Dataset Information

Metagenomics: read length matters.

ABSTRACT: Obtaining an unbiased view of the phylogenetic composition and functional diversity within a microbial community is one central objective of metagenomic analysis. New technologies, such as 454 pyrosequencing, have dramatically reduced sequencing costs, to a level where metagenomic analysis may become a viable alternative to more-focused assessments of the phylogenetic (e.g., 16S rRNA genes) and functional diversity of microbial communities. To determine whether the short (approximately 100 to 200 bp) sequence reads obtained from pyrosequencing are appropriate for the phylogenetic and functional characterization of microbial communities, the results of BLAST and COG analyses were compared for long (approximately 750 bp) and randomly derived short reads from each of two microbial and one virioplankton metagenome libraries. Overall, BLASTX searches against the GenBank nr database found far fewer homologs within the short-sequence libraries. This was especially pronounced for a Chesapeake Bay virioplankton metagenome library. Increasing the short-read sampling depth or the length of derived short reads (up to 400 bp) did not completely resolve the discrepancy in BLASTX homolog detection. Only in cases where the long-read sequence had a close homolog (low BLAST E-score) did the derived short-read sequence also find a significant homolog. Thus, more-distant homologs of microbial and viral genes are not detected by short-read sequences. Among COG hits, derived short reads sampled at a depth of two short reads per long read missed up to 72% of the COG hits found using long reads. Noting the current limitation in computational approaches for the analysis of short sequences, the use of short-read-length libraries does not appear to be an appropriate tool for the metagenomic characterization of microbial communities.

SUBMITTER: Wommack KE

PROVIDER: S-EPMC2258652 | biostudies-literature | 2008 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Metagenomics: read length matters.

Wommack K Eric KE Bhavsar Jaysheel J Ravel Jacques J

Applied and environmental microbiology 20080111 5

Obtaining an unbiased view of the phylogenetic composition and functional diversity within a microbial community is one central objective of metagenomic analysis. New technologies, such as 454 pyrosequencing, have dramatically reduced sequencing costs, to a level where metagenomic analysis may become a viable alternative to more-focused assessments of the phylogenetic (e.g., 16S rRNA genes) and functional diversity of microbial communities. To determine whether the short (approximately 100 to 20 ...[more]

PMID: 18192407

Similar Datasets

Project description:BackgroundThere are many programs available for generating simulated whole-genome shotgun sequence reads. The data generated by many of these programs follow predefined models, which limits their use to the authors' original intentions. For example, many models assume that read lengths follow a uniform or normal distribution. Other programs generate models from actual sequencing data, but are limited to reads from single-genome studies. To our knowledge, there are no programs that allow a user to generate simulated data following non-parametric read-length distributions and quality profiles based on empirically-derived information from metagenomics sequencing data.ResultsWe present BEAR (Better Emulation for Artificial Reads), a program that uses a machine-learning approach to generate reads with lengths and quality values that closely match empirically-derived distributions. BEAR can emulate reads from various sequencing platforms, including Illumina, 454, and Ion Torrent. BEAR requires minimal user input, as it automatically determines appropriate parameter settings from user-supplied data. BEAR also uses a unique method for deriving run-specific error rates, and extracts useful statistics from the metagenomic data itself, such as quality-error models. Many existing simulators are specific to a particular sequencing technology; however, BEAR is not restricted in this way. Because of its flexibility, BEAR is particularly useful for emulating the behaviour of technologies like Ion Torrent, for which no dedicated sequencing simulators are currently available. BEAR is also the first metagenomic sequencing simulator program that automates the process of generating abundances, which can be an arduous task.ConclusionsBEAR is useful for evaluating data processing tools in genomics. It has many advantages over existing comparable software, such as generating more realistic reads and being independent of sequencing technology, and has features particularly useful for metagenomics work.

Project description:Microbial secondary metabolites play crucial roles in microbial competition, communication, resource acquisition, antibiotic production, and a variety of other biotechnological processes. The retrieval of full-length BGC (biosynthetic gene cluster) sequences from uncultivated bacteria is difficult due to the technical constraints of short-read sequencing, making it impossible to determine BGC diversity. Using long-read sequencing and genome mining, 339 mainly full-length BGCs were recovered in this study, illuminating the wide range of BGCs from uncultivated lineages discovered in seawater from Aoshan Bay, Yellow Sea, China. Many extremely diverse BGCs were discovered in bacterial phyla such as Proteobacteria, Bacteroidota, Acidobacteriota, and Verrucomicrobiota as well as the previously uncultured archaeal phylum "Candidatus Thermoplasmatota." The data from metatranscriptomics showed that 30.1% of secondary metabolic genes were being expressed, and they also revealed the expression pattern of BGC core biosynthetic genes and tailoring enzymes. Taken together, our results demonstrate that long-read metagenomic sequencing combined with metatranscriptomic analysis provides a direct view into the functional expression of BGCs in environmental processes. IMPORTANCE Genome mining of metagenomic data has become the preferred method for the bioprospecting of novel compounds by cataloguing secondary metabolite potential. However, the accurate detection of BGCs requires unfragmented genomic assemblies, which have been technically difficult to obtain from metagenomes until recently with new long-read technologies. We used high-quality metagenome-assembled genomes generated from long-read data to determine the biosynthetic potential of microbes found in the surface water of the Yellow Sea. We recovered 339 highly diverse and mostly full-length BGCs from largely uncultured and underexplored bacterial and archaeal phyla. Additionally, we present long-read metagenomic sequencing combined with metatranscriptomic analysis as a potential method for gaining access to the largely underutilized genetic reservoir of specialized metabolite gene clusters in the majority of microbes that are not cultured. The combination of long-read metagenomic and metatranscriptomic analyses is significant because it can more accurately assess the mechanisms of microbial adaptation to the environment through BGC expression based on metatranscriptomic data.

Project description:BackgroundLong-read sequencing in metagenomics facilitates the assembly of complete genomes out of complex microbial communities. These genomes include essential biologic information such as the ribosomal genes or the mobile genetic elements, which are usually missed with short-reads. We applied long-read metagenomics with Nanopore sequencing to retrieve high-quality metagenome-assembled genomes (HQ MAGs) from a dog fecal sample.ResultsWe used nanopore long-read metagenomics and frameshift aware correction on a canine fecal sample and retrieved eight single-contig HQ MAGs, which were > 90% complete with < 5% contamination, and contained most ribosomal genes and tRNAs. At the technical level, we demonstrated that a high-molecular-weight DNA extraction improved the metagenomics assembly contiguity, the recovery of the rRNA operons, and the retrieval of longer and circular contigs that are potential HQ MAGs. These HQ MAGs corresponded to Succinivibrio, Sutterella, Prevotellamassilia, Phascolarctobacterium, Catenibacterium, Blautia, and Enterococcus genera. Linking our results to previous gastrointestinal microbiome reports (metagenome or 16S rRNA-based), we found that some bacterial species on the gastrointestinal tract seem to be more canid-specific -Succinivibrio, Prevotellamassilia, Phascolarctobacterium, Blautia_A sp900541345-, whereas others are more broadly distributed among animal and human microbiomes -Sutterella, Catenibacterium, Enterococcus, and Blautia sp003287895. Sutterella HQ MAG is potentially the first reported genome assembly for Sutterella stercoricanis, as assigned by 16S rRNA gene similarity. Moreover, we show that long reads are essential to detect mobilome functions, usually missed in short-read MAGs.ConclusionsWe recovered eight single-contig HQ MAGs from canine feces of a healthy dog with nanopore long-reads. We also retrieved relevant biological insights from these specific bacterial species previously missed in public databases, such as complete ribosomal operons and mobilome functions. The high-molecular-weight DNA extraction improved the assembly's contiguity, whereas the high-accuracy basecalling, the raw read error correction, the assembly polishing, and the frameshift correction reduced the insertion and deletion errors. Both experimental and analytical steps ensured the retrieval of complete bacterial genomes.

Project description:The recovery of DNA from viromes is a major obstacle in the use of long-read sequencing to study their genomes. For this reason, the use of cellular metagenomes (>0.2-μm size range) emerges as an interesting complementary tool, since they contain large amounts of naturally amplified viral genomes from prelytic replication. We have applied second-generation (Illumina NextSeq; short reads) and third-generation (PacBio Sequel II; long reads) sequencing to compare the diversity and features of the viral community in a marine sample obtained from offshore waters of the western Mediterranean. We found that a major wedge of the expected marine viral diversity was directly recovered by the raw PacBio circular consensus sequencing (CCS) reads. More than 30,000 sequences were detected only in this data set, with no homologues in the long- and short-read assembly, and ca. 26,000 had no homologues in the large data set of the Global Ocean Virome 2 (GOV2), highlighting the information gap created by the assembly bias. At the level of complete viral genomes, the performance was similar in both approaches. However, the hybrid long- and short-read assembly provided the longest average length of the sequences and improved the host assignment. Although no novel major clades of viruses were found, there was an increase in the intraclade genomic diversity recovered by long reads that produced an enriched assessment of the real diversity and allowed the discovery of novel genes with biotechnological potential (e.g., endolysin genes). IMPORTANCE We explored the vast genetic diversity of environmental viruses by using a combination of cellular metagenome (as opposed to virome) sequencing using high-fidelity long-read sequences (in this case, PacBio CCS). This approach resulted in the recovery of a representative sample of the viral population, and it performed better (more phage contigs, larger average contig size) than Illumina sequencing applied to the same sample. By this approach, the many biases of assembly are avoided, as the CCS reads recovers (typically around 5 kb) complete genes and even operons, resulting in a better discovery of the viral gene diversity based on viral marker proteins. Thus, biotechnologically promising genes, such as endolysin genes, can be very efficiently searched with this approach. In addition, hybrid assembly produces more complete and longer contigs, which is particularly important for studying little-known viral groups such as the nucleocytoplasmic large DNA viruses (NCLDV).

Dataset Information

Metagenomics: read length matters.

Publications

Metagenomics: read length matters.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets