Advances in Metagenomics and Its Application in Environmental Microorganisms

Future directions for early detection of fracture related infections

Introduction

Fracture related infection (FRI) refers to pathogens infecting a fracture site and hence impeding fracture healing. It is a significant complication that carries substantial disease burden and socio-economic costs, but has had limited scientific development. Hence, this paper will review the existing strategies for early detection of FRI, in the form of serum markers, molecular diagnostics and imaging modalities, and further discuss potential future directions for improved detection of FRI.

Existing Strategies for Diagnosis of FRI

The Anti-infection Global Expert Committee (AIGEC) developed a consensus definition for FRI in 2017, which includes confirmatory and suggestive criteria for diagnosis of FRI. Existing strategies for diagnosis include clinical, laboratory, histopathological, microbiological and radiological investigations.

Future Directions for Early Detection of FRI

With increasing recognition of FRI, early detection is crucial for early treatment to be enforced. We have identified potential areas for future development in diagnostics for early detection of FRI, which are discussed in this manuscript. They include inflammatory cytokines, serum calcium levels, platelet count, improved management of histopathological and microbiological specimens, metagenomics, wound biomarkers, gut microbiota analysis, and novel imaging technologies.

Detection value of third-generation sequencing to identify the pathogenic organisms in prosthetic joint infection

To compare the detection value of third-generation sequencing (TGS) with pathogenic microbial culture in prosthetic joint infection (PJI). Arthrocentesis was performed on 29 patients who underwent hip and knee revision surgeries. In the PJI group, TGS detected 85.71 % of positive cases, while pathogenic microbial culture detected only 42.85 %. TGS identified 17 different pathogenic microorganisms, including Staphylococcus epidermidis, Staphylococcus aureus, Streptococcus lactis, and Mycobacterium tuberculosis complex. In the loosening group, TGS was positive in one patient, while microbial culture was negative in all cases. TGS showed higher sensitivity (85.71 % vs. 42.85 %), comparable specificity (93.33 % vs. 100 %), and similar positive predictive value (92.31 % vs. 100 %) compared to culture.However, TGS had a higher negative predictive value (87.5 % vs. 65.22 %).Additionally, TGS provided faster results (mean time 23.8±3.6 h) compared to microbial culture (mean time 108.0±9.4 h).These findings suggest that TGS holds promise for detecting pathogenic microorganisms in PJI and has potential for clinical application.

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.

Metagenomics approaches in unveiling the dynamics of Plant Growth-Promoting Microorganisms (PGPM) vis-à-vis Phytophthora sp. suppression in various crop ecological systems

Phytophthora species are destructive pathogens causing yield losses in different ecological systems, such as potato, black pepper, pepper, avocado, citrus, and tobacco. The diversity of plant growth-promoting microorganisms (PGPM) plays a crucial role in disease suppression. Knowledge of metagenomics approaches is essential for assessing the dynamics of PGPM and Phytophthora species across various ecosystems, facilitating effective management strategies for better crop protection. This review discusses the dynamic interplay between PGPM and Phytophthora sp. using metagenomics approaches that sheds light on the potential of PGPM strains tailored to specific crop ecosystems to bolster pathogen suppressiveness.

Understanding the Effect of Compound Probiotics on the Health of Rabbits and Its Mechanisms Through Metagenomics

In this study, we investigated the effects of probiotics on growth performance, immunity, intestinal flora, and antioxidant capacity of rabbits. Three hundred New Zealand white rabbits were randomly divided into four groups. Groups A, B, C, and D were the lactobacillus group, compound probiotic group, control group, and antibiotic group, respectively. The results showed compared with the control group, the average weight of groups A, B, and D increased by 14.88%, 12.33%, and 11.97%, respectively. Moreover, the index of immune organs and the IgG and IgM in serum of group B were significantly increased (P < 0.05). Meanwhile, the activities of superoxide dismutase (SOD) in group B and catalase (CAT) in group A were significantly increased (P < 0.05). At week 5, the contents of rabbit cecum were taken for metagenome sequencing, and the results showed probiotics increased the relative abundance of Akkermansia, and decreased the relative abundance of Bacteroides. According to the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, we found probiotics could enrich metabolic pathways such as carbohydrates, amino acids, and lipids. According to the Comprehensive Antibiotic Resistance Database (CARD), we found antibiotic resistance ontology (ARO) in cecum mainly included β-lactamases, macrolide 2'-phosphotransferase II, and plasmid-mediated quinolone resistance protein. Among them, there were 1964, 2105, and 1982 types of ARO in group B, group D, and groups A and C, respectively. These results showed probiotics played a beneficial role in maintaining or enhancing the health and growth of rabbits and could replace antibiotics under certain feeding conditions.

Omics approaches in understanding the benefits of plant-microbe interactions

Plant-microbe interactions are pivotal for ecosystem dynamics and sustainable agriculture, and are influenced by various factors, such as host characteristics, environmental conditions, and human activities. Omics technologies, including genomics, transcriptomics, proteomics, and metabolomics, have revolutionized our understanding of these interactions. Genomics elucidates key genes, transcriptomics reveals gene expression dynamics, proteomics identifies essential proteins, and metabolomics profiles small molecules, thereby offering a holistic perspective. This review synthesizes diverse microbial-plant interactions, showcasing the application of omics in understanding mechanisms, such as nitrogen fixation, systemic resistance induction, mycorrhizal association, and pathogen-host interactions. Despite the challenges of data integration and ethical considerations, omics approaches promise advancements in precision intervention and resilient agricultural practices. Future research should address data integration challenges, enhance omics technology resolution, explore epigenomics, and understand plant-microbe dynamics under diverse conditions. In conclusion, omics technologies hold immense promise for optimizing agricultural strategies and fortifying resilient plant-microbe alliances, paving the way for sustainable agriculture and environmental stewardship.

The Impact of Metagenomics on Biocatalysis

In the ever-growing demand for sustainable ways to produce high-value small molecules, biocatalysis has come to the forefront of greener routes to these chemicals. As such, the need to constantly find and optimise suitable biocatalysts for specific transformations has never been greater. Metagenome mining has been shown to rapidly expand the toolkit of promiscuous enzymes needed for new transformations, without requiring protein engineering steps. If protein engineering is needed, the metagenomic candidate can often provide a better starting point for engineering than a previously discovered enzyme on the open database or from literature, for instance. In this review, we highlight where metagenomics has made substantial impact on the area of biocatalysis in recent years. We review the discovery of enzymes in previously unexplored or 'hidden' sequence space, leading to the characterisation of enzymes with enhanced properties that originate from natural selection pressures in native environments.

