Microbial metabolomics: innovation, application, insight

Plasma metabonomics of classical swine fever virus-infected pigs

Classical swine fever (CSF) is an infectious disease caused by Classical swine fever virus (CSFV), which is characterized by depression, high fever, extensive skin bleeding, leukopenia, anorexia, alternating constipation, and diarrhea. Hemorrhagic infarction of the spleen is the main characteristic pathological change following CSFV infection. Large-scale outbreaks of CSF are rare in China and are mainly distributed regionally. The clinical symptoms of CSF are not obvious, and show variation from typical to atypical symptoms, which makes diagnosis based on clinical symptoms and pathology challenging. In recent years, the incidence of CSF-immunized pig farms in China has increased and new CSFV gene subtypes have appeared, posing new challenges to the prevention and control of CSF in China. Changes in metabolites caused by viral infection reflect the pathogenic process. Metabonomics can reveal the trace metabolites of organisms; however, plasma metabonomics of CSFV-infected pigs have rarely been investigated. Therefore, we used an established pig CSFV infection model to study changes in plasma metabolites. The results showed significant differences in forty-five plasma metabolites at different time periods after CSFV infection in pigs, with an increase in twenty-five metabolites and a decrease in twenty metabolites. These changed metabolites were mainly attributed to the tricarboxylic acid cycle, amino acid cycle, sugar metabolism, and fat metabolism. Thirteen metabolic pathways changed significantly in CSFV-infected pigs, including tricarboxylic acid cycle, inositol phosphate metabolism, glycine, serine and threonine metabolism,lysine degradation, alanine, aspartate and glutamic acid metabolism, pantothenate and CoA biosynthesis, β-alanine metabolism, lysine degradation, arginine and proline metabolism, glycerolipid metabolism, phenylalanine metabolism, arachidonic acid metabolism, linoleic acid metabolism. Among these, changes in fatty acid biosynthesis and metabolism occurred at all time periods post-infection. These results indicate that CSFV infection in pigs could seriously alter metabolic pathways.

Mussel mass mortality in the Clinch River, USA: metabolomics detects affected pathways and biomarkers of stress

Biologists monitoring freshwater mussel (order Unionida) populations rely on behavioral, often subjective, signs to identify moribund ("sick") or stressed mussels, such as gaping valves and slow response to probing, and they lack clinical indicators to support a diagnosis. As part of a multi-year study to investigate causes of reoccurring mortality of pheasantshell (Ortmanniana pectorosa; synonym Actinonaias pectorosa) in the Clinch River, Virginia and Tennessee, USA, we analyzed the hemolymph metabolome of a subset of mussels from the 2018 sampling period. Mussels at the mortality sites were diagnosed in the field as affected (case) or unaffected (control) based on behavioral and physical signs. Hemolymph was collected in the field by non-lethal methods from the anterior adductor muscle for analysis. We used ultra-high-performance liquid chromatography with quadrupole time-of-flight mass spectroscopy to detect targeted and untargeted metabolites in hemolymph and compared metabolomic profiles by field assessment of clinical status. Targeted biomarker analysis found 13 metabolites associated with field assessments of clinical status. Of these, increased gamma-linolenic acid and N-methyl-l-alanine were most indicative of case mussels, while adenine and inosine were the best indicators of control mussels. Five pathways in the targeted analysis differed by clinical status; two of these, purine metabolism and glycerophospholipid metabolism, were also indicated in the untargeted analysis. In the untargeted nalysis, 22 metabolic pathways were associated with clinical status. Many of the impacted pathways in the case group were catabolic processes, such as degradation of amino acids and fatty acids. Hierarchical clustering analysis matched clinical status in 72% (18 of 25) of mussels, with control mussels more frequently (5 of 16) not matching clinical status. Our study demonstrated that metabolomic analysis of hemolymph is suitable for assessing mussel condition and complements field-based indicators of health.

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.

Anti-cancer activity of human gastrointestinal bacteria

Malignant neoplasm is one of the most incurable diseases among inflammatory diseases. Researchers have been studying for decades to win over this lethal disease and provide the light of hope to humankind. The gastrointestinal bacteria of human hold a complex ecosystem and maintain homeostasis. One hundred trillion microbes are residing in the gastrointestinal tract of human. Disturbances in the microbiota of human's gastrointestinal tract can create immune response against inflammation and also can develop diseases, including cancer. The bacteria of the gastrointestinal tract of human can secrete a variety of metabolites and bioproducts which aid in the preservation of homeostasis in the host and gut. During pathogenic dysbiosis, on the other hand, numerous microbiota subpopulations may increase and create excessive levels of toxins, which can cause inflammation and cancer. Furthermore, the immune system of host and the epithelium cell can be influenced by gut microbiota. Probiotics, which are bacteria that live in the gut, have been protected against tumor formation. Probiotics are now studied to see if they can help fight dysbiosis in cancer patients undergoing chemotherapy or radiotherapy because of their capacity to maintain gut homeostasis. Countless numbers of gut bacteria have demonstrated anti-cancer efficiency in cancer treatment, prevention, and boosting the efficiency of immunotherapy. The review article has briefly explained the anti-cancer immunity of gut microbes and their application in treating a variety of cancer. This review paper also highlights the pre-clinical studies of probiotics against cancer and the completed and ongoing clinical trials on cancers with the two most common and highly effective probiotics Lactobacillus and Bacillus spp.

Marine Bacteria and Omic Approaches: A Novel and Potential Repository for Bioremediation Assessment

Marine environments accommodating diverse assortments of life constitute a great pool of differentiated natural resources. The cumulative need to remedy unpropitious effects of anthropogenic activities on estuaries, and coastal marine ecosystems has propelled the development of effective bioremediation strategies. Marine bacteria producing biosurfactants are promising agents for bio-remediating oil pollution in marine environments, making them prospective candidates for enhancing oil recovery. Molecular omics technologies are considered an emerging field of research in ecological and diversity assessment owing to their utility in environmental surveillance and bioremediation of polluted sites. A thorough literature review was undertaken to understand the applicability of different omic techniques employed for bioremediation assessment using marine bacteria. This review further establishes that for bioremediation of environmental pollutants (i.e., heavy metals, hydrocarbons, xenobiotic and numerous recalcitrant compounds), organisms isolated from marine environments can be better utilized for their removal. The literature survey shows that omics approaches can provide exemplary knowledge about microbial communities and their role in the bioremediation of environmental pollutants. This review centres on applications of marine bacteria in enhanced bioremediation, utilizing the omics approaches that can be a vital biological contrivance in environmental monitoring to tackle environmental degradation. The paper aims to identify the gaps in investigations involving marine bacteria to help researchers, ecologists, and decision-makers to develop a holistic understanding regarding their utility in bioremediation assessment.

Current State and Challenges of the Global Outcomes of Dental Caries Research in the Meta-Omics Era

Despite significant healthcare advances in the 21st century, the exact etiology of dental caries remains unsolved. The past two decades have witnessed a tremendous growth in our understanding of dental caries amid the advent of revolutionary omics technologies. Accordingly, a consensus has been reached that dental caries is a community-scale metabolic disorder, and its etiology is beyond a single causative organism. This conclusion was based on a variety of microbiome studies following the flow of information along the central dogma of biology from genomic data to the end products of metabolism. These studies were facilitated by the unprecedented growth of the next- generation sequencing tools and omics techniques, such as metagenomics and metatranscriptomics, to estimate the community composition of oral microbiome and its functional potential. Furthermore, the rapidly evolving proteomics and metabolomics platforms, including nuclear magnetic resonance spectroscopy and/or mass spectrometry coupled with chromatography, have enabled precise quantification of the translational outcomes. Although the majority supports 'conserved functional changes' as indicators of dysbiosis, it remains unclear how caries dynamics impact the microbiota functions and vice versa, over the course of disease onset and progression. What compounds the situation is the host-microbiota crosstalk. Genome-wide association studies have been undertaken to elucidate the interaction of host genetic variation with the microbiome. However, these studies are challenged by the complex interaction of host genetics and environmental factors. All these complementary approaches need to be orchestrated to capture the key players in this multifactorial disease. Herein, we critically review the milestones in caries research focusing on the state-of-art singular and integrative omics studies, supplemented with a bibliographic network analysis to address the oral microbiome, the host factors, and their interactions. Additionally, we highlight gaps in the dental literature and shed light on critical future research questions and study designs that could unravel the complexities of dental caries, the most globally widespread disease.

Inferring microbiota functions from taxonomic genes: a review

Deciphering microbiota functions is crucial to predict ecosystem sustainability in response to global change. High-throughput sequencing at the individual or community level has revolutionized our understanding of microbial ecology, leading to the big data era and improving our ability to link microbial diversity with microbial functions. Recent advances in bioinformatics have been key for developing functional prediction tools based on DNA metabarcoding data and using taxonomic gene information. This cheaper approach in every aspect serves as an alternative to shotgun sequencing. Although these tools are increasingly used by ecologists, an objective evaluation of their modularity, portability, and robustness is lacking. Here, we reviewed 100 scientific papers on functional inference and ecological trait assignment to rank the advantages, specificities, and drawbacks of these tools, using a scientific benchmarking. To date, inference tools have been mainly devoted to bacterial functions, and ecological trait assignment tools, to fungal functions. A major limitation is the lack of reference genomes-compared with the human microbiota-especially for complex ecosystems such as soils. Finally, we explore applied research prospects. These tools are promising and already provide relevant information on ecosystem functioning, but standardized indicators and corresponding repositories are still lacking that would enable them to be used for operational diagnosis.

Application oriented bioaugmentation processes: Mechanism, performance improvement and scale-up

Bioaugmentation is an optimization method with great potential to improve the treatment effect by introducing specific strains into the biological treatment system. In this study, a comprehensive review of the mechanism of bioaugmentation from the aspect of microbial community structure, the optimization methods facilitating application as well as feasible approaches of scale-up application has been provided. The different contribution of indigenous and exogenous strains was critically analyzed, the relationship between microbial community variation and system performance was clarified. Operation regulation and immobilization technologies are effective methods to deal with the possible failure of bioaugmentation. The gradual expansion from lab-scale, pilot scale to full-scale, the transformation and upgrading of wastewater treatment plants through the combination of direct dosing and biofilm, and the application of side-stream reactors are feasible ways to realize the full-scale application. The future challenges and prospects in this field were also proposed.

Metabolomics Comparison of Drug-Resistant and Drug-Susceptible Pseudomonas aeruginosa Strain (Intra- and Extracellular Analysis)

Pseudomonas aeruginosa is a common human pathogen belonging to the ESKAPE group. The multidrug resistance of bacteria is a considerable problem in treating patients and may lead to increased morbidity and mortality rate. The natural resistance in these organisms is caused by the production of specific enzymes and biofilm formation, while acquired resistance is multifactorial. Precise recognition of potential antibiotic resistance on different molecular levels is essential. Metabolomics tools may aid in the observation of the flux of low molecular weight compounds in biochemical pathways yielding additional information about drug-resistant bacteria. In this study, the metabolisms of two P. aeruginosa strains were compared-antibiotic susceptible vs. resistant. Analysis was performed on both intra- and extracellular metabolites. The ¹H NMR method was used together with multivariate and univariate data analysis, additionally analysis of the metabolic pathways with the FELLA package was performed. The results revealed the differences in P. aeruginosa metabolism of drug-resistant and drug-susceptible strains and provided direct molecular information about P. aeruginosa response for different types of antibiotics. The most significant differences were found in the turnover of amino acids. This study can be a valuable source of information to complement research on drug resistance in P. aeruginosa.

Improvement of Soil Microbial Diversity through Sustainable Agricultural Practices and Its Evaluation by -Omics Approaches: A Perspective for the Environment, Food Quality and Human Safety

Soil is one of the key elements for supporting life on Earth. It delivers multiple ecosystem services, which are provided by soil processes and functions performed by soil biodiversity. In particular, soil microbiome is one of the fundamental components in the sustainment of plant biomass production and plant health. Both targeted and untargeted management of soil microbial communities appear to be promising in the sustainable improvement of food crop yield, its nutritional quality and safety. –Omics approaches, which allow the assessment of microbial phylogenetic diversity and functional information, have increasingly been used in recent years to study changes in soil microbial diversity caused by agronomic practices and environmental factors. The application of these high-throughput technologies to the study of soil microbial diversity, plant health and the quality of derived raw materials will help strengthen the link between soil well-being, food quality, food safety and human health.

