A practical guide to amplicon and metagenomic analysis of microbiome data

Efficient perchlorate reduction in microaerobic environment facilitated by partner methane oxidizers

The conventional perchlorate (ClO4-) reduction typically necessitates anaerobic conditions. However, in this study, we observed efficient ClO4- reduction using CH4 as the electron donor in a microaerobic environment. The maximum ClO4- removal flux of 2.18 g/m2·d was achieved in CH4-based biofilm. The kinetics of ClO4- reduction showed significant differences, with trace oxygen increasing the reduction rate of ClO4-, whereas oxygen levels exceeding 2 mg/L decelerated the ClO4- reduction. In the absence of exogenous oxygen, anaerobic methanotrophic (ANME) archaea contribute more than 80% electrons through the reverse methanogenesis pathway for ClO4- reduction. Simultaneously, microorganisms activate CH4 by utilizing oxygen generated from chlorite (ClO2-) disproportionation. In the presence of exogenous oxygen, methane oxidizers predominantly consume oxygen to drive the aerobic oxidation of methane. It is indicated that methane oxidizers and perchlorate reducing bacteria can form aggregates to resist external oxygen shocks and achieve efficient ClO4- reduction under microaerobic condition. These findings provide new insights into biological CH4 mitigation and ClO4- removal in hypoxic environment.

Holomics - a user-friendly R shiny application for multi-omics data integration and analysis

An organism's observable traits, or phenotype, result from intricate interactions among genes, proteins, metabolites and the environment. External factors, such as associated microorganisms, along with biotic and abiotic stressors, can significantly impact this complex biological system, influencing processes like growth, development and productivity. A comprehensive analysis of the entire biological system and its interactions is thus crucial to identify key components that support adaptation to stressors and to discover biomarkers applicable in breeding programs or disease diagnostics. Since the genomics era, several other 'omics' disciplines have emerged, and recent advances in high-throughput technologies have facilitated the generation of additional omics datasets. While traditionally analyzed individually, the last decade has seen an increase in multi-omics data integration and analysis strategies aimed at achieving a holistic understanding of interactions across different biological layers. Despite these advances, the analysis of multi-omics data is still challenging due to their scale, complexity, high dimensionality and multimodality. To address these challenges, a number of analytical tools and strategies have been developed, including clustering and differential equations, which require advanced knowledge in bioinformatics and statistics. Therefore, this study recognizes the need for user-friendly tools by introducing Holomics, an accessible and easy-to-use R shiny application with multi-omics functions tailored for scientists with limited bioinformatics knowledge. Holomics provides a well-defined workflow, starting with the upload and pre-filtering of single-omics data, which are then further refined by single-omics analysis focusing on key features. Subsequently, these reduced datasets are subjected to multi-omics analyses to unveil correlations between 2-n datasets. This paper concludes with a real-world case study where microbiomics, transcriptomics and metabolomics data from previous studies that elucidate factors associated with improved sugar beet storability are integrated using Holomics. The results are discussed in the context of the biological background, underscoring the importance of multi-omics insights. This example not only highlights the versatility of Holomics in handling different types of omics data, but also validates its consistency by reproducing findings from preceding single-omics studies.

Multiomics insights into the female reproductive aging

The human female reproductive lifespan significantly diminishes with age, leading to decreased fertility, reduced fertility quality and endocrine function disorders. While many aspects of aging in general have been extensively documented, the precise mechanisms governing programmed aging in the female reproductive system remain elusive. Recent advancements in omics technologies and computational capabilities have facilitated the emergence of multiomics deep phenotyping. Through the application and refinement of various high-throughput omics methods, a substantial volume of omics data has been generated, deepening our comprehension of the pathogenesis and molecular underpinnings of reproductive aging. This review highlights current and emerging multiomics approaches for investigating female reproductive aging, encompassing genomics, epigenomics, transcriptomics, proteomics, metabolomics, and microbiomics. We elucidate their influence on fundamental cell biology and translational research in the context of reproductive aging, address the limitations and current challenges associated with multiomics studies, and offer a glimpse into future prospects.

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.

Biochar application can enhance phosphorus solubilization by strengthening redox properties of humic reducing microorganisms during composting

Phosphorus (P) in nature mostly exists in an insoluble state, and humic reducing microorganisms (HRMs) can dissolve insoluble substances through redox properties. This study aimed to investigate the correlations between insoluble P and dominant HRMs amenable to individual culture during biochar composting. These analyses revealed that, in comparison to the control, biochar addition increased the relative abundance of dominant HRMs by 20.3% and decreased redox potential (Eh) levels by 15.4% hence, enhancing the moderately-labile-P and non-labile-P dissolution. The pathways underlying the observed effects were additionally assessed through structural equation modeling, revealing that biochar addition promoted insoluble P dissolution through both the direct effects of bacterial community structure as well as the direct effects of HRMs community structure and indirect effects based on Eh of HRMs community structure. This research offers a better understanding of the effect of HRMs on insoluble P during the composting process.

Microbial community dynamics and functional potentials in the conversion of oil palm wastes into biomethane

Oil palm processing generates substantial waste materials rich in organic content, posing various environmental challenges. Anaerobic digestion (AD), particularly for palm oil mill effluent (POME), offers a sustainable solution, by converting waste into valuable biomethane for thermal energy or electricity generation. The synergistic activities of the AD microbiota directly affect the biomethane production, and the microbial community involved in biomethane production in POME anaerobic digestion has been reported. The composition of bacterial and archaeal communities varies under different substrate and physicochemical conditions. This review discusses the characteristics of POME, explores the microbial members engaged in each stage of AD, and elucidates the impacts of substrate and physicochemical conditions on the microbial community dynamics, with a specific focus on POME. Finally, the review outlines current research needs and provides future perspectives on optimizing the microbial communities for enhanced biomethane production from oil palm wastes.

Impact of dietary fiber on gut microbiota composition, function and gut-brain-modules in healthy adults - a systematic review protocol

Background

The gut microbiota has been extensively implicated in health and disease. The functional outputs of the gut microbiota, such as microbial metabolites, are considered particularly important in this regard. Significant associations exist between alterations in the relative abundance of specific microbial taxa and mental health disorders. Dietary fiber has the potential to alter gut microbiota composition and function, modifying bacterial enzymatic function and the production of metabolites. As many taxa of microorganisms have enzymes capable of producing or degrading neurochemicals i.e. neuroactive gut brain modules, new predictive tools can be applied to existing datasets such as those harvested from dietary fiber interventions. We endeavor to perform a systematic review in order to identify studies reporting compositional gut microbiota alterations after interventions with dietary fiber in healthy individuals. We aim to also extract from the selected studies publicly available microbial genomic sequence datasets for reanalysis with a consistent bioinformatics pipeline, with the ultimate intention of identifying altered gut brain modules following dietary fiber interventions.

Methods

Interventional trials and randomized controlled studies that are originally published, including cross-over and non-crossover design and involving healthy adult humans will be included. A systematic search of PubMed/MEDLINE and EMBASE, two electronic databases, will be completed.

Discussion

Various types of dietary fiber have an impact on the gut microbiota composition, with some promoting the growth of particular taxa while others are reduced in relative abundance. Our search focuses on the impact of this food component on the microbiota of healthy individuals. Compositional gut microbial changes have been reported and our review will compile and update these observations after reanalysis of their datasets with a consistent bioinformatic pipeline. From this it may be possible to predict more detailed functional consequences in terms of neuroactive gut brain modules, of the compositional alterations in gut microbial taxa.

Dynamic root microbiome sustains soybean productivity under unbalanced fertilization

Root-associated microbiomes contribute to plant growth and health, and are dynamically affected by plant development and changes in the soil environment. However, how different fertilizer regimes affect quantitative changes in microbial assembly to effect plant growth remains obscure. Here, we explore the temporal dynamics of the root-associated bacteria of soybean using quantitative microbiome profiling (QMP) to examine its response to unbalanced fertilizer treatments (i.e., lacking either N, P or K) and its role in sustaining plant growth after four decades of unbalanced fertilization. We show that the root-associated bacteria exhibit strong succession during plant development, and bacterial loads largely increase at later stages, particularly for Bacteroidetes. Unbalanced fertilization has a significant effect on the assembly of the soybean rhizosphere bacteria, and in the absence of N fertilizer the bacterial community diverges from that of fertilized plants, while lacking P fertilizer impedes the total load and turnover of rhizosphere bacteria. Importantly, a SynCom derived from the low-nitrogen-enriched cluster is capable of stimulating plant growth, corresponding with the stabilized soybean productivity in the absence of N fertilizer. These findings provide new insights in the quantitative dynamics of the root-associated microbiome and highlight a key ecological cluster with prospects for sustainable agricultural management.

