and their associated toxins, however, are present and most likely in undetectable concentrations pre-harvest and post-harvest of many major staple crops. Metabolomic approaches have been used extensively for better characterizing and diagnosing human disease, plant disease and, their etiological agents. Their use in agro-industrial research focusing specifically on tripartite (plant - toxicogenic microbe - beneficial microbe) interactions is, however, limited. Since new approaches for eradicating food-borne pathogens, increasing crop productivity and improving agro-international trade are being sought worldwide, the consequent integration of metabolomic approaches and perspectives in crop protection strategies for better understanding plant - toxicogenic microbe - beneficial microbe interaction in tandem is discussed.

Absolute Quantification of the Central Carbon Metabolome in Eight Commonly Applied Prokaryotic and Eukaryotic Model Systems

Absolute quantification of intracellular metabolite pools is a prerequisite for modeling and in-depth biological interpretation of metabolomics data. It is the final step of an elaborate metabolomics workflow, with challenges associated with all steps—from sampling to quantifying the physicochemically diverse metabolite pool. Chromatographic separation combined with mass spectrometric (MS) detection is the superior platform for high coverage, selective, and sensitive detection of metabolites. Herein, we apply our quantitative MS-metabolomics workflow to measure and present the central carbon metabolome of a panel of commonly applied biological model systems. The workflow includes three chromatographic methods combined with isotope dilution tandem mass spectrometry to allow for absolute quantification of 68 metabolites of glycolysis, the pentose phosphate pathway, the tricarboxylic acid cycle, and the amino acid and (deoxy) nucleoside pools. The biological model systems; Bacillus subtilis, Saccharomyces cerevisiae, two microalgal species, and four human cell lines were all cultured in commonly applied culture media and sampled in exponential growth phase. Both literature and databases are scarce with comprehensive metabolite datasets, and existing entries range over several orders of magnitude. The workflow and metabolite panel presented herein can be employed to expand the list of reference metabolomes, as encouraged by the metabolomics community, in a continued effort to develop and refine high-quality quantitative metabolomics workflows.

From Samples to Insights into Metabolism: Uncovering Biologically Relevant Information in LC-HRMS Metabolomics Data

Untargeted metabolomics (including lipidomics) is a holistic approach to biomarker discovery and mechanistic insights into disease onset and progression, and response to intervention. Each step of the analytical and statistical pipeline is crucial for the generation of high-quality, robust data. Metabolite identification remains the bottleneck in these studies; therefore, confidence in the data produced is paramount in order to maximize the biological output. Here, we outline the key steps of the metabolomics workflow and provide details on important parameters and considerations. Studies should be designed carefully to ensure appropriate statistical power and adequate controls. Subsequent sample handling and preparation should avoid the introduction of bias, which can significantly affect downstream data interpretation. It is not possible to cover the entire metabolome with a single platform; therefore, the analytical platform should reflect the biological sample under investigation and the question(s) under consideration. The large, complex datasets produced need to be pre-processed in order to extract meaningful information. Finally, the most time-consuming steps are metabolite identification, as well as metabolic pathway and network analysis. Here we discuss some widely used tools and the pitfalls of each step of the workflow, with the ultimate aim of guiding the reader towards the most efficient pipeline for their metabolomics studies.

Metabolomics Study of Subsurface Wastewater Infiltration System Under Fluctuation of Organic Load

Subsurface Wastewater Infiltration System (SWIS) is a sewage ecological treatment technology with low investment, energy consumption, and operating cost. SWIS soil contains a large variety of microorganisms. The metabolic process and production of microorganisms are an important basis for qualitatively describing the process of pollutant removal. In order to discover the microbial decontamination pathways in SWIS, the metabolic profiles of soil microorganisms in SWIS were analyzed by UPLC-MS. Partial least squares-discriminant analysis (PLS-DA)and principal component analysis (PCA) pattern recognition methods were used to classify the samples. According to the model's variable importance factor (VIP value), potential biomarkers were screened and biological information contained in the metabolites was also analyzed. The correlation between metabolites and environmental factors was explored by RDA analysis. In total, 230 differential metabolites with VIP value greater than 1.5 were screened out when the influent organic load fluctuated at 250 mg L^-1, 400 mg L^-1, and 500 mg L^-1. After identifying and screening, 35 differential metabolites were identified and used to further analyze the metabolic pathway. It turns out that microbial metabolites in SWIS were mainly glycosides, fatty acids, amino acids, pigments, diterpenoids, and some polymers under medium and high organic loading conditions. At low organic load, the microbial metabolites in SWIS were mainly ketones, alcohols, and esters.

