Groundtruthing next-gen sequencing for microbial ecology-biases and errors in community structure estimates from PCR amplicon pyrosequencing

Unveiling errors in soil microbial community sequencing: a case for reference soils and improved diagnostics for nanopore sequencing

The sequencing platform and workflow strongly influence microbial community analyses through potential errors at each step. Effective diagnostics and experimental controls are needed to validate data and improve reproducibility. This cross-laboratory study evaluates sources of variability and error at three main steps of a standardized amplicon sequencing workflow (DNA extraction, polymerase chain reaction [PCR], and sequencing) using Oxford Nanopore MinION to analyze agricultural soils and a simple mock community. Variability in sequence results occurs at each step in the workflow with PCR errors and differences in library size greatly influencing diversity estimates. Common bioinformatic diagnostics and the mock community are ineffective at detecting PCR abnormalities. This work outlines several diagnostic checks and techniques to account for sequencing depth and ensure accuracy and reproducibility in soil community analyses. These diagnostics and the inclusion of a reference soil can help ensure data validity and facilitate the comparison of multiple sequencing runs within and between laboratories.

Using short-read 16S rRNA sequencing of multiple variable regions to generate high-quality results to a species level

Introduction

Short-read amplicon sequencing studies have typically focused on 1-2 variable regions of the 16S rRNA gene. Species-level resolution is limited in these studies, as each variable region enables the characterisation of a different subsection of the microbiome. Although long-read sequencing techniques take advantage of all 9 variable regions by sequencing the entire 16S rRNA gene, they are substantially more expensive. This work assessed the feasibility of accurate species-level resolution and reproducibility using a relatively new sequencing kit and bioinformatics pipeline developed for short-read sequencing of multiple variable regions of the 16S rRNA gene. In addition, we evaluated the potential impact of different sample collection methods on our outcomes.

Methods

Using xGen™ 16S Amplicon Panel v2 kits, sequencing of all 9 variable regions of the 16S rRNA gene was carried out on an Illumina MiSeq platform. Mock cells and mock DNA for 8 bacterial species were included as extraction and sequencing controls respectively. Within-run and between-run replicate samples, and pairs of stool and rectal swabs collected at 0-5 weeks from the same participants, were incorporated. Observed relative abundances of each species were compared to theoretical abundances provided by ZymoBIOMICS. Paired Wilcoxon rank sum tests and distance-based intraclass correlation coefficients were used to statistically compare alpha and beta diversity measures, respectively, for pairs of replicates and stool/rectal swab sample pairs.

Results

Using multiple variable regions of the 16S ribosomal Ribonucleic Acid (rRNA) gene, we found that we could accurately identify taxa to a species level and obtain highly reproducible results at a species level. Yet, the microbial profiles of stool and rectal swab sample pairs differed substantially despite being collected concurrently from the same infants.

Conclusion

This protocol provides an effective means for studying infant gut microbial samples at a species level. However, sample collection approaches need to be accounted for in any downstream analysis.

Global abundance patterns, diversity, and ecology of Patescibacteria in wastewater treatment plants

BACKGROUND

Microorganisms are responsible for nutrient removal and resource recovery in wastewater treatment plants (WWTPs), and their diversity is often studied by 16S rRNA gene amplicon sequencing. However, this approach underestimates the abundance and diversity of Patescibacteria due to the low coverage of commonly used PCR primers for this highly divergent bacterial phylum. Therefore, our current understanding of the global diversity, distribution, and ecological role of Patescibacteria in WWTPs is very incomplete. This is particularly relevant as Patescibacteria are considered to be associated with microbial host cells and can therefore influence the abundance and temporal variability of other microbial groups that are important for WWTP functioning.

RESULTS

Here, we evaluated the in silico coverage of widely used 16S rRNA gene-targeted primer pairs and redesigned a primer pair targeting the V4 region of bacterial and archaeal 16S rRNA genes to expand its coverage for Patescibacteria. We then experimentally evaluated and compared the performance of the original and modified V4-targeted primers on 565 WWTP samples from the MiDAS global sample collection. Using the modified primer pair, the percentage of ASVs classified as Patescibacteria increased from 5.9 to 23.8%, and the number of detected patescibacterial genera increased from 560 to 1576, while the detected diversity of the remaining microbial community remained similar. Due to this significantly improved coverage of Patescibacteria, we identified 23 core genera of Patescibacteria in WWTPs and described the global distribution pattern of these unusual microbes in these systems. Finally, correlation network analysis revealed potential host organisms that might be associated with Patescibacteria in WWTPs. Interestingly, strong indications were found for an association between Patescibacteria of the Saccharimonadia and globally abundant polyphosphate-accumulating organisms of the genus Ca. Phosphoribacter.

CONCLUSIONS

Our study (i) provides an improved 16S rRNA gene V4 region-targeted amplicon primer pair inclusive of Patescibacteria with little impact on the detection of other taxa, (ii) reveals the diversity and distribution patterns of Patescibacteria in WWTPs on a global scale, and (iii) provides new insights into the ecological role and potential hosts of Patescibacteria in WWTPs. Video Abstract.

Sodium levels and grazing pressure shape natural communities of the intracellular pathogen Legionella

BACKGROUND

Legionella are parasites of freshwater protozoa, responsible for Legionellosis. Legionella can be found in a variety of aquatic environments, including rivers, lakes, and springs, as well as in engineered water systems where they can potentially lead to human disease outbarks. Legionella are considered to be predominantly freshwater organisms with a limited ability to proliferate in saline environments. Exposure of Legionella to high sodium concentrations inhibits growth and virulence of laboratory strains, particularly under elevated temperatures. Nonetheless, Legionella have been identified in some saline environments where they likely interact with various protozoan hosts. In this work, we examine how these selection pressures, sodium and grazing, help shape Legionella ecology within natural environments. Utilizing Legionella-specific primers targeting a variable region of the Legionella 16S rRNA gene, we characterized Legionella abundance, diversity, and community composition in natural spring clusters of varying sodium concentrations, focusing on high sodium concentrations and elevated temperatures.

RESULTS

We observed the highest abundance of Legionella in spring clusters of high salinity, particularly in combination with elevated temperatures. Legionella abundance was strongly related to sodium concentrations. The Legionella community structure in saline environments was characterized by relatively low diversity, compared to spring clusters of lower salinity. The community composition in high salinity was characterized by few dominant Legionella genotypes, not related to previously described species. Protozoan microbial community structure and composition patterns resembled those of Legionella, suggesting a common response to similar selection pressures. We examined Legionella co-occurrence with potential protozoan hosts and found associations with Ciliophora and Amoebozoa representatives.

CONCLUSIONS

Our results indicate that selection forces in saline environments favor a small yet dominant group of Legionella species that are not closely related to known species. These novel environmental genotypes interact with various protozoan hosts, under environmental conditions of high salinity. Our findings suggest that alternative survival mechanisms are utilized by these species, representing mechanisms distinct from those of well-studied laboratory strains. Our study demonstrate how salinity can shape communities of opportunistic pathogens and their hosts, in natural environments, shedding light on evolutionary forces acting within these complex environments. Video Abstract.

The waterbodies of the halo-volcanic Dallol complex: earth analogs to guide us, where to look for life in the universe

Microbes are the Earth life forms that have the highest degree of adaptability to survive, live, or even proliferate in very hostile environments. It is even stated that microbes can cope with any extreme physico-chemical condition and are, therefore, omnipresent all over the Earth: on all the continents, inside its crust and in all its waterbodies. However, our study suggests that there exists areas and even water rich environments on Earth where no life is possible. To support the fact that water rich environments can be lifeless, we performed an extensive survey of 10 different hyper extreme waterbodies of the halo-volcanic Dallol complex (Danakil depression, Ethiopia, Horn of Africa). In our study, we combined physico-chemical analyses, mineralogical investigations, XRD and SEM-EDX analyses, ATP measurements, 16S rDNA microbial community determinations, and microbial culturing techniques. According to our findings, we suggest that the individual physico-chemical parameters, water activity, and kosmo-chaotropicity, are the two most important factors that determine whether an environment is lifeless or capable of hosting specific extreme lifeforms. Besides, waterbodies that contained saturated levels of sodium chloride but at the same time possessed extreme low pH values, appeared to be poly-extreme environments in which no life could be detected. However, we clearly discovered a low diversity microbial community in waterbodies that were fully saturated with sodium chloride and only mildly acidic. Our results can be beneficial to more precisely classify whole or certain areas of planetary bodies, including water rich environments, as either potentially habitable or factual uninhabitable environments.