Profiling pathogenic protozoan and their functional pathways in wastewater using 18S rRNA and shotgun metagenomics

Despite extensive research, little is known about the composition of eukaryotic protists in environmental samples. This is due to low parasite concentrations, the complexity of parasite diversity, and a lack of suitable reference databases and standardized protocols. To bridge this knowledge gap, this study used 18S rRNA short amplicon and shotgun metagenomic sequencing approaches to profile protozoan microbial communities as well as their functional pathways in treated and untreated wastewater samples collected from different regions of South Africa. Results demonstrated that protozoan diversity (Shannon index P-value = 0.03) and taxonomic composition (PERMANOVA, P-value = 0.02) was mainly driven by the type of wastewater samples (treated & untreated) and geographic location. However, these WWTPs were also found to contain a core community of protozoan parasites. The untreated wastewater samples revealed a predominant presence of free-living, parasitic, and potentially pathogenic protists typically found in humans and animals, ranging from Alveolata (27 %) phylum (Apicomplexa and Ciliophora) to Excavata (3.88 %) (Discoba and Parasalia) and Amoebozoa (2.84 %) (Entamoeba and Acanthamoeba). Shotgun metagenomics analyses in a subset of the untreated wastewater samples confirmed the presence of public health-importance protozoa, including Cryptosporidium species (3.48 %), Entamoeba hystolitica (6.58 %), Blastocystis hominis (2.91 %), Naegleria gruberi (2.37 %), Toxoplasma gondii (1.98 %), Cyclospora cayetanensis (1.30 %), and Giardia intestinalis (0.31 %). Virulent gene families linked to pathogenic protozoa, such as serine/threonine protein phosphatase and mucin-desulfating sulfatase were identified. Additionally, enriched pathways included thiamine diphosphate biosynthesis III, heme biosynthesis, Methylerythritol 4-Phosphate Pathway, methyl erythritol phosphate (MEP), and pentose phosphate pathways. These findings suggest that protozoan pathogens may possess metabolic and growth potential within WWTPs, posing a severe risk of transmission to humans and animals if inadequately disinfected before release. This study provides a baseline for the future investigation of diverse protozoal communities in wastewater, which are of public health importance.

Techniques, procedures, and applications in microbiome analysis

Microbiota is a complex community of microorganisms living in a defined environment. Until the 20th century, knowledge of microbiota was partial, as the techniques available for their characterization were primarily based on bacteriological culture. In the last twenty years, the development of DNA sequencing technologies, multi-omics, and bioinformatics has expanded our understanding of microorganisms. We have moved from mainly considering them isolated disease-causing agents to recognizing the microbiota as an essential component of host biology. These techniques have shown that the microbiome plays essential roles in various host phenotypes, influencing development, physiology, reproduction, and evolution. This chapter provides researchers with a summary of the primary concepts, sample collection, experimental techniques, and bioinformatics analysis commonly used in microbiome research. The main features, applications in microbiome studies, and their advantages and limitations are included in each section.

Associations between vaginal microbiota and endometrial polypoid lesions in women of reproductive age: a cross-sectional study

RESEARCH QUESTION

What are the different characteristics of vaginal microbial composition between patients with endometrial polypoid lesions and controls?

DESIGN

This cohort study compared the pre-operative microbial compositions of vaginal samples in a cohort of 703 women with endometrial polypoid lesions [293 and 410 women diagnosed and not diagnosed with polyps pathologically (polyps group and not-polyps group, respectively] and 703 women in the control group. Bacterial abundance, diversity, differential taxa and microbial network structure were assessed using 16S rRNA gene sequencing. Predictive algorithms were used to determine the functional pathways of vaginal microbiota within the cohort.

RESULTS

The control group exhibited higher relative abundance of Lactobacillus crispatus in comparison with the polypoid lesions group (P = 0.0427). Beta diversity of vaginal microbiota differed significantly between the groups (P < 0.05). Comparing the polyps group with the not-polyps group, Leptotrichia spp. and Cutibacterium spp. were more abundant in the polyps group, and Fannyhessea spp., Acinetobacter spp. and Achromobacter spp. were more abundant in the not-polyps group. The control group exhibited higher abundance of Bifidobacterium spp., Achromobacter spp. and Escherichia/Shigella spp. (false discovery rate < 0.05). Furthermore, the polyps group and not-polyps group displayed more complex co-occurrence networks compared with the control group.

CONCLUSIONS

The results of this study provide compelling evidence supporting associations between vaginal microbiota and endometrial polypoid lesions, highlighting the potential relationship between a well-balanced vaginal microbial ecosystem and a healthy intrauterine environment.

Wekemo Bioincloud: A user-friendly platform for meta-omics data analyses

The increasing application of meta-omics approaches to investigate the structure, function, and intercellular interactions of microbial communities has led to a surge in available data. However, this abundance of human and environmental microbiome data has exposed new scalability challenges for existing bioinformatics tools. In response, we introduce Wekemo Bioincloud-a specialized platform for -omics studies. This platform offers a comprehensive analysis solution, specifically designed to alleviate the challenges of tool selection for users in the face of expanding data sets. As of now, Wekemo Bioincloud has been regularly equipped with 22 workflows and 65 visualization tools, establishing itself as a user-friendly and widely embraced platform for studying diverse data sets. Additionally, the platform enables the online modification of vector outputs, and the registration-independent personalized dashboard system ensures privacy and traceability. Wekemo Bioincloud is freely available at https://www.bioincloud.tech/.

[Advances in next-generation sequencing technology to analyze the microbiome of patients with chronic sinusitis]

Chronic rhinosinusitis （CRS） is a chronic inflammatory disease of the sinus mucosa, and the pathogenesis of CRS has not been fully elucidated, and the impact of dysbiosis of the microbiome in the nasal cavity and even in the gut on the pathogenesis of CRS remains controversial. Next-generation sequencing technology, a culture-independent high-throughput sequencing method, contributes to a comprehensive understanding of the CRS microbiome. This article reviews the progress of research on the relevance of bacteria and other microorganisms to CRS and the microbial characteristics of the sinus and intestinal tract of patients with CRS, introduces next-generation sequencing technologies for the study of the CRS microbiome, and discusses the therapeutic prospects of CRS and the possibility of probiotic therapy.

The role of microbiomes in gastrointestinal cancers: new insights

Gastrointestinal (GI) cancers constitute more than 33% of new cancer cases worldwide and pose a considerable burden on public health. There exists a growing body of evidence that has systematically recorded an upward trajectory in GI malignancies within the last 5 to 10 years, thus presenting a formidable menace to the health of the human population. The perturbations in GI microbiota may have a noteworthy influence on the advancement of GI cancers; however, the precise mechanisms behind this association are still not comprehensively understood. Some bacteria have been observed to support cancer development, while others seem to provide a safeguard against it. Recent studies have indicated that alterations in the composition and abundance of microbiomes could be associated with the progression of various GI cancers, such as colorectal, gastric, hepatic, and esophageal cancers. Within this comprehensive analysis, we examine the significance of microbiomes, particularly those located in the intestines, in GI cancers. Furthermore, we explore the impact of microbiomes on various treatment modalities for GI cancer, including chemotherapy, immunotherapy, and radiotherapy. Additionally, we delve into the intricate mechanisms through which intestinal microbes influence the efficacy of GI cancer treatments.

Microbiome-Mediated Strategies to Manage Major Soil-Borne Diseases of Tomato

The tomato (Solanum lycopersicum L.) is consumed globally as a fresh vegetable due to its high nutritional value and antioxidant properties. However, soil-borne diseases can severely limit tomato production. These diseases, such as bacterial wilt (BW), Fusarium wilt (FW), Verticillium wilt (VW), and root-knot nematodes (RKN), can significantly reduce the yield and quality of tomatoes. Using agrochemicals to combat these diseases can lead to chemical residues, pesticide resistance, and environmental pollution. Unfortunately, resistant varieties are not yet available. Therefore, we must find alternative strategies to protect tomatoes from these soil-borne diseases. One of the most promising solutions is harnessing microbial communities that can suppress disease and promote plant growth and immunity. Recent omics technologies and next-generation sequencing advances can help us develop microbiome-based strategies to mitigate tomato soil-borne diseases. This review emphasizes the importance of interdisciplinary approaches to understanding the utilization of beneficial microbiomes to mitigate soil-borne diseases and improve crop productivity.

