The first ITS2 sequence data set of eDNA from honey of Malaysian giant honeybees (Apis dorsata) and stingless bees (Heterotrigona itama) reveals plant species diversity

OBJECTIVES

Pollen is a useful tool for identifying the provenance and complex ecosystems surrounding honey production in Malaysian forests. As native key pollinators in Malaysia, Apis dorsata and Heterotrigona itama forage on various plant/pollen species to collect honey. This study aims to generate a dataset that uncovers the presence of these plant/pollen species and their relative abundance in the honey of A. dorsata and H. itama. The information gathered from this study can be used to determine the geographical and botanical origin and authenticity of the honey produced by these two species.

RESULTS

Sequence data were obtained for both A. dorsata and H. itama. The raw sequence data for A. dorsata was 5 Mb, which was assembled into 5 contigs with a size of 6,098,728 bp, an N50 of 15,534, and a GC average of 57.42. Similarly, the raw sequence data for H. itama was 6.3 Mb, which was assembled into 11 contigs with a size of 7,642,048 bp, an N50 of 17,180, and a GC average of 55.38. In the honey sample of A. dorsata, we identified five different plant/pollen species, with only one of the five species exhibiting a relative abundance of less than 1%. For H. itama, we identified seven different plant/pollen species, with only three of the species exhibiting a relative abundance of less than 1%. All of the identified plant species were native to Peninsular Malaysia, especially the East Coast area of Terengganu.

DATA DESCRIPTION

Our data offers valuable insights into honey's geographical and botanical origin and authenticity. Metagenomic studies could help identify the plant species that honeybees forage and provide preliminary data for researchers studying the biological development of A. dorsata and H. itama. The identification of various flowers from the eDNA of honey that are known for their medicinal properties could aid in regional honey with accurate product origin labeling, which is crucial for guaranteeing product authenticity to consumers.

Potential values of formalin-fixed paraffin-embedded tissues for intratumoral microbiome analysis in breast cancer

Breast cancer (BC) tissues have been proved to harbor microorganisms, which could potentially contribute to oncogenesis. Formalin-fixed paraffin-embedded (FFPE) tissues are the most widespread clinical samples in BC research. To verify the potential of FFPE tissues in microbiological analysis, we analyzed the microbial communities of FFPE and fresh frozen (FF) tumor samples from 30 participants diagnosed with BC deploying 16S rRNA sequencing. The operational taxonomic units (OTUs) analysis showed that 78.55% of OTUs in FFPE samples were consistent with FF samples. The composition of core bacteria did not change much, and there is also no difference in alpha diversity between FFPE and FF (without unclassified bacteria). Taxonomic variation results show that Firmicutes and Bacteroidota phyla, and their major classes, maintained the same proportion under two preservation methods. In addition, the major class Gammaproteobacteria, as well as its dominant orders Burkholderiales and Pseudomonadales all showed no significant difference in paired analysis. Moreover, the Proteobacteria and Actinobacteriota phyla showed no significant difference between FFPE and FF samples after subtracting unclassified bacteria. Therefore, premised with the intrinsic tumor heterogeneity and unclassified bacteria, there are potential values of FFPE tissues for intratumoral microbiome analysis in breast cancer.

Mutational analysis of catalytic site domain of CCHFV L RNA segment

INTRODUCTION

Crimean-Congo haemorrhagic fever virus (CCHFV) has tripartite RNA genome and is endemic in various countries of Asia, Africa and Europe.

METHOD

The present study is focused on mutation profiling of CCHFV L segment and phylogenetic clustering of protein dataset into six CCHFV genotypes.

RESULTS

Phylogenetic tree rooted with NCBI reference sequence (YP_325663.1) indicated less divergence from genotype III and the sequences belonging to same genotypes have shown less divergence among each other. Mutation frequency at 729 mutated positions was calculated and 563, 49, 33, 46 and 38 amino acid positions were found to be mutated at mutation frequency intervals of 0-0.2, 0.21-0.4, 0.41-0.6, 0.61-0.8 and 0.81-1.0 respectively. Thirty-eight highly frequent mutations (0.81-1.0 interval) were found in all genotypes and mapping in L segment (encoded for RdRp) revealed four mutations (V2074I, I2134T/A, V2148A and Q2695H/R) in catalytic site domain and no mutation in OTU domain. Molecular dynamic simulation and in silico analysis showed that catalytic site domain displayed large deviation and fluctuation upon introduction of these point mutations.

CONCLUSION

Overall study provides strong evidence that OTU domain is highly conserved and less prone to mutation whereas point mutations recorded in catalytic domain have affected the stability of protein and were found to be persistent in the large population.

Plant deubiquitinases: from structure and activity to biological functions

This article attempts to provide comprehensive review of plant deubiquitinases, paying special attention to recent advances in their biochemical activities and biological functions. Proteins in eukaryotes are subjected to post-translational modifications, in which ubiquitination is regarded as a reversible process. Cellular deubiquitinases (DUBs) are a key component of the ubiquitin (Ub)-proteasome system responsible for cellular protein homeostasis. DUBs recycle Ub by hydrolyzing poly-Ub chains on target proteins, and maintain a balance of the cellular Ub pool. In addition, some DUBs prefer to cleave poly-Ub chains not linked through the conventional K48 residue, which often alter the substrate activity instead of its stability. In plants, all seven known DUB subfamilies have been identified, namely Ub-binding protease/Ub-specific protease (UBP/USP), Ub C-terminal hydrolase (UCH), Machado-Joseph domain-containing protease (MJD), ovarian-tumor domain-containing protease (OTU), zinc finger with UFM1-specific peptidase domain protease (ZUFSP), motif interacting with Ub-containing novel DUB family (MINDY), and JAB1/MPN/MOV34 protease (JAMM). This review focuses on recent advances in the structure, activity, and biological functions of plant DUBs, particularly in the model plant Arabidopsis.

Bacterial usurpation of the OTU deubiquitinase fold

The extensive cellular signalling events controlled by posttranslational ubiquitination are tightly regulated through the action of specialized proteases termed deubiquitinases. Among them, the OTU family of deubiquitinases can play very specialized roles in the regulation of discrete subtypes of ubiquitin signals that control specific cellular functions. To exert control over host cellular functions, some pathogenic bacteria have usurped the OTU deubiquitinase fold as a secreted virulence factor that interferes with ubiquitination inside infected cells. Herein, we provide a review of the function of bacterial OTU deubiquitinases during infection, the structural basis for their deubiquitinase activities and the bioinformatic approaches leading to their identification. Understanding bacterial OTU deubiquitinases holds the potential for discoveries not only in bacterial pathogenesis but in eukaryotic biology as well.

The effect of sheep grazing abandonment on soil bacterial communities in productive mountain grasslands

Livestock grazing abandonment entails important shifts on the overall ecosystem function, but the effects of this land-use change on specific bacterial taxa remain poorly understood in mountain grasslands. Moreover, we currently lack knowledge about the feedbacks between changes in ecosystem functions affected by livestock abandonment in mountain grasslands and the soil bacterial communities. Here, we evaluated the behavior of bacterial communities' structure and composition at taxa level as a function of short (1-year) and long-term (15-years) grazing abandonment in a mountain grassland. We also linked the observed responses in the bacterial communities to changes in several ecosystem functions (i.e. primary production, plant species biodiversity, carbon stocks and soil fertility). The alpha diversity of the bacterial communities did not show a significant response as a consequence of grazing abandonment. However, we identified significant changes on the overall composition of soil bacterial communities between the long-term abandoned grassland areas and grazed or abandoned areas in the short term. We also evidenced a balance between the number of operational taxonomic units (OTUs) whose relative abundance is favored by livestock grazing (19.51 %) and those with higher relative abundances in long-term grazing exclusion areas (20.23 %) that could behave as indicators of grazing abandonment. Structural Equation Modeling analyses proved that several bacterial taxa associated with relevant ecosystem functions, such as Rhodospirillales order within Alphaproteobacteria phylum, featured significant changes in their relative abundance between grazing treatments. The direct and indirect effects of grazing exclusion on woody species encroachment and soil organic carbon were strongly linked to the changes in the abundance of bacterial taxa indicators. The assessment of the bacterial community response to livestock abandonment in mountain grasslands may thus provide early warning signs before subtle changes in ecosystem functions occur.

Response of human gut microbiota under simulated microgravity

The present study was conducted to investigate the influence of microgravity on human gut microbiota using 16S rRNA gene sequencing in vitro. The diamagnetic material magnetic levitation method was used to simulate weightless environment. The human gut microbiota was cultured under two different conditions: normal gravity (1 g), and simulated microgravity (0 g), which showed that both the richness (P = 0.04) and diversity (P = 0.0002) of human gut microbiota were significantly altered. As compared to the normal gravity, the simulated microgravity significantly reduced abundance of bacteria related to anti-inflammatory effects, such as Subdoligranulum, Faecalibacterium, Fusicatenibacter, Butyricicoccus, and Lachnospiraceae-NK4A136-0 group (P < 0.05), while significantly increased that of Alistipes and Eubacterium-Ventriosum-group (P < 0.05). Moreover, the Spearman's correlation analysis showed that there were more significantly correlated species (|r|≥ 0.5, P < 0.05) in normal gravity than that in the simulated microgravity. KEGG pathway analysis revealed that the microgravity significantly (P < 0.05) affected the metabolism of gut microbiota, such as the metabolism of pyrimidine, fatty acids, glyoxylate and dicarboxylate, peptidoglycan biosynthesis, and carbon fixation in photosynthetic organisms. These results suggested that the exposure to a microgravity environment might induce disturbances in human gut microbiota. KEY POINTS: • Using 16sRNA gene sequencing technology, it was found that magnetic levitation-simulated microgravity had varying degrees of influence on the abundance, diversity, species correlation, and KEGG pathways of human intestinal microbes. • Digital PCR can improve the detection rate of microorganisms with low abundance.