Culturing Human Gut Microbiomes in the Laboratory

The human gut microbiota is a complex community of prokaryotic and eukaryotic microbes and viral particles that is increasingly associated with many aspects of host physiology and health. However, the classical microbiology approach of axenic culture cannot provide a complete picture of the complex interactions between microbes and their hosts in vivo. As such, recently there has been much interest in the culture of gut microbial ecosystems in the laboratory as a strategy to better understand their compositions and functions. In this review, we discuss the model platforms and methods available in the contemporary microbiology laboratory to study human gut microbiomes, as well as current knowledge surrounding the isolation of human gut microbes for the potential construction of defined communities for use in model systems. Expected final online publication date for the Annual Review of Microbiology, Volume 75 is October 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Expanding the drug discovery space with predicted metabolite-target interactions

Metabolites produced in the human gut are known modulators of host immunity. However, large-scale identification of metabolite-host receptor interactions remains a daunting challenge. Here, we employed computational approaches to identify 983 potential metabolite-target interactions using the Inflammatory Bowel Disease (IBD) cohort dataset of the Human Microbiome Project 2 (HMP2). Using a consensus of multiple machine learning methods, we ranked metabolites based on importance to IBD, followed by virtual ligand-based screening to identify possible human targets and adding evidence from compound assay, differential gene expression, pathway enrichment, and genome-wide association studies. We confirmed known metabolite-target pairs such as nicotinic acid-GPR109a or linoleoyl ethanolamide-GPR119 and inferred interactions of interest including oleanolic acid-GABRG2 and alpha-CEHC-THRB. Eleven metabolites were tested for bioactivity in vitro using human primary cell-types. By expanding the universe of possible microbial metabolite-host protein interactions, we provide multiple drug targets for potential immune-therapies.

Hydroxylation of Antitubercular Drug Candidate, SQ109, by Mycobacterial Cytochrome P450

Spreading of the multidrug-resistant (MDR) strains of the one of the most harmful pathogen Mycobacterium tuberculosis (Mtb) generates the need for new effective drugs. SQ109 showed activity against resistant Mtb and already advanced to Phase II/III clinical trials. Fast SQ109 degradation is attributed to the human liver Cytochrome P450s (CYPs). However, no information is available about interactions of the drug with Mtb CYPs. Here, we show that Mtb CYP124, previously assigned as a methyl-branched lipid monooxygenase, binds and hydroxylates SQ109 in vitro. A 1.25 Å-resolution crystal structure of the CYP124-SQ109 complex unambiguously shows two conformations of the drug, both positioned for hydroxylation of the ω-methyl group in the trans position. The hydroxylated SQ109 presumably forms stabilizing H-bonds with its target, Mycobacterial membrane protein Large 3 (MmpL3). We anticipate that Mtb CYPs could function as analogs of drug-metabolizing human CYPs affecting pharmacokinetics and pharmacodynamics of antitubercular (anti-TB) drugs.

Metabolomics as an Emerging Tool in the Search for Astrobiologically Relevant Biomarkers

It is now routinely possible to sequence and recover microbial genomes from environmental samples. To the degree it is feasible to assign transcriptional and translational functions to these genomes, it should be possible, in principle, to largely understand the complete molecular inputs and outputs of a microbial community. However, gene-based tools alone are presently insufficient to describe the full suite of chemical reactions and small molecules that compose a living cell. Metabolomic tools have developed quickly and now enable rapid detection and identification of small molecules within biological and environmental samples. The convergence of these technologies will soon facilitate the detection of novel enzymatic activities, novel organisms, and potentially extraterrestrial life-forms on solar system bodies. This review explores the methodological problems and scientific opportunities facing researchers who hope to apply metabolomic methods in astrobiology-related fields, and how present challenges might be overcome.

Sputum microbiome profiling in COPD: beyond singular pathogen detection

Culture-independent microbial sequencing techniques have revealed that the respiratory tract harbours a complex microbiome not detectable by conventional culturing methods. The contribution of the microbiome to chronic obstructive pulmonary disease (COPD) pathobiology and the potential for microbiome-based clinical biomarkers in COPD are still in the early phases of investigation. Sputum is an easily obtainable sample and has provided a wealth of information on COPD pathobiology, and thus has been a preferred sample type for microbiome studies. Although the sputum microbiome likely reflects the respiratory microbiome only in part, there is increasing evidence that microbial community structure and diversity are associated with disease severity and clinical outcomes, both in stable COPD and during the exacerbations. Current evidence has been limited to mainly cross-sectional studies using 16S rRNA gene sequencing, attempting to answer the question 'who is there?' Longitudinal studies using standardised protocols are needed to answer outstanding questions including differences between sputum sampling techniques. Further, with advancing technologies, microbiome studies are shifting beyond the examination of the 16S rRNA gene, to include whole metagenome and metatranscriptome sequencing, as well as metabolome characterisation. Despite being technically more challenging, whole-genome profiling and metabolomics can address the questions 'what can they do?' and 'what are they doing?' This review provides an overview of the basic principles of high-throughput microbiome sequencing techniques, current literature on sputum microbiome profiling in COPD, and a discussion of the associated limitations and future perspectives.

