Classification of 16S rRNA reads is improved using a niche-specific database constructed by near-full length sequencing

A curated bacterial and archaeal 16S rRNA Gene Oral Sequences dataset

In a given species, genomes and 16S rRNA gene sequences, along with their intragenomic copy numbers, can vary greatly across environments. The gene copy numbers are crucial for technologies which estimate microbial abundances based on gene counts, such as polymerase chain reaction and high-throughput sequencing. In these, taxa with fewer genes may be underestimated, while those with more genes might be overestimated. Therefore, it is essential to have accurate gene copy number databases specific to the niche under study. The 16S rRNA Gene Oral Sequences dataset (16SGOSeq) contains the number of 16S rRNA genes and their variants in the complete genomes of the bacterial and archaeal species present in the human oral cavity. It includes 3,192 complete genomes of oral bacteria and 191 complete genomes of oral archaea, from which the 16S rRNA gene sequences were extracted, and the sequence variants were identified. This oral-specific dataset of prokaryotic organisms and the pipeline followed for its construction can be applied by clinical microbiologists, bioinformaticians, or microbial ecologists in future microbiome research.

Intermittent fasting induced cerebral ischemic tolerance altered gut microbiome and increased levels of short-chain fatty acids to a beneficial phenotype

Preconditioning-induced cerebral ischemic tolerance is known to be a beneficial adaptation to protect the brain in an unavoidable event of stroke. We currently demonstrate that a short bout (6 weeks) of intermittent fasting (IF; 15 h fast/day) induces similar ischemic tolerance to that of a longer bout (12 weeks) in adult C57BL/6 male mice subjected to transient middle cerebral artery occlusion (MCAO). In addition, the 6 weeks IF regimen induced ischemic tolerance irrespective of age (3 months or 24 months) and sex. Mice subjected to transient MCAO following IF showed improved motor function recovery (rotarod and beam walk tests) between days 1 and 14 of reperfusion and smaller infarcts (T2-MRI) on day 1 of reperfusion compared with age/sex matched ad libitum (AL) controls. Diet influences the gut microbiome composition and stroke is known to promote gut bacterial dysbiosis. We presently show that IF promotes a beneficial phenotype of gut microbiome following transient MCAO compared with AL cohort. Furthermore, post-stroke levels of short-chain fatty acids (SCFAs), which are known to be neuroprotective, are higher in the fecal samples of the IF cohort compared with the AL cohort. Thus, our studies indicate the efficacy of IF in protecting the brain after stroke, irrespective of age and sex, probably by altering gut microbiome and SCFA production.

Species-level characterization of gut microbiota and their metabolic role in kidney stone formation using full-length 16S rRNA sequencing

The critical role of the human gut microbiota in kidney stone formation remains largely unknown, due to the low taxonomic resolution of previous sequencing technologies. Therefore, this study aimed to explore the gut microbiota using high-throughput sequencing to provide valuable insights and identify potential bacterial species and metabolite roles involved in kidney stone formation. The overall gut bacterial community and its potential functions in healthy participants and patients were examined using PacBio sequencing targeting the full-length 16S rRNA gene, coupled with stone and statistical analyses. Most kidney stones comprised calcium oxalate and calcium phosphate (75%), pure calcium oxalate (20%), and calcium phosphate and magnesium phosphate (5%), with higher content of Ca (130,510.5 ± 108,362.7 ppm) followed by P (18,746.4 ± 23,341.2 ppm). The microbial community structure was found to be weaker in patients' kidney stone samples, followed by patients' stool samples, than in healthy participants' stool samples. The most abundant bacterial species in kidney stone samples was uncultured Morganella, whereas that in patient and healthy participant stool samples was Bacteroides vulgatus. Similarly, Akkermansia muciniphila was significantly enriched in patient stool samples at the species level, whereas Bacteroides plebeius was significantly enriched in kidney stone samples than that in healthy participant stool samples. Three microbial metabolic pathways, TCA cycle, fatty acid oxidation, and urea cycle, were significantly enriched in kidney stone patients compared to healthy participants. Inferring bacteria at the species level revealed key players in kidney stone formation, enhancing the clinical relevance of gut microbiota.

Comparative analysis of gut microbiota in children with obstructive sleep apnea: assessing the efficacy of 16S rRNA gene sequencing in metabolic function prediction based on weight status

Background

Analyzing bacterial microbiomes consistently using next-generation sequencing (NGS) is challenging due to the diversity of synthetic platforms for 16S rRNA genes and their analytical pipelines. This study compares the efficacy of full-length (V1-V9 hypervariable regions) and partial-length (V3-V4 hypervariable regions) sequencing of synthetic 16S rRNA genes from human gut microbiomes, with a focus on childhood obesity.

Methods

In this observational and comparative study, we explored the differences between these two sequencing methods in taxonomic categorization and weight status prediction among twelve children with obstructive sleep apnea.

Results

The full-length NGS method by Pacbio® identified 118 genera and 248 species in the V1-V9 regions, all with a 0% unclassified rate. In contrast, the partial-length NGS method by Illumina® detected 142 genera (with a 39% unclassified rate) and 6 species (with a 99% unclassified rate) in the V3-V4 regions. These approaches showed marked differences in gut microbiome composition and functional predictions. The full-length method distinguished between obese and non-obese children using the Firmicutes/Bacteroidetes ratio, a known obesity marker (p = 0.046), whereas the partial-length method was less conclusive (p = 0.075). Additionally, out of 73 metabolic pathways identified through full-length sequencing, 35 (48%) were associated with level 1 metabolism, compared to 28 of 61 pathways (46%) identified through the partial-length method. The full-length NGS also highlighted complex associations between body mass index z-score, three bacterial species (Bacteroides ovatus, Bifidobacterium pseudocatenulatum, and Streptococcus parasanguinis ATCC 15912), and 17 metabolic pathways. Both sequencing techniques revealed relationships between gut microbiota composition and OSA-related parameters, with full-length sequencing offering more comprehensive insights into associated metabolic pathways than the V3-V4 technique.

Conclusion

These findings highlight disparities in NGS-based assessments, emphasizing the value of full-length NGS with amplicon sequence variant analysis for clinical gut microbiome research. They underscore the importance of considering methodological differences in future meta-analyses.

The Impact of Nitrogen-Fixing Bacteria-Based Biostimulant Alone or in Combination with Commercial Inoculum on Tomato Native Rhizosphere Microbiota and Production: An Open-Field Trial

The agricultural sector is currently encountering significant challenges due to the effects of climate change, leading to negative consequences for crop productivity and global food security. In this context, traditional agricultural practices have been inadequate in addressing the fast-evolving challenges while maintaining environmental sustainability. A possible alternative to traditional agricultural management is represented by using beneficial micro-organisms that, once applied as bioinoculants, may enhance crop resilience and adaptability, thereby mitigating the adverse effects of environmental stressors and boosting productivity. Tomato is one of the most important crops worldwide, playing a central role in the human diet. The aim of this study was to evaluate the impact of a nitrogen-fixing bacterial-based biostimulant (Azospirillum sp., Azotobacter sp., and Rhizobium sp.) in combination or not with a commercial inoculum Micomix (Rhizoglomus irregulare, Funnelliformis mosseae, Funnelliformis caledonium, Bacillus licheniformis, and Bacillus mucilaginosus) (MYC) on the native rhizosphere communities and tomato production. Bacterial populations in the different samples were characterized using an environmental metabarcoding approach. The bioinocula effect on the native rhizosphere microbiota resulted in significant variation both in alpha and beta diversity and in a specific signature associated with the presence of biostimulants.

Strategies for Bovine Respiratory Disease (BRD) Diagnosis and Prognosis: A Comprehensive Overview

Despite significant advances in vaccination strategies and antibiotic therapy, bovine respiratory disease (BRD) continues to be the leading disease affecting the global cattle industry. The etiology of BRD is complex, often involving multiple microbial agents, which lead to intricate interactions between the host immune system and pathogens during various beef production stages. These interactions present environmental, social, and geographical challenges. Accurate diagnosis is essential for effective disease management. Nevertheless, correct identification of BRD cases remains a daunting challenge for animal health technicians in feedlots. In response to current regulations, there is a growing interest in refining clinical diagnoses of BRD to curb the overuse of antimicrobials. This shift marks a pivotal first step toward establishing a structured diagnostic framework for this disease. This review article provides an update on recent developments and future perspectives in clinical diagnostics and prognostic techniques for BRD, assessing their benefits and limitations. The methods discussed include the evaluation of clinical signs and animal behavior, biomarker analysis, molecular diagnostics, ultrasound imaging, and prognostic modeling. While some techniques show promise as standalone diagnostics, it is likely that a multifaceted approach-leveraging a combination of these methods-will yield the most accurate diagnosis of BRD.

Isolation, identification, and biological characterization of bacterial endophytes isolated from Gunnera perpensa L

In the present study, eleven endophytic bacterial strains, Herbaspirillum sp. (GP-SGM1, GP-SGM2, GP-SGM3, and GP-SGM11), Pseudomonas sp. (GP-SGM4, GP-SGM5), Novosphingobium sp. GP-SGM6, Chryseobacterium sp. GP-SGM7, Labedella sp. GP-SGM8, Brevibacterium sp. GP-SGM9, and Pseudomonas sp. GP-SGM10, were isolated from the rhizomes of Gunnera perpensa L. The growth kinetics, assessed through maximum growth rates (μmax) and optical density (OD) values, revealed that GP-SGM7 exhibited highest μmax values of 0.33 ± 0.01 hours (h)-1 with an OD of 4.20 ± 0.04. In contrast, GP-SGM11 exhibited the lowest μmax of 0.12 ± 0.05 h-1 and the smallest OD of 1.50 ± 0.00. In addition, the endophyte crude extracts were tested for antibacterial activity against five pathogenic strains using the disk diffusion method, with GP-SGM7 crude extracts exhibiting promising antibacterial activity against Klebsiella pneumoniae and Staphylococcus aureus. Antioxidant activity was determined by DPPH (2, 2-diphenyl-1-picrylhydrazyl) and FRAP (ferric reducing antioxidant power) assays. The crude extracts of GP-SGM1, GP-SGM7, GP-SGM9, and GP-SGM10 were the most effective at scavenging DPPH radicals, with GP-SGM7 also exhibiting a high FRAP value of 0.54 ± 0.01. These findings emphasize the therapeutic potential of endophytic bacteria from G. perpensa L. in addressing skin-related issues, including bacterial infections and free radicals.

Guidelines for microbiome studies in renal physiology

Gut microbiome research has increased dramatically in the last decade, including in renal health and disease. The field is moving from experiments showing mere association to causation using both forward and reverse microbiome approaches, leveraging tools such as germ-free animals, treatment with antibiotics, and fecal microbiota transplantations. However, we are still seeing a gap between discovery and translation that needs to be addressed, so that patients can benefit from microbiome-based therapies. In this guideline paper, we discuss the key considerations that affect the gut microbiome of animals and clinical studies assessing renal function, many of which are often overlooked, resulting in false-positive results. For animal studies, these include suppliers, acclimatization, baseline microbiota and its normalization, littermates and cohort/cage effects, diet, sex differences, age, circadian differences, antibiotics and sweeteners, and models used. Clinical studies have some unique considerations, which include sampling, gut transit time, dietary records, medication, and renal phenotypes. We provide best-practice guidance on sampling, storage, DNA extraction, and methods for microbial DNA sequencing (both 16S rRNA and shotgun metagenome). Finally, we discuss follow-up analyses, including tools available, metrics, and their interpretation, and the key challenges ahead in the microbiome field. By standardizing study designs, methods, and reporting, we will accelerate the findings from discovery to translation and result in new microbiome-based therapies that may improve renal health.

Habitats modulate influencing factors shaping the spatial distribution of bacterial communities along a Tibetan Plateau riverine wetland

The Tibetan Plateau riverine wetland is very sensitive to global climate change. Understanding the mechanisms that maintain the spatial patterns of bacterial communities provides insight into the dominant biogeochemical processes within the plateau riverine wetlands. Nonetheless, the spatial distribution of bacterial communities along these wetlands has rarely been explored. We investigated the spatial patterns of bacterial community within rhizosphere soil, bulk soil, and sediment samples collected along the Yarlung Tsangpo riverine wetland (YTRW), the longest plateau riverine wetland in China. Our results indicated that the diversity of bacterial communities in all three habitats increased significantly along the YTRW. The slope of the linear relationship between distance and bacterial community diversity in sediment was steeper than those for bulk and rhizosphere soils. Furthermore, bacterial communities in all three habitats showed significant distance-decay relationships. A combination of historical factors (geographical distance and climatic factors) and contemporary environmental heterogeneity (edaphic properties) controlled spatial distributions of bacterial communities in all three habitats, although climatic factors were predominant. Climatic factors affected rhizosphere bacterial communities more than those in bulk soil and sediment. Co-occurrence network analysis revealed that the potential interactions between bacterial taxa may decrease along the YTRW. This field investigation highlighted that the climatic factors strongly influenced the spatial distribution of bacterial communities along the YTRW; however, habitat differences among rhizosphere soil, bulk soil, and sediment samples affected the relative importance of climatic factors on spatial distributions of the associated bacterial communities. These findings would improve the understanding of biogeochemical processes in these typical habitats and potential alterations provoked by climate change.

16S-FASAS: an integrated pipeline for synthetic full-length 16S rRNA gene sequencing data analysis

Background

The full-length 16S rRNA sequencing can better improve the taxonomic and phylogenetic resolution compared to the partial 16S rRNA gene sequencing. The 16S-FAS-NGS (16S rRNA full-length amplicon sequencing based on a next-generation sequencing platform) technology can generate high-quality, full-length 16S rRNA gene sequences using short-read sequencers, together with assembly procedures. However there is a lack of a data analysis suite that can help process and analyze the synthetic long read data.

Results

Herein, we developed software named 16S-FASAS (16S full-length amplicon sequencing data analysis software) for 16S-FAS-NGS data analysis, which provided high-fidelity species-level microbiome data. 16S-FASAS consists of data quality control, de novo assembly, annotation, and visualization modules. We verified the performance of 16S-FASAS on both mock and fecal samples. In mock communities, we proved that taxonomy assignment by MegaBLAST had fewer misclassifications and tended to find more low abundance species than the USEARCH-UNOISE3-based classifier, resulting in species-level classification of 85.71% (6/7), 85.71% (6/7), 72.72% (8/11), and 70% (7/10) of the target bacteria. When applied to fecal samples, we found that the 16S-FAS-NGS datasets generated contigs grouped into 60 and 56 species, from which 71.62% (43/60) and 76.79% (43/56) were shared with the Pacbio datasets.

Conclusions

16S-FASAS is a valuable tool that helps researchers process and interpret the results of full-length 16S rRNA gene sequencing. Depending on the full-length amplicon sequencing technology, the 16S-FASAS pipeline enables a more accurate report on the bacterial complexity of microbiome samples. 16S-FASAS is freely available for use at https://github.com/capitalbio-bioinfo/FASAS.

Nasopharyngeal microbiota profiling of pregnant women with SARS-CoV-2 infection

We aimed to analyze the nasopharyngeal microbiota profiles in pregnant women with and without SARS-CoV-2 infection, considered a vulnerable population during COVID-19 pandemic. Pregnant women were enrolled from a multicenter prospective population-based cohort during the first SARS-CoV-2 wave in Spain (March-June 2020 in Barcelona, Spain) in which the status of SARS-CoV-2 infection was determined by nasopharyngeal RT–PCR and antibodies in peripheral blood. Women were randomly selected for this cross-sectional study on microbiota. DNA was extracted from nasopharyngeal swab samples, and the V3-V4 region of the 16S rRNA of bacteria was amplified using region-specific primers. The differential abundance of taxa was tested, and alpha/beta diversity was evaluated. Among 76 women, 38 were classified as positive and 38 as negative for SARS-CoV-2 infection. All positive women were diagnosed by SARS-CoV-2 IgG and IgM/IgA antibodies, and 14 (37%) also had a positive RT–PCR. The overall composition of the nasopharyngeal microbiota differ in pregnant women with SARS-CoV-2 infection (positive SARS-CoV-2 antibodies), compared to those without the infection (negative SARS-CoV-2 antibodies) (p = 0.001), with a higher relative abundance of the Tenericutes and Bacteroidetes phyla and a higher abundance of the Prevotellaceae family. Infected women presented a different pattern of microbiota profiling due to beta diversity and higher richness (observed ASV < 0.001) and evenness (Shannon index < 0.001) at alpha diversity. These changes were also present in women after acute infection, as revealed by negative RT–PCR but positive SARS-CoV-2 antibodies, suggesting a potential association between SARS-CoV-2 infection and long-lasting shift in the nasopharyngeal microbiota. No significant differences were reported in mild vs. severe cases. This is the first study on nasopharyngeal microbiota during pregnancy. Pregnant women with SARS-CoV-2 infection had a different nasopharyngeal microbiota profile compared to negative cases.

Incorporation of Data From Multiple Hypervariable Regions when Analyzing Bacterial 16S rRNA Gene Sequencing Data

Short read 16 S rRNA amplicon sequencing is a common technique used in microbiome research. However, inaccuracies in estimated bacterial community composition can occur due to amplification bias of the targeted hypervariable region. A potential solution is to sequence and assess multiple hypervariable regions in tandem, yet there is currently no consensus as to the appropriate method for analyzing this data. Additionally, there are many sequence analysis resources for data produced from the Illumina platform, but fewer open-source options available for data from the Ion Torrent platform. Herein, we present an analysis pipeline using open-source analysis platforms that integrates data from multiple hypervariable regions and is compatible with data produced from the Ion Torrent platform. We used the ThermoFisher Ion 16 S Metagenomics Kit and a mock community of twenty bacterial strains to assess taxonomic classification of six amplicons from separate hypervariable regions (V2, V3, V4, V6-7, V8, V9) using our analysis pipeline. We report that different amplicons have different specificities for taxonomic classification, which also has implications for global level analyses such as alpha and beta diversity. Finally, we utilize a generalized linear modeling approach to statistically integrate the results from multiple hypervariable regions and apply this methodology to data from a representative clinical cohort. We conclude that examining sequencing results across multiple hypervariable regions provides more taxonomic information than sequencing across a single region. The data across multiple hypervariable regions can be combined using generalized linear models to enhance the statistical evaluation of overall differences in community structure and relatedness among sample groups.

Bovine respiratory microbiota of feedlot cattle and its association with disease

Bovine respiratory disease (BRD), as one of the most common and costly diseases in the beef cattle industry, has significant adverse impacts on global food security and the economic stability of the industry. The bovine respiratory microbiome is strongly associated with health and disease and may provide insights for alternative therapy when treating BRD. The niche-specific microbiome communities that colonize the inter-surface of the upper and the lower respiratory tract consist of a dynamic and complex ecological system. The correlation between the disequilibrium in the respiratory ecosystem and BRD has become a hot research topic. Hence, we summarize the pathogenesis and clinical signs of BRD and the alteration of the respiratory microbiota. Current research techniques and the biogeography of the microbiome in the healthy respiratory tract are also reviewed. We discuss the process of resident microbiota and pathogen colonization as well as the host immune response. Although associations between the microbiota and BRD have been revealed to some extent, interpreting the development of BRD in relation to respiratory microbial dysbiosis will likely be the direction for upcoming studies, which will allow us to better understand the importance of the airway microbiome and its contributions to animal health and performance.

Species-Level Resolution of Female Bladder Microbiota from 16S rRNA Amplicon Sequencing

The human bladder contains bacteria, even in the absence of infection. Interest in studying these bacteria and their association with bladder conditions is increasing. However, the chosen experimental method can limit the resolution of the taxonomy that can be assigned to the bacteria found in the bladder. 16S rRNA amplicon sequencing is commonly used to identify bacteria in urinary specimens, but it is typically restricted to genus-level identification. Our primary aim here was to determine if accurate species-level identification of bladder bacteria is possible using 16S rRNA amplicon sequencing. We evaluated the ability of different classification schemes, each consisting of combinations of a reference database, a 16S rRNA gene variable region, and a taxonomic classification algorithm to correctly classify bladder bacteria. We show that species-level identification is possible and that the reference database chosen is the most important component, followed by the 16S variable region sequenced. IMPORTANCE Accurate species-level identification from culture-independent techniques is of importance for microbial niches that are less well characterized, such as that of the bladder. 16S rRNA amplicon sequencing, a common culture-independent way to identify bacteria, is often critiqued for lacking species-level resolution. Here, we extensively evaluate classification schemes for species-level bacterial annotation of 16S amplicon data from bladder bacteria. Our results show that the proper choice of taxonomic database and variable region of the 16S rRNA gene sequence makes species level identification possible. We also show that this improvement can be achieved through the more careful application of existing methods and resources. Species-level information may deepen our understanding of associations between bacteria in the bladder and bladder conditions such as lower urinary tract symptoms and urinary tract infections.