Effects of PCR cycle number and DNA polymerase type on the 16S rRNA gene pyrosequencing analysis of bacterial communities

Organophosphorus mineralizing-Streptomyces species underpins uranate immobilization and phosphorus availability in uranium tailings

Phosphate-solubilizing bacteria (PSB) are important but often overlooked regulators of uranium (U) cycling in soil. However, the impact of PSB on uranate fixation coupled with the decomposition of recalcitrant phosphorus (P) in mining land remains poorly understood. Here, we combined gene amplicon sequencing, metagenome and metatranscriptome sequencing analysis and strain isolation to explore the effects of PSB on the stabilization of uranate and P availability in U mining areas. We found that the content of available phosphorus (AP), carbonate-U and Fe-Mn-U oxides in tailings was significantly (P < 0.05) higher than their adjacent soils. Also, organic phosphate mineralizing (PhoD) bacteria (e.g., Streptomyces) and inorganic phosphate solubilizing (gcd) bacteria (e.g., Rhodococcus) were enriched in tailings and soils, but only organic phosphate mineralizing-bacteria substantially contributed to the AP. Notably, most genes involved in organophosphorus mineralization and uranate resistance were widely present in tailings rather than soil. Comparative genomics analyses supported that organophosphorus mineralizing-Streptomyces species could increase soil AP content and immobilize U(VI) through organophosphorus mineralization (e.g., PhoD, ugpBAEC) and U resistance related genes (e.g., petA). We further demonstrated that the isolated Streptomyces sp. PSBY1 could enhance the U(VI) immobilization mediated by the NADH-dependent ubiquinol-cytochrome c reductase (petA) through decomposing organophosphorous compounds. This study advances our understanding of the roles of PSB in regulating the fixation of uranate and P availability in U tailings.

Microbiome depiction through user-adapted bioinformatic pipelines and parameters

Introduction. The role of the microbiome in health and disease continues to be increasingly recognized. However, there is significant variability in the bioinformatic protocols for analysing genomic data. This, in part, has impeded the potential incorporation of microbiomics into the clinical setting and has challenged interstudy reproducibility. In microbial compositional analysis, there is a growing recognition for the need to move away from a one-size-fits-all approach to data processing.Gap Statement. Few evidence-based recommendations exist for setting parameters of programs that infer microbiota community profiles despite these parameters significantly impacting the accuracy of taxonomic inference.Aim. To compare three commonly used programs (DADA2, QIIME2, and mothur) and optimize them into four user-adapted pipelines for processing paired-end amplicon reads. We aim to increase the accuracy of compositional inference and help standardize microbiomic protocol.Methods. Two key parameters were isolated across four pipelines: filtering sequence reads based on a whole-number error threshold (maxEE) and truncating read ends based on a quality score threshold (QTrim). Closeness of sample inference was then evaluated using a mock community of known composition.Results. We observed that raw genomic data lost were proportionate to how stringently parameters were set. Exactly how much data were lost varied by pipeline. Accuracy of sample inference correlated with increased sequence read retention. Falsely detected taxa and unaccounted for microbial constituents were unique to pipeline and parameter. Implementation of optimized parameter values led to better approximation of the known mock community.Conclusions. Microbial compositions generated based on the 16S rRNA marker gene should be interpreted with caution. To improve microbial community profiling, bioinformatic protocols must be user-adapted. Analysis should be performed with consideration for the select target amplicon, pipelines and parameters used, and taxa of interest.

Human Microbiomes and Disease for the Biomedical Data Scientist

The human microbiome is complex, variable from person to person, essential for health, and related to both the risk for disease and the efficacy of our treatments. There are robust techniques to describe microbiota with high-throughput sequencing, and there are hundreds of thousands of already-sequenced specimens in public archives. The promise remains to use the microbiome both as a prognostic factor and as a target for precision medicine. However, when used as an input in biomedical data science modeling, the microbiome presents unique challenges. Here, we review the most common techniques used to describe microbial communities, explore these unique challenges, and discuss the more successful approaches for biomedical data scientists seeking to use the microbiome as an input in their studies.

Multi-factorial examination of amplicon sequencing workflows from sample preparation to bioinformatic analysis

BACKGROUND

The development of sequencing technologies to evaluate bacterial microbiota composition has allowed new insights into the importance of microbial ecology. However, the variety of methodologies used among amplicon sequencing workflows leads to uncertainty about best practices as well as reproducibility and replicability among microbiome studies. Using a bacterial mock community composed of 37 soil isolates, we performed a comprehensive methodological evaluation of workflows, each with a different combination of methodological factors spanning sample preparation to bioinformatic analysis to define sources of artifacts that affect coverage, accuracy, and biases in the resulting compositional profiles.

RESULTS

Of the workflows examined, those using the V4-V4 primer set enabled the highest level of concordance between the original mock community and resulting microbiome sequence composition. Use of a high-fidelity polymerase, or a lower-fidelity polymerase with an increased PCR elongation time, limited chimera formation. Bioinformatic pipelines presented a trade-off between the fraction of distinct community members identified (coverage) and fraction of correct sequences (accuracy). DADA2 and QIIME2 assembled V4-V4 reads amplified by Taq polymerase resulted in the highest accuracy (100%) but had a coverage of only 52%. Using mothur to assemble and denoise V4-V4 reads resulted in a coverage of 75%, albeit with marginally lower accuracy (99.5%).

CONCLUSIONS

Optimization of microbiome workflows is critical for accuracy and to support reproducibility and replicability among microbiome studies. These considerations will help reveal the guiding principles of microbial ecology and impact the translation of microbiome research to human and environmental health.

Best practices in metabarcoding of fungi: From experimental design to results

The development of high-throughput sequencing (HTS) technologies has greatly improved our capacity to identify fungi and unveil their ecological roles across a variety of ecosystems. Here we provide an overview of current best practices in metabarcoding analysis of fungal communities, from experimental design through molecular and computational analyses. By reanalysing published data sets, we demonstrate that operational taxonomic units (OTUs) outperform amplified sequence variants (ASVs) in recovering fungal diversity, a finding that is particularly evident for long markers. Additionally, analysis of the full-length ITS region allows more accurate taxonomic placement of fungi and other eukaryotes compared to the ITS2 subregion. Finally, we show that specific methods for compositional data analyses provide more reliable estimates of shifts in community structure. We conclude that metabarcoding analyses of fungi are especially promising for integrating fungi into the full microbiome and broader ecosystem functioning context, recovery of novel fungal lineages and ancient organisms as well as barcoding of old specimens including type material.

