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A new generation of non-Sanger-based sequencing technologies has delivered on its promise of sequencing DNA at unprecedented speed, thereby enabling impressive scientific achievements and novel biological applications. However, before stepping into the limelight, next-generation sequencing had to overcome the inertia of a field that relied on Sanger-sequencing for 30 years.

Background: Soil ecosystems harbor the most complex prokaryotic and eukaryotic microbial communities on Earth. Experimental approaches studying these systems usually focus on either the soil community’s taxonomic structure or its functional characteristics. Many methods target DNA as marker molecule and use PCR for amplification. Methodology/Principal Findings: Here we apply an RNA-centered meta-transcriptomic approach to simultaneously obtain information on both structure and function of a soil community. Total community RNA is random reversely transcribed into cDNA without any PCR or cloning step. Direct pyrosequencing produces large numbers of cDNA rRNA-tags; these are taxonomically profiled in a binning approach using the MEGAN software and two specifically compiled rRNA reference databases containing small and large subunit rRNA sequences. The pyrosequencing also produces mRNA-tags; these provide a sequence-based transcriptome of the community. One soil dataset of 258,411 RNA-tags of ~98 bp length contained 193,219 rRNA-tags with valid taxonomic information, together with 21,133 mRNA-tags. Quantitative information about the relative abundance of organisms from all three domains of life and from different trophic levels was obtained in a single experiment. Less frequent taxa, such as soil Crenarchaeota, were well represented in the data set. These were identified by more than 2,000 rRNA-tags; furthermore, their activity in situ was revealed through the presence of mRNA-tags specific for enzymes involved in ammonia oxidation and CO² fixation. Conclusions/Significance: This approach could be widely applied in microbial ecology by efficiently linking community structure and function in a single experiment while avoiding biases inherent in other methods.

Assessment of the microbial diversity residing in arthropod vectors of medical importance is crucial for monitoring endemic infections, for surveillance of newly emerging zoonotic pathogens, and for unraveling the associated bacteria within its host. The tick Ixodes ricinus is recognized as the primary European vector of disease-causing bacteria in humans. Despite I. ricinus being of great public health relevance, its microbial communities remain largely unexplored to date. Here we evaluate the pathogen-load and the microbiome in single adult I. ricinus by using 454- and Illumina-based metagenomic approaches. Genomic DNA-derived sequences were taxonomically profiled using a computational approach based on the BWA algorithm, allowing for the identification of known tick-borne pathogens at the strain level and the putative tick core microbiome. Additionally, we assessed and compared the bacterial taxonomic profile in nymphal and adult I. ricinus pools collected from two distinct geographic regions in Northern Italy by means of V6-16S rRNA amplicon pyrosequencing and community based ecological analysis. A total of 108 genera belonging to representatives of all bacterial phyla were detected and a rapid qualitative assessment for pathogenic bacteria, such as Borrelia, Rickettsia and Candidatus Neoehrlichia, and for other bacteria with mutualistic relationship or undetermined function, such as Wolbachia and Rickettsiella, was possible. Interestingly, the ecological analysis revealed that the bacterial community structure differed between the examined geographic regions and tick life stages. This finding suggests that the environmental context (abiotic and biotic factors) and host-selection behaviors affect their microbiome.Our data provide the most complete picture to date of the bacterial communities present within I. ricinus under natural conditions by using high-throughput sequencing technologies. This study further demonstrates a novel detection strategy for the microbiomes of arthropod vectors in the context of epidemiological and ecological studies.

Next-generation sequencings platforms coupled with advanced bioinformatic tools enable re-sequencing of the human genome at high-speed and large cost savings. We compare sequencing platforms from Roche/454(GS FLX), Illumina/HiSeq (HiSeq 2000), and Life Technologies/SOLiD (SOLiD 3 ECC) for their ability to identify single nucleotide substitutions in whole genome sequences from the same human sample. We report on significant GC-related bias observed in the data sequenced on Illumina and SOLiD platforms. The differences in the variant calls were investigated with regards to coverage, and sequencing error. Some of the variants called by only one or two of the platforms were experimentally tested using mass spectrometry; a method that is independent of DNA sequencing. We establish several causes why variants remained unreported, specific to each platform. We report the indel called using the three sequencing technologies and from the obtained results we conclude that sequencing human genomes with more than a single platform and multiple libraries is beneficial when high level of accuracy is required.

Coconut, cocoa and arecanut are commercial plantation crops that play a vital role in the Indian economy while sustaining the livelihood of more than 10 million Indians. According to 2012 Food and Agricultural organization's report, India is the third largest producer of coconut and it dominates the production of arecanut worldwide. In this study, three Plant Growth Promoting Rhizobacteria (PGPR) from coconut (CPCRI-1), cocoa (CPCRI-2) and arecanut (CPCRI-3) characterized for the PGP activities have been sequenced. The draft genome sizes were 4.7 Mb (56% GC), 5.9 Mb (63.6% GC) and 5.1 Mb (54.8% GB) for CPCRI-1, CPCRI-2, CPCRI-3, respectively. These genomes encoded 4056 (CPCRI-1), 4637 (CPCRI-2) and 4286 (CPCRI-3) protein-coding genes. Phylogenetic analysis revealed that both CPCRI-1 and CPCRI-3 belonged to Enterobacteriaceae family, while, CPCRI-2 was a Pseudomonadaceae family member. Functional annotation of the genes predicted that all three bacteria encoded genes needed for mineral phosphate solubilization, siderophores, acetoin, butanediol, 1-aminocyclopropane-1-carboxylate (ACC) deaminase, chitinase, phenazine, 4-hydroxybenzoate, trehalose and quorum sensing molecules supportive of the plant growth promoting traits observed in the course of their isolation and characterization. Additionally, in all the three CPCRI PGPRs, we identified genes involved in synthesis of hydrogen sulfide (H2S), which recently has been proposed to aid plant growth. The PGPRs also carried genes for central carbohydrate metabolism indicating that the bacteria can efficiently utilize the root exudates and other organic materials as energy source. Genes for production of peroxidases, catalases and superoxide dismutases that confer resistance to oxidative stresses in plants were identified. Besides these, genes for heat shock tolerance, cold shock tolerance and glycine-betaine production that enable bacteria to survive abiotic stress were also identified.

Whole genome bisulfite sequencing (WGBS), with its ability to interrogate methylation status at single CpG site resolution epigenome-wide, is a powerful technique for use in molecular experiments. Here, we aim to advance strategies for accurate and efficient WGBS for application in future large-scale epidemiological studies. We systematically compared the performance of three WGBS library preparation methods with low DNA input requirement (Swift Biosciences Accel-NGS, Illumina TruSeq and QIAGEN QIAseq) on two state-of-the-art sequencing platforms (Illumina NovaSeq and HiSeq X), and also assessed concordance between data generated by WGBS and methylation arrays. Swift achieved the highest proportion of CpG sites assayed and effective coverage at 26x (P < 0.001). TruSeq suffered from the highest proportion of PCR duplicates, while QIAseq failed to deliver across all quality metrics. There was little difference in performance between NovaSeq and HiSeq X, with the exception of higher read duplication rate on the NovaSeq (P < 0.05), likely attributable to the higher cluster densities on its flow cells. Systematic biases exist between WGBS and methylation arrays, with lower precision observed for WGBS across the range of depths investigated. To achieve a level of precision broadly comparable to the methylation array, a minimum coverage of 100x is recommended.

Oscillating diurnal rhythms of gene transcription, metabolic activity, and behavior are found in all three domains of life. However, diel cycles in naturally occurring heterotrophic bacteria and archaea have rarely been observed. Here, we report time-resolved whole-genome transcriptome profiles of multiple, naturally occurring oceanic bacterial populations sampled in situ over 3 days. As anticipated, the cyanobacterial transcriptome exhibited pronounced diel periodicity. Unexpectedly, several different heterotrophic bacterioplankton groups also displayed diel cycling in many of their gene transcripts. Furthermore, diel oscillations in different heterotrophic bacterial groups suggested population-specific timing of peak transcript expression in a variety of metabolic gene suites. These staggered multispecies waves of diel gene transcription may influence both the tempo and the mode of matter and energy transformation in the sea.

