Microbial Community Profiles Research Articles

Taxonomic and functional profiling of microbial community in municipal solid waste dumpsite

Taxonomic and functional profiling of microbial community in municipal solid waste dumpsite

Machine Learning in Genomics: Applications in Whole Genome Sequencing, Whole Exome Sequencing, Single-Cell Genomics, and Spatial Transcriptomics

The application of machine learning (ML) to genomics has transformed the process of analyzing and interpreting large-scale, complex datasets, leading to important breakthroughs in our knowledge of biological systems. This review provides a comprehensive overview of ML applications in key genomic areas: Whole Genome Sequencing (WGS), Whole Exome Sequencing (WES), single-cell genomics, and spatial transcriptomics. In WGS and WES, ML techniques are employed for variant calling, genome-wide association studies, rare variant analysis, and the prediction of pathogenicity. In single-cell genomics, ML facilitates clustering, trajectory inference, and cell type identification, while in spatial transcriptomics, it aids in deciphering spatial patterns of gene expression and tissue heterogeneity. This review further explores the application of ML in related omics fields, including proteomics, transcriptomics, metagenomics, epigenomics, and microbiome research. These applications encompass protein structure prediction, functional annotation, microbial community profiling, and the analysis of epigenetic modifications. We address the challenges caused by high dimensionality, variability in the data, and the requirement for interpretable machine learning models when dealing with genomic data. Emerging technologies like explainable AI and federated learning are highlighted for their potential to address these challenges. Additionally, the review addresses ethical considerations, data privacy issues, and the necessity for standardized protocols in ML applications. This comprehensive examination underscores the transformative impact of ML in genomics and highlights its potential to drive future innovations in personalized medicine and biological research.

Rapid diagnosis of Mycoplasma pneumoniae and prediction of antibiotic resistance by nanopore adaptive sampling

AbstractBackgroundMicrobial infections, particularly in children, require rapid and accurate diagnostics. It is difficult to differentiate pathogens from commensal organisms, and it is impossible to identify antibiotic resistance genes that belong to pathogens with current methods. Third‐generation sequencing provides rapid library preparation and real‐time data acquisition. Nanopore normal sampling (NNS) enables unbiased sequencing of clinical samples without amplification, aiding pathogen identification and antimicrobial resistance gene prediction. However, clinical samples often contain a considerable amount of human DNA, potentially masking pathogen data. Nanopore adaptive sampling (NAS) aims to selectively enrich pathogens, promising improved diagnostics for acute infections and better treatment decisions in clinical practice. This study aimed to determine the utility of NAS in enhancing the real‐time detection of pathogens and predicting AMR in infectious disease outbreaks.MethodsThis study used NAS technology to rapidly and directly detect Mycoplasma pneumoniae infection in bronchoalveolar lavage fluid samples from 28 pediatric patients at Shenzhen Children's Hospital. We assessed the efficacy of NAS compared with that of NNS by evaluating the number of microbial reads and the amount of microbial DNA data. We then compared the accuracy of detecting pathogens between NNS and NAS and between NAS and real‐time polymerase chain reaction assays. Furthermore, we predicted antimicrobial resistance (AMR) and examined AMR genes associated with pathogens.ResultsNAS showed up to a 14.67‐fold increase in the amount of microbial DNA data from patients' samples compared with NNS within the initial 2.5 h of sequencing. Additionally, NAS reduced the amount of host DNA data by up to 6.67‐fold compared with NNS. Unlike TaqMan real‐time polymerase chain reaction assays, NAS technology identified dominant pathogens and provided detailed insight into the abundance of the microbial community. Furthermore, NAS was able to predict AMR profiles of microbial communities and attribute specific AMR traits to individual microbes within the samples.ConclusionThis study shows that NAS advances the clinical diagnosis because it can rapidly detect pathogens directly from patients' samples and provides antimicrobial resistance information for clinical guidance. These abilities further facilitate the application of NAS in personalized treatment, reduce the misuse of broad‐spectrum antibiotics, and promote patients' recovery.

