Editorial: Using Genomics, Metagenomics and Other "Omics" to Assess Valuable Microbial Ecosystem Services and Novel Biotechnological Applications

Non-pathogenic microbiome associated to aquatic plants and anthropogenic impacts on this interaction

The microbiota associated with aquatic plants plays a crucial role in promoting plant growth and development. The structure of the plant microbiome is shaped by intricate interactions among hosts, microbes, and environmental factors. Consequently, anthropogenic pressures that disrupt these interactions can indirectly impact the ecosystem services provided by aquatic plants, such as CO2 fixation, provision of food resources, shelter to animals, nutrient cycling, and water purification. Presently, studies on plant-microbiota interactions primarily focus on terrestrial hosts and overlook aquatic environments with their unique microbiomes. Therefore, there is a pressing need for a comprehensive understanding of plant microbiomes in aquatic ecosystems. This review delves into the overall composition of the microbiota associated with aquatic plant, with a particular emphasis on bacterial communities, which have been more extensively studied. Subsequently, the functions provided by the microbiota to their aquatic plants hosts are explored, including the acquisition and mobilization of nutrients, production of auxin and related compounds, enhancement of photosynthesis, and protection against biotic and abiotic stresses. Additionally, the influence of anthropogenic stressors, such as climate change and aquatic contamination, on the interaction between microbiota and aquatic plants is discussed. Finally, knowledge gaps are highlighted and future directions in this field are suggested.

Thraustochytrids as a promising source of fatty acids, carotenoids, and sterols: bioactive compound biosynthesis, and modern biotechnology

Thraustochytrids are eukaryotes and obligate marine protists. They are increasingly considered to be a promising feed additive because of their superior and sustainable application in the production of health-benefiting bioactive compounds, such as fatty acids, carotenoids, and sterols. Moreover, the increasing demand makes it critical to rationally design the targeted products by engineering industrial strains. In this review, bioactive compounds accumulated in thraustochytrids were comprehensively evaluated according to their chemical structure, properties, and physiological function. Metabolic networks and biosynthetic pathways of fatty acids, carotenoids, and sterols were methodically summarized. Further, stress-based strategies used in thraustochytrids were reviewed to explore the potential methodologies for enhancing specific product yields. There are internal relationships between the biosynthesis of fatty acids, carotenoids, and sterols in thraustochytrids since they share some branches of the synthetic routes with some intermediate substrates in common. Although there are classic synthesis pathways presented in the previous research, the metabolic flow of how these compounds are being synthesized in thraustochytrids still remains uncovered. Further, combined with omics technologies to deeply understand the mechanism and effects of different stresses is necessary, which could provide guidance for genetic engineering. While gene-editing technology has allowed targeted gene knock-in and knock-outs in thraustochytrids, efficient gene editing is still required. This critical review will provide comprehensive information to benefit boosting the commercial productivity of specific bioactive substances by thraustochytrids.

Interfacing Machine Learning and Microbial Omics: A Promising Means to Address Environmental Challenges

Microbial communities are ubiquitous and carry an exceptionally broad metabolic capability. Upon environmental perturbation, microbes are also amongst the first natural responsive elements with perturbation-specific cues and markers. These communities are thereby uniquely positioned to inform on the status of environmental conditions. The advent of microbial omics has led to an unprecedented volume of complex microbiological data sets. Importantly, these data sets are rich in biological information with potential for predictive environmental classification and forecasting. However, the patterns in this information are often hidden amongst the inherent complexity of the data. There has been a continued rise in the development and adoption of machine learning (ML) and deep learning architectures for solving research challenges of this sort. Indeed, the interface between molecular microbial ecology and artificial intelligence (AI) appears to show considerable potential for significantly advancing environmental monitoring and management practices through their application. Here, we provide a primer for ML, highlight the notion of retaining biological sample information for supervised ML, discuss workflow considerations, and review the state of the art of the exciting, yet nascent, interdisciplinary field of ML-driven microbial ecology. Current limitations in this sphere of research are also addressed to frame a forward-looking perspective toward the realization of what we anticipate will become a pivotal toolkit for addressing environmental monitoring and management challenges in the years ahead.

Merging Fungal and Bacterial Community Profiles via an Internal Control

Integrated measurements of fungi and bacteria are critical to understand how interactions between these taxa drive key processes in ecosystems ranging from soils to animal guts. High-throughput amplicon sequencing is commonly used to census microbiomes, but the genetic markers targeted for fungi and bacteria (typically ribosomal regions) are domain-specific so profiling must be performed separately, obscuring relationships between these groups. To solve this problem, we developed a spike-in method with an internal control (IC) construct containing primer sites commonly used for bacterial and fungal taxonomic profiling. The internal control offers several advantages: estimation of absolute abundances, estimation of fungal to bacterial ratios (F:B), integration of bacterial and fungal profiles for holistic community analysis, and lower costs compared to other quantitation methods. To validate the IC as a scaling method, we compared IC-derived measures of F:B to measures from quantitative PCR (qPCR) using a commercial mock community (the ZymoBiomic Microbial Community DNA Standard II, containing two fungi and eight bacteria) and complex environmental samples. For both the mock community and the environmental samples, the IC produced F:B values that were statistically consistent with qPCR. Merging the environmental fungal and bacterial profiles based on the IC-derived F:B values revealed new relationships among samples in terms of community similarity. This IC method is the first spike-in method to employ a single construct for cross-domain amplicon sequencing, offering more reliable measurements.

Recent Advanced Technologies for the Characterization of Xenobiotic-Degrading Microorganisms and Microbial Communities

Global environmental contamination with a complex mixture of xenobiotics has become a major environmental issue worldwide. Many xenobiotic compounds severely impact the environment due to their high toxicity, prolonged persistence, and limited biodegradability. Microbial-assisted degradation of xenobiotic compounds is considered to be the most effective and beneficial approach. Microorganisms have remarkable catabolic potential, with genes, enzymes, and degradation pathways implicated in the process of biodegradation. A number of microbes, including Alcaligenes, Cellulosimicrobium, Microbacterium, Micrococcus, Methanospirillum, Aeromonas, Sphingobium, Flavobacterium, Rhodococcus, Aspergillus, Penecillium, Trichoderma, Streptomyces, Rhodotorula, Candida, and Aureobasidium, have been isolated and characterized, and have shown exceptional biodegradation potential for a variety of xenobiotic contaminants from soil/water environments. Microorganisms potentially utilize xenobiotic contaminants as carbon or nitrogen sources to sustain their growth and metabolic activities. Diverse microbial populations survive in harsh contaminated environments, exhibiting a significant biodegradation potential to degrade and transform pollutants. However, the study of such microbial populations requires a more advanced and multifaceted approach. Currently, multiple advanced approaches, including metagenomics, proteomics, transcriptomics, and metabolomics, are successfully employed for the characterization of pollutant-degrading microorganisms, their metabolic machinery, novel proteins, and catabolic genes involved in the degradation process. These technologies are highly sophisticated, and efficient for obtaining information about the genetic diversity and community structures of microorganisms. Advanced molecular technologies used for the characterization of complex microbial communities give an in-depth understanding of their structural and functional aspects, and help to resolve issues related to the biodegradation potential of microorganisms. This review article discusses the biodegradation potential of microorganisms and provides insights into recent advances and omics approaches employed for the specific characterization of xenobiotic-degrading microorganisms from contaminated environments.

Complete genome sequencing and comparative genome characterization of the lignocellulosic biomass degrading bacterium Pseudomonas stutzeri MP4687 from cattle rumen

We report the complete genome sequencing of novel Pseudomonas stutzeri strain MP4687 isolated from cattle rumen. Various strains of P. stutzeri have been reported from different environmental samples including oil-contaminated sites, crop roots, air, and human clinical samples, but not from rumen samples, which is being reported here for the first time. The genome of P. stutzeri MP4687 has a single replicon, 4.75 Mb chromosome and a G + C content of 63.45%. The genome encodes for 4,790 protein coding genes including 164 CAZymes and 345 carbohydrate processing genes. The isolate MP4687 harbors LCB hydrolyzing potential through endoglucanase (4.5 U/mL), xylanase (3.1 U/mL), β-glucosidase (3.3 U/mL) and β-xylosidase (1.9 U/mL) activities. The pangenome analysis further revealed that MP4687 has a very high number of unique genes (>2100) compared to other P. stutzeri genomes, which might have an important role in rumen functioning.

Omics era in forensic medicine: towards a new age

Background/aim

Forensic medicine and sciences is a multidisciplinary branch of science, which frequently benefit from novel technologies. State of the art omics technologies have begun to be performed in forensic medicine and sciences, particularly in postmortem interval, intoxication, drugs of abuse, diagnosis of diseases and cause of death. This review aims to discuss the role and use of great omics (metabolomics, proteomics, genomics and transcriptomics) in forensic sciences, in detail.

Materials and methods

A detailed review of related literature was performed, and studies were subdivided as per the type of omics.

Results and conclusion

Omics seems as a revolutionary step in forensic science and sure carries it towards a new age. The number of forensic studies utilizing omics steadily increases in last years. Omics strategies should be used together in order to gather more accurate and certain data. Additional studies need to be performed to incorporate omics into routine forensic methodology.

Characterization of Bacterial and Fungal Assemblages From Historically Contaminated Metalliferous Soils Using Metagenomics Coupled With Diffusion Chambers and Microbial Traps

The majority of environmental microbiomes are not amenable to cultivation under standard laboratory growth conditions and hence remain uncharacterized. For environmental applications, such as bioremediation, it is necessary to isolate microbes performing the desired function, which may not necessarily be the fast growing or the copiotroph microbiota. Toward this end, cultivation and isolation of microbial strains using diffusion chambers (DC) and/or microbial traps (MT) have both been recently demonstrated to be effective strategies because microbial enrichment is facilitated by soil nutrients and not by synthetically defined media, thus simulating their native habitat. In this study, DC/MT chambers were established using soils collected from two US Department of Energy (DOE) sites with long-term history of heavy metal contamination, including mercury (Hg). To characterize the contamination levels and nutrient status, soils were first analyzed for total mercury (THg), methylmercury (MeHg), total carbon (TC), total nitrogen (TN), and total phosphorus (TP). Multivariate statistical analysis on these measurements facilitated binning of soils under high, medium and low levels of contamination. Bacterial and fungal microbiomes that developed within the DC and MT chambers were evaluated using comparative metagenomics, revealing Chthoniobacter, Burkholderia and Bradyrhizobium spp., as the predominant bacteria while Penicillium, Thielavia, and Trichoderma predominated among fungi. Many of these core microbiomes were also retrieved as axenic isolates. Furthermore, canonical correspondence analysis (CCA) of biogeochemical measurements, metal concentrations and bacterial communities revealed a positive correlation of Chthoniobacter/Bradyrhizobium spp., to THg whereas Burkholderia spp., correlated with MeHg. Penicillium spp., correlated with THg whereas Trichoderma spp., and Aspergillus spp., correlated with MeHg, from the MT approach. This is the first metagenomics-based assessment, isolation and characterization of soil-borne bacterial and fungal communities colonizing the diffusion chambers (DC) and microbial traps (MT) established with long-term metal contaminated soils. Overall, this study provides proof-of-concept for the successful application of DC/MT based assessment of mercury resistant (HgR) microbiomes in legacy metal-contaminated soils, having complex contamination issues. Overall, this study brings out the significance of microbial communities and their relevance in context to heavy metal cycling for better stewardship and restoration of such historically contaminated systems.

Tailoring plant-associated microbial inoculants in agriculture: a roadmap for successful application

Plants are now recognized as metaorganisms which are composed of a host plant associated with a multitude of microbes that provide the host plant with a variety of essential functions to adapt to the local environment. Recent research showed the remarkable importance and range of microbial partners for enhancing the growth and health of plants. However, plant-microbe holobionts are influenced by many different factors, generating complex interactive systems. In this review, we summarize insights from this emerging field, highlighting the factors that contribute to the recruitment, selection, enrichment, and dynamic interactions of plant-associated microbiota. We then propose a roadmap for synthetic community application with the aim of establishing sustainable agricultural systems that use microbial communities to enhance the productivity and health of plants independently of chemical fertilizers and pesticides. Considering global warming and climate change, we suggest that desert plants can serve as a suitable pool of potentially beneficial microbes to maintain plant growth under abiotic stress conditions. Finally, we propose a framework for advancing the application of microbial inoculants in agriculture.

Alternative Strategies for Microbial Remediation of Pollutants via Synthetic Biology

Continuous contamination of the environment with xenobiotics and related recalcitrant compounds has emerged as a serious pollution threat. Bioremediation is the key to eliminating persistent contaminants from the environment. Traditional bioremediation processes show limitations, therefore it is necessary to discover new bioremediation technologies for better results. In this review we provide an outlook of alternative strategies for bioremediation via synthetic biology, including exploring the prerequisites for analysis of research data for developing synthetic biological models of microbial bioremediation. Moreover, cell coordination in synthetic microbial community, cell signaling, and quorum sensing as engineered for enhanced bioremediation strategies are described, along with promising gene editing tools for obtaining the host with target gene sequences responsible for the degradation of recalcitrant compounds. The synthetic genetic circuit and two-component regulatory system (TCRS)-based microbial biosensors for detection and bioremediation are also briefly explained. These developments are expected to increase the efficiency of bioremediation strategies for best results.

Omics for Bioprospecting and Drug Discovery from Bacteria and Microalgae

"Omics" represent a combinatorial approach to high-throughput analysis of biological entities for various purposes. It broadly encompasses genomics, transcriptomics, proteomics, lipidomics, and metabolomics. Bacteria and microalgae exhibit a wide range of genetic, biochemical and concomitantly, physiological variations owing to their exposure to biotic and abiotic dynamics in their ecosystem conditions. Consequently, optimal conditions for adequate growth and production of useful bacterial or microalgal metabolites are critically unpredictable. Traditional methods employ microbe isolation and 'blind'-culture optimization with numerous chemical analyses making the bioprospecting process laborious, strenuous, and costly. Advances in the next generation sequencing (NGS) technologies have offered a platform for the pan-genomic analysis of microbes from community and strain downstream to the gene level. Changing conditions in nature or laboratory accompany epigenetic modulation, variation in gene expression, and subsequent biochemical profiles defining an organism's inherent metabolic repertoire. Proteome and metabolome analysis could further our understanding of the molecular and biochemical attributes of the microbes under research. This review provides an overview of recent studies that have employed omics as a robust, broad-spectrum approach for screening bacteria and microalgae to exploit their potential as sources of drug leads by focusing on their genomes, secondary metabolite biosynthetic pathway genes, transcriptomes, and metabolomes. We also highlight how recent studies have combined molecular biology with analytical chemistry methods, which further underscore the need for advances in bioinformatics and chemoinformatics as vital instruments in the discovery of novel bacterial and microalgal strains as well as new drug leads.