In plaque-mass spectrometry imaging of a bloom-forming alga during viral infection reveals a metabolic shift towards odd-chain fatty acid lipids

Tapping into the metabolic cross-talk between a host and its virus can reveal unique strategies employed during infection. Viral infection is a dynamic process that generates an evolving metabolic landscape. Gaining a continuous view into the infection process is highly challenging and is limited by current metabolomics approaches, which typically measure the average of the entire population at various stages of infection. Here, we took an innovative approach to study the metabolic basis of host-virus interactions between the bloom-forming alga Emiliania huxleyi and its specific virus. We combined a classical method in virology, the plaque assay, with advanced mass spectrometry imaging (MSI), an approach we termed ‘in plaque-MSI’. Taking advantage of the spatial characteristics of the plaque, we mapped the metabolic landscape induced during infection in a high spatiotemporal resolution, unfolding the infection process in a continuous manner. Further unsupervised spatially-aware clustering, combined with known lipid biomarkers, revealed a systematic metabolic shift during infection towards lipids containing the odd-chain fatty acid pentadecanoic acid (C15:0). Applying ‘in plaque-MSI’ might facilitate the discovery of bioactive compounds that mediate the chemical arms race of host-virus interactions in diverse model systems.

Recent Advancements in Intestinal Microbiota Analyses: A Review for Non-Microbiologists

Microbial constituents naturally inhabiting the gastrointestinal tract may influence the homeostasis of the gut environment. The presence or overabundance of some bacterial taxa has been reported to be associated with complex diseases, and the metabolites of certain bacteria may contribute to diverse disorders by influencing signaling pathways. Therefore, the study of gut microbial population has emerged as a crucial field and a new potential area of clinical significance. Advances in the methods of microbiota analysis have shed light upon the details including species diversity, microfloral activities as well as the entire gut microbiota. Nevertheless, comprehensive reviews on this subject are still limited. For elucidating the appropriate selection strategy of the methods to address a particular research question, we comprehensively reviewed the continuously improving technologies, classical to newly developed, and dissected their relative advantages and drawbacks. In addition, aiming at the rapidly advancing next-generation sequencing, we enumerated the improvements in mainstream platforms and made the horizontal and vertical comparison among them. Additionally, we demonstrated the four main -omics methods, which may provide further mechanistic insights into the role of microbiota, to propel phylotyping analysis to functional analysis.

Antimycobacterial Metabolism: Illuminating Mycobacterium tuberculosis Biology and Drug Discovery

Bacteria are capable of performing a number of biotransformations that may activate or deactivate xenobiotics. Recent efforts have utilized metabolomics techniques to study the fate of small-molecule antibacterials within the targeted organism. Examples involving Mycobacterium tuberculosis are reviewed and analyzed with regard to the insights they provide as to both activation and deactivation of the antibacterial. The studies, in particular, shed light on biosynthetic transformations performed by M. tuberculosis while suggesting avenues for the evolution of chemical tools, highlighting potential areas for drug discovery, and mechanisms of approved drugs. A two-pronged approach investigating the metabolism of antibacterials within both the host and bacterium is outlined and will be of value to both the chemical biology and drug discovery fields.