Metagenomics profiling of the microbial community and functional differences in solid-state fermentation vinegar starter (seed Pei) from different Chinese regions

Introduction

The starter used in solid-state fermentation (SSF) vinegar, known as seed Pei is a microbial inoculant from the previous batch that is utilized during the acetic acid fermentation stage. The seed Pei, which has a notable impact on vinegar fermentation and flavor, is under-researched with comparative studies on microorganisms.

Methods

Herein metagenomics was employed to reveal the microbes and their potential metabolic functions of four seed Pei from three regions in China.

Results

The predominant microbial taxa in all four starters were bacteria, followed by viruses, eukaryotes, and archaea, with Lactobacillus sp. or Acetobacter sp. as main functional taxa. The seed Pei used in Shanxi aged vinegar (SAV) and Sichuan bran vinegar (SBV) exhibited a higher similarity in microbial composition and distribution of functional genes, while those used in two Zhenjiang aromatic vinegar (ZAV) differed significantly. Redundancy analysis (RDA) of physicochemical factors and microbial communities indicated that moisture content, pH, and reducing sugar content are significant factors influencing microbial distribution. Moreover, seven metagenome-assembled genomes (MAGs) that could potentially represent novel species were identified.

Conclusions

There are distinctions in the microbiome and functional genes among different seed Pei. The vinegar starters were rich in genes related to carbohydrate metabolism. This research provides a new perspective on formulating vinegar fermentation starters and developing commercial fermentation agents for vinegar production.

Centrifuger: lossless compression of microbial genomes for efficient and accurate metagenomic sequence classification

Centrifuger is an efficient taxonomic classification method that compares sequencing reads against a microbial genome database. In Centrifuger, the Burrows-Wheeler transformed genome sequences are losslessly compressed using a novel scheme called run-block compression. Run-block compression achieves sublinear space complexity and is effective at compressing diverse microbial databases like RefSeq while supporting fast rank queries. Combining this compression method with other strategies for compacting the Ferragina-Manzini (FM) index, Centrifuger reduces the memory footprint by half compared to other FM-index-based approaches. Furthermore, the lossless compression and the unconstrained match length help Centrifuger achieve greater accuracy than competing methods at lower taxonomic levels.

Nitrite-dependent anaerobic methane oxidation (N-DAMO) in global aquatic environments: A review

The vast majority of processes in the carbon and nitrogen cycles are driven by microorganisms. The nitrite-dependent anaerobic oxidation of methane (N-DAMO) process links carbon and nitrogen cycles, offering a novel approach for the simultaneous reduction of methane emissions and nitrite pollution. However, there is currently no comprehensive summary of the current status of the N-DAMO process in natural aquatic environments. Therefore, our study aims to fill this knowledge gap by conducting a comprehensive review of the global research trends in N-DAMO processes in various aquatic environments (excluding artificial bioreactors). Our review mainly focused on molecular identification, global study sites, and their interactions with other elemental cycling processes. Furthermore, we performed a data integration analysis to unveil the effects of key environmental factors on the abundance of N-DAMO bacteria and the rate of N-DAMO process. By combining the findings from the literature review and data integration analysis, we proposed future research perspectives on N-DAMO processes in global aquatic environments. Our overarching goal is to advance the understanding of the N-DAMO process and its role in synergistically reducing carbon emissions and removing nitrogen. By doing so, we aim to make a significant contribution to the timely achievement of China's carbon peak and carbon neutrality targets.

Biological Basis of Breast Cancer-Related Disparities in Precision Oncology Era

Precision oncology is based on deep knowledge of the molecular profile of tumors, allowing for more accurate and personalized therapy for specific groups of patients who are different in disease susceptibility as well as treatment response. Thus, onco-breastomics is able to discover novel biomarkers that have been found to have racial and ethnic differences, among other types of disparities such as chronological or biological age-, sex/gender- or environmental-related ones. Usually, evidence suggests that breast cancer (BC) disparities are due to ethnicity, aging rate, socioeconomic position, environmental or chemical exposures, psycho-social stressors, comorbidities, Western lifestyle, poverty and rurality, or organizational and health care system factors or access. The aim of this review was to deepen the understanding of BC-related disparities, mainly from a biomedical perspective, which includes genomic-based differences, disparities in breast tumor biology and developmental biology, differences in breast tumors' immune and metabolic landscapes, ecological factors involved in these disparities as well as microbiomics- and metagenomics-based disparities in BC. We can conclude that onco-breastomics, in principle, based on genomics, proteomics, epigenomics, hormonomics, metabolomics and exposomics data, is able to characterize the multiple biological processes and molecular pathways involved in BC disparities, clarifying the differences in incidence, mortality and treatment response for different groups of BC patients.

A comparative analysis between next-generation sequencing and conventional culture method to detect empyema-associated microorganisms: A systematic review

Empyema poses a significant global health concern, yet identifying responsible bacteria remains elusive. Recent studies question the efficacy of conventional pleural fluid culture in accurately identifying empyema-causing bacteria. The aim of this study was to compare diagnostic capabilities of next-generation sequencing (NGS) with conventional pleural fluid culture in identifying empyema-causing bacteria. Five databases (Google Scholar, Science Direct, Cochrane, Research Gate, and PubMed) were used to search studies comparing conventional pleural fluid culture with NGS for identifying empyema-causing bacteria using keywords. Positive results identified through conventional pleural fluid culture and NGS were extracted. In addition, bacterial profiles identified by NGS were also documented. Joanna-Briggs Institute (JBI) critical appraisal tool was employed to assess quality of included studies. Descriptive analysis was employed to present outcome of interests. From five databases, three studies, with 354 patients, were included. Findings from three studies showed that NGS outperformed conventional pleural fluid culture in detecting empyema-causing bacteria even in culture-negative samples. Moreover, dominant bacterial profiles identified through NGS included Streptococcus pneumoniae, Staphylococcus aureus, and anaerobic bacteria. In conclusion, NGS outperforms conventional pleural fluid culture in detection empyema-causing bacteria, yet further studies with larger samples and broader bacterial profiles are needed to increase confidence and urgency in its adoption over conventional pleural fluid culture.

Bridging the gap between omics research and dental practice

AIM

The burgeoning field of omics research has witnessed exponential growth in both medicine and dentistry. However, despite more than a decade of advancements, clinical dentistry, particularly in Low- and Middle-Income Countries (LMICs), has seen limited progress in integrating omics-based approaches into routine practice. This review aims to provide a comprehensive overview of the integration of omics approaches in dentistry, focusing on the challenges and opportunities for translating research findings into clinical practice.

METHODS

we conducted a literature review using key databases to provide a brief overview of the history of genomics in dentistry. Additionally, we summarised recent breakthroughs in omics relevant to oral health practitioners, emphasising the inadequate translation of omics research into clinical practice.

RESULTS

Despite significant growth in omics research in both medicine and dentistry, its translation into routine clinical practice in dentistry remains limited. We summarise recent breakthroughs in omics and highlight the gap between research advancements and clinical implementation.

DISCUSSION AND CONCLUSION

The integration of omics approaches holds promise for enhancing diagnostics, personalised treatment strategies, and preventive measures in dental practice, ushering in a new era of precision oral healthcare. However, several challenges, including infrastructure limitations, cost-effectiveness, and education gaps, hinder the widespread adoption of omics-based approaches in clinical dentistry. A strong commitment to transforming dentistry is required to embrace this transition. This shift has the potential to revolutionise oral healthcare by advancing precision diagnostics and treatment strategies tailored to individual patient needs.

Molecular docking and metagenomics assisted mitigation of microplastic pollution

Microplastics, tiny, flimsy, and direct progenitors of principal and subsidiary plastics, cause environmental degradation in aquatic and terrestrial entities. Contamination concerns include irrevocable impacts, potential cytotoxicity, and negative health effects on mortals. The detection, recovery, and degradation strategies of these pollutants in various biota and ecosystems, as well as their impact on plants, animals, and humans, have been a topic of significant interest. But the natural environment is infested with several types of plastics, all having different chemical makeup, structure, shape, and origin. Plastic trash acts as a substrate for microbial growth, creating biofilms on the plastisphere surface. This colonizing microbial diversity can be glimpsed with meta-genomics, a culture-independent approach. Owing to its comprehensive description of microbial communities, genealogical evidence on unconventional biocatalysts or enzymes, genomic correlations, evolutionary profile, and function, it is being touted as one of the promising tools in identifying novel enzymes for the degradation of polymers. Additionally, computational tools such as molecular docking can predict the binding of these novel enzymes to the polymer substrate, which can be validated through in vitro conditions for its environmentally feasible applications. This review mainly deals with the exploration of metagenomics along with computational tools to provide a clearer perspective into the microbial potential in the biodegradation of microplastics. The computational tools due to their polymathic nature will be quintessential in identifying the enzyme structure, binding affinities of the prospective enzymes to the substrates, and foretelling of degradation pathways involved which can be quite instrumental in the furtherance of the plastic degradation studies.

"Smart markets": harnessing the potential of new technologies for endemic and emerging infectious disease surveillance in traditional food markets

Emerging and endemic zoonotic diseases continue to threaten human and animal health, our social fabric, and the global economy. Zoonoses frequently emerge from congregate interfaces where multiple animal species and humans coexist, including farms and markets. Traditional food markets are widespread across the globe and create an interface where domestic and wild animals interact among themselves and with humans, increasing the risk of pathogen spillover. Despite decades of evidence linking markets to disease outbreaks across the world, there remains a striking lack of pathogen surveillance programs that can relay timely, cost-effective, and actionable information to decision-makers to protect human and animal health. However, the strategic incorporation of environmental surveillance systems in markets coupled with novel pathogen detection strategies can create an early warning system capable of alerting us to the risk of outbreaks before they happen. Here, we explore the concept of "smart" markets that utilize continuous surveillance systems to monitor the emergence of zoonotic pathogens with spillover potential.IMPORTANCEFast detection and rapid intervention are crucial to mitigate risks of pathogen emergence, spillover and spread-every second counts. However, comprehensive, active, longitudinal surveillance systems at high-risk interfaces that provide real-time data for action remain lacking. This paper proposes "smart market" systems harnessing cutting-edge tools and a range of sampling techniques, including wastewater and air collection, multiplex assays, and metagenomic sequencing. Coupled with robust response pathways, these systems could better enable Early Warning and bolster prevention efforts.

On the limits of 16S rRNA gene-based metagenome prediction and functional profiling

Molecular profiling techniques such as metagenomics, metatranscriptomics or metabolomics offer important insights into the functional diversity of the microbiome. In contrast, 16S rRNA gene sequencing, a widespread and cost-effective technique to measure microbial diversity, only allows for indirect estimation of microbial function. To mitigate this, tools such as PICRUSt2, Tax4Fun2, PanFP and MetGEM infer functional profiles from 16S rRNA gene sequencing data using different algorithms. Prior studies have cast doubts on the quality of these predictions, motivating us to systematically evaluate these tools using matched 16S rRNA gene sequencing, metagenomic datasets, and simulated data. Our contribution is threefold: (i) using simulated data, we investigate if technical biases could explain the discordance between inferred and expected results; (ii) considering human cohorts for type two diabetes, colorectal cancer and obesity, we test if health-related differential abundance measures of functional categories are concordant between 16S rRNA gene-inferred and metagenome-derived profiles and; (iii) since 16S rRNA gene copy number is an important confounder in functional profiles inference, we investigate if a customised copy number normalisation with the rrnDB database could improve the results. Our results show that 16S rRNA gene-based functional inference tools generally do not have the necessary sensitivity to delineate health-related functional changes in the microbiome and should thus be used with care. Furthermore, we outline important differences in the individual tools tested and offer recommendations for tool selection.