Intratumoral microorganisms in tumors of the digestive system

Tumors of the digestive system pose a significant threat to human health and longevity. These tumors are associated with high morbidity and mortality rates, leading to a heavy economic burden on healthcare systems. Several intratumoral microorganisms are present in digestive system tumors, and their sources and abundance display significant heterogeneity depending on the specific tumor subtype. These microbes have a complex and precise function in the neoplasm. They can facilitate tumor growth through various mechanisms, such as inducing DNA damage, influencing the antitumor immune response, and promoting the degradation of chemotherapy drugs. Therefore, these microorganisms can be targeted to inhibit tumor progression for improving overall patient prognosis. This review focuses on the current research progress on microorganisms present in the digestive system tumors and how they influence the initiation, progression, and prognosis of tumors. Furthermore, the primary sources and constituents of tumor microbiome are delineated. Finally, we summarize the application potential of intratumoral microbes in the diagnosis, treatment, and prognosis prediction of digestive system tumors. Video Abstract.

The Peri-Implant Microbiome-A Possible Factor Determining the Success of Surgical Peri-Implantitis Treatment?

The objective was to assess the effect of peri-implantitis surgery on the peri-implant microbiome with a follow-up of one year. A total of 25 peri-implantitis patients in whom non-surgical treatment has failed to solve peri-implantitis underwent resective surgical treatment. Their peri-implant pockets were sampled prior to surgical treatment (T0) and one year post treatment (T12). The natural dentition was sampled to analyse similarities and differences with the peri-implantitis samples. Treatment success was recorded. The change in microbial relative abundance levels was evaluated. The microbiota was analysed by sequencing the amplified V3-V4 region of the 16S rRNA genes. Sequence data were binned to amplicon sequence variants that were assigned to bacterial genera. Group differences were analysed using principal coordinate analysis, Wilcoxon signed rank tests, and t-tests. Beta diversity analyses reported a significant separation between peri-implantitis and natural dentition samples on T0 and T12, along with significant separations between successfully and non-successfully treated patients. Eubacterium was significantly lower on T12 compared to T0 for the peri-implantitis samples. Treponema and Eubacterium abundance levels were significantly lower in patients with treatment success on T0 and T12 versus no treatment success. Therefore, lower baseline levels of Treponema and Eubacterium seem to be associated with treatment success of peri-implantitis surgery. This study might aid clinicians in determining which peri-implantitis cases might be suitable for treatment and give a prognosis with regard to treatment success.

Enhanced lignin degradation by Irpex lacteus through expanded sterilization further improved the fermentation quality and microbial community during the silage preservation process

Traditional autoclaving, slow degradation rate and preservation of biomass treated by fungi are the main factors restricting biological treatment. In our previous studies, strains with high efficiency and selective lignin degradation ability were obtained. To further solve the limiting factors of biological treatment, this paper proposed a composite treatment technology, which could replace autoclaves for fungal treatment and improve the preservation and utilization of fungal-pretreated straw. The autoclaved and expanded buckwheat straw were, respectively, degraded by Irpex lacteus for 14 days (CIL, EIL), followed by ensiling of raw materials (CK) and biodegraded straw of CIL and EIL samples with Lactobacillus plantarum for different days, respectively (CP, CIP, EIP). An expansion led to lactic acid bacteria, mold, and yeast of the samples below the detection line, and aerobic bacteria was significantly reduced, indicating a positive sterilization effect. Expansion before I. lacteus significantly enhanced lignin selective degradation by about 6%, and the absolute content of natural detergent solute was about 5% higher than that of the CIL. Moreover, EIL decreased pH by producing higher organic acids. The combination treatment created favorable conditions for ensiling. During ensiling, EIP silage produced high lactic acid about 26.83 g/kg DM and the highest acetic acid about 22.35 g/kg DM, and the pH value could be stable at 4.50. Expansion before I. lacteus optimized the microbial community for ensiling, resulting in EIP silage co-dominated by Lactobacillus, Pediococcus and Weissella, whereas only Lactobacillus was always dominant in CP and CIP silage. Clavispora gradually replaced Irpex in EIP silage, which potentially promoted lactic acid bacteria growth and acetic acid production. In vitro gas production (IVGP) in EIL was increased by 30% relative to CK and was higher than 24% in CIL. The role of expansion was more significant after ensiling, the IVGP in EIP was increased by 22% relative to CP, while that in CIP silage was only increased by 9%. Silage of fungal-treated samples reduced methane emissions by 28% to 31%. The study demonstrated that expansion provides advantages for fungal colonization and delignification, and further improves the microbial community and fermentation quality for silage, enhancing the nutrition and utilization value. This has practical application value for scaling up biological treatment and preserving the fungal-treated lignocellulose.

Structure and assembly process of fungal communities in the Yangtze River Estuary

Marine fungi are essential for the ecological function of estuarine ecosystems. However, limited studies have reported on the structure and assembly pattern of the fungal communities in estuaries. The purpose of this study is to reveal the structure and the ecological process of the fungal community in the Yangtze River Estuary (YRE) by using the amplicon sequencing method. Phyla of Ascomycota, Basidiomycota, and Chytridiomycota were dominant in the seawater and sediment samples from YRE. The null model analysis, community-neutral community model (NCM), and phylogenetic normalized stochasticity ratio (pNST) showed that the stochastic process dominated the assembly of fungal communities in YRE. Drift and homogeneous dispersal were the predominant stochastic processes for the fungal community assembly in seawater and sediment samples, respectively. The co-occurrence network analysis showed that fungal communities were more complex and closely connected in the sediment than in the seawater samples. Phyla Ascomycota, Basidiomycota, and Mucoromycota were the potential keystone taxa in the network. These findings demonstrated the importance of stochastic processes for the fungal community assembly, thereby widening our knowledge of the community structure and dynamics of fungi for future study and utilization in the YRE ecosystem.

Unravelling the enigma of the human microbiome: Evolution and selection of sequencing technologies

The human microbiome plays a crucial role in maintaining health, with advances in high-throughput sequencing technology and reduced sequencing costs triggering a surge in microbiome research. Microbiome studies generally incorporate five key phases: design, sampling, sequencing, analysis, and reporting, with sequencing strategy being a crucial step offering numerous options. Present mainstream sequencing strategies include Amplicon sequencing, Metagenomic Next-Generation Sequencing (mNGS), and Targeted Next-Generation Sequencing (tNGS). Two innovative technologies recently emerged, namely MobiMicrobe high-throughput microbial single-cell genome sequencing technology and 2bRAD-M simplified metagenomic sequencing technology, compensate for the limitations of mainstream technologies, each boasting unique core strengths. This paper reviews the basic principles and processes of these three mainstream and two novel microbiological technologies, aiding readers in understanding the benefits and drawbacks of different technologies, thereby guiding the selection of the most suitable method for their research endeavours.

The Diversity of Bacteriophages in the Human Gut

Bacteriophages, commonly referred to as phages, are viruses that infect bacteria and are among the most numerous microorganisms on the planet. They occur throughout nature occupying every habitat where their bacterial hosts can be found. Within these communities, phages are responsible for shaping the bacterial community structure and function through their interactions. Phages shape the community structure and function within the human gut but are also able to influence the human host. As such, there is increased interest in understanding the composition and activity of the gastrointestinal phages, although these studies have been hindered by the difficulties accompanying the study of the human gut. Here, we summarize the methods and findings pertaining to the diversity of the human gastrointestinal phages.

Metagenomic insights into jellyfish-associated microbiome dynamics during strobilation

Host-associated microbiomes can play key roles in the metamorphosis of animals. Most scyphozoan jellyfish undergo strobilation in their life cycles, similar to metamorphosis in classic bilaterians. The exploration of jellyfish microbiomes may elucidate the ancestral mechanisms and evolutionary trajectories of metazoan-microbe associations and interactions during metamorphosis. However, current knowledge of the functional features of jellyfish microbiomes remains limited. Here, we performed a genome-centric analysis of associated microbiota across four successive life stages (polyp, early strobila, advanced strobila, and ephyra) during strobilation in the common jellyfish Aurelia coerulea. We observed shifts in taxonomic and functional diversity of microbiomes across distinct stages and proposed that the low microbial diversity in ephyra stage may be correlated with the high expression of the host-derived antimicrobial peptide aurelin. Furthermore, we recovered 43 high-quality metagenome-assembled genomes and determined the nutritional potential of the dominant Vibrio members. Interestingly, we observed increased abundances of genes related to the biosynthesis of amino acids, vitamins, and cofactors, as well as carbon fixation during the loss of host feeding ability, indicating the functional potential of Aurelia-associated microbiota to support the synthesis of essential nutrients. We also identified several potential mechanisms by which jellyfish-associated microbes establish stage-specific community structures and maintain stable colonization in dynamic host environments, including eukaryotic-like protein production, bacterial secretion systems, restriction-modification systems, and clustered regularly interspaced short palindromic repeats-Cas systems. Our study characterizes unique taxonomic and functional changes in jellyfish microbiomes during strobilation and provides foundations for uncovering the ancestral mechanism of host-microbe interactions during metamorphosis.

Gut microbiome predicts gastrointestinal toxicity outcomes from chemoradiation therapy in patients with head and neck squamous cell carcinoma

OBJECTIVES

Chemoradiation (CRT) in patients with locally advanced head and neck squamous cell cancer (HNSCC) is associated with significant toxicities, including mucositis. The gut microbiome represents an emerging hallmark of cancer and a potentially important biomarker for CRT-related adverse events. This prospective study investigated the association between the gut microbiome composition and CRT-related toxicities in patients with HNSCC, including mucositis.

MATERIALS AND METHODS

Stool samples from patients diagnosed with locally advanced HNSCC were prospectively collected prior to CRT initiation and analyzed using shotgun metagenomic sequencing to evaluate gut microbiome composition at baseline. Concurrently, clinicopathologic data, survival outcomes and the incidence and grading of CRT-emergent adverse events were documented in all patients.

RESULTS

A total of 52 patients were included, of whom 47 had baseline stool samples available for metagenomic analysis. Median age was 62, 83 % patients were men and 54 % had stage III-IV disease. All patients developed CRT-induced mucositis, including 42 % with severe events (i.e. CTCAE v5.0 grade ≥ 3) and 25 % who required enteral feeding. With a median follow-up of 26.5 months, patients with severe mucositis had shorter overall survival (HR = 3.3, 95 %CI 1.0-10.6; p = 0.02) and numerically shorter progression-free survival (HR = 2.8, 95 %CI, 0.8-9.6; p = 0.09). The gut microbiome beta-diversity of patients with severe mucositis differed from patients with grades 1-2 mucositis (p = 0.04), with enrichment in Mediterraneibacter (Ruminococcus gnavus) and Clostridiaceae family members, including Hungatella hathewayi. Grade 1-2 mucositis was associated with enrichment in Eubacterium rectale, Alistipes putredinis and Ruminococcaceae family members. Similar bacterial profiles were observed in patients who required enteral feeding.

CONCLUSION

Patients who developed severe mucositis had decreased survival and enrichment in specific bacteria associated with mucosal inflammation. Interestingly, these same bacteria have been linked to immune checkpoint inhibitor resistance.

Metatranscriptomic characterization of six types of forensic samples and its potential application to body fluid/tissue identification: A pilot study

Microorganisms are potential markers for identifying body fluids (venous and menstrual blood, semen, saliva, and vaginal secretion) and skin tissue in forensic genetics. Existing published studies have mainly focused on investigating microbial DNA by 16 S rRNA gene sequencing or metagenome shotgun sequencing. We rarely find microbial RNA level investigations on common forensic body fluid/tissue. Therefore, the use of metatranscriptomics to characterize common forensic body fluids/tissue has not been explored in detail, and the potential application of metatranscriptomics in forensic science remains unknown. Here, we performed 30 metatranscriptome analyses on six types of common forensic sample from healthy volunteers by massively parallel sequencing. After quality control and host RNA filtering, a total of 345,300 unigenes were assembled from clean reads. Four kingdoms, 137 phyla, 267 classes, 488 orders, 985 families, 2052 genera, and 4690 species were annotated across all samples. Alpha- and beta-diversity and differential analysis were also performed. As a result, the saliva and skin groups demonstrated high alpha diversity (Simpson index), while the venous blood group exhibited the lowest diversity despite a high Chao1 index. Specifically, we discussed potential microorganism contamination and the "core microbiome," which may be of special interest to forensic researchers. In addition, we implemented and evaluated artificial neural network (ANN), random forest (RF), and support vector machine (SVM) models for forensic body fluid/tissue identification (BFID) using genus- and species-level metatranscriptome profiles. The ANN and RF prediction models discriminated six forensic body fluids/tissue, demonstrating that the microbial RNA-based method could be applied to BFID. Unlike metagenomic research, metatranscriptomic analysis can provide information about active microbial communities; thus, it may have greater potential to become a powerful tool in forensic science for microbial-based individual identification. This study represents the first attempt to explore the application potential of metatranscriptome profiles in forensic science. Our findings help deepen our understanding of the microorganism community structure at the RNA level and are beneficial for other forensic applications of metatranscriptomics.

Inoculation with plant growth-promoting rhizobacteria improves seagrass Thalassia hemprichii photosynthesis performance and shifts rhizosphere microbiome

Plant growth-promoting rhizobacteria (PGPR) inoculation is a crucial strategy for maintaining the sustainability of agriculture and presents a promising solution for seagrass ecological restoration in the face of disturbances. However, the possible roles and functions of PGPRs in the seagrass rhizosphere remain unclear. Here, we isolated rhizosphere bacterial strains from both reef and coastal regions and screened two PGPR isolates regarding their in vivo functional traits. Subsequently, we conducted microcosm experiments to elucidate how PGPR inoculation affected seagrass photosynthesis and shape within each rhizosphere microbiome. Both screened PGPR strains, Raoultella terrigena NXT28 and Bacillus aryabhattai XT37, excelled at expressing a specific subset of plant-beneficial functions and increased the photosynthetic rates of the seagrass host. PGPR inoculation not only decreased the abundance of sulfur-cycling bacteria, it also improved the abundance of putative iron-cycling bacteria in the seagrass rhizosphere. Strain XT37 successfully colonized the seagrass rhizosphere and displayed a leading role in microbial network structure. As a nitrogen-fixing bacteria, NXT28 showed potential to change the microbial nitrogen cycle with denitrification in the rhizosphere and alter dissimilatory and assimilatory nitrate reduction in bulk sediment. These findings have implications for the development of eco-friendly strategies aimed at exploiting microbial communities to confer sulfide tolerance in coastal seagrass ecosystem.

Changes in Gut Microbiota Associated with Parity in Large White Sows

As one of the most critical economic traits, the litter performance of sows is influenced by their parity. Some studies have indicated a connection between the gut microbiota and the litter performance of animals. In this study, we examined litter performance in 1363 records of different parities of Large White sows. We observed a marked decline in TNB (Total Number Born) and NBH (Number of Healthy Born) We observed a marked decline in TNB (Total Number Born) and NBH (Number of Healthy Born) among sows with parity 7 or higher. To gain a deeper understanding of the potential role of gut microbiota in this phenomenon, we conducted 16S rRNA amplicon sequencing of fecal DNA from 263 Large White sows at different parities and compared the changes in their gut microbiota with increasing parity. The results revealed that in comparison to sows with a parity from one to six, sows with a parity of seven or higher exhibited decreased alpha diversity in their gut microbiota. There was an increased proportion of pathogenic bacteria (such as Enterobacteriaceae, Streptococcus, and Escherichia-Shigella) and a reduced proportion of SCFA-producing families (such as Ruminococcaceae), indicating signs of inflammatory aging. The decline in sow function may be one of the primary reasons for the reduction in their litter performance.

Comparative Rumen Metagenome and CAZyme Profiles in Cattle and Buffaloes: Implications for Methane Yield and Rumen Fermentation on a Common Diet

A study was undertaken to compare the rumen microbial community composition, methane yield, rumen fermentation, and CAZyme profiles between cattle and buffaloes. The primary aim of this study was to ascertain the impact of the host species on the above when diet and environmental factors are fixed. A total of 43 phyla, 200 orders, 458 families, and 1722 microbial genera were identified in the study. Bacteroidetes was the most prominent bacterial phylum and constituted >1/3rd of the ruminal microbiota; however, their abundances were comparable between cattle and buffaloes. Firmicutes were the second most abundant bacteria, found to be negatively correlated with the Bacteroidetes. The abundances of Firmicutes as well as the F/B ratio were not different between the two host species. In this study, archaea affiliated with the nine phyla were identified, with Euryarchaeota being the most prominent. Like bacterial phyla, the abundances of Euryarchaeota methanogens were also similar between the cattle and buffaloes. At the order level, Methanobacteriales dominated the archaea. Methanogens from the Methanosarcinales, Methanococcales, Methanomicrobiales, and Methanomassiliicoccales groups were also identified, but at a lower frequency. Methanobrevibacter was the most prevalent genus of methanogens, accounting for approximately three percent of the rumen metagenome. However, their distribution was not different between the two host species. CAZymes affiliated with five classes, namely CBM, CE, GH, GT, and PL, were identified in the metagenome, where the GH class was the most abundant and constituted ~70% of the total CAZymes. The protozoal numbers, including Entodiniomorphs and Holotrichs, were also comparable between the cattle and buffaloes. Results from the study did not reveal any significant difference in feed intake, nutrient digestibility, and rumen fermentation between cattle and buffaloes fed on the same diet. As methane yield due to the similar diet composition, feed ingredients, rumen fermentation, and microbiota composition did not vary, these results indicate that the microbiota community structure and methane emissions are under the direct influence of the diet and environment, and the host species may play only a minor role until the productivity does not vary. More studies are warranted to investigate the effect of different diets and environments on microbiota composition and methane yield. Further, the impact of variable productivity on both the cattle and buffaloes when the diet and environmental factors are fixed needs to be ascertained.

Antibiotic resistance profiles of gut microbiota across various primate species in Guangxi

Introduction

Understanding the gut microbiota and antibiotic resistance gene (ARG) profiles in non-human primates (NHPs) is crucial for evaluating their potential impact on human health and the environment.

Methods

In this study, we performed metagenomic analysis of 203 primate fecal samples, including nine NHP species and humans, to comprehensively characterize their gut microbiota and ARGs.

Results

Our study reveals the prevailing phyla in primates as Firmicutes, Bacteroidetes, Euryarchaeota, and Proteobacteria. The captive NHPs exhibited higher ARG abundance compared to their wild counterparts, with tetracycline and beta-lactam resistance genes prevailing. Notably, ARG subtypes in Trachypithecus leucocephalus (T. leucocephalus) residing in karst limestone habitats displayed a more dispersed distribution compared to other species. Interestingly, ARG profiles of NHPs clustered based on geographic location and captivity status. Co-occurrence network analysis revealed intricate correlations between ARG subtypes and bacterial taxa. Procrustes analysis unveiled a significant correlation between ARGs and microbial phylogenetic community structure. Taxonomic composition analysis further highlighted differences in microbial abundance among NHPs and humans.

Discussion

Our study underscores the impact of lifestyle and geographical location on NHP gut microbiota and ARGs, providing essential insights into the potential risks posed by NHPs to antibiotic resistance dissemination. This comprehensive analysis enhances our understanding of the interplay between NHPs and the gut resistome, offering a critical reference for future research on antibiotic resistance and host-microbe interactions.

Long-read MinION™ sequencing of 16S and 16S-ITS-23S rRNA genes provides species-level resolution of Lactobacillaceae in mixed communities

The Lactobacillaceae are lactic acid bacteria harnessed to deliver important outcomes across numerous industries, and their unambiguous, species-level identification from mixed community environments is an important endeavor. Amplicon-based metataxonomics using short-read sequencing of partial 16S rRNA gene regions is widely used to support this, however, the high genetic similarity among Lactobacillaceae species restricts our ability to confidently describe these communities even at genus level. Long-read sequencing (LRS) of the whole 16S rRNA gene or the near complete rRNA operon (16S-ITS-23S) has the potential to improve this. We explored species ambiguity amongst Lactobacillaceae using in-silico tool RibDif2, which identified allele overlap when various partial and complete 16S rRNA gene and 16S-ITS-23S rRNA regions were amplified. We subsequently implemented LRS by MinION™ to compare the capacity of V3-V4, 16S and 16S-ITS-23S rRNA amplicons to accurately describe the diversity of a 20-species Lactobacillaceae mock community in practice. In-silico analysis identified more instances of allele/species overlap with V3-V4 amplicons (n = 43) compared to the 16S rRNA gene (n = 11) and partial (n = up to 15) or complete (n = 0) 16S-ITS-23S rRNA amplicons. With subsequent LRS of a DNA mock community, 80% of target species were identified using V3-V4 amplicons whilst the 16S rRNA gene and 16S-ITS-23S rRNA region amplicons resulted in 95 and 100% of target species being identified. A considerable reduction in false-positive identifications was also seen with 16S rRNA gene (n = 3) and 16S-ITS-23S rRNA region (n = 9) amplicons compared with V3-V4 amplicons (n = 43). Whilst the target species affected by allele overlap in V3-V4 and 16S rRNA gene sequenced mock communities were predicted by RibDif2, unpredicted species ambiguity was observed in 16S-ITS-23S rRNA sequenced communities. Considering the average nucleotide identity (ANI) between ambiguous species (~97%) and the basecall accuracy of our MinION™ sequencing protocol (96.4%), the misassignment of reads between closely related taxa is to be expected. With basecall accuracy exceeding 99% for recent MinION™ releases, the increased species-level differentiating power promised by longer amplicons like the 16S-ITS-23S rRNA region, may soon be fully realized.

Diversity and correlation analysis of different root exudates on the regulation of microbial structure and function in soil planted with Panax notoginseng

Introduction

Specific interactions between root exudates and soil microorganisms has been proposed as one of the reasons accounting for the continuous cropping obstacle (CCO) of Panax notoginseng. However, rotation of other crops on soils planted with P. notoginseng (SPP) did not show CCO, suggesting that root exudates of different crops differentially regulate soil microorganisms in SPP.

Methods

Here, we investigated the microbial community structure and specific interaction mechanisms of the root exudates of the four plant species, P. notoginseng (Pn), Zea mays (Zm), Nicotiana tabacum (Nt) and Perilla frutescens (Pf), in SPP by static soil culture experiment.

Results

The results showed that the chemical diversity of root exudates varied significantly among the four plant species. Pn had the highest number of unique root exudates, followed by Nt, Zm and Pf. Terpenoids, flavonoids, alkaloids and phenolic acids were the most abundant differentially accumulated metabolites (DAMs) in Pn, Nt, Zm and Pf, respectively. However, lipids were the most abundant common DAMs among Zm Nt and Pf. Pn root exudates decreased the relative abundance of bacteria, but increased that of fungi. While specific DAMs in Pn enriched Phenylobacterium_zucineum, Sphingobium_yanoikuyae, Ophiostoma_ulmi and functional pathways of Nucleotide excision repair, Streptomycin biosynthesis, Cell cycle-Caulobacter and Glycolysis/Gluconeogenesis, it inhibited Paraburkholderia _caledonica and Ralstonia_pickettii. However, common DAMs in Zm, Nt and Pf had opposite effects. Moreover, common DAMs in Zm, Nt and Pf enriched Ralstonia_pseudosolanacearum and functional pathway of Xylene degradation; unique DAMs in Zm enriched Talaromyces_purcureogeneus, while inhibiting Fusarium_tricinctum and functional pathways of Nucleotide excision repair and Alanine, aspartate and glutamate metabolism; unique DAMs in Pf enriched Synchytrium_taraxaci.

Discussion

The core strains identified that interact with different root exudates will provide key clues for regulation of soil microorganisms in P. notoginseng cultivation to alleviate CCO.

Sequence-based Functional Metagenomics Reveals Novel Natural Diversity of Functional CopA in Environmental Microbiomes

Exploring the natural diversity of functional genes/proteins from environmental DNA in high throughput remains challenging. In this study, we developed a sequence-based functional metagenomics procedure for mining the diversity of copper (Cu) resistance gene copA in global microbiomes, by combining the metagenomic assembly technology, local BLAST, evolutionary trace analysis (ETA), chemical synthesis, and conventional functional genomics. In total, 87 metagenomes were collected from a public database and subjected to copA detection, resulting in 93,899 hits. Manual curation of 1214 hits of high confidence led to the retrieval of 517 unique CopA candidates, which were further subjected to ETA. Eventually, 175 novel copA sequences of high quality were discovered. Phylogenetic analysis showed that almost all these putative CopA proteins were distantly related to known CopA proteins, with 55 sequences from totally unknown species. Ten novel and three known copA genes were chemically synthesized for further functional genomic tests using the Cu-sensitive Escherichia coli (ΔcopA). The growth test and Cu uptake determination showed that five novel clones had positive effects on host Cu resistance and uptake. One recombinant harboring copA-like 15 (copAL15) successfully restored Cu resistance of the host with a substantially enhanced Cu uptake. Two novel copA genes were fused with the gfp gene and expressed in E. coli for microscopic observation. Imaging results showed that they were successfully expressed and their proteins were localized to the membrane. The results here greatly expand the diversity of known CopA proteins, and the sequence-based procedure developed overcomes biases in length, screening methods, and abundance of conventional functional metagenomics.