Metabolomics technology and bioinformatics for precision medicine

Precision medicine is rapidly emerging as a strategy to tailor medical treatment to a small group or even individual patients based on their genetics, environment and lifestyle. Precision medicine relies heavily on developments in systems biology and omics disciplines, including metabolomics. Combination of metabolomics with sophisticated bioinformatics analysis and mathematical modeling has an extreme power to provide a metabolic snapshot of the patient over the course of disease and treatment or classifying patients into subpopulations and subgroups requiring individual medical treatment. Although a powerful approach, metabolomics have certain limitations in technology and bioinformatics. We will review various aspects of metabolomics technology and bioinformatics, from data generation, bioinformatics analysis, data fusion and mathematical modeling to data management, in the context of precision medicine.

Expression of extracellular peroxidases and catalases in mesophilic and thermophilic Chaetomia in response to environmental oxidative stress stimuli

Peroxidases and catalases are well-known antioxidant enzymes produced in almost all living organisms for the elimination of reactive oxygen species (ROS) and thus they prevent the occurrence of oxidative stress. In our study we focused on two soil fungi of the family Chaetomiaceae (mesophilic Chaetomium cochliodes and its thermophilic counterpart C. thermophilum var. dissitum) in order to explore the presence of peroxidase and catalase genes, formation of their native transcripts and protective effect of corresponding translation products in a case study. Predicted genes of our interest were confirmed by genomic PCR and their inducible transcripts by RT-PCR. We were able to quantify the expression levels of newly discovered fungal heme peroxidases and catalases with the reverse-transcription quantitative real-time PCR method. We compared obtained quantitative levels of mRNA production with the level of corresponding extracellular protein occurrence as detected with monitoring their specific peroxidase and catalase activities directly in the cultivation media at optimal growth temperatures. The presence of secretory Catalase 2 from C. thermophilum var. dissitum was detected and identified with mass spectrometry approach directly in the growth medium. This unique catalase is phylogenetically closely related with a previously described catalase-phenol oxidase thus representing an effective and versatile antioxidant in the environment of the fungal mycelia also involved in the catabolism of recalcitrant phenolic substances.

Choosing an Optimal Sample Preparation in Caulobacter crescentus for Untargeted Metabolomics Approaches

Untargeted metabolomics aims to provide a global picture of the metabolites present in the system under study. To this end, making a careful choice of sample preparation is mandatory to obtain reliable and reproducible biological information. In this study, eight different sample preparation techniques were evaluated using Caulobacter crescentus as a model for Gram-negative bacteria. Two cell retrieval systems, two quenching and extraction solvents, and two cell disruption procedures were combined in a full factorial experimental design. To fully exploit the multivariate structure of the generated data, the ANOVA multiblock orthogonal partial least squares (AMOPLS) algorithm was employed to decompose the contribution of each factor studied and their potential interactions for a set of annotated metabolites. All main effects of the factors studied were found to have a significant contribution on the total observed variability. Cell retrieval, quenching and extraction solvent, and cell disrupting mechanism accounted respectively for 27.6%, 8.4%, and 7.0% of the total variability. The reproducibility and metabolome coverage of the sample preparation procedures were then compared and evaluated in terms of relative standard deviation (RSD) on the area for the detected metabolites. The protocol showing the best performance in terms of recovery, versatility, and variability was centrifugation for cell retrieval, using MeOH:H₂O (8:2) as quenching and extraction solvent, and freeze-thaw cycles as the cell disrupting mechanism.

Evaluation of metabolome sample preparation and extraction methodologies for oleaginous filamentous fungi Mortierella alpina

INTRODUCTION

Metabolomics has been successfully applied to guide the rational engineering of industrial strains and improve the performance of bioprocesses. Mortierella alpina has traditionally been one of the most popular industrial strains for the production of polyunsaturated fatty acids. However, a systematic comparison and optimisation of the metabolomic analysis methods of M. alpina has not yet been reported.

OBJECTIVE

We sought to identify potential weaknesses that are important for accurate metabolomic analysis. We also aimed to determine an efficient sample preparation protocol for metabolomics studies in the oleaginous filamentous fungus M. alpina.

METHODS

In this study, using GC-MS, we evaluated three sample preparation protocols and five solvent mixtures by assessment of the metabolite profile differences, the sum of peak intensities and the reproducibility of metabolite quantification.

RESULTS

The freeze-dried biomass had better reproducibility and recovery than fresh biomass for metabolite extraction and data normalisation that is part of a metabolomics analysis of filamentous fungi M. alpina. Methanol:water (1:1) was superior for the profiling of metabolites in oleaginous fungi M. alpina. The unbiased metabolite profiling difference between the growth phase and lipids synthesis phase revealed that the degradation of amino acids were critical nodes for the efficient synthesis of lipids in M. alpina.

CONCLUSION

The use of freeze-dried biomass for metabolite extraction and data normalisation was more efficient at measuring the active state of the intracellular metabolites in M. alpina. We recommend extracting the intracellular metabolites with methanol:water (1:1). An important role of amino acid oxidation in the nitrogen limitation-mediated lipid accumulation was found.