Fungal Gut Microbiome in Myasthenia Gravis: A Sub-Analysis of the MYBIOM Study

An altered gut microbiota is a possible contributing pathogenic factor in myasthenia gravis (MG), an autoimmune neuromuscular disease. However, the significance of the fungal microbiome is an understudied and neglected part of the intestinal microbiome in MG. We performed a sub-analysis of the MYBIOM study including faecal samples from patients with MG (n = 41), non-inflammatory neurological disorder (NIND, n = 18), chronic inflammatory demyelinating polyradiculoneuropathy (CIDP, n = 6) and healthy volunteers (n = 12) by sequencing the internal transcribed spacer 2 (ITS2). Fungal reads were obtained in 51 out of 77 samples. No differences were found in alpha-diversity indices computed between the MG, NIND, CIDP and HV groups, indicating an unaltered fungal diversity and structure. Overall, four mould species (Penicillium aurantiogriseum, Mycosphaerella tassiana, Cladosporium ramonetellum and Alternaria betae-kenyensis) and five yeast species (Candida. albicans, Candida. sake, Candida. dubliniensis, Pichia deserticola and Kregervanrija delftensis) were identified. Besides one MG patient with abundant Ca. albicans, no prominent dysbiosis in the MG group of the mycobiome was found. Not all fungal sequences within all groups were successfully assigned, so further sub-analysis was withdrawn, limiting robust conclusions.

Diet preferences based on sequence read count: the role of species interaction in tissue bias correction

High-throughput sequencing and metabarcoding techniques provide a unique opportunity to study predator-prey relationships. However, in animal dietary preference studies, how to properly correct tissue bias within the sequence read count and the role of interactions between co-occurring species in metabarcoding mixtures remain largely unknown. In this study, we proposed two categories of tissue bias correction indices: sequence read count number per unit tissue (SCN) and its ratio form (SCN ratio). By constructing plant mock communities with different numbers of co-occurring species in metabarcoding mixtures and conducting feeding trails on captive sika deer (Cervus nippon), we demonstrated the features of the SCN and SCN ratio, evaluated their correction effects, and assessed the role of species interactions during tissue bias correction. Tissue differences between species are defined as the differential ability in generating sequence counts. Our study suggests that pure tissue differences among species without species interaction is not an optimal correction index for many biomes with limited tissue differences among species. Species interactions in mixtures may amplify tissue differences, which is beneficial for tissue bias correction. However, caution must be taken because varied species interaction among communities may increase the risk of worse correction. Correction effects based on the SCN and SCN ratio are comparable, while the SCN is less influenced by control species than the SCN ratio. According to our study, several suggestions were provided for future animal diet studies or other high-throughput sequencing studies containing tissue bias.

Shifts in DNA yield and biological community composition in stored sediment: implications for paleogenomic studies

Lake sediments hold a wealth of information from past environments that is highly valuable for paleolimnological reconstructions. These studies increasingly apply modern molecular tools targeting sedimentary DNA (sedDNA). However, sediment core sampling can be logistically difficult, making immediate subsampling for sedDNA challenging. Sediment cores are often refrigerated (4 °C) for weeks or months before subsampling. We investigated the impact of storage time on changes in DNA (purified or as cell lysate) concentrations and shifts in biological communities following storage of lake surface sediment at 4 °C for up to 24 weeks. Sediment samples (~ 0.22 g, in triplicate per time point) were spiked with purified DNA (100 or 200 ng) or lysate from a brackish water cyanobacterium that produces the cyanotoxin nodularin or non-spiked. Samples were analysed every 1–4 weeks over a 24-week period. Droplet digital PCR showed no significant decrease in the target gene (nodularin synthetase – subunit F; ndaF) over the 24-week period for samples spiked with purified DNA, while copy number decreased by more than half in cell lysate-spiked samples. There was significant change over time in bacteria and eukaryotic community composition assessed using metabarcoding. Amongst bacteria, the cyanobacterial signal became negligible after 5 weeks while Proteobacteria increased. In the eukaryotic community, Cercozoa became dominant after 6 weeks. These data demonstrate that DNA yields and community composition data shift significantly when sediments are stored chilled for more than 5 weeks. This highlights the need for rapid subsampling and appropriate storage of sediment core samples for paleogenomic studies.

Development of droplet digital Polymerase Chain Reaction assays for the detection of long-finned (Anguilla dieffenbachii) and short-finned (Anguilla australis) eels in environmental samples

Freshwater eels are ecologically, and culturally important worldwide. The New Zealand long-finned eel (Anguilla dieffenbachii) and short-finned eel (Anguilla australis) are apex predators, playing an important role in ecosystem functioning of rivers and lakes. Recently, there has been a national decline in their populations due to habitat destruction and commercial harvest. The emergence of targeted environmental DNA detection methodologies provides an opportunity to enhance information about their past and present distributions. In this study we successfully developed species-specific droplet digital Polymerase Chain Reaction (ddPCR) assays to detect A. dieffenbachii and A. australis DNA in water and sediment samples. Assays utilized primers and probes designed for regions of the mitochondrial cytochrome b and 16S ribosomal RNA genes in A. dieffenbachii and A. australis, respectively. River water samples (n = 27) were analyzed using metabarcoding of fish taxa and were compared with the ddPCR assays. The presence of A. dieffenbachii and A. australis DNA was detected in a greater number of water samples using ddPCR in comparison to metabarcoding. There was a strong and positive correlation between gene copies (ddPCR analyses) and relative eel sequence reads (metabarcoding analyses) when compared to eel biomass. These ddPCR assays provide a new method for assessing spatial distributions of A. dieffenbachii and A. australis in a range of environments and sample types.

Deciphering the molecular signal from past and alive bacterial communities in aquatic sedimentary archives

Lake sediments accumulate information on biological communities thus acting as natural archives. Traditionally paleolimnology has focussed on fossilized remains of organisms, however, many organisms do not leave fossil evidence, meaning major ecosystem components are missing from environmental reconstructions. Many paleolimnology studies now incorporate molecular methods, including investigating microbial communities using environmental DNA (eDNA), but there is uncertainty about the contribution of living organisms to molecular inventories. In the present study, we obtained DNA and RNA inventories from sediment spanning 700 years to investigate the contribution of past and active communities to the molecular signal from sedimentary archives. Additionally, a droplet digital PCR (ddPCR) targeting the 16S ribosomal RNA (16S rRNA) gene of the photosynthetic cyanobacterial genera Microcystis was used to explore if RNA signals were from legacy RNA. We posit that the RNA signal is a mixture of legacy RNA, dormant cells, living bacteria and modern-day trace level contaminants that were introduced during sampling and preferentially amplified. The presence of legacy RNA was confirmed by the detection of Microcystis in sediments aged to ~200 years ago. Recent comparisons between 16S rRNA gene metabarcoding and traditional paleo proxies showed that past changes in bacterial communities can be reconstructed from sedimentary archives. The recovery of RNA in the present study has provided new insights into the origin of these signals. However, caution is required during analysis and interpretation of 16S rRNA gene metabarcoding data especially in recent sediments were there are potentially active bacteria.

A Slimy Business: the Future of Fish Skin Microbiome Studies

Fish skin contains a mucosal microbiome for the largest and oldest group of vertebrates, a location ideal for microbial community ecology and practical applications in agriculture and veterinary medicine. These selective microbiomes are dominated by Proteobacteria, with compositions different from the surrounding water. Core taxa are a small percentage of those present and are currently functionally uncharacterized. Methods for skin sampling, DNA extraction and amplification, and sequence data processing are highly varied across the field, and reanalysis of recent studies using a consistent pipeline revealed that some conclusions did change in statistical significance. Further, the 16S gene sequencing approaches lack quantitation of microbes and copy number adjustment. Thus, consistency in the field is a serious limitation in comparing across studies. The most significant area for future study, requiring metagenomic and metabolomics data, is the biochemical pathways and functions within the microbiome community, the interactions between members, and the resulting effects on fish host health being linked to specific nutrients and microbial species. Genes linked to skin colonization, such as those for attachment or mucin degradation, need to be uncovered and explored. Skin immunity factors need to be directly linked to microbiome composition and individual taxa. The basic foundation has been laid, and many exciting future discoveries remain.

Comparing Quantitative Methods for Analyzing Sediment DNA Records of Cyanobacteria in Experimental and Reference Lakes

Sediment DNA (sedDNA) analyses are rapidly emerging as powerful tools for the reconstruction of environmental and evolutionary change. While there are an increasing number of studies using molecular genetic approaches to track changes over time, few studies have compared the coherence between quantitative polymerase chain reaction (PCR) methods and metabarcoding techniques. Primer specificity, bioinformatic analyses, and PCR inhibitors in sediments could affect the quantitative data obtained from these approaches. We compared the performance of droplet digital polymerase chain reaction (ddPCR) and high-throughput sequencing (HTS) for the quantification of target genes of cyanobacteria in lake sediments and tested whether the two techniques similarly reveal expected patterns through time. Absolute concentrations of cyanobacterial 16S rRNA genes were compared between ddPCR and HTS using dated sediment cores collected from two experimental (Lake 227, fertilized since 1969 and Lake 223, acidified from 1976 to 1983) and two reference lakes (Lakes 224 and 442) in the Experimental Lakes Area (ELA), Canada. Relative abundances of Microcystis 16S rRNA (MICR) genes were also compared between the two methods. Moderate to strong positive correlations were found between the molecular approaches among all four cores but results from ddPCR were more consistent with the known history of lake manipulations. A 100-fold increase in ddPCR estimates of cyanobacterial gene abundance beginning in ~1968 occurred in Lake 227, in keeping with experimental addition of nutrients and increase in planktonic cyanobacteria. In contrast, no significant rise in cyanobacterial abundance associated with lake fertilization was observed with HTS. Relative abundances of Microcystis between the two techniques showed moderate to strong levels of coherence in top intervals of the sediment cores. Both ddPCR and HTS approaches are suitable for sedDNA analysis, but studies aiming to quantify absolute abundances from complex environments should consider using ddPCR due to its high tolerance to PCR inhibitors.

Role of Phylogenetic Structure in the Dynamics of Coastal Viral Assemblages

Marine microbes, including viruses, are an essential part of the marine ecosystem, forming the base of the food web and driving biogeochemical cycles. Within this system, the composition of viral assemblages changes markedly with time, and some of these changes are repeatable through time; however, the extent to which these dynamics are reflected within versus among evolutionarily related groups of viruses is largely unexplored. To examine these dynamics, changes in the composition of two groups of ecologically important viruses and communities of their potential hosts were sampled every 2 weeks for 13 months at a coastal site in British Columbia, Canada. We sequenced two marker genes for viruses-the gene encoding the major capsid protein of T4-like phages and their relatives (gp23) and the RNA-dependent RNA polymerase (RdRp) gene of marnavirus-like RNA viruses-as well as marker genes for their bacterial and eukaryotic host communities, the genes encoding 16S rRNA and 18S rRNA. There were strong lagged correlations between viral diversity and community similarity of putative hosts, implying that the viruses influenced the composition of the host communities. The results showed that for both viral assemblages, the dominant clusters of phylogenetically related viruses shifted over time, and this was correlated with environmental changes. Viral clusters contained many ephemeral taxa and few persistent taxa, but within a viral assemblage, the ephemeral and persistent taxa were closely related, implying ecological dynamics within these clusters. Furthermore, these dynamics occurred in both the RNA and DNA viral assemblages surveyed, implying that this structure is common in natural viral assemblages.IMPORTANCE Viruses are major agents of microbial mortality in marine systems, yet little is known about changes in the composition of viral assemblages in relation to those of the microbial communities that they infect. Here, we sampled coastal seawater every 2 weeks for 1 year and used high-throughput sequencing of marker genes to follow changes in the composition of two groups of ecologically important viruses, as well as the communities of bacteria and protists that serve as their respective hosts. Different subsets of genetically related viruses dominated at different times. These results demonstrate that although the genetic composition of viral assemblages is highly dynamic temporally, for the most part the shuffling of genotypes occurs within a few clusters of phylogenetically related viruses. Thus, it appears that even in temperate coastal waters with large seasonal changes, the highly dynamic shuffling of viral genotypes occurs largely within a few subsets of related individuals.

CaptureSeq: Hybridization-Based Enrichment of cpn60 Gene Fragments Reveals the Community Structures of Synthetic and Natural Microbial Ecosystems

Background. The molecular profiling of complex microbial communities has become the basis for examining the relationship between the microbiome composition, structure and metabolic functions of those communities. Microbial community structure can be partially assessed with “universal” PCR targeting taxonomic or functional gene markers. Increasingly, shotgun metagenomic DNA sequencing is providing more quantitative insight into microbiomes. However, both amplicon-based and shotgun sequencing approaches have shortcomings that limit the ability to study microbiome dynamics. Methods. We present a novel, amplicon-free, hybridization-based method (CaptureSeq) for profiling complex microbial communities using probes based on the chaperonin-60 gene. Molecular profiles of a commercially available synthetic microbial community standard were compared using CaptureSeq, whole metagenome sequencing, and 16S universal target amplification. Profiles were also generated for natural ecosystems including antibiotic-amended soils, manure storage tanks, and an agricultural reservoir. Results. The CaptureSeq method generated a microbial profile that encompassed all of the bacteria and eukaryotes in the panel with greater reproducibility and more accurate representation of high G/C content microorganisms compared to 16S amplification. In the natural ecosystems, CaptureSeq provided a much greater depth of coverage and sensitivity of detection compared to shotgun sequencing without prior selection. The resulting community profiles provided quantitatively reliable information about all three domains of life (Bacteria, Archaea, and Eukarya) in the different ecosystems. The applications of CaptureSeq will facilitate accurate studies of host-microbiome interactions for environmental, crop, animal and human health. Conclusions: cpn60-based hybridization enriched for taxonomically informative DNA sequences from complex mixtures. In synthetic and natural microbial ecosystems, CaptureSeq provided sequences from prokaryotes and eukaryotes simultaneously, with quantitatively reliable read abundances. CaptureSeq provides an alternative to PCR amplification of taxonomic markers with deep community coverage while minimizing amplification biases.

DNA metabarcoding of zooplankton communities: species diversity and seasonal variation revealed by 18S rRNA and COI

Background

Zooplankton is an important component of aquatic organisms and has important biological and economical significance in freshwater ecosystems. However, traditional methods that rely on morphology to classify zooplankton require expert taxonomic skills. Moreover, traditional classification methods are time-consuming and labor-intensive, which is not practical for the design of conservation measures and ecological management tools based on zooplankton diversity assessment.

Methods

We used DNA metabarcoding technology with two different markers: the nuclear small subunit ribosomal RNA (18S rRNA) and mitochondrial cytochrome c oxidase (COI), to analyze 72 zooplankton samples collected in 4 seasons and 9 locations from the Sanmenxia Reservoir. We investigated seasonal changes in the zooplankton community and their relationship with water environmental factors.

Results

A total of 190 species of zooplankton were found, belonging to 12 phyla, 24 classes, 61 orders, 111 families, and 174 genera. Protozoa, especially ciliates, were the most diverse taxa. Richness and relative abundance of zooplankton showed significant seasonal changes. Both alpha and beta diversity showed seasonal trends: the diversity in summer and autumn was higher than that in winter and spring. The zooplankton diversity was most similar in winter and spring. By correlating metabarcoding data and water environmental factors, we proved that water temperature, chemical oxygen demand, total nitrogen and ammoniacal nitrogen were the main environmental factors driving the seasonal changes in zooplankton in the Sanmenxia Reservoir. Water temperature, followed by total nitrogen, were the most influential factors. This study highlights the advantages and some limitations of zooplankton molecular biodiversity assessment using two molecular markers.

Effects of surface skewness on local shear stresses, biofilm activity, and microbial communities for wastewater treatment

This study's objective was to assess attachment surface skewness (asymmetric surface height variation) effects on biofilm development. 3D printed molds were used to create surfaces with 300 μm features to provide opposite skewness but identical roughness values. Surfaces with negative skewness had consistently greater nitrite oxidation and biomass growth than other surfaces during biofilm development when studied in annular bioreactor systems. CFD modelling predicted local shear stress differences that could explain experimental results. 16 s rRNA gene amplicon sequencing revealed population differences, including relatively high Acinetobacter and Terrimonas fractions on the negative skew surfaces, and PCoA analyses indicated the flat surface populations diverged from the skew surfaces by the study's end. The results suggest skewness is particularly important in systems where biofilms have not overgrown surface features, as in system startup, thin biofilms, and shorter time frame studies, which includes much previous microbial attachment research.

An Improved hgcAB Primer Set and Direct High-Throughput Sequencing Expand Hg-Methylator Diversity in Nature

The gene pair hgcAB is essential for microbial mercury methylation. Our understanding of its abundance and diversity in nature is rapidly evolving. In this study we developed a new broad-range primer set for hgcAB, plus an expanded hgcAB reference library, and used these to characterize Hg-methylating communities from diverse environments. We applied this new Hg-methylator database to assign taxonomy to hgcA sequences from clone, amplicon, and metagenomic datasets. We evaluated potential biases introduced in primer design, sequence length, and classification, and suggest best practices for studying Hg-methylator diversity. Our study confirms the emerging picture of an expanded diversity of HgcAB-encoding microbes in many types of ecosystems, with abundant putative mercury methylators Nitrospirae and Chloroflexi in several new environments including salt marsh and peat soils. Other common microbes encoding HgcAB included Phycisphaerae, Aminicenantes, Spirochaetes, and Elusimicrobia. Combined with high-throughput amplicon specific sequencing, the new primer set also indentified novel hgcAB sequences similar to Lentisphaerae, Bacteroidetes, Atribacteria, and candidate phyla WOR-3 and KSB1 bacteria. Gene abundance data also corroborate the important role of two "classic" groups of methylators (Deltaproteobacteria and Methanomicrobia) in many environments, but generally show a scarcity of hgcAB+ Firmicutes. The new primer set was developed to specifically target hgcAB sequences found in nature, reducing degeneracy and providing increased sensitivity while maintaining broad diversity capture. We evaluated mock communities to confirm primer improvements, including culture spikes to environmental samples with variable DNA extraction and PCR amplification efficiencies. For select sites, this new workflow was combined with direct high-throughput hgcAB sequencing. The hgcAB diversity generated by direct amplicon sequencing confirmed the potential for novel Hg-methylators previously identified using metagenomic screens. A new phylogenetic analysis using sequences from freshwater, saline, and terrestrial environments showed Deltaproteobacteria HgcA sequences generally clustered among themselves, while metagenome-resolved HgcA sequences in other phyla tended to cluster by environment, suggesting horizontal gene transfer into many clades. HgcA from marine metagenomes often formed distinct subtrees from those sequenced from freshwater ecosystems. Overall the majority of HgcA sequences branch from a cluster of HgcAB fused proteins related to Thermococci, Atribacteria (candidate division OP9), Aminicenantes (OP8), and Chloroflexi. The improved primer set and library, combined with direct amplicon sequencing, provide a significantly improved assessment of the abundance and diversity of hgcAB+ microbes in nature.

The Microbiome in Immuno-oncology

The field of cancer therapy has been revolutionized through the use of immunotherapy, and treatment with these therapies now spans from early to late stage, and even into prevention. However, there are still a significant proportion of patients who do not derive long-term benefit from monotherapy and even combined therapy regimens, and novel approaches are needed to enhance therapeutic responses. Additionally, ideal biomarkers of response to immunotherapy are lacking and are critically needed. An emerging area of interest in immuno-oncology (IO) is the microbiome, which refers to the collection of microbes (and their genomes) that inhabit an individual and live in symbiosis. There is now evidence that these microbes (particularly those within the gut) impact host physiology and can impact responses to immunotherapy. The field of microbiome research in immuno-oncology is quickly emerging, with the potential use of the microbiome (in the gut as well as in the tumor) as a biomarker for response to IO as well as a therapeutic target. Notably, the microbiome may even have a role in toxicity to therapy. The state of the science in microbiome and IO are discussed and caveats and future directions are outlined to provide insights as we move forward as a field.

Bradyrhizobium as the Only Rhizobial Inhabitant of Mung Bean (Vigna radiata) Nodules in Tropical Soils: A Strategy Based on Microbiome for Improving Biological Nitrogen Fixation Using Bio-Products

The mung bean has a great potential under tropical conditions given its high content of grain protein. Additionally, its ability to benefit from biological nitrogen fixation (BNF) through association with native rhizobia inhabiting nodule microbiome provides most of the nitrogen independence on fertilizers. Soil microbial communities which are influenced by biogeographical factors and soil properties, represent a source of rhizobacteria capable of stimulating plant growth. The objective of this study is to support selection of beneficial bacteria that form positive interactions with mung bean plants cultivated in tropical soils, as part of a seed inoculation program for increasing grain yield based on the BNF and other mechanisms. Two mung bean genotypes (Camaleão and Esmeralda) were cultivated in 10 soil samples. Nodule microbiome was characterized by next-generation sequencing using Illumina MiSeq 16S rRNA. More than 99% of nodule sequences showed similarity with Bradyrhizobium genus, the only rhizobial present in nodules in our study. Higher bacterial diversity of soil samples collected in agribusiness areas (MW_MT-I, II or III) was associated with Esmeralda genotype, while an organic agroecosystem soil sample (SE_RJ-V) showed the highest bacterial diversity independent of genotype. Furthermore, OTUs close to Bradyrhizobium elkanii have dominated in all soil samples, except in the sample from the organic agroecosystem, where just B. japonicum was present. Bacterial community of mung bean nodules is mainly influenced by soil pH, K, Ca, and P. Besides a difference on nodule colonization by OTU sequences close to the Pseudomonas genus regarding the two genotypes was detected too. Although representing a small rate, around 0.1% of the total, Pseudomonas OTUs were only retrieved from nodules of Esmeralda genotype, suggesting a different trait regarding specificity between macro- and micro-symbionts. The microbiome analysis will guide the next steps in the development of an inoculant for mung bean aiming to promote plant growth and grain yield, composed either by an efficient Bradyrhizobium strain on its own or co-inoculated with a Pseudomonas strain. Considering the results achieved, the assessment of microbial ecology parameters is a potent coadjuvant capable to accelerate the inoculant development process and to improve the benefits to the crop by soil microorganisms.

Protocatechuic acid improved growth performance, meat quality, and intestinal health of Chinese yellow-feathered broilers

The aim of this study was to investigate the effect of protocatechuic acid (PCA) on the growth performance, meat quality, and intestinal health of Chinese yellow-feathered broilers. Growing broilers were fed the basal diet or diets supplemented with 300 or 600 mg/kg PCA, or 200 mg/kg enramycin for 52 D. We found that addition of 300 mg/kg PCA significantly increased body weight, live weight, and carcass weight and decreased the feed to gain ratio of broilers; PCA improved meat quality through reducing shear force, and increasing a* (relative redness) and decreasing b* (relative yellowness) at 24 h after slaughter. The activities of alkaline phosphatase and diamine oxidase in plasma were significantly decreased by administration of 300 mg/kg PCA; PCA also significantly increased total antioxidant capability and decreased malondialdehyde content and activity of xanthine oxidase in liver. Meanwhile, it enhanced activities of total superoxide dismutase, glutathione s-transferase, and glutathione peroxidase in the jejunal mucosa. Interleukin-10 and transforming growth factor-β were significantly increased in jejunal mucosa and plasma of 300 mg/kg PCA diet group, whereas interluekin-2 and interferon-γ dropped dramatically. Moreover, relative expression of apoptosis-related genes decreased in liver, whereas that of intestinal barrier-related and immunity-related genes increased in jejunum. Furthermore, 300 mg/kg PCA treatment significantly changed α-diversity and structure of the cecal microflora in broilers, with increasing relative abundance of Firmicutes and Actinobacteria while reducing Bacteroidetes and Proteobacteria. These results indicated that PCA improved the feed efficiency, growth performance, meat quality of broilers, and antioxidant capacity. It also enhanced intestinal immune function and improved the structure of intestinal flora to favor improved intestinal health in Chinese yellow-feathered broilers.

Wood Decay Characteristics and Interspecific Interactions Control Bacterial Community Succession in Populus grandidentata (Bigtooth Aspen)

Few studies have investigated bacterial community succession and the role of bacterial decomposition over a continuum of wood decay. Here, we identified how (i) the diversity and abundance of bacteria changed along a chronosequence of decay in Populus grandidentata (bigtooth aspen); (ii) bacterial community succession was dependent on the physical and chemical characteristics of the wood; (iii) interspecific bacterial interactions may mediate community structure. Four hundred and fifty-nine taxa were identified through Illumina sequencing of 16S rRNA amplicons from samples taken along a continuum of decay, representing standing dead trees, downed wood, and soil. Community diversity increased as decomposition progressed, peaking in the most decomposed trees. While a small proportion of taxa displayed a significant pattern in regards to decay status of the host log, many bacterial taxa followed a stochastic distribution. Changes in the water availability and chemical composition of standing dead and downed trees and soil were strongly coupled with shifts in bacterial communities. Nitrogen was a major driver of succession and nitrogen-fixing taxa of the order Rhizobiales were abundant early in decomposition. Recently downed logs shared 65% of their bacterial abundance with the microbiomes of standing dead trees while only sharing 16% with soil. As decay proceeds, bacterial communities appear to respond less to shifting resource availability and more to interspecific bacterial interactions - we report an increase in both the proportion (+9.3%) and the intensity (+62.3%) of interspecific interactions in later stages of decomposition, suggesting the emergence of a more complex community structure as wood decay progresses.