Identification of gut microbiota dysbiosis in bullous pemphigoid under different disease activity

Bullous pemphigoid (BP) is a severe autoimmune blistering disease affecting patients' quality of life. Gut microbiota (GM) dysbiosis have been investigated to be associated with multiple autoimmune diseases. However, the relationship between GM and BP onset and remission remains to be established by a systematic study. We conducted a study that enrolled 24 patients with BP onset (BP group), 24 patients under remission stage (BP-R group) and 24 healthy controls (HC group). We applied 16S rRNA sequencing on faecal samples and revealed a separation of the microbiota structure. At the family level, Lachnospiraceae, Prevotellaceae and Veillonellaceae were more abundant in the HC and BP-R groups, while Bacteroidaceae, Ruminococcaceae and Enterobacteriaceae were more abundant in the BP group. Bugbase analysis revealed the potentially pathogenic bacteria had an increasing trend in the BP group compared with the HC group and this variation vanished in the BP-R group. At the amplicon sequence variants (ASV) level, Bacteroides ovatus (ASV40) and Veillonella dispar (ASV140) significantly decreased, while Prevotella copri (ASV54) increased in the BP group compared to the HC and BP-R groups. The HC group and BP-R group shared similar abundance. Furthermore, by correlation analysis, we investigated key ASVs correlated with clinical parameters and found some discriminate biomarkers between the BP and BP-R groups. Our study established a dynamic GM profile in BP patients under different disease activity, providing a new direction to understand the role of GM in BP pathogenesis and therapeutic effects.

Unveiling the microbiome during post-partum uterine infection: a deep shotgun sequencing approach to characterize the dairy cow uterine microbiome

BACKGROUND

The goal of this study was to assess the microbial ecology and diversity present in the uterus of post-partum dairy cows with and without metritis from 24 commercial California dairy farms using shotgun metagenomics. A set subset of 95 intrauterine swab samples, taken from a larger selection of 307 individual cow samples previously collected, were examined for α and β diversity and differential abundance associated with metritis. Cows within 21 days post-partum were categorized into one of three clinical groups during sample collection: control (CT, n = 32), defined as cows with either no vaginal discharge or a clear, non-purulent mucus vaginal discharge; metritis (MET, n = 33), defined as a cow with watery, red or brown colored, and fetid vaginal discharge; and purulent discharge cows (PUS, n = 31), defined as a non-fetid purulent or mucopurulent vaginal discharge.

RESULTS

All three clinical groups (CT, MET, and PUS) were highly diverse, with the top 12 most abundant genera accounting for 10.3%, 8.8%, and 10.1% of mean relative abundance, respectively. The α diversity indices revealed a lower diversity from samples collected from MET and PUS when compared to CT cows. PERMANOVA statistical testing revealed a significant difference (P adjusted < 0.01) in the diversity of genera between CT and MET samples (R2 = 0.112, P = 0.003) and a non-significant difference between MET and PUS samples (R2 = 0.036, P = 0.046). ANCOM-BC analysis revealed that from the top 12 most abundant genera, seven genera were increased in the natural log fold change (LFC) of abundance in MET when compared to CT samples: Bacteroides, Clostridium, Fusobacterium, Phocaeicola, Porphyromonas, Prevotella, and Streptococcus. Two genera, Dietzia and Microbacterium, were decreased in natural LFC of abundance when comparing MET (regardless of treatment) and CT, while no changes in natural LFC of abundance were observed for Escherichia, Histophilus, and Trueperella.

CONCLUSIONS

The results presented here, are the current deepest shotgun metagenomic analyses conducted on the bovine uterine microbiome to date (mean of 256,425 genus-level reads per sample). Our findings support that uterine samples from cows without metritis (CT) had increased α-diversity but decreased β-diversity when compared to metritis or PUS cows, characteristic of dysbiosis. In summary, our findings highlight that MET cows have an increased abundance of Bacteroides, Porphyromonas, and Fusobacterium when compared to CT and PUS, and support the need for further studies to better understand their potential causal role in metritis pathogenesis.

Nanopore-Sequencing Metabarcoding for Identification of Phytopathogenic and Endophytic Fungi in Olive (Olea europaea) Twigs

Metabarcoding approaches for the identification of plant disease pathogens and characterization of plant microbial populations constitute a rapidly evolving research field. Fungal plant diseases are of major phytopathological concern; thus, the development of metabarcoding approaches for the detection of phytopathogenic fungi is becoming increasingly imperative in the context of plant disease prognosis. We developed a multiplex metabarcoding method for the identification of fungal phytopathogens and endophytes in olive young shoots, using the MinION sequencing platform (Oxford Nanopore Technologies). Selected fungal-specific primers were used to amplify three different genomic DNA loci (ITS, beta-tubulin, and 28S LSU) originating from olive twigs. A multiplex metabarcoding approach was initially evaluated using healthy olive twigs, and further assessed with naturally infected olive twig samples. Bioinformatic analysis of basecalled reads was carried out using MinKNOW, BLAST+ and R programming, and results were also evaluated using the BugSeq cloud platform. Data analysis highlighted the approaches based on ITS and their combination with beta-tubulin as the most informative ones according to diversity estimations. Subsequent implementation of the method on symptomatic samples identified major olive pathogens and endophytes including genera such as Cladosporium, Didymosphaeria, Paraconiothyrium, Penicillium, Phoma, Verticillium, and others.

Spatio-temporal variation of bacterial community structure in two intertidal sediment types of Jiaozhou Bay

The intertidal sediment environment is dynamic and the biofilm bacterial community within it must constantly adapt, but an understanding of the differences in the biofilm bacterial community within sediments of different types is still relatively limited. The semi-enclosed Jiaozhou Bay has a temperate monsoon climate, with strong currents at the mouth of the bay. In this study, the structure of the bacterial community in Jiaozhou Bay sediment biofilms are described using high-throughput 16 S rRNA gene sequencing and the effects of temporal change and different sediment environment types are discussed. Alpha diversity was significantly higher in sandy samples than in muddy samples. Sandy sediments with increased heterogeneity promote bacterial aggregation. Beta diversity analysis showed significant differences between sediment types and between stations. Proteobacteria and Acidobacteria were significantly more abundant at ZQ, while Campilobacterota was significantly more abundant at LC. The relative abundances of Bacteroidetes, Campilobacterota, Firmicutes, and Chloroflexi were significantly higher in the muddy samples, while Actinobacteria and Proteobacteria were higher in the sandy samples. There were different phylum-level biomarkers between sediment types at different stations. There were also different patterns of functional enrichment in biogeochemical cycles between sediment types and stations with the former having more gene families that differed significantly, highlighting their greater role in determining bacterial function. Bacterial amplicon sequence variant variation between months was less than KEGG ortholog variation between months, presumably the temporal change had an impact on shaping the intertidal sediment bacterial community, although this was less clear at the gene family level. Random forest prediction yielded a combination of 43 family-level features that responded well to temporal change, reflecting the influence of temporal change on sediment biofilm bacteria.

Metagenomic sequencing reveals swine lung microbial communities and metagenome-assembled genomes associated with lung lesions-a pilot study

Low microbial biomass in the lungs, high host-DNA contamination and sampling difficulty limit the study on lung microbiome. Therefore, little is still known about lung microbial communities and their functions. Here, we perform a preliminary exploratory study to investigate the composition of swine lung microbial community using shotgun metagenomic sequencing and compare the microbial communities between healthy and severe-lesion lungs. We collected ten lavage-fluid samples from swine lungs (five from healthy lungs and five from severe-lesion lungs), and obtained their metagenomes by shotgun metagenomic sequencing. After filtering host genomic DNA contamination (93.5% ± 1.2%) in the lung metagenomic data, we annotated swine lung microbial communities ranging from four domains to 645 species. Compared with previous taxonomic annotation of the same samples by the 16S rRNA gene amplicon sequencing, it annotated the same number of family taxa but more genera and species. We next performed an association analysis between lung microbiome and host lung-lesion phenotype. We found three species (Mycoplasma hyopneumoniae, Ureaplasma diversum, and Mycoplasma hyorhinis) were associated with lung lesions, suggesting they might be the key species causing swine lung lesions. Furthermore, we successfully reconstructed the metagenome-assembled genomes (MAGs) of these three species using metagenomic binning. This pilot study showed us the feasibility and relevant limitations of shotgun metagenomic sequencing for the characterization of swine lung microbiome using lung lavage-fluid samples. The findings provided an enhanced understanding of the swine lung microbiome and its role in maintaining lung health and/or causing lung lesions.