Effects of dietary fiber on intestinal microbiota in geese evaluated by 16SrRNA gene sequencing

AIMS

The purpose of the research is to study the effects of different fiber types and sources on the intestinal flora of geese.

METHODS AND RESULTS

A total of 48 geese (males 35 days old) were divided into 4 groups, each of which included 3 replicates of 4 geese. Groups 1 to 4 were fed a diet containing 5% corn stover Crude fiber (CF, the LJ group), 8% corn stover CF (the HJ group), 5% alfalfa CF (the LM group), or 8% alfalfa CF (the HM group) respectively. After 42 days of feeding, the intestinal flora of each group was determined by 16SrRNA gene sequencing. In the duodenum, the diet supplemented with corn stover meal increased the relative abundance of Proteobacteria, Actinobacteria and Euryarchaeota, and with alfalfa as fiber source increased the relative abundance of Firmicutes, Bacteroidetes, Tenericutes and Chloroflexi. In the jejunum, Bacteroidetes, Actinobacteria, Planctomycetes, Acidobacteria, Tenericutes and Spirochetes were significantly more abundant in the corn stover group. There were no significant differences among the results for the other two fiber sources, which were fibre level in their influence where in ileum. Firmicutes, Deferribacteres and Euryarchaeota with corn stover as fiber source in the cecum were higher than the alfalfa group.

CONCLUSIONS

Different fiber sources have significant effects on goose gut microbiota. There were same flora has the same trend of change in different intestinal segments. The relative fiber source in the ileum makes the gut microbiota more sensitive to differences in fiber levels..

SIGNIFICANCE AND IMPACT OF THE STUDY

This study proved that the dietary fibre affects the intestinal flora. At the same time, different groups of dietary fibre may be used to provide the possibility to study functional roles of specific bacteria in host physiology.

Hawaiian Fungal Amplicon Sequence Variants Reveal Otherwise Hidden Biogeography

To study biogeography and other ecological patterns of microorganisms, including fungi, scientists have been using operational taxonomic units (OTUs) as representations of species or species hypotheses. However, when defined by 97% sequence similarity cutoff at an accepted barcode locus such as 16S in bacteria or ITS in fungi, these OTUs can obscure biogeographic patterns, mask taxonomic diversity, and hinder meta-analyses. Amplicon sequence variants (ASVs) have been proposed to alleviate all of these issues and have been shown to do so in bacteria. Analyzing ASVs is just emerging as a common practice among fungal studies, and it is unclear whether the benefits found in bacterial studies of using such an approach carryover to fungi. Here, we conducted a meta-analysis of Hawaiian fungi by analyzing ITS1 amplicon sequencing data as ASVs and exploring ecological patterns. These surveys spanned three island groups and five ecosystems combined into the first comprehensive Hawaiian Mycobiome ASV Database. Our results show that ASVs can be used to combine fungal ITS surveys, increase reproducibility, and maintain the broad ecological patterns observed with OTUs, including diversity orderings. Additionally, the ASVs that comprise some of the most common OTUs in our database reveals some island specialists, indicating that traditional OTU clustering can obscure important biogeographic patterns. We recommend that future fungal studies, especially those aimed at assessing biogeography, analyze ASVs rather than OTUs. We conclude that similar to bacterial studies, ASVs improve reproducibility and data sharing for fungal studies.

Substrate-assisted activation and selectivity of the bacterial RavD effector deubiquitinylase

Deubiquitinylases (DUBs) catalyze the peptide bond cleavage of specific ubiquitin linkages at distinct protein substrates. Pathogens from viruses and bacteria independently developed effector proteins with DUB activity to mimic host DUB functions and circumvent immune responses. The effector protein RavD from Legionella pneumophila cleaves linear ubiquitin chains with an exclusive methionine-1 selectivity. It thus performs as a functional analogue of the human DUB OTULIN, which achieves its selectivity only via a specialized proximal ubiquitin S1' binding site as well as a substrate-assisted activation of the catalytic triad. An analysis of the crystal structures of bacterial RavD in its free and di-ubiquitin-bound forms, in order to rationalize the structural basis for its selectivity and activation mechanism, is not fully conclusive. As these ambiguities might arise from the introduced double mutation of the di-ubiquitin substrate in the RavD-di-ubiquitin complex crystal structure, biomolecular modeling, and molecular dynamics sampling (1-2 μs for each system of RavD and OTULIN) were employed to reconstitute the physiological RavD-di-ubiquitin complex. The simulations show that the distal S1 ubiquitin binding sites of RavD and OTULIN are similar in terms of interface area, composition, and ubiquitin binding affinity. The proximal S1' site of RavD, in contrast, is significantly smaller and ubiquitin binding is weaker and more flexible than in OTULIN. Upon substrate access, the residues of the catalytic triad of RavD show a reduction of flexibility and a conformational transition toward a catalytically active state. Thus, the enzymatic activation of RavD is presumably also substrate-assisted and a clear rationale for the common M1-substrate selectivity.

Comparative Analysis of the Cultured and Total Bacterial Community in the Wheat Rhizosphere Microbiome Using Culture-Dependent and Culture-Independent Approaches

Rhizosphere and root-associated bacteria are key components of crop production and sustainable agriculture. However, utilization of these beneficial bacteria is often limited by conventional culture techniques because a majority of soil microorganisms cannot be cultured using standard laboratory media. Therefore, the purpose of this study was to improve culturability and investigate the diversity of the bacterial communities from the wheat rhizosphere microbiome collected from three locations in Egypt with contrasting soil characteristics by using metagenomic analysis and improved culture-based methods. The improved strategies of the culture-dependent approach included replacing the agar in the medium with gellan gums and modifying its preparation by autoclaving the phosphate and gelling agents separately. Compared to the total operational taxonomic units (OTUs) observed from the metagenomic data sets derived from the three analyzed soils, 1.86 to 2.52% of the bacteria were recovered using the modified cultivation strategies, whereas less than 1% were obtained employing the standard cultivation protocols. Twenty-one percent of the cultivable isolates exhibited multiple plant growth-promoting (PGP) properties, including P solubilization activity and siderophore production. From the metagenomic analysis, the most abundant phyla were Proteobacteria, Actinobacteria, Chloroflexi, Bacteroidetes, and Firmicutes. Moreover, the relative abundance of the specific bacterial taxa was correlated with the soil characteristics, demonstrating the effect of the soil in modulating the plant rhizosphere microbiome.

IMPORTANCE Bacteria colonizing the rhizosphere, a narrow zone of soil surrounding the root system, are known to have beneficial effects in improving the growth and stress tolerance of plants. However, most bacteria in natural environments, especially those in rhizosphere soils, are recalcitrant to cultivation using traditional techniques, and thus their roles in soil health and plant growth remain unexplored. Hence, investigating new culture media and culture conditions to bring “not-yet-cultured” species into cultivation and to identify new functions is still an important task for all microbiologists. To this end, we describe improved cultivation protocols that increase the number and diversity of cultured bacteria from the rhizosphere of wheat plants. Using such approaches will lead to new insights into culturing more beneficial bacteria that live in the plant rhizosphere, in so doing creating greater opportunities not only for field application but also for promoting sustainability.

Unraveling City-Specific Microbial Signatures and Identifying Sample Origins for the Data From CAMDA 2020 Metagenomic Geolocation Challenge

The composition of microbial communities has been known to be location-specific. Investigating the microbial composition across different cities enables us to unravel city-specific microbial signatures and further predict the origin of unknown samples. As part of the CAMDA 2020 Metagenomic Geolocation Challenge, MetaSUB provided the whole genome shotgun (WGS) metagenomics data from samples across 28 cities along with non-microbial city data for 23 of these cities. In our solution to this challenge, we implemented feature selection, normalization, clustering and three methods of machine learning to classify the cities based on their microbial compositions. Of the three methods, multilayer perceptron obtained the best performance with an error rate of 19.60% based on whether the correct city received the highest or second highest number of votes for the test data contained in the main dataset. We then trained the model to predict the origins of samples from the mystery dataset by including these samples with the additional group label of "mystery." The mystery dataset compromised of samples collected from a subset of the cities in the main dataset as well as samples collected from new cities. For samples from cities that belonged to the main dataset, error rates ranged from 18.18 to 72.7%. For samples from new cities that did not belong to the main dataset, 57.7% of the test samples could be correctly labeled as "mystery" samples. Furthermore, we also predicted some of the non-microbial features for the mystery samples from the cities that did not belong to main dataset to draw inferences and narrow the range of the possible sample origins using a multi-output multilayer perceptron algorithm.

Amplicon Sequence Variants Artificially Split Bacterial Genomes into Separate Clusters

Amplicon sequencing variants (ASVs) have been proposed as an alternative to operational taxonomic units (OTUs) for analyzing microbial communities. ASVs have grown in popularity, in part because of a desire to reflect a more refined level of taxonomy since they do not cluster sequences based on a distance-based threshold. However, ASVs and the use of overly narrow thresholds to identify OTUs increase the risk of splitting a single genome into separate clusters. To assess this risk, I analyzed the intragenomic variation of 16S rRNA genes from the bacterial genomes represented in an rrn copy number database, which contained 20,427 genomes from 5,972 species. As the number of copies of the 16S rRNA gene increased in a genome, the number of ASVs also increased. There was an average of 0.58 ASVs per copy of the 16S rRNA gene for full-length 16S rRNA genes. It was necessary to use a distance threshold of 5.25% to cluster full-length ASVs from the same genome into a single OTU with 95% confidence for genomes with 7 copies of the 16S rRNA, such as Escherichia coli. This research highlights the risk of splitting a single bacterial genome into separate clusters when ASVs are used to analyze 16S rRNA gene sequence data. Although there is also a risk of clustering ASVs from different species into the same OTU when using broad distance thresholds, these risks are of less concern than artificially splitting a genome into separate ASVs and OTUs.

IMPORTANCE 16S rRNA gene sequencing has engendered significant interest in studying microbial communities. There has been tension between trying to classify 16S rRNA gene sequences to increasingly lower taxonomic levels and the reality that those levels were defined using more sequence and physiological information than is available from a fragment of the 16S rRNA gene. Furthermore, the naming of bacterial taxa reflects the biases of those who name them. One motivation for the recent push to adopt ASVs in place of OTUs in microbial community analyses is to allow researchers to perform their analyses at the finest possible level that reflects species-level taxonomy. The current research is significant because it quantifies the risk of artificially splitting bacterial genomes into separate clusters. Far from providing a better representation of bacterial taxonomy and biology, the ASV approach can lead to conflicting inferences about the ecology of different ASVs from the same genome.

Microbiome Preprocessing Machine Learning Pipeline

Background

16S sequencing results are often used for Machine Learning (ML) tasks. 16S gene sequences are represented as feature counts, which are associated with taxonomic representation. Raw feature counts may not be the optimal representation for ML.

Methods

We checked multiple preprocessing steps and tested the optimal combination for 16S sequencing-based classification tasks. We computed the contribution of each step to the accuracy as measured by the Area Under Curve (AUC) of the classification.

Results

We show that the log of the feature counts is much more informative than the relative counts. We further show that merging features associated with the same taxonomy at a given level, through a dimension reduction step for each group of bacteria improves the AUC. Finally, we show that z-scoring has a very limited effect on the results.

Conclusions

The prepossessing of microbiome 16S data is crucial for optimal microbiome based Machine Learning. These preprocessing steps are integrated into the MIPMLP - Microbiome Preprocessing Machine Learning Pipeline, which is available as a stand-alone version at: https://github.com/louzounlab/microbiome/tree/master/Preprocess or as a service at http://mip-mlp.math.biu.ac.il/Home Both contain the code, and standard test sets.

General Unified Microbiome Profiling Pipeline (GUMPP) for Large Scale, Streamlined and Reproducible Analysis of Bacterial 16S rRNA Data to Predicted Microbial Metagenomes, Enzymatic Reactions and Metabolic Pathways

General Unified Microbiome Profiling Pipeline (GUMPP) was developed for large scale, streamlined and reproducible analysis of bacterial 16S rRNA data and prediction of microbial metagenomes, enzymatic reactions and metabolic pathways from amplicon data. GUMPP workflow introduces reproducible data analyses at each of the three levels of resolution (genus; operational taxonomic units (OTUs); amplicon sequence variants (ASVs)). The ability to support reproducible analyses enables production of datasets that ultimately identify the biochemical pathways characteristic of disease pathology. These datasets coupled to biostatistics and mathematical approaches of machine learning can play a significant role in extraction of truly significant and meaningful information from a wide set of 16S rRNA datasets. The adoption of GUMPP in the gut-microbiota related research enables focusing on the generation of novel biomarkers that can lead to the development of mechanistic hypotheses applicable to the development of novel therapies in personalized medicine.

16S rRNA gene profiling of rhizospheric microbial community of Eichhornia crassipes

The rhizosphere of a plant is an important interface for the plant-microbe interaction that plays a significant role in the uptake and removal of heavy metal from contaminated sites. Eichhornia crassipes is a free-floating macrophyte and a well-known metal hyperaccumulator. It is a promising plant, which harbors a diverse microbial community in its rhizosphere. Therefore it is hypothesized that it can be a good habitat for microorganisms that supports plant growth and increases its phytoremediation potential. The rhizospheric DNA was extracted from the procured plant samples. The library was prepared and sequenced using the Illumina platform. 16S rRNA data from the Next Generation Sequencing (NGS) platform was analyzed using the QIIME software package. Alpha diversity was estimated from statistical indices i.e. Shannon index, Chao1 index, and observed species. The rarefaction plots, rank abundance curve, krona graph, and heat map were generated to study the rhizospheric community in detail. Metagenome consisted of 225,408 flash reads, 185,008 non-chimeric sequences with 17,578 Operational Taxonomic Units (OTU's), and 4622 OTU's without singletons. The data of present study are available at NCBI Bioproject (PRJNA631882). The taxonomic analysis of OTU's showed that the sequences belonged to major Phyla revealing the dominance of Proteobacteria, Bacteroidetes, Cyanobacteria, and Verrucomicrobia. The most abundant Genera in the sampled rhizosphere recorded were Thiothrix and Flavobacterium.

Marine Group-II archaea dominate particle-attached as well as free-living archaeal assemblages in the surface waters of Kongsfjorden, Svalbard, Arctic Ocean

Marine archaea are a significant component of the global oceanic ecosystems, including the polar oceans. However, only a few attempts have been made to study archaea in the high Arctic fjords. Given the importance of Archaea in carbon and nitrogen cycling, it is imperative to explore their diversity and community composition in the high Arctic fjords, such as Kongsfjorden (Svalbard). In the present study, we evaluated archaeal diversity and community composition in the size-fractionated microbial population, viz-a-viz free-living (FL; 0.2-3 μm) and particle-attached (PA; > 3 μm) using archaeal V3-V4 16S rRNA gene amplicon sequencing. Our results indicate that the overall archaeal community in the surface water of Kongsfjorden was dominated by the members of the marine group-II (MGII) archaea, followed by the MGI group members, including Nitrosopumilaceae and Nitrososphaeraceae. Although a clear niche partitioning between PA and FL archaeal communities was not observed, 2 OTUs among 682 OTUs, and 3 ASVs out of 1932 ASVs were differentially abundant among the fractions. OTU001/ASV0002, classified as MGIIa, was differentially abundant in the PA fraction. OTU006/ASV0006/ASV0010 affiliated with MGIIb were differentially abundant in the FL fraction. Particulate organic nitrogen and C:N ratio were the most significant variables (P < 0.05) explaining the observed variation in the FL and PA archaeal communities, respectively. These results indicate an exchange between archaeal communities or a generalist lifestyle switching between FL and PA fractions. Besides, the particles' elemental composition (carbon and nitrogen) seems to play an essential role in shaping the PA archaeal communities in the surface waters of Kongsfjorden.

Unraveling city-specific signature and identifying sample origin locations for the data from CAMDA MetaSUB challenge

BACKGROUND

Composition of microbial communities can be location-specific, and the different abundance of taxon within location could help us to unravel city-specific signature and predict the sample origin locations accurately. In this study, the whole genome shotgun (WGS) metagenomics data from samples across 16 cities around the world and samples from another 8 cities were provided as the main and mystery datasets respectively as the part of the CAMDA 2019 MetaSUB "Forensic Challenge". The feature selecting, normalization, three methods of machine learning, PCoA (Principal Coordinates Analysis) and ANCOM (Analysis of composition of microbiomes) were conducted for both the main and mystery datasets.

RESULTS

Features selecting, combined with the machines learning methods, revealed that the combination of the common features was effective for predicting the origin of the samples. The average error rates of 11.93 and 30.37% of three machine learning methods were obtained for main and mystery datasets respectively. Using the samples from main dataset to predict the labels of samples from mystery dataset, nearly 89.98% of the test samples could be correctly labeled as "mystery" samples. PCoA showed that nearly 60% of the total variability of the data could be explained by the first two PCoA axes. Although many cities overlapped, the separation of some cities was found in PCoA. The results of ANCOM, combined with importance score from the Random Forest, indicated that the common "family", "order" of the main-dataset and the common "order" of the mystery dataset provided the most efficient information for prediction respectively.

CONCLUSIONS

The results of the classification suggested that the composition of the microbiomes was distinctive across the cities, which could be used to identify the sample origins. This was also supported by the results from ANCOM and importance score from the RF. In addition, the accuracy of the prediction could be improved by more samples and better sequencing depth.

Alterations in Intestinal Microbiota of Children With Celiac Disease at the Time of Diagnosis and on a Gluten-free Diet

BACKGROUND AND AIMS

It is not clear whether alterations in the intestinal microbiota of children with celiac disease (CD) cause the disease or are a result of disease and/or its treatment with a gluten-free diet (GFD).

METHODS

We obtained 167 fecal samples from 141 children (20 with new-onset CD, 45 treated with a GFD, 57 healthy children, and 19 unaffected siblings of children with CD) in Glasgow, Scotland. Samples were analyzed by 16S ribosomal RNA sequencing, and diet-related metabolites were measured by gas chromatography. We obtained fecal samples from 13 children with new-onset CD after 6 and 12 months on a GFD. Relationships between microbiota with diet composition, gastrointestinal function, and biomarkers of GFD compliance were explored.

RESULTS

Microbiota α diversity did not differ among groups. Microbial dysbiosis was not observed in children with new-onset CD. In contrast, 2.8% (Bray-Curtis dissimilarity index, P = .025) and 2.5% (UniFrac distances, P = .027) of the variation in microbiota composition could be explained by the GFD. Between 3% and 5% of all taxa differed among all group comparisons. Eleven distinctive operational taxonomic units composed a microbe signature specific to CD with high diagnostic probability. Most operational taxonomic units that differed between patients on a GFD with new-onset CD vs healthy children were associated with nutrient and food group intake (from 75% to 94%) and with biomarkers of gluten ingestion. Fecal levels of butyrate and ammonia decreased during the GFD.

CONCLUSIONS

Although several alterations in the intestinal microbiota of children with established CD appear to be effects of a GFD, specific bacteria were found to be distinct biomarkers of CD. Studies are needed to determine whether these bacteria contribute to pathogenesis of CD.