Metabolomic Insights into Human Arboviral Infections: Dengue, Chikungunya, and Zika Viruses

The global burden of arboviral diseases and the limited success in controlling them calls for innovative methods to understand arbovirus infections. Metabolomics has been applied to detect alterations in host physiology during infection. This approach relies on mass spectrometry or nuclear magnetic resonance spectroscopy to evaluate how perturbations in biological systems alter metabolic pathways, allowing for differentiation of closely related conditions. Because viruses heavily depend on host resources and pathways, they present unique challenges for characterizing metabolic changes. Here, we review the literature on metabolomics of arboviruses and focus on the interpretation of identified molecular features. Metabolomics has revealed biomarkers that differentiate disease states and outcomes, and has shown similarities in metabolic alterations caused by different viruses (e.g., lipid metabolism). Researchers investigating such metabolomic alterations aim to better understand host⁻virus dynamics, identify diagnostically useful molecular features, discern perturbed pathways for therapeutics, and guide further biochemical research. This review focuses on lessons derived from metabolomics studies on samples from arbovirus-infected humans.

Addressing Global Ruminant Agricultural Challenges Through Understanding the Rumen Microbiome: Past, Present, and Future

The rumen is a complex ecosystem composed of anaerobic bacteria, protozoa, fungi, methanogenic archaea and phages. These microbes interact closely to breakdown plant material that cannot be digested by humans, whilst providing metabolic energy to the host and, in the case of archaea, producing methane. Consequently, ruminants produce meat and milk, which are rich in high-quality protein, vitamins and minerals, and therefore contribute to food security. As the world population is predicted to reach approximately 9.7 billion by 2050, an increase in ruminant production to satisfy global protein demand is necessary, despite limited land availability, and whilst ensuring environmental impact is minimized. Although challenging, these goals can be met, but depend on our understanding of the rumen microbiome. Attempts to manipulate the rumen microbiome to benefit global agricultural challenges have been ongoing for decades with limited success, mostly due to the lack of a detailed understanding of this microbiome and our limited ability to culture most of these microbes outside the rumen. The potential to manipulate the rumen microbiome and meet global livestock challenges through animal breeding and introduction of dietary interventions during early life have recently emerged as promising new technologies. Our inability to phenotype ruminants in a high-throughput manner has also hampered progress, although the recent increase in “omic” data may allow further development of mathematical models and rumen microbial gene biomarkers as proxies. Advances in computational tools, high-throughput sequencing technologies and cultivation-independent “omics” approaches continue to revolutionize our understanding of the rumen microbiome. This will ultimately provide the knowledge framework needed to solve current and future ruminant livestock challenges.

Comprehensive optimization of the metabolomic methodology for metabolite profiling of Corynebacterium glutamicum

Metabolomics has been a potential tool for strain improvement through analyzing metabolite changes in the context of different conditions. However, the availability of a universal metabolite profiling analysis is still a big challenge. In this study, we presented an optimized liquid chromatography-tandem mass spectrometry-based metabolomics methodology for Corynebacterium glutamicum, an important industrial workhorse. It was found that quenching the cellular metabolism with 5-fold volume of - 20 °C 40% methanol was highly recommended due to its lower cell damage rate and higher intracellular metabolite recovery rate. For extracting intracellular metabolites, ethanol/water (3:1, v/v) at 100 °C combined with acidic acetonitrile/water (1:1, v/v, with 0.1% formic acid) at - 20 °C achieved the unbiased metabolite profiling of C. glutamicum. The established methodology was then applied to investigate the intracellular metabolite differences between C. glutamicum ATCC 13032 and an mscCG-deleted mutant under biotin limitation condition. It was observed that in the presence of the functional L-glutamate exporter MscCG, biotin limitation led to accumulation of intracellular 2-oxoglutarate but not L-glutamate. Deletion of mscCG severely inhibited L-glutamate excretion and resulted in a dramatical increase of intracellular L-glutamate, which in turn affected the metabolite profile. The optimized metabolomics methodology holds promise for promoting studies on metabolic mechanism of C. glutamicum.

Mass spectrometry-based metabolomics for tuberculosis meningitis

Tuberculosis meningitis (TBM) is a prevalent form of extra-pulmonary tuberculosis that causes substantial morbidity and mortality. Diagnosis of TBM is difficult because of the limited sensitivity of existing laboratory techniques. A metabolomics approach can be used to investigate the sets of metabolites of both bacteria and host, and has been used to clarify the mechanisms underlying disease development, and identify metabolic changes, leadings to improved methods for diagnosis, treatment, and prognostication. Mass spectrometry (MS) is a major analysis platform used in metabolomics, and MS-based metabolomics provides wide metabolite coverage, because of its high sensitivity, and is useful for the investigation of Mycobacterium tuberculosis (Mtb) and related diseases. It has been used to investigate TBM diagnosis; however, the processes involved in the MS-based metabolomics approach are complex and flexible, and often consist of several steps, and small changes in the methods used can have a huge impact on the final results. Here, the process of MS-based metabolomics is summarized and its applications in Mtb and Mtb-related diseases discussed. Moreover, the current status of TBM metabolomics is described.

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.