Restoration Measures of Fencing after Tilling Guided Succession of Grassland Soil Microbial Community Structure to Natural Grassland in the Sanjiangyuan Agro-pasture Ecotone of the Qinghai-Tibetan Plateau

In the fragile Sanjiangyuan (SJY) agro-pasture ecotone of the Qinghai-Tibetan Plateau (QTP), planting and fencing have been used to alleviate grassland degradation and to provide high-quality grass seeds for the implementation of the project of "grain for green". The soil microbe is the major driving factor in maintaining plant productivity and soil nutrient cycling. However, few studies have explored the effects of planting and fencing on soil microorganisms in the SJY agro-pasture ecotone. We explored the effects of tilling (TG) and fencing after tilling (FTG) on soil microbial communities to reveal the effects of restoration measures on soil microbes and to provide a reference in assessing and improving ecosystem structure. The results showed that restoration measures increased soil microbial species diversity and significantly changed their community structure. We found, the microbial composition was more complex under FTG, and its fungal variability was higher and more similar to that of natural grassland. Additionally, restoration measures resulted in fungal co-occurrence network was more edges, higher density, larger diameter and more positive interactions. This was due to the management of the vegetation-soil microenvironment by FTG inducing a differentiation of microbial community structure. In summary, the implementation of FTG could change the microenvironment in the SJY agro-pasture ecotone, so that variation in the structure of microbial community tended toward that of natural grassland, and increased the stability of microbial co-occurrence network, which was more obvious in the fungal community. HIGHLIGHTS: • Restoration measures have changed the vegetation characteristics and soil microenvironment. • Fencing after tilling (FTG) has brought the microenvironment closer to natural grassland. • FTG significantly increased microbial unique ASVs. The number of fungal unique ASVs was similar to that of natural grassland. • FTG resulted in changes in microbial community structure towards natural grasslands and increased the stability of the microbial co-occurrence network, which was more apparent in the fungal community.

Dynamic interplay between nano-enabled agrochemicals and the plant-associated microbiome

The plant-associated microbiome is known to be a critical component for crop growth, nutrient acquisition, resistance to pathogens, and abiotic stress tolerance. Conventional approaches have been attempted to manipulate the plant-soil microbiome to improve plant performance; however, several issues have arisen, such as collateral negative impacts on microbiota composition. The lack of reliability and robustness of conventional techniques warrants efforts to develop novel alternative strategies. Nano-enabled approaches have emerged as promising platforms for enhancing agricultural sustainability and global food security. Specifically, the use of engineered nanomaterials (ENMs) as nanoscale agrochemicals has great potential to modulate the plant-associated microbiome. We review the dynamic interplay between nano-agrochemicals and the plant-associated microbiome for the safe development and use of nano-enabled microbiome engineering.

Bioinformatic approaches for studying the microbiome of fermented food

High-throughput DNA sequencing-based approaches continue to revolutionise our understanding of microbial ecosystems, including those associated with fermented foods. Metagenomic and metatranscriptomic approaches are state-of-the-art biological profiling methods and are employed to investigate a wide variety of characteristics of microbial communities, such as taxonomic membership, gene content and the range and level at which these genes are expressed. Individual groups and consortia of researchers are utilising these approaches to produce increasingly large and complex datasets, representing vast populations of microorganisms. There is a corresponding requirement for the development and application of appropriate bioinformatic tools and pipelines to interpret this data. This review critically analyses the tools and pipelines that have been used or that could be applied to the analysis of metagenomic and metatranscriptomic data from fermented foods. In addition, we critically analyse a number of studies of fermented foods in which these tools have previously been applied, to highlight the insights that these approaches can provide.

Seagrass Thalassia hemprichii and associated bacteria co-response to the synergistic stress of ocean warming and ocean acidification

Seagrass meadows play vital ecological roles in the marine ecosystem. Global climate change poses considerable threats to seagrass survival. However, it is unclear how seagrass and its associated bacteria will respond under future complex climate change scenarios. This study explored the effects of ocean warming (+2 °C) and ocean acidification (-0.4 units) on seagrass physiological indexes and bacterial communities (sediment and rhizosphere bacteria) of the seagrass Thalassia hemprichii during an experimental exposure of 30 days. Results demonstrated that the synergistic effect of ocean warming and ocean acidification differed from that of one single factor on seagrass and the associated bacterial community. The seagrass showed a weak resistance to ocean warming and ocean acidification, which manifested through the increase in the activity of typical oxidoreductase enzymes. Moreover, the synergistic effect of ocean warming and ocean acidification caused a significant decrease in seagrass's chlorophyll content. Although the bacterial community diversity exhibited higher resistance to ocean warming and ocean acidification, further bacterial functional analysis revealed the synergistic effect of ocean warming and ocean acidification led to significant increases in SOX-related genes abundance which potentially supported the seagrass in resisting climate stress by producing sulfates and oxidizing hydrogen sulfide. More stable bacterial communities were detected in the seagrass rhizosphere under combined ocean warming and ocean acidification. While for one single environmental stress, simpler networks were detected in the rhizosphere. In addition, the observed significant correlations between several modules of the bacterial community and the physiological indexes of the seagrass indicate the possible intimate interaction between seagrass and bacteria under ocean warming and ocean acidification. This study extends our understanding regarding the role of seagrass associated bacterial communities and sheds light on both the prediction and preservation of the seagrass meadow ecosystems in response to global climate change.

Application of Nanopore Sequencing in the Diagnosis and Treatment of Pulmonary Infections

This review provides an in-depth discussion of the development, principles and utility of nanopore sequencing technology and its diverse applications in the identification of various pulmonary pathogens. We examined the emergence and advancements of nanopore sequencing as a significant player in this field. We illustrate the challenges faced in diagnosing mixed infections and further scrutinize the use of nanopore sequencing in the identification of single pathogens, including viruses (with a focus on its use in epidemiology, outbreak investigation, and viral resistance), bacteria (emphasizing 16S targeted sequencing, rare bacterial lung infections, and antimicrobial resistance studies), fungi (employing internal transcribed spacer sequencing), tuberculosis, and atypical pathogens. Furthermore, we discuss the role of nanopore sequencing in metagenomics and its potential for unbiased detection of all pathogens in a clinical setting, emphasizing its advantages in sequencing genome repeat areas and structural variant regions. We discuss the limitations in dealing with host DNA removal, the inherent high error rate of nanopore sequencing technology, along with the complexity of operation and processing, while acknowledging the possibilities provided by recent technological improvements. We compared nanopore sequencing with the BioFire system, a rapid molecular diagnostic system based on polymerase chain reaction. Although the BioFire system serves well for the rapid screening of known and common pathogens, it falls short in the identification of unknown or rare pathogens and in providing comprehensive genome analysis. As technological advancements continue, it is anticipated that the role of nanopore sequencing technology in diagnosing and treating lung infections will become increasingly significant.

Analysis of oral microbiome on temporary anchorage devices under different periodontal conditions

BACKGROUND

Temporary anchorage devices (TADs) are maximum anchorages that have been widely used in orthodontic treatment. The aim of the study was to uncover whether a history of periodontitis would influence microbiome colonization on the TAD surface.

RESULTS

Patients were grouped by periodontal evaluations before the orthodontic treatment. Patients with healthy periodontal conditions were classified as the healthy group, and patients diagnosed with periodontitis stage II or even worse were classified as the periodontitis group. Scanning electron microscopy (SEM) was used to analyze the existence of biofilm on the surface of 4 TADs from the healthy group and 4 TADs from the periodontitis group. Fifteen TADs from the healthy group and 12 TADs from the periodontitis group were collected. The microorganisms on the surface of TADs were harvested and analyzed by 16S rRNA gene sequencing. α-diversity indices and β-diversity indices were calculated. Wilcoxon's test was used to determine differences between genera, species as well as KEGG functions. SEM analysis revealed bacteria colonization on the surface of TADs from both groups. Principal coordinate analysis (PCoA) based on β diversity revealed differential sample clusters depending on periodontal conditions (P < 0.01). When comparing specific genera, Fusobacterium, Porphyromonas, Saccharibacteria_(TM7)_[G-1], Dialister, Parvimonas, Fretibacterium, Treponema were more enriched in TADs in the periodontitis group. In the KEGG analysis, TADs in the periodontitis group demonstrated enriched microbial activities involved with translation, genetic information processing, metabolism, and cell motility.