Differentiation complex sputum microbiome in patients suspected TB pulmonary

<b>Purpose: </b>This is the first study to attempt microbiome diversity using metagenomic full-length 16S rRNA from respiratory specimens suspected of chronic pulmonary TB patients.<br /> <b>Materials and methods:</b> A 33 patients with suspected chronic pulmonary TB were included. Sputum specimens were cultured to detect <i>mycobacterium sp.</i> and extracted using QiAmp DNA mini kit modification and 16S rRNA metagenomic sequencing by nanopore grid ion sequencer. Microbiome analysis was performed using Pavian and Krona tools.<br /> <b>Results: </b>9 patients were diagnosed with TB based on GeneXpert MTB/RIF assay, and 3 patients were detected with NTM pulmonary infection.The common genera identified from TB culture positive patients were <i>streptococcus sp.</i>, <i>prevotella sp., </i>and <i>veilonella sp. </i>However, less was detected in two NTM infection patients<i>. </i>Metagenomic analysis revealed community bacteria species, including mycobacterium tuberculosis and NTM species, with the lowest number of unique reads. The abundance of <i>streptococcus sp.</i> were less than 30% in 4 patient with comorbid diabetes mellitus.<br /> <b>Conclusions:</b> Metagenomic targeted 16SrRNA full-length sequencing in the clinical respiratory specimen can provide diagnostic insight beyond standard microbiologic cultures and detailed profiling of microbial communities at the species level.

SALINITY-Induced Changes in Diversity, Stability, and Functional Profiles of Microbial Communities in Different Saline Lakes in Arid Areas

Saline lakes, characterized by high salinity and limited nutrient availability, provide an ideal environment for studying extreme halophiles and their biogeochemical processes. The present study examined prokaryotic microbial communities and their ecological functions in lentic sediments (with the salinity gradient and time series) using 16S rRNA amplicon sequencing and a metagenomic approach. Our findings revealed a negative correlation between microbial diversity and salinity. The notable predominance of Archaea in high-salinity lakes signified a considerable alteration in the composition of the microbial community. The results indicate that elevated salinity promotes homogeneous selection pressures, causing substantial alterations in microbial diversity and community structure, and simultaneously hindering interactions among microorganisms. This results in a notable decrease in the complexity of microbial ecological networks, ultimately influencing the overall ecological functional responses of microbial communities such as carbon fixation, sulfur, and nitrogen metabolism. Overall, our findings reveal salinity drives a notable predominance of Archaea, selects for species adapted to extreme conditions, and decreases microbial community complexity within saline lake ecosystems.

The source and dissemination of ARGs in pristine environments: Elucidating the role of migratory birds in the Arctic

Antibiotic resistance genes (ARGs) are a class of emerging contaminants that significantly threaten public health. In this work, the profiles of ARGs and microbial communities in the soil, sediment, migratory bird, and local deer fecal samples collected from the Arctic were characterized using a metagenomic approach. The results retrieved the baseline profiles of ARGs and identified the role of migratory birds in disseminating ARGs in the Arctic. A total of 26 ARG types and 718 subtypes were determined, and 131 core ARGs were identified. All the samples were dominated by multidrug resistance genes, and some genes resistant to antibiotics commonly used in anthropogenic were also detected. Characterization of ARGs in bird fecal samples was significantly distinct from other media, with higher abundance, richness, and unique ARGs detected. Proteobacteria was the most predominant phylum in soil and fecal samples, while Thaumarchaeota was prevalent in sediment samples. Firmicutes harbored the majority of ARGs in all samples. The results of FEAST indicated that migratory birds were crucial allochthonous ARG sources in the Arctic. These significant findings shed light on the global spread of ARGs and should facilitate efforts to map baseline levels of ARGs before the era of antibiotics.

