No abstract

Sequencing by translocating DNA fragments through an array of nanopores is a rapidly maturing technology that offers faster and cheaper sequencing than other approaches. However, accurately deciphering the DNA sequence from the noisy and complex electrical signal is challenging. Here, we report Chiron, the first deep learning model to achieve end-to-end basecalling and directly translate the raw signal to DNA sequence without the error-prone segmentation step. Trained with only a small set of 4,000 reads, we show that our model provides state-of-the-art basecalling accuracy, even on previously unseen species. Chiron achieves basecalling speeds of more than 2,000 bases per second using desktop computer graphics processing units.

Sequencing by translocating DNA fragments through an array of nanopores is a rapidly maturing technology which offers faster and cheaper sequencing than other approaches. However, accurately deciphering the DNA sequence from the noisy and complex electrical signal is challenging. Here, we report the first deep learning model, named Chiron, that can directly translate the raw signal to DNA sequence without the error-prone segmentation step. We show that our model provides state-of-the-art basecalling accuracy when trained with only a small set of 4000 reads. Chiron achieves basecalling speeds of over 2000 bases per second using desktop computer graphics processing units, making it competitive with other deep-learning basecalling algorithms.

A better understanding of the genomic changes that facilitate the emergence and spread of drug-resistant Mycobacterium tuberculosis strains is currently required. Here, we report the use of the MinION nanopore sequencer (Oxford Nanopore Technologies) to sequence and assemble an extensively drug-resistant (XDR) isolate, which is part of a modern Beijing sub-lineage strain, prevalent in Western Province, Papua New Guinea. Using 238-fold coverage obtained from a single flow-cell, de novo assembly of nanopore reads resulted into one contiguous assembly with 99.92 % assembly accuracy. Incorporation of complementary short read sequences (Illumina) as part of consensus error correction resulted in a 4 404 064 bp genome with 99.98 % assembly accuracy. This assembly had an average nucleotide identity of 99.7 % relative to the reference genome, H37Rv. We assembled nearly all GC-rich repetitive PE/PPE family genes (166/168) and identified variants within these genes. With an estimated genotypic error rate of 5.3 % from MinION data, we demonstrated identification of variants to include the conventional drug resistance mutations, and those that contribute to the resistance phenotype (efflux pumps/transporter) and virulence. Reference-based alignment of the assembly allowed detection of deletions and insertions. MinION sequencing provided a fully annotated assembly of a transmissible XDR strain from an endemic setting and showed its utility to provide further understanding of genomic processes within Mycobacterium tuberculosis.

BackgroundDetection of genomic inversions remains challenging. Many existing methods primarily target inzversions with a non repetitive breakpoint, leaving inverted repeat (IR) mediated non-allelic homologous recombination (NAHR) inversions largely unexplored.ResultWe present npInv, a novel tool specifically for detecting and genotyping NAHR inversion using long read sub-alignment of long read sequencing data. We benchmark npInv with other tools in both simulation and real data. We use npInv to generate a whole-genome inversion map for NA12878 consisting of 30 NAHR inversions (of which 15 are novel), including all previously known NAHR mediated inversions in NA12878 with flanking IR less than 7kb. Our genotyping accuracy on this dataset was 94%. We used PCR to confirm the presence of two of these novel inversions. We show that there is a near linear relationship between the length of flanking IR and the minimum inversion size, without inverted repeats.ConclusionThe application of npInv shows high accuracy in both simulation and real data. The results give deeper insight into understanding inversion.Electronic supplementary materialThe online version of this article (10.1186/s12859-018-2252-9) contains supplementary material, which is available to authorized users.