CONCLUSIONS

This analysis elucidated the difference in total composition and function of TADs oral microorganisms between patients periodontally healthy and with periodontitis.

The best practice for microbiome analysis using R

With the gradual maturity of sequencing technology, many microbiome studies have published, driving the emergence and advance of related analysis tools. R language is the widely used platform for microbiome data analysis for powerful functions. However, tens of thousands of R packages and numerous similar analysis tools have brought major challenges for many researchers to explore microbiome data. How to choose suitable, efficient, convenient, and easy-to-learn tools from the numerous R packages has become a problem for many microbiome researchers. We have organized 324 common R packages for microbiome analysis and classified them according to application categories (diversity, difference, biomarker, correlation and network, functional prediction, and others), which could help researchers quickly find relevant R packages for microbiome analysis. Furthermore, we systematically sorted the integrated R packages (phyloseq, microbiome, MicrobiomeAnalystR, Animalcules, microeco, and amplicon) for microbiome analysis, and summarized the advantages and limitations, which will help researchers choose the appropriate tools. Finally, we thoroughly reviewed the R packages for microbiome analysis, summarized most of the common analysis content in the microbiome, and formed the most suitable pipeline for microbiome analysis. This paper is accompanied by hundreds of examples with 10,000 lines codes in GitHub, which can help beginners to learn, also help analysts compare and test different tools. This paper systematically sorts the application of R in microbiome, providing an important theoretical basis and practical reference for the development of better microbiome tools in the future. All the code is available at GitHub github.com/taowenmicro/EasyMicrobiomeR.

Machine learning: a powerful tool for identifying key microbial agents associated with specific cancer types

Machine learning (ML) includes a broad class of computer programs that improve with experience and shows unique strengths in performing tasks such as clustering, classification and regression. Over the past decade, microbial communities have been implicated in influencing the onset, progression, metastasis, and therapeutic response of multiple cancers. Host-microbe interaction may be a physiological pathway contributing to cancer development. With the accumulation of a large number of high-throughput data, ML has been successfully applied to the study of human cancer microbiomics in an attempt to reveal the complex mechanism behind cancer. In this review, we begin with a brief overview of the data sources included in cancer microbiomics studies. Then, the characteristics of the ML algorithm are briefly introduced. Secondly, the application progress of ML in cancer microbiomics is also reviewed. Finally, we highlight the challenges and future prospects facing ML in cancer microbiomics. On this basis, we conclude that the development of cancer microbiomics can not be achieved without ML, and that ML can be used to develop tumor-targeting microbial therapies, ultimately contributing to personalized and precision medicine.

The effects of arsenic on dechlorination of trichloroethene by consortium DH: Microbial response and resistance

Inorganic arsenic and organochlorines are frequently co-occurring contaminants in anoxic groundwater environments, and the bioremediation of their composite pollution has long been a rigorous predicament. Currently, the dechlorination behaviors and stress responses of microbial dechlorination consortia to arsenic are not yet fully understood. This study assessed the reductive dechlorination performance of a Dehalococcoides-bearing microcosm DH under gradient concentrations of arsenate [As(V)] or arsenite [As(III)] and investigated the response patterns of different functional microorganisms. Our results demonstrated that although the dechlorination rates declined with increasing arsenic concentrations in both As(III/V) scenarios, the inhibitory impact was more pronounced in As(III)-amended groups compared to As(V)-amended groups. Moreover, the vinyl chloride (VC)-to-ethene step was more susceptible to arsenic exposure compared to the trichloroethene (TCE)-to-dichloroethane (DCE) step, while high levels of arsenic exposure [e.g. As(III) > 75 μM] can induce significant accumulation of VC. Functional gene variations and microbial community analyses revealed that As(III/V) affected reductive dechlorination by directly inhibiting organohalide-respiring bacteria (OHRB) and indirectly inhibiting synergistic populations such as acetogens. Metagenomic results indicated that arsenic metabolic and efflux mechanisms were identical among different Dhc strains, and variations in arsenic uptake pathways were possibly responsible for their differential responses to arsenic exposures. By comparison, fermentative bacteria showed high potential for arsenic resistance due to their inherent advantages in arsenic detoxification and efflux mechanisms. Collectively, our findings expanded the understanding of the response patterns of different functional populations to arsenic stress in the dechlorinating consortium and provided insights into modifying bioremediation strategies at co-contaminated sites for furtherance.

Exercise and microbiome: From big data to therapy

Exercise is a vital component in maintaining optimal health and serves as a prospective therapeutic intervention for various diseases. The human microbiome, comprised of trillions of microorganisms, plays a crucial role in overall health. Given the advancements in microbiome research, substantial databases have been created to decipher the functionality and mechanisms of the microbiome in health and disease contexts. This review presents an initial overview of microbiomics development and related databases, followed by an in-depth description of the multi-omics technologies for microbiome. It subsequently synthesizes the research pertaining to exercise-induced modifications of the microbiome and diseases that impact the microbiome. Finally, it highlights the potential therapeutic implications of an exercise-modulated microbiome in intestinal disease, obesity and diabetes, cardiovascular disease, and immune/inflammation-related diseases.

Microbiome variations among age classes and diets of captive Asian elephants (Elephas maximus) in Thailand using full-length 16S rRNA nanopore sequencing

Asian elephant (Elephas maximus) is the national symbol of Thailand and linked to Thai history and culture for centuries. The elephant welfare improvement is one of the major components to achieve sustainable captive management. Microbiome inhabiting digestive tracts have been shown with symbiotic relations to host health. This work provided high-resolution microbiome profiles of 32 captive elephants at a species level by utilizing full-length 16S rRNA gene nanopore sequencing. Eleven common uncultured bacterial species were found across elephants fed with solid food including uncultured bacterium Rikenellaceae RC9 gut group, Kiritimatiellae WCHB1-41, Phascolarctobacterium, Oscillospiraceae NK4A214 group, Christensenellaceae R-7 group, Oribacterium, Oscillospirales UCG-010, Lachnospiraceae, Bacteroidales F082, uncultured rumen Rikenellaceae RC9 gut group, and Lachnospiraceae AC2044 group. We observed microbiome shifts along the age classes of baby (0-2 years), juvenile (2-10 years), and adult (> 10 years). Interestingly, we found distinct microbiome profiles among adult elephants fed with a local palm, Caryota urens, as a supplement. Potential beneficial microbes have been revealed according to the age classes and feed diets. The retrieved microbiome data could be provided as good baseline microbial profiles for monitoring elephant health, suggesting further studies towards dietary selection suitable for each age class and the use of local supplementary diets.

Gut microbiome predicts selenium supplementation efficiency across different Chinese adult cohorts using hybrid modeling and feature refining

Selenium (Se) is an essential trace element that plays a vital role in various physiological functions of the human body, despite its small proportion. Due to the inability of the human body to synthesize selenium, there has been increasing concern regarding its nutritional value and adequate intake as a micronutrient. The efficiency of selenium absorption varies depending on individual biochemical characteristics and living environments, underscoring the importance of accurately estimating absorption efficiency to prevent excessive or inadequate intake. As a crucial digestive organ in the human body, gut harbors a complex and diverse microbiome, which has been found to have a significant correlation with the host's overall health status. To investigate the relationship between the gut microbiome and selenium absorption, a two-month intervention experiment was conducted among Chinese adult cohorts. Results indicated that selenium supplementation had minimal impact on the overall diversity of the gut microbiome but was associated with specific subsets of microorganisms. More importantly, these dynamics exhibited variations across regions and sequencing batches, which complicated the interpretation and utilization of gut microbiome data. To address these challenges, we proposed a hybrid predictive modeling method, utilizing refined gut microbiome features and host variable encoding. This approach accurately predicts individual selenium absorption efficiency by revealing hidden microbial patterns while minimizing differences in sequencing data across batches and regions. These efforts provide new insights into the interaction between micronutrients and the gut microbiome, as well as a promising direction for precise nutrition in the future.