Metabolic Profiles in Cell Lines Infected with Classical Swine Fever Virus

Viruses require energy and biosynthetic precursors from host cells for replication. An understanding of the metabolic interplay between classical swine fever virus (CSFV) and host cells is important for exploring the complex pathological mechanisms of classical swine fever (CSF). In the current study, and for the first time, we utilized an approach involving gas chromatography coupled with mass spectrometry (GC-MS) to examine the metabolic profiles within PK-15 and 3D4/2 cells infected with CSFV. The differential metabolites of PK-15 cells caused by CSFV infection mainly included the decreased levels of glucose 6-phosphate [fold change (FC) = −1.94)] and glyceraldehyde-3-phosphate (FC = −1.83) during glycolysis, ribulose 5-phosphate (FC = −1.51) in the pentose phosphate pathway, guanosine (FC = −1.24) and inosine (FC = −1.16) during purine biosynthesis, but the increased levels of 2-ketoisovaleric acid (FC = 0.63) during the citrate cycle, and ornithine (FC = 0.56) and proline (FC = 0.62) during arginine and proline metabolism. However, metabolite changes caused by CSFV infection in 3D4/2 cells included the reduced glyceraldehyde-3-phosphate (FC = −0.77) and pyruvic acid (FC = −1.42) during glycolysis, 2-ketoglutaric acid (FC = −1.52) in the citrate cycle, and the elevated cytosine (FC = 2.15) during pyrimidine metabolism. Our data showed that CSFV might rebuild cellular metabolic programs, thus aiding viral replication. These findings may be important in developing targets for new biomarkers for the diagnosis and identification of enzyme inhibitors or metabolites as antiviral drugs, or screening viral gene products as vaccines.

Renal Medulla is More Sensitive to Cisplatin than Cortex Revealed by Untargeted Mass Spectrometry-Based Metabolomics in Rats

Nephrotoxicity has long been the most severe and life-threatening side-effect of cisplatin, whose anticancer effect is therefore restricted. Previous pathological studies have shown that both renal cortex and medulla could be injured by cisplatin. Our TUNEL (terminal deoxynucleotidyl transferase-mediated dUTP nick end-labeling) assay results further uncovered that medulla subjected more severe injury than cortex. In order to depict the underlying metabolic mechanism of spatial difference in response to cisplatin, in the present study, mass spectrometry-based untargeted metabolomics approach was applied to profile renal cortex and medulla metabolites of rat after receiving a single dose of cisplatin (2.5, 5 or 10 mg/kg). Eventually, 53 and 55 differential metabolites in cortex and medulla were screened out, respectively. Random forest, orthogonal partial least squares-discriminant analysis and metabolic cumulative fold change analysis revealed that metabolic changes in medulla were more obviously dose-dependent than those in cortex, which confirmed the conclusion that medulla was more sensitive to cisplatin exposure. Furthermore, 29 intermediates were recognized as the most contributive metabolites for the sensitivity difference. Metabolic pathways interrupted by cisplatin mainly included amino acid, energy, lipid, pyrimidine, purine, and creatine metabolism. Our findings provide new insight into the mechanism study of cisplatin-induced nephrotoxicity.

Metagenomics, Metatranscriptomics, and Metabolomics Approaches for Microbiome Analysis

Microbiomes are ubiquitous and are found in the ocean, the soil, and in/on other living organisms. Changes in the microbiome can impact the health of the environmental niche in which they reside. In order to learn more about these communities, different approaches based on data from multiple omics have been pursued. Metagenomics produces a taxonomical profile of the sample, metatranscriptomics helps us to obtain a functional profile, and metabolomics completes the picture by determining which byproducts are being released into the environment. Although each approach provides valuable information separately, we show that, when combined, they paint a more comprehensive picture. We conclude with a review of network-based approaches as applied to integrative studies, which we believe holds the key to in-depth understanding of microbiomes.

Metabolomics in chemical ecology

Chemical ecology elucidates the nature and role of natural products as mediators of organismal interactions. The emerging techniques that can be summarized under the concept of metabolomics provide new opportunities to study such environmentally relevant signaling molecules. Especially comparative tools in metabolomics enable the identification of compounds that are regulated during interaction situations and that might play a role as e.g. pheromones, allelochemicals or in induced and activated defenses. This approach helps overcoming limitations of traditional bioassay-guided structure elucidation approaches. But the power of metabolomics is not limited to the comparison of metabolic profiles of interacting partners. Especially the link to other -omics techniques helps to unravel not only the compounds in question but the entire biosynthetic and genetic re-wiring, required for an ecological response. This review comprehensively highlights successful applications of metabolomics in chemical ecology and discusses existing limitations of these novel techniques. It focuses on recent developments in comparative metabolomics and discusses the use of metabolomics in the systems biology of organismal interactions. It also outlines the potential of large metabolomics initiatives for model organisms in the field of chemical ecology.

