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September 22, 2019  |  

PhyloPythiaS+: a self-training method for the rapid reconstruction of low-ranking taxonomic bins from metagenomes.

Background. Metagenomics is an approach for characterizing environmental microbial communities in situ, it allows their functional and taxonomic characterization and to recover sequences from uncultured taxa. This is often achieved by a combination of sequence assembly and binning, where sequences are grouped into ‘bins’ representing taxa of the underlying microbial community. Assignment to low-ranking taxonomic bins is an important challenge for binning methods as is scalability to Gb-sized datasets generated with deep sequencing techniques. One of the best available methods for species bins recovery from deep-branching phyla is the expert-trained PhyloPythiaS package, where a human expert decides on the taxa to incorporate in the model and identifies ‘training’ sequences based on marker genes directly from the sample. Due to the manual effort involved, this approach does not scale to multiple metagenome samples and requires substantial expertise, which researchers who are new to the area do not have. Results. We have developed PhyloPythiaS+, a successor to our PhyloPythia(S) software. The new (+) component performs the work previously done by the human expert. PhyloPythiaS+ also includes a new k-mer counting algorithm, which accelerated the simultaneous counting of 4-6-mers used for taxonomic binning 100-fold and reduced the overall execution time of the software by a factor of three. Our software allows to analyze Gb-sized metagenomes with inexpensive hardware, and to recover species or genera-level bins with low error rates in a fully automated fashion. PhyloPythiaS+ was compared to MEGAN, taxator-tk, Kraken and the generic PhyloPythiaS model. The results showed that PhyloPythiaS+ performs especially well for samples originating from novel environments in comparison to the other methods. Availability. PhyloPythiaS+ in a virtual machine is available for installation under Windows, Unix systems or OS X on: https://github.com/algbioi/ppsp/wiki.

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September 22, 2019  |  

Bacterial community structure in simultaneous nitrification, denitrification and organic matter removal process treating saline mustard tuber wastewater as revealed by 16S rRNA sequencing.

A simultaneous nitrification, denitrification and organic matter removal (SNDOR) process in sequencing batch biofilm reactor (SBBR) was established to treat saline mustard tuber wastewater (MTWW) in this study. An average COD removal efficiency of 86.48% and total nitrogen removal efficiency of 86.48% were achieved at 30gNaClL(-1) during 100days’ operation. The underlying mechanisms were investigated by PacBio SMRT DNA sequencing (V1-V9) to analyze the microbial community structures and its variation from low salinity at 10gNaClL(-1) to high salinity at 30gNaClL(-1). Results showed elevated salinity did not affect biological performance but reduced microbial diversity in SBBR, and halophilic bacteria gradually predominated by succession. Despite of high C/N, autotrophic ammonia-oxidizing bacteria (AOB) Nitrosomonas and ammonia-oxidizing archaea (AOA) Candidatus Nitrososphaera both contributed to ammonium oxidation. As salinity increasing, nitrite-oxidizing bacteria (NOB) were significantly inhibited, partial nitrification and denitrification (PND) process gradually contributed to nitrogen removal. Copyright © 2016 Elsevier Ltd. All rights reserved.

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September 22, 2019  |  

Analysis of microbial community structure of pit mud for Chinese strong-flavor liquor fermentation using next generation DNA sequencing of full-length 16S rRNA

The pit is the necessary bioreactor for brewing process of Chinese strong-flavor liquor. Pit mud in pits contains a large number of microorganisms and is a complex ecosystem. The analysis of bacterial flora in pit mud is of great significance to understand liquor fermentation mechanisms. To overcome taxonomic limitations of short reads in 16S rRNA variable region sequencing, we used high-throughput DNA sequencing of near full-length 16S rRNA gene to analyze microbial compositions of different types of pit mud that produce different qualities of strong-flavor liquor. The results showed that the main species in pit mud were Pseudomonas extremaustralis 14-3, Pseudomonas veronii, Serratia marcescens WW4, and Clostridium leptum in Ruminiclostridium. The microbial diversity of pit mud with different quality was significantly different. From poor to good quality of pit mud (thus the quality of liquor), the relative abundances of Ruminiclostridium and Syntrophomonas in Firmicutes was increased, and the relative abundance of Olsenella in Actinobacteria also increased, but the relative abundances of Pseudomonas and Serratia in Proteobacteria were decreased. The surprising findings of this study include that the diversity of intermediate level quality of N pit mud was the lowest, and the diversity levels of high quality pit mud G and poor quality pit mud B were similar. Correlation analysis showed that there were high positive correlations (r > 0.8) among different microbial groups in the flora. Based on the analysis of the microbial structures of pit mud in different quality, the good quality pit mud has a higher microbial diversity, but how this higher diversity and differential microbial compositions contribute to better quality of liquor fermentation remains obscure.