Insights into the Microbiome and Antibiotic Resistance Genes from Hospital Environmental Surfaces: A Prime Source of Antimicrobial Resistance

Hospital environmental surfaces are potential reservoirs for transmitting hospital-associated pathogens. This study aimed to profile microbiomes and antibiotic resistance genes (ARGs) from hospital environmental surfaces using 16S rRNA amplicon and metagenomic sequencing at a tertiary teaching hospital in Malaysia. Samples were collected from patient sinks and healthcare staff counters at surgery and orthopaedic wards. The samples' DNA were subjected to 16S rRNA amplicon and shotgun sequencing to identify bacterial taxonomic profiles, antibiotic resistance genes, and virulence factor pathways. The bacterial richness was more diverse in the samples collected from patient sinks than those collected from staff counters. Proteobacteria and Verrucomicrobia dominated at the phylum level, while Bacillus, Staphylococcus, Pseudomonas, and Acinetobacter dominated at the genus level. Staphylococcus epidermidis and Staphylococcus aureus were prevalent on sinks while Bacillus cereus dominated the counter samples. The highest counts of ARGs to beta-lactam were detected, followed by ARGs against fosfomycin and cephalosporin. We report the detection of mcr-10.1 that confers resistance to colistin at a hospital setting in Malaysia. The virulence gene pathways that aid in antibiotic resistance gene transfer between bacteria were identified. Environmental surfaces serve as potential reservoirs for nosocomial infections and require mitigation strategies to control the spread of antibiotic resistance bacteria.

Advancing pathogen genomics in resource-limited settings

Genomic sequencing has emerged as a powerful tool to enhance early pathogen detection and characterization with implications for public health and clinical decision making. Although widely available in developed countries, the application of pathogen genomics among low-resource, high-disease burden settings remains at an early stage. In these contexts, tailored approaches for integrating pathogen genomics within infectious disease control programs will be essential to optimize cost efficiency and public health impact. We propose a framework for embedding pathogen genomics within national surveillance plans across a spectrum of surveillance and laboratory capacities. We adopt a public health approach to genomics and examine its application to high-priority diseases relevant in resource-limited settings. For each grouping, we assess the value proposition for genomics to inform public health and clinical decision-making, alongside its contribution toward research and development of novel diagnostics, therapeutics, and vaccines.

Centrifuger: lossless compression of microbial genomes for efficient and accurate metagenomic sequence classification

Centrifuger is an efficient taxonomic classification method that compares sequencing reads against a microbial genome database. In Centrifuger, the Burrows-Wheeler transformed genome sequences are losslessly compressed using a novel scheme called run-block compression. Run-block compression achieves sublinear space complexity and is effective at compressing diverse microbial databases like RefSeq while supporting fast rank queries. Combining this compression method with other strategies for compacting the Ferragina-Manzini (FM) index, Centrifuger reduces the memory footprint by half compared to other FM-index-based approaches. Furthermore, the lossless compression and the unconstrained match length help Centrifuger achieve greater accuracy than competing methods at lower taxonomic levels.

Leptospirosis-associated meningitis in a patient with sjögren's syndrome: a case report

BACKGROUND

Leptospirosis is a zoonotic disease that afflicts both humans and animals. It progresses from flu-like symptoms to more severe hepatic and renal failure, and may also lead to aseptic meningitis. Individuals with autoimmune diseases (ADs) are potentially more susceptible to Leptospirosis. Thus far, limited data has documented the association between Leptospirosis and autoimmune disorders.

CASE PRESENTATION

The patient had a definitive pathological diagnosis of Sjögren's syndrome (SS). Due to recurrent headaches, the patient sought consultation with a neurologist. Lumbar puncture revealed elevated white blood cells and protein levels in the cerebrospinal fluid, along with decreased glucose. Tuberculous meningitis was suspected. Radiographic imaging exhibited meningeal enhancement, ventricular enlargement, and hydrocephalus. The patient commenced treatment with anti-tuberculosis therapy and corticosteroids. Subsequently, high-throughput sequencing (HTS) of cerebrospinal fluid identified the presence of Leptospira interrogans. The patient was ultimately diagnosed with Leptospiral meningitis, and underwent antimicrobial and immunosuppressive therapy, resulting in stabilization of the condition and gradual symptom recovery.

CONCLUSIONS

The case highlights the challenges in diagnosing and managing leptospirosis-related meningitis in the presence of ADs and emphasizes the importance of utilizing HTS for accurate pathogen detection. The potential correlation between leptospirosis and SS warrants further investigation, as does the need for multidisciplinary involvement in treatment strategies for such complex cases.

Benchmarking Metagenomic Classifiers on Simulated Ancient and Modern Metagenomic Data

Taxonomic profiling of ancient metagenomic samples is challenging due to the accumulation of specific damage patterns on DNA over time. Although a number of methods for metagenome profiling have been developed, most of them have been assessed on modern metagenomes or simulated metagenomes mimicking modern metagenomes. Further, a comparative assessment of metagenome profilers on simulated metagenomes representing a spectrum of degradation depth, from the extremity of ancient (most degraded) to current or modern (not degraded) metagenomes, has not yet been performed. To understand the strengths and weaknesses of different metagenome profilers, we performed their comprehensive evaluation on simulated metagenomes representing human dental calculus microbiome, with the level of DNA damage successively raised to mimic modern to ancient metagenomes. All classes of profilers, namely, DNA-to-DNA, DNA-to-protein, and DNA-to-marker comparison-based profilers were evaluated on metagenomes with varying levels of damage simulating deamination, fragmentation, and contamination. Our results revealed that, compared to deamination and fragmentation, human and environmental contamination of ancient DNA (with modern DNA) has the most pronounced effect on the performance of each profiler. Further, the DNA-to-DNA (e.g., Kraken2, Bracken) and DNA-to-marker (e.g., MetaPhlAn4) based profiling approaches showed complementary strengths, which can be leveraged to elevate the state-of-the-art of ancient metagenome profiling.

Consolidated knowledge-guided computational pipeline for therapeutic intervention against bacterial biofilms - a review

Biofilm-associated bacterial infections attributed to multifactorial antimicrobial resistance have caused worldwide challenges in formulating successful treatment strategies. In search of accelerated yet cost-effective therapeutics, several researchers have opted for bioinformatics-based protocols to systemize targeted therapies against biofilm-producing strains. The present review investigated the up-to-date computational databases and servers dedicated to anti-biofilm research to design/screen novel biofilm inhibitors (antimicrobial peptides/phytocompounds/synthetic compounds) and predict their biofilm-inhibition efficacy. Scrutinizing the contemporary in silico methods, a consolidated approach has been highlighted, referred to as a knowledge-guided computational pipeline for biofilm-targeted therapy. The proposed pipeline has amalgamated prominently employed methodologies in genomics, transcriptomics, interactomics and proteomics to identify potential target proteins and their complementary anti-biofilm compounds for effective functional inhibition of biofilm-linked pathways. This review can pave the way for new portals to formulate successful therapeutic interventions against biofilm-producing pathogens.

Clinical metagenomics-assisted diagnosis of relapsed HIV-associated cryptococcal meningitis

To date, the identification of crypotococcal relapse remains clinically challenging as it often has similar manifestation with paradoxical immune reconstitution inflammatory syndrome. This study reports on the use of metagenomics assisted next generation sequencing to aid in diagnosing recurrent cryptococcal meningitis in an person living with HIV experiencing recurring symptoms, despite negative culture results for Cryptococcus neoformans in the cerebrospinal fluid. Although fungal culture was negative, when reads from metagenomic and metatranscriptomic sequencing performed on the Day 308 cerebrospinal fluid sample were mapped onto the genome from the Day 4 isolate, 589 specific reads were identified. NCBI BLAST search also revealed Cryptococcus-specific 18S/25S/28S ribosomal RNA, indicating a relapse of the disease.

Assessing the impact of meta-genomic tools on current cutting-edge genome engineering and technology

Metagenomics is defined as the study of the genome of the total microbiota found in nature and is often referred to as microbial environmental genomics because it entails the examination of a group of genetic components (genomes) from a diverse community of organisms in a particular setting. It is a sub-branch of omics technology that encompasses Deoxyribonucleic Acid (DNA), Ribonucleic acid (DNA), proteins, and various components associated with comprehensive analysis of all aspects of biological molecules in a system-wide manner. Clustered regularly interspaced palindromic repeats and its endonuclease, CRISPR-associated protein which forms a complex called CRISPR-cas9 technology, though it is a different technique used to make precise changes to the genome of an organism, it can be used in conjunction with metagenomic approaches to give a better, rapid, and more accurate description of genomes and sequence reads. There have been ongoing improvements in sequencing that have deepened our understanding of microbial genomes forever. From the time when only a small amount of gene could be sequenced using traditional methods (e.g., "the plus and minus" method developed by Allan and Sanger and the "chemical cleavage" method that is known for its use in the sequencing the phiX174 bacteriophage genome via radio-labeled DNA polymerase-primer in a polymerization reaction aided by polyacrylamide gel) to the era of total genomes sequencing which includes "sequencing-by-ligation" and the "sequencing-by-synthesis" that detects hydrogen ions when new DNA is synthesized (Second Generation) and then Next Generation Sequencing technologies (NGS). With these technologies, the Human Genome Project (HGP) was made possible. The study looks at recent advancements in metagenomics in plants and animals by examining findings from randomly selected research papers. All selected case studies examined the functional and taxonomical analysis of different microbial communities using high-throughput sequencing to generate different sequence reads. In animals, five studies indicated how Zebrafish, Livestock, Poultry, cattle, niches, and the human microbiome were exploited using environmental samples, such as soil and water, to identify microbial communities and their functions. It has also been used to study the microbiome of humans and other organisms, including gut microbiomes. Recent studies demonstrated how these technologies have allowed for faster and more accurate identification of pathogens, leading to improved disease diagnostics. They have also enabled the development of personalized medicine by allowing for the identification of genetic variations that can impact drug efficacy and toxicity. Continued advancements in sequencing techniques and the refinement of CRISPR-Cas9 tools offer even greater potential for transformative breakthroughs in scientific research and applications. On the other hand, metagenomic data are always large and uneasy to handle. The complexity of taxonomical profiling, functional annotation, and mechanisms of complex interaction still needs better bioinformatics tools. Current review focuses on better (e.g., AI-driven algorithms) tools that can predict metabolic pathways and interactions, and manipulate complex data to address potential bias for accurate interpretation.

Amplicon-Based Microbiome Profiling: From Second- to Third-Generation Sequencing for Higher Taxonomic Resolution

The 16S rRNA amplicon-based sequencing approach represents the most common and cost-effective strategy with great potential for microbiome profiling. The use of second-generation sequencing (NGS) technologies has led to protocols based on the amplification of one or a few hypervariable regions, impacting the outcome of the analysis. Nowadays, comparative studies are necessary to assess different amplicon-based approaches, including the full-locus sequencing currently feasible thanks to third-generation sequencing (TGS) technologies. This study compared three different methods to achieve the deepest microbiome taxonomic characterization: (a) the single-region approach, (b) the multiplex approach, covering several regions of the target gene/region, both based on NGS short reads, and (c) the full-length approach, which analyzes the whole length of the target gene thanks to TGS long reads. Analyses carried out on benchmark microbiome samples, with a known taxonomic composition, highlighted a different classification performance, strongly associated with the type of hypervariable regions and the coverage of the target gene. Indeed, the full-length approach showed the greatest discriminating power, up to species level, also on complex real samples. This study supports the transition from NGS to TGS for the study of the microbiome, even if experimental and bioinformatic improvements are still necessary.

Integration of multi-omics data to elucidate keystone unknown taxa within microbialite-forming ecosystems

Microbes continually shape Earth's biochemical and physical landscapes by inhabiting diverse metabolic niches. Despite the important role microbes play in ecosystem functioning, most microbial species remain unknown highlighting a gap in our understanding of structured complex ecosystems. To elucidate the relevance of these unknown taxa, often referred to as "microbial dark matter," the integration of multiple high throughput sequencing technologies was used to evaluate the co-occurrence and connectivity of all microbes within the community. Since there are no standard methodologies for multi-omics integration of microbiome data, we evaluated the abundance of "microbial dark matter" in microbialite-forming communities using different types meta-omic datasets: amplicon, metagenomic, and metatranscriptomic sequencing previously generated for this ecosystem. Our goal was to compare the community structure and abundances of unknown taxa within the different data types rather than to perform a functional characterization of the data. Metagenomic and metatranscriptomic data were input into SortMeRNA to extract 16S rRNA gene reads. The output, as well as amplicon sequences, were processed through QIIME2 for taxonomy analysis. The R package mdmnets was utilized to build co-occurrence networks. Most hubs presented unknown classifications, even at the phyla level. Comparisons of the highest scoring hubs of each data type using sequence similarity networks allowed the identification of the most relevant hubs within the microbialite-forming communities. This work highlights the importance of unknown taxa in community structure and proposes that ecosystem network construction can be used on several types of data to identify keystone taxa and their potential function within microbial ecosystems.

Metagenomics: An Effective Approach for Exploring Microbial Diversity and Functions

Various fields have been identified in the "omics" era, such as genomics, proteomics, transcriptomics, metabolomics, phenomics, and metagenomics. Among these, metagenomics has enabled a significant increase in discoveries related to the microbial world. Newly discovered microbiomes in different ecologies provide meaningful information on the diversity and functions of microorganisms on the Earth. Therefore, the results of metagenomic studies have enabled new microbe-based applications in human health, agriculture, and the food industry, among others. This review summarizes the fundamental procedures on recent advances in bioinformatic tools. It also explores up-to-date applications of metagenomics in human health, food study, plant research, environmental sciences, and other fields. Finally, metagenomics is a powerful tool for studying the microbial world, and it still has numerous applications that are currently hidden and awaiting discovery. Therefore, this review also discusses the future perspectives of metagenomics.

Bacterial Extracellular Vesicles: A Candidate Molecule for the Diagnosis and Treatment of Allergic Diseases

Extracellular vesicles (EVs) are an end product released from almost all living cells such as eukaryotic cells and bacteria. These membrane vesicles containing proteins, lipids, and nucleic acids are mainly involved in intracellular communications through the transfer of their components from donor to acceptor cells. Moreover, EVs have been implicated in many functions in response to environmental changes, contributing to health and disease; bacterial EVs depending on their specific parental bacterium have diverse effects on immune responses to play a beneficial or pathogenic role in patients with various allergic and immunologic diseases. As bacterial EVs are a completely new area of investigation in this field, we highlight our current understanding of bacterial EVs and discuss their diagnostic and therapeutic potentials (as immunomodulators) for targeting asthma and atopic dermatitis.

The Landscape of Global Ocean Microbiome: From Bacterioplankton to Biofilms

The development of metagenomics has opened up a new era in the study of marine microbiota, which play important roles in biogeochemical cycles. In recent years, the global ocean sampling expeditions have spurred this research field toward a deeper understanding of the microbial diversities and functions spanning various lifestyles, planktonic (free-living) or sessile (biofilm-associated). In this review, we deliver a comprehensive summary of marine microbiome datasets generated in global ocean expeditions conducted over the last 20 years, including the Sorcerer II GOS Expedition, the Tara Oceans project, the bioGEOTRACES project, the Micro B3 project, the Bio-GO-SHIP project, and the Marine Biofilms. These datasets have revealed unprecedented insights into the microscopic life in our oceans and led to the publication of world-leading research. We also note the progress of metatranscriptomics and metaproteomics, which are confined to local marine microbiota. Furthermore, approaches to transforming the global ocean microbiome datasets are highlighted, and the state-of-the-art techniques that can be combined with data analyses, which can present fresh perspectives on marine molecular ecology and microbiology, are proposed.

Unveiling the Human Gastrointestinal Tract Microbiome: The Past, Present, and Future of Metagenomics

Over 10¹⁴ symbiotic microorganisms are present in a healthy human body and are responsible for the synthesis of vital vitamins and amino acids, mediating cellular pathways and supporting immunity. However, the deregulation of microbial dynamics can provoke diverse human diseases such as diabetes, human cancers, cardiovascular diseases, and neurological disorders. The human gastrointestinal tract constitutes a hospitable environment in which a plethora of microbes, including diverse species of archaea, bacteria, fungi, and microeukaryotes as well as viruses, inhabit. In particular, the gut microbiome is the largest microbiome community in the human body and has drawn for decades the attention of scientists for its significance in medical microbiology. Revolutions in sequencing techniques, including 16S rRNA and ITS amplicon sequencing and whole genome sequencing, facilitate the detection of microbiomes and have opened new vistas in the study of human microbiota. Especially, the flourishing fields of metagenomics and metatranscriptomics aim to detect all genomes and transcriptomes that are retrieved from environmental and human samples. The present review highlights the complexity of the gastrointestinal tract microbiome and deciphers its implication not only in cellular homeostasis but also in human diseases. Finally, a thorough description of the widely used microbiome detection methods is discussed.

Combining Flow Cytometry and Metagenomics Improves Recovery of Metagenome-Assembled Genomes in a Cell Culture from Activated Sludge

The recovery of metagenome-assembled genomes is biased towards the most abundant species in a given community. To improve the identification of species, even if only dominant species are recovered, we investigated the integration of flow cytometry cell sorting with bioinformatics tools to recover metagenome-assembled genomes. We used a cell culture of a wastewater microbial community as our model system. Cells were separated based on fluorescence signals via flow cytometry cell sorting into sub-communities: dominant gates, low abundant gates, and outer gates into subsets of the original community. Metagenome sequencing was performed for all groups. The unsorted community was used as control. We recovered a total of 24 metagenome-assembled genomes (MAGs) representing 11 species-level genome operational taxonomic units (gOTUs). In addition, 57 ribosomal operational taxonomic units (rOTUs) affiliated with 29 taxa at species level were reconstructed from metagenomic libraries. Our approach suggests a two-fold increase in the resolution when comparing sorted and unsorted communities. Our results also indicate that species abundance is one determinant of genome recovery from metagenomes as we can recover taxa in the sorted libraries that are not present in the unsorted community. In conclusion, a combination of cell sorting and metagenomics allows the recovery of MAGs undetected without cell sorting.

Insights on the effects of antimicrobial and heavy metal usage on the antimicrobial resistance profiles of pigs based on culture-independent studies

Antimicrobial resistance is a global threat to human, animal, and environmental health. In pig production, antimicrobials and heavy metals such as zinc oxide are commonly used for treatment and prevention of disease. Nevertheless, the effects of antimicrobials and heavy metals on the porcine resistome composition and the factors influencing this resistance profile are not fully understood. Advances in technologies to determine the presence of antimicrobial resistance genes in diverse sample types have enabled a more complete understanding of the resistome and the factors which influence its composition. The aim of this review is to provide a greater understanding of the influence of antimicrobial and heavy metal usage on the development and transmission of antimicrobial resistance on pig farms. Furthermore, this review aims to identify additional factors that can affect the porcine resistome. Relevant literature that used high-throughput sequencing or quantitative PCR methods to examine links between antimicrobial resistance and antimicrobial and heavy metal use was identified using a systematic approach with PubMed (NCBI), Scopus (Elsevier), and Web of Science (Clarivate Analytics) databases. In total, 247 unique records were found and 28 publications were identified as eligible for inclusion in this review. Based on these, there is clear evidence that antimicrobial and heavy metal use are positively linked with antimicrobial resistance in pigs. Moreover, associations of genes conferring antimicrobial resistance with mobile genetic elements, the microbiome, and the virome were reported, which were further influenced by the host, the environment, or the treatment itself.

Construction of Small-Insert and Large-Insert Metagenomic Libraries

The vast majority of the Earth's biological diversity are hidden in uncultured and yet uncharacterized microbial genomes. The construction of metagenomic libraries is one cultivation-independent molecular approach to assess this unexplored genetic reservoir. High numbers of novel biocatalysts have been identified by function-based or sequence-based screening of metagenomic libraries derived from various environments. Here, we describe detailed protocols for the construction of metagenomic small-insert and large-insert libraries in plasmids and fosmids, respectively, from environmental DNA.

Tool and techniques study to plant microbiome current understanding and future needs: an overview

Microorganisms are present in the universe and they play role in beneficial and harmful to human life, society, and environments. Plant microbiome is a broad term in which microbes are present in the rhizo, phyllo, or endophytic region and play several beneficial and harmful roles with the plant. To know of these microorganisms, it is essential to be able to isolate purification and identify them quickly under laboratory conditions. So, to improve the microbial study, several tools and techniques such as microscopy, rRNA, or rDNA sequencing, fingerprinting, probing, clone libraries, chips, and metagenomics have been developed. The major benefits of these techniques are the identification of microbial community through direct analysis as well as it can apply in situ. Without tools and techniques, we cannot understand the roles of microbiomes. This review explains the tools and their roles in the understanding of microbiomes and their ecological diversity in environments.

Systematic review and critical reflection on the isolation and identification methods for spoilage associated bacteria in fresh marine fish

Consumers demand more fresh, safe, and high-quality food. As this is partiallycorrelated to the microbial profile, several microbiological examination tools are available. Incontrast to meat, no microbiological normalized methods to assess the microbiological quality of fresh marine fish have been agreed on. As a result, studies on the detection and diversity of spoilage associated organisms (SAOs) in fish often apply various detection, isolation, and identification techniques. This complicates the comparison and interpretation of data reported, and often results in different or inconclusive results. Therefore, the present review aimed to present a critical overview of the isolation/cultivation and detection techniques currently applied in fish microbiology. After a comprehensive search in the PubMed, Web of Science and Scopus databases, a total of 111 studies fulfilled the review selection criteria. Results revealed that when relying on culture media for the isolation of SAOs in fish, it is essential to include a salt-containing medium next to plate count agar that is currently used as the reference medium for the enumeration of bacteria on fish. In terms of identification, MALDI-TOF MS and 16S rRNA gene sequencing are currently the most promising tools, though other housekeeping genes should be targeted as well, and, the biggest challenge at this point is still the lack of comprehensive proteomic and sequence databases for SAOs. A full replacement of cultivation by next generation sequencing is difficult to recommend due to the absence of a standardized experimental methodology, especially for fish, and the relatively high sequencing costs. Additionally, a discrepancy between culture-dependent and independent methods in revealing the bacterial diversity, and abundancy, from marine fish was demonstrated by several authors. It is therefore recommended to consider both approaches as complements of one another, rather than substitutes, and to include them simultaneously to yield more complete results regarding the SAOs in fresh marine fish. As such, a thorough understanding of the biology of spoilage organisms and process will be obtained to prolong the shelf-life and deliver a high-quality product.

Microbes of traditional fermentation processes as synthetic biology chassis to tackle future food challenges

Microbial diversity is magnificent and essential to almost all life on Earth. Microbes are an essential part of every human, allowing us to utilize otherwise inaccessible resources. It is no surprise that humans started, initially unconsciously, domesticating microbes for food production: one may call this microbial domestication 1.0. Sourdough bread is just one of the miracles performed by microbial fermentation, allowing extraction of more nutrients from flour and at the same time creating a fluffy and delicious loaf. There are a broad range of products the production of which requires fermentation such as chocolate, cheese, coffee and vinegar. Eventually, with the rise of microscopy, humans became aware of microbial life. Today our knowledge and technological advances allow us to genetically engineer microbes - one may call this microbial domestication 2.0. Synthetic biology and microbial chassis adaptation allow us to tackle current and future food challenges. One of the most apparent challenges is the limited space on Earth available for agriculture and its major tolls on the environment through use of pesticides and the replacement of ecosystems with monocultures. Further challenges include transport and packaging, exacerbated by the 24/7 on-demand mentality of many customers. Synthetic biology already tackles multiple food challenges and will be able to tackle many future food challenges. In this perspective article, we highlight recent microbial synthetic biology research to address future food challenges. We further give a perspective on how synthetic biology tools may teach old microbes new tricks, and what standardized microbial domestication could look like.

Biosensors for rapid detection of bacterial pathogens in water, food and environment

Conventional techniques (e.g., culture-based method) for bacterial detection typically require a central laboratory and well-trained technicians, which may take several hours or days. However, recent developments within various disciplines of science and engineering have led to a major paradigm shift in how microorganisms can be detected. The analytical sensors which are widely used for medical applications in the literature are being extended for rapid and on-site monitoring of the bacterial pathogens in food, water and the environment. Especially, within the low-resource settings such as low and middle-income countries, due to the advantages of low cost, rapidness and potential for field-testing, their use is indispensable for sustainable development of the regions. Within this context, this paper discusses analytical methods and biosensors which can be used to ensure food safety, water quality and environmental monitoring. In brief, most of our discussion is focused on various rapid sensors including biosensors and microfluidic chips. The analytical performances such as the sensitivity, specificity and usability of these sensors, as well as a brief comparison with the conventional techniques for bacteria detection, form the core part of the discussion. Furthermore, we provide a holistic viewpoint on how future research should focus on exploring the synergy of different sensing technologies by developing an integrated multiplexed, sensitive and accurate sensors that will enable rapid detection for food safety, water and environmental monitoring.

Metagenomics: A Tool for Exploring Key Microbiome With the Potentials for Improving Sustainable Agriculture

Microorganisms are immense in nature and exist in every imaginable ecological niche, performing a wide range of metabolic processes. Unfortunately, using traditional microbiological methods, most microorganisms remain unculturable. The emergence of metagenomics has resolved the challenge of capturing the entire microbial community in an environmental sample by enabling the analysis of whole genomes without requiring culturing. Metagenomics as a non-culture approach encompasses a greater amount of genetic information than traditional approaches. The plant root-associated microbial community is essential for plant growth and development, hence the interactions between microorganisms, soil, and plants is essential to understand and improve crop yields in rural and urban agriculture. Although some of these microorganisms are currently unculturable in the laboratory, metagenomic techniques may nevertheless be used to identify the microorganisms and their functional traits. A detailed understanding of these organisms and their interactions should facilitate an improvement of plant growth and sustainable crop production in soil and soilless agriculture. Therefore, the objective of this review is to provide insights into metagenomic techniques to study plant root-associated microbiota and microbial ecology. In addition, the different DNA-based techniques and their role in elaborating plant microbiomes are discussed. As an understanding of these microorganisms and their biotechnological potentials are unlocked through metagenomics, they can be used to develop new, useful and unique bio-fertilizers and bio-pesticides that are not harmful to the environment.

Exploring Newer Biosynthetic Gene Clusters in Marine Microbial Prospecting

Marine microbes genetically evolved to survive varying salinity, temperature, pH, and other stress factors by producing different bioactive metabolites. These microbial secondary metabolites (SMs) are novel, have high potential, and could be used as lead molecule. Genome sequencing of microbes revealed that they have the capability to produce numerous novel bioactive metabolites than observed under standard in vitro culture conditions. Microbial genome has specific regions responsible for SM assembly, termed biosynthetic gene clusters (BGCs), possessing all the necessary genes to encode different enzymes required to generate SM. In order to augment the microbial chemo diversity and to activate these gene clusters, various tools and techniques are developed. Metagenomics with functional gene expression studies aids in classifying novel peptides and enzymes and also in understanding the biosynthetic pathways. Genome shuffling is a high-throughput screening approach to improve the development of SMs by incorporating genomic recombination. Transcriptionally silent or lower level BGCs can be triggered by artificially knocking promoter of target BGC. Additionally, bioinformatic tools like antiSMASH, ClustScan, NAPDOS, and ClusterFinder are effective in identifying BGCs of existing class for annotation in genomes. This review summarizes the significance of BGCs and the different approaches for detecting and elucidating BGCs from marine microbes.

Campylobacter Species, Microbiological Source Tracking and Risk Assessment of Bacterial pathogens

Campylobacter species continue to remain critical pathogens of public health interest. They are responsible for approximately 500 million cases of gastroenteritis per year worldwide. Infection occurs through the consumption of contaminated food and water. Microbial risk assessment and source tracking are crucial epidemiological strategies to monitor the outbreak of campylobacteriosis effectively. Various methods have been proposed for microbial source tracking and risk assessment, most of which rely on conventional microbiological techniques such as detecting fecal indicator organisms and other novel microbial source tracking methods, including library-dependent microbial source tracking and library-independent source tracking approaches. However, both the traditional and novel methods have their setbacks. For example, while the conventional techniques are associated with a poor correlation between indicator organism and pathogen presence, on the other hand, it is impractical to interpret qPCR-generated markers to establish the exact human health risks even though it can give information regarding the potential source and relative human risk. Therefore, this article provides up-to-date information on campylobacteriosis, various approaches for source attribution, and risk assessment of bacterial pathogens, including next-generation sequencing approaches such as shotgun metagenomics, which effectively answer the questions of potential pathogens are there and in what quantities.

Integrating 16S rRNA amplicon metagenomics and selective culture for developing thermophilic bacterial inoculants to enhance manure composting

Composting is an important method for treating and recycling organic waste, and the use of microbial inoculants can increase the efficiency of composting. Herein, we illustrate an approach that integrate 16S rRNA amplicon metagenomics and selective culture of thermophilic bacteria for the development of inoculants to improve manure composting. The 16S rRNA amplicon sequencing analysis revealed that Firmicutes and Actinobacteria were dominant in the composting mixture, and that different microbial hubs succeeded during the thermophilic stage. All isolated thermophilic bacteria were affiliated with the order Bacillales, such as Geobacillus, Bacillus, and Aeribacillus. These isolated thermophilic bacteria were grouped into 11 phylotypes, which shared ＞99% sequence identity to 0.15% to 5.32% of 16S rRNA reads by the amplicon sequencing. Three of these phylotypes transiently enriched during the thermophilic stage. Six thermophilic bacteria were selected from the three phylotypes to obtain seven microbial inoculants. Five out of seven of the microbial inoculants enhanced the thermophilic stage of composting by 16.9% to 52.2%. Three-dimensional excitation emission matrix analysis further revealed that two inoculants (Thermoactinomyces intermedius and Ureibacillus thermophilus) stimulated humification. Additionally, the 16S rRNA amplicon sequencing analysis revealed that inoculation with thermophilic bacteria enhanced the succession of the microbial community during composting. In conclusion, 16S rRNA amplicon metagenomics is a useful tool for the development of microbial inoculants to enhance manure composting.

Decoding the roles of extremophilic microbes in the anaerobic environments: Past, Present, and Future

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The inaccessible extreme environments harbor a large majority of anaerobic microbes which remain unknown.

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Anaerobic microbes are used in a variety of industrial applications.

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In the future, metagenomic-assisted techniques can be used to identify novel anaerobic microbes from the unexplored extreme environments.

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Genetic engineering can be used to enhance the efficiency of anaerobic microbes for various processes.

The genome of an organism is directly or indirectly correlated with its environment. Consequently, different microbes have evolved to survive and sustain themselves in a variety of environments, including unusual anaerobic environments. It is believed that their genetic material could have played an important role in the early evolution of their existence in the past. Presently, out of the uncountable number of microbes found in different ecosystems we have been able to discover only one percent of the total communities. A large majority of the microbial populations exists in the most unusual and extreme environments. For instance, many anaerobic bacteria are found in the gastrointestinal tract of humans, soil, and hydrothermal vents. The recent advancements in Metagenomics and Next Generation Sequencing technologies have improved the understanding of their roles in these environments. Presently, anaerobic bacteria are used in various industries associated with biofuels, fermentation, production of enzymes, vaccines, vitamins, and dairy products. This broad applicability brings focus to the significant contribution of their genomes in these functions. Although the anaerobic microbes have become an irreplaceable component of our lives, a major and important section of such anaerobic microbes still remain unexplored. Therefore, it can be said that unlocking the role of the microbial genomes of the anaerobes can be a noteworthy discovery not just for mankind but for the entire biosystem as well.