Microbial mechanisms for CO2 and CH4 emissions in Robinia pseudoacacia forests along a North–South transect in the Loess Plateau

Forest soil microbes play a crucial role in regulating atmospheric-soil carbon fluxes. Environmental heterogeneity across forest types and regions may lead to differences in soil CO2 and CH4 emissions. However, the microbial mechanisms underlying these emission variations are currently unclear. In this study, we measured CO2 and CH4 emissions of Robinia pseudoacacia forests along a north–south transect in the Loess Plateau. Using metagenomic sequencing, we investigated the structural and functional profiles of soil carbon cycling microbial communities. Results indicated that the forest CO2 emissions of Robinia pseudoacacia was significantly higher in the north region than in the south region, while the CH4 emission was oppositely. This is mainly attributed to changes in gene abundance driven by soil pH and moisture in participating carbon degradation and methane oxidation processes across different forest regions. The gene differences in carbon fixation processes between regions primarily stem from the Calvin cycle, where the abundance of rbcL, rbcS, and prkB genes dominates microbial carbon fixation in forest soils. Random forest models revealed key genes involved in predicting forest soil CO2 emissions, including SGA1 and amyA for starch decomposition, TYR for lignin decomposition, chitinase for chitin decomposition, and pectinesterase for pectin decomposition. Microbial functional characterization revealed that interregional differences in CH4 emissions during methane metabolism may originate from methane oxidation processes, and the associated gene abundances (glyA, ppc, and pmoB) were key genes for predicting CH4 emissions from forest soils. Our results provide new insights into the microbial mechanisms of CO2 and CH4 emissions from forest soils, which will be crucial for accurate prediction of the forest soil carbon cycle in the future.

Potential functional profiling of soil microbial communities under long-term application of tannery sludge

This study investigated the impact of Cr contamination on the functional profiling of bacterial and archaeal communities in a tropical soil. The contaminated soil contained ∼300 mg kg⁻¹ of Cr due to the long-term application of tannery sludge. The FAPROTAX database was used to assess the potential functional profiling of bacterial and archaeal communities based on 16S rRNA gene phylogeny. The results showed a higher relative abundance of Actinobacteria, Proteobacteria, and Firmicutes. Additionally, an increased relative abundance of Bacillaceae and Paenibacillaceae was observed in Cr-contaminated soil. The functional profiling predicted eleven potential functions, with Cr contamination negatively affecting chemoheterotrophy, nitrification, ammonia oxidation, and nitrogen fixation. This study reveals that Cr contamination significantly impacts the functional profiling of soil bacterial and archaeal communities, emphasizing the importance of monitoring and mitigating Cr contamination to preserve soil function.

Assembly and functional profile of rhizosphere microbial community during the Salix viminalis-AMF remediation of polycyclic aromatic hydrocarbon polluted soils

Arbuscular mycorrhizal fungi (AMF) are positive to the phytoremediation by improving plant biomass and soil properties. However, the role of AM plants to the remediation of polycyclic aromatic hydrocarbons (PAHs) is yet to be widely recognized, and the impact of AM plants to indigenous microbial communities during remediation remains unclear. In this work, a 90-day study was conducted to assess the effect of AMF-Salix viminalis on the removal of PAHs, and explore the impact to the microbial community composition, abundance, and function. Results showed that AMF-Salix viminalis effectively enhanced the removal of benzo[a]pyrene, and enriched more PAH-degrading bacteria, consisting of Actinobacteria, Chloroflexi, Sphingomonas, and Stenotrophobacter, as well as fungi including Basidiomycota, Pseudogymnoascus, and Tomentella. For gene function, AM willow enhanced the enrichment of genes involved in amino acid synthesis, aminoacyl-tRNA biosynthesis, and cysteine and methionine metabolism pathways. F. mosseae inoculation had a greater effect on alpha- and beta-diversity of microbial genes at 90 d. Additionally, AMF inoculation significantly increased the soil microbial biomass carbon and organic matter concentration. All together, the microbial community assembly and function shaped by AM willow promoted the dissipation of PAHs. Our results support the effectiveness of AM remediation and contribute to reveal the enhancing-remediation mechanism to PAHs using multi-omics data.

Microbial community profiling in intestinal tract of indigenous chickens from different villages

Village chickens (Gallus gallus domesticus) are commonly reared in rural households of South Africa and other developing countries. They play a vital role as a primary source of protein through the provision of meat and eggs. The chicken gut microbiota plays an important role in chicken’s immune system, its health, physiological development of the gut, digestion of food, nutrient absorption and productivity. Thus, it is imperative to critically investigate the chicken microbial composition in order to develop effective disease control measures and increase production. In this present study, microbial DNA was isolated from 34 non-descript mixed gender matured village chickens’ intestinal contents followed by high throughput Illumina sequencing targeting 16S rRNA gene. Senwamokgope village had the largest microbiota composition as compared to Itieleni and Thakgalang villages. Overall, Firmicutes (74%) was the most abundant phylum observed, followed by Proteobacteria (8%), Actinobateria (5%), and Bacteroidota (3%). At the genus level, Lactobacillus was the dominant bacteria. Other genera found included Sphingomonas (7%), Cutibacterium (4%), and Clostridium_sensu_stricto_1 (2%). The richness of female intestinal microbiota was higher compared to the male microbiota. The findings of this study provide baseline information that can assist to better understand the chicken gut microbiota and its interaction with diseases and parasites.

A novel barcoded nanopore sequencing workflow of high-quality, full-length bacterial 16S amplicons for taxonomic annotation of bacterial isolates and complex microbial communities.

Due to recent improvements, Nanopore sequencing has become a promising method for experiments relying on amplicon sequencing. We describe a flexible workflow to generate and annotate high-quality, full-length 16S rDNA amplicons. We evaluated it for two applications, namely, (i) identification of bacterial isolates and (ii) species-level profiling of microbial communities. We assessed the identification of single bacterial isolates by sequencing, using a set of barcoded full-length 16S rRNA gene primer pairs (pair A), on 47 isolates encompassing multiple genera and compared those results with matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS)-based identification. Species-level community profiling was tested with two sets of barcoded full-length 16S primer pairs (A and B) and compared to the results obtained with shotgun Illumina sequencing using 27 stool samples. We developed a Nextflow pipeline to retain high-quality reads and taxonomically annotate them. We found high agreement between our workflow and MALDI-TOF data for isolate identification (positive predictive value = 0.90, Cramér's V = 0.857, and Theil's U = 0.316). For species-level community profiling, we found strong correlations (rs > 0.6) of alpha diversity indices between the two primer sets and Illumina sequencing. At the community level, we found significant but small differences when comparing sequencing techniques. Finally, we found a moderate to strong correlation when comparing the relative abundances of individual species (average rs = 0.6 and 0.533 for primers A and B). Despite identified shortcomings, the proposed workflow enabled accurate identification of single bacterial isolates and prominent features in microbial communities, making it a worthwhile alternative to MALDI-TOF MS and Illumina sequencing.IMPORTANCEA quick, robust, simple, and cost-effective method to identify bacterial isolates and communities in each sample is indispensable in the fields of microbiology and infection biology. Recent technological advances in Oxford Nanopore Technologies sequencing make this technique an attractive option considering the adaptability, portability, and cost-effectiveness of the platform, even with small sequencing batches. Here, we validated a flexible workflow to identify bacterial isolates and characterize bacterial communities using the Oxford Nanopore Technologies sequencing platform combined with the most recent v14 chemistry kits. For bacterial isolates, we compared our nanopore-based approach to matrix-assisted laser desorption ionization-time of flight mass spectrometry-based identification. For species-level profiling of complex bacterial communities, we compared our nanopore-based approach to Illumina shotgun sequencing. For reproducibility purposes, we wrapped the code used to process the sequencing data into a ready-to-use and self-contained Nextflow pipeline.

Soil pH enhancement and alterations in nutrient and Bacterial Community profiles following Pleioblastus amarus expansion in tea plantations

