Marker Gene Sequencing Research Articles

TCM-Suite: A comprehensive and holistic platform for Traditional Chinese Medicine component identification and network pharmacology analysis.

DNA-based biological ingredient identification and downstream pharmacology network analysis are commonly used in research for Traditional Chinese Medicine preparations (TCM formulas). Advancements in bioinformatics tools and the accumulation of related data have become driving forces for progress in this field. However, a lack of a platform integrating biological ingredient identification and downstream pharmacology network analysis hinders the deep understanding of TCM. In this study, we developed the TCM-Suite platform composed of two sub-databases, Holmes-Suite and Watson-Suite, for TCM biological ingredient identification and network pharmacology investigation, respectively, both are among the most complete: In the Holmes-Suite, we collected and processed six types of marker gene sequences, accounting for 1,251,548 marker gene sequences. In the Watson-Suite, we curated and integrated a massive number of entries from more than 10 public databases. Importantly, we developed a comprehensive pipeline to integrate TCM biological ingredient identification and downstream network pharmacology research, allowing users to simultaneously identify components of a TCM formula and analyze its potential pharmacology mechanism. Furthermore, we designed search engines and a user-friendly platform to better search and visualize these rich resources. TCM-Suite is a comprehensive and holistic platform for TCM-based drug discovery and repurposing. TCM-Suite website: http://TCM-Suite.AImicrobiome.cn.

Cropping System Diversification Influences Soil Microbial Diversity in Subtropical Dryland Farming Systems

Conventional dryland cropping systems are characterised by low crop diversity and frequent fallows. This has significant impacts on soil microbes that underpin soil function. Diversifying crop rotations can potentially counter these effects; however, limited data exists on the impacts of diversified crop rotations on soil microbes in drylands. Using phylogenetic marker gene sequencing, we characterised soil microbial diversity in conventional and diversified dryland crop rotations in subtropical Australia. This included winter and summer dominant rotations. Conventional systems were cereal-dominant with a crop-fallow rotation. Diversified systems included greater crop diversity, double crops, cover crops, and a multi-year ley pasture. In summer rotations with increased crop diversity and cover crops, bacterial and fungal richness increased, and distinct communities were formed compared to fallow land. Often, these community shifts were associated with greater soil organic carbon (SOC) and nitrogen. All winter rotations had distinct fungal communities and ley pasture resulted in greater fungal diversity compared to other rotations. No effects of the winter rotations were evident on bacterial communities. Our results show that diversification of dryland crop rotations leads to significant shifts in soil microbial communities in both winter and summer cropping systems. Both summer and winter rotations incorporating cover crops and ley pasture had greater soil respiration and nitrogen, indicating increases in soil fertility. These rotations may offer an alternative to conventional crop-fallow rotations to counter ongoing declines in soil health.

Mining of Wheat Pm2 Alleles for Goal-Oriented Marker-Assisted Breeding.

Powdery mildew of wheat, caused by Blumeria graminis f. sp. tritici (Bgt), is a devastating disease that seriously reduces yield and quality worldwide. Utilization of plant resistance genes is an attractive and effective strategy for controlling this disease. Among the reported powdery mildew (Pm) resistance genes, Pm2 exhibits a diverse resistance spectrum among its multiple alleles. It has been widely used in China for resistance breeding for powdery mildew. To mine more Pm2 alleles and clarify their distribution, we screened 33 wheat cultivars/breeding lines carrying Pm2 alleles from 641 wheat genotypes using diagnostic and Pm2-linked markers. To further investigate the relationships within the Pm2 alleles, we compared their resistance spectra, polymorphism of marker alleles and gene sequences, and found that they have identical marker alleles and gene sequences but diverse resistance spectra. In addition, the diagnostic kompetitive allele-specific PCR (KASP) marker, YTU-KASP-Pm2, was developed and was shown to detect all the Pm2 alleles in the different genetic backgrounds. These findings provide valuable information for the distribution and rational use of Pm2 alleles, push forward their marker-assisted breeding (MAS), and hence improve the control of wheat powdery mildew.