Understanding the particle size distribution in the air and patterns of environmental contamination of SARS-CoV-2 is essential for infection prevention policies. Here we screen surface and air samples from hospital rooms of COVID-19 patients for SARS-CoV-2 RNA. Environmental sampling is conducted in three airborne infection isolation rooms (AIIRs) in the ICU and 27 AIIRs in the general ward. 245 surface samples are collected. 56.7% of rooms have at least one environmental surface contaminated. High touch surface contamination is shown in ten (66.7%) out of 15 patients in the first week of illness, and three (20%) beyond the first week of illness ( p  = 0.01, χ 2 test). Air sampling is performed in three of the 27 AIIRs in the general ward, and detects SARS-CoV-2 PCR-positive particles of sizes >4 µm and 1–4 µm in two rooms, despite these rooms having 12 air changes per hour. This warrants further study of the airborne transmission potential of SARS-CoV-2. Here, the authors sample air and surfaces in hospital rooms of COVID-19 patients, detect SARS-CoV-2 RNA in air samples of two of three tested airborne infection isolation rooms, and find surface contamination in 66.7% of tested rooms during the first week of illness and 20% beyond the first week of illness.

Metagenomics is expanding our knowledge of the gene content, functional significance, and genetic variability in natural microbial communities. Still, there exists limited information concerning the regulation and dynamics of genes in the environment. We report here global analysis of expressed genes in a naturally occurring microbial community. We first adapted RNA amplification technologies to produce large amounts of cDNA from small quantities of total microbial community RNA. The fidelity of the RNA amplification procedure was validated with Prochlorococcus cultures and then applied to a microbial assemblage collected in the oligotrophic Pacific Ocean. Microbial community cDNAs were analyzed by pyrosequencing and compared with microbial community genomic DNA sequences determined from the same sample. Pyrosequencing-based estimates of microbial community gene expression compared favorably to independent assessments of individual gene expression using quantitative PCR. Genes associated with key metabolic pathways in open ocean microbial species--including genes involved in photosynthesis, carbon fixation, and nitrogen acquisition--and a number of genes encoding hypothetical proteins were highly represented in the cDNA pool. Genes present in the variable regions of Prochlorococcus genomes were among the most highly expressed, suggesting these encode proteins central to cellular processes in specific genotypes. Although many transcripts detected were highly similar to genes previously detected in ocean metagenomic surveys, a significant fraction ([almost equal to]50%) were unique. Thus, microbial community transcriptomic analyses revealed not only indigenous gene- and taxon-specific expression patterns but also gene categories undetected in previous DNA-based metagenomic surveys.

The subseafloor marine biosphere may be one of the largest reservoirs of microbial biomass on Earth and has recently been the subject of debate in terms of the composition of its microbial inhabitants, particularly on sediments from the Peru Margin. A metagenomic analysis was made by using whole-genome amplification and pyrosequencing of sediments from Ocean Drilling Program Site 1229 on the Peru Margin to further explore the microbial diversity and overall community composition within this environment. A total of 61.9 Mb of genetic material was sequenced from sediments at horizons 1, 16, 32, and 50 m below the seafloor. These depths include sediments from both primarily sulfate-reducing methane-generating regions of the sediment column. Many genes of the annotated genes, including those encoding ribosomal proteins, corresponded to those from the Chloroflexi and Euryarchaeota. However, analysis of the 16S small-subunit ribosomal genes suggests that Crenarchaeota are the abundant microbial member. Quantitative PCR confirms that uncultivated Crenarchaeota are indeed a major microbial group in these subsurface samples. These findings show that the marine subsurface is a distinct microbial habitat and is different from environments studied by metagenomics, especially because of the predominance of uncultivated archaeal groups.