Bile Diversion Improves Metabolic Phenotype Dependent on Farnesoid X Receptor (FXR)

OBJECTIVE

The current study investigated whether bile diversion (BD) improves metabolic phenotype under farnesoid X receptor (FXR) deficiency.

METHODS

BD was performed in high-fat diet (HFD)-fed FXR knockout (FXRko) and wild-type (WT) animals. Metabolic phenotypes, circulating enteroendocrine hormones, total bile acids (BAs) and BA composition, and cecal gut microbiota were analyzed.

RESULTS

FXR-deficient mice were resistant to HFD-induced obesity; however, FXR-deficient mice also developed hyperglycemia and exhibited increased liver weight, liver steatosis, and circulating triglycerides. BD increased circulating total BAs and taurine-b-muricholic acid, which were in line with normalized hyperglycemia and improved glucose tolerance in HFD-fed WT mice. FXR deficiency also increased total BAs and taurine-b-muricholic acid, but these animals remained hyperglycemic. While BD improved metabolic phenotype in HFD-fed FXRko mice, these improvements were not as effective as in WT mice. BD increased liver expression of fibroblast growth factor 21 and peroxisome proliferator-activated receptor γ coactivator-1β and elevated circulating glucagon-like peptide-1 levels in WT mice but not in FXRko mice. FXR deficiency altered gut microbiota composition with a specific increase in phylum Proteobacteria that may act as a possible microbial signature of some diseases. These cellular and molecular changes in FXRko mice may contribute to resistance toward improved metabolism.

CONCLUSIONS

FXR signaling plays a pivotal role in improved metabolic phenotype following BD surgery.

Microbial community analysis in biologically active filters exhibiting efficient removal of emerging contaminants and impact of operational conditions

In biologically active filters (BAFs), microorganisms acclimated on the media surface are the key players responsible for removing organic water contaminants. In this study, next generation sequencing by Illumina MiSeq was used to characterize the microbial community structures in the influent, effluent, and media of a set of bench-scale BAFs that have been demonstrated with high removal efficiency (>75%) of 16 contaminants of emerging concern (CECs), which include a variety of pharmaceuticals (e.g., sulfamethoxazole and ibuprofen), X-ray contrast agent (i.e., iopromide), and pesticides (e.g., atrazine) that are prevalently found in municipal waste streams. Proteobacteria and Planctomycetes were the most abundant phyla in filter media, while the influent and effluent samples were dominated by Proteobacteria, Actinobacteria, and Chlamydiae. Factorial and principal component analysis revealed microbial structures in the media were significantly affected by the operation conditions, including media type (GAC versus dual media anthracite sand), EBCT (10 versus 18 min), and pre-ozonation. Detrended correspondence analysis demonstrated media materials predominantly governed the structures of the acclimated biofilm in BAFs as they provide direct attachment surface. This is in line with the higher microbial activity and better treatment performance exhibited by GAC BAFs compared to the dual media BAFs, corroborating the importance of filter media selection to promote the acclimation of active and robust biofilm for efficient CEC removal. Principal component analysis revealed the significant influence from ozonation, which does not only break down CECs, but also stimulates microbes that grow on the ozonation products. Partial canonical correlation analysis further proved the shaping of biofilm communities on the BAF media is more associated with media type and ozonation compared to EBCT. Putative CEC degraders are predicted based on their dominance in the media and degradation capabilities reported in previous literature. This is the first study to examine the relationship between the microbial community structure and the BAF operating parameters, which are both aligned with the treatment performance exhibited by the BAFs.

Microbial Communities Associated With Indigo Fermentation That Thrive in Anaerobic Alkaline Environments

Indigo fermentation, which depends on the indigo-reducing action of microorganisms, has traditionally been performed to dye textiles blue in Asia as well as in Europe. This fermentation process is carried out by naturally occurring microbial communities and occurs under alkaline, anaerobic conditions. Therefore, there is uncertainty regarding the fermentation process, and many unknown microorganisms thrive in this unique fermentation environment. Until recently, there was limited information available on bacteria associated with this fermentation process. Indigo reduction normally occurs from 4 days to 2 weeks after initiation of fermentation. However, the changes in the microbiota that occur during the transition to an indigo-reducing state have not been elucidated. Here, the structural changes in the bacterial community were estimated by PCR-based methods. On the second day of fermentation, a large change in the redox potential occurred. On the fourth day, distinct substitution of the genus Halomonas with the aerotolerant genus Amphibacillus was observed, corresponding to marked changes in indigo reduction. Under open-air conditions, indigo reduction during the fermentation process continued for 6 months on average. The microbiota, including indigo-reducing bacteria, was continuously replaced with other microbial communities that consisted of other types of indigo-reducing bacteria. A stable state consisting mainly of the genus Anaerobacillus was also observed in a long-term fermentation sample. The stability of the microbiota, proportion of indigo-reducing microorganisms, and appropriate diversity and microbiota within the fluid may play key factors in the maintenance of a reducing state during long-term indigo fermentation. Although more than 10 species of indigo-reducing bacteria were identified, the reduction mechanism of indigo particle is riddle. It can be predicted that the mechanism involves electrons, as byproducts of metabolism, being discarded by analogs mechanisms reported in bacterial extracellular solid Fe3+ reduction under alkaline anaerobic condition.

The evidence for fungus in Crohn's disease pathogenesis

Current evidence suggests the etiology of inflammatory bowel diseases (IBD) involves the confluence of host genetic, environmental, and microbial factors that lead to chronic, and often refractory, disease in susceptible individuals. The involvement of microbial triggers in IBD, including Crohn's disease (CD), is increasingly evident with supporting data provided with advancements in metagenomic sequencing that have identified perturbations in microbial structure and function-broadly termed dysbiosis-in CD patients compared with healthy subjects. This concept is supported by the finding germ-free animals with CD genetic susceptibility fail to develop disease; demonstrating microorganisms are necessary but not sufficient for CD. The vast majority of CD microbiome research has focused on the complex bacterial communities and microbiome dysbiosis in the gut with 16S metagenomic sequencing. However, emerging data capturing eukaryotes suggest fungal opportunistic pathogens are also associated with IBD pathogenesis and chronicity. This hypothesis is further supported by historical observations that CD patient populations display elevated antibodies against fungal targets, even evident before disease diagnosis. This review discusses the current findings in the field, followed by historical and metagenomic evidence for fungal pathogens in the development and recurrence of CD in adult and pediatric populations.

Bacterial communities associated with honeybee food stores are correlated with land use

Microbial communities, associated with almost all metazoans, can be inherited from the environment. Although the honeybee (Apis mellifera L.) gut microbiome is well documented, studies of the gut focus on just a small component of the bee microbiome. Other key areas such as the comb, propolis, honey, and stored pollen (bee bread) are poorly understood. Furthermore, little is known about the relationship between the pollinator microbiome and its environment. Here we present a study of the bee bread microbiome and its relationship with land use. We estimated bacterial community composition using both Illumina MiSeq DNA sequencing and denaturing gradient gel electrophoresis (DGGE). Illumina was used to gain a deeper understanding of precise species diversity across samples. DGGE was used on a larger number of samples where the costs of MiSeq had become prohibitive and therefore allowed us to study a greater number of bee breads across broader geographical axes. The former demonstrates bee bread comprises, on average, 13 distinct bacterial phyla; Bacteroidetes, Firmicutes, Alpha-proteobacteria, Beta-proteobacteria, and Gamma-proteobacteria were the five most abundant. The most common genera were Pseudomonas, Arsenophonus, Lactobacillus, Erwinia, and Acinetobacter. DGGE data show bacterial community composition and diversity varied spatially and temporally both within and between hives. Land use data were obtained from the 2007 Countryside Survey. Certain habitats, such as improved grasslands, are associated with low diversity bee breads, meaning that these environments may be poor sources of bee-associated bacteria. Decreased bee bread bacterial diversity may result in reduced function within hives. Although the dispersal of microbes is ubiquitous, this study has demonstrated landscape-level effects on microbial community composition.

Toxic Cyanobacteria in Svalbard: Chemical Diversity of Microcystins Detected Using a Liquid Chromatography Mass Spectrometry Precursor Ion Screening Method

Cyanobacteria synthesize a large variety of secondary metabolites including toxins. Microcystins (MCs) with hepato- and neurotoxic potential are well studied in bloom-forming planktonic species of temperate and tropical regions. Cyanobacterial biofilms thriving in the polar regions have recently emerged as a rich source for cyanobacterial secondary metabolites including previously undescribed congeners of microcystin. However, detection and detailed identification of these compounds is difficult due to unusual sample matrices and structural congeners produced. We here report a time-efficient liquid chromatography-mass spectrometry (LC-MS) precursor ion screening method that facilitates microcystin detection and identification. We applied this method to detect six different MC congeners in 8 out of 26 microbial mat samples of the Svalbard Archipelago in the Arctic. The congeners, of which [Asp³, ADMAdda⁵, Dhb⁷] MC-LR was most abundant, were similar to those reported in other polar habitats. Microcystins were also determined using an Adda-specific enzyme-linked immunosorbent assay (Adda-ELISA). Nostoc sp. was identified as a putative toxin producer using molecular methods that targeted 16S rRNA genes and genes involved in microcystin production. The mcy genes detected showed highest similarities to other Arctic or Antarctic sequences. The LC-MS precursor ion screening method could be useful for microcystin detection in unusual matrices such as benthic biofilms or lichen.

Testing culture purity in prokaryotes: criteria and challenges

Reliance on pure cultures was introduced at the beginning of microbiology as a discipline and has remained significant although their adaptive properties are essentially dissimilar from those of mixed cultures and environmental populations. They are needed for (i) taxonomic identification; (ii) diagnostics of pathogens; (iii) virulence and pathogenicity studies; (iv) elucidation of metabolic properties; (v) testing sensitivity to antibiotics; (vi) full-length genome assembly; (vii) strain deposition in microbial collections; and (viii) description of new species with name validation. Depending on the specific task there are alternative claims for culture purity, i.e., when conventional criteria are satisfied or when looking deeper is necessary. Conventional proof (microscopic and plating controls) has a low resolution and depends on the observer's personal judgement. Phenotypic criteria alone cannot prove culture purity and should be complemented with genomic criteria. We consider the possible use of DNA high-throughput culture sequencing data to define criteria for only one genospecies, axenic state detection panel and only one genome. The second and third of these are preferable, although their resolving capacity (depth) is limited. Because minor contaminants may go undetected, even with deep sequencing, the reliably pure culture would be a clonal culture launched from a single cell or trichome (multicellular bacterium). Although this type of culture is associated with technical difficulties and cannot be employed on a large scale (the corresponding inoculums may have low chances of growth when transferred to solid media), it is hoped that the high-throughput culturing methods introduced by 'culturomics' will overcome this obstacle.

Protocols for Investigating the Leaf Mycobiome Using High-Throughput DNA Sequencing

High-throughput sequencing of taxon-specific loci, or DNA metabarcoding, has become an invaluable tool for investigating the composition of plant-associated fungal communities and for elucidating plant-fungal interactions. While sequencing fungal communities has become routine, there remain numerous potential sources of systematic error that can introduce biases and compromise metabarcoding data. This chapter presents a protocol for DNA metabarcoding of the leaf mycobiome based on current best practices to minimize errors through careful laboratory practices and validation.

Statistical analysis of co-occurrence patterns in microbial presence-absence datasets

Drawing on a long history in macroecology, correlation analysis of microbiome datasets is becoming a common practice for identifying relationships or shared ecological niches among bacterial taxa. However, many of the statistical issues that plague such analyses in macroscale communities remain unresolved for microbial communities. Here, we discuss problems in the analysis of microbial species correlations based on presence-absence data. We focus on presence-absence data because this information is more readily obtainable from sequencing studies, especially for whole-genome sequencing, where abundance estimation is still in its infancy. First, we show how Pearson's correlation coefficient (r) and Jaccard's index (J)-two of the most common metrics for correlation analysis of presence-absence data-can contradict each other when applied to a typical microbiome dataset. In our dataset, for example, 14% of species-pairs predicted to be significantly correlated by r were not predicted to be significantly correlated using J, while 37.4% of species-pairs predicted to be significantly correlated by J were not predicted to be significantly correlated using r. Mismatch was particularly common among species-pairs with at least one rare species (<10% prevalence), explaining why r and J might differ more strongly in microbiome datasets, where there are large numbers of rare taxa. Indeed 74% of all species-pairs in our study had at least one rare species. Next, we show how Pearson's correlation coefficient can result in artificial inflation of positive taxon relationships and how this is a particular problem for microbiome studies. We then illustrate how Jaccard's index of similarity (J) can yield improvements over Pearson's correlation coefficient. However, the standard null model for Jaccard's index is flawed, and thus introduces its own set of spurious conclusions. We thus identify a better null model based on a hypergeometric distribution, which appropriately corrects for species prevalence. This model is available from recent statistics literature, and can be used for evaluating the significance of any value of an empirically observed Jaccard's index. The resulting simple, yet effective method for handling correlation analysis of microbial presence-absence datasets provides a robust means of testing and finding relationships and/or shared environmental responses among microbial taxa.

16S rRNA gene sequencing on a benchtop sequencer: accuracy for identification of clinically important bacteria

AIMS

Test the choice of 16S rRNA gene amplicon and data analysis method on the accuracy of identification of clinically important bacteria utilizing a benchtop sequencer.

METHODS AND RESULTS

Nine 16S rRNA amplicons were tested on an Ion Torrent PGM to identify 41 strains of clinical importance. The V1-V2 region identified 40 of 41 isolates to the species level. Three data analysis methods were tested, finding that the Ribosomal Database Project's SequenceMatch outperformed BLAST and the Ion Reporter Metagenomics analysis pipeline. Lastly, 16S rRNA gene sequencing mixtures of four species through a six log range of dilution showed species were identifiable even when present as 0·1% of the mixture.

CONCLUSIONS

Sequencing the V1-V2 16S rRNA gene region, made possible by the increased read length Ion Torrent PGM sequencer's 400 base pair chemistry, may be a better choice over other commonly used regions for identifying clinically important bacteria. In addition, the SequenceMatch algorithm, freely available from the Ribosomal Database Project, is a good choice for matching filtered reads to organisms. Lastly, 16S rRNA gene sequencing's sensitivity to the presence of a bacterial species at 0·1% of a mixture suggests it has sufficient sensitivity for samples in which important bacteria may be rare.

SIGNIFICANCE AND IMPACT OF THE STUDY

We have validated 16S rRNA gene sequencing on a benchtop sequencer including simple mixtures of organisms; however, our results highlight deficits for clinical application in place of current identification methods.

Nutritional composition of honey bee food stores vary with floral composition

Sufficiently diverse and abundant resources are essential for generalist consumers, and form an important part of a suite of conservation strategies for pollinators. Honey bees are generalist foragers and are dependent on diverse forage to adequately meet their nutritional needs. Through analysis of stored pollen (bee bread) samples obtained from 26 honey bee (Apis mellifera L.) hives across NW-England, we quantified bee bread nutritional content and the plant species that produced these stores from pollen. Protein was the most abundant nutrient by mass (63%), followed by carbohydrates (26%). Protein and lipid content (but not carbohydrate) contributed significantly to ordinations of floral diversity, linking dietary quality with forage composition. DNA sequencing of the ITS2 region of the nuclear ribosomal DNA gene identified pollen from 89 distinct plant genera, with each bee bread sample containing between 6 and 35 pollen types. Dominant genera included dandelion (Taraxacum), which was positively correlated with bee bread protein content, and cherry (Prunus), which was negatively correlated with the amount of protein. In addition, proportions of amino acids (e.g. histidine and valine) varied as a function of floral species composition. These results also quantify the effects of individual plant genera on the nutrition of honey bees. We conclude that pollens of different plants act synergistically to influence host nutrition; the pollen diversity of bee bread is linked to its nutrient content. Diverse environments compensate for the loss of individual forage plants, and diversity loss may, therefore, destabilize consumer communities due to restricted access to alternative resources.

Indigenous species barcode database improves the identification of zooplankton

Incompleteness and inaccuracy of DNA barcode databases is considered an important hindrance to the use of metabarcoding in biodiversity analysis of zooplankton at the species-level. Species barcoding by Sanger sequencing is inefficient for organisms with small body sizes, such as zooplankton. Here mitochondrial cytochrome c oxidase I (COI) fragment barcodes from 910 freshwater zooplankton specimens (87 morphospecies) were recovered by a high-throughput sequencing platform, Ion Torrent PGM. Intraspecific divergence of most zooplanktons was < 5%, except Branchionus leydign (Rotifer, 14.3%), Trichocerca elongate (Rotifer, 11.5%), Lecane bulla (Rotifer, 15.9%), Synchaeta oblonga (Rotifer, 5.95%) and Schmackeria forbesi (Copepod, 6.5%). Metabarcoding data of 28 environmental samples from Lake Tai were annotated by both an indigenous database and NCBI Genbank database. The indigenous database improved the taxonomic assignment of metabarcoding of zooplankton. Most zooplankton (81%) with barcode sequences in the indigenous database were identified by metabarcoding monitoring. Furthermore, the frequency and distribution of zooplankton were also consistent between metabarcoding and morphology identification. Overall, the indigenous database improved the taxonomic assignment of zooplankton.

Methanogens predominate in natural corrosion protective layers on metal sheet piles

Microorganisms are able to cause, but also to inhibit or protect against corrosion. Corrosion inhibition by microbial processes may be due to the formation of mineral deposition layers on metal objects. Such deposition layers have been found in archaeological studies on ancient metal objects, buried in soil, which were hardly corroded. Recent field investigations showed that natural mineral deposition layers can be found on sheet piles in soil. We investigated the microbial communities of these deposition layers and the adjacent soil. Our data, from five different sampling sites, all show striking differences between microbial communities of the deposition layer versus the adjacent soil over the depth profile. Bacterial species dominated in top soil while archaeal sequences increased in abundance with depth. All mineral deposition layers from the steel surface were dominated by Euryarchaeota, of which almost all sequences were phylogenetically related with the Methanobacteria genus. The mineral layer consisted of carbonate precipitates. Based on 16S rDNA gene sequencing data we hypothesize that the methanogens directly extract electrons from the metal surface, thereby, initially inducing mild corrosion, but simultaneously, inducing carbonate precipitation. This, will cause encrustation of the archaea, which drastically slow down their activity and create a natural protective layer against further corrosion.

Degenerate ITS7 primer enhances oomycete community coverage and PCR sensitivity to Aphanomyces species, economically important plant pathogens

Metagenomic analysis of oomycetes through deep amplicon sequencing has been conducted primarily using the ITS6-ITS7 primer set that targets the ITS1 region. While this primer set shows a perfect match to most oomycete taxa, ITS7 contains 3 mismatches to the corresponding binding site of plant pathogens within the genus Aphanomyces. Polymerase chain reaction (PCR) efficiency differs for taxa with uneven primer matching characteristics, which may explain why previous studies have detected this genus at low abundance. To overcome the impact of these mismatches on PCR sensitivity, the mismatched nucleotides were replaced with degenerate nucleotides. Oomycete communities from 35 soil samples collected from asymptomatic and root rot diseased sites in pea fields across Alberta were analyzed simultaneously using ITS6-ITS7 and ITS6-ITS7-a.e. (modified version of ITS7) primer sets on 1 Illumina MiSeq run. The number of high-quality reads obtained by ITS6-ITS7-a.e. was more than twice that of ITS6-ITS7. The relative abundance of Pythium spp. was reduced and Aphanomyces spp. increased. Aphanomyces cf. cladogamus and Aphanomyces euteiches were the second and third most abundant species, respectively, in the pea rhizosphere using the ITS7-a.e. primer, but were rare using the ITS7 primer. These results indicate that use of ITS7-a.e. provides a more accurate picture of oomycete communities than ITS7 by enhancing PCR sensitivity to Aphanomyces.

Bioinformatics for NGS-based metagenomics and the application to biogas research

Metagenomics has proven to be one of the most important research fields for microbial ecology during the last decade. Starting from 16S rRNA marker gene analysis for the characterization of community compositions to whole metagenome shotgun sequencing which additionally allows for functional analysis, metagenomics has been applied in a wide spectrum of research areas. The cost reduction paired with the increase in the amount of data due to the advent of next-generation sequencing led to a rapidly growing demand for bioinformatic software in metagenomics. By now, a large number of tools that can be used to analyze metagenomic datasets has been developed. The Bielefeld-Gießen center for microbial bioinformatics as part of the German Network for Bioinformatics Infrastructure bundles and imparts expert knowledge in the analysis of metagenomic datasets, especially in research on microbial communities involved in anaerobic digestion residing in biogas reactors. In this review, we give an overview of the field of metagenomics, introduce into important bioinformatic tools and possible workflows, accompanied by application examples of biogas surveys successfully conducted at the Center for Biotechnology of Bielefeld University.

Evaluation of method bias for determining bacterial populations in bacterial community analyses

Various methods are used for analyzing a bacterial community. We recently developed a method for quantifying each bacterium constituting the microbiota by combining a next-generation sequencing (NGS) analysis with a quantitative polymerase chain reaction (NGS-qPCR) assay. Our NGS-qPCR method is useful for analyzing a comprehensive bacterial community because it is enables the easy calculation of the amounts of each bacterium constituting the microbiota. However, it has not been confirmed whether the estimated bacterial community obtained using this NGS-qPCR method corresponds to the results obtained using conventional methods. Accordingly, we prepared model bacterial community samples and analyzed them by several methods (NGS-qPCR, species-specific qPCR, flow cytometry, total direct counting by epifluorescent microscopy [TDC], and plate count). The total bacterial cell densities determined by the PCR-based methods were largely consistent with those determined by the TDC method. There was a difference between the amounts of each bacterium analyzed by NGS-qPCR and species-specific qPCR, although the same trend was shown by both species-specific qPCR and NGS-qPCR. Our findings also demonstrated that there is a strong positive correlation between the cell densities of a specific bacterial group in craft beer samples determined by group-specific qPCR and NGS-qPCR, and there were no significant differences among quantification methods (we tested two bacterial groups: lactic acid bacteria and acetic acid bacteria). Thus, the NGS-qPCR method is a practical method for analyzing a comprehensive bacterial community based on a bacterial cell density.

Evaluating the accuracy of amplicon-based microbiome computational pipelines on simulated human gut microbial communities

Background

Microbiome studies commonly use 16S rRNA gene amplicon sequencing to characterize microbial communities. Errors introduced at multiple steps in this process can affect the interpretation of the data. Here we evaluate the accuracy of operational taxonomic unit (OTU) generation, taxonomic classification, alpha- and beta-diversity measures for different settings in QIIME, MOTHUR and a pplacer-based classification pipeline, using a novel software package: DECARD.

Results

In-silico we generated 100 synthetic bacterial communities approximating human stool microbiomes to be used as a gold-standard for evaluating the colligative performance of microbiome analysis software. Our synthetic data closely matched the composition and complexity of actual healthy human stool microbiomes. Genus-level taxonomic classification was correctly done for only 50.4–74.8% of the source organisms. Miscall rates varied from 11.9 to 23.5%. Species-level classification was less successful, (6.9–18.9% correct); miscall rates were comparable to those of genus-level targets (12.5–26.2%). The degree of miscall varied by clade of organism, pipeline and specific settings used. OTU generation accuracy varied by strategy (closed, de novo or subsampling), reference database, algorithm and software implementation. Shannon diversity estimation accuracy correlated generally with OTU-generation accuracy. Beta-diversity estimates with Double Principle Coordinate Analysis (DPCoA) were more robust against errors introduced in processing than Weighted UniFrac. The settings suggested in the tutorials were among the worst performing in all outcomes tested.

Conclusions

Even when using the same classification pipeline, the specific OTU-generation strategy, reference database and downstream analysis methods selection can have a dramatic effect on the accuracy of taxonomic classification, and alpha- and beta-diversity estimation. Even minor changes in settings adversely affected the accuracy of the results, bringing them far from the best-observed result. Thus, specific details of how a pipeline is used (including OTU generation strategy, reference sets, clustering algorithm and specific software implementation) should be specified in the methods section of all microbiome studies. Researchers should evaluate their chosen pipeline and settings to confirm it can adequately answer the research question rather than assuming the tutorial or standard-operating-procedure settings will be adequate or optimal.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-017-1690-0) contains supplementary material, which is available to authorized users.