Influence of Post-Milking Treatment on Microbial Diversity on the Cow Teat Skin and in Milk

In dairy cattle, teat disinfection at the end of milking is commonly applied to limit colonization of the milk by pathogenic microorganisms via the teat canal. The post-milking products used can irritate the teat skin and unbalance its microbial population. Our study aimed to assess the impact of different milking products on the balance of the microbial communities on the teat skin of cows and in their milk. For 12 weeks at the end of each milking operation, three groups of seven Holstein dairy cows on pasture received either a chlorhexidine gluconate-based product (G) or a hydrocolloidal water-in-oil emulsion (A), or no post-milking product (C). The composition of the bacterial and fungal communities on the teat skin and in the milk were characterized using a culture-dependent method and by high-throughput sequencing of marker genes to obtain amplicon sequence variants (ASVs). The individual microbiota on the cows’ teat skin was compared for the first time to that of a cow pool. In contrast to the milk, the post-milking treatment influenced the microbiota of the teat skin, which revealed a high microbial diversity. The water-in-oil emulsion appeared to slightly favour lactic acid bacteria and yeasts and to limit the development of undesirable bacteria such as Pseudomonas and Staphylococcus.

Phylogenetic analysis confirms the taxonomic placement of the marine flagellate Hermesinum adriaticum (Thecofilosea, Cercozoa, Rhizaria).

Hermesinum adriaticum is a rare marine and brackish flagellate that is of considerable interest due to its markable and fossilizable siliceous skeleton. Based on this skeleton, Hermesinum was initially considered a microalga of the Dictyochophyceae (Ochrophyta, Stramenopiles). Later on, it was assigned to the Ebriida due to its similarity to Ebria tripartita. The taxonomic assignment of the Ebriida, however, changed several times until it was placed within the Thecofilosea (Cercozoa, Rhizaria), based on genetic data of E.tripartita. We sequenced the 18S marker gene sequence of Hermesinum and confirm the close relationship of Ebria and Hermesinum.

Flavobacterium ammonificans sp. nov. and Flavobacterium ammoniigenes sp. nov., ammonifying bacteria isolated from surface river water.

Three aerobic, Gram-stain-negative, non-motile, rod-shaped bacteria, designated as strains SHINM13T, GENT5T and GENT11 were isolated from surface river water (Saitama Prefecture, Japan). SHINM13T and GENT11 were positive for catalase, whereas GENT5T was negative. Phylogenetic analyses based on the 16S rRNA gene (1341 bp) or 40 marker gene (34,513 bp) sequences revealed that the strains formed distinct phylogenetic lineages within the genus Flavobacterium. The three strains shared 99.3-99.6 % 16S rRNA gene sequence similarity among each other. The average nucleotide identity by orthology (OrthoANI) and digital DNA-DNA hybridization (dDDH) values between strains SHINM13T and GENT11 were 96.56 and 82.1 %, respectively, and those between SHINM13T and GENT5T were 83.46 % and 52.9 %, respectively. The major cellular fatty acids were C15 : 1ω6c, iso-C15 : 0, iso-C15 : 1G, anteiso-C15 : 0 and iso-C15 : 0 3-OH. The major polar lipid was phosphatidylethanolamine. SHINM13T and GENT5T contained menaquinone-6 (MK-6) as the predominant respiratory quinone, and their DNA G+C contents were 34.4 and 35.1 mol%, respectively. Genome sequencing of the three isolates revealed a genome size of 2.26-2.40 Mbp. Furthermore, all three isolates converted dissolved organic nitrogen to ammonium during cell growth. On the basis of the results of phenotypic and phylogenetic analyses, strains SHINM13T and GENT11 and GENT5T represent two distinct novel species in the genus Flavobacterium, for which the names Flavobacterium ammonificans sp. nov. (type strain SHINM13T =JCM 34684T =NCIMB 15379T) and Flavobacterium ammoniigenes sp. nov. (type strain GENT5T =JCM 32249T=NCIMB 15380T) are proposed.

