Microbial metabolomics: From novel technologies to diversified applications

Strategies for Actinobacteria Isolation, Cultivation, and Metabolite Production that Are Biologically Important

Novel antimicrobial agents are urgently needed to combat antimicrobial resistance from multidrug-resistant organisms. Actinobacteria are key sources of bioactive metabolites with diverse biological activities. Despite their contributions to drug discovery, the process from strain identification to drug manufacturing faces many challenges, especially the rediscovery of known compounds. Recent technological and scientific advancements have accelerated drug development. Efforts to isolate and screen rare actinobacterial species could yield novel bioactive compounds. This review summarizes techniques for selectively isolating rare actinobacteria, improving bioactive metabolite production, and discovering potential strains. Notably, new genomic strategies and new discoveries regarding spectroscopic signature-based bioactive natural products containing specific structural motifs are also discussed. Furthermore, this review updates the compounds derived from rare actinobacteria and their biological applications.

From discovery to application: Enabling technology-based optimizing carbonyl reductases biocatalysis for active pharmaceutical ingredient synthesis

The catalytic conversion of chiral alcohols and corresponding carbonyl compounds by carbonyl reductases (alcohol dehydrogenases), which are NAD(P) or NAD(P)H-dependent oxidoreductases, has attracted considerable attention. However, existing carbonyl reductases are insufficient to meet the demands of diverse industrial applications; hence, new enzymes with functions that can expand the toolbox of biocatalysts are urgently required. Developing precisely controlled chiral biocatalysts is of great significance for the efficient development of a broad spectrum of active pharmaceutical ingredients via biosynthesis. In this review, we summarized methods for discovering novel natural carbonyl reductases from various perspectives. Furthermore, advances in protein engineering, utilizing known sequence and structural information as well as catalytic dynamics mechanisms to improve potential functions, are also addressed. The exponential growth in data-driven tools over the past decade has made it possible to de novo design carbonyl reductases. Additionally, various applications of these high-performance carbonyl reductases and different strategies for coenzyme regeneration involving photocatalysis during the reaction process were reviewed. These advancements will bring new opportunities and challenges to the fields of green chemistry and biosynthesis in the future.

Volatile organic compounds (VOCs) in terrestrial extreme environments: implications for life detection beyond Earth

Covering: 1961 to 2024Discovering and identifying unique natural products/biosignatures (signatures that can be used as evidence for past or present life) that are abundant, and complex enough that they indicate robust evidence of life is a multifaceted process. One distinct category of biosignatures being explored is organic compounds. A subdivision of these compounds not yet readily investigated are volatile organic compound (VOCs). When assessing these VOCs as a group (volatilome) a fingerprint of all VOCs within an environment allows the complex patterns in metabolic data to be unravelled. As a technique already successfully applied to many biological and ecological fields, this paper explores how analysis of volatilomes in terrestrial extreme environments could be used to enhance processes (such as metabolomics and metagenomics) already utilised in life detection beyond Earth. By overcoming some of the complexities of collecting VOCs in remote field sites, a variety of lab based analytical equipment and techniques can then be utilised. Researching volatilomics in astrobiology requires time to characterise the patterns of VOCs. They must then be differentiated from abiotic (non-living) signals within extreme environments similar to those found on other planetary bodies (analogue sites) or in lab-based simulated environments or microcosms. Such an effort is critical for understanding data returned from past or upcoming missions, but it requires a step change in approach which explores the volatilome as a vital additional tool to current 'Omics techniques.

Universal, untargeted detection of bacteria in tissues using metabolomics workflows

Fast and reliable identification of bacteria directly in clinical samples is a critical factor in clinical microbiological diagnostics. Current approaches require time-consuming bacterial isolation and enrichment procedures, delaying stratified treatment. Here, we describe a biomarker-based strategy that utilises bacterial small molecular metabolites and lipids for direct detection of bacteria in complex samples using mass spectrometry (MS). A spectral metabolic library of 233 bacterial species is mined for markers showing specificity at different phylogenetic levels. Using a univariate statistical analysis method, we determine 359 so-called taxon-specific markers (TSMs). We apply these TSMs to the in situ detection of bacteria using healthy and cancerous gastrointestinal tissues as well as faecal samples. To demonstrate the MS method-agnostic nature, samples are analysed using spatial metabolomics and traditional bulk-based metabolomics approaches. In this work, TSMs are found in >90% of samples, suggesting the general applicability of this workflow to detect bacterial presence with standard MS-based analytical methods.

β-lactam antibiotics induce metabolic perturbations linked to ROS generation leads to bacterial impairment

Understanding the impact of antibiotics on bacterial metabolism is crucial for elucidating their mechanisms of action and developing more effective therapeutic strategies. β-lactam antibiotics, distinguished by their distinctive β-lactam ring structure, are widely used as antimicrobial agents. This study investigates the global metabolic alterations induced by three β-lactam antibiotics-meropenem (a carbapenem), ampicillin (a penicillin), and ceftazidime (a cephalosporin)-in Escherichia coli. Our comprehensive metabolic profiling revealed significant perturbations in bacterial metabolism, particularly in pathways such as glutathione metabolism, pantothenate and CoA biosynthesis, pyrimidine metabolism, and purine metabolism. Antibiotic treatment markedly increased reactive oxygen species levels, with meropenem reaching nearly 200 ± 7%, ampicillin at 174 ± 11%, and ceftazidime at 152 ± 7%. Additionally, β-lactam antibiotics elevated 8-OHdG levels to 4.73 ± 0.56-fold for meropenem, 2.49 ± 0.19-fold for ampicillin, and 3.19 ± 0.34-fold for ceftazidime; 8-OHG levels increased to 5.57 ± 0.72-fold for meropenem, 3.08 ± 0.31-fold for ampicillin, and 4.45 ± 0.66-fold for ceftazidime, indicating that oxidative stress enhances oxidative damage to bacterial DNA and RNA. Notably, we observed a selective upregulation of specific amino acids associated with cellular repair mechanisms, indicating a metabolic adaptation to counteract oxidative damage. These findings illustrate that β-lactam antibiotics induce a complex metabolic perturbations associated with ROS production, potentially compromising critical cellular components. This study enhances our understanding of the intricate relationship between antibiotic action and bacterial metabolism, providing valuable insights for developing effective strategies against antibiotic-resistant pathogens.

Disentangling the molecular mystery of tumour-microbiota interactions: Microbial metabolites

The profound impact of the microbiota on the initiation and progression of cancer has been a focus of attention. In recent years, many studies have shown that microbial metabolites serve as key hubs that connect the microbiome and cancer progression, but the underlying molecular mechanisms have not been fully elucidated. Multiple mechanisms that influence tumour development and therapy resistance, including disrupting cellular signalling pathways, triggering oxidative stress, inducing metabolic reprogramming and reshaping tumour immune microenvironment, are reviewed. Focusing on recent advancements in this field, this review also summarises the methodological framework of studies regarding microbial metabolites. In this review, we outline the current state of research on tumour-associated microbial metabolites and describe the challenges in future scientific research and clinical applications. KEY POINTS: Metabolites derived from both gut and intratumoural microbiota play important roles in cancer initiation and progression. The dual roles of microbial metabolites pose an obstacle for clinical translations. Absolute quantification and tracing techniques of microbial metabolites are essential for addressing the gaps in studies on microbial metabolites. Integrating microbial metabolomics with multi-omics transcends current research paradigms.

Innovative omics strategies in fermented fruits and vegetables: Unveiling nutritional profiles, microbial diversity, and future prospects

Fermented fruits and vegetables (FFVs) are not only rich in essential nutrients but also contain distinctive flavors, prebiotics, and metabolites. Although omics techniques have gained widespread recognition as an analytical strategy for FFVs, its application still encounters several challenges due to the intricacies of biological systems. This review systematically summarizes the advances, obstacles and prospects of genomics, transcriptomics, proteomics, metabolomics, and multi-omics strategies in FFVs. It is evident that beyond traditional applications, such as the exploration of microbial diversity, protein expression, and metabolic pathways, omics techniques exhibit innovative potential in deciphering stress response mechanisms and uncovering spoilage microorganisms. The adoption of multi-omics strategies is paramount to acquire a multidimensional network fusion, thereby mitigating the limitations of single omics strategies. Although substantial progress has been made, this review underscores the necessity for a comprehensive repository of omics data and the establishment of universal databases to ensure precision in predictions. Furthermore, multidisciplinary integration with other physical or biochemical approaches is imperative, as it enriches our comprehension of this intricate process.

A Comprehensive Overview of Postbiotics with a Special Focus on Discovery Techniques and Clinical Applications

The increasing interest in postbiotics, a term gaining recognition alongside probiotics and prebiotics, aligns with a growing number of clinical trials demonstrating positive outcomes for specific conditions. Postbiotics present several advantages, including safety, extended shelf life, ease of administration, absence of risk, and patentability, making them more appealing than probiotics alone. This review covers various aspects, starting with an introduction, terminology, classification of postbiotics, and brief mechanisms of action. It emphasizes microbial metabolomics as the initial step in discovering novel postbiotics. Commonly employed techniques such as NMR, GC-MS, and LC-MS are briefly outlined, along with their application principles and limitations in microbial metabolomics. The review also examines existing research where these techniques were used to identify, isolate, and characterize postbiotics derived from different microbial sources. The discovery section concludes by highlighting challenges and future directions to enhance postbiotic discovery. In the second half of the review, we delve deeper into numerous published postbiotic clinical trials to date. We provide brief overviews of system-specific trial applications, their objectives, the postbiotics tested, and their outcomes. The review concludes by highlighting ongoing applications of postbiotics in extended clinical trials, offering a comprehensive overview of the current landscape in this evolving field.

Lung microbiota: implications and interactions in chronic pulmonary diseases

The lungs, as vital organs in the human body, continuously engage in gas exchange with the external environment. The lung microbiota, a critical component in maintaining internal homeostasis, significantly influences the onset and progression of diseases. Beneficial interactions between the host and its microbial community are essential for preserving the host's health, whereas disease development is often linked to dysbiosis or alterations in the microbial community. Evidence has demonstrated that changes in lung microbiota contribute to the development of major chronic lung diseases, including chronic obstructive pulmonary disease (COPD), idiopathic pulmonary fibrosis (IPF), asthma, and lung cancer. However, in-depth mechanistic studies are constrained by the small scale of the lung microbiota and its susceptibility to environmental pollutants and other factors, leaving many questions unanswered. This review examines recent research on the lung microbiota and lung diseases, as well as methodological advancements in studying lung microbiota, summarizing the ways in which lung microbiota impacts lung diseases and introducing research methods for investigating lung microbiota.

Mass spectrometry-based metabolomics for the investigation of antibiotic-bacterial interactions

With the development of analytical technologies especially mass spectrometry, metabolomics is becoming increasingly hot in the field of studying antibiotic-bacterial interactions. On the one hand, metabolomics can reveal metabolic perturbations in bacteria in the presence of antibiotics and expose metabolic mechanisms. On the other hand, through in-depth analysis of bacterial metabolic profiles, biomarkers and bioactive secondary metabolites with great potential as drug precursors can be discovered. This review focuses on the experimental workflow of bacterial metabolomics and its application to study the interaction between bacteria and antibiotics. Metabolomics improves the understanding of antibiotic lethality, reveals metabolic perturbations in antibiotic-resistant bacteria, guides the diagnosis and antibiotic treatment of infectious diseases, and aids in the exploration of antibacterial metabolites in nature. Furthermore, current limitations and directions for future developments in this area are discussed.

Survival prediction using apparent diffusion coefficient values in recurrent glioblastoma under bevacizumab treatment: an updated systematic review and meta-analysis

Bevacizumab is a common strategy for the treatment of recurrent glioblastoma. Survival status is a crucial issue for patients with recurrent glioblastoma, and the apparent diffusion coefficient (ADC) values of the lower Gaussian curve have been reported to have the potential to predict prognosis in recurrent glioblastoma. In the present study, we aimed to clarify the survival prediction of ADC values in patients with recurrent glioblastoma receiving bevacizumab treatment through a systematic review and meta-analysis of randomized clinical trials, comparing ADC values higher than the cut-off values with those lower than the cut-off values to determine which type of ADC values can be associated with significant survival benefits. Different survival indicators were analyzed, including overall survival (OS) and progression-free survival (PFS). Ten studies with a total of 782 patients with recurrent glioblastoma were included. The focused outcomes were OS and PFS. Our results showed that ADC values lower than the cut-off values were associated with significant benefits for OS status compared with ADC values higher than the cut-off values. Similar significant benefits were observed for PFS. The meta-analysis results suggest that ADC values lower than the cut-off values might be associated with significant benefits for OS and PFS when compared with ADC values higher than the cut-off values. However, bias in relation to the different stages of recurrent glioblastoma and different types, doses, and regimens of bevacizumab should not be ignored.

Metabolomics approach to understand molecular mechanisms involved in fungal pathogen-citrus pathosystems

Citrus is a crucial crop with a significant economic impact globally. However, postharvest decay caused by fungal pathogens poses a considerable threat, leading to substantial financial losses. Penicillium digitatum, Penicillium italicum, Geotrichum citri-aurantii and Phyllosticta citricarpa are the main fungal pathogens, causing green mold, blue mold, sour rot and citrus black spot diseases, respectively. The use of chemical fungicides as a control strategy in citrus raises concerns about food and environmental safety. Therefore, understanding the molecular basis of host-pathogen interactions is essential to find safer alternatives. This review highlights the potential of the metabolomics approach in the search for bioactive compounds involved in the pathogen-citrus interaction, and how the integration of metabolomics and genomics contributes to the understanding of secondary metabolites associated with fungal virulence and the fungal infection mechanisms. Our goal is to provide a pipeline combining metabolomics and genomics that can effectively guide researchers to perform studies aiming to contribute to the understanding of the fundamental chemical and biochemical aspects of pathogen-host interactions, in order to effectively develop new alternatives for fungal diseases in citrus cultivation. We intend to inspire the scientific community to question unexplored biological systems, and to employ diverse analytical approaches and metabolomics techniques to address outstanding questions about the non-studied pathosystems from a chemical biology perspective.

Inhibition of anaerobic digestion by various ammonia sources resulted in subtle differences in metabolite dynamics

The impact of ammonia on anaerobic digestion performance and microbial dynamics has been extensively studied, but the concurrent effect of anions brought by ammonium salt should not be neglected. This paper studied this effect using metabolomics and a time-course statistical framework. Metabolomics provides novel perspectives to study microbial processes and facilitates a more profound understanding at the metabolic level. The advanced statistical framework enables deciphering the complexity of large metabolomics data sets. More specifically, a series of lab-scale batch reactors were set up with different ammonia sources added. Samples of nine time points over the degradation were analyzed with liquid chromatography-mass spectrometry. A filtering procedure was applied to select the promising metabolomic peaks from 1262 peaks, followed by modeling their intensities across time. The metabolomic peaks with similar time profiles were clustered, evidencing the correlation of different biological processes. Differential analysis was performed to seek the differences in metabolite dynamics caused by different anions. Finally, tandem mass spectrometry and metabolite annotation provided further information on the molecular structure and possible metabolic pathways. For example, the consumption of 5-aminovaleric acid, a short-chain fatty acid obtained from l-lysine degradation, was slowed down by phosphates. Overall, by investigating the effect of anions on anaerobic digestion, our study demonstrated the effectiveness of metabolomics in providing detailed information in a set of samples from different experimental conditions. With the statistical framework, the approach enables capturing subtle differences in metabolite dynamics between samples while accounting for the differences caused by time variations.

Monotonic trends of soil microbiomes, metagenomic and metabolomic functioning across ecosystems along water gradients in the Altai region, northwestern China

To investigate microbial communities and their contributions to carbon and nutrient cycling along water gradients can enhance our comprehension of climate change impacts on ecosystem services. Thus, we conducted an assessment of microbial communities, metagenomic functions, and metabolomic profiles within four ecosystems, i.e., desert grassland (DG), shrub-steppe (SS), forest (FO), and marsh (MA) in the Altai region of Xinjiang, China. Our results showed that soil total carbon (TC), total nitrogen, NH4+, and NO3- increased, but pH decreased with soil water gradients. Microbial abundances and richness also increased with soil moisture except the abundances of fungi and protists being lowest in MA. A shift in microbial community composition is evident along the soil moisture gradient, with Proteobacteria, Basidiomycota, and Evosea proliferating but a decline in Actinobacteria and Cercozoa. The β-diversity of microbiomes, metagenomic, and metabolomic functioning were correlated with soil moisture gradients and have significant associations with specific soil factors of TC, NH4+, and pH. Metagenomic functions associated with carbohydrate and DNA metabolisms, as well as phages, prophages, TE, plasmids functions diminished with moisture, whereas the genes involved in nitrogen and potassium metabolism, along with certain biological interactions and environmental information processing functions, demonstrated an augmentation. Additionally, MA harbored the most abundant metabolomics dominated by lipids and lipid-like molecules and organic oxygen compounds, except certain metabolites showing decline trends along water gradients, such as N'-Hydroxymethylnorcotinine and 5-Hydroxyenterolactone. Thus, our study suggests that future ecosystem succession facilitated by changes in rainfall patterns will significantly alter soil microbial taxa, functional potential, and metabolite fractions.

Strain-specific metabolomic diversity of Lactiplantibacillus plantarum under aerobic and anaerobic conditions

The chemotaxonomic diversity of 20 Lactiplantibacillus plantarum strains was investigated using non-targeted metabolite profiling under different culture conditions. Multivariate and metabolic pathway analyses based on GC-MS and LC-MS/MS datasets showed that amino acid metabolism, especially 2-hydroxy acids, was enriched under aerobic conditions (AE), whereas fatty acid & sugar metabolism was increased under anaerobic conditions (AN). Based on the metabolite profiles, L. plantarum strains were clustered into three main groups (A, B, and C). Overall, 79 and 83 significantly discriminant metabolites were characterized as chemical markers of AE and AN growth conditions, respectively. Notably, alcohols were more abundant in group A whereas amino acids, peptides, purines, and pyrimidines were significantly higher in group C. 2-hydroxy acids and oxylipins biosynthesized through amino acid and fatty acid metabolism, respectively, were more abundant in groups A and B. Furthermore, we observed a strong correlation between the chemical diversity of L. plantarum groups and their antioxidant activity from metabolite extracts. We propose a non-targeted metabolomic workflow to comprehensively characterize the chemodiversity of L. plantarum strain under different culture conditions, which may help reveal specific biomarkers of individual strains depending on the culture conditions.

Integrating metagenomics and metabolomics to study the response of microbiota in black soil degradation

As the largest commercial food production base and ecological security barrier, land degradation in black soil areas seriously threatens the global food supply and natural ecosystems. Therefore, determining the response of soil microbiota is crucial to restoring degraded soils. This study combined metagenomics and metabolomics to investigate the effect of different degrees of soil degradation on microbial community composition and metabolic function in black soils. It was found that alpha diversity in degraded soils (Shannon: 22.3) was higher than in nondegraded soil (ND) (Shannon: 21.8), and the degree of degradation significantly altered the structure and composition of soil microbial communities. The results of LEfSe analysis obtained 9 (ND), 7 (lightly degraded, LD), 10 (moderately degraded, MD), and 1 (severely degraded, SD) biomarkers in four samples. Bradyrhizobium, Sphingomonas, and Ramlibacter were significantly affected by soil degradation and can be considered biomarkers of ND, MD, and SD, respectively. Soil nutrient and enzyme activities decreased significantly with increasing black soil degradation, soil organic matter (SOM) content decreased from 11.12 % to 1.97 %, and Sucrase decreased from 23.53 to 6.59 mg/g/d. In addition, C was the critical driver affecting microbial community structure, contributing 61.2 % to differences in microbial community distribution, and microbial altering relative abundance which participle in the carbon cycle to respond to soil degradation. Metabolomic analyses indicated that soil degradation significantly modified the soil metabolite spectrum, and the metabolic functions of most microorganisms responding to soil degradation were adversely affected. The combined multi-omics analysis further indicated that biomarkers dominate in accumulating metabolites. These findings confirmed that due to their role in the composition and functioning of these degraded soils, these biomarkers could be employed in strategies for managing and restoring degraded black soils.

UHPLC/MS-Based Untargeted Metabolomics Reveals Metabolic Characteristics of Clinical Strain of Mycoplasma bovis

Mycoplasma bovis is a global concern for the cattle industry owing to its high rates of infection and resulting morbidity, but its pathogenesis remains poorly understood. Metabolic pathways and characteristics of M. bovis clinical strain were elucidated by comparing the differential expression of metabolites between M. bovis clinical strain NX114 and M. bovis international reference strain PG45. Metabolites of M. bovis in the logarithmic stage were analyzed based on the non-targeted metabolomic technology of ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS). We found 596 metabolites with variable expression, of which, 190 had substantial differences. Differential metabolite analysis of M. bovis NX114 showed organic acids and their derivatives, nucleosides, and nucleotide analogs as important components. We found O-Phospho-L-serine (SEP) as a potential signature metabolite and indicator of pathogenicity. The difference in nucleic acid metabolites reflects the difference in growth phenotypes between both strains of M. bovis. According to KEGG enrichment analysis, the ABC transporter synthesis route had the most differential metabolites of the first 15 differential enrichment pathways. This study reflects the species-specific differences between two strains of M. bovis and further enriches our understanding of its metabolism, paving the way for further research into its pathogenesis.

Study on the metabolic process of phthalic acid driven proliferation of Rhizoctonia solani

Introduction

Continuous cropping obstacle seriously affects the quality and yield of Salvia miltiorrhiza, and the synergistic effect of root exudates and rhizosphere pathogenic microorganisms may be an important cause of continuous cropping obstacle. This study aimed to explore the effects of representative organic acids on the growth and metabolism of specific microorganisms in the S. miltiorrhiza rhizosphere soil under continuous cropping, and clarify its mechanism.

Methods

The effect of phthalic acid (PA) on the growth and metabolism of Rhizoctonia solani was evaluated by mycelial growth inhibition method. Ultra-high performance liquid chromatography and tandem mass spectrometry were used to identify the differential metabolites of R. solani induced by exogenous PA.

Results

PA exerted a concentration-dependent effect on mycelial growth, biomass, intracellular polysaccharides con-tent, and total protein content in R. solani. A total of 1773 metabolites and 1040 differential metabolites were identified in the blank medium (CK), Fungi (CK + fungi), and PA-Fungi (CK + fungi + acid) groups. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis showed that the differential metabolites were mainly involved in the sugar, lipid, and protein metabolic pathways related to stable membrane structure and cell growth.

Discussion

The proliferation and metabolism network of R. solani induced by PA was proposed, and the enhancement of sugar, lipid, and amino acid metabolism was presumed to be related to the active resistance of cells to organic acid stress. These results offer new in-sights into the effects of PA metabolism on promoting R. solani proliferation, and provide theoretical support for further optimizing the rhizosphere microecological environment of Salvia miltiorrhiza continuous cropping soil and reducing continuous cropping obstacle.

Integrated multi-omics analyses of microbial communities: a review of the current state and future directions

Integrated multi-omics analyses of microbiomes have become increasingly common in recent years as the emerging omics technologies provide an unprecedented opportunity to better understand the structural and functional properties of microbial communities. Consequently, there is a growing need for and interest in the concepts, approaches, considerations, and available tools for investigating diverse environmental and host-associated microbial communities in an integrative manner. In this review, we first provide a general overview of each omics analysis type, including a brief history, typical workflow, primary applications, strengths, and limitations. Then, we inform on both experimental design and bioinformatics analysis considerations in integrated multi-omics analyses, elaborate on the current approaches and commonly used tools, and highlight the current challenges. Finally, we discuss the expected key advances, emerging trends, potential implications on various fields from human health to biotechnology, and future directions.

Recent Review on Selected Xenobiotics and Their Impacts on Gut Microbiome and Metabolome

As it is well known, the gut is one of the primary sites in any host for xenobiotics, and the many microbial metabolites responsible for the interactions between the gut microbiome and the host. However, there is a growing concern about the negative impacts on human health induced by toxic xenobiotics. Metabolomics, broadly including lipidomics, is an emerging approach to studying thousands of metabolites in parallel. In this review, we summarized recent advancements in mass spectrometry (MS) technologies in metabolomics. In addition, we reviewed recent applications of MS-based metabolomics for the investigation of toxic effects of xenobiotics on microbial and host metabolism. It was demonstrated that metabolomics, gut microbiome profiling, and their combination have a high potential to identify metabolic and microbial markers of xenobiotic exposure and determine its mechanism. Further, there is increasing evidence supporting that reprogramming the gut microbiome could be a promising approach to the intervention of xenobiotic toxicity.

Exploring the Microbiome in Human Reproductive Tract: High-Throughput Methods for the Taxonomic Characterization of Microorganisms

Microorganisms are important due to their widespread presence and multifaceted roles across various domains of life, ecology, and industries. In humans, they underlie the proper functioning of multiple systems crucial to well-being, including immunological and metabolic functions. Emerging research addressing the presence and roles of microorganisms within human reproduction is increasingly relevant. Studies implementing new methodologies (e.g., to investigate vaginal, uterine, and semen microenvironments) can now provide relevant insights into fertility, reproductive health, or pregnancy outcomes. In that sense, cutting-edge sequencing techniques, as well as others such as meta-metabolomics, culturomics, and meta-proteomics, are becoming more popular and accessible worldwide, allowing the characterization of microbiomes at unprecedented resolution. However, they frequently involve rather complex laboratory protocols and bioinformatics analyses, for which researchers may lack the required expertise. A suitable pipeline would successfully enable both taxonomic classification and functional profiling of the microbiome, providing easy-to-understand biological interpretations. However, the selection of an appropriate methodology would be crucial, as it directly impacts the reproducibility, accuracy, and quality of the results and observations. This review focuses on the different current microbiome-related techniques in the context of human reproduction, encompassing niches like vagina, endometrium, and seminal fluid. The most standard and reliable methods are 16S rRNA gene sequencing, metagenomics, and meta-transcriptomics, together with complementary approaches including meta-proteomics, meta-metabolomics, and culturomics. Finally, we also offer case examples and general recommendations about the most appropriate methods and workflows and discuss strengths and shortcomings for each technique.

Metabolomic Strategies to Improve Chemical Information from OSMAC Studies of Endophytic Fungi

Metabolomics strategies are important tools to get holistic chemical information from a system, but they are scarcely applied to endophytic fungi to understand their chemical profiles of biosynthesized metabolites. Here Penicillium sp. was cultured using One Strain Many Compounds (OSMAC) conditions as a model system to demonstrate how this strategy can help in understanding metabolic profiles and determining bioactive metabolites with the application of metabolomics and statistical analyses, as well as molecular networking. Penicillium sp. was fermented in different culture media and the crude extracts from mycelial biomass (CEm) and broth (CEb) were obtained, evaluated against bacterial strains (Staphylococcus aureus and Pseudomonas aeruginosa), and the metabolomic profiles by LC-DAD-MS were obtained and chemometrics statistical analyses were applied. The CEm and CEb extracts presented different chemical profiles and antibacterial activities; the highest activities observed were against S. aureus from CEm (MIC = 16, 64, and 128 µg/mL). The antibacterial properties from the extracts were impacted for culture media from which the strain was fermented. From the Volcano plot analysis, it was possible to determine statistically the most relevant features for the antibacterial activity, which were also confirmed from biplots of PCA as strong features for the bioactive extracts. These compounds included 75 (13-oxoverruculogen isomer), 78 (austalide P acid), 87 (austalide L or W), 88 (helvamide), 92 (viridicatumtoxin A), 96 (austalide P), 101 (dihydroaustalide K), 106 (austalide k), 110 (spirohexaline), and 112 (pre-viridicatumtoxin). Thus, these features included diketopiperazines, meroterpenoids, and polyketides, such as indole alkaloids, austalides, and viridicatumtoxin A, a rare tetracycline.

Applying multi-omics toward tumor microbiome research

Rather than a "short-term tenant," the tumor microbiome has been shown to play a vital role as a "permanent resident," affecting carcinogenesis, cancer development, metastasis, and cancer therapies. As the tumor microbiome has great potential to become a target for the early diagnosis and treatment of cancer, recent research on the relevance of the tumor microbiota has attracted a wide range of attention from various scientific fields, resulting in remarkable progress that benefits from the development of interdisciplinary technologies. However, there are still a great variety of challenges in this emerging area, such as the low biomass of intratumoral bacteria and unculturable character of some microbial species. Due to the complexity of tumor microbiome research (e.g., the heterogeneity of tumor microenvironment), new methods with high spatial and temporal resolution are urgently needed. Among these developing methods, multi-omics technologies (combinations of genomics, transcriptomics, proteomics, and metabolomics) are powerful approaches that can facilitate the understanding of the tumor microbiome on different levels of the central dogma. Therefore, multi-omics (especially single-cell omics) will make enormous impacts on the future studies of the interplay between microbes and tumor microenvironment. In this review, we have systematically summarized the advances in multi-omics and their existing and potential applications in tumor microbiome research, thus providing an omics toolbox for investigators to reference in the future.

Sample Preparation in Microbial Metabolomics: Advances and Challenges

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

Unveiling Microbial Chemical Interactions Based on Metabolomics Approaches

Microorganisms are ubiquitous in diverse habitats and studying their chemical interactions with the environment and comprehend its complex relations with both hosts and environment, are crucial for the development of strategies to control microbial diseases. This chapter discusses the importance of studying microorganisms with agricultural benefits, using specialized metabolites as examples. Herein we highlight the challenges and opportunities in utilizing microorganisms as alternatives to synthetic pesticides and fertilizers in agriculture. Genome-guided investigations and improved analytical methodologies are necessary to characterize diverse and complex biomolecules produced by microorganisms. Predicting and isolating bioproducts based on genetic information have become a focus for researchers, aided by tools like antiSMASH, BiG-SCAPE, PRISM, and others. However, translating genomic data into practical applications can be complex. Therefore, integrating genomics, transcriptomics, and metabolomics enhances chemical characterization, aiding in discovering new metabolic pathways and specialized metabolites. Additionally, elicitation is one promising strategy to enhance beneficial metabolite production. Finally, identify and characterize microbial secondary metabolites remain challenging due to their low production, complex chemical structure characterization and different environmental factors necessary for metabolite in vitro production.

Discovering New Natural Products Using Metabolomics-Based Approaches

The incessant search for new natural molecules with biological activities has forced researchers in the field of chemistry of natural products to seek different approaches for their prospection studies. In particular, researchers around the world are turning to approaches in metabolomics to avoid high rates of re-isolation of certain compounds, something recurrent in this branch of science. Thanks to the development of new technologies in the analytical instrumentation of spectroscopic and spectrometric techniques, as well as the advance in the computational processing modes of the results, metabolomics has been gaining more and more space in studies that involve the prospection of natural products. Thus, this chapter summarizes the precepts and good practices in the metabolomics of microbial natural products using mass spectrometry and nuclear magnetic resonance spectroscopy, and also summarizes several examples where this approach has been applied in the discovery of bioactive molecules.

Microbial containment device: A platform for comprehensive analysis of microbial metabolism without sample preparation

Metabolomics is a mainstream strategy for investigating microbial metabolism. One emerging application of metabolomics is the systematic quantification of metabolic boundary fluxes – the rates at which metabolites flow into and out of cultured cells. Metabolic boundary fluxes can capture complex metabolic phenotypes in a rapid assay, allow computational models to be built that predict the behavior of cultured organisms, and are an emerging strategy for clinical diagnostics. One advantage of quantifying metabolic boundary fluxes rather than intracellular metabolite levels is that it requires minimal sample processing. Whereas traditional intracellular analyses require a multi-step process involving extraction, centrifugation, and solvent exchange, boundary fluxes can be measured by simply analyzing the soluble components of the culture medium. To further simplify boundary flux analyses, we developed a custom 96-well sampling system—the Microbial Containment Device (MCD)—that allows water-soluble metabolites to diffuse from a microbial culture well into a bacteria-free analytical well via a semi-permeable membrane. The MCD was designed to be compatible with the autosamplers present in commercial liquid chromatography-mass spectrometry systems, allowing metabolic fluxes to be analyzed with minimal sample handling. Herein, we describe the design, evaluation, and performance testing of the MCD relative to traditional culture methods. We illustrate the utility of this platform, by quantifying the unique boundary fluxes of four bacterial species and demonstrate antibiotic-induced perturbations in their metabolic activity. We propose the use of the MCD for enabling single-step metabolomics sample preparation for microbial identification, antimicrobial susceptibility testing, and other metabolic boundary flux applications where traditional sample preparation methods are impractical.

Integrated multi-omics approaches to understand microbiome assembly in Jiuqu, a mixed-culture starter

The use of Jiuqu as a saccharifying and fermenting starter in the production of fermented foods is a very old biotechnological process that can be traced back to ancient times. Jiuqu harbors a hub of microbial communities, in which prokaryotes and eukaryotes cohabit, interact, and communicate. However, the spontaneous fermentation based on empirical processing hardly guarantees the stable assembly of the microbiome and a standardized quality of Jiuqu. This review describes the state of the art, limitations, and challenges towards the application of traditional and omics-based technology to study the Jiuqu microbiome and highlights the need for integrating meta-omics data. In addition, we review the varieties of Jiuqu and their production processes, with particular attention to factors shaping the microbiota of Jiuqu. Then, the potentials of integrated omics approaches used in Jiuqu research are examined in order to understand the assembly of the microbiome and improve the quality of the products. A variety of different approaches, including molecular and mass spectrometry-based techniques, have led to scientific advances in the analysis of the complex ecosystem of Jiuqu. To date, the extensive research on Jiuqu has mainly focused on the microbial community diversity, flavor profiles, and biochemical characteristics. An integrative approach to large-scale omics datasets and cultivated microbiota has great potential for understanding the interrelation of the Jiuqu microbiome. Further research on the Jiuqu microbiome may explain the inherent property of compositional stability and stable performance of a complex microbiota coping with environmental perturbations and provide important insights to reconstruct synthetic microbiota and develop modern intelligent manufacturing procedures for Jiuqu.

Synergistic effect of co-culture rhizosphere Streptomyces: A promising strategy to enhance antimicrobial activity and plant growth-promoting function

Rhizosphere Streptomyces is one of the important types of rhizosphere microorganisms that plays an important role in promoting plant growth and controlling plant diseases to maintain agricultural ecosystem balance and green ecological agriculture development as beneficial bacteria. Microbial co-culture simulates the complex biocommunity in nature, which has more advantages than the monoculture with a synergistic effect. As the key signal mediums of microorganisms, plants, and their interactions, microbial metabolites are of great significance in revealing their functional mechanism. In this study, two potential plant growth-promoting rhizobacteria, Streptomyces albireticuli MDJK11, and Streptomyces alboflavus MDJK44, were selected to explore the effects of co-culture and monoculture on plant growth promotion and disease prevention, and the metabolic material basis was analyzed by metabonomics. Results showed that Streptomyces MDJK11, MDJK44 monoculture, and co-culture condition all showed good growth promoting and antimicrobial effects. Moreover, as compared to the monoculture, the co-culture showed the advantage of a synergistic enhancement effect. LC-MS-based metabonomics analysis showed the metabolic material bases of Streptomyces for plant growth promotion and disease prevention were mainly plant hormone and antibiotics and the co-culture condition could significantly stimulate the production of plant hormone promoters and macrolide, cyclic peptide, and aminoglycoside antibiotics. The study proved that the co-cultures of S. albireticuli MDJK11 and S. alboflavus MDJK44 have great potential in crop growth promotion and disease prevention.