Large-scale and significant expression from pseudogenes in Sodalis glossinidius – a facultative bacterial endosymbiont

The majority of bacterial genomes have high coding efficiencies, but there are some genomes of intracellular bacteria that have low gene density. The genome of the endosymbiont Sodalis glossinidius contains almost 50 % pseudogenes containing mutations that putatively silence them at the genomic level. We have applied multiple ‘omic’ strategies, combining Illumina and Pacific Biosciences Single-Molecule Real-Time DNA sequencing and annotation, stranded RNA sequencing and proteome analysis to better understand the transcriptional and translational landscape of Sodalis pseudogenes, and potential mechanisms for their control. Between 53 and 74 % of the Sodalis transcriptome remains active in cell-free culture. The mean sense transcription from coding domain sequences (CDSs) is four times greater than that from pseudogenes. Comparative genomic analysis of six Illumina-sequenced Sodalis isolates from different host Glossina species shows pseudogenes make up ~40 % of the 2729 genes in the core genome, suggesting that they are stable and/or that Sodalis is a recent introduction across the genus Glossina as a facultative symbiont. These data shed further light on the importance of transcriptional and translational control in deciphering host–microbe interactions. The combination of genomics, transcriptomics and proteomics gives a multidimensional perspective for studying prokaryotic genomes with a view to elucidating evolutionary adaptation to novel environmental niches

Rapid resistome mapping using nanopore sequencing

The emergence of antibiotic resistance in human pathogens has become a major threat to modern medicine. The outcome of antibiotic treatment can be affected by the composition of the gut. Accordingly, knowledge of the gut resistome composition could enable more effective and individualized treatment of bacterial infections. Yet, rapid workflows for resistome characterization are lacking. To address this challenge we developed the poreFUME workflow that deploys functional metagenomic selections and nanopore sequencing to resistome mapping. We demonstrate the approach by functionally characterizing the gut resistome of an ICU (intensive care unit) patient. The accuracy of the poreFUME pipeline is with &gt;97% sufficient for the annotation of antibiotic resistance genes. The poreFUME pipeline provides a promising approach for efficient resistome profiling that could inform antibiotic treatment decisions in the future.</p

Shotgun metagenome data of a defined mock community using Oxford Nanopore, PacBio and Illumina technologies.

Metagenomic sequence data from defined mock communities is crucial for the assessment of sequencing platform performance and downstream analyses, including assembly, binning and taxonomic assignment. We report a comparison of shotgun metagenome sequencing and assembly metrics of a defined microbial mock community using the Oxford Nanopore Technologies (ONT) MinION, PacBio and Illumina sequencing platforms. Our synthetic microbial community BMock12 consists of 12 bacterial strains with genome sizes spanning 3.2-7.2 Mbp, 40-73% GC content, and 1.5-7.3% repeats. Size selection of both PacBio and ONT sequencing libraries prior to sequencing was essential to yield comparable relative abundances of organisms among all sequencing technologies. While the Illumina-based metagenome assembly yielded good coverage with few misassemblies, contiguity was greatly improved by both, Illumina + ONT and Illumina + PacBio hybrid assemblies but increased misassemblies, most notably in genomes with high sequence similarity to each other. Our resulting datasets allow evaluation and benchmarking of bioinformatics software on Illumina, PacBio and ONT platforms in parallel

Improving sequencing by tunneling with multiplexing and cross-correlations

Sequencing by tunneling is a next-generation approach to read single-base information using electronic tunneling transverse to the single-stranded DNA (ssDNA) backbone while the latter is translocated through a narrow channel. The original idea considered a single pair of electrodes to read out the current and distinguish the bases [1, 2]. Here, we propose an improvement to the original sequencing by tunneling method, in which $N$ pairs of electrodes are built in series along a synthetic nanochannel. While the ssDNA is forced through the channel using a longitudinal field it passes by each pair of electrodes for long enough time to gather a minimum of $m$ tunneling current measurements, where $m$ is determined by the level of sequencing error desired. Each current time series for each nucleobase is then cross-correlated together, from which the DNA bases can be distinguished. We show using random sampling of data from classical molecular dynamics, that indeed the sequencing error is significantly reduced as the number of pairs of electrodes, $N$, increases. Compared to the sequencing ability of a single pair of electrodes, cross-correlating $N$ pairs of electrodes is exponentially better due to the approximate log-normal nature of the tunneling current probability distributions. We have also used the Fenton-Wilkinson approximation to analytically describe the mean and variance of the cross-correlations that are used to distinguish the DNA bases. The method we suggest is particularly useful when the measurement bandwidth is limited, allowing a smaller electrode gap residence time while still promising to consistently identify the DNA bases correctly.Comment: 8 pages, 4 figure

Detailed evaluation of data analysis tools for subtyping of bacterial isolates based on whole genome sequencing : Neisseria meningitidis as a proof of concept