Zooplankton Community Profiling in a Eutrophic Freshwater Ecosystem-Lake Tai Basin by DNA Metabarcoding

Communities of zooplankton, a critical portion of aquatic ecosystems, can be adversely affected by contamination resulting from human activities. Understanding the influence of environmental change on zooplankton communities under field-conditions is hindered by traditional labor-intensive approaches that are prone to taxonomic and enumeration mistakes. Here, metabarcoding of cytochrome c oxidase I (COI) region of mitochondrial DNA was used to characterize the genetic diversity of zooplankton. The species composition of zooplankton communities determined by metabarcoding was consistent with the results based on the traditional morphological approach. The spatial distribution of common species (frequency of occurrence >10 samples) by metabarcoding exhibited good agreement with morphological data. Furthermore, metabarcoding can clearly distinguish the composition of the zooplankton community between lake and river ecosystems. In general, rotifers were more abundant in riverine environments than lakes and reservoirs. Finally, the sequence read number of different taxonomic groups using metabarcoding was positively correlated with the zooplankton biomass inferred by density and body length of zooplankton. Overall, the utility of metabarcoding for taxonomic profiling of zooplankton communities was validated by the morphology-based method on a large ecological scale. Metabarcoding of COI could be a powerful and efficient biomonitoring tool to protect local aquatic ecosystems.

Microbiome disruption and recovery in the fish Gambusia affinis following exposure to broad-spectrum antibiotic

Antibiotics are a relatively common disturbance to the normal microbiota of humans and agricultural animals, sometimes resulting in severe side effects such as antibiotic-associated enterocolitis. Gambusia affinis was used as a vertebrate model for effects of a broad-spectrum antibiotic, rifampicin, on the skin and gut mucosal microbiomes. The fish were exposed to the antibiotic in the water column for 1 week, and then monitored during recovery. As observed via culture, viable counts from the skin microbiome dropped strongly yet returned to pretreatment levels by 1.6 days and became >70% resistant. The gut microbiome counts dropped and took longer to recover (2.6 days), and became >90% drug resistant. The resistance persisted at ~20% of skin counts in the absence of antibiotic selection for 2 weeks. A community biochemical analysis measuring the presence/absence of 31 activities observed a 39% change in results after 3 days of antibiotic treatment. The antibiotic lowered the skin and gut microbiome community diversity and altered taxonomic composition, observed by 16S rRNA profiling. A 1-week recovery period did not return diversity or composition to pretreatment levels. The genus Myroides dominated both the microbiomes during the treatment, but was not stable and declined in abundance over time during recovery. Rifampicin selected for members of the family Comamonadaceae in the skin but not the gut microbiome. Consistent with other studies, this tractable animal model shows lasting effects on mucosal microbiomes following antibiotic exposure, including persistence of drug-resistant organisms in the community.

From Vineyard Soil to Wine Fermentation: Microbiome Approximations to Explain the "terroir" Concept

Wine originally emerged as a serendipitous mix of chemistry and biology, where microorganisms played a decisive role. From these ancient fermentations to the current monitored industrial processes, winegrowers and winemakers have been continuously changing their practices according to scientific knowledge and advances. A new enology direction is emerging and aiming to blend the complexity of spontaneous fermentations with industrial safety of monitored fermentations. In this context, wines with distinctive autochthonous peculiarities have a great acceptance among consumers, causing important economic returns. The concept of terroir, far from being a rural term, conceals a wide range of analytical parameters that are the basis of the knowledge-based enology trend. In this sense, the biological aspect of soils has been underestimated for years, when actually it contains a great microbial diversity. This soil-associated microbiota has been described as determinant, not only for the chemistry and nutritional properties of soils, but also for health, yield, and quality of the grapevine. Additionally, recent works describe the soil microbiome as the reservoir of the grapevine associated microbiota, and as a contributor to the final sensory properties of wines. To understand the crucial roles of microorganisms on the entire wine making process, we must understand their ecological niches, population dynamics, and relationships between ‘microbiome- vine health’ and ‘microbiome-wine metabolome.’ These are critical steps for designing precision enology practices. For that purpose, current metagenomic techniques are expanding from laboratories, to the food industry. This review focuses on the current knowledge about vine and wine microbiomes, with emphasis on their biological roles and the technical basis of next-generation sequencing pipelines. An overview of molecular and informatics tools is included and new directions are proposed, highlighting the importance of –omics technologies in wine research and industry.

Second Era of OMICS in Caries Research: Moving Past the Phase of Disillusionment

Novel approaches using OMICS techniques enable a collective assessment of multiple related biological units, including genes, gene expression, proteins, and metabolites. In the past decade, next-generation sequencing ( NGS) technologies were improved by longer sequence reads and the development of genome databases and user-friendly pipelines for data analysis, all accessible at lower cost. This has generated an outburst of high-throughput data. The application of OMICS has provided more depth to existing hypotheses as well as new insights in the etiology of dental caries. For example, the determination of complete bacterial microbiomes of oral samples rather than selected species, together with oral metatranscriptome and metabolome analyses, supports the viewpoint of dysbiosis of the supragingival biofilms. In addition, metabolome studies have been instrumental in disclosing the contributions of major pathways for central carbon and amino acid metabolisms to biofilm pH homeostasis. New, often noncultured, oral streptococci have been identified, and their phenotypic characterization has revealed candidates for probiotic therapy. Although findings from OMICS research have been greatly informative, problems related to study design, data quality, integration, and reproducibility still need to be addressed. Also, the emergence and continuous updates of these computationally demanding technologies require expertise in advanced bioinformatics for reliable interpretation of data. Despite the obstacles cited above, OMICS research is expected to encourage the discovery of novel caries biomarkers and the development of next-generation diagnostics and therapies for caries control. These observations apply equally to the study of other oral diseases.

Development of a genus-specific next generation sequencing approach for sensitive and quantitative determination of the Legionella microbiome in freshwater systems

BACKGROUND

Next Generation Sequencing (NGS) has revolutionized the analysis of natural and man-made microbial communities by using universal primers for bacteria in a PCR based approach targeting the 16S rRNA gene. In our study we narrowed primer specificity to a single, monophyletic genus because for many questions in microbiology only a specific part of the whole microbiome is of interest. We have chosen the genus Legionella, comprising more than 20 pathogenic species, due to its high relevance for water-based respiratory infections.

METHODS

A new NGS-based approach was designed by sequencing 16S rRNA gene amplicons specific for the genus Legionella using the Illumina MiSeq technology. This approach was validated and applied to a set of representative freshwater samples.

RESULTS

Our results revealed that the generated libraries presented a low average raw error rate per base (<0.5%); and substantiated the use of high-fidelity enzymes, such as KAPA HiFi, for increased sequence accuracy and quality. The approach also showed high in situ specificity (>95%) and very good repeatability. Only in samples in which the gammabacterial clade SAR86 was present more than 1% non-Legionella sequences were observed. Next-generation sequencing read counts did not reveal considerable amplification/sequencing biases and showed a sensitive as well as precise quantification of L. pneumophila along a dilution range using a spiked-in, certified genome standard. The genome standard and a mock community consisting of six different Legionella species demonstrated that the developed NGS approach was quantitative and specific at the level of individual species, including L. pneumophila. The sensitivity of our genus-specific approach was at least one order of magnitude higher compared to the universal NGS approach. Comparison of quantification by real-time PCR showed consistency with the NGS data. Overall, our NGS approach can determine the quantitative abundances of Legionella species, i. e. the complete Legionella microbiome, without the need for species-specific primers.

CONCLUSIONS

The developed NGS approach provides a new molecular surveillance tool to monitor all Legionella species in qualitative and quantitative terms if a spiked-in genome standard is used to calibrate the method. Overall, the genus-specific NGS approach opens up a new avenue to massive parallel diagnostics in a quantitative, specific and sensitive way.

Biogeography and diversity of Collodaria (Radiolaria) in the global ocean

Collodaria are heterotrophic marine protists that exist either as large colonies composed of hundreds of cells or as large solitary cells. All described species so far harbour intracellular microalgae as photosymbionts. Although recent environmental diversity surveys based on molecular methods demonstrated their consistently high contribution to planktonic communities and their worldwide occurrence, our understanding of their diversity and biogeography is still very limited. Here we estimated the 18S ribosomal DNA (rDNA) gene copies per collodarian cell for solitary (5770±1960 small subunit (SSU) rDNA copies) and colonial specimens (37 474±17 799 SSU rDNA copies, for each individual cell within a colony) using single-specimen quantitative PCR. We then investigated the environmental diversity of Collodaria within the photic zone through the metabarcoding survey from the Tara Oceans expedition and found that the two collodarian families Collosphaeridae and Sphaerozoidae contributed the most to the collodarian diversity and encompassed mostly cosmopolitan taxa. Although the biogeographical patterns were homogeneous within each biogeochemical biome considered, we observed that coastal biomes were consistently less diverse than oceanic biomes and were dominated by the Sphaerozoidae while the Collosphaeridae were dominant in the open oceans. The significant relationships with six environmental variables suggest that collodarian diversity is influenced by the trophic status of oceanic provinces and increased towards more oligotrophic regions.