Microbial metabolomics

Beyond the Gut: The intratumoral microbiome's influence on tumorigenesis and treatment response

The intratumoral microbiome (TM) refers to the microorganisms in the tumor tissues, including bacteria, fungi, viruses, and so on, and is distinct from the gut microbiome and circulating microbiota. TM is strongly associated with tumorigenesis, progression, metastasis, and response to therapy. This paper highlights the current status of TM. Tract sources, adjacent normal tissue, circulatory system, and concomitant tumor co-metastasis are the main origin of TM. The advanced techniques in TM analysis are comprehensively summarized. Besides, TM is involved in tumor progression through several mechanisms, including DNA damage, activation of oncogenic signaling pathways (phosphoinositide 3-kinase [PI3K], signal transducer and activator of transcription [STAT], WNT/β-catenin, and extracellular regulated protein kinases [ERK]), influence of cytokines and induce inflammatory responses, and interaction with the tumor microenvironment (anti-tumor immunity, pro-tumor immunity, and microbial-derived metabolites). Moreover, promising directions of TM in tumor therapy include immunotherapy, chemotherapy, radiotherapy, the application of probiotics/prebiotics/synbiotics, fecal microbiome transplantation, engineered microbiota, phage therapy, and oncolytic virus therapy. The inherent challenges of clinical application are also summarized. This review provides a comprehensive landscape for analyzing TM, especially the TM-related mechanisms and TM-based treatment in cancer.

Bacterial metabolomics: current applications for human welfare and future aspects

An imbalanced microbiome is linked to several diseases, such as cancer, inflammatory bowel disease, obesity, and even neurological disorders. Bacteria and their by-products are used for various industrial and clinical purposes. The metabolites under discussion were chosen based on their biological impacts on host and gut microbiota interactions as established by metabolome research. The separation of bacterial metabolites by using statistics and machine learning analysis creates new opportunities for applications of bacteria and their metabolites in the environmental and medical sciences. Thus, the metabolite production strategies, methodologies, and importance of bacterial metabolites for human well-being are discussed in this review.

Breaking boundaries in microbiology: customizable nanoparticles transforming microbial detection

The detection and identification of microorganisms are crucial in microbiology laboratories. Traditionally, detecting and identifying microbes require extended periods of incubation, significant manual effort, skilled personnel, and advanced laboratory facilities. Recent progress in nanotechnology has provided novel opportunities for detecting and identifying bacteria, viruses, and microbial metabolites using customized nanoparticles. These improvements are thought to have the ability to surpass the constraints of existing procedures and make a substantial contribution to the development of rapid microbiological diagnosis. This review article examines the customizability of nanoparticles for detecting bacteria, viruses, and microbial metabolites and discusses recent cutting-edge studies demonstrating the use of nanotechnology in biomedical research.

Biobased short chain fatty acid production - Exploring microbial community dynamics and metabolic networks through kinetic and microbial modeling approaches

In recent years, there has been growing interest in harnessing anaerobic digestion technology for resource recovery from waste streams. This approach has evolved beyond its traditional role in energy generation to encompass the production of valuable carboxylic acids, especially volatile fatty acids (VFAs) like acetic acid, propionic acid, and butyric acid. VFAs hold great potential for various industries and biobased applications due to their versatile properties. Despite increasing global demand, over 90% of VFAs are currently produced synthetically from petrochemicals. Realizing the potential of large-scale biobased VFA production from waste streams offers significant eco-friendly opportunities but comes with several key challenges. These include low VFA production yields, unstable acid compositions, complex and expensive purification methods, and post-processing needs. Among these, production yield and acid composition stand out as the most critical obstacles impacting economic viability and competitiveness. This paper seeks to offer a comprehensive view of combining complementary modeling approaches, including kinetic and microbial modeling, to understand the workings of microbial communities and metabolic pathways in VFA production, enhance production efficiency, and regulate acid profiles through the integration of omics and bioreactor data.

Unveiling the regulatory mechanism of poly-γ-glutamic acid on soil characteristics under drought stress through integrated metagenomics and metabolomics analysis

It is of utmost importance to understand the characteristics and regulatory mechanisms of soil in order to optimize soil management and enhance crop yield. Poly-γ-glutamic acid (γ-PGA), a stress-resistant amino acid polymer, plays a crucial role in plant drought stress resistance. However, little is known about the effects of γ-PGA on soil characteristics during drought treatments. In this study, the effects of different forms of γ-PGA on soil texture and basic physical and chemical properties under short-term drought conditions were investigated. Furthermore, the impact of γ-PGA on the microbial community and metabolic function of maize was analyzed. Under drought conditions, the introduction of γ-PGA into the soil resulted in notable improvements in the mechanical composition ratio and infiltration capacity of the soil. Concurrently, this led to a reduction in soil bulk density and improved soil organic matter content and fertility. Additionally, metagenomic analysis revealed that under drought conditions, the incorporation of γ-PGA into the soil enhanced the soil microbiota structure. This shift led to the predominance of bacteria that are crucial for carbon, nitrogen, and phosphorus cycles in the soil. Metabolomics analysis revealed that under drought treatment, γ-PGA affected soil metabolic patterns, with a particular focus on alterations in amino acid and vitamin metabolism pathways. Correlation analysis between the soil metagenome and metabolites showed that microorganisms played a significant role in metabolite accumulation. These results demonstrated that γ-PGA could improve soil characteristics under drought conditions and play an important role in soil microorganisms and microbial metabolism, providing further insights into the changes in soil characteristics under drought conditions.

Recent advances in plant translational genomics for crop improvement

The growing population, climate change, and limited agricultural resources put enormous pressure on agricultural systems. A plateau in crop yields is occurring and extreme weather events and urbanization threaten the livelihood of farmers. It is imperative that immediate attention is paid to addressing the increasing food demand, ensuring resilience against emerging threats, and meeting the demand for more nutritious, safer food. Under uncertain conditions, it is essential to expand genetic diversity and discover novel crop varieties or variations to develop higher and more stable yields. Genomics plays a significant role in developing abundant and nutrient-dense food crops. An alternative to traditional breeding approach, translational genomics is able to improve breeding programs in a more efficient and precise manner by translating genomic concepts into practical tools. Crop breeding based on genomics offers potential solutions to overcome the limitations of conventional breeding methods, including improved crop varieties that provide more nutritional value and are protected from biotic and abiotic stresses. Genetic markers, such as SNPs and ESTs, contribute to the discovery of QTLs controlling agronomic traits and stress tolerance. In order to meet the growing demand for food, there is a need to incorporate QTLs into breeding programs using marker-assisted selection/breeding and transgenic technologies. This chapter primarily focuses on the recent advances that are made in translational genomics for crop improvement and various omics techniques including transcriptomics, metagenomics, pangenomics, single cell omics etc. Numerous genome editing techniques including CRISPR Cas technology and their applications in crop improvement had been discussed.

Unveiling the Gut Microbiome: How Junk Food Impacts the Gut

The human gut microbiome, a complex community of microorganisms, profoundly influences human health and disease. Bacteroidetes and Firmicutes make up the majority of the normal human gut microbiota. These microorganisms wield considerable influence over our physiological functions, impacting both our well-being and our susceptibility to disease. The surge of interest in the gut microbiome over the past decade has been remarkable. Once overlooked, the gastrointestinal tract's microbiota has gained recognition for its significance in maintaining optimal health. The food industry has capitalized on this, flooding the market with "probiotic" and "fermented" products. This article aims to provide a critical review of the current literature on the gut microbiome and its significance in human health, with a particular focus on the impact of dietary choices, especially junk food, on the composition and function of the gut microbiota. Microbes possess the remarkable ability to unlock nutrients from otherwise indigestible substances. The gut microbiome of individuals who consume healthy foods and those who prefer junk food varies significantly. Healthy diets promote a diverse and beneficial gut microbiome, while junk food consumption often leads to a less diverse microbiome with negative consequences for health.