Newly designed foraminifera primers identify habitat-specific lineages through metabarcoding analyses

Foraminifera include diverse shell-building lineages found in a wide array of aquatic habitats from the deep-sea to intertidal zones to brackish and freshwater ecosystems. Recent estimates of morphological and molecular foraminifera diversity have increased the knowledge of foraminiferal diversity, which is critical as these lineages are used as bioindicators of past and present environmental perturbation. However, a comparative analysis of foraminiferal biodiversity between their major habitats (freshwater, brackish, intertidal, and marine) is underexplored, particularly using molecular tools. Here, we present metabarcoding survey of foraminiferal diversity across different ecosystems using newly designed foraminifera-specific primers that target the hypervariable regions of the foraminifera SSU-rRNA gene (~250-300bp long). We tested these primer sets on four foraminifera species and then across several environments: the intertidal zone, coastal ecosystems, and freshwater vernal pools. We retrieved 655 operational taxonomic units (OTUs); the majority are undetermined taxa that have no closely-matching sequences in the database. Furthermore, we identified 163 OTUs with distinct habitat preferences. Most of the observed OTUs belonged to lineages of single-chambered foraminifera, including poorly explored freshwater foraminifera which encompass a clade of Reticulomyxa-like forms. Our pilot study provides the community with an additional set of newly designed and taxon-specific primers to elucidate foraminiferal diversity across different habitats.

Centennial Review: Factors affecting the chicken gastrointestinal microbial composition and their association with gut health and productive performance

Maintenance of "gut health" is considered a priority in commercial chicken farms, although a precise definition of what constitutes gut health and how to evaluate it is still lacking. In research settings, monitoring of gut microbiota has gained great attention as shifts in microbial community composition have been associated with gut health and productive performance. However, microbial signatures associated with productivity remain elusive because of the high variability of the microbiota of individual birds resulting in multiple and sometimes contradictory profiles associated with poor or high performance. The high costs associated with the testing and the need for the terminal sampling of a large number of birds for the collection of gut contents also make this tool of limited use in commercial settings. This review highlights the existing literature on the chicken digestive system and associated microbiota; factors affecting the gut microbiota and emergence of the major chicken enteric diseases coccidiosis and necrotic enteritis; methods to evaluate gut health and their association with performance; main issues in investigating chicken microbial populations; and the relationship of microbial profiles and production outcomes. Emphasis is given to emerging noninvasive and easy-to-collect sampling methods that could be used to monitor gut health and microbiological changes in commercial flocks.

Benchmarking laboratory processes to characterise low-biomass respiratory microbiota

The low biomass of respiratory samples makes it difficult to accurately characterise the microbial community composition. PCR conditions and contaminating microbial DNA can alter the biological profile. The objective of this study was to benchmark the currently available laboratory protocols to accurately analyse the microbial community of low biomass samples. To study the effect of PCR conditions on the microbial community profile, we amplified the 16S rRNA gene of respiratory samples using various bacterial loads and different number of PCR cycles. Libraries were purified by gel electrophoresis or AMPure XP and sequenced by V2 or V3 MiSeq reagent kits by Illumina sequencing. The positive control was diluted in different solvents. PCR conditions had no significant influence on the microbial community profile of low biomass samples. Purification methods and MiSeq reagent kits provided nearly similar microbiota profiles (paired Bray–Curtis dissimilarity median: 0.03 and 0.05, respectively). While profiles of positive controls were significantly influenced by the type of dilution solvent, the theoretical profile of the Zymo mock was most accurately analysed when the Zymo mock was diluted in elution buffer (difference compared to the theoretical Zymo mock: 21.6% for elution buffer, 29.2% for Milli-Q, and 79.6% for DNA/RNA shield). Microbiota profiles of DNA blanks formed a distinct cluster compared to low biomass samples, demonstrating that low biomass samples can accurately be distinguished from DNA blanks. In summary, to accurately characterise the microbial community composition we recommend 1. amplification of the obtained microbial DNA with 30 PCR cycles, 2. purifying amplicon pools by two consecutive AMPure XP steps and 3. sequence the pooled amplicons by V3 MiSeq reagent kit. The benchmarked standardized laboratory workflow presented here ensures comparability of results within and between low biomass microbiome studies.

Towards reproducible metabarcoding data: Lessons from an international cross-laboratory experiment

Advances in high-throughput sequencing (HTS) are revolutionizing monitoring in marine environments by enabling rapid, accurate and holistic detection of species within complex biological samples. Research institutions worldwide increasingly employ HTS methods for biodiversity assessments. However, variance in laboratory procedures, analytical workflows and bioinformatic pipelines impede the transferability and comparability of results across research groups. An international experiment was conducted to assess the consistency of metabarcoding results derived from identical samples and primer sets using varying laboratory procedures. Homogenized biofouling samples collected from four coastal locations (Australia, Canada, New Zealand and the USA) were distributed to 12 independent laboratories. Participants were asked to follow one of two HTS library preparation workflows. While DNA extraction, primers and bioinformatic analyses were purposefully standardized to allow comparison, many other technical variables were allowed to vary among laboratories (amplification protocols, type of instrument used, etc.). Despite substantial variation observed in raw results, the primary signal in the data was consistent, with the samples grouping strongly by geographical origin for all data sets. Simple post hoc data clean-up by removing low-quality samples gave the best improvement in sample classification for nuclear 18S rRNA gene data, with an overall 92.81% correct group attribution. For mitochondrial COI gene data, the best classification result (95.58%) was achieved after correction for contamination errors. The identified critical methodological factors that introduced the greatest variability (preservation buffer, sample defrosting, template concentration, DNA polymerase, PCR enhancer) should be of great assistance in standardizing future biodiversity studies using metabarcoding.

On the robustness of inference of association with the gut microbiota in stool, rectal swab and mucosal tissue samples

The gut microbiota plays an important role in human health and disease. Stool, rectal swab and rectal mucosal tissue samples have been used in individual studies to survey the microbial community but the consequences of using these different sample types are not completely understood. In this study, we report differences in stool, rectal swab and rectal mucosal tissue microbial communities with shotgun metagenome sequencing of 1397 stool, swab and mucosal tissue samples from 240 participants. The taxonomic composition of stool and swab samples was distinct, but less different to each other than mucosal tissue samples. Functional profile differences between stool and swab samples are smaller, but mucosal tissue samples remained distinct from the other two types. When the taxonomic and functional profiles were used for inference in association with host phenotypes of age, sex, body mass index (BMI), antibiotics or non-steroidal anti-inflammatory drugs (NSAIDs) use, hypothesis testing using either stool or rectal swab gave broadly significantly correlated results, but inference performed on mucosal tissue samples gave results that were generally less consistent with either stool or swab. Our study represents an important resource for determination of how inference can change for taxa and pathways depending on the choice of where to sample within the human gut.