Purpose: To explore phenotype-genotype correlations that may contribute to a better understanding of diabetic retinopathy (DR). Procedures: An exploratory association study was performed to identify genetic variants associated with non-proliferative DR (NPDR) in 307 type 2 diabetic patients who were previously stratified into 3 different phenotypes of NPDR progression. The 307 patients were genotyped for 174 single nucleotide polymorphisms of 11 candidate genes (ACE, AGER, AKR1B1, ICAM1, MTHFR, NOS1, NOS3, PPARGC1A, TGFB1, TNF and VEGFA). Results: Significant associations were observed for PPARGC1A rs16874120 with phenotype A (odds ratio, OR = 0.60, 95% confidence interval, CI 0.36-0.99), ICAM1 rs1801714 with phenotype B (OR = 3.32, 95% CI 1.05-10.50) and both PPARGC1A rs10213440 (OR = 2.00, 95% CI 1.07-3.73) and MTHFR rs1801133 (OR = 1.84, 95% CI 1.08-3.11) with phenotype C. Conclusions: Results indicate that specific gene variants in ICAM1, PPARGC1A and MTHFR are associated with different NPDR phenotypes, being likely candidates to explain different disease mechanisms underlying the different phenotypes. This is the first study to show correlations between specific gene variants and NPDR phenotypes, opening new perspectives on DR.

Background Klebsiella pneumoniae frequently harbours multidrug resistance, and current diagnostics struggle to rapidly identify appropriate antibiotics to treat these bacterial infections. The MinION device can sequence native DNA and RNA in real time, providing an opportunity to compare the utility of DNA and RNA for prediction of antibiotic susceptibility. However, the effectiveness of bacterial direct RNA sequencing and base-calling has not previously been investigated. This study interrogated the genome and transcriptome of 4 extensively drug-resistant (XDR) K. pneumoniae clinical isolates; however, further antimicrobial susceptibility testing identified 3 isolates as pandrug-resistant (PDR). Results The majority of acquired resistance (≥75%) resided on plasmids including several megaplasmids (≥100 kb). DNA sequencing detected most resistance genes (≥70%) within 2 hours of sequencing. Neural network–based base-calling of direct RNA achieved up to 86% identity rate, although ≤23% of reads could be aligned. Direct RNA sequencing (with ∼6 times slower pore translocation) was able to identify (within 10 hours) ≥35% of resistance genes, including those associated with resistance to aminoglycosides, β-lactams, trimethoprim, and sulphonamide and also quinolones, rifampicin, fosfomycin, and phenicol in some isolates. Direct RNA sequencing also identified the presence of operons containing up to 3 resistance genes. Polymyxin-resistant isolates showed a heightened transcription of phoPQ (≥2-fold) and the pmrHFIJKLM operon (≥8-fold). Expression levels estimated from direct RNA sequencing displayed strong correlation (Pearson: 0.86) compared to quantitative real-time PCR across 11 resistance genes. Conclusion Overall, MinION sequencing rapidly detected the XDR/PDR K. pneumoniae resistome, and direct RNA sequencing provided accurate estimation of expression levels of these genes.

Background Rapid diagnosis and appropriate treatment is imperative in bacterial sepsis due increasing risk of mortality with every hour without appropriate antibiotic therapy. Atypical infections with fastidious organisms may take more than 4 days to diagnose leading to calls for improved methods for rapidly diagnosing sepsis. Capnocytophaga canimorsus is a slow-growing, fastidious gram-negative bacillus which is a common commensal within the mouths of dogs, but rarely cause infections in humans. C. canimorsus sepsis risk factors include immunosuppression, alcoholism and elderly age. Here we report on the application of emerging nanopore sequencing methods to rapidly diagnose an atypical case of C. canimorsus septic shock. Case presentation A 62 year-old female patient was admitted to an intensive care unit with septic shock and multi-organ failure six days after a reported dog bite. Blood cultures were unable to detect a pathogen after 3 days despite observed intracellular bacilli on blood smears. Real-time nanopore sequencing was subsequently employed on whole blood to detect Capnocytophaga canimorsus in 19 h. The patient was not immunocompromised and did not have any other known risk factors. Whole-genome sequencing of clinical sample and of the offending dog’s oral swabs showed near-identical C. canimorsus genomes. The patient responded to antibiotic treatment and was discharged from hospital 31 days after admission. Conclusions Use of real-time nanopore sequencing reduced the time-to-diagnosis of Capnocytophaga canimorsus in this case from 6.25 days to 19 h. Capnocytophaga canimorsus should be considered in cases of suspected sepsis involving cat or dog contact, irrespective of the patient’s known risk factors. Electronic supplementary material The online version of this article (10.1186/s12879-019-4173-2) contains supplementary material, which is available to authorized users.