Study of chemical constituents, antioxidants and antimicrobial activities of Tamarindus indica L. seed

The fruits of Tamarindus indica L. are consumed worldwide, with various parts of the plant being used for medicinal purposes. The residues (pericarp and seeds) generated during cellulose processing are of significant value as they contain bioactive compounds with diverse biological activities. The objective of this study was to evaluate the chemical constituents of the ethyl acetate fraction as possible substitutes for synthetic compounds with biological properties using ultra-high performance liquid chromatography coupled to high-resolution mass spectrometry (UHPLC-HRMS/MS) analysis and the evaluation of the antioxidant activity (ferric reducing antioxidant power [FRAP], 2,2'-azino-bis-3-ethylbenzthiazoline-6-sulphonic acid [ABTS], and 1-diphenyl-2-picrylhydrazyl [DPPH]), total phenolic compounds (TPC), and antimicrobial activity of the hydroalcoholic extract and tamarind seed fractions were also performed. The chemical investigation of the acetate fraction using UHPLC-HRMS/MS resulted in the putative identification of 14 compounds, including flavonoids, (+)-catechin/(-)-epicatechin, procyanidin B2, procyanidin C2, isoquercetin, quercetin, luteolin, rutin, taxifolin, eriodictyol, kaempferide, hydroxybenzoic acid, protocathecuic acid, and protocathecuic acid methyl and ethyl esters derivatives. The crude hydroalcoholic extract exhibited the best results in terms of TPC: 883.87 gallic acid equivalent (GAE; mg/g) and antioxidant activity: FRAP: 183.29 GAE (mg/g), ABTS: 39.67%, and DPPH: 91.08%. The extract exhibited excellent antibacterial activity against gram-positive bacteria, specifically Staphylococcus aureus minimum inhibitory concentration (MIC)/minimum bactericidal concentration (MBC; 62.5/125 g/mL) and Bacillus cereus MIC/MBC (125/250 g/mL), and gram-negative bacteria, specifically Aeromonas hydrophila MIC/MBC (125/250 µg/mL) and Pseudomonas aeruginosa MIC/MBC (250/500 g/mL). Morphological damage to cells was observed using flow cytometry and scanning electron microscopy. Tamarind seeds contain unique bioactive compounds that should be explored for their use as novel food preservatives. PRACTICAL APPLICATION: Original data were obtained regarding the Tamarindus indica L. seed extract and the ethyl acetate and hexane fractions. This research aimed to investigate the potential of these for food preservation and as alternatives to additives and synthetic compounds added to cattle feed. This paper reports novel findings regarding the chemical composition of the extract and its antioxidant activity, along with its antimicrobial activity against bacteria (gram-positive: Staphylococcus aureus, Bacillus cereus, and gram-negative: Salmonella enterica serovar Enteritidis, Escherichia coli, Pseudomonas aeruginosa, and Aeromonas hydrophila) and yeasts (Candida albicans and Saccharomyces cerevisiae).

Metabolomic Differences between Viable but Nonculturable and Recovered Lacticaseibacillus paracasei Zhang

The fermentation process can be affected when the starter culture enters the viable but nonculturable (VBNC) state. Therefore, it is of interest to investigate how VBNC cells change physiologically. Lacticaseibacillus (L.) paracasei Zhang is both a probiotic and a starter strain. This study aimed to investigate the metabolomic differences between VBNC and recovered L. paracasei Zhang cells. First, L. paracasei Zhang was induced to enter the VBNC state by keeping the cells in a liquid de Man-Rogosa-Sharpe (MRS) medium at 4 °C for 220 days. Flow cytometry was used to sort the induced VBNC cells, and three different types of culture media (MRS medium, skim milk with 1% yeast extract, and skim milk) were used for cell resuscitation. Cell growth responses in the three types of recovery media suggested that the liquid MRS medium was the most effective in reversing the VBNC state in L. paracasei Zhang. Metabolomics analysis revealed 25 differential metabolites from five main metabolite classes (amino acid, carbohydrate, lipid, vitamin, and purine and pyrimidine). The levels of L-cysteine, L-alanine, L-lysine, and L-arginine notably increased in the revived cells, while cellulose, alginose, and guanine significantly decreased. This study confirmed that VBNC cells had an altered physiology.

New Approach for the Identification of Isobaric and Isomeric Metabolites

The structural elucidation of metabolite molecules is important in many branches of the life sciences. However, the isomeric and isobaric complexity of metabolites makes their identification extremely challenging, and analytical standards are often required to confirm the presence of a particular compound in a sample. We present here an approach to overcome these challenges using high-resolution ion mobility spectrometry in combination with cryogenic vibrational spectroscopy for the rapid separation and identification of metabolite isomers and isobars. Ion mobility can separate isomeric metabolites in tens of milliseconds, and cryogenic IR spectroscopy provides highly structured IR fingerprints for unambiguous molecular identification. Moreover, our approach allows one to identify metabolite isomers automatically by comparing their IR fingerprints with those previously recorded in a database, obviating the need for a recurrent introduction of analytical standards. We demonstrate the principle of this approach by constructing a database composed of IR fingerprints of eight isomeric/isobaric metabolites and use it for the identification of these isomers present in mixtures. Moreover, we show how our fast IR fingerprinting technology allows to probe the IR fingerprints of molecules within just a few seconds as they elute from an LC column. This approach has the potential to greatly improve metabolomics workflows in terms of accuracy, speed, and cost.

Modulators of a robust and efficient metabolism: Perspective and insights from the Rid superfamily of proteins

Metabolism is an integrated network of biochemical pathways that assemble to generate the robust, responsive physiologies of microorganisms. Despite decades of fundamental studies on metabolic processes and pathways, our understanding of the nuance and complexity of metabolism remains incomplete. The ability to predict and model metabolic network structure, and its influence on cellular fitness, is complicated by the persistence of genes of unknown function, even in the best-studied model organisms. This review describes the definition and continuing study of the Rid superfamily of proteins. These studies are presented with a perspective that illustrates how metabolic complexity can complicate the assignment of function to uncharacterized genes. The Rid superfamily of proteins has been divided into eight subfamilies, including the well-studied RidA subfamily. Aside from the RidA proteins, which are present in all domains of life and prevent metabolic stress, most members of the Rid superfamily have no demonstrated physiological role. Recent progress on functional assignment supports the hypothesis that, overall, proteins in the Rid superfamily modulate metabolic processes to ensure optimal organismal fitness.

Current Limitations of Staph Infection Diagnostics, and the Role for VOCs in Achieving Culture-Independent Detection

Staphylococci are broadly adaptable and their ability to grow in unique environments has been widely established, but the most common and clinically relevant staphylococcal niche is the skin and mucous membranes of mammals and birds. S. aureus causes severe infections in mammalian tissues and organs, with high morbidities, mortalities, and treatment costs. S. epidermidis is an important human commensal but is also capable of deadly infections. Gold-standard diagnostic methods for staph infections currently rely upon retrieval and characterization of the infectious agent through various culture-based methods. Yet, obtaining a viable bacterial sample for in vitro identification of infection etiology remains a significant barrier in clinical diagnostics. The development of volatile organic compound (VOC) profiles for the detection and identification of pathogens is an area of intensive research, with significant efforts toward establishing breath tests for infections. This review describes the limitations of existing infection diagnostics, reviews the principles and advantages of VOC-based diagnostics, summarizes the analytical tools for VOC discovery and clinical detection, and highlights examples of how VOC biomarkers have been applied to diagnosing human and animal staph infections.

Comparison of freeze-thaw and sonication cycle-based methods for extracting AMR-associated metabolites from Staphylococcus aureus

Emerging antimicrobial resistance (AMR) among Gram-positive pathogens, specifically in Staphylococcus aureus (S. aureus), is becoming a leading public health concern demanding effective therapeutics. Metabolite modulation can improve the efficacy of existing antibiotics and facilitate the development of effective therapeutics. However, it remained unexplored for drug-resistant S. aureus (gentamicin and methicillin-resistant), primarily due to the dearth of optimal metabolite extraction protocols including a protocol for AMR-associated metabolites. Therefore, in this investigation, we have compared the performance of the two most widely used methods, i.e., freeze-thaw cycle (FTC) and sonication cycle (SC), alone and in combination (FTC + SC), and identified the optimal method for this purpose. A total of 116, 119, and 99 metabolites were identified using the FTC, SC, and FTC + SC methods, respectively, leading to the identification of 163 metabolites cumulatively. Out of 163, 69 metabolites were found to be associated with AMR in published literature consisting of the highest number of metabolites identified by FTC (57) followed by SC (54) and FTC + SC (40). Thus, the performances of FTC and SC methods were comparable with no additional benefits of combining both. Moreover, each method showed biasness toward specific metabolite(s) or class of metabolites, suggesting that the choice of metabolite extraction method shall be decided based on the metabolites of interest in the investigation.

Hyperglycemia and cancer in human lung carcinoma by means of Raman spectroscopy and imaging

Raman spectroscopy and Raman imaging were used to identify the biochemical and structural features of human cancer lung cells (CCL-185) and the cancer cells supplemented with glucose and deuterated glucose at normal and hyperglycemia conditions. We found that isotope substitution of glucose by deuterated glucose allows to separate de novo lipid synthesis from exogenous uptake of lipids obtained from the diet. We demonstrated that glucose is largely utilized for de novo lipid synthesis. Our results provide a direct evidence that high level of glucose decreases the metabolism via oxidative phosphorylation in mitochondria in cancer cells and shifts the metabolism to glycolysis via Warburg effect. It suggests that hyperglycemia is a factor that may contribute to a more malignant phenotype of cancer cells by inhibition of oxidative phosphorylation and apoptosis.

Metabolomic insight into the synergistic mechanism of action of a bacterial consortium in plant growth promotion

It has been established that a consortium consisting of compatible plant growth promoting rhizobacterial strains outperforms their individual impacts on plant attributes. While the phenomenon of synergism is extensively reported, the mechanism that underpins it is yet to be elucidated. In the present study the impact of three plant growth promoting bacteria, Azotobacter chroococcum (A), Priestia megaterium (formerly Bacillus megaterium) (B), and Pseudomonas sp. SK3 (P) was studied as a consortium on the growth attributes of pigeonpea. In addition, microbe-microbe interactions were investigated through metabolomic profiling to understand the mechanism of synergism. Plant growth experiments revealed that bacterial consortium A + B + P showed a significant increase in plant attributes such as shoot length, root length, fresh weight, and dry weight as compared to monocultures and two-membered consortia. Metabolomic profiling through high resolution liquid chromatograph mass spectrometer revealed the presence of a few bioactive compounds in the consortium that might play a potential role in the enhancement of biometric parameters of the plant. Several compounds, such as antipyrine, 6,6-dimethoxy-2,5,5-trimethyl-2-hexene, N-methyltryptamine, 2,2-dimethyl-3,4-bis(4-methoxyphenyl)-2H-1-benzopyran-7-ol acetate, N6-hydroxy-l-lysine, and l-furosin, were detected in the metabolome of the consortium, which was unique among all the treatments. The study also detected a few metabolites involved in sphingolipid biosynthesis (ketosphinganine and sphinganine) known for cell signaling in the consortium. This unravels the possible mechanism of synergism between bacterial strains in a consortium. The metabolomic profile would be helpful to strategically develop unique and more effective consortia that are tailored to the soil type.

Application of Metabolomics in Fungal Research

Metabolomics is an essential method to study the dynamic changes of metabolic networks and products using modern analytical techniques, as well as reveal the life phenomena and their inherent laws. Currently, more and more attention has been paid to the development of metabolic histochemistry in the fungus field. This paper reviews the application of metabolomics in fungal research from five aspects: identification, response to stress, metabolite discovery, metabolism engineering, and fungal interactions with plants.

Metabolomics-Driven Exploration of the Antibacterial Activity and Mechanism of 2-Methoxycinnamaldehyde

Methicillin-resistant Staphylococcus epidermidis (MRSE) is one of the most commonly found pathogens that may cause uncontrollable infections in immunocompromised and hospitalized patients. Compounds isolated from cinnamon such as cinnamaldehyde and cinnamic acid showed promising anti-oxidant, anti-tumor, and immunoregulatory effects; more importantly, these compounds also possess promising broad-spectrum antibacterial activity. In this study, the potential antibacterial activity of 2-methoxycinnamaldehyde (MCA), another compound in cinnamon, against MRSE was investigated. Combining the broth microdilution test, live/dead assay, and biofilm formation assay, we found MCA was able to inhibit the proliferation, as well as the biofilm formation of MRSE, indicating MCA could not only affect the growth of MRSE but also inhibit the pathogenic potential of this bacterium. Additionally, the results of scanning electron microscopy (SEM) and transmission electron microscopy (TEM) demonstrated that MCA caused morphological changes and the leakage of DNA, RNA, and cellular contents of MRSE. Due to the close relationship between cell wall synthesis, ROS formation, and cell metabolism, the ROS level and metabolic profile of MRSE were explored. Our study showed MCA significantly increased the ROS production in MRSE, and the following metabolomics analysis showed that the increased ROS production may partially be due to the increased metabolic flux through the TCA cycle. In addition, we noticed the metabolic flux through the pentose phosphate pathway (PPP) was upregulated accompanied by elevated ROS production. Therefore, the alterations in cell metabolism and increased ROS production could lead to the damage of the cell wall, which in turn decreased the proliferation of MRSE. In conclusion, MCA seemed to be a promising alternative antimicrobial agent to control MRSE infections.

Apex Predator Nematodes and Meso-Predator Bacteria Consume Their Basal Insect Prey through Discrete Stages of Chemical Transformations

