Exploring the potential of Oxford Nanopore Technologies sequencing for Mycobacterium tuberculosis sequencing: An assessment of R10 flowcells and V14 chemistry.

Oxford Nanopore Technologies (ONT) sequencing is a promising technology. We assessed the performance of the new ONT R10 flowcells and V14 rapid sequencing chemistry for Mtb whole genome sequencing of Mycobacterium tuberculosis (Mtb) DNA extracted from clinical primary liquid cultures (CPLCs). Using the recommended protocols for MinION Mk1C, R10.4.1 MinION flowcells, and the ONT Rapid Sequencing Kit V14 on six CPLC samples, we obtained a pooled library yield of 10.9 ng/µl, generated 1.94 Gb of sequenced bases and 214k reads after 48h in a first sequencing run. Only half (49%) of all generated reads met the Phred Quality score threshold (>8). To assess if the low data output and sequence quality were due to impurities present in DNA extracted directly from CPLCs, we added a pre-library preparation bead-clean-up step and included purified DNA obtained from an Mtb subculture as a control sample in a second sequencing run. The library yield for DNA extracted from four CPLCs and one Mtb subculture (control) was similar (10.0 ng/µl), 2.38 Gb of bases and 822k reads were produced. The quality was slightly better with 66% of the produced reads having a Phred Quality >8. A third run of DNA from six CPLCs with bead clean-up pre-processing produced a low library yield (±1 Gb of bases, 166k reads) of low quality (51% of reads with a Phred Quality score >8). A median depth of coverage above 10× was only achieved for five of 17 (29%) sequenced libraries. Compared to Illumina WGS of the same samples, accurate lineage predictions and full drug resistance profiles from the generated ONT data could not be determined by TBProfiler. Further optimization of the V14 ONT rapid sequencing chemistry and library preparation protocol is needed for clinical Mtb WGS applications.

Genomic transmission clusters and circulating lineages of Mycobacterium tuberculosis among refugees residing in refugee camps in Ethiopia.

BACKGROUND: Understanding the transmission dynamics of Mycobacterium tuberculosis (Mtb) could benefit the design of tuberculosis (TB) prevention and control strategies for refugee populations. Whole Genome Sequencing (WGS) has not yet been used to document the Mtb transmission dynamics among refugees in Ethiopia. We applied WGS to accurately identify transmission clusters and Mtb lineages among TB cases in refugee camps in Ethiopia. METHOD AND DESIGN: We conducted a cross-sectional study of 610 refugees in refugee camps in Ethiopia presenting with symptoms of TB. WGS data of 67 isolates was analyzed using the Maximum Accessible Genome for Mtb Analysis (MAGMA) pipeline; iTol and FigTree were used to visualize phylogenetic trees, lineages, and the presence of transmission clusters. RESULTS: Mtb culture-positive refugees originated from South Sudan (52/67, 77.6%), Somalia (9/67, 13.4%). Eritrea (4/67, 6%), and Sudan (2/67, 3%). The majority (52, 77.6%) of the isolates belonged to Mtb lineage (L) 3, and one L9 was identified from a Somalian refugee. The vast majority (82%) of the isolates were pan-susceptible Mtb, and none were multi-drug-resistant (MDR)-TB. Based on the 5-single nucleotide polymorphisms cutoff, we identified eight potential transmission clusters containing 23.9% of the isolates. Contact investigation confirmed epidemiological links with either family or social interaction within the refugee camps or with neighboring refugee camps. CONCLUSION: Four lineages (L1, L3, L4, and L9) were identified, with the majority of strains being L3, reflecting the Mtb L3 dominance in South Sudan, where the majority of refugees originated from. Recent transmission among refugees was relatively low (24%), likely due to the short study period. The improved understanding of the Mtb transmission dynamics using WGS in refugee camps could assist in designing effective TB control programs for refugees.

The MAGMA pipeline for comprehensive genomic analyses of clinical Mycobacterium tuberculosis samples.

BACKGROUND: Whole genome sequencing (WGS) holds great potential for the management and control of tuberculosis. Accurate analysis of samples with low mycobacterial burden, which are characterized by low (<20x) coverage and high (>40%) levels of contamination, is challenging. We created the MAGMA (Maximum Accessible Genome for Mtb Analysis) bioinformatics pipeline for analysis of clinical Mtb samples. METHODS AND RESULTS: High accuracy variant calling is achieved by using a long seedlength during read mapping to filter out contaminants, variant quality score recalibration with machine learning to identify genuine genomic variants, and joint variant calling for low Mtb coverage genomes. MAGMA automatically generates a standardized and comprehensive output of drug resistance information and resistance classification based on the WHO catalogue of Mtb mutations. MAGMA automatically generates phylogenetic trees with drug resistance annotations and trees that visualize the presence of clusters. Drug resistance and phylogeny outputs from sequencing data of 79 primary liquid cultures were compared between the MAGMA and MTBseq pipelines. The MTBseq pipeline reported only a proportion of the variants in candidate drug resistance genes that were reported by MAGMA. Notable differences were in structural variants, variants in highly conserved rrs and rrl genes, and variants in candidate resistance genes for bedaquiline, clofazmine, and delamanid. Phylogeny results were similar between pipelines but only MAGMA visualized clusters. CONCLUSION: The MAGMA pipeline could facilitate the integration of WGS into clinical care as it generates clinically relevant data on drug resistance and phylogeny in an automated, standardized, and reproducible manner.