Eurosurveillance - Volume 24, Issue 4, 24 January 2019

The analysis of transmission of tuberculosis (TB) is challenging in areas with a large migrant population. Standard genotyping may fail to differentiate transmission within the host country from new importations, which is key from an epidemiological perspective.

To propose a new strategy to simplify and optimise cross-border surveillance of tuberculosis and to distinguish between recent transmission in the host country and new importations

We selected 10 clusters, defined by 24-locus mycobacterial interspersed repetitive unit-variable number tandem repeat (MIRU-VNTR), from a population in Spain rich in migrants from eastern Europe, north Africa and west Africa and reanalysed 66 isolates by whole-genome sequencing (WGS). A multiplex-allele-specific PCR was designed to target strain-specific marker single nucleotide polymorphisms (SNPs), identified from WGS data, to optimise the surveillance of the most complex cluster.

In five of 10 clusters not all isolates showed the short genetic distances expected for recent transmission and revealed a higher number of SNPs, thus suggesting independent importations of prevalent strains in the country of origin. In the most complex cluster, rich in Moroccan cases, a multiplex allele-specific oligonucleotide-PCR (ASO-PCR) targeting the marker SNPs for the transmission subcluster enabled us to prospectively identify new secondary cases. The ASO-PCR-based strategy was transferred and applied in Morocco, demonstrating that the strain was prevalent in the country.

We provide a new model for optimising the analysis of cross-border surveillance of TB transmission in the scenario of global migration.

Mandatory reporting of methicillin-resistant Staphylococcus aureus (MRSA) bloodstream infections (BSI) has occurred in England for over 15years. Epidemiological information is recorded, but routine collection of isolates for characterisation has not been routinely undertaken. Ongoing developments in whole-genome sequencing (WGS) have demonstrated its value in outbreak investigations and for determining the spread of antimicrobial resistance and bacterial population structure. Benefits of adding genomics to routine epidemiological MRSA surveillance are unknown.

To determine feasibility and potential utility of adding genomics to epidemiological surveillance of MRSA.

We conducted an epidemiological and genomic survey of MRSA BSI in England over a 1-year period (1 October 2012­–30 September 2013).

During the study period, 903 cases of MRSA BSI were reported; 425 isolates were available for sequencing of which, 276 (65%) were clonal complex (CC) 22. Addition of 64 MRSA genomes from published outbreak investigations showed that the study genomes could provide context for outbreak isolates and supported cluster identification. Comparison to other MRSA genome collections demonstrated variation in clonal diversity achieved through different sampling strategies and identified potentially high-risk clones e.g. USA300 and local expansion of CC5 MRSA in South West England.

We demonstrate the potential utility of combined epidemiological and genomic MRSA BSI surveillance to determine the national population structure of MRSA, contextualise previous MRSA outbreaks, and detect potentially high-risk lineages. These findings support the integration of epidemiological and genomic surveillance for MRSA BSI as a step towards a comprehensive surveillance programme in England.

During summer 2016, Norway observed an increase in Salmonella enterica subsp. enterica serovar Chester cases among travellers to Greece.

Our aim was to investigate genetic relatedness of S. Chester for surveillance and outbreak detection by core genome multilocus sequence typing (cgMLST) and compare the results to genome mapping.

We included S. Chester isolates from 51 cases of salmonellosis between 2000 and 2016. Paired-end sequencing (2 × 250 bp) was performed on Illumina MiSeq. Genetic relatedness by cgMLST for Salmonellaenterica subsp. enterica, including 3,002 genes and seven housekeeping genes, was compared by reference genome mapping with CSI Phylogeny version 1.4 and conventional MLST.

Confirmed travel history was available for 80% of included cases, to Europe (n = 13), Asia (n = 12) and Africa (n = 16). Isolates were distributed into four phylogenetic clusