Sequencing introduced false positive rare taxa lead to biased microbial community diversity, assembly, and interaction interpretation in amplicon studies

Spatial Distribution Patterns and Assembly Processes of Abundant and Rare Fungal Communities in Pinus sylvestris var. mongolica Forests

Revealing the biogeography and community assembly mechanisms of soil microorganisms is crucial in comprehending the diversity and maintenance of Pinus sylvestris var. mongolica forests. Here, we used high-throughput sequencing techniques and null model analysis to explore the distribution patterns and assembly processes of abundant, rare, and total fungal communities in P. sylvestris var. mongolica forests based on a large-scale soil survey across northern China. Compared to the abundant and total taxa, the diversity and composition of rare taxa were found to be more strongly influenced by regional changes and environmental factors. At the level of class, abundant and total taxa were dominated by Agaricomycetes and Leotiomycetes, while Agaricomycetes and Sordariomycetes were dominant in the rare taxa. In the functional guilds, symbiotrophic fungi were advantaged in the abundant and total taxa, and saprotrophic fungi were advantaged in the rare taxa. The null model revealed that the abundant, rare, and total taxa were mainly governed by stochastic processes. However, rare taxa were more influenced by deterministic processes. Precipitation and temperature were the key drivers in regulating the balance between stochastic and deterministic processes. This study provides new insights into both the biogeographical patterns and assembly processes of soil fungi in P. sylvestris var. mongolica forests.

Dynamics of rhizosphere microbial structure and function associated with the biennial bearing of moso bamboo

Moso bamboo (Phyllostachys edulis) is a valuable nontimber forestry product with a biennial cycle, producing abundant bamboo shoots within one year (on-year) and few shoots within the following year (off-year). Moso bamboo plants undergo clonal reproduction, resulting in similar genetic backgrounds. However, the number of moso bamboo shoots produced each year varies. Despite this variation, the impact of soil nutrients and the root microbiome on the biennial bearing of moso bamboo is poorly understood. We collected 139 soil samples and determined 14 major physicochemical properties of the rhizosphere, rhizoplane, and bulk soil in different seasons (i.e., the growing and deciduous seasons) and different years (i.e., on- and off-years). Based on 16S rRNA and metagenomic sequencing, major variations were found in the rhizospheric microbial composition during different seasons and years in the moso bamboo forest. Environmental driver analysis revealed that essential nutrients (i.e., SOC, TOC, TN, P, and NH4+) were the main drivers of the soil microbial community composition and were correlated with the on- and off-year cycles. Moreover, 19 MAGs were identified as important biomarkers that could distinguish on- and off-years. We found that both season and year influenced both the microbial community structure and functional pathways through the biosynthesis of nutrients that potentially interact with the moso bamboo growth rhythm, especially the on-year root-associated microbiome, which had a greater abundance of specific nutrients such as gibberellins and vitamin B6. This work provides a dynamic perspective of the differential responses of various on- and off-year microbial communities and enhances our understanding of bamboo soil microbiome biodiversity and stability.

YACHT: an ANI-based statistical test to detect microbial presence/absence in a metagenomic sample

MOTIVATION

In metagenomics, the study of environmentally associated microbial communities from their sampled DNA, one of the most fundamental computational tasks is that of determining which genomes from a reference database are present or absent in a given sample metagenome. Existing tools generally return point estimates, with no associated confidence or uncertainty associated with it. This has led to practitioners experiencing difficulty when interpreting the results from these tools, particularly for low-abundance organisms as these often reside in the "noisy tail" of incorrect predictions. Furthermore, few tools account for the fact that reference databases are often incomplete and rarely, if ever, contain exact replicas of genomes present in an environmentally derived metagenome.

RESULTS

We present solutions for these issues by introducing the algorithm YACHT: Yes/No Answers to Community membership via Hypothesis Testing. This approach introduces a statistical framework that accounts for sequence divergence between the reference and sample genomes, in terms of ANI, as well as incomplete sequencing depth, thus providing a hypothesis test for determining the presence or absence of a reference genome in a sample. After introducing our approach, we quantify its statistical power and how this changes with varying parameters. Subsequently, we perform extensive experiments using both simulated and real data to confirm the accuracy and scalability of this approach.

AVAILABILITY AND IMPLEMENTATION

The source code implementing this approach is available via Conda and at https://github.com/KoslickiLab/YACHT. We also provide the code for reproducing experiments at https://github.com/KoslickiLab/YACHT-reproducibles.

Bovine milk osteopontin improved intestinal health of pregnant rats fed a high-fat diet through improving bile acid metabolism

The main purpose of the current study was to investigate the ameliorative effects of bovine milk osteopontin (bmOPN) on the gut dysfunction of pregnant rats fed a high-fat diet (HFD). Bovine milk osteopontin was supplemented at a dose of 6 mg/kg body weight. Bovine milk osteopontin supplementation during pregnancy reduced colonic inflammation of HFD dams, and it also increased the colonic expression of ZO-1 and claudin-4 of HFD dams. Bovine milk osteopontin significantly enriched the relative abundance of Bacteroidetes, whereas it decreased Proteobacteria, Helicobacteraceae, and Desulfovibrionaceae in feces of HFD dams. The levels of isobutyric acid and pentanoic acid in the HFD + bmOPN group were higher than that of the HFD group. Functional predication analysis of microbial genomes revealed that bmOPN supplementation to HFD pregnancies changed 4 Kyoto Encyclopedia of Genes and Genomes pathways including bile acid biosynthesis. Further, bmOPN enriched hepatic taurochenodeoxycholic acid and tauroursodeoxycholic acid plus taurohyodeoxycholic acid in the gut of HFD maternal rats. Our findings suggested that bmOPN improved the gut health of HFD pregnant rats partially through modulating bile acid biosynthesis.

Core taxa drive microeukaryotic community stability of a deep subtropical reservoir after complete mixing

Microeukaryotes are key for predicting the change of ecosystem processes in the face of a disturbance. However, their vertical responses to multiple interconnected factors caused by water mixing remain unknown. Here, we conducted a 12-month high-frequency study to compare the impacts of mixing disturbances on microeukaryotic community structure and stability over different depths in a stratified reservoir. We demonstrate that core and satellite microeukaryotic compositions and interactions in surface waters were not resistant to water mixing, but significantly recovered. This was because the water temperature rebounded to the pre-mixing level. Core microeukaryotes maintained community stability in surface waters with high recovery capacity after water mixing. In contrast, the changes in water temperature, chlorophyll-a, and nutrients resulted in steep and prolonged variations in the bottom core and satellite microeukaryotic compositions and interactions. Under low environmental fluctuation, the recovery of microbial communities did not affect nutrient cycling in surface waters. Under high environmental fluctuation, core and satellite microeukaryotic compositions in bottom waters were significantly correlated with the multi-nutrient cycling index. Our findings shed light on different mechanisms of plankton community resilience in reservoir ecosystems to a major disturbance over depths, highlighting the role of bottom microeukaryotes in nutrient cycling.

Prokaryotic taxonomy and functional diversity assessment of different sequencing platform in a hyper-arid Gobi soil in Xinjiang Turpan Basin, China

Turpan Basin located in the eastern Xinjiang is a typical arid inland basin with extremely scarce water resources and a fragile ecosystem. Prokaryotic communities with unique genetic and physiological modifications can survive and function in such harsh environments, offering diverse microbial resources. However, numerous microbes can enter the viable but non-culturable state because of drought stress in the desert soil. In this work, next generation sequencing (NGS) technology based on DNA nanoball sequencing platform (DNBSEQ-G400) and sequencing-by-synthesis platform (NovaSeq 6000) were applied to analyze the prokaryotic diversity in three hyper-arid Gobi soils from Flaming Mountain, Toksun, and Kumtag. The comparison between two platforms indicated that DNBSEQ-G400 had better repeatability and could better reflect the prokaryotic community of this hyper-arid region. The diversity analysis based on DNBSEQ-G400 identified a total of 36 bacterial phyla, including Pseudomonadota, Bacteroidota, Bacillota, Actinomycetota, Methanobacteriota, Acidobacteriota, Nitrososphaerota, and Planctomycetota. The environmental factors, including soluble salt, available potassium, total nitrogen, and organic matter, were positively correlated with the abundance of most prokaryote. In addition, the prokaryotic community assembly in hyper-arid soil was well described by neutral-based models, indicating that the community assembly was mainly controlled by stochastic processes. Finally, the phylogenetic analysis of Actinomycetota proved that such extremophiles played an important role in the ecosystems they colonize. Overall, our result provides a reference for choosing the appropriate sequencing platform and a perspective for the utilization of soil microbial resources from hyper-arid regions.

Composition, function, and timing: exploring the early-life gut microbiota in piglets for probiotic interventions

BACKGROUND

The establishment of a robust gut microbiota in piglets during their early developmental stage holds the potential for long-term advantageous effects. However, the optimal timeframe for introducing probiotics to achieve this outcome remains uncertain.

RESULTS

In the context of this investigation, we conducted a longitudinal assessment of the fecal microbiota of 63 piglets at three distinct pre-weaning time points. Simultaneously, we gathered vaginal and fecal samples from 23 sows. Employing 16S rRNA gene and metagenomic sequencing methodologies, we conducted a comprehensive analysis of the fluctuation patterns in microbial composition, functional capacity, interaction networks, and colonization resistance within the gut microbiota of piglets. As the piglets progressed in age, discernible modifications in intestinal microbial diversity, composition, and function were observed. A source-tracking analysis unveiled the pivotal role of fecal and vaginal microbiota derived from sows in populating the gut microbiota of neonatal piglets. By D21, the microbial interaction network displayed a more concise and efficient configuration, accompanied by enhanced colonization resistance relative to the other two time points. Moreover, we identified three strains of Ruminococcus sp. at D10 as potential candidates for improving piglets' weight gain during the weaning phase.

CONCLUSIONS

The findings of this study propose that D10 represents the most opportune juncture for the introduction of external probiotic interventions during the early stages of piglet development. This investigation augments our comprehension of the microbiota dynamics in early-life of piglets and offers valuable insights for guiding forthcoming probiotic interventions.

The newest Oxford Nanopore R10.4.1 full-length 16S rRNA sequencing enables the accurate resolution of species-level microbial community profiling

The long-read amplicon provides a species-level solution for the community. With the improvement of nanopore flowcells, the accuracy of Oxford Nanopore Technologies (ONT) R10.4.1 has been substantially enhanced, with an average of approximately 99%. To evaluate its effectiveness on amplicons, three types of microbiomes were analyzed by 16S ribosomal RNA (hereinafter referred to as "16S") amplicon sequencing using Novaseq, Pacbio sequel II, and Nanopore PromethION platforms (R9.4.1 and R10.4.1) in the current study. We showed the error rate, recall, precision, and bias index in the mock sample. The error rate of ONT R10.4.1 was greatly reduced, with a better recall in the case of the synthetic community. Meanwhile, in different types of environmental samples, ONT R10.4.1 analysis resulted in a composition similar to Pacbio data. We found that classification tools and databases influence ONT data. Based on these results, we conclude that the ONT R10.4.1 16S amplicon can also be used for application in environmental samples. IMPORTANCE The long-read amplicon supplies the community with a species-level solution. Due to the high error rate of nanopore sequencing early on, it has not been frequently used in 16S studies. Oxford Nanopore Technologies (ONT) introduced the R10.4.1 flowcell with Q20+ reagent to achieve more than 99% accuracy as sequencing technology advanced. However, there has been no published study on the performance of commercial PromethION sequencers with R10.4.1 flowcells on 16S sequencing or on the impact of accuracy improvement on taxonomy (R9.4.1 to R10.4.1) using 16S ONT data. In this study, three types of microbiomes were investigated by 16S ribosomal RNA (rRNA) amplicon sequencing using Novaseq, Pacbio sequel II, and Nanopore PromethION platforms (R9.4.1 and R10.4.1). In the mock sample, we displayed the error rate, recall, precision, and bias index. We observed that the error rate in ONT R10.4.1 is significantly lower, especially when deletions are involved. First and foremost, R10.4.1 and Pacific Bioscience platforms reveal a similar microbiome in environmental samples. This study shows that the R10.4.1 full-length 16S rRNA sequences allow for species identification of environmental microbiota.

Effects of ammonia nitrogen and organic carbon availability on microbial community structure and ecological interactions in a full-scale partial nitritation and anammox (PN/A) system

Nutrient availability significantly impacts microbial biosynthesis, cell growth, and cell cycle progression. In this study, a full-scale plug-flow partial nitritation/anammox (PN/A) system was used to investigate variations in the microbial community structure in both immobilized carriers and flocs, as well as a gradual decrease in nutrient availability from upstream to downstream. We found that reduced ammonia nitrogen (from 150.4 to 30.6 mg/L) and organic carbon (from 415.7 to 342.8 mg/L) availability significantly lowered microbial diversity and altered microbial communities in biofilms other than flocs from upstream to downstream. The abundance of all anammox bacteria increased by 1.97 times, from 3.25 × 1010 to 6.40 × 1010 copies per gram of wet sludge, in the biofilm core microbiome. Furthermore, from upstream to downstream, taxa with lower ribosomal RNA operon copy numbers were consistently enriched in both biofilm and floc communities, indicating that slow-growing microorganisms are more likely to be enriched in low-nutrient environments. Rare taxa with a relative abundance of less than 0.1% exhibited unique metabolic functions, including amino acid, carbohydrate, cofactor, and vitamin metabolisms, which was inferred by PICRUST2 and persisted across the nutrient gradient in both the biofilm and floc communities. Despite their low abundance, they may play important roles in mediating the stability and function of the PN/A system. Overall, the results demonstrate the impact of a naturally formed ammonia nitrogen and organic carbon gradient in a full-scale plug-flow PN/A installation on nutrient availability and its effects on microbial diversity, community composition, and microbial interactions, which expands our fundamental understanding of this energy-efficient and promising biotechnology for treating high-strength ammonium wastewater.

Denoising sparse microbial signals from single-cell sequencing of mammalian host tissues

Existing genomic sequencing data can be used to study host-microbiome ecosystems, however distinguishing signals originating from truly present microbes versus contaminating species and artifacts is a substantial and often prohibitive challenge. Here we show that emerging sequencing technologies definitely capture reads from present microbes. We developed SAHMI, a computational resource to identify truly present microbial nucleic acids and filter contaminants and spurious false-positive taxonomic assignments from standard transcriptomic sequencing of mammalian tissues. In benchmark studies, SAHMI correctly identifies known microbial infections present in diverse tissues, and we validate SAHMI's enrichment for correctly classified, truly present species using multiple orthogonal computational experiments. The application of SAHMI to single-cell and spatial genomic data thus enables co-detection of somatic cells and microorganisms and joint analysis of host-microbiome ecosystems.

Urban Microbiomes in Narita, Chiba, Japan: Shotgun Metagenome Sequences of a Train Station

Here, we performed shotgun metagenome sequencing of swab samples collected on floors at a train station in Narita City, Chiba, Japan. The taxonomic analysis revealed that Actinobacteria and Proteobacteria were the dominant phyla. The data will contribute to insight into the microbiome community on the surfaces of urban built environments.