Microbial symbiosis drives physiological processes of higher-order systems, including the acquisition and consumption of nutrients that support symbiotic partner reproduction. Metabolic analytics provide new avenues to examine how chemical ecology, or the conversion of existing biomass to new forms, changes over a symbiotic life cycle. We applied these approaches to the nematode Steinernema carpocapsae, its mutualist bacterium, Xenorhabdus nematophila, and the insects they infect. The nematode-bacterium pair infects, kills, and reproduces in an insect until nutrients are depleted. To understand the conversion of insect biomass over time into either nematode or bacterium biomass, we integrated information from trophic, metabolomic, and gene regulation analyses. Trophic analysis established bacteria as meso-predators and primary insect consumers. Nematodes hold a trophic position of 4.6, indicative of an apex predator, consuming bacteria and likely other nematodes. Metabolic changes associated with Galleria mellonella insect bioconversion were assessed using multivariate statistical analyses of metabolomics data sets derived from sampling over an infection time course. Statistically significant, discrete phases were detected, indicating the insect chemical environment changes reproducibly during bioconversion. A novel hierarchical clustering method was designed to probe molecular abundance fluctuation patterns over time, revealing distinct metabolite clusters that exhibit similar abundance shifts across the time course. Composite data suggest bacterial tryptophan and nematode kynurenine pathways are coordinated for reciprocal exchange of tryptophan and NAD⁺ and for synthesis of intermediates that can have complex effects on bacterial phenotypes and nematode behaviors. Our analysis of pathways and metabolites reveals the chemistry underlying the recycling of organic material during carnivory. IMPORTANCE The processes by which organic life is consumed and reborn in a complex ecosystem were investigated through a multiomics approach applied to the tripartite Xenorhabdus bacterium-Steinernema nematode-Galleria insect symbiosis. Trophic analyses demonstrate the primary consumers of the insect are the bacteria, and the nematode in turn consumes the bacteria. This suggests the Steinernema-Xenorhabdus mutualism is a form of agriculture in which the nematode cultivates the bacterial food sources by inoculating them into insect hosts. Metabolomics analysis revealed a shift in biological material throughout progression of the life cycle: active infection, insect death, and conversion of cadaver tissues into bacterial biomass and nematode tissue. We show that each phase of the life cycle is metabolically distinct, with significant differences including those in the tricarboxylic acid cycle and amino acid pathways. Our findings demonstrate that symbiotic life cycles can be defined by reproducible stage-specific chemical signatures, enhancing our broad understanding of metabolic processes that underpin a three-way symbiosis.

Exometabolomic Analysis of Susceptible and Multi-Drug Resistant Pseudomonas aeruginosa

Multidrug resistant (MDR) Pseudomonas aeruginosa strains have recently become one of the major public health concerns worldwide leading to difficulties in selecting appropriate antibiotic treatment. Thus, it is important to elucidate the characteristics of MDR isolates. Herein, we aimed to determine the unique exometabolome profile of P. aeruginosa clinical isolates in monocultures that comprise high resistance to multiple antibiotics, and compare the differential metabolite profiles obtained from susceptible isolates by using GC/MS. Our results showed that partial least square-discriminant analysis (PLS-DA) score plot clearly discriminated the MDR and susceptible isolates indicating the altered exometabolite profiles, and highlighted the significantly enriched levels of trehalose and glutamic acid in MDR isolates. Expression of trehalose synthase (treS) was also 1.5 fold higher in MDR isolates, relatively to susceptible isolates. Overall, our study provides insights into the distinct footprints of MDR P. aeruginosa isolates in mono-culture.

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.

Synergistic antibacterial combination of Sapindoside A and B changes the fatty acid compositions and membrane properties of Cutibacterium acnes

Sapindus saponins extracted from S. mukorossi have been reported to exert antibacterial activities against skin pathogenic bacteria, but their antibacterial mechanism is still at an exploratory stage. The objective of this study was to explore the synergistic antibacterial mechanism of the combination of two Sapindus saponins, namely Sapindoside A and B (SAB) against Cutibacterium acnes (C. acnes) 6919 via targeting the fatty acid compositions and membrane properties. After exposure to SAB, C. acnes cells increased the cell surface hydrophobicity and reduced the cell membrane fluidity by changing the composition of membrane fatty acids. In the fatty acid compositions, the content of two main fatty acids 12-methyl-tetradecanoic acid (isoC15:0) and octadecanoic acid (C18:0) reduced and improved respectively with the addition of SAB, and fatty acid biosynthesis-related genes were significantly down-regulated (p < 0.05). Further, molecular docking demonstrated that SAB interacted with FabD, which is an essential enzyme for bacterial type II fatty acid synthesis, via hydrogen bonds and hydrophobic interactions. In the above results, the contribution of SA to SAB was greater than that of SB. In summary, the results revealed that SAB changed the fatty acid compositions of C. acnes, further disrupting the cell membrane properties, and SA played a major role, suggesting that SAB could be a natural antiacne additive against C. acnes-associated infections.

Different Wines from Different Yeasts? "Saccharomyces cerevisiae Intraspecies Differentiation by Metabolomic Signature and Sensory Patterns in Wine"

Alcoholic fermentation is known to be a key stage in the winemaking process that directly impacts the composition and quality of the final product. Twelve wines were obtained from fermentations of Chardonnay must made with twelve different commercial wine yeast strains of Saccharomyces cerevisiae. In our study, FT-ICR-MS, GC-MS, and sensory analysis were combined with multivariate analysis. Ultra-high-resolution mass spectrometry (uHRMS) was able to highlight hundreds of metabolites specific to each strain from the same species, although they are characterized by the same technological performances. Furthermore, the significant involvement of nitrogen metabolism in this differentiation was considered. The modulation of primary metabolism was also noted at the volatilome and sensory levels. Sensory analysis allowed us to classify wines into three groups based on descriptors associated with white wine. Thirty-five of the volatile compounds analyzed, including esters, medium-chain fatty acids, superior alcohols, and terpenes discriminate and give details about differences between wines. Therefore, phenotypic differences within the same species revealed metabolic differences that resulted in the diversity of the volatile fraction that participates in the palette of the sensory pattern. This original combination of metabolomics with the volatilome and sensory approaches provides an integrative vision of the characteristics of a given strain. Metabolomics shine the new light on intraspecific discrimination in the Saccharomyces cerevisiae species.

Metabolomics Data Treatment: Basic Directions of the Full Process

The present chapter describes basic aspects of the main steps for data processing on mass spectrometry-based metabolomics platforms, focusing on the main objectives and important considerations of each step. Initially, an overview of metabolomics and the pivotal techniques applied in the field are presented. Important features of data acquisition and preprocessing such as data compression, noise filtering, and baseline correction are revised focusing on practical aspects. Peak detection, deconvolution, and alignment as well as missing values are also discussed. Special attention is given to chemical and mathematical normalization approaches and the role of the quality control (QC) samples. Methods for uni- and multivariate statistical analysis and data pretreatment that could impact them are reviewed, emphasizing the most widely used multivariate methods, i.e., principal components analysis (PCA), partial least squares-discriminant analysis (PLS-DA), orthogonal partial least square-discriminant analysis (OPLS-DA), and hierarchical cluster analysis (HCA). Criteria for model validation and softwares used in data processing were also approached. The chapter ends with some concerns about the minimal requirements to report metadata in metabolomics.

Toxicometabolomics: Small Molecules to Answer Big Toxicological Questions

Given the high biological impact of classical and emerging toxicants, a sensitive and comprehensive assessment of the hazards and risks of these substances to organisms is urgently needed. In this sense, toxicometabolomics emerged as a new and growing field in life sciences, which use metabolomics to provide new sets of susceptibility, exposure, and/or effects biomarkers; and to characterize in detail the metabolic responses and altered biological pathways that various stressful stimuli cause in many organisms. The present review focuses on the analytical platforms and the typical workflow employed in toxicometabolomic studies, and gives an overview of recent exploratory research that applied metabolomics in various areas of toxicology.

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.

The oral microbiome: Role of key organisms and complex networks in oral health and disease

States of oral health and disease reflect the compositional and functional capacities of, as well as the interspecies interactions within, the oral microbiota. The oral cavity exists as a highly dynamic microbial environment that harbors many distinct substrata and microenvironments that house diverse microbial communities. Specific to the oral cavity, the nonshedding dental surfaces facilitate the development of highly complex polymicrobial biofilm communities, characterized not only by the distinct microbes comprising them, but cumulatively by their activities. Adding to this complexity, the oral cavity faces near-constant environmental challenges, including those from host diet, salivary flow, masticatory forces, and introduction of exogenous microbes. The composition of the oral microbiome is shaped throughout life by factors including host genetics, maternal transmission, as well as environmental factors, such as dietary habits, oral hygiene practice, medications, and systemic factors. This dynamic ecosystem presents opportunities for oral microbial dysbiosis and the development of dental and periodontal diseases. The application of both in vitro and culture-independent approaches has broadened the mechanistic understandings of complex polymicrobial communities within the oral cavity, as well as the environmental, local, and systemic underpinnings that influence the dynamics of the oral microbiome. Here, we review the present knowledge and current understanding of microbial communities within the oral cavity and the influences and challenges upon this system that encourage homeostasis or provoke microbiome perturbation, and thus contribute to states of oral health or disease.

Identification of bacteria in the tracheal swabs of farmed ostriches and their effect on the viability of influenza A virus

Avian influenza surveillance is a requirement for commercial trade in ostrich products, but influenza A viruses (IAVs) have proven difficult to isolate from ostrich tracheal swabs that test positive using molecular methods. We hypothesized that microbes unique to the ostrich trachea propagate in the transport medium after sampling and affect viral viability. We cultured tracheal swabs from 50 ostriches on 4 farms in South Africa, and recovered and identified 13 bacterial, 1 yeast, and 2 fungal species. Dietzia sp. had not been identified previously in the oropharyngeal tract of a bird, to our knowledge. The bacteria were tested for antimicrobial susceptibility, and most aerobic species, except for Streptococcus sp. and Pseudomonas sp., were sensitive to enrofloxacin; all were susceptible to sulfonamide. Virus inhibition experiments determined that ostrich-source Streptococcus sp., Pantoea sp., and Citrobacter freundii produced extracellular metabolites that caused a substantial reduction in the IAV titers of 99.9%. Streptomyces, Corynebacterium, Staphylococcus, Arthrobacter gandavensis, Pseudomonas putida, and Acinetobacter spp. similarly reduced the viability of IAV from 77.6% to 24.1%. Dietzia appeared to have no effect, but Rothia dentocariosa, Rhodotorula spp., and Clostridium spp. slightly increased the viability of IAV by 25.9, 34.9, and 58.5%, respectively.

Influence of Supplementation of Lactoferrin, Melittin and Cecropin A to Rat Diet on Changes in Faecal Ammonia Concentrations, Short-Chain Fatty Acid Concentrations and Activities of Bacterial Enzymes

Simple Summary

In the present study conducted on Wistar laboratory rats, the effects of two selected insect antimicrobial peptides (AMPs), melittin and cecropin A, were investigated and compared to those attributed to well-known antibacterial action of lactoferrin. It was hypothesised that the dietary presence of lactoferrin, melittin or cecropin A strongly affects the rat large gut microbial activity at the time of protein/peptide administration and the durability of the effects may differ after their withdrawal from a diet. The experiment was conducted on living animals (without their euthanasia) and the dynamics of changes in pH, microbial enzyme activity, ammonia and short-chain fatty acids concentrations were investigated in the faeces during and after the dietary treatments with lactoferrin, melittin or cecropin A. The results suggested that the faecal intensity of microbial fermentation processes in rats was quickly reduced upon dietary addition of two AMPs and lactoferrin after two days of treatment, on average. The strongest suppression effect was observed on the 5th day of treatment and persisted on days 5–8. The changes caused by the supplemented lactoferrin and AMPs were reversible after 15 days, i.e., 10 days after the withdrawal of lactoferrin, melittin and cecropin A from the diet.

Abstract

We hypothesised that the dietary addition of the bioactive antimicrobial protein lactoferrin (LF) and peptides melittin (MT) or cecropin A (CR) at a dosage of 100 mg/kg to the diet of Wistar rats would result in strong modulatory effects on faecal microbial enzymatic activity, short-chain fatty acid and ammonia concentrations. To date, the changes in bacterial extracellular and intracellular enzymatic activities upon addition of dietary AMPs have not yet been studied. This experiment lasted 15 days; during the first 5 day period, the rats were fed the control diet (S) and diets supplemented with LF, MT or CR. On days 6–15, all rats were fed the control S diet. The faecal fermentation processes were substantially stopped after two days of treatment, on average, in all rats receiving LF and two AMPs. The deepest suppression effect was observed on the last day of treatment (day 5) and persisted through days 5–8. The highest decreases in faecal bacterial β-glucosidase and β-glucuronidase activities as well as in SCFA and ammonia concentrations were observed in the rats fed the CR diet. Only in the CR animals did the mechanism of suppressed microbial fermentation involve diminished enzyme release from bacterial cells to the digesta.

Infrared MALDI Mass Spectrometry with Laser-Induced Postionization for Imaging of Bacterial Colonies

Ultraviolet matrix-assisted laser desorption ionization mass spectrometry imaging (UV-MALDI-MSI) is a powerful tool to visualize bacterial metabolites in microbial colonies and in biofilms. However, a challenge for the method is the efficient extraction of analytes from deeper within the bacterial colonies and from the cytoplasm of individual cells during the matrix coating step. Here, we used a pulsed infrared (IR) laser of 2.94 μm wavelength to disrupt and ablate bacterial cells without a prior coating with a MALDI matrix. Instead, tissue water or, in some experiments, in addition a small amount of glycerol was exploited for the deposition of the IR laser energy and for supporting the ionization of the analytes. Compared to water, glycerol exhibits a lower vapor pressure, which prolonged the available measurement time window within an MSI experiment. Mass spectra were acquired with a hybrid Synapt G2-S HDMS instrument at a pixel size of 120 μm. A frequency-quadrupled q-switched Nd:YAG laser with 266 nm wavelength served for laser-induced postionization (MALDI-2). In this way, the ion abundances of numerous small molecules such as nucleobases, 2-alkyl-quinolones, a prominent class of Pseudomonas aeruginosa signaling molecules involved in one of the three quorum-sensing pathways, and also the signals of various bacterial phospholipids were boosted, partially by orders of magnitude. We analyzed single and cocultured colonies of Gram-negative P. aeruginosa and of Gram-positive Bacillus subtilis and Staphylococcus aureus as exemplary bacterial systems. To enable a rapid (within 5 s) MSI-compatible steam inactivation in a custom-made autoclave filled with hot water steam, bacterial cultures were grown on porous polyamide membranes. Compared to a UV-MALDI-2-MS measurement of the same systems, mass spectra with a reduced low mass background were generally generated. This resulted in the unequivocal detection of numerous metabolites only with the IR laser. In a fundamental part of our study, and to optimize the IR-MALDI-2 approach for the highest analytical sensitivity, we characterized the expansion dynamics of the particle plume as generated by the IR laser. Here, we recorded the total ion count and the intensities of selected signals registered from P. aeruginosa samples as a function of the interlaser delay and buffer gas pressure in the ion source. The data revealed that the IR-MALDI-2 ion signals are primarily generated from slow particles having mean velocities of ∼10 m/s. Interestingly, two different pressure/delay time regimes of the optimized ionization efficiency for phospholipids and smaller metabolites, respectively, were revealed, a result pointing to yet-unknown convoluted reaction cascades. The described IR-MALDI-2 method could be a helpful new tool for a microbial mass spectrometry imaging of small molecules requiring little sample preparation.