Biases in bulk: DNA metabarcoding of marine communities and the methodology involved

With the growing anthropogenic pressure on marine ecosystems, the need for efficient monitoring of biodiversity grows stronger. DNA metabarcoding of bulk samples is increasingly being implemented in ecosystem assessments and is more cost-efficient and less time-consuming than monitoring based on morphology. However, before raw sequences are obtained from bulk samples, a profound number of methodological choices must be made. Here, we critically review the recent methods used for metabarcoding of marine bulk samples (including benthic, plankton and diet samples) and indicate how potential biases can be introduced throughout sampling, preprocessing, DNA extraction, marker and primer selection, PCR amplification and sequencing. From a total of 64 studies evaluated, our recommendations for best practices include to (a) consider DESS as a fixative instead of ethanol, (b) use the DNeasy PowerSoil kit for any samples containing traces of sediment, (c) not limit the marker selection to COI only, but preferably include multiple markers for higher taxonomic resolution, (d) avoid touchdown PCR profiles, (e) use a fixed annealing temperature for each primer pair when comparing across studies or institutes, (f) use a minimum of three PCR replicates, and (g) include both negative and positive controls. Although the implementation of DNA metabarcoding still faces several technical complexities, we foresee wide-ranging advances in the near future, including improved bioinformatics for taxonomic assignment, sequencing of longer fragments and the use of whole-genome information. Despite the bulk of biases involved in metabarcoding of bulk samples, if appropriate controls are included along the data generation process, it is clear that DNA metabarcoding provides a valuable tool in ecosystem assessments.

Monthly eDNA Monitoring of an Invasive Bryozoan, Bugulina californica, in Seawater Using Species-Specific Markers

Simple Summary

Bugulina californica, marine invasive bryozoan, is hard to monitor the biomass and presence because of their habitat in underwater. Additionally, they have life stage difficult to find such as larva, and we need an effective survey method to detect whole life stages for monitoring early invasion stage. Therefore, we tried to applied environmental DNA to monitor the monthly changes of B. californica in harbors of Korea. We collect seawater environmental samples and developed a molecular target species detection method to detect B. californica DNA of monthly changes. We analyzed the environmental samples using our molecular markers and calculated the DNA copies. We determined method of environmental DNA assay as effectiveness survey technique for marine invasive species which has a non-visual life stage and spatial changes of whole biomass.

Abstract

Environmental DNA (eDNA) method used by many ecologists as effective investigation tool can detect endangered species, rare species, and invasive species. In case of invasive species, eDNA method help to monitor the target species when the species was hard to detect through the traditional survey such as the early stage of invasion, low abundance, and larva or juvenile stage. The bryozoan, Bugulina californica, was known as a marine fouling invasive species in Korea since its first reported in 1978. This species expanded nationwide, and damages to ascidian aquaculture through attached on the ship hulls and artificial facilities. To monitor the distribution and biomass of invasive bryozoan, B. californica, the qPCR analysis of environmental DNA was performed on seawater samples from 12 harbors. In this study, we designed species-specific markers which can calculate the detected DNA copies of B. californica, and the presence and monitoring of this species can be more accurately estimated by environmental DNA analysis than by traditional survey, in which it is difficult to identify the species. Real-time PCR analysis using environmental DNA is an effective monitoring method that can determine both the distribution and the monthly change in biomass of B. californica in Korea.

Gut microbiota characterization in Chinese patients with alopecia areata

BACKGROUND

The gut microbiota is known to play a key role in autoimmune diseases.

OBJECTIVES

To identify and compare the characteristics in the gut microbial composition of patients with alopecia areata (AA) and healthy controls (HCs).

METHODS

In a cross-sectional discovery cohort, we enrolled 33 patients with AA and 35 HCs from the same geographic location in Shanghai, China. The 16S rRNA gene sequencing and bioinformatic analyses were conducted to analyze DNA extracted from the subjects.

RESULTS

The α-diversity of the AA group demonstrated no statistically significant differences compared with the HC group (P > 0.05). However, the overall gut microbial communities in the AA group were distinct from the HCs (P = 0.0096). We also adopted a random forest model to select three AA-associated OTU biomarkers: OTU1237(Achromobacter), OTU257(Megasphaera), and OTU1784(Lachnospiraceae Incertae Sedis).

CONCLUSION

The overall gut microbial composition for AA was distinct from that of HCs. The gut microbial markers we identified may potentially be used for earlier diagnosis and as therapeutic targets.

Effectiveness of decontamination protocols when analyzing ancient DNA preserved in dental calculus

Ancient DNA analysis of human oral microbial communities within calcified dental plaque (calculus) has revealed key insights into human health, paleodemography, and cultural behaviors. However, contamination imposes a major concern for paleomicrobiological samples due to their low endogenous DNA content and exposure to environmental sources, calling into question some published results. Decontamination protocols (e.g. an ethylenediaminetetraacetic acid (EDTA) pre-digestion or ultraviolet radiation (UV) and 5% sodium hypochlorite immersion treatments) aim to minimize the exogenous content of the outer surface of ancient calculus samples prior to DNA extraction. While these protocols are widely used, no one has systematically compared them in ancient dental calculus. Here, we compare untreated dental calculus samples to samples from the same site treated with four previously published decontamination protocols: a UV only treatment; a 5% sodium hypochlorite immersion treatment; a pre-digestion in EDTA treatment; and a combined UV irradiation and 5% sodium hypochlorite immersion treatment. We examine their efficacy in ancient oral microbiota recovery by applying 16S rRNA gene amplicon and shotgun sequencing, identifying ancient oral microbiota, as well as soil and skin contaminant species. Overall, the EDTA pre-digestion and a combined UV irradiation and 5% sodium hypochlorite immersion treatment were both effective at reducing the proportion of environmental taxa and increasing oral taxa in comparison to untreated samples. This research highlights the importance of using decontamination procedures during ancient DNA analysis of dental calculus to reduce contaminant DNA.

Nanoliter-scale next-generation sequencing library-mediated high-throughput 16S rRNA microbial community profiling

An ultra-high-throughput workflow for next-generation sequencing library construction at nanoliter scale for amplicon sequencing, termed Smartchip Nanowell Platform for Target Enrichment, was established using a nanodispenser system and a nanoliter-scale PCR chip. To demonstrate its cost and time advantages over conventional methods for library construction, quality control and pooling for large-scale samples, target amplicon sequencing of the 16S ribosomal RNA gene V3-V4 region widely used for microbial community profiling was chosen for comparison. The finding of no significant difference in microbial community profiling between the two methods strongly supports the conclusion that Smartchip Nanowell Platform for Target Enrichment is a cost-effective method for next-generation sequencing library construction for large-scale samples to conduct amplicon sequencing-based applications.

Taxonomic classification and abundance estimation using 16S and WGS-A comparison using controlled reference samples

The assessment of microbiome biodiversity is the most common application of metagenomics. While 16S sequencing remains standard procedure for taxonomic profiling of metagenomic data, a growing number of studies have clearly demonstrated biases associated with this method. By using Whole Genome Shotgun sequencing (WGS) metagenomics, most of the known restrictions associated with 16S data are alleviated. However, due to the computationally intensive data analyses and higher sequencing costs, WGS based metagenomics remains a less popular option. Selecting the experiment type that provides a comprehensive, yet manageable amount of information is a challenge encountered in many metagenomics studies. In this work, we created a series of artificial bacterial mixes, each with a different distribution of skin-associated microbial species. These mixes were used to estimate the resolution of two different metagenomic experiments - 16S and WGS - and to evaluate several different bioinformatics approaches for taxonomic read classification. In all test cases, WGS approaches provide much more accurate results, in terms of taxa prediction and abundance estimation, in comparison to those of 16S. Furthermore, we demonstrate that a 16S dataset, analysed using different state of the art techniques and reference databases, can produce widely different results. In light of the fact that most forensic metagenomic analysis are still performed using 16S data, our results are especially important.

Bacterial community profiling highlights complex diversity and novel organisms in wildlife ticks

Ticks Acari:Ixodida transmit a greater variety of pathogens than any other blood-feeding group of arthropods. While numerous microbes have been identified inhabiting Australian Ixodidae, some of which are related to globally important tick-borne pathogens, little is known about the bacterial communities within ticks collected from Australian wildlife. In this study, 1,019 ticks were identified on 221 hosts spanning 27 wildlife species. Next-generation sequencing was used to amplify the V1-2 hypervariable region of the bacterial 16S rRNA gene from 238 ticks; Amblyomma triguttatum (n = 6), Bothriocroton auruginans (n = 11), Bothriocroton concolor (n = 20), Haemaphysalis bancrofti (n = 10), Haemaphysalis bremneri (n = 4), Haemaphysalis humerosa (n = 13), Haemaphysalis longicornis (n = 4), Ixodes antechini (n = 29), Ixodes australiensis (n = 26), Ixodes fecialis (n = 13), Ixodes holocyclus (n = 37), Ixodes myrmecobii (n = 1), Ixodes ornithorhynchi (n = 10), Ixodes tasmani (n = 51) and Ixodes trichosuri (n = 3). After bioinformatic analyses, over 14 million assigned bacterial sequences revealed the presence of recently described bacteria 'Candidatus Borrelia tachyglossi', 'Candidatus Neoehrlichia australis', 'Candidatus Neoehrlichia arcana' and 'Candidatus Ehrlichia ornithorhynchi'. Furthermore, three novel Anaplasmataceae species were identified in the present study including; a Neoehrlichia sp. in I. australiensis and I. fecialis collected from quenda (Isoodon fusciventer) (Western Australia), an Anaplasma sp. from one B. concolor from echidna (Tachyglossus aculeatus) (New South Wales), and an Ehrlichia sp. from a single I. fecialis parasitising a quenda (WA). This study highlights the diversity of bacterial genera harboured within wildlife ticks, which may prove to be of medical and/or veterinary importance in the future.

Next-generation sequencing as a screening tool for foodborne pathogens in fresh produce

Next generation sequencing (NGS) approaches are increasingly applied to tracing microbial contaminants entering the food chain due to NGS' untargeted nature and ability to investigate non-culturable (and/or difficult to culture) organisms while yielding genomic information about the microbiota. So far, a plethora of microbes has been shown to be associated with fresh produce, but few studies have utilised NGS to identify contamination with human pathogens. This study aims to establish the limit of detection (LoD) for Salmonella and phage MS2 (a Norovirus surrogate) contamination of fresh produce employing NGS approaches on the Illumina MiSeq: 16S amplicon-sequencing, and RNA-seq, using ScriptSeq (Illumina) and NEBNext (New England BioLabs) kits. ScriptSeq proved the most sensitive approach; delivering an LoD of 10⁴ CFU reaction^-1 (Colony Forming Units) for Salmonella and 10⁵ PFU reaction^-1 (Plaque Forming Units) for phage MS2. Use of the NEBNext kit resulted in detection of Salmonella at 10⁶ CFU reaction^-1 and phage MS2 at 10⁷ PFU reaction^-1. 16S amplicon-sequencing yielded a similar LoD of 10⁵ CFU reaction^-1 for Salmonella but could not detect MS2. The tested NGS methodologies, in combination with bioinformatics approaches applied, proved less sensitive than conventional microbial detection approaches.

A Metataxonomic Tool to Investigate the Diversity of Treponema

The genus Treponema contains a number of human and animal pathogenic as well as symbiotic bacteria that are found in vastly different anatomical and environmental habitats. Our understanding of the species range, evolution, and biology of these important bacteria is still limited. To explore the diversity of treponemes, we established, validated, and tested a novel metataxonomic approach. As the informative nature of the hypervariable regions of the 16S rRNA gene differ, we first analyzed each variable region independently. Considering the in silico results obtained, we established and validated the sequencing of the V4-region of the 16S rRNA gene using known mixtures of Treponema species as well as a selected number of clinical samples. The metataxonomic approach was able to identify Treponema to a near-species level. We demonstrate that using a spirochete-specific enrichment, our method is applicable to complex microbial communities and large variety of biological samples. The metataxonomic approach described provides a useful method to unravel the full diversity and range of Treponema in various ecosystems.

Assessing the comparability of different DNA extraction and amplification methods in gut microbial community profiling

Automated, high-throughput technologies are becoming increasingly common in microbiome studies to decrease costs and increase efficiency. However, in microbiome studies, small differences in methodology – including storage conditions, wet lab methods, sequencing platforms and data analysis – can influence the reproducibility and comparability of data across studies. There has been limited testing of the effects of high-throughput methods, including microfluidic PCR technologies. In this paper, we compare two extraction methods (the QIAamp DNA Stool Mini Kit and the MoBio PowerSoil DNA Isolation kit), two taq polymerase enzymes (MyTaq HS Red Mix and Accustart II PCR ToughMix), two primer sets (V3–V4 and V4–V5) and two amplification methods (a common two-step PCR protocol and amplicon library preparation on the Fluidigm Access Array system that allows automated multiplexing of primers). Gut microbial community profiles were significantly affected by all variables. While there were no significant differences in alpha diversity measured between the two extraction methods, there was an effect of extraction method on community composition measured by unweighted UniFrac distances. Both amplification method and primers had a significant effect on both alpha diversity and community composition. The relative abundance of Actinobacteria was significantly lower when using the MoBio kit or Fluidigm amplification method, and the relative abundance of Firmicutes was lower when using the Qiagen kit. Microbial community profiles based on Fluidigm-generated amplicon libraries were not comparable to those generated with more commonly used methods. Researchers should carefully consider the limitations and biases that different extraction and amplification methods can introduce into their results. Additionally, more thorough benchmarking of automated and multiplexing methods is necessary to determine the magnitude of the potential trade-off between the quality and the quantity of data.