Cosmopolitan Distribution of Endozoicomonas-Like Organisms and Other Intracellular Microcolonies of Bacteria Causing Infection in Marine Mollusks

Intracellular microcolonies of bacteria (IMC), in some cases developing large extracellular cysts (bacterial aggregates), infecting primarily gill and digestive gland, have been historically reported in a wide diversity of economically important mollusk species worldwide, sometimes associated with severe lesions and mass mortality events. As an effort to characterize those organisms, traditionally named as Rickettsia or Chlamydia-like organisms, 1950 specimens comprising 22 mollusk species were collected over 10 countries and after histology examination, a selection of 99 samples involving 20 species were subjected to 16S rRNA gene amplicon sequencing. Phylogenetic analysis showed Endozoicomonadaceae sequences in all the mollusk species analyzed. Geographical differences in the distribution of Operational Taxonomic Units (OTUs) and a particular OTU associated with pathology in king scallop (OTU_2) were observed. The presence of Endozoicomonadaceae sequences in the IMC was visually confirmed by in situ hybridization (ISH) in eight selected samples. Sequencing data also indicated other symbiotic bacteria. Subsequent phylogenetic analysis of those OTUs revealed a novel microbial diversity associated with molluskan IMC infection distributed among different taxa, including the phylum Spirochetes, the families Anaplasmataceae and Simkaniaceae, the genera Mycoplasma and Francisella, and sulfur-oxidizing endosymbionts. Sequences like Francisella halioticida/philomiragia and Candidatus Brownia rhizoecola were also obtained, however, in the absence of ISH studies, the association between those organisms and the IMCs were not confirmed. The sequences identified in this study will allow for further molecular characterization of the microbial community associated with IMC infection in marine mollusks and their correlation with severity of the lesions to clarify their role as endosymbionts, commensals or true pathogens.

Daring to be differential: metabarcoding analysis of soil and plant-related microbial communities using amplicon sequence variants and operational taxonomical units

Background

Microorganisms are not only indispensable to ecosystem functioning, they are also keystones for emerging technologies. In the last 15 years, the number of studies on environmental microbial communities has increased exponentially due to advances in sequencing technologies, but the large amount of data generated remains difficult to analyze and interpret. Recently, metabarcoding analysis has shifted from clustering reads using Operational Taxonomical Units (OTUs) to Amplicon Sequence Variants (ASVs). Differences between these methods can seriously affect the biological interpretation of metabarcoding data, especially in ecosystems with high microbial diversity, as the methods are benchmarked based on low diversity datasets.

Results

In this work we have thoroughly examined the differences in community diversity, structure, and complexity between the OTU and ASV methods. We have examined culture-based mock and simulated datasets as well as soil- and plant-associated bacterial and fungal environmental communities. Four key findings were revealed. First, analysis of microbial datasets at family level guaranteed both consistency and adequate coverage when using either method. Second, the performance of both methods used are related to community diversity and sample sequencing depth. Third, differences in the method used affected sample diversity and number of detected differentially abundant families upon treatment; this may lead researchers to draw different biological conclusions. Fourth, the observed differences can mostly be attributed to low abundant (relative abundance < 0.1%) families, thus extra care is recommended when studying rare species using metabarcoding. The ASV method used outperformed the adopted OTU method concerning community diversity, especially for fungus-related sequences, but only when the sequencing depth was sufficient to capture the community complexity.

Conclusions

Investigation of metabarcoding data should be done with care. Correct biological interpretation depends on several factors, including in-depth sequencing of the samples, choice of the most appropriate filtering strategy for the specific research goal, and use of family level for data clustering.

Metatax: Metataxonomics with a Compi-Based Pipeline for Precision Medicine

The human body immune system, metabolism and homeostasis are affected by microbes. Dysbiosis occurs when the homeostatic equilibrium is disrupted due to an alteration in the normal microbiota of the intestine. Dysbiosis can cause cancer, and also affect a patient's ability to respond to treatment. Metataxonomics seeks to identify the bacteria present in a biological sample, based on the sequencing of the 16S rRNA genetic marker. Precision medicine attempts to find relationships between the microbiota and the risk of acquiring cancer, and design new therapies targeting bacteria. Flexible and portable bioinformatic pipelines are necessary to be able to bring metataxonomics to the clinical field, which allow groups of biological samples to be classified according to their diversity in the microbiota. With this aim we implemented Metatax, a new pipeline to analyze biological samples based on 16S rRNA gene sequencing. The results obtained with our pipeline should complement those obtained by sequencing a patient's DNA and RNA, in addition to clinical data, to improve knowledge of the possible reasons for a disease or a worse response to treatment.

Uncovering Effects from the Structure of Metabarcode Sequences for Metagenetic and Microbiome Analysis

The advent of next-generation sequencing has allowed for higher-throughput determination of which species live within a specific location. Here we establish that three analysis methods for estimating diversity within samples—namely, Operational Taxonomic Units; the newer Amplicon Sequence Variants; and a method commonly found in sequence analysis, minhash—are affected by various properties of these sequence data. Using simulations we show that the presence of Single Nucleotide Polymorphisms and the depth of coverage from each species affect the correlations between these approaches. Through this analysis, we provide insights which would affect the decisions on the application of each method. Specifically, the presence of sequence read errors and variability in sequence read coverage deferentially affects these processing methods.

The impact of antibiotic exposure in water and zebrafish gut microbiomes: A 16S rRNA gene-based metagenomic analysis

In order to supply human demand for food, the aquaculture industry has been growing fast in the last years, being fish usually cultivated in overcrowded conditions. Hence, to prevent the rapidly disease spreading, antibiotics may be applied to both sick and healthy animals. Due to its broad spectrum, oxytetracycline (OTC) is one of the most used antibiotics in food-production. Yet, although useful to prevent infections, antibiotics may reshape aquatic animals' microbiome, disturbing hosts' welfare. However, the impact of this exposure to the organism microbiome and its surrounding environment is poorly understood. Then, the objective of this study was to analyze in detail the long-term effect of OTC in both zebrafish gut and water microbiomes. Zebrafish adults were exposed, via water, for two months to three concentrations of OTC (0, 10 and 10000 μg/L). Total DNA was extracted from gut and water samples and the V3-V4 region of the bacterial 16 S rRNA gene was sequenced using Illumina technology. Results of alpha and beta-diversity analyses revealed that long-term exposure to OTC impacted both zebrafish gut and water microbiomes. In water samples, effects were observed even at the lowest (10 μg/L) OTC concentration tested resulting in an increase in Deltaproteobacteria, namely the Myxococcales and Bdellovibrionales orders. On the other hand, effects on zebrafish gut were only observed at the highest concentration with the selection of Alphaproteobacteria and Actinobacteria classes. Although these classes are common in fish gut, the increase of Actinobacteria may represent a health problem since some genera like Gordonia are linked to some human infection disease. Nevertheless, in both gut and water, it was observed a decrease in Gamaproteobacteria, probably due to OTC mode of action. In silico functional metagenomic analysis revealed that OTC exposure selected general detoxification mechanisms. In addition, the abundance of functional genes involved in Quorum Sensing (QS) increased under OTC exposure suggesting that QS may help bacteria to survive OTC stress. Thus, future studies should consider post-exposure scenarios for a deeper analysis of the water and zebrafish gut resistome, since bacteria may react differently after exposure ceased.

Phytovirome Analysis of Wild Plant Populations: Comparison of Double-Stranded RNA and Virion-Associated Nucleic Acid Metagenomic Approaches

Metagenomic studies have indicated that the diversity of plant viruses was until recently far underestimated. As important components of ecosystems, there is a need to explore the diversity and richness of the viruses associated with plant populations and to understand the drivers shaping their diversity in space and time. Two viral sequence enrichment approaches, double-stranded RNA (dsRNA) and virion-associated nucleic acids (VANA), have been used and compared here for the description of the virome of complex plant pools representative of the most prevalent plant species in unmanaged and cultivated ecosystems. A novel bioinformatics strategy was used to assess viral richness not only at the family level but also by determining operational taxonomic units (OTU) following the clustering of conserved viral domains. A large viral diversity dominated by novel dsRNA viruses was detected in all sites, while a large between-site variability limited the ability to draw a clear conclusion on the impact of cultivation. A trend for a higher diversity of dsRNA viruses was nevertheless detected in unmanaged sites (118 versus 77 unique OTUs). The dsRNA-based approach consistently revealed a broader and more comprehensive diversity for RNA viruses than the VANA approach, whatever the assessment criterion. In addition, dissimilarity analyses indicated both approaches to be largely reproducible but not necessarily convergent. These findings illustrate features of phytoviromes in various ecosystems and a novel strategy for precise virus richness estimation. These results allow us to reason methodological choices in phytovirome studies and likely in other virome studies where RNA viruses are the focal taxa.IMPORTANCE There are today significant knowledge gaps on phytovirus populations and on the drivers impacting them but also on the comparative performance-methodological approaches for their study. We used and compared two viral sequence enrichment approaches, double-stranded RNAs (dsRNA) and virion-associated nucleic acids (VANA), for phytovirome description in complex pools representative of the most prevalent plant species in unmanaged and cultivated ecosystems. Viral richness was assessed by determining operational taxonomic units (OTU) following the clustering of conserved viral domains. There is some limited evidence of an impact of cultivation on viral populations. These results provide data allowing us to reason the methodological choices in virome studies. For researchers primarily interested in RNA viruses, the dsRNA approach is recommended because it consistently provided a more comprehensive description of the analyzed phytoviromes, but it understandably underrepresented DNA viruses and bacteriophages.