Whole genome sequencing is increasingly recognized as the most informative approach for characterization of bacterial isolates. Success of the routine use of this technology in public health laboratories depends on the availability of well-characterized and verified data analysis methods. However, multiple subtyping workflows are now often being used for a single organism, and differences between them are not always well described. Moreover, methodologies for comparison of subtyping workflows, and assessment of their performance are only beginning to emerge. Current work focuses on the detailed comparison of WGS-based subtyping workflows and evaluation of their suitability for the organism and the research context in question. We evaluated the performance of pipelines used for subtyping of Neisseria meningitidis, including the currently widely applied cgMLST approach and different SNP-based methods. In addition, the impact of the use of different tools for detection and filtering of recombinant regions and of different reference genomes were tested. Our benchmarking analysis included both assessment of technical performance of the pipelines and functional comparison of the generated genetic distance matrices and phylogenetic trees. It was carried out using replicate sequencing datasets of high- and low-coverage, consisting mainly of isolates belonging to the clonal complex 269. We demonstrated that cgMLST and some of the SNP-based subtyping workflows showed very good performance characteristics and highly similar genetic distance matrices and phylogenetic trees with isolates belonging to the same clonal complex. However, only two of the tested workflows demonstrated reproducible results for a group of more closely related isolates. Additionally, results of the SNP-based subtyping workflows were to some level dependent on the reference genome used. Interestingly, the use of recombination-filtering software generally reduced the similarity between the gene-by-gene and SNP-based methodologies for subtyping of N. meningitidis. Our study, where N. meningitidis was taken as an example, clearly highlights the need for more benchmarking comparative studies to eventually contribute to a justified use of a specific WGS data analysis workflow within an international public health laboratory context

Ultra-high resolution HLA genotyping and allele discovery by highly multiplexed cDNA amplicon pyrosequencing

Background: High-resolution HLA genotyping is a critical diagnostic and research assay. Current methods rarely achieve unambiguous high-resolution typing without making population-specific frequency inferences due to a lack of locus coverage and difficulty in exon-phase matching. Achieving high-resolution typing is also becoming more challenging with traditional methods as the database of known HLA alleles increases. Results: We designed a cDNA amplicon-based pyrosequencing method to capture 94% of the HLA class I open-reading-frame with only two amplicons per sample, and an analogous method for class II HLA genes, with a primary focus on sequencing the DRB loci. We present a novel Galaxy server-based analysis workflow for determining genotype. During assay validation, we performed two GS Junior sequencing runs to determine the accuracy of the HLA class I amplicons and DRB amplicon at different levels of multiplexing. When 116 amplicons were multiplexed, we unambiguously resolved 99%of class I alleles to four- or six-digit resolution, as well as 100% unambiguous DRB calls. The second experiment, with 271 multiplexed amplicons, missed some alleles, but generated high-resolution, concordant typing for 93% of class I alleles, and 96% for DRB1 alleles. In a third, preliminary experiment we attempted to sequence novel amplicons for other class II loci with mixed success. Conclusions: The presented assay is higher-throughput and higher-resolution than existing HLA genotyping methods, and suitable for allele discovery or large cohort sampling. The validated class I and DRB primers successfully generated unambiguously high-resolution genotypes, while further work is needed to validate additional class II genotyping amplicons

The evolution of the natural killer complex; a comparison between mammals using new high-quality genome assemblies and targeted annotation.

Natural killer (NK) cells are a diverse population of lymphocytes with a range of biological roles including essential immune functions. NK cell diversity is in part created by the differential expression of cell surface receptors which modulate activation and function, including multiple subfamilies of C-type lectin receptors encoded within the NK complex (NKC). Little is known about the gene content of the NKC beyond rodent and primate lineages, other than it appears to be extremely variable between mammalian groups. We compared the NKC structure between mammalian species using new high-quality draft genome assemblies for cattle and goat; re-annotated sheep, pig, and horse genome assemblies; and the published human, rat, and mouse lemur NKC. The major NKC genes are largely in the equivalent positions in all eight species, with significant independent expansions and deletions between species, allowing us to propose a model for NKC evolution during mammalian radiation. The ruminant species, cattle and goats, have independently evolved a second KLRC locus flanked by KLRA and KLRJ, and a novel KLRH-like gene has acquired an activating tail. This novel gene has duplicated several times within cattle, while other activating receptor genes have been selectively disrupted. Targeted genome enrichment in cattle identified varying levels of allelic polymorphism between the NKC genes concentrated in the predicted extracellular ligand-binding domains. This novel recombination and allelic polymorphism is consistent with NKC evolution under balancing selection, suggesting that this diversity influences individual immune responses and may impact on differential outcomes of pathogen infection and vaccination

Diversity oriented biosynthesis via accelerated evolution of modular gene clusters.

Erythromycin, avermectin and rapamycin are clinically useful polyketide natural products produced on modular polyketide synthase multienzymes by an assembly-line process in which each module of enzymes in turn specifies attachment of a particular chemical unit. Although polyketide synthase encoding genes have been successfully engineered to produce novel analogues, the process can be relatively slow, inefficient, and frequently low-yielding. We now describe a method for rapidly recombining polyketide synthase gene clusters to replace, add or remove modules that, with high frequency, generates diverse and highly productive assembly lines. The method is exemplified in the rapamycin biosynthetic gene cluster where, in a single experiment, multiple strains were isolated producing new members of a rapamycin-related family of polyketides. The process mimics, but significantly accelerates, a plausible mechanism of natural evolution for modular polyketide synthases. Detailed sequence analysis of the recombinant genes provides unique insight into the design principles for constructing useful synthetic assembly-line multienzymes