Evaluating the Effect of QIIME Balanced Default Parameters on Metataxonomic Analysis Workflows With a Mock Community

Metataxonomic analysis represents a fast and cost-effective approach for acquiring informative insight into the composition of the microbiome of samples with variable diversity, such as wine samples. Nevertheless, it comprises a vast amount of laboratory procedures and bioinformatic frameworks each one associated with an inherent variability of protocols and algorithms, respectively. As a solution to the bioinformatic maze, QIIME bioinformatic framework has incorporated benchmarked, and balanced parameters as default parameters. In the current study, metataxonomic analysis of two types of mock community standards with the same microbial composition has been performed for evaluating the effectivess of QIIME balanced default parameters on a variety of aspects related to different laboratory and bioinformatic workflows. These aspects concern NGS platforms, PCR protocols, bioinformatic pipelines, and taxonomic classification algorithms. Several qualitative performance expectations have been the outcome of the analysis, rendering the mock community a useful evaluation tool.

A 16S rDNA PCR-based theoretical to actual delta approach on culturable mock communities revealed severe losses of diversity information

BACKGROUND

Subunits of ribosomal RNA genes (rDNAs) characterized by PCR-based protocols have been the proxy for studies in microbial taxonomy, phylogenetics, evolution and ecology. However, relevant factors have shown to interfere in the experimental outputs in a variety of systems. In this work, a 'theoretical' to 'actual' delta approach was applied to data on culturable mock bacterial communities (MBCs) to study the levels of losses in operational taxonomic units (OTUs) detectability. Computational and lab-bench strategies based on 16S rDNA amplification by 799F and U1492R primers were employed, using a fingerprinting method with highly improved detectability of fragments as a case-study tool. MBCs were of two major types: in silico MBCs, assembled with database-retrieved sequences, and in vitro MBCs, with AluI digestions of PCR data generated from culturable endophytes isolated from cacao trees.

RESULTS

Interfering factors for the 16 s rDNA amplifications, such as the type of template, direct and nested PCR, proportion of chloroplast DNA from a tropical plant source (Virola officinalis), and biased-amplification by the primers resulted in altered bacterial 16S rDNA amplification, both on MBCs and V. officinalis leaf-extracted DNA. For the theoretical data, the maximum number of fragments for in silico and in vitro cuts were not significantly different from each other. Primers' preferences for certain sequences were detected, depending on the MBCs' composition prior to PCR. The results indicated overall losses from 2.3 up to 8.2 times in the number of OTUs detected from actual AluI digestions of MBCs when compared to in silico and in vitro theoretical data.

CONCLUSIONS

Due to all those effects, the final amplification profile of the bacterial community assembled was remarkably simplified when compared to the expected number of detectable fragments known to be present in the MBC. From these findings, the scope of hypotheses generation and conclusions from experiments based on PCR amplifications of bacterial communities was discussed.

Early detection of marine invasive species, Bugula neritina (Bryozoa: Cheilostomatida), using species-specific primers and environmental DNA analysis in Korea

The bryozoan, Bugula neritina, is one of the most widespread sessile marine invasive species. Since its first discovery in Korea in 1978, the gradual increase in the distribution and abundance of this species resulted in a significant damage to growth of aquaculture. Environmental DNA (eDNA) is a potentially useful tool for species detection including rare, invasive and threatened native species. In this study, species-specific primers and probe were designed to amplify a 185-bp region based on mitochondrial COI of B. neritina for monitoring, and tested on environmental samples from 35 harbors of Korea in 2017. Among 35 sites monitored, B. neritina colonies were detected in 27 sites during field survey. However, B. neritina DNA was detected in all examined eDNA isolated from seawater. These results suggested that eDNA-based methods coupled with simple seawater sampling could be suitable for determining the distribution and abundance of B. neritina as complementary traditional monitoring.

Assessment of microbiota:host interactions at the vaginal mucosa interface

There is increasing appreciation of the role that vaginal microbiota play in health and disease throughout a woman's lifespan. This has been driven partly by molecular techniques that enable detailed identification and characterisation of microbial community structures. However, these methods do not enable assessment of the biochemical and immunological interactions between host and vaginal microbiota involved in pathophysiology. This review examines our current knowledge of the relationships that exist between vaginal microbiota and the host at the level of the vaginal mucosal interface. We also consider methodological approaches to microbiomic, immunologic and metabolic profiling that permit assessment of these interactions. Integration of information derived from these platforms brings the potential for biomarker discovery, disease risk stratification and improved understanding of the mechanisms regulating vaginal microbial community dynamics in health and disease.

The impact of storage buffer, DNA extraction method, and polymerase on microbial analysis

Next-generation sequencing approaches used to characterize microbial communities are subject to technical caveats that can lead to major distortion of acquired data. Determining the optimal sample handling protocol is essential to minimize the bias for different sample types. Using a mock community composed of 22 bacterial strains of even concentration, we studied a combination of handling conditions to determine the optimal conditions for swab material. Examining a combination of effects simulates the reality of handling environmental samples and may thus provide a better foundation for the standardization of protocols. We found that the choice of storage buffer and extraction kit affects the detected bacterial composition, while different 16S rRNA amplification methods only had a minor effect. All bacterial genera present in the mock community were identified with minimal levels of contamination independent of the choice of sample processing. Despite this, the observed bacterial profile for all tested conditions were significantly different from the expected abundance. This highlights the need for proper validation and standardization for each sample type using a mock community and blank control samples, to assess the bias in the protocol and reduce variation across the datasets.

Capturing the 'ome': the expanding molecular toolbox for RNA and DNA library construction

All sequencing experiments and most functional genomics screens rely on the generation of libraries to comprehensively capture pools of targeted sequences. In the past decade especially, driven by the progress in the field of massively parallel sequencing, numerous studies have comprehensively assessed the impact of particular manipulations on library complexity and quality, and characterized the activities and specificities of several key enzymes used in library construction. Fortunately, careful protocol design and reagent choice can substantially mitigate many of these biases, and enable reliable representation of sequences in libraries. This review aims to guide the reader through the vast expanse of literature on the subject to promote informed library generation, independent of the application.

The Madness of Microbiome: Attempting To Find Consensus "Best Practice" for 16S Microbiome Studies

The development and continuous improvement of high-throughput sequencing platforms have stimulated interest in the study of complex microbial communities. Currently, the most popular sequencing approach to study microbial community composition and dynamics is targeted 16S rRNA gene metabarcoding. To prepare samples for sequencing, there are a variety of processing steps, each with the potential to introduce bias at the data analysis stage. In this short review, key information from the literature pertaining to each processing step is described, and consequently, general recommendations for future 16S rRNA gene metabarcoding experiments are made.

Mosquito vector-associated microbiota: Metabarcoding bacteria and eukaryotic symbionts across habitat types in Thailand endemic for dengue and other arthropod-borne diseases

Vector-borne diseases are a major health burden, yet factors affecting their spread are only partially understood. For example, microbial symbionts can impact mosquito reproduction, survival, and vectorial capacity, and hence affect disease transmission. Nonetheless, current knowledge of mosquito-associated microbial communities is limited. To characterize the bacterial and eukaryotic microbial communities of multiple vector species collected from different habitat types in disease endemic areas, we employed next-generation 454 pyrosequencing of 16S and 18S rRNA amplicon libraries, also known as metabarcoding. We investigated pooled whole adult mosquitoes of three medically important vectors, Aedes aegypti, Ae. albopictus, and Culex quinquefasciatus, collected from different habitats across central Thailand where we previously characterized mosquito diversity. Our results indicate that diversity within the mosquito microbiota is low, with the majority of microbes assigned to one or a few taxa. Two of the most common eukaryotic and bacterial genera recovered (Ascogregarina and Wolbachia, respectively) are known mosquito endosymbionts with potentially parasitic and long evolutionary relationships with their hosts. Patterns of microbial composition and diversity appeared to differ by both vector species and habitat for a given species, although high variability between samples suggests a strong stochastic element to microbiota assembly. In general, our findings suggest that multiple factors, such as habitat condition and mosquito species identity, may influence overall microbial community composition, and thus provide a basis for further investigations into the interactions between vectors, their microbial communities, and human-impacted landscapes that may ultimately affect vector-borne disease risk.

Core fecal microbiota of domesticated herbivorous ruminant, hindgut fermenters, and monogastric animals

In this pilot study, we determined the core fecal microbiota composition and overall microbiota diversity of domesticated herbivorous animals of three digestion types: hindgut fermenters, ruminants, and monogastrics. The 42 animals representing 10 animal species were housed on a single farm in Ireland and all the large herbivores consumed similar feed, harmonizing two of the environmental factors that influence the microbiota. Similar to other mammals, the fecal microbiota of all these animals was dominated by the Firmicutes and Bacteroidetes phyla. The fecal microbiota spanning all digestion types comprised 42% of the genera identified. Host phylogeny and, to a lesser extent, digestion type determined the microbiota diversity in these domesticated herbivores. This pilot study forms a platform for future studies into the microbiota of nonbovine and nonequine domesticated herbivorous animals.

Integrating the microbiota of the respiratory tract with the unified airway model

The unified airway model has developed from indications that the upper and lower respiratory tracts share key elements of pathogenesis. These shared traits likely extend to similar niche characteristics that support bacterial communities, and as such, we suspect that similar microbes exist on upper and lower respiratory tract epithelium. Over the past decade and a half there have been significant improvements in microbiological identification and analysis due to the development of new molecular technologies, including next-generation sequencing. In this review, we provide an overview of the modern collection and sequencing methods involved in respiratory microbiota research, and outline the specific microbial communities that have been found to be associated with the healthy and diseased human respiratory tract. Demonstration of a remarkable similarity between the upper and lower respiratory tract in terms of microbiological presence adds further corroboration to the existence of a unified airway.

Phylogenetic Heatmaps Highlight Composition Biases in Sequenced Reads

Due to advancements in sequencing technology, sequence data production is no longer a constraint in the field of microbiology and has made it possible to study uncultured microbes or whole environments using metagenomics. However, these new technologies introduce different biases in metagenomic sequencing, affecting the nucleotide distribution of resulting sequence reads. Here, we illustrate such biases using two methods. One is based on phylogenetic heatmaps (PGHMs), a novel approach for compact visualization of sequence composition differences between two groups of sequences containing the same phylogenetic groups. This method is well suited for finding noise and biases when comparing metagenomics samples. We apply PGHMs to detect noise and bias in the data produced with different DNA extraction protocols, different sequencing platforms and different experimental frameworks. In parallel, we use principal component analysis displaying different clustering of sequences from each sample to support our findings and illustrate the utility of PGHMs. We considered contributions of the read length and GC-content variation and observed that in most cases biases were generally due to the GC-content of the reads.

Toward a Resilient, Functional Microbiome: Drought Tolerance-Alleviating Microbes for Sustainable Agriculture

In recent years, the utilization of novel sequencing techniques opened a new field of research into plant microbiota and was used to explore a wide diversity of microorganisms both inside and outside of plant host tissues, i.e., the endosphere and rhizosphere, respectively. An early realization from such research was that species richness and diversity of the plant microbiome are both greater than believed even a few years ago, and soil is likely home to the most abundant and diverse microbial habitats known. In most ecosystems sampled thus far, overall microbial complexity is determined by the combined influences of plant genotype, soil structure and chemistry, and prevailing environmental conditions, as well as the native "bulk soil" microbial populations from which membership is drawn. Beneficial microorganisms, traditionally referring primarily to nitrogen-fixing bacteria, plant growth-promoting rhizobacteria, and mycorrhizal fungi, play a key role in major functions such as plant nutrition acquisition and plant resistance to biotic and abiotic stresses . Utilization of plant-associated microbes in food production is likely to be critical for twenty-first century agriculture, where arable cropland is limited and food, fiber, and feed productivity must be sustained or even improved with fewer chemical inputs and less irrigation.

Accurate Estimation of Fungal Diversity and Abundance through Improved Lineage-Specific Primers Optimized for Illumina Amplicon Sequencing

While high-throughput sequencing methods are revolutionizing fungal ecology, recovering accurate estimates of species richness and abundance has proven elusive. We sought to design internal transcribed spacer (ITS) primers and an Illumina protocol that would maximize coverage of the kingdom Fungi while minimizing nontarget eukaryotes. We inspected alignments of the 5.8S and large subunit (LSU) ribosomal genes and evaluated potential primers using PrimerProspector. We tested the resulting primers using tiered-abundance mock communities and five previously characterized soil samples. We recovered operational taxonomic units (OTUs) belonging to all 8 members in both mock communities, despite DNA abundances spanning 3 orders of magnitude. The expected and observed read counts were strongly correlated (r = 0.94 to 0.97). However, several taxa were consistently over- or underrepresented, likely due to variation in rRNA gene copy numbers. The Illumina data resulted in clustering of soil samples identical to that obtained with Sanger sequence clone library data using different primers. Furthermore, the two methods produced distance matrices with a Mantel correlation of 0.92. Nonfungal sequences comprised less than 0.5% of the soil data set, with most attributable to vascular plants. Our results suggest that high-throughput methods can produce fairly accurate estimates of fungal abundances in complex communities. Further improvements might be achieved through corrections for rRNA copy number and utilization of standardized mock communities.

IMPORTANCE

Fungi play numerous important roles in the environment. Improvements in sequencing methods are providing revolutionary insights into fungal biodiversity, yet accurate estimates of the number of fungal species (i.e., richness) and their relative abundances in an environmental sample (e.g., soil, roots, water, etc.) remain difficult to obtain. We present improved methods for high-throughput Illumina sequencing of the species-diagnostic fungal ribosomal marker gene that improve the accuracy of richness and abundance estimates. The improvements include new PCR primers and library preparation, validation using a known mock community, and bioinformatic parameter tuning.

An introduction to microbiome analysis for human biology applications

Research examining the gut microbiota is currently exploding, and results are providing new perspectives on human biology. Factors such as host diet and physiology influence the composition and function of the gut microbiota, which in turn affects human nutrition, health, and behavior via interactions with metabolism, the immune system, and the brain. These findings represent an exciting new twist on familiar topics, and as a result, gut microbiome research is likely to provide insight into unresolved biological mechanisms driving human health. However, much remains to be learned about the broader ecological and evolutionary contexts within which gut microbes and humans are affecting each other. Here, I outline the procedures for generating data describing the gut microbiota with the goal of facilitating the wider integration of microbiome analyses into studies of human biology. I describe the steps involved in sample collection, DNA extraction, PCR amplification, high-throughput sequencing, and bioinformatics. While this review serves only as an introduction to these topics, it provides sufficient resources for researchers interested in launching new microbiome initiatives. As knowledge of these methods spreads, microbiome analysis should become a standard tool in the arsenal of human biology research.

On the use of high-throughput sequencing for the study of cyanobacterial diversity in Antarctic aquatic mats

The study of Antarctic cyanobacterial diversity has been mostly limited to morphological identification and traditional molecular techniques. High-throughput sequencing (HTS) allows a much better understanding of microbial distribution in the environment, but its application is hampered by several methodological and analytical challenges. In this work, we explored the use of HTS as a tool for the study of cyanobacterial diversity in Antarctic aquatic mats. Our results highlight the importance of using artificial communities to validate the parameters of the bioinformatics procedure used to analyze natural communities, since pipeline-dependent biases had a strong effect on the observed community structures. Analysis of microbial mats from five Antarctic lakes and an aquatic biofilm from the Sub-Antarctic showed that HTS is a valuable tool for the assessment of cyanobacterial diversity. The majority of the operational taxonomic units retrieved were related to filamentous taxa such as Leptolyngbya and Phormidium, which are common genera in Antarctic lacustrine microbial mats. However, other phylotypes related to different taxa such as Geitlerinema, Pseudanabaena, Synechococcus, Chamaesiphon, Calothrix, and Coleodesmium were also found. Results revealed a much higher diversity than what had been reported using traditional methods and also highlighted remarkable differences between the cyanobacterial communities of the studied lakes. The aquatic biofilm from the Sub-Antarctic had a distinct cyanobacterial community from the Antarctic lakes, which in turn displayed a salinity-dependent community structure at the phylotype level.

Characterization of the gut microbiome in epidemiologic studies: the multiethnic cohort experience

PURPOSE

The development of next-generation sequencing and accompanying bioinformatics tools has revolutionized characterization of microbial communities. As interest grows in the role of the human microbiome in health and disease, so does the need for well-powered, robustly designed epidemiologic studies. Here, we discuss sources of bias that can arise in gut microbiome research.

METHODS

Research comparing methods of specimen collection, preservation, processing, and analysis of gut microbiome samples is reviewed. Although selected studies are primarily based on the gut, many of the same principles are applicable to samples derived from other anatomical sites. Methods for participant recruitment and sampling of the gut microbiome implemented in an ongoing population-based study, the Multiethnic Cohort (MEC), are also described.

RESULTS

Variation in methodologies can influence the results of human microbiome studies. To help minimize bias, techniques such as sample homogenization, addition of internal standards, and quality filtering should be adopted in protocols. Within the MEC, participant response rates to stool sample collection were comparable to other studies, and in-home stool sample collection yields sufficient high-quality DNA for gut microbiome analysis.

CONCLUSIONS

Application of standardized and quality controlled methods in human microbiome studies is necessary to ensure data quality and comparability among studies.

Natural decay process affects the abundance and community structure of Bacteria and Archaea in Picea abies logs

Prokaryotes colonize decaying wood and contribute to the degradation process, but the dynamics of prokaryotic communities during wood decay is still poorly understood. We studied the abundance and community composition of Bacteria and Archaea inhabiting naturally decaying Picea abies logs and tested the hypothesis that the variations in archaeal and bacterial abundances and community composition are coupled with environmental parameters related to the decay process. The data set comprises >500 logs at different decay stages from five geographical locations in south and central Finland. The results show that Bacteria and Archaea are an integral and dynamic component of decaying wood biota. The abundances of bacterial and archaeal 16S rRNA genes increase as wood decay progresses. Changes in bacterial community composition are clearly linked to the loss of density of wood, while specific fungal-bacterial interactions may also affect the distribution of bacterial taxa in decaying wood. Thaumarchaeota were prominent members of the archaeal populations colonizing decaying wood, providing further evidence of the versatility and cosmopolitan nature of this phylum in the environment. The composition and dynamics of the prokaryotic community suggest that they are an active component of biota that are involved in processing substrates in decaying wood material.

Characterization of MHC class II B polymorphism in multiple populations of wild gorillas using non-invasive samples and next-generation sequencing

Genes encoded by the major histocompatibility complex (MHC) are crucial for the recognition and presentation of antigens to the immune system. In contrast to their closest relatives, chimpanzees and humans, much less is known about variation in gorillas at these loci. This study explored the exon 2 variation of -DPB1, -DQB1, and -DRB genes in 46 gorillas from four populations while simultaneously evaluating the feasibility of using fecal samples for high-throughput MHC genotyping. By applying strict similarity- and frequency-based analysis, we found, despite our modest sample size, a total of 18 alleles that have not been described previously, thereby illustrating the potential for efficient and highly accurate MHC genotyping from non-invasive DNA samples. We emphasize the importance of controlling for multiple potential sources of error when applying this massively parallel short-read sequencing technology to PCR products generated from low concentration DNA extracts. We observed pronounced differences in MHC variation between species, subspecies and populations that are consistent with both the ancient and recent demographic histories experienced by gorillas.

Development and Validation of Environmental DNA (eDNA) Markers for Detection of Freshwater Turtles

Environmental DNA (eDNA) is a potentially powerful tool for detection and monitoring of rare species, including threatened native species and recently arrived invasive species. Here, we develop DNA primers for a suite of nine sympatric freshwater turtles, and use it to test whether turtle eDNA can be successfully detected in samples from aquaria and an outdoor pond. We also conduct a cost comparison between eDNA detection and detection through traditional survey methods, using data from field surveys at two sites in our target area. We find that eDNA from turtles can be detected using both conventional polymerase chain reaction (PCR) and quantitative PCR (qPCR), and that the cost of detection through traditional survey methods is 2–10X higher than eDNA detection for the species in our study range. We summarize necessary future steps for application of eDNA surveys to turtle monitoring and conservation and propose specific cases in which the application of eDNA could further the conservation of threatened turtle species.

The truth about metagenomics: quantifying and counteracting bias in 16S rRNA studies

BACKGROUND

Characterizing microbial communities via next-generation sequencing is subject to a number of pitfalls involving sample processing. The observed community composition can be a severe distortion of the quantities of bacteria actually present in the microbiome, hampering analysis and threatening the validity of conclusions from metagenomic studies. We introduce an experimental protocol using mock communities for quantifying and characterizing bias introduced in the sample processing pipeline. We used 80 bacterial mock communities comprised of prescribed proportions of cells from seven vaginally-relevant bacterial strains to assess the bias introduced in the sample processing pipeline. We created two additional sets of 80 mock communities by mixing prescribed quantities of DNA and PCR product to quantify the relative contribution to bias of (1) DNA extraction, (2) PCR amplification, and (3) sequencing and taxonomic classification for particular choices of protocols for each step. We developed models to predict the "true" composition of environmental samples based on the observed proportions, and applied them to a set of clinical vaginal samples from a single subject during four visits.

RESULTS

We observed that using different DNA extraction kits can produce dramatically different results but bias is introduced regardless of the choice of kit. We observed error rates from bias of over 85% in some samples, while technical variation was very low at less than 5% for most bacteria. The effects of DNA extraction and PCR amplification for our protocols were much larger than those due to sequencing and classification. The processing steps affected different bacteria in different ways, resulting in amplified and suppressed observed proportions of a community. When predictive models were applied to clinical samples from a subject, the predicted microbiome profiles were better reflections of the physiology and diagnosis of the subject at the visits than the observed community compositions.

CONCLUSIONS

Bias in 16S studies due to DNA extraction and PCR amplification will continue to require attention despite further advances in sequencing technology. Analysis of mock communities can help assess bias and facilitate the interpretation of results from environmental samples.

Changes in bacterial and eukaryotic communities during sewage decomposition in Mississippi river water

Microbial decay processes are one of the mechanisms whereby sewage contamination is reduced in the environment. This decomposition process involves a highly complex array of bacterial and eukaryotic communities from both sewage and ambient waters. However, relatively little is known about how these communities change due to mixing and subsequent decomposition of the sewage contaminant. We investigated decay of sewage in upper Mississippi River using Illumina sequencing of 16S and 18S rRNA gene hypervariable regions and qPCR for human-associated and general fecal Bacteroidales indicators. Mixtures of primary treated sewage and river water were placed in dialysis bags and incubated in situ under ambient conditions for seven days. We assessed changes in microbial community composition under two treatments in a replicated factorial design: sunlight exposure versus shaded and presence versus absence of native river microbiota. Initial diversity was higher in sewage compared to river water for 16S sequences, but the reverse was observed for 18S sequences. Both treatments significantly shifted community composition for eukaryotes and bacteria (P < 0.05). Data indicated that the presence of native river microbiota, rather than exposure to sunlight, accounted for the majority of variation between treatments for both 16S (R = 0.50; P > 0.001) and 18S (R = 0.91; P = 0.001) communities. A comparison of 16S sequence data and fecal indicator qPCR measurements indicated that the latter was a good predictor of overall bacterial community change over time (rho: 0.804-0.814, P = 0.001). These findings suggest that biotic interactions, such as predation by bacterivorous protozoa, can be critical factors in the decomposition of sewage in freshwater habitats and support the use of Bacteroidales genetic markers as indicators of fecal pollution.

Pyrosequencing revealed SAR116 clade as dominant dddP-containing bacteria in oligotrophic NW Pacific Ocean

Dimethyl sulfide (DMS) is a climatically active gas released into the atmosphere from oceans. It is produced mainly by bacterial enzymatic cleavage of dimethylsulfoniopropionate (DMSP), and six DMSP lyases have been identified to date. To determine the biogeographical distribution of bacteria relevant to DMS production, we investigated the diversity of dddP—the most abundant DMS-producing gene—in the northwestern Pacific Ocean using newly developed primers and the pyrosequencing method. Consistent with previous studies, the major dddP-containing bacteria in coastal areas were those belonging to the Roseobacter clade. However, genotypes closely related to the SAR116 group were found to represent a large portion of dddP-containing bacteria in the surface waters of the oligotrophic ocean. The addition of DMSP to a culture of the SAR116 strain Candidatus Puniceispirillum marinum IMCC1322 resulted in the production of DMS and upregulated expression of the dddP gene. Considering the large area of oligotrophic water and the wide distribution of the SAR116 group in oceans worldwide, we propose that these bacteria may play an important role in oceanic DMS production and biogeochemical sulfur cycles, especially via bacteria-mediated DMSP degradation.

Effect of long-term different fertilization on bacterial community structures and diversity in citrus orchard soil of volcanic ash

This study was conducted to assess bacterial species richness, diversity and community distribution according to different fertilization regimes for 16 years in citrus orchard soil of volcanic ash. Soil samples were collected and analyzed from Compost (cattle manure, 2,000 kg/10a), 1/2 NPK+compost (14-20-14+2,000 kg/10a), NPK+compost (28-40-28+2,000 kg/10a), NPK (28-40-28 kg/10a), 3 NPK (84-120-84 kg/10a), and Control (no fertilization) plot which have been managed in the same manners with compost and different amount of chemical fertilization. The range of pyrosequencing reads and OTUs were 4,687-7,330 and 1,790-3,695, respectively. Species richness estimates such as Ace, Chao1, and Shannon index were higher in 1/2 NPK+compost than other treatments, which were 15,202, 9,112, 7.7, respectively. Dominant bacterial groups at level of phylum were Proteobacteria, Acidobacteria, and Actinobacteria. Those were occupied at 70.9% in 1/2 NPK+compost. Dominant bacterial groups at level of genus were Pseudolabrys, Bradyrhizobium, and Acidobacteria. Those were distributed at 14.4% of a total of bacteria in Compost. Soil pH displayed significantly closely related to bacterial species richness estimates such as Ace, Chao1 (p<0.05) and Shannon index (p<0.01). However, it showed the negative correlation with exchangeable aluminum contents (p<0.05). In conclusion, diversity of bacterial community in citrus orchard soil was affected by fertilization management, soil pH changes and characteristics of volcanic ash.