Phages drive bacterial diversity, profoundly influencing microbial communities, from microbiomes to the drivers of global biogeochemical cycling. Aiming to broaden our understanding of Escherichia coli (MG1655, K-12) phages, we screened 188 Danish wastewater samples and isolated 136 phages. Ninety-two of these have genomic sequences with less than 95% similarity to known phages, while most map to existing genera several represent novel lineages. The isolated phages are highly diverse, estimated to represent roughly one-third of the true diversity of culturable virulent dsDNA Escherichia phages in Danish wastewater, yet almost half (40%) are not represented in metagenomic databases, emphasising the importance of isolating phages to uncover diversity. Seven viral families, Myoviridae, Siphoviridae, Podoviridae, Drexlerviridae, Chaseviridae, Autographviridae, and Microviridae, are represented in the dataset. Their genomes vary drastically in length from 5.3 kb to 170.8 kb, with a guanine and cytosine (GC) content ranging from 35.3% to 60.0%. Hence, even for a model host bacterium, substantial diversity remains to be uncovered. These results expand and underline the range of coliphage diversity and demonstrate how far we are from fully disclosing phage diversity and ecology.
A wealth of viral data sits untapped in publicly available metagenomic data sets when it might be extracted to create a usable index for the virological research community. We hypothesized that work of this complexity and scale could be done in a hackathon setting. Ten teams comprised of over 40 participants from six countries, assembled to create a crowd-sourced set of analysis and processing pipelines for a complex biological data set in a three-day event on the San Diego State University campus starting 9 January 2019. Prior to the hackathon, 141,676 metagenomic data sets from the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) were pre-assembled into contiguous assemblies (contigs) by NCBI staff. During the hackathon, a subset consisting of 2953 SRA data sets (approximately 55 million contigs) was selected, which were further filtered for a minimal length of 1 kb. This resulted in 4.2 million (Mio) contigs, which were aligned using BLAST against all known virus genomes, phylogenetically clustered and assigned metadata. Out of the 4.2 Mio contigs, 360,000 contigs were labeled with domains and an additional subset containing 4400 contigs was screened for virus or virus-like genes. The work yielded valuable insights into both SRA data and the cloud infrastructure required to support such efforts, revealing analysis bottlenecks and possible workarounds thereof. Mainly: (i) Conservative assemblies of SRA data improves initial analysis steps; (ii) existing bioinformatic software with weak multithreading/multicore support can be elevated by wrapper scripts to use all cores within a computing node; (iii) redesigning existing bioinformatic algorithms for a cloud infrastructure to facilitate its use for a wider audience; and (iv) a cloud infrastructure allows a diverse group of researchers to collaborate effectively. The scientific findings will be extended during a follow-up event. Here, we present the applied workflows, initial results, and lessons learned from the hackathon.
The phyllosphere microbiome plays an important role in plant fitness. Recently, bacteriophages have been shown to play a role in shaping the bacterial community composition of the phyllosphere. However, no studies on the diversity and abundance of phyllosphere bacteriophage communities have been carried out until now. In this study, we extracted, sequenced, and characterized the dsDNA and ssDNA viral community from a phyllosphere for the first time. We sampled leaves from winter wheat (Triticum aestivum), where we identified a total of 876 virus operational taxonomic units (vOTUs), mostly predicted to be bacteriophages with a lytic lifestyle. Remarkably, 848 of these vOTUs corresponded to new viral species, and we estimated a minimum of 2.0 × 106 viral particles per leaf. These results suggest that the wheat phyllosphere harbors a large and active community of novel bacterial viruses. Phylloviruses have potential applications as biocontrol agents against phytopathogenic bacteria or as microbiome modulators to increase plant growth-promoting bacteria.
Today, it is well-known that not only the DNA sequence, but also its modifications, impact the biological function of diverse organisms, such as bacteria and eukaryotes. Genome modifications can also impact the biology of viruses. A variety of moieties can be appended to the nucleobase of a nucleotide, ranging from simple methyl groups to a highly diverse collection of more complex molecules. Since these modifications often play an important role in the inheritable phenotypic expression of the genome without altering the DNA sequence itself, they are typically referred to as epigenetic determinants, and altogether they constitute the epigenome of a given organism. Because epigenetic processes in eukaryotes, mostly including DNA methylations and histone modifications, are
Despite the massive developments within culture-independent methods for detection of microorganisms during the last decade, culture-based methods remain a cornerstone in microbiology. Yet, the problem of rapid, accurate and inexpensive identification of bacterial isolates down to species/strain level remains unresolved. We have developed a new method for bacterial DNA enrichment and tagmentation allowing fast (<24 h) and cost-effective species level identification and strain level differentiation using the MinION portable sequencing platform (ON-rep-seq). DNA library preparation for 96 isolates takes less than 5 h and ensures highly reproducible distribution of reads that can be used to generate strain level specific read length counts profiles (LCp). We have developed a pipeline that by correcting reads error within peaks of LCp generates a set of high quality (>99%) consensus reads. Whereas, the information from high quality reads is used to retrieve species level taxonomy, comparison of LCp allows for strain level differentiation.
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