Identification of the rhizosphere microbes that actively consume plant-derived carbon

Rhizosphere microbial communities play essential roles in plant growth and health, with plant-derived carbon serving as the primary resource fueling the growth and activity of these root-associated communities. However, not all rhizosphere microbes are likely equivalent in their ability to metabolize root-derived carbon inputs, and far fewer studies have sought to identify the rhizosphere taxa, and the traits of those taxa that actively consume plant photosynthates. Here, we labeled wheat plants (Triticum aestivum L.) with 13C–CO2, combining stable isotope probing, quantitative PCR, marker gene sequencing, and shotgun metagenomic sequencing to identify rhizosphere microbes that metabolized plant-derived carbon and their genomic attributes. Those rhizosphere taxa that incorporated the plant-derived 13C were not necessarily the most abundant taxa in the rhizosphere. Rhizosphere microbes clearly differed in their capacity to consume plant-derived carbon, with the bacterial photosynthate consumers having distinct metabolic and genomic profiles with higher estimated potential growth rates and more genes associated with carbon metabolism, resource uptake, and potential for plant growth promotion. Together, this work highlights the important roles and the differential contributions of rhizosphere microbes to belowground carbon dynamics, building a more nuanced understanding of the complexity of plant-microbe interactions in the rhizosphere.

Fine-Scale Adaptations to Environmental Variation and Growth Strategies Drive Phyllosphere Methylobacterium Diversity.

ABSTRACTMethylobacterium is a prevalent bacterial genus of the phyllosphere. Despite its ubiquity, little is known about the extent to which its diversity reflects neutral processes like migration and drift, versus environmental filtering of life history strategies and adaptations. In two temperate forests, we investigated how phylogenetic diversity within Methylobacterium is structured by biogeography, seasonality, and growth strategies. Using deep, culture-independent barcoded marker gene sequencing coupled with culture-based approaches, we uncovered a considerable diversity of Methylobacterium in the phyllosphere. We cultured different subsets of Methylobacterium lineages depending upon the temperature of isolation and growth (20°C or 30°C), suggesting long-term adaptation to temperature. To a lesser extent than temperature adaptation, Methylobacterium diversity was also structured across large (>100 km; between forests) and small (<1.2 km; within forests) geographical scales, among host tree species, and was dynamic over seasons. By measuring the growth of 79 isolates during different temperature treatments, we observed contrasting growth performances, with strong lineage- and season-dependent variations in growth strategies. Finally, we documented a progressive replacement of lineages with a high-yield growth strategy typical of cooperative, structured communities in favor of those characterized by rapid growth, resulting in convergence and homogenization of community structure at the end of the growing season. Together, our results show how Methylobacterium is phylogenetically structured into lineages with distinct growth strategies, which helps explain their differential abundance across regions, host tree species, and time. This work paves the way for further investigation of adaptive strategies and traits within a ubiquitous phyllosphere genus.

Rhizosphere and Endosphere Bacterial Communities Survey by Metagenomics Approach.

The diversity of microbes associated with plant roots is in the order of tens of thousands of species. It is estimated that only 0.1-1.0% of the living bacteria present in soils can be cultured under standard conditions. The microbial marker-gene sequence data and the next-generation sequencing technologies have enabled systemic studies of root-associated microbiomes. Molecular techniques can be used to generate comprehensive taxonomic profiles of the microorganisms present in roots. The aim of this chapter is to provide a standard method for the obtention of rhizosphere and endosphere fractions, and a generic workflow of the Quantitative Insights Into Microbial Ecology version 2 (QIIME2) software to analysis of 16S rRNA marker-gene.

Microbiota composition is moderately associated with greenspace composition in a UK cohort of twins

Exposure to natural environments, known as greenspace, appears to positively influence health, yet the mechanisms are unclear. Given that gut microbiota are associated with inflammatory disorders more prevalent in urban areas and individuals with lower greenspace exposure, microbiota may act as a mediator between greenspace and health. Using 2443 participants of the TwinsUK cohort, microbiota differences were compared in relation to rural/urban living and with quantiles of area-level greenspace at three different neighbourhood distances: 800 m, 3000 m and 5000 m. Using microbiota data captured from faecal samples using 16S rRNA marker gene sequencing, small compositional differences in association with 3000 m greenspace (p = 0.003) in models adjusted for confounders of microbiota variance (sequencing depth, antibiotics use, body mass index, frailty, age, diet, region and socioeconomic variables) were observed. Differences in abundances of genus were observed for all measures of greenspace in adjusted models; a key pathogenic genus was increased in abundance in association with urbanicity (Escherichia/Shigella, logFC = 0.73742, padj <0.001). Further, utilising the twin structure, within-pair differences in microbiota composition were compared and associations with 800 m greenspace observed (factor level significance in association with greatest difference, β = 0.08, p = 0.0162) as were differences in Escherichia/Shigella. The microbiota signature of those with a greater exposure to greenspace, but not necessarily explicitly rural individuals, was distinct from other individuals, suggesting microbiota as a potential mediator for greenspace and health.

Stochastic processes regulate belowground community assembly in alpine grasslands on the Tibetan Plateau.

Understanding biogeographical patterns and underlying processes of belowground community assembly is crucial for predicting soil functions and their responses to global environmental change. However, little is known about potential differences of belowground community assembly among bacteria, fungi, protists and soil animals, particularly for alpine ecosystems. Based on the combination of large-scale field sampling, high-throughput marker-gene sequencing and multiple statistical analyses, we explored patterns and drivers of belowground community assembly in alpine grasslands on the Tibetan Plateau. Our results revealed that the distance-decay rates varied among trophic levels, with organisms of higher trophic level having weaker distance-decay pattern. The spatial and environmental variables explained limited variations of belowground communities. By contrast, the stochastic processes, mainly consisting of dispersal limitation and drift, played a primary role in regulating belowground community assembly. Moreover, the relative importance of stochastic processes varied among trophic levels, with the role of dispersal limitation weakening whereas that of drift enhancing in the order of bacteria, fungi, protists and soil animals. These findings advance our understanding of patterns and mechanisms driving belowground community assembly in alpine ecosystems and provide a reference basis for predicting the dynamics of ecosystem functions under changing environment.

From DNA sequences to microbial ecology: Wrangling NEON soil microbe data with the neonMicrobe R package

AbstractSoil microbial communities play critical roles in various ecosystem processes, but studies at a large spatial and temporal scale have been challenging due to the difficulty in finding the relevant samples in available data sets as well as the lack of standardization in sample collection and processing. The National Ecological Observatory Network (NEON) has been collecting soil microbial community data multiple times per year for 47 terrestrial sites in 20 eco‐climatic domains, producing one of the most extensive standardized sampling efforts for soil microbial biodiversity to date. Here, we introduce the neonMicrobe R package—a suite of downloading, preprocessing, data set assembly, and sensitivity analysis tools for NEON’s newly published 16S and ITS amplicon sequencing data products which characterize soil bacterial and fungal communities, respectively. neonMicrobe is designed to make these data more accessible to ecologists without assuming prior experience with bioinformatic pipelines. We describe quality control steps used to remove quality‐flagged samples, report on sensitivity analyses used to determine appropriate quality filtering parameters for the DADA2 workflow, and demonstrate the immediate usability of the output data by conducting standard analyses of soil microbial diversity. The sequence abundance tables produced by neonMicrobe can be linked to NEON’s other data products (e.g., soil physical and chemical properties, plant community composition) and soil subsamples archived in the NEON Biorepository. We provide recommendations for incorporating neonMicrobe into reproducible scientific workflows, discuss technical considerations for large‐scale amplicon sequence analysis, and outline future directions for NEON‐enabled microbial ecology. In particular, we believe that NEON marker gene sequence data will allow researchers to answer outstanding questions about the spatial and temporal dynamics of soil microbial communities while explicitly accounting for scale dependence. We expect that the data produced by NEON and the neonMicrobe R package will act as a valuable ecological baseline to inform and contextualize future experimental and modeling endeavors.

Pathways and microbiome modifications related to surgery and enterocolitis in Hirschsprung disease.

Hirschsprung disease (HSCR) is a congenital anomaly of the enteric nervous system. Abnormal microbiome composition was reported in HSCR patients. In this study, we addressed and analyzed microbiome modifications with relation tosurgery and HSCR associated enterocolitis (HAEC). The faecal microbiome of 31 HSCR patients (overall 64 samples) was analyzed. HAEC was diagnosed and classified according to a combination of Pastor's and Elhalabi's criteria. Stool samples were analyzed by 16S sequencing (7 out of 9 polymorphic regions). Compositional and relative abundance profiles, as well as the functional potentials of the microbial community, were analyzed with the marker gene sequencing profiles using PICRUSt. The relative abundance of Bacteroidetes showed a severe decrease with slow recovery after surgery. Conversely, Proteobacteria transiently increased their abundance. Noteworthy, a strong linkage has been found between Proteobacteria descendants and HAEC occurrences. The inferred functional analysis indicated that virulence factors and fimbriae or pili might be associated with HAEC. Our study, addressing microbiome dynamics, demonstrated relevant changes after surgical manipulation. Alpha-diversity analyses indicated that surgery deeply affects microbiome composition. Proteobacteria and Enterobacteriaceae seem to play a pivotal role in HAEC occurrences. Several virulence factors, such as fimbriae or pili, might explain the HAEC-predisposing potential of selected microbiomes. These results suggest some innovative therapeutic approaches that deserve to be tested in appropriate clinical trials.

The complete chloroplast genome of a shrub species, Smilax glabra (Smilacaceae) from Guangdong, China

Smilax glabra is a perennial woody scandent shrub, of which the dried aerial tuber has been used as Chinese medicine. Here, we sequenced S. glabra and assembled its complete chloroplast (cp) genome. The genome is 157,889 bp in length and has a typical quadripartite structure. We annotated 131 genes, of which 84 were protein-coding genes, 37 were tRNAs and 8 were rRNA genes. Phylogenetic analysis of this genome with 26 representatives Liliales fully resolved S. glabra in a clade with S. china. The phylogenetic tree we constructed is largely consistent with recently published phylogenetic trees using both complete chloroplast genomes and marker gene sequences.

Global co‐occurrence of methanogenic archaea and methanotrophic bacteria in Microcystis aggregates

Global warming and eutrophication contribute to the worldwide increase in cyanobacterial blooms, and the level of cyanobacterial biomass is strongly associated with rises in methane emissions from surface lake waters. Hence, methane-metabolizing microorganisms may be important for modulating carbon flow in cyanobacterial blooms. Here, we surveyed methanogenic and methanotrophic communities associated with floating Microcystis aggregates in 10 lakes spanning four continents, through sequencing of 16S rRNA and functional marker genes. Methanogenic archaea (mainly Methanoregula and Methanosaeta) were detectable in 5 of the 10 lakes and constituted the majority (~50%-90%) of the archaeal community in these lakes. Three of the 10 lakes contained relatively more abundant methanotrophs than the other seven lakes, with the methanotrophic genera Methyloparacoccus, Crenothrix, and an uncultured species related to Methylobacter dominating and nearly exclusively found in each of those three lakes. These three are among the five lakes in which methanogens were observed. Operational taxonomic unit (OTU) richness and abundance of methanotrophs were strongly positively correlated with those of methanogens, suggesting that their activities may be coupled. These Microcystis-aggregate-associated methanotrophs may be responsible for a hitherto overlooked sink for methane in surface freshwaters, and their co-occurrence with methanogens sheds light on the methane cycle in cyanobacterial aggregates.

MOTUs: Profiling Taxonomic Composition, Transcriptional Activity and Strain Populations of Microbial Communities.

The mOTU profiler, or mOTUs for short, is a software tool that enables the profiling of microbial communities in terms of their taxonomic composition, relative abundance of metabolically active members, and diversity of strain populations. To this end, it maintains a database of single-copy phylogenetic marker gene sequences, which are used as a reference to which short read metagenomic and metatranscriptomic reads are mapped for the identification and quantification of microbial taxa. Here, we describe the most common use cases of the mOTU profiler in two basic protocols. Additional supporting protocols provide information on its installation and in-depth guidance on adjusting its settings for increasing or decreasing the stringency with which taxa are detected and quantified, as well as for customizing the output file format. Guidelines for understanding the profiling results are provided, along with additional information on unique features, methodological details, and the development history of the tool. © 2021 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Metagenomic and metatranscriptomic mOTU profiling Basic Protocol 2: Metagenomic SNV profiling Support Protocol 1: Installing mOTUs Support Protocol 2: Profiling pipeline-step by step Support Protocol 3: The mOTUs profiling routine using advanced parameters Support Protocol 4: Metagenomic SNV calling: advanced parameters.

EnsembleTax: an R package for determinations of ensemble taxonomic assignments of phylogenetically-informative marker gene sequences.

BackgroundHigh-throughput sequencing of phylogenetically informative marker genes is a widely used method to assess the diversity and composition of microbial communities. Taxonomic assignment of sampled marker gene sequences (referred to as amplicon sequence variants, or ASVs) imparts ecological significance to these genetic data. To assign taxonomy to an ASV, a taxonomic assignment algorithm compares the ASV to a collection of reference sequences (a reference database) with known taxonomic affiliations. However, many taxonomic assignment algorithms and reference databases are available, and the optimal algorithm and database for a particular scientific question is often unclear. Here, we present the ensembleTax R package, which provides an efficient framework for integrating taxonomic assignments predicted with any number of taxonomic assignment algorithms and reference databases to determine ensemble taxonomic assignments for ASVs.MethodsThe ensembleTax R package relies on two core algorithms: taxmapper and assign.ensembleTax. The taxmapper algorithm maps taxonomic assignments derived from one reference database onto the taxonomic nomenclature (a set of taxonomic naming and ranking conventions) of another reference database. The assign.ensembleTax algorithm computes ensemble taxonomic assignments for each ASV in a data set based on any number of taxonomic assignments determined with independent methods. Various parameters allow analysts to prioritize obtaining either more ASVs with more predicted clade names or more robust clade name predictions supported by multiple independent methods in ensemble taxonomic assignments.ResultsThe ensembleTax R package is used to compute two sets of ensemble taxonomic assignments for a collection of protistan ASVs sampled from the coastal ocean. Comparisons of taxonomic assignments predicted by individual methods with those predicted by ensemble methods show that conservative implementations of the ensembleTax package minimize disagreements between taxonomic assignments predicted by individual and ensemble methods, but result in ASVs with fewer ranks assigned taxonomy. Less conservative implementations of the ensembleTax package result in an increased fraction of ASVs classified at all taxonomic ranks, but increase the number of ASVs for which ensemble assignments disagree with those predicted by individual methods.DiscussionWe discuss how implementation of the ensembleTax R package may be optimized to address specific scientific objectives based on the results of the application of the ensembleTax package to marine protist communities. While further work is required to evaluate the accuracy of ensemble taxonomic assignments relative to taxonomic assignments predicted by individual methods, we also discuss scenarios where ensemble methods are expected to improve the accuracy of taxonomy prediction for ASVs.

Changes in Soil Microbial Communities across an Urbanization Gradient: A Local-Scale Temporal Study in the Arid Southwestern USA.

Urban development is one of the leading causes of biodiversity change. Understanding how soil microorganisms respond to urbanization is particularly important because they are crucial for the provisioning of ecosystem functions and services. Here, we collected monthly soil samples over one year across three locations representing an urbanization gradient (low-moderate-high) in the arid Southwestern USA, and we characterized their microbial communities using marker gene sequencing. Our results showed that microbial richness and community composition exhibited nonsignificant changes over time regardless of the location. Soil fungal richness was lower in moderately and highly urbanized locations, but soil bacterial/archaeal richness was not significantly different among locations. Both bacteria/archaea and fungi exhibited significant differences in community composition across locations. After inferring potential functional groups, soils in the highly urbanized location had lower proportions of arbuscular mycorrhizal fungi and soil saprotrophic fungi but had higher proportions of bacterial taxa involved in aromatic compound degradation, human pathogens, and intracellular parasites. Furthermore, ammonia-oxidizing bacteria were more abundant in the highly urbanized location, but ammonia-oxidizing archaea were more abundant in lowly and moderately urbanized locations. Together, these results highlight the significant changes in belowground microbial communities across an urbanization gradient, and these changes might have important implications for aboveground–belowground interactions, nutrient cycling, and human health.

Evaluating and Improving Small Subunit rRNA PCR Primer Coverage for Bacteria, Archaea, and Eukaryotes Using Metagenomes from Global Ocean Surveys.

ABSTRACTSmall subunit rRNA (SSU rRNA) amplicon sequencing can quantitatively and comprehensively profile natural microbiomes, representing a critically important tool for studying diverse global ecosystems. However, results will only be accurate if PCR primers perfectly match the rRNA of all organisms present. To evaluate how well marine microorganisms across all 3 domains are detected by this method, we compared commonly used primers with >300 million rRNA gene sequences retrieved from globally distributed marine metagenomes. The best-performing primers compared to 16S rRNA of bacteria and archaea were 515Y/926R and 515Y/806RB, which perfectly matched over 96% of all sequences. Considering cyanobacterial and chloroplast 16S rRNA, 515Y/926R had the highest coverage (99%), making this set ideal for quantifying marine primary producers. For eukaryotic 18S rRNA sequences, 515Y/926R also performed best (88%), followed by V4R/V4RB (18S rRNA specific; 82%)—demonstrating that the 515Y/926R combination performs best overall for all 3 domains. Using Atlantic and Pacific Ocean samples, we demonstrate high correspondence between 515Y/926R amplicon abundances (generated for this study) and metagenomic 16S rRNA (median R2 = 0.98, n = 272), indicating amplicons can produce equally accurate community composition data compared with shotgun metagenomics. Our analysis also revealed that expected performance of all primer sets could be improved with minor modifications, pointing toward a nearly completely universal primer set that could accurately quantify biogeochemically important taxa in ecosystems ranging from the deep sea to the surface. In addition, our reproducible bioinformatic workflow can guide microbiome researchers studying different ecosystems or human health to similarly improve existing primers and generate more accurate quantitative amplicon data.IMPORTANCE PCR amplification and sequencing of marker genes is a low-cost technique for monitoring prokaryotic and eukaryotic microbial communities across space and time but will work optimally only if environmental organisms match PCR primer sequences exactly. In this study, we evaluated how well primers match globally distributed short-read oceanic metagenomes. Our results demonstrate that primer sets vary widely in performance, and that at least for marine systems, rRNA amplicon data from some primers lack significant biases compared to metagenomes. We also show that it is theoretically possible to create a nearly universal primer set for diverse saline environments by defining a specific mixture of a few dozen oligonucleotides, and present a software pipeline that can guide rational design of primers for any environment with available meta’omic data.

Individuals with substance use disorders have a distinct oral microbiome pattern

BackgroundSubstance use disorder emerges from a complex interaction between genetic predisposition, life experiences, exposure, and subsequent adaptation of biological systems to the repeated use of drugs. Recently, investigators have proposed that the human microbiota may play a role in brain health and disease. In particular, the human oral microbiome is a distinct and diverse ecological niche with its composition influenced by external factors such as lifestyle, diet, and oral hygiene. This investigation examined whether individuals with substance use disorder (SU) show a different oral microbiome pattern and whether this pattern is sufficient to delineate the SU group from healthy comparison (HC) subjects. MethodsParticipants were a sub-sample (N ​= ​177) of the Tulsa 1000 (T-1000) project. We analyzed 123 SU and 54 HC subjects using 16S rRNA marker gene sequencing to characterize the oral microbiome. ResultsThe groups differed significantly based on the UniFrac distance, a phylogenetic-based measure of beta diversity, but did not differ in alpha diversity. Using a machine learning approach, microbiome features combined with socio-demographic variables successfully categorized group membership with 87%–92% accuracy, even after controlling for external factors such as smoking or alcohol consumption. SU individuals with relatively lower diversity also reported higher levels of negative reinforcement experiences associated with their primary substance of abuse. ConclusionsOral microbiome features are useful to sufficiently differentiate SU from HC subjects. There is some evidence that subjects whose drug use is driven by negative reinforcement show an impoverished oral microbiome. Taken together, the oral microbiome may help to understand the dysfunctional biological processes that promote substance use or may be pragmatically useful as a risk or severity biological marker.