Mass spectrometry tools and workflows for revealing microbial chemistry

Since the time Van Leeuwenhoek was able to observe microbes through a microscope, an innovation that led to the birth of the field of microbiology, we have aimed to understand how microorganisms function, interact and communicate. The exciting progress in the development of analytical technologies and workflows has demonstrated that mass spectrometry is a very powerful technique for the interrogation of microbiology at the molecular level. In this review, we aim to highlight the available and emerging tools in mass spectrometry for microbial analysis by overviewing the methods and workflow advances for taxonomic identification, microbial interaction, dereplication and drug discovery. We emphasize their potential for future development and point out unsolved problems and future directions that would aid in the analysis of the chemistry produced by microbes.

Interactions Between the Gastrointestinal Microbiome and Clostridium difficile

Antibiotics have significant and long-lasting effects on the intestinal microbiota and consequently reduce colonization resistance against pathogens, including Clostridium difficile. By altering the community structure of the gut microbiome, antibiotics alter the intestinal metabolome, which includes both host- and microbe-derived metabolites. The mechanisms by which antibiotics reduce colonization resistance against C. difficile are unknown yet important for development of preventative and therapeutic approaches against this pathogen. This review focuses on how antibiotics alter the structure of the gut microbiota and how this alters microbial metabolism in the intestine. Interactions between gut microbial products and C. difficile spore germination, growth, and toxin production are discussed. New bacterial therapies to restore changes in bacteria-driven intestinal metabolism following antibiotics will have important applications for treatment and prevention of C. difficile infection.

Roseomics: a blank slate

Recent technological advances have led to an explosion in the system-wide profiling of biological processes in the study of herpesvirus biology, herein referred to as '-omics'. In many cases these approaches have revealed novel virus-induced changes to host cell biology that can be targeted with new antiviral therapeutics. Despite these successes, -omics approaches are not widely applied in the study of roseoloviruses. Here we describe examples of how -omics studies have shaped our understanding of herpesvirus biology, and discuss how these approaches might be used to identify host and viral factors that mediate roseolovirus pathogenesis.

Linking metabolomics data to underlying metabolic regulation

The comprehensive experimental analysis of a metabolic constitution plays a central role in approaches of organismal systems biology. Quantifying the impact of a changing environment on the homeostasis of cellular metabolism has been the focus of numerous studies applying various metabolomics techniques. It has been proven that approaches which integrate different analytical techniques, e.g., LC-MS, GC-MS, CE-MS and H-NMR, can provide a comprehensive picture of a certain metabolic homeostasis. Identification of metabolic compounds and quantification of metabolite levels represent the groundwork for the analysis of regulatory strategies in cellular metabolism. This significantly promotes our current understanding of the molecular organization and regulation of cells, tissues and whole organisms. Nevertheless, it is demanding to elicit the pertinent information which is contained in metabolomics data sets. Based on the central dogma of molecular biology, metabolite levels and their fluctuations are the result of a directed flux of information from gene activation over transcription to translation and posttranslational modification. Hence, metabolomics data represent the summed output of a metabolic system comprising various levels of molecular organization. As a consequence, the inverse assignment of metabolomics data to underlying regulatory processes should yield information which—if deciphered correctly—provides comprehensive insight into a metabolic system. Yet, the deduction of regulatory principles is complex not only due to the high number of metabolic compounds, but also because of a high level of cellular compartmentalization and differentiation. Motivated by the question how metabolomics approaches can provide a representative view on regulatory biochemical processes, this article intends to present and discuss current metabolomics applications, strategies of data analysis and their limitations with respect to the interpretability in context of biological processes.

Microbiota control of a tryptophan-AhR pathway in disease tolerance to fungi

An increased understanding of the importance of microbiota in shaping the host's immune and metabolic activities has rendered fungal interactions with their hosts more complex than previously appreciated. The aryl hydrocarbon receptor (AhR) has a pivotal role in connecting tryptophan catabolism by microbial communities and the host's own pathway of tryptophan metabolite production with the orchestration of T-cell function. AhR activation by a Lactobacillus-derived AhR ligand leads to the production of IL-22 to the benefit of mucosal defense mechanisms, an activity upregulated in the absence of the host tryptophan catabolic enzyme, indoleamine 2,3-dioxygenase 1 (IDO1), which is required for protection from fungal diseases ("disease tolerance"). As AhR activation in turn leads to the activation-in a feedback fashion-of IDO1, the regulatory loop involving AhR and IDO1 may have driven the coevolution of commensal fungi with the mammalian immune system and the microbiota, to the benefit of host survival and fungal commensalism. This review will discuss the essential help the microbiota provides in controlling the balance between the dual nature of the fungal-host relationship, namely, commensalism vs. infection.