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September 22, 2019  |  

Biogas production from hydrothermal liquefaction wastewater (HTLWW): Focusing on the microbial communities as revealed by high-throughput sequencing of full-length 16S rRNA genes.

Hydrothermal liquefaction (HTL) is an emerging and promising technology for the conversion of wet biomass into bio-crude, however, little attention has been paid to the utilization of hydrothermal liquefaction wastewater (HTLWW) with high concentration of organics. The present study investigated biogas production from wastewater obtained from HTL of straw for bio-crude production, with focuses on the analysis of the microbial communities and characterization of the organics. Batch experiments showed the methane yield of HTLWW (R-HTLWW) was 184 mL/g COD, while HTLWW after petroleum ether extraction (PE-HTLWW), to extract additional bio-crude, had higher methane yield (235 mL/g COD) due to the extraction of recalcitrant organic compounds. Sequential batch experiments further demonstrated the higher methane yield of PE-HTLWW. LC-TOF-MS, HPLC and gel filtration chromatography showed organics with molecular weight (MW) < 1000 were well degraded. Results from the high-throughput sequencing of full-length 16S rRNA genes analysis showed similar microbial community compositions were obtained for the reactors fed with either R-HTLWW or PE-HTLWW. The degradation of fatty acids were related with Mesotoga infera, Syntrophomonas wolfei et al. by species level identification. However, the species related to the degradation of other compounds (e.g. phenols) were not found, which could be due to the presence of uncharacterized microorganisms. It was also found previously proposed criteria (97% and 98.65% similarity) for species identification of 16S rRNA genes were not suitable for a fraction of 16S rRNA genes. Copyright © 2016 Elsevier Ltd. All rights reserved.

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September 22, 2019  |  

Long-read, Single Molecule, Real-Time (SMRT) DNA Sequencing for metagenomic applications

In this chapter, we describe applications of single molecule, real-time (SMRT) DNA sequencing toward metagenomic research. The long sequence reads, combined with a lack of bias with respect to DNA sequence context or GC content, facilitate a more comprehensive analysis of the genomic constitution of microbial communities. Full-length 16S RNA gene sequencing at high (>99%) accuracy allows for species-level characterization of community members concomitant with the determination of community structure. The application of SMRT sequencing to whole-community shotgun microbial metagenomics has also been discussed.

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September 22, 2019  |  

Soil microbial communities are shaped by plant-driven changes in resource availability during secondary succession.

Although we understand the ecological processes eliciting changes in plant community composition during secondary succession, we do not understand whether co-occurring changes in plant detritus shape saprotrophic microbial communities in soil. In this study, we investigated soil microbial composition and function across an old-field chronosequence ranging from 16 to 86 years following agricultural abandonment, as well as three forests representing potential late-successional ecosystems. Fungal and bacterial community composition was quantified from ribosomal DNA, and insight into the functional potential of the microbial community to decay plant litter was gained from shotgun metagenomics and extracellular enzyme assays. Accumulation of soil organic matter across the chronosequence exerted a positive and significant effect on fungal phylogenetic ß-diversity and the activity of extracellular enzymes with lignocellulolytic activity. In addition, the increasing abundance of lignin-rich C4 grasses was positively related to the composition of fungal genes with lignocellulolytic function, thereby linking plant community composition, litter biochemistry, and microbial community function. However, edaphic properties were the primary agent shaping bacterial communities, as bacterial ß-diversity and variation in functional gene composition displayed a significant and positive relationship to soil pH across the chronosequence. The late-successional forests were compositionally distinct from the oldest old fields, indicating that substantial changes occur in soil microbial communities as old fields give way to forests. Taken together, our observations demonstrate that plants govern the turnover of soil fungal communities and functional characteristics during secondary succession, due to the continual input of detritus and differences in litter biochemistry among plant species.

