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Multicenter Study
. 2020 Apr 15;70(9):1855-1864.
doi: 10.1093/cid/ciz526.

Cross-transmission Is Not the Source of New Mycobacterium abscessus Infections in a Multicenter Cohort of Cystic Fibrosis Patients

Affiliations
Multicenter Study

Cross-transmission Is Not the Source of New Mycobacterium abscessus Infections in a Multicenter Cohort of Cystic Fibrosis Patients

Ronan M Doyle et al. Clin Infect Dis. .

Abstract

Background: Mycobacterium abscessus is an extensively drug-resistant pathogen that causes pulmonary disease, particularly in cystic fibrosis (CF) patients. Identifying direct patient-to-patient transmission of M. abscessus is critically important in directing an infection control policy for the management of risk in CF patients. A variety of clinical labs have used molecular epidemiology to investigate transmission. However, there is still conflicting evidence as to how M. abscessus is acquired and whether cross-transmission occurs. Recently, labs have applied whole-genome sequencing (WGS) to investigate this further and, in this study, we investigated whether WGS can reliably identify cross-transmission in M. abscessus.

Methods: We retrospectively sequenced the whole genomes of 145 M. abscessus isolates from 62 patients, seen at 4 hospitals in 2 countries over 16 years.

Results: We have shown that a comparison of a fixed number of core single nucleotide variants alone cannot be used to infer cross-transmission in M. abscessus but does provide enough information to replace multiple existing molecular assays. We detected 1 episode of possible direct patient-to-patient transmission in a sibling pair. We found that patients acquired unique M. abscessus strains even after spending considerable time on the same wards with other M. abscessus-positive patients.

Conclusions: This novel analysis has demonstrated that the majority of patients in this study have not acquired M. abscessus through direct patient-to-patient transmission or a common reservoir. Tracking transmission using WGS will only realize its full potential with proper environmental screening, as well as patient sampling.

Keywords: cystic fibrosis; nontuberculous mycobacteria; phylogenomics; transmission; whole-genome sequencing.

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Figures

Figure 1.
Figure 1.
Maximum likelihood SNV tree, using only the earliest isolated sample from all 62 patients. SNVs were identified from mapping reads to the ATCC19977 Mycobacterium abscessus subsp. abscessus reference genome. Sample names are highlighted in color, based on what hospital they were isolated from: Great Ormond Street Hospital, London, United Kingdom; Hospital Clínic, Barcelona, Spain; Hospital de la Santa Creu i Sant Pau, Barcelona, Spain; and Hospital Vall d’Hebron, Barcelona, Spain. The scale bar represents the number of SNVs and the node bootstrap scores below are shown if below 75. Abbreviation: SNV, single nucleotide variant.
Figure 2.
Figure 2.
Frequency of pairwise SNV distances between all isolates. SNVs were identified from mapping sequence reads to Mycobacterium abscessus subsp. abscessus ATCC19977. The full plot includes all samples, while the bottom subsidiary plot only includes isolates that have a pairwise difference between 0 and 1000 SNVs. Abbreviations: ABS; Mycobacterium abscessus subsp. abscessus; BOL, Mycobacterium abscessus subsp. bolletii; MAS, Mycobacterium abscessus subsp. massiliense; SNV, single nucleotide variant; ST, sequence type.
Figure 3.
Figure 3.
Maximum likelihood SNV tree for all ST-26 isolates. SNVs were identified from mapping reads to a de novo assembled study isolate genome (ldn_gos_2_520). Samples are highlighted based on inclusion in sequence clusters. The tree is annotated with the presence (black) and absence (white) of accessory genes, as well as the presence of AMR-associated genes and mutations. This includes the presence of a functional erm(41) gene conferring inducible resistance to macrolides; the presence of 2 rrl mutations conferring high-level macrolide resistance; and the presence of a mutation in rrs conferring high-level amikacin resistance. The scale bar represents the number of SNVs and the node bootstrap scores below are shown if below 75. Abbreviations: AMR, antimicrobial resistance; SNV, single nucleotide variant.
Figure 4.
Figure 4.
Maximum likelihood SNV tree for all ST-1 isolates. SNVs were identified from mapping reads to Mycobacterium abscessus subsp. abscessus ATCC19977. Samples are highlighted based on inclusion in sequence clusters. The tree is annotated with the presence (black) and absence (white) of accessory genes, as well as the presence of AMR-associated genes and mutations. This included the presence of a functional erm(41) gene conferring inducible resistance to macrolides; the presence of 2 rrl mutations conferring high-level macrolide resistance; and the presence of a mutation in rrs conferring high-level amikacin resistance. The scale bar represents the number of SNVs, and the node bootstrap scores below are shown if below 75. Abbreviations: AMR, antimicrobial resistance; SNV, single nucleotide variant.
Figure 5.
Figure 5.
Maximum likelihood SNV tree for all ST-23 and ST-48 isolates. SNVs were identified from mapping reads to Mycobacterium abscessus subsp. massiliense GO 06. Samples are highlighted based on inclusion in sequence clusters. The tree is annotated with the presence (black) and absence (white) of accessory genes, as well as the presence of AMR-associated genes and mutations. This included the presence of a functional erm(41) gene conferring inducible resistance to macrolides; the presence of 2 rrl mutations conferring high-level macrolide resistance; and the presence of a mutation in rrs conferring high-level amikacin resistance. The scale bar represents the number of SNVs and the node bootstrap scores below are shown if below 75. Abbreviations: AMR, antimicrobial resistance; SNV, single nucleotide variant; ST, sequence typing.

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