Network analyses in microbiome based on high-throughput multi-omics data

Together with various hosts and environments, ubiquitous microbes interact closely with each other forming an intertwined system or community. Of interest, shifts of the relationships between microbes and their hosts or environments are associated with critical diseases and ecological changes. While advances in high-throughput Omics technologies offer a great opportunity for understanding the structures and functions of microbiome, it is still challenging to analyse and interpret the omics data. Specifically, the heterogeneity and diversity of microbial communities, compounded with the large size of the datasets, impose a tremendous challenge to mechanistically elucidate the complex communities. Fortunately, network analyses provide an efficient way to tackle this problem, and several network approaches have been proposed to improve this understanding recently. Here, we systemically illustrate these network theories that have been used in biological and biomedical research. Then, we review existing network modelling methods of microbial studies at multiple layers from metagenomics to metabolomics and further to multi-omics. Lastly, we discuss the limitations of present studies and provide a perspective for further directions in support of the understanding of microbial communities.

Reflections on the Use of an Invertebrate Chordate Model System for Studies of Gut Microbial Immune Interactions

The functional ecology of the gastrointestinal tract impacts host physiology, and its dysregulation is at the center of various diseases. The immune system, and specifically innate immunity, plays a fundamental role in modulating the interface of host and microbes in the gut. While humans remain a primary focus of research in this field, the use of diverse model systems help inform us of the fundamental principles legislating homeostasis in the gut. Invertebrates, which lack vertebrate-style adaptive immunity, can help define conserved features of innate immunity that shape the gut ecosystem. In this context, we previously proposed the use of a marine invertebrate, the protochordate Ciona robusta, as a novel tractable model system for studies of host-microbiome interactions. Significant progress, reviewed herein, has been made to fulfill that vision. We examine and review discoveries from Ciona that include roles for a secreted immune effector interacting with elements of the microbiota, as well as chitin-rich mucus lining the gut epithelium, the gut-associated microbiome of adults, and the establishment of a large catalog of cultured isolates with which juveniles can be colonized. Also discussed is the establishment of methods to rear the animals germ-free, an essential technology for dissecting the symbiotic interactions at play. As the foundation is now set to extend these studies into the future, broadening our comprehension of how host effectors shape the ecology of these microbial communities in ways that establish and maintain homeostasis will require full utilization of "multi-omics" approaches to merge computational sciences, modeling, and experimental biology in hypothesis-driven investigations.

Omics-Driven Biotechnology for Industrial Applications

Biomanufacturing is a key component of biotechnology that uses biological systems to produce bioproducts of commercial relevance, which are of great interest to the energy, material, pharmaceutical, food, and agriculture industries. Biotechnology-based approaches, such as synthetic biology and metabolic engineering are heavily reliant on "omics" driven systems biology to characterize and understand metabolic networks. Knowledge gained from systems biology experiments aid the development of synthetic biology tools and the advancement of metabolic engineering studies toward establishing robust industrial biomanufacturing platforms. In this review, we discuss recent advances in "omics" technologies, compare the pros and cons of the different "omics" technologies, and discuss the necessary requirements for carrying out multi-omics experiments. We highlight the influence of "omics" technologies on the production of biofuels and bioproducts by metabolic engineering. Finally, we discuss the application of "omics" technologies to agricultural and food biotechnology, and review the impact of "omics" on current COVID-19 research.

Metabolomic analysis of Trichophyton rubrum and Microsporum canis during keratin degradation

Keratin is important and needed for the growth of dermatophytes in the host tissue. In turn, the ability to invade keratinised tissues is defined as a pivotal virulence attribute of this group of medically important fungi. The host–dermatophyte interaction is accompanied by an adaptation of fungal metabolism that allows them to adhere to the host tissue as well as utilize the available nutrients necessary for their survival and growth. Dermatophyte infections pose a significant epidemiological and clinical problem. Trichophyton rubrum is the most common anthropophilic dermatophyte worldwide and its typical infection areas include skin of hands or feet and nail plate. In turn, Microsporum canis is a zoophilic pathogen, and mostly well known for ringworm in pets, it is also known to infect humans. The aim of the study was to compare the intracellular metabolite content in the T. rubrum and M. canis during keratin degradation using liquid chromatography system coupled with tandem mass spectrometer (LC-MS/MS). The metabolite “fingerprints” revealed compounds associated with amino acids metabolism, carbohydrate metabolism related to the glycolysis and the tricarboxylic acid cycle (TCA), as well as nucleotide and energy metabolism. The metabolites such as kynurenic acid, l-alanine and cysteine in case of T. rubrum as well as cysteine and riboflavin in case of M. canis were detected only during keratin degradation what may suggest that these compounds may play a key role in the interactions of T. rubrum and M. canis with the host tissue. The metabolomic results were completed by qPCR gene expression assay. Our findings suggest that metabolomic analysis of T. rubrum and M. canis growing in culture media that mimic the dermatophyte infection could allow the understanding of processes involved in the pathogenesis of dermatophytes.

Microbiota as Drivers and as Therapeutic Targets in Ocular and Tissue Specific Autoimmunity

Autoimmune uveitis is a major cause of blindness in humans. Activation of retina-specific autoreactive T cells by commensal microbiota has been shown to trigger uveitis in mice. Although a culprit microbe and/or its immunogenic antigen remains to be identified, studies from inducible and spontaneous mouse models suggest the potential of microbiota-modulating therapies for treating ocular autoimmune disease. In this review, we summarize recent findings on the contribution of microbiota to T cell-driven, tissue-specific autoimmunity, with an emphasis on autoimmune uveitis, and analyze microbiota-altering interventions, including antibiotics, probiotics, and microbiota-derived metabolites (e.g., short-chain fatty acids), which have been shown to be effective in other autoimmune diseases. We also discuss the need to explore more translational animal models as well as to integrate various datasets (microbiomic, transcriptomic, proteomic, metabolomic, and other cellular measurements) to gain a better understanding of how microbiota can directly or indirectly modulate the immune system and contribute to the onset of disease. It is hoped that deeper understanding of these interactions may lead to more effective treatment interventions.

Effect of diet and intestinal AhR expression on fecal microbiome and metabolomic profiles

BACKGROUND

Diet, loss of aryl hydrocarbon receptor (AhR) expression and their modification of the gut microbiota community composition and its metabolites affect the development of colorectal cancer (CRC). However, the concordance between fecal microbiota composition and the fecal metabolome is poorly understood. Mice with specific AhR deletion (AhRKO) in intestinal epithelial cell and their wild-type littermates were fed a low-fat diet or a high-fat diet. Shifts in the fecal microbiome and metabolome associated with diet and loss of AhR expression were assessed. Microbiome and metabolome data were integrated to identify specific microbial taxa that contributed to the observed metabolite shifts.

RESULTS

Our analysis shows that diet has a more pronounced effect on mouse fecal microbiota composition than the impact of the loss of AhR. In contrast, metabolomic analysis showed that the loss of AhR in intestinal epithelial cells had a more pronounced effect on metabolite profile compared to diet. Integration analysis of microbiome and metabolome identified unclassified Clostridiales, unclassified Desulfovibrionaceae, and Akkermansia as key contributors to the synthesis and/or utilization of tryptophan metabolites.

CONCLUSIONS

Akkermansia are likely to contribute to the synthesis and/or degradation of tryptophan metabolites. Our study highlights the use of multi-omic analysis to investigate the relationship between the microbiome and metabolome and identifies possible taxa that can be targeted to manipulate the microbiome for CRC treatment.

Towards continuous industrial bioprocessing with solventogenic and acetogenic clostridia: challenges, progress and perspectives

The sustainable production of solvents from above ground carbon is highly desired. Several clostridia naturally produce solvents and use a variety of renewable and waste-derived substrates such as lignocellulosic biomass and gas mixtures containing H2/CO2 or CO. To enable economically viable production of solvents and biofuels such as ethanol and butanol, the high productivity of continuous bioprocesses is needed. While the first industrial-scale gas fermentation facility operates continuously, the acetone-butanol-ethanol (ABE) fermentation is traditionally operated in batch mode. This review highlights the benefits of continuous bioprocessing for solvent production and underlines the progress made towards its establishment. Based on metabolic capabilities of solvent producing clostridia, we discuss recent advances in systems-level understanding and genome engineering. On the process side, we focus on innovative fermentation methods and integrated product recovery to overcome the limitations of the classical one-stage chemostat and give an overview of the current industrial bioproduction of solvents.

FUNCTIONAL METABOLOMICS DECIPHER BIOCHEMICAL FUNCTIONS AND ASSOCIATED MECHANISMS UNDERLIE SMALL-MOLECULE METABOLISM

Metabolism is the collection of biochemical reactions enabled by chemically diverse metabolites, which facilitate different physiological processes to exchange substances and synthesize energy in diverse living organisms. Metabolomics has emerged as a cutting-edge method to qualify and quantify the metabolites in different biological matrixes, and it has the extraordinary capacity to interrogate the biological significance that underlies metabolic modification and modulation. Liquid chromatography combined with mass spectrometry (LC/MS), as a robust platform for metabolomics analysis, has increased in popularity over the past 10 years due to its excellent sensitivity, throughput, and versatility. However, metabolomics investigation currently provides us with only phenotype data without revealing the biochemical functions and associated mechanisms. This limitation indeed weakens the core value of metabolomics data in a broad spectrum of the life sciences. In recent years, the scientific community has actively explored the functional features of metabolomics and translated this cutting-edge approach to be used to solve key multifaceted questions, such as disease pathogenesis, the therapeutic discovery of drugs, nutritional issues, agricultural problems, environmental toxicology, and microbial evolution. Here, we are the first to briefly review the history and applicable progression of LC/MS-based metabolomics, with an emphasis on the applications of metabolic phenotyping. Furthermore, we specifically highlight the next era of LC/MS-based metabolomics to target functional metabolomes, through which we can answer phenotype-related questions to elucidate biochemical functions and associated mechanisms implicated in dysregulated metabolism. Finally, we propose many strategies to enhance the research capacity of functional metabolomics by enabling the combination of contemporary omics technologies and cutting-edge biochemical techniques. The main purpose of this review is to improve the understanding of LC/MS-based metabolomics, extending beyond the conventional metabolic phenotype toward biochemical functions and associated mechanisms, to enhance research capability and to enlarge the applicable scope of functional metabolomics in small-molecule metabolism in different living organisms.

A multidimensional perspective on microbial interactions

Beyond being simply positive or negative, beneficial or inhibitory, microbial interactions can involve a diverse set of mechanisms, dependencies and dynamical properties. These more nuanced features have been described in great detail for some specific types of interactions, (e.g. pairwise metabolic cross-feeding, quorum sensing or antibiotic killing), often with the use of quantitative measurements and insight derived from modeling. With a growing understanding of the composition and dynamics of complex microbial communities for human health and other applications, we face the challenge of integrating information about these different interactions into comprehensive quantitative frameworks. Here, we review the literature on a wide set of microbial interactions, and explore the potential value of a formal categorization based on multidimensional vectors of attributes. We propose that such an encoding can facilitate systematic, direct comparisons of interaction mechanisms and dependencies, and we discuss the relevance of an atlas of interactions for future modeling and rational design efforts.

Gut-Brain Axis and Neurodegeneration: State-of-the-Art of Meta-Omics Sciences for Microbiota Characterization

Recent advances in the field of meta-omics sciences and related bioinformatics tools have allowed a comprehensive investigation of human-associated microbiota and its contribution to achieving and maintaining the homeostatic balance. Bioactive compounds from the microbial community harboring the human gut are involved in a finely tuned network of interconnections with the host, orchestrating a wide variety of physiological processes. These includes the bi-directional crosstalk between the central nervous system, the enteric nervous system, and the gastrointestinal tract (i.e., gut-brain axis). The increasing accumulation of evidence suggest a pivotal role of the composition and activity of the gut microbiota in neurodegeneration. In the present review we aim to provide an overview of the state-of-the-art of meta-omics sciences including metagenomics for the study of microbial genomes and taxa strains, metatranscriptomics for gene expression, metaproteomics and metabolomics to identify and/or quantify microbial proteins and metabolites, respectively. The potential and limitations of each discipline were highlighted, as well as the advantages of an integrated approach (multi-omics) to predict microbial functions and molecular mechanisms related to human diseases. Particular emphasis is given to the latest results obtained with these approaches in an attempt to elucidate the link between the gut microbiota and the most common neurodegenerative diseases, such as multiple sclerosis (MS), Alzheimer's disease (AD), Parkinson's disease (PD), and amyotrophic lateral sclerosis (ALS).

In vitro human colonic microbiota utilises D-β-hydroxybutyrate to increase butyrogenesis

The ketone body D-β-hydroxybutyrate (DBHB) has gained attention owing to its cellular signalling function; however, its effect on the human colonic microbiota remains unclear. Here, DBHB dynamics in the human colon were investigated using an in vitro colonic microbiota model, which maintained most of the operational taxonomic units detected in the original faeces. Over 54% of 0.41% (w/v) DBHB was metabolised by microbiota models originating from seven faecal samples after 30 h of fermentation (regarded as DBHB utilisers); however, <19% of DBHB was metabolised by microbiota models from five faecal samples (regarded as non-utilisers of DBHB). In utilisers, DBHB administration increased the relative abundance of the genus Coprococcus, correlated with increased butyrogenesis. Increased butyrogenesis was not observed in DBHB non-utilisers. Based on PICRUSt analysis, the relative abundance of β-hydroxybutyrate dehydrogenase was maintained in microbiota models from DBHB utilisers following DBHB administration; however, it decreased in microbiota models from non-utilisers. After 21 h of fermentation, the intracellular glutamate concentration, which is indicative of growth, showed a positive correlation with DBHB utilisation (R² = 0.70). Human colonic microbiotas with high growth activity demonstrate efficient utilisation of DBHB for increased butyrate production, which affords health benefits.

Metabolomics Analysis Reveals Global Metabolic Changes in the Evolved E. coli Strain with Improved Growth and 1-Butanol Production in Minimal Medium

Production of 1-butanol from microorganisms has garnered significant interest due to its prospect as a drop-in biofuel and precursor for a variety of commercially relevant chemicals. Previously, high 1-butanol titer has been reported in Escherichia coli strain JCL166, which contains a modified clostridial 1-butanol pathway. Although conventional and metabolomics-based strain improvement strategies of E. coli strain JCL166 have been successful in improving production in rich medium, 1-butanol titer was severely limited in minimal medium. To further improve growth and consequently 1-butanol production in minimal medium, adaptive laboratory evolution (ALE) using mutD5 mutator plasmid was done on JCL166. Comparative metabolomics analysis of JCL166 and BP1 revealed global perturbations in the evolved strain BP1 compared to JCL166 (44 out of 64 metabolites), encompassing major metabolic pathways such as glycolysis, nucleotide biosynthesis, and CoA-related processes. Collectively, these metabolic changes in BP1 result in improved growth and, consequently, 1-butanol production in minimal medium. Furthermore, we found that the mutation in ihfB caused by ALE had a significant effect on the metabolome profile of the evolved strain. This study demonstrates how metabolomics was utilized for characterization of ALE-developed strains to understand the overall effect of mutations acquired through evolution.

Host-microbe interactions: Profiles in the transcriptome, the proteome, and the metabolome

Periodontal studies using transcriptomics, proteomics, and metabolomics encompass the collection of mRNA transcripts, proteins, and small-molecule chemicals in the context of periodontal health and disease. The number of studies using these approaches has significantly increased in the last decade and they have provided new insight into the pathogenesis and host-microbe interactions that define periodontal diseases. This review provides an overview of current molecular findings using -omic approaches that underlie periodontal disease, including modulation of the host immune response, tissue homeostasis, and complex metabolic processes of the host and the oral microbiome. Integration of these -omic approaches will broaden our perspective of the molecular mechanisms involved in periodontal disease, advancing and improving the diagnosis and treatment of various stages and forms of periodontal disease.

Linoleic acid induces metabolic stress in the intestinal microorganism Bifidobacterium breve DSM 20213

Despite clinical and research interest in the health implications of the conjugation of linoleic acid (LA) by bifidobacteria, the detailed metabolic pathway and physiological reasons underlying the process remain unclear. This research aimed to investigate, at the molecular level, how LA affects the metabolism of Bifidobacterium breve DSM 20213 as a model for the well-known LA conjugation phenotype of this species. The mechanisms involved and the meaning of the metabolic changes caused by LA to B. breve DSM 20213 are unclear due to the lack of comprehensive information regarding the responses of B. breve DSM 20213 under different environmental conditions. Therefore, for the first time, an untargeted metabolomics-based approach was used to depict the main changes in the metabolic profiles of B. breve DSM 20213. Both supervised and unsupervised statistical methods applied to the untargeted metabolomic data allowed confirming the metabolic changes of B. breve DSM 20213 when exposed to LA. In particular, alterations to the amino-acid, carbohydrate and fatty-acid biosynthetic pathways were observed at the stationary phase of growth curve. Among others, significant up-regulation trends were detected for aromatic (such as tyrosine and tryptophan) and sulfur amino acids (i.e., methionine and cysteine). Besides confirming the conjugation of LA, metabolomics suggested a metabolic reprogramming during the whole growth curve and an imbalance in redox status following LA exposure. Such redox stress resulted in the down-accumulation of peroxide scavengers such as low-molecular-weight thiols (glutathione- and mycothiol-related compounds) and ascorbate precursors, together with the up-accumulation of oxidized (hydroxy- and epoxy-derivatives) forms of fatty acids. Consistently, growth was reduced and the levels of the oxidative stress marker malondialdehyde were higher in LA-exposed B. breve DSM 20213 than in the control.

Antimicrobial Resistance in Veterinary Medicine: An Overview

Antimicrobial resistance (AMR) represents one of the most important human- and animal health-threatening issues worldwide. Bacterial capability to face antimicrobial compounds is an ancient feature, enabling bacterial survival over time and the dynamic surrounding. Moreover, bacteria make use of their evolutionary machinery to adapt to the selective pressure exerted by antibiotic treatments, resulting in reduced efficacy of the therapeutic intervention against human and animal infections. The mechanisms responsible for both innate and acquired AMR are thoroughly investigated. Commonly, AMR traits are included in mobilizable genetic elements enabling the homogeneous diffusion of the AMR traits pool between the ecosystems of diverse sectors, such as human medicine, veterinary medicine, and the environment. Thus, a coordinated multisectoral approach, such as One-Health, provides a detailed comprehensive picture of the AMR onset and diffusion. Following a general revision of the molecular mechanisms responsible for both innate and acquired AMR, the present manuscript focuses on reviewing the contribution of veterinary medicine to the overall issue of AMR. The main sources of AMR amenable to veterinary medicine are described, driving the attention towards the indissoluble cross-talk existing between the diverse ecosystems and sectors and their cumulative cooperation to this warning phenomenon.

Implementation of liquid chromatography-high resolution mass spectrometry methods for untargeted metabolomic analyses of biological samples: A tutorial

Untargeted metabolomics is now widely recognized as a useful tool for exploring metabolic changes taking place in biological systems under different conditions. By its nature, this is a highly interdisciplinary field of research, and mastering all of the steps comprised in the pipeline can be a challenging task, especially for those researchers new to the topic. In this tutorial, we aim to provide an overview of the most widely adopted methods of performing LC-HRMS-based untargeted metabolomics of biological samples. A detailed protocol is provided in the Supplementary Information for rapidly implementing a basic screening workflow in a laboratory setting. This tutorial covers experimental design, sample preparation and analysis, signal processing and data treatment, and, finally, data analysis and its biological interpretation. Each section is accompanied by up-to-date literature to guide readers through the preparation and optimization of such a workflow, as well as practical information for avoiding or fixing some of the most frequently encountered pitfalls.

Bioassay- and metabolomics-guided screening of bioactive soil actinomycetes from the ancient city of Ihnasia, Egypt

Literature surveys, taxonomical differences, and bioassay results have been utilized in the discovery of new natural products to aid in Actinomycetes isolate-selection. However, no or less investigation have been done on establishing the differences in metabolomic profiles of the isolated microorganisms. The study aims to utilise bioassay- and metabolomics-guided tools that included dereplication study and multivariate analysis of the NMR and mass spectral data of microbial extracts to assist the selection of isolates for scaling-up the production of antimicrobial natural products. A total of 58 actinomycetes were isolated from different soil samples collected from Ihnasia City, Egypt and screened for their antimicrobial activities against indicator strains that included Bacillus subtilis, Escherichia coli, methicillin-resistant Staphylococcus aureus and Candida albicans. A number of 25 isolates were found to be active against B. subtilis and/or to at least one of the tested indicator strains. Principal component analyses showed chemical uniqueness for four outlying bioactive actinomycetes extracts. In addition, Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA) and dereplication study led us to further select two outlying anti-MRSA active isolates MS.REE.13 and 22 for scale-up work. MS.REE.13 and 22 exhibited zones of inhibition at 19 and 13 mm against MRSA, respectively. A metabolomics-guided approach provided the steer to target the bioactive metabolites (P<0.01) present in a crude extract or fraction even at nanogram levels but it was a challenge that such low-yielding bioactive natural products would be feasible to isolate. Validated to occur only on the active side of OPLS-DA loadings plot, the isolated compounds exhibited medium to weak antibiotic activity with MIC values between 250 and 800 μM. Two new compounds, P_24306 (C₁₀H₁₃N₂) and N_12799 (C₁₈H₃₂O₃) with MICs of 795 and 432 μM, were afforded from the scale-up of MS.REE. 13 and 22, respectively.

NMR-Metabolomics Shows That BolA Is an Important Modulator of Salmonella Typhimurium Metabolic Processes under Virulence Conditions

BolA is a ubiquitous global transcription factor. Despite its clear role in the induction of important stress-resistant physiological changes and its recent implication in the virulence of Salmonella, further research is required to shed light on the pathways modulated by BolA. In this study, we resorted to untargeted ¹H-NMR metabolomics to understand the impact of BolA on the metabolic profile of Salmonella Typhimurium, under virulence conditions. Three strains of S. Typhimurium SL1344 were studied: An SL1344 strain transformed with an empty plasmid (control), a bolA knockout mutant (ΔbolA), and a strain overexpressing bolA (bolA⁺). These strains were grown in a minimal virulence-inducing medium and cells were collected at the end of the exponential and stationary phases. The extracts were analyzed by NMR, and multivariate and univariate statistical analysis were performed to identify significant alterations. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) of ¹H-NMR data allowed the discrimination between the metabolic profiles of these strains, revealing increased levels of acetate, valine, alanine, NAD⁺, succinate, coenzyme A, glutathione, and putrescine in bolA⁺. These results indicate that BolA regulates pathways related to stress resistance and virulence, being an important modulator of the metabolic processes needed for S. Typhimurium infection.