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September 22, 2019  |  

A novel enrichment strategy reveals unprecedented number of novel transcription start sites at single base resolution in a model prokaryote and the gut microbiome.

The initiating nucleotide found at the 5′ end of primary transcripts has a distinctive triphosphorylated end that distinguishes these transcripts from all other RNA species. Recognizing this distinction is key to deconvoluting the primary transcriptome from the plethora of processed transcripts that confound analysis of the transcriptome. The currently available methods do not use targeted enrichment for the 5’end of primary transcripts, but rather attempt to deplete non-targeted RNA.We developed a method, Cappable-seq, for directly enriching for the 5′ end of primary transcripts and enabling determination of transcription start sites at single base resolution. This is achieved by enzymatically modifying the 5′ triphosphorylated end of RNA with a selectable tag. We first applied Cappable-seq to E. coli, achieving up to 50 fold enrichment of primary transcripts and identifying an unprecedented 16539 transcription start sites (TSS) genome-wide at single base resolution. We also applied Cappable-seq to a mouse cecum sample and identified TSS in a microbiome.Cappable-seq allows for the first time the capture of the 5′ end of primary transcripts. This enables a unique robust TSS determination in bacteria and microbiomes.  In addition to and beyond TSS determination, Cappable-seq depletes ribosomal RNA and reduces the complexity of the transcriptome to a single quantifiable tag per transcript enabling digital profiling of gene expression in any microbiome.

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September 22, 2019  |  

Revealing missing human protein isoforms based on Ab initio prediction, RNA-seq and proteomics.

Biological and biomedical research relies on comprehensive understanding of protein-coding transcripts. However, the total number of human proteins is still unknown due to the prevalence of alternative splicing. In this paper, we detected 31,566 novel transcripts with coding potential by filtering our ab initio predictions with 50 RNA-seq datasets from diverse tissues/cell lines. PCR followed by MiSeq sequencing showed that at least 84.1% of these predicted novel splice sites could be validated. In contrast to known transcripts, the expression of these novel transcripts were highly tissue-specific. Based on these novel transcripts, at least 36 novel proteins were detected from shotgun proteomics data of 41 breast samples. We also showed L1 retrotransposons have a more significant impact on the origin of new transcripts/genes than previously thought. Furthermore, we found that alternative splicing is extraordinarily widespread for genes involved in specific biological functions like protein binding, nucleoside binding, neuron projection, membrane organization and cell adhesion. In the end, the total number of human transcripts with protein-coding potential was estimated to be at least 204,950.

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September 22, 2019  |  

Single cell genomic study of Dehalococcoidetes species from deep-sea sediments of the Peruvian Margin.

The phylum Chloroflexi is one of the most frequently detected phyla in the subseafloor of the Pacific Ocean margins. Dehalogenating Chloroflexi (Dehalococcoidetes) was originally discovered as the key microorganisms mediating reductive dehalogenation via their key enzymes reductive dehalogenases (Rdh) as sole mode of energy conservation in terrestrial environments. The frequent detection of Dehalococcoidetes-related 16S rRNA and rdh genes in the marine subsurface implies a role for dissimilatory dehalorespiration in this environment; however, the two genes have never been linked to each other. To provide fundamental insights into the metabolism, genomic population structure and evolution of marine subsurface Dehalococcoidetes sp., we analyzed a non-contaminated deep-sea sediment core sample from the Peruvian Margin Ocean Drilling Program (ODP) site 1230, collected 7.3?m below the seafloor by a single cell genomic approach. We present for the first time single cell genomic data on three deep-sea Chloroflexi (Dsc) single cells from a marine subsurface environment. Two of the single cells were considered to be part of a local Dehalococcoidetes population and assembled together into a 1.38-Mb genome, which appears to be at least 85% complete. Despite a high degree of sequence-level similarity between the shared proteins in the Dsc and terrestrial Dehalococcoidetes, no evidence for catabolic reductive dehalogenation was found in Dsc. The genome content is however consistent with a strictly anaerobic organotrophic or lithotrophic lifestyle.

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September 22, 2019  |  

A comprehensive benchmarking study of protocols and sequencing platforms for 16S rRNA community profiling.

In the last 5 years, the rapid pace of innovations and improvements in sequencing technologies has completely changed the landscape of metagenomic and metagenetic experiments. Therefore, it is critical to benchmark the various methodologies for interrogating the composition of microbial communities, so that we can assess their strengths and limitations. The most common phylogenetic marker for microbial community diversity studies is the 16S ribosomal RNA gene and in the last 10 years the field has moved from sequencing a small number of amplicons and samples to more complex studies where thousands of samples and multiple different gene regions are interrogated.We assembled 2 synthetic communities with an even (EM) and uneven (UM) distribution of archaeal and bacterial strains and species, as metagenomic control material, to assess performance of different experimental strategies. The 2 synthetic communities were used in this study, to highlight the limitations and the advantages of the leading sequencing platforms: MiSeq (Illumina), The Pacific Biosciences RSII, 454 GS-FLX/+ (Roche), and IonTorrent (Life Technologies). We describe an extensive survey based on synthetic communities using 3 experimental designs (fusion primers, universal tailed tag, ligated adaptors) across the 9 hypervariable 16S rDNA regions. We demonstrate that library preparation methodology can affect data interpretation due to different error and chimera rates generated during the procedure. The observed community composition was always biased, to a degree that depended on the platform, sequenced region and primer choice. However, crucially, our analysis suggests that 16S rRNA sequencing is still quantitative, in that relative changes in abundance of taxa between samples can be recovered, despite these biases.We have assessed a range of experimental conditions across several next generation sequencing platforms using the most up-to-date configurations. We propose that the choice of sequencing platform and experimental design needs to be taken into consideration in the early stage of a project by running a small trial consisting of several hypervariable regions to quantify the discriminatory power of each region. We also suggest that the use of a synthetic community as a positive control would be beneficial to identify the potential biases and procedural drawbacks that may lead to data misinterpretation. The results of this study will serve as a guideline for making decisions on which experimental condition and sequencing platform to consider to achieve the best microbial profiling.

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September 22, 2019  |  

Genomic and metabolic diversity of Marine Group I Thaumarchaeota in the mesopelagic of two subtropical gyres.

Marine Group I (MGI) Thaumarchaeota are one of the most abundant and cosmopolitan chemoautotrophs within the global dark ocean. To date, no representatives of this archaeal group retrieved from the dark ocean have been successfully cultured. We used single cell genomics to investigate the genomic and metabolic diversity of thaumarchaea within the mesopelagic of the subtropical North Pacific and South Atlantic Ocean. Phylogenetic and metagenomic recruitment analysis revealed that MGI single amplified genomes (SAGs) are genetically and biogeographically distinct from existing thaumarchaea cultures obtained from surface waters. Confirming prior studies, we found genes encoding proteins for aerobic ammonia oxidation and the hydrolysis of urea, which may be used for energy production, as well as genes involved in 3-hydroxypropionate/4-hydroxybutyrate and oxidative tricarboxylic acid pathways. A large proportion of protein sequences identified in MGI SAGs were absent in the marine cultures Cenarchaeum symbiosum and Nitrosopumilus maritimus, thus expanding the predicted protein space for this archaeal group. Identifiable genes located on genomic islands with low metagenome recruitment capacity were enriched in cellular defense functions, likely in response to viral infections or grazing. We show that MGI Thaumarchaeota in the dark ocean may have more flexibility in potential energy sources and adaptations to biotic interactions than the existing, surface-ocean cultures.

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September 22, 2019  |  

Cultivation and sequencing of rumen microbiome members from the Hungate1000 Collection.

Productivity of ruminant livestock depends on the rumen microbiota, which ferment indigestible plant polysaccharides into nutrients used for growth. Understanding the functions carried out by the rumen microbiota is important for reducing greenhouse gas production by ruminants and for developing biofuels from lignocellulose. We present 410 cultured bacteria and archaea, together with their reference genomes, representing every cultivated rumen-associated archaeal and bacterial family. We evaluate polysaccharide degradation, short-chain fatty acid production and methanogenesis pathways, and assign specific taxa to functions. A total of 336 organisms were present in available rumen metagenomic data sets, and 134 were present in human gut microbiome data sets. Comparison with the human microbiome revealed rumen-specific enrichment for genes encoding de novo synthesis of vitamin B12, ongoing evolution by gene loss and potential vertical inheritance of the rumen microbiome based on underrepresentation of markers of environmental stress. We estimate that our Hungate genome resource represents ~75% of the genus-level bacterial and archaeal taxa present in the rumen.

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September 22, 2019  |  

Genomic insights into the acid adaptation of novel methanotrophs enriched from acidic forest soils.

Soil acidification is accelerated by anthropogenic and agricultural activities, which could significantly affect global methane cycles. However, detailed knowledge of the genomic properties of methanotrophs adapted to acidic soils remains scarce. Using metagenomic approaches, we analyzed methane-utilizing communities enriched from acidic forest soils with pH 3 and 4, and recovered near-complete genomes of proteobacterial methanotrophs. Novel methanotroph genomes designated KS32 and KS41, belonging to two representative clades of methanotrophs (Methylocystis of Alphaproteobacteria and Methylobacter of Gammaproteobacteria), were dominant. Comparative genomic analysis revealed diverse systems of membrane transporters for ensuring pH homeostasis and defense against toxic chemicals. Various potassium transporter systems, sodium/proton antiporters, and two copies of proton-translocating F1F0-type ATP synthase genes were identified, which might participate in the key pH homeostasis mechanisms in KS32. In addition, the V-type ATP synthase and urea assimilation genes might be used for pH homeostasis in KS41. Genes involved in the modification of membranes by incorporation of cyclopropane fatty acids and hopanoid lipids might be used for reducing proton influx into cells. The two methanotroph genomes possess genes for elaborate heavy metal efflux pumping systems, possibly owing to increased heavy metal toxicity in acidic conditions. Phylogenies of key genes involved in acid adaptation, methane oxidation, and antiviral defense in KS41 were incongruent with that of 16S rRNA. Thus, the detailed analysis of the genome sequences provides new insights into the ecology of methanotrophs responding to soil acidification.

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September 22, 2019  |  

Analyses of intestinal microbiota: culture versus sequencing.

Analyzing human as well as animal microbiota composition has gained growing interest because structural components and metabolites of microorganisms fundamentally influence all aspects of host physiology. Originally dominated by culture-dependent methods for exploring these ecosystems, the development of molecular techniques such as high throughput sequencing has dramatically increased our knowledge. Because many studies of the microbiota are based on the bacterial 16S ribosomal RNA (rRNA) gene targets, they can, at least in principle, be compared to determine the role of the microbiome composition for developmental processes, host metabolism, and physiology as well as different diseases. In our review, we will summarize differences and pitfalls in current experimental protocols, including all steps from nucleic acid extraction to bioinformatical analysis which may produce variation that outweighs subtle biological differences. Future developments, such as integration of metabolomic, transcriptomic, and metagenomic data sets and standardization of the procedures, will be discussed. © The Author 2015. Published by Oxford University Press on behalf of the Institute for Laboratory Animal Research. All rights reserved. For permissions, please email: journals.permissions@oup.com.

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September 22, 2019  |  

MEGAN-LR: new algorithms allow accurate binning and easy interactive exploration of metagenomic long reads and contigs.

There are numerous computational tools for taxonomic or functional analysis of microbiome samples, optimized to run on hundreds of millions of short, high quality sequencing reads. Programs such as MEGAN allow the user to interactively navigate these large datasets. Long read sequencing technologies continue to improve and produce increasing numbers of longer reads (of varying lengths in the range of 10k-1M bps, say), but of low quality. There is an increasing interest in using long reads in microbiome sequencing, and there is a need to adapt short read tools to long read datasets.We describe a new LCA-based algorithm for taxonomic binning, and an interval-tree based algorithm for functional binning, that are explicitly designed for long reads and assembled contigs. We provide a new interactive tool for investigating the alignment of long reads against reference sequences. For taxonomic and functional binning, we propose to use LAST to compare long reads against the NCBI-nr protein reference database so as to obtain frame-shift aware alignments, and then to process the results using our new methods.All presented methods are implemented in the open source edition of MEGAN, and we refer to this new extension as MEGAN-LR (MEGAN long read). We evaluate the LAST+MEGAN-LR approach in a simulation study, and on a number of mock community datasets consisting of Nanopore reads, PacBio reads and assembled PacBio reads. We also illustrate the practical application on a Nanopore dataset that we sequenced from an anammox bio-rector community.This article was reviewed by Nicola Segata together with Moreno Zolfo, Pete James Lockhart and Serghei Mangul.This work extends the applicability of the widely-used metagenomic analysis software MEGAN to long reads. Our study suggests that the presented LAST+MEGAN-LR pipeline is sufficiently fast and accurate.

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