BackgroundThe expansion of bamboo forests increases environmental heterogeneity in tea plantation ecosystems, affecting soil properties and microbial communities. Understanding these impacts is essential for developing sustainable bamboo management and maintaining ecological balance in tea plantations.MethodsWe studied the effect of the continuous expansion of Pleioblastus amarus into tea plantations, by establishing five plot types: pure P. amarus forest area (BF), P. amarus forest interface area (BA), mixed forest interface area (MA), mixed forest center area (TB), and pure tea plantation area (TF). We conducted a comprehensive analysis of soil chemical properties and utilized Illumina sequencing to profile microbial community composition and diversity, emphasizing their responses to bamboo expansion.Results(1) Bamboo expansion significantly raised soil pH and enhanced levels of organic matter, nitrogen, and phosphorus, particularly noticeable in BA and MA sites. In the TB sites, improvements in soil nutrients were statistically indistinguishable from those in pure tea plantation areas. (2) Continuous bamboo expansion led to significant changes in soil bacterial diversity, especially noticeable between BA and TF sites, while fungal diversity was unaffected. (3) Bamboo expansion substantially altered the composition of less abundant bacterial and fungal communities, which proved more sensitive to changes in soil chemical properties.ConclusionThe expansion of bamboo forests causes significant alterations in soil pH and nutrient characteristics, impacting the diversity and composition of soil bacteria in tea plantations. However, as expansion progresses, its long-term beneficial impact on soil quality in tea plantations appears limited.

Comparative analysis of size-fractional eukaryotic microbes in subtropical riverine systems inferred from 18S rRNA gene V4 and V9 regions

Eukaryotic microbes play key ecological roles in riverine ecosystems. Amplicon sequencing has greatly facilitated the identification and characterization of eukaryotic microbial communities. Currently, 18S rRNA gene V4 and V9 hypervariable regions are widely used for sequencing eukaryotic microbes. Identifying optimal regions for the profiling of size-fractional eukaryotic microbial communities is critical for microbial ecological studies. In this study, we spanned three rivers with typical natural-human influenced transition gradients to evaluate the performance of the 18S rRNA gene V4 and V9 hypervariable regions for sequencing size-fractional eukaryotic microbes (>180 μm, 20-180 μm, 5-20 μm, 3-5 μm, 0.8-3 μm). Our comparative analysis revealed that amplicon results depend on the specific species and microbial size. The V9 region was most effective for detecting a broad taxonomic range of species. The V4 region was superior to the V9 region for the identification of microbes in the minor 3 μm and at the family and genus levels, especially for specific microbial groups, such as Labyrinthulomycetes. However, the V9 region was more effective for studies of diverse eukaryotic groups, including Archamoebae, Heterolobosea, and Microsporidia, and various algae, such as Haptophyta, Florideophycidae, and Bangiales. Our results highlight the importance of accounting for potential misclassifications when employing both V4 and V9 regions for the identification of microbial sequences. The use of optimal regions for amplification could enhance the utility of amplicon sequencing in environmental studies. The insights gained from this work will aid future studies that employ amplicon-based identification approaches for the characterization of eukaryotic microbial communities and contribute to our understanding of microbial ecology within aquatic systems.

Bioturbation effect of high - Yield pyrazine strain on the microbial community and flavour metabolites of fortified Daqu

In order to comprehensively explore the regulatory effect of bioturbation on the assembly and overall metabolic characteristics of Daqu microbial community. This study used metatranscriptomics and metabolomics to investigate the composition of the microbial community, physicochemical properties, and overall metabolic profile of Daqu before and after bioturbation by Bacillus velezensis. The results demonstrated that the acidity, moisture, amino acid nitrogen, and starch content of Daqu exhibited a significant increase following bioturbation. The symbol microorganisms of Daqu have also changed significantly, from the original Aspergillus chevalieri, Rasamsonia emersonii, Aspergillus ruber, Aspergillus glaucus, Aspergillus wentii and Aspergillus cristatus to Paecilomyces varioti, Trichomonascus ciferrii and Staphylococcus gallinarum. Correlation analyses and integration pathways indicated that altered microbial community abundance also promoted the metabolism of starch, ethanol, fatty acids, and pyrazine, resulting in a significant enhancement of Daqu's saccharification and liquefaction power, as well as the content of some volatile and non-volatile metabolites, with pyrazines increased by 24.50%. The application of fortified Daqu to Baijiu fermentation can significantly enhance the content of various pyrazines in Baijiu. These results are helpful to elucidate the mechanism of biochemical changes, microbial assembly and flavor production of Daqu after biodisturbance.

Metagenomic profiling of rhizosphere microbiota: Unraveling the plant-soil dynamics

Rhizosphere is a dynamic and complex environment shaped by intricate interactions between plants and a diverse microbial community. The rhizosphere microbiome is crucial for plant growth, nutrition, and health in agro-ecosystems. Recent advancements in metagenomics, especially through shotgun sequencing, offer unprecedented opportunities to unravel the complexities of rhizosphere microbial dynamics. Sequence and function-based metagenomic approaches enhance our understanding of plant-microbe relationships and serve as transformative tools for sustainable agriculture. They offer insights into precision microbiome engineering and ecosystem management by capturing the genomic landscape of microbial communities, revealing their taxonomic composition and functional potential. The integration of computational tools and machine learning approaches provides a powerful analytical framework to interpret vast and intricate metagenomic datasets. This paper comprehensively explores the rhizosphere using cutting-edge shotgun sequencing techniques to capture a holistic view of microbial communities in this crucial zone. Additionally, it delves into the emerging domain of virus-rhizosphere interactions, elucidating the impact of viral dynamics on rhizosphere microbial composition. To date, significant achievements in rhizosphere biology through metagenomics include detailed characterizations of microbial diversity, functional profiling of microbial communities, and identification of key microbial players in plant health and nutrient cycling. These advances underscore the critical role of metagenomics in advancing our understanding of rhizosphere biology and its applications in sustainable agriculture. The novel application of these advanced metagenomic techniques presents both opportunities and challenges, offering deeper insights into the rhizosphere while highlighting the need for improved data integration and interpretation methods.

Impact of microbial-based biopreparations on soil quality, plant health, and fruit chemistry in raspberry cultivation

Application of microbial-based biopreparations as a pre-harvest strategy offers a method to obtain sustainable agricultural practices and could be an important approach for advancing food science, promoting sustainability, and meeting global food market demands.The impact of a bacterial-fungal biopreparation mixture on soil-plant-microbe interactions, fruit chemical composition and yield of 7 raspberry clones was investigated by examining the structural and functional profiles of microbial communities within leaves, fruits, and soil. Biopreparation addition caused the enhancement of the microbiological utilization of specific compounds, such as d-mannitol, relevant in plant-pathogen interactions and overall plant health. The biopreparation treatment positively affected the nitrogen availability in soil (9–160%).The analysis of plant stress marker enzymes combined with the evaluation of fruit quality and chemical properties highlight changes inducted by the pre-harvest biopreparation application. Chemical analyses highlight biopreparations' role in soil and fruit quality improvement, promoting sustainable agriculture. This effect was dependent on tested clones, showing increase of soluble solid content in fruits, concentration of polyphenols or the sensory quality of the fruits. The results of the next-generation sequencing indicated increase in the effective number of bacterial species after biopreparation treatment. The network analysis showed stimulating effect of biopreparation on microbial communities by enhancing microbial interactions (increasing the number of network edges up to 260%) of and affecting the proportions of mutual relationships between both bacteria and fungi.These findings show the potential of microbial-based biopreparation in enhancing raspberry production whilst promoting sustainable practices and maintaining environmental homeostasis and giving inshght in holistic understanding of microbial-based approaches for advancing food science monitoring.

Microbial Dynamics and Metabolite Profiles in Different Types of Salted Seafood (Jeotgal) During Fermentation.

Salted and fermented seafood (jeotgal) is known for its long shelf life and unique flavor. Despite the existence of various types of salted seafood, the factors influencing this quality have yet to be identified. These factors are essential for improving the quality of salted seafood, optimizing the fermentation process, and advancing the industrialization of fermented foods. Therefore, in this study, we explored microbial dynamics and changes in quality characteristics in three salted seafood items - salted anchovies (MJ), salted cutlass offal (GJ), and salted croakers (HJ), over a 24-month fermentation period. Distinct microbial community profiles, dominated by Tetragenococcus halophilus, Halanaerobium fermentans, and Chromohalobacter canadensis in MJ, GJ, and HJ, respectively, affect the metabolic pathways and the corresponding flavor profiles. The pH of all samples ranged from 5.7-6.0. The titratable acidity was highest in MJ at 1.4% and lowest in HJ at approximately 0.7%. Salinity was below 25% in all samples but slightly lower in MJ. Significant differences were observed in the amino acid, nucleotide, and overall metabolite profiles. MJ exhibited the highest amino acid and nitrogen-related factor levels, such as glutamic acid and hypoxanthine, enhancing flavor complexity. Correlation analysis revealed significant associations among the types, metabolites, and microbial communities. Microbial survival mechanisms in high-salt environments result in the production of unique metabolites, including umami and aroma components as well as precursors of biogenic amines, which can affect the overall quality of the final product. These differences were primarily influenced by the fish type rather than the fermentation time. Our findings provide foundational insights for enhancing fermentation strategies, improving product consistency, and advancing the industrial application of microbial management in seafood fermentation. This study not only fills a significant gap in the current understanding of fermented seafood but also outlines practical approaches for industry applications for the optimization of product quality.

Database size positively correlates with the loss of species-level taxonomic resolution for the 16S rRNA and other prokaryotic marker genes.

For decades, the 16S rRNA gene has been used to taxonomically classify prokaryotic species and to taxonomically profile microbial communities. However, the 16S rRNA gene has been criticized for being too conserved to differentiate between distinct species. We argue that the inability to differentiate between species is not a unique feature of the 16S rRNA gene. Rather, we observe the gradual loss of species-level resolution for other nearly-universal prokaryotic marker genes as the number of gene sequences increases in reference databases. This trend was strongly correlated with how represented a taxonomic group was in the database and indicates that, at the gene-level, the boundaries between many species might be fuzzy. Through our study, we argue that any approach that relies on a single marker to distinguish bacterial taxa is fraught even if some markers appear to be discriminative in current databases.

Integrated analysis of intestinal microbial community and muscle transcriptome profile in rabbits

Intestinal microbial community plays an important part in maintaining health and skeletal muscle development in livestock. This study is the first of its kind in the world. In order to better understand the relationship between gut microbiota and gene expression in skeletal muscle of rabbits, caecum contents and longissimus dorsi tissues of rabbits at 0 d (S1), 35 d (S2) and 70d (S3) were collected and subjected for 16S rRNA sequencing and transcriptome sequencing. Our results showed that, among three groups of rabbits, Firmicutes and Bacteroidetes were the dominant phyla at the phylum level, while Akmansia, Bacteroides and Ruminobacter were the dominant genera at the genus level, and the relative abundance of Akmansia and Bacteroides increased firstly and then decreased from 0 d to 70 d. By analyzing the transcriptome sequencing data, we identified 2866, 2446 and 4541 differentially expressed genes (DEGs) in S1 vs S2, S2 vs S3 and S1 vs S3 groups, respectively. Finally, we performed correlation analysis between gut microbiota and the expression levels of muscle development-related genes of rabbits at 0 d and 70 d. Compared with 0 day old rabbits, in 70 day old rabbits Acinetobacter and Cronbacter with decreased abundance, and Ruminococcaceae_UCG-014 and Ruminococcus_1 with increase abundance is beneficial to caecum health in rabbits. These results will lay a foundation for further re-searches about the relationship between caecum microflora and muscle development in rabbits.

Optimised human stool sample collection for multi-omic microbiota analysis

To accurately define the role of the gut microbiota in health and disease pathogenesis, the preservation of stool sample integrity, in terms of microbial community composition and metabolic function, is critical. This presents a challenge for any studies which rely on participants self-collecting and returning stool samples as this introduces variability and uncertainty of sample storage/handling. Here, we tested the performance of three stool sample collection/preservation buffers when storing human stool samples at different temperatures (room temperature [20 °C], 4 °C and – 80 °C) for up to three days. We compared and quantified differences in 16S rRNA sequencing composition and short-chain fatty acid profiles compared against immediately snap-frozen stool. We found that the choice of preservation buffer had the largest effect on the resulting microbial community and metabolomic profiles. Collectively analysis confirmed that PSP and RNAlater buffered samples most closely recapitulated the microbial diversity profile of the original (immediately – 80 °C frozen) sample and should be prioritised for human stool microbiome studies.