Identification of city specific important bacterial signature for the MetaSUB CAMDA challenge microbiome data

Background

Metagenomic data of whole genome sequences (WGS) from samples across several cities around the globe may unravel city specific signatures of microbes. Illumina MiSeq sequencing data was provided from 12 cities in 7 different countries as part of the 2018 CAMDA “MetaSUB Forensic Challenge”, including also samples from three mystery sets. We used appropriate machine learning techniques on this massive dataset to effectively identify the geographical provenance of “mystery” samples. Additionally, we pursued compositional data analysis to develop accurate inferential techniques for such microbiome data. It is expected that this current data, which is of higher quality and higher sequence depth compared to the CAMDA 2017 MetaSUB challenge data, along with improved analytical techniques would yield many more interesting, robust and useful results that can be beneficial for forensic analysis.

Results

A preliminary quality screening of the data revealed a much better dataset in terms of Phred quality score (hereafter Phred score), and larger paired-end MiSeq reads, and a more balanced experimental design, though still not equal number of samples across cities. PCA (Principal Component Analysis) analysis showed interesting clusters of samples and a large amount of the variability in the data was explained by the first three components (~ 70%). The classification analysis proved to be consistent across both the testing mystery sets with a similar percentage of the samples correctly predicted (up to 90%). The analysis of the relative abundance of bacterial “species” showed that some “species” are specific to some regions and can play important roles for predictions. These results were also corroborated by the variable importance given to the “species” during the internal cross validation (CV) run with Random Forest (RF).

Conclusions

The unsupervised analysis (PCA and two-way heatmaps) of the log2-cpm normalized data and relative abundance differential analysis seemed to suggest that the bacterial signature of common “species” was distinctive across the cities; which was also supported by the variable importance results. The prediction of the city for mystery sets 1 and 3 showed convincing results with high classification accuracy/consistency. The focus of this work on the current MetaSUB data and the analytical tools utilized here can be of great help in forensic, metagenomics, and other sciences to predict city of provenance of metagenomic samples, as well as in other related fields. Additionally, the pairwise analysis of relative abundance showed that the approach provided consistent and comparable “species” when compared with the classification importance variables.

Reviewers

This article was reviewed by Manuela Oliveira, Dimitar Vassilev, and Patrick Lee.

Deciphering the Composition and Functional Profile of the Microbial Communities in Chinese Moutai Liquor Starters

Moutai is a world-famous traditional Chinese liquor with complex taste and aroma, which are considered to be strongly influenced by the quality of fermentation starters (Daqu). However, the role of microbial communities in the starters has not been fully understood. In this study, we revealed the microbial composition of 185 Moutai starter samples, covering three different types of starters across immature and mature phases, and functional gene composition of mature starter microbiome. Our results showed that microbial composition patterns of immature starters varied, but they eventually were similar and steady when they became mature starters, after half-year storage and subsequent mixing. To help identify two types of immature starters, we selected seven operational taxonomic unit (OTU) markers by leave-one-out cross validation (LOOCV) and an OTU classified as Saccharopolyspora was the most decisive one. For mature starters, we identified a total of 16 core OTUs, one of which annotated as Bacillus was found positively associated with saccharifying power. We also identified the functional gene and microbial composition in starch and cellulose hydrolysis pathways. Microbes with higher abundances of alpha-glucosidase, alpha-amylase, and glucoamylase probably contributed to high saccharifying power. Overall, this study reveals the features of Moutai starter microbial communities in different phases and improves understanding of the relationships between microbiota and functional properties of the starters.

Metagenomic analysis of tarball-associated bacteria from Goa, India

The beaches of Goa state in India are frequently polluted with tarballs, specifically during pre-monsoon and monsoon seasons. Tarballs contain hydrocarbons, including polycyclic aromatic hydrocarbons, which pose significant environmental risks. Microbes associated with tarballs reportedly possess capabilities to degrade toxic hydrocarbons present in tarballs. In this study, bacterial diversity associated with tarballs from Vagator and Morjim beaches of north Goa was analysed based on V3-V4 regions of 16S rRNA gene sequenced using Illumina Miseq Platform. The Proteobacterial members were dominant in both Vagator (≥85.5%) and Morjim (≥94.0%) samples. Many of the identified taxa have been previously reported as hydrocarbon degraders (e.g. Halomonas, Marinobacter) or possible human pathogens (e.g. Acinetobacter, Klebsiella, Rhodococcus, Staphylococcus, Vibrio). This is the first study reported on a metagenomic analysis of bacteria associated with tarballs from Goa.

Desiccation events change the microbial response to gradients of wastewater effluent pollution

While wastewater treatment plant (WWTP) effluents have become increasingly recognized as a stressor for receiving rivers, their effects on river microbial communities remain elusive. Moreover, global change is increasing the frequency and duration of desiccation events in river networks, and we ignore how desiccation might influence the response of microbial communities to WWTP effluents. In this study, we evaluated the interaction between desiccation events and WWTP effluents under different dilution capacities. Specifically, we used artificial streams in a replicated regressional design, exposing first a section of the streams to a 7-day desiccation period and then the full stream to different levels of a realistic WWTP effluent dilution, from 0% to 100% of WWTP effluent proportion of the total stream flow. The microbial community response was assessed by means of high-throughput sequencing of 16S rRNA gene amplicons and quantitative PCR targeting ecologically-relevant microbial groups. Threshold Indicator Taxa Analysis (TITAN) was used, together with model fitting, to determine community thresholds and potential indicator taxa. Results show significant interactions between WWTP effluents and desiccation, particularly when sediment type is considered. Indicator taxa included members of Proteobacteria, Actinobacteria and Cyanobacteria, with abrupt changes in community structure at WWTP effluent proportion of the total flow above 50%, which is related to nutrient levels ranging 4.6-5.2 mg N-NO₃^-L^-1, 0.21-0.32 mg P-PO₄^3-L^-1 and 7.09-9.00 mg DOC L^-1. Our work indicates that situations where WWTP effluents account for >50% of the total river flow might risk of dramatic microbial community structure changes and should be avoided.

Variation in the skull morphometry of four taxonomic units of Thrichomys (Rodentia: Echimyidae), from different Neotropical biomes

The echimyid rodents of the genus Thrichomys vary considerably in their behavior and feeding ecology, reflecting their occurrence in environments as different as the Caatinga, Cerrado, Pantanal, and Chaco biomes. While the genus was originally classified as monospecific, a number of Thrichomys species have been recognized in recent decades, based on morphometric, cytogenetic, and molecular analyses. While Thrichomys is well studied, the variation found in its cranial morphology is poorly understood, given the taxonomic and ecological complexities of the genus. Using a geometric morphometric approach, we characterized the differences found in the cranial morphology of four Thrichomys taxonomic units, including three established species, Thrichomys apereoides, Thrichomys fosteri, and Thrichomys laurentius, and one operational taxonomic unit (OTU), Thrichomys aff. laurentius. No significant differences were found among these units in cranium size, but significant variation was found in skull shape. The Procrustes distances provided a quantification of the differences in the shape of the skull, with the largest distances being found between T. aff. laurentius and T. fosteri in the dorsal view, and between T. aff. laurentius and T. apereoides in the ventral view. A Discriminant Function Analysis (DFA) with cross-validation determined that the pairings with the highest correct classification were T. aff. laurentius vs. T. apereoides and T. aff. laurentius vs. T. fosteri, in both views. The principal variation in skull shape was found in the posterior region and the zygomatic arch, which may be related to differences in diet.

The impact of OTU sequence similarity threshold on diatom-based bioassessment: A case study of the rivers of Mayotte (France, Indian Ocean)

Extensive studies on the taxonomic resolution required for bioassessment purposes have determined that resolution above species level (genus, family) is sufficient for their use as indicators of relevant environmental pressures. The high-throughput sequencing (HTS) and meta-barcoding methods now used for bioassessment traditionally employ an arbitrary sequence similarity threshold (SST) around 95% or 97% to cluster sequences into operational taxonomic units, which is considered descriptive of species-level resolution. In this study, we analyzed the effect of the SST on the resulting diatom-based ecological quality index, which is based on OTU abundance distribution along a defined environmental gradient, ideally avoiding taxonomic assignments that could result in high rates of unclassified OTUs and biased final values. A total of 90 biofilm samples were collected in 2014 and 2015 from 51 stream sites on Mayotte Island in parallel with measures of relevant physical and chemical parameters. HTS sequencing was performed on the biofilms using the rbcL region as the genetic marker and diatom-specific primers. Hierarchical clustering was used to group sequences into OTUs using 20 experimental SST levels (80%-99%). An OTU-based quality index (IdxOTU) was developed based on a weighted average equation using the abundance profiles of the OTUs. The developed IdxOTU revealed significant correlations between the IdxOTU values and the reference pressure gradient, which reached maximal performance using an SST of 90% (well above species level delimitation). We observed an interesting and important trade-off with the power to discriminate between sampling sites and index stability that will greatly inform future applications of the index. Taken together, the results from this study detail a thoroughly optimized and validated approach to generating robust, reproducible, and complete indexes that will greatly facilitate effective and efficient environmental monitoring.

An Eimeria acervulina OTU protease exhibits linkage-specific deubiquitinase activity

Ubiquitination is an important post-translational modification process that regulates many cellular processes. Proteins can be modified at single or multiple lysine residues by a single ubiquitin protein or by ubiquitin oligomers. It is important to note that the type of ubiquitin chains determines the functional outcome of the modification. Ubiquitin or ubiquitin chains can be removed by deubiquitinases (DUBs). In our previous study, the Eimeria tenella ovarian tumour (Et-OTU) DUB was shown to regulate the telomerase activity of E. tenella and affect E. tenella proliferation. The amino acid sequences of Et-OTU (GenBank: XP_013229759.1) and Eimeria acervulina (E. acervulina) ovarian tumour (Ea-OTUD3) DUB (XP_013250378.1) are 74% identical. Although Et-OTU may regulate E. tenella telomerase activity, whether Ea-OTUD3 affects E. acervulina growth and reproduction remains unclear. We show here that Ea-OTUD3 belongs to the OTU domain class of cysteine protease deubiquitinating enzymes. Ea-OTUD3 is highly linkage-specific, cleaving K48 (Lys48)-, K63-, and K6-linked diubiquitin but not K29-, K33-, and K11-linked diubiquitin. The precise linkage preference of Ea-OTUD3 among these three nonlinear diubiquitin chains is K6 > K48 > K63. Recombinant Ea-OTUD3, but not its catalytic-site mutant Ea-OTUD3 (C247A), exhibits activity against diubiquitin. Ea-OTUD3 removes ubiquitin from the K48-, but to a lesser extent from the K63-linked ubiquitinated E. acervulina proteins of the modified target protein, thereby exhibiting the characteristics of deubiquitinase. This study reveals that the Ea-OTUD3 is a novel functional deubiquitinating enzyme. Furthermore, the Ea-OTUD3 protein may regulate the stability of some K48-linked ubiquitinated E. acervulina proteins.

A Modified Low-quantity RNA-Seq Method for Microbial Community and Diversity Analysis Using Small Subunit Ribosomal RNA

We propose a modified RNA-Seq method for small subunit ribosomal RNA (SSU rRNA)-based microbial community analysis that depends on the direct ligation of a 5' adaptor to RNA before reverse-transcription. The method requires only a low-input quantity of RNA (10-100 ng) and does not require a DNA removal step. Using this method, we could obtain more 16S rRNA sequences of the same regions (variable regions V1-V2) without the interference of DNA in order to analyze OTU (operational taxonomic unit)-based microbial communities and diversity. The generated SSU rRNA sequences are also suitable for the coverage evaluation for bacterial universal primer 8F (Escherichia coli position 8 to 27), which is commonly used for bacterial 16S rRNA gene amplification. The modified RNA-Seq method will be useful to determine potentially active microbial community structures and diversity for various environmental samples, and will also be useful for identifying novel microbial taxa.

Killing Effects of an Isolated Serratia marcescens KH-001 on Diaphorina citri via Lowering the Endosymbiont Numbers

Huanglongbing (HLB) is the most devastating citrus disease worldwide, and suppression of the Asian citrus psyllid (Diaphorina citri) is regarded as an effective method to inhibit the spread of HLB. In this study, we isolated a strain named as Serratia marcescens KH-001 from D. citri nymphs suffering from disease, and evaluated its killing effect on D. citri via toxicity test and effect on microbial community in D. citri using high-throughput sequencing. Our results indicated that S. marcescens KH-001 could effectively kill 83% of D. citri nymphs, while the fermentation products of S. marcescens KH-001 only killed 40% of the D. citrinymphs. High-throughput sequencing results indicated that the S. marcescens KH-001 increased the OTU numbers from 62.5 (PBS buffer) to 81.5, while significantly lowered the Shannon index compared with Escherichia coli DH5α (group E) (p < 0.05). OTU analysis showed that the S. marcescens KH-001 had significantly reduced the relative abundance of endosymbionts Wolbachia, Profftella, and Carsonella in group S compared with that in other groups (p < 0.05). Therefore, the direct killing effect of the fermentation products of S. marcescens KH-001 and the indirect effect via reducing the numbers of endosymbionts (Wolbachia, Profftella, and Carsonella) of D. citri endow S. marcescens KH-001 a sound killing effect on D. citri. Further work need to do before this strain is used as a sound biological control agents.

The diversity of ice algal communities on the Greenland Ice Sheet as revealed by oligotyping

The Arctic is being disproportionally affected by climate change compared with other geographic locations, and is currently experiencing unprecedented melt rates. The Greenland Ice Sheet (GrIS) can be regarded as the largest supraglacial ecosystem on Earth, and ice algae are the dominant primary producers on bare ice surfaces throughout the course of a melt season. Ice-algal-derived pigments cause a darkening of the ice surface, which in turn decreases albedo and increases melt rates. The important role of ice algae in changing melt rates has only recently been recognized, and we currently know little about their community compositions and functions. Here, we present the first analysis of ice algal communities across a 100 km transect on the GrIS by high-throughput sequencing and subsequent oligotyping of the most abundant taxa. Our data reveal an extremely low algal diversity with Ancylonema nordenskiöldii and a Mesotaenium species being by far the dominant taxa at all sites. We employed an oligotyping approach and revealed a hidden diversity not detectable by conventional clustering of operational taxonomic units and taxonomic classification. Oligotypes of the dominant taxa exhibit a site-specific distribution, which may be linked to differences in temperatures and subsequently the extent of the melting. Our results help to better understand the distribution patterns of ice algal communities that play a crucial role in the GrIS ecosystem.

TREE2FASTA: a flexible Perl script for batch extraction of FASTA sequences from exploratory phylogenetic trees

Objective

The body of DNA sequence data lacking taxonomically informative sequence headers is rapidly growing in user and public databases (e.g. sequences lacking identification and contaminants). In the context of systematics studies, sorting such sequence data for taxonomic curation and/or molecular diversity characterization (e.g. crypticism) often requires the building of exploratory phylogenetic trees with reference taxa. The subsequent step of segregating DNA sequences of interest based on observed topological relationships can represent a challenging task, especially for large datasets.

Results

We have written TREE2FASTA, a Perl script that enables and expedites the sorting of FASTA-formatted sequence data from exploratory phylogenetic trees. TREE2FASTA takes advantage of the interactive, rapid point-and-click color selection and/or annotations of tree leaves in the popular Java tree-viewer FigTree to segregate groups of FASTA sequences of interest to separate files. TREE2FASTA allows for both simple and nested segregation designs to facilitate the simultaneous preparation of multiple data sets that may overlap in sequence content.

Electronic supplementary material

The online version of this article (10.1186/s13104-018-3268-y) contains supplementary material, which is available to authorized users.

Investigating monsoon and post-monsoon variabilities of bacterioplankton communities in a mangrove ecosystem

In mangrove environments, bacterioplankton communities constitute an important component of aquatic biota and play a major role in ecosystem processes. Variability of bacterioplankton communities from Sundarbans mangrove, located in the Indian subcontinent in South Asia and sits on the apex of Bay of Bengal, was investigated over monsoon and post-monsoon seasons. The study was undertaken in two stations in Sundarbans using 16S rRNA clone library and Illumina MiSeq approaches with focus on the functionally important members that participate in coastal biogeochemical cycling. Out of 544 sequenced clones, Proteobacteria dominated the study area (373 sequences) with persistence of two major classes, namely, Gammaproteobacteria and Alphaproteobacteria across both monsoon and post-monsoon seasons in both stations. Several sequences belonging to Sphingomonadales, Chromatiales, Alteromonadales, Oceanospirillales, and Bacteroidetes were encountered that are known to play important roles in coastal carbon cycling. Some sequences showed identity with published uncultured Planctomycetes and Chloroflexi highlighting their role in nitrogen cycling. The detection of two novel clades highlighted the existence of indigenous group of bacterioplankton that may play important roles in this ecosystem. The eubacterial V3-V4 region from environmental DNA extracted from the above two stations, followed by sequencing in Illumina MiSeq system, was also targeted in the study. A congruency between the clone library and Illumina approaches was observed. Strong variability in bacterioplankton community structure was encountered at a seasonal scale in link with precipitation. Drastic increase in sediment associated bacteria such as members of Firmicutes and Desulfovibrio was found in monsoon hinting possible resuspension of sediment-dwelling bacteria into the overlying water column. Principal component analysis (PCA) revealed dissolved ammonium and dissolved nitrate to account for maximum variation observed in the bacterioplankton community structure. Overall, the study showed that a strong interplay exists between environmental parameters and observed variability in bacterioplankton communities as a result of precipitation which can ultimately influence processes and rates linked to coastal biogeochemical cycles.

Accuracy of microbial community diversity estimated by closed- and open-reference OTUs

Next-generation sequencing of 16S ribosomal RNA is widely used to survey microbial communities. Sequences are typically assigned to Operational Taxonomic Units (OTUs). Closed- and open-reference OTU assignment matches reads to a reference database at 97% identity (closed), then clusters unmatched reads using a de novo method (open). Implementations of these methods in the QIIME package were tested on several mock community datasets with 20 strains using different sequencing technologies and primers. Richness (number of reported OTUs) was often greatly exaggerated, with hundreds or thousands of OTUs generated on Illumina datasets. Between-sample diversity was also found to be highly exaggerated in many cases, with weighted Jaccard distances between identical mock samples often close to one, indicating very low similarity. Non-overlapping hyper-variable regions in 70% of species were assigned to different OTUs. On mock communities with Illumina V4 reads, 56% to 88% of predicted genus names were false positives. Biological inferences obtained using these methods are therefore not reliable.

Metagenome analysis of the root endophytic microbial community of Indian rice (O. sativa L.)

This study reports the root endophytic microbial community profile in rice (Oryza sativa L.), the largest food crop of Asia, using 16S rRNA gene amplicon sequencing. Metagenome of OS01 and OS04 consisted of 11,17,900 sequences with 300 Mbp size and average 55.6% G + C content. Data of this study are available at NCBI Bioproject (PRJNA360379). The taxonomic analysis of 843 OTU's showed that the sequences belonged to four major phyla revealing dominance of Proteobacteria, Firmicutes, Cyanobacteria and Actinobacteria. Results reveal the dominance of Bacillus as major endophytic genera in rice roots, probably playing a key role in Nitrogen fixation.

Community Structure, Species Variation, and Potential Functions of Rhizosphere-Associated Bacteria of Different Winter Wheat (Triticum aestivum) Cultivars

Minimal tillage management of extensive crops like wheat can provide significant environmental services but can also lead to adverse interactions between soil borne microbes and the host. Little is known about the ability of the wheat cultivar to alter the microbial community from a long-term recruitment standpoint, and whether this recruitment is consistent across field sites. To address this, nine winter wheat cultivars were grown for two consecutive seasons on the same plots on two different farm sites and assessed for their ability to alter the rhizosphere bacterial communities in a minimal tillage system. Using deep amplicon sequencing of the V1-V3 region of the 16S rDNA, a total of 26,604 operational taxonomic units (OTUs) were found across these two sites. A core bacteriome consisting of 962 OTUs were found to exist in 95% of the wheat rhizosphere samples. Differences in the relative abundances for these wheat cultivars were observed. Of these differences, 24 of the OTUs were found to be significantly different by wheat cultivar and these differences occurred at both locations. Several of the cultivar-associated OTUs were found to correspond with strains that may provide beneficial services to the host plant. Network correlations demonstrated significant co-occurrences for different taxa and their respective OTUs, and in some cases, these interactions were determined by the wheat cultivar. Microbial abundances did not play a role in the number of correlations, and the majority of the co-occurrences were shown to be positively associated. Phylogenetic Investigation of Communities by Reconstruction of Unobserved States was used to determine potential functions associated with OTUs by association with rhizosphere members which have sequenced metagenomics data. Potentially beneficial pathways for nitrogen, sulfur, phosphorus, and malate metabolism, as well as antimicrobial compounds, were inferred from this analysis. Differences in these pathways and their associated functions were found to differ by wheat cultivar. In conclusion, our study suggests wheat cultivars are involved in shaping the rhizosphere by differentially altering the bacterial OTUs consistently across different sites, and these altered bacterial communities may provide beneficial services to the host.

Metabarcoding of marine nematodes - evaluation of similarity scores used in alignment-based taxonomy assignment approach

BACKGROUND

The diversity of organisms is being commonly accessed using metabarcoding of environmental samples. Reliable identification of barcodes is one of the critical steps in the process and several taxonomy assignment methods were proposed to accomplish this task, including alignment-based approach that uses Basic Local Alignment Search Tool (BLAST) algorithm. This publication evaluates the variability of 5' end of 18S rRNA barcoding region as expressed by similarity scores (alignment score and identity score) produced by BLAST, and its impact on barcode identification to family-level taxonomic categories.

NEW INFORMATION

In alignment-based taxonomy assignment approach, reliable identification of anonymous OTUs to supraspecific taxa depends on the correct application of similarity thresholds. Since various taxa show different level of genetic variation, practical application of alignment-based approach requires the determination and use of taxon-specific similarity thresholds.

Metabarcoding of marine nematodes - evaluation of reference datasets used in tree-based taxonomy assignment approach

Background

Metabarcoding is becoming a common tool used to assess and compare diversity of organisms in environmental samples. Identification of OTUs is one of the critical steps in the process and several taxonomy assignment methods were proposed to accomplish this task. This publication evaluates the quality of reference datasets, alongside with several alignment and phylogeny inference methods used in one of the taxonomy assignment methods, called tree-based approach. This approach assigns anonymous OTUs to taxonomic categories based on relative placements of OTUs and reference sequences on the cladogram and support that these placements receive.

New information

In tree-based taxonomy assignment approach, reliable identification of anonymous OTUs is based on their placement in monophyletic and highly supported clades together with identified reference taxa. Therefore, it requires high quality reference dataset to be used. Resolution of phylogenetic trees is strongly affected by the presence of erroneous sequences as well as alignment and phylogeny inference methods used in the process. Two preparation steps are essential for the successful application of tree-based taxonomy assignment approach.

Completing the above mentioned preparation steps is expected to decrease the number of unassigned OTUs and thus improve the results of the tree-based taxonomy assignment approach.

PhyloCore: A phylogenetic approach to identifying core taxa in microbial communities

BACKGROUND

Identifying core microbiota is an important step for understanding the key components of microbial communities. Traditional approach that identifies core taxa at the OTU level ignores potential ecological coherence of higher rank taxa. There is a need to develop software that can systematically identify core taxa at and above the species level.

RESULTS

Here we developed PhyloCore, an application that uses a phylogeny-based algorithm to identify core taxa at the proper taxonomic levels. It incorporates a number of features that users can set according to their needs. Using multiple gut microbiota as test cases, we demonstrate that PhyloCore is more powerful and flexible than OTU-based approaches.

CONCLUSIONS

PhyloCore is a flexible and fast application that identifies core taxa at proper taxonomic levels, making it useful to sequence-based microbial ecology studies. The software is freely available at http://wolbachia.biology.virginia.edu/WuLab/Software.html.

A Cell Cycle-Regulated Toxoplasma Deubiquitinase, TgOTUD3A, Targets Polyubiquitins with Specific Lysine Linkages

The role of ubiquitin-mediated processes in the regulation of the apicomplexan cell cycle is beginning to be elucidated. The recent analysis of the Toxoplasma “ubiquitome” highlights the importance of ubiquitination in the parasite cell cycle. The machinery regulating the ubiquitin dynamics in T. gondii has remained understudied. Here, we provide a biochemical characterization of an OTU (ovarian tumor) family deubiquitinase, TgOTUD3A, defining its localization and dynamic expression pattern at various stages of the cell cycle. We further establish that TgOTUD3A has activity preference for polyubiquitin chains with certain lysine linkages—such unique activity has not been previously reported in any apicomplexan. This is particularly important given the finding in this study that Toxoplasma gondii proteins are modified by diverse lysine-linked polyubiquitin chains and that these modifications are very dynamic across the cell cycle, pointing toward the sophistication of the “ubiquitin code” as a potential mechanism to regulate parasite biology.

The contribution of ubiquitin-mediated mechanisms in the regulation of the Toxoplasma gondii cell cycle has remained largely unexplored. Here, we describe the functional characterization of a T. gondii deubiquitinase (TGGT1_258780) of the ovarian-tumor domain-containing (OTU) family, which, based on its structural homology to the human OTUD3 clade, has been designated TgOTUD3A. The TgOTUD3A protein is expressed in a cell cycle-dependent manner mimicking its mRNA expression, indicating that it is regulated primarily at the transcriptional level. TgOTUD3A, which was found in the cytoplasm at low levels in G₁ parasites, increased in abundance with the progression of the cell cycle and exhibited partial localization to the developing daughter scaffolds during cytokinesis. Recombinant TgOTUD3A but not a catalytic-site mutant TgOTUD3A (C229A) exhibited activity against poly- but not monoubiquitinated targets. This activity was selective for polyubiquitin chains with preference for specific lysine linkages (K48 > K11 > K63). All three of these polyubiquitin linkage modifications were found to be present in Toxoplasma, where they exhibited differential levels and localization patterns in a cell cycle-dependent manner. TgOTUD3A removed ubiquitin from the K48- but not the K63-linked ubiquitinated T. gondii proteins independently of the modified target protein, thereby exhibiting the characteristics of an exodeubiquitinase. In addition to cell cycle association, the demonstration of multiple ubiquitin linkages together with the selective deubiquitinase activity of TgOTUD3A reveals an unappreciated level of complexity in the T. gondii “ubiquitin code.”

IMPORTANCE The role of ubiquitin-mediated processes in the regulation of the apicomplexan cell cycle is beginning to be elucidated. The recent analysis of the Toxoplasma “ubiquitome” highlights the importance of ubiquitination in the parasite cell cycle. The machinery regulating the ubiquitin dynamics in T. gondii has remained understudied. Here, we provide a biochemical characterization of an OTU (ovarian tumor) family deubiquitinase, TgOTUD3A, defining its localization and dynamic expression pattern at various stages of the cell cycle. We further establish that TgOTUD3A has activity preference for polyubiquitin chains with certain lysine linkages—such unique activity has not been previously reported in any apicomplexan. This is particularly important given the finding in this study that Toxoplasma gondii proteins are modified by diverse lysine-linked polyubiquitin chains and that these modifications are very dynamic across the cell cycle, pointing toward the sophistication of the “ubiquitin code” as a potential mechanism to regulate parasite biology.

Application of a Database-Independent Approach To Assess the Quality of Operational Taxonomic Unit Picking Methods

Assignment of 16S rRNA gene sequences to operational taxonomic units (OTUs) allows microbial ecologists to overcome the inconsistencies and biases within bacterial taxonomy and provides a strategy for clustering similar sequences that do not have representatives in a reference database. I have applied the Matthews correlation coefficient to assess the ability of 15 reference-independent and -dependent clustering algorithms to assign sequences to OTUs. This metric quantifies the ability of an algorithm to reflect the relationships between sequences without the use of a reference and can be applied to any data set or method. The most consistently robust method was the average neighbor algorithm; however, for some data sets, other algorithms matched its performance.

Monitoring Target Engagement of Deubiquitylating Enzymes Using Activity Probes: Past, Present, and Future

Deubiquitylating enzymes or DUBs are a class of enzymes that selectively remove the polypeptide posttranslational modification ubiquitin from a number of substrates. Approximately 100 DUBs exist in human cells and are involved in key regulatory cellular processes, which drive many disease states, making them attractive therapeutic targets. Several aspects of DUB biology have been studied through genetic knock-out or knock-down, genomic, or proteomic studies. However, investigation of enzyme activation and regulation requires additional tools to monitor cellular and physiological dynamics. A comparison between genetic ablation and dominant-negative target validation with pharmacological inhibition often leads to striking discrepancies. Activity probes have been used to profile classes of enzymes, including DUBs, and allow functional and dynamic properties to be assigned to individual proteins. The ability to directly monitor DUB activity within a native biological system is essential for understanding the physiological and pathological role of individual DUBs. We will discuss the evolution of DUB activity probes, from in vitro assay development to their use in monitoring DUB activity in cells and in animal tissues, as well as recent progress and prospects for assessing DUB inhibition in vivo.

De novo clustering methods outperform reference-based methods for assigning 16S rRNA gene sequences to operational taxonomic units

Background. 16S rRNA gene sequences are routinely assigned to operational taxonomic units (OTUs) that are then used to analyze complex microbial communities. A number of methods have been employed to carry out the assignment of 16S rRNA gene sequences to OTUs leading to confusion over which method is optimal. A recent study suggested that a clustering method should be selected based on its ability to generate stable OTU assignments that do not change as additional sequences are added to the dataset. In contrast, we contend that the quality of the OTU assignments, the ability of the method to properly represent the distances between the sequences, is more important. Methods. Our analysis implemented six de novo clustering algorithms including the single linkage, complete linkage, average linkage, abundance-based greedy clustering, distance-based greedy clustering, and Swarm and the open and closed-reference methods. Using two previously published datasets we used the Matthew's Correlation Coefficient (MCC) to assess the stability and quality of OTU assignments. Results. The stability of OTU assignments did not reflect the quality of the assignments. Depending on the dataset being analyzed, the average linkage and the distance and abundance-based greedy clustering methods generated OTUs that were more likely to represent the actual distances between sequences than the open and closed-reference methods. We also demonstrated that for the greedy algorithms VSEARCH produced assignments that were comparable to those produced by USEARCH making VSEARCH a viable free and open source alternative to USEARCH. Further interrogation of the reference-based methods indicated that when USEARCH or VSEARCH were used to identify the closest reference, the OTU assignments were sensitive to the order of the reference sequences because the reference sequences can be identical over the region being considered. More troubling was the observation that while both USEARCH and VSEARCH have a high level of sensitivity to detect reference sequences, the specificity of those matches was poor relative to the true best match. Discussion. Our analysis calls into question the quality and stability of OTU assignments generated by the open and closed-reference methods as implemented in current version of QIIME. This study demonstrates that de novo methods are the optimal method of assigning sequences into OTUs and that the quality of these assignments needs to be assessed for multiple methods to identify the optimal clustering method for a particular dataset.

Fragmentation and Coverage Variation in Viral Metagenome Assemblies, and Their Effect in Diversity Calculations

Metagenomic libraries consist of DNA fragments from diverse species, with varying genome size and abundance. High-throughput sequencing platforms produce large volumes of reads from these libraries, which may be assembled into contigs, ideally resembling the original larger genomic sequences. The uneven species distribution, along with the stochasticity in sample processing and sequencing bias, impacts the success of accurate sequence assembly. Several assemblers enable the processing of viral metagenomic data de novo, generally using overlap layout consensus or de Bruijn graph approaches for contig assembly. The success of viral genomic reconstruction in these datasets is limited by the degree of fragmentation of each genome in the sample, which is dependent on the sequencing effort and the genome length. Depending on ecological, biological, or procedural biases, some fragments have a higher prevalence, or coverage, in the assembly. However, assemblers must face challenges, such as the formation of chimerical structures and intra-species variability. Diversity calculation relies on the classification of the sequences that comprise a metagenomic dataset. Whenever the corresponding genomic and taxonomic information is available, contigs matching the same species can be classified accordingly and the coverage of its genome can be calculated for that species. This may be used to compare populations by estimating abundance and assessing species distribution from this data. Nevertheless, the coverage does not take into account the degree of fragmentation, or else genome completeness, and is not necessarily representative of actual species distribution in the samples. Furthermore, undetermined sequences are abundant in viral metagenomic datasets, resulting in several independent contigs that cannot be assigned by homology or genomic information. These may only be classified as different operational taxonomic units (OTUs), sometimes remaining inadvisably unrelated. Thus, calculations using contigs as different OTUs ultimately overestimate diversity when compared to diversity calculated from species coverage. In order to compare the effect of coverage and fragmentation, we generated three sets of simulated Illumina paired-end reads with different sequencing depths. We compared different assemblies performed with RayMeta, CLC Assembly Cell, MEGAHIT, SPAdes, Meta-IDBA, SOAPdenovo, Velvet, Metavelvet, and MIRA with the best attainable assemblies for each dataset (formed by arranging data using known genome coordinates) by calculating different assembly statistics. A new fragmentation score was included to estimate the degree of genome fragmentation of each taxon and adjust the coverage accordingly. The abundance in the metagenome was compared by bootstrapping the assembly data and hierarchically clustering them with the best possible assembly. Additionally, richness and diversity indexes were calculated for all the resulting assemblies and were assessed under two distributions: contigs as independent OTUs and sequences classified by species. Finally, we search for the strongest correlations between the diversity indexes and the different assembly statistics. Although fragmentation was dependent of genome coverage, it was not as heavily influenced by the assembler. The sequencing depth was the predominant attractor that influenced the success of the assemblies. The coverage increased notoriously in larger datasets, whereas fragmentation values remained lower and unsaturated. While still far from obtaining the ideal assemblies, the RayMeta, SPAdes, and the CLC assemblers managed to build the most accurate contigs with larger datasets while Meta-IDBA showed a good performance with the medium-sized dataset, even after the adjusted coverage was calculated. Their resulting assemblies showed the highest coverage scores and the lowest fragmentation values. Alpha diversity calculated from contigs as OTUs resulted in significantly higher values for all assemblies when compared with actual species distribution, showing an overestimation due to the increased predicted abundance. Conversely, using PHACCS resulted in lower values for all assemblers. Different association methods (random-forest, generalized linear models, and the Spearman correlation index) support the number of contigs, the coverage, and fragmentation as the assembly parameters that most affect the estimation of the alpha diversity. Coverage calculations may provide an insight into relative completeness of a genome but they overlook missing fragments or overly separated sequences in a genome. The assembly of a highly fragmented genomes with high coverage may still lead to the clustering of different OTUs that are actually different fragments of a genome. Thus, it proves useful to penalize coverage with a fragmentation score. Using contigs for calculating alpha diversity result in overestimation but it is usually the only approach available. Still, it is enough for sample comparison. The best approach may be determined by choosing the assembler that better fits the sequencing depth and adjusting the parameters for longer accurate contigs whenever possible whereas diversity may be calculated considering taxonomical and genomic information if available.

High-throughput sequencing of 16S rDNA amplicons characterizes bacterial composition in bronchoalveolar lavage fluid in patients with ventilator-associated pneumonia

Ventilator-associated pneumonia (VAP) is a life-threatening disease that is associated with high rates of morbidity and likely mortality, placing a heavy burden on an individual and society. Currently available diagnostic and therapeutic approaches for VAP treatment are limited, and the prognosis of VAP is poor. The present study aimed to reveal and discriminate the identification of the full spectrum of the pathogens in patients with VAP using high-throughput sequencing approach and analyze the species richness and complexity via alpha and beta diversity analysis. The bronchoalveolar lavage fluid samples were collected from 27 patients with VAP in intensive care unit. The polymerase chain reaction products of the hypervariable regions of 16S rDNA gene in these 27 samples of VAP were sequenced using the 454 GS FLX system. A total of 103,856 pyrosequencing reads and 638 operational taxonomic units were obtained from these 27 samples. There were four dominant phyla, including Proteobacteria, Firmicutes, Actinobacteria, and Bacteroidetes. There were 90 different genera, of which 12 genera occurred in over ten different samples. The top five dominant genera were Streptococcus, Acinetobacter, Limnohabitans, Neisseria, and Corynebacterium, and the most widely distributed genera were Streptococcus, Limnohabitans, and Acinetobacter in these 27 samples. Of note, the mixed profile of causative pathogens was observed. Taken together, the results show that the high-throughput sequencing approach facilitates the characterization of the pathogens in bronchoalveolar lavage fluid samples and the determination of the profile for bacteria in the bronchoalveolar lavage fluid samples of the patients with VAP. This study can provide useful information of pathogens in VAP and assist clinicians to make rational and effective therapeutic decisions.

High-throughput sequencing of 16S rDNA amplicons characterizes bacterial composition in cerebrospinal fluid samples from patients with purulent meningitis

Purulent meningitis (PM) is a severe infectious disease that is associated with high rates of morbidity and mortality. It has been recognized that bacterial infection is a major contributing factor to the pathogenesis of PM. However, there is a lack of information on the bacterial composition in PM, due to the low positive rate of cerebrospinal fluid bacterial culture. Herein, we aimed to discriminate and identify the main pathogens and bacterial composition in cerebrospinal fluid sample from PM patients using high-throughput sequencing approach. The cerebrospinal fluid samples were collected from 26 PM patients, and were determined as culture-negative samples. The polymerase chain reaction products of the hypervariable regions of 16S rDNA gene in these 26 samples of PM were sequenced using the 454 GS FLX system. The results showed that there were 71,440 pyrosequencing reads, of which, the predominant phyla were Proteobacteria and Firmicutes; and the predominant genera were Streptococcus, Acinetobacter, Pseudomonas, and Neisseria. The bacterial species in the cerebrospinal fluid were complex, with 61.5% of the samples presenting with mixed pathogens. A significant number of bacteria belonging to a known pathogenic potential was observed. The number of operational taxonomic units for individual samples ranged from six to 75 and there was a comparable difference in the species diversity that was calculated through alpha and beta diversity analysis. Collectively, the data show that high-throughput sequencing approach facilitates the characterization of the pathogens in cerebrospinal fluid and determine the abundance and the composition of bacteria in the cerebrospinal fluid samples of the PM patients, which may provide a better understanding of pathogens in PM and assist clinicians to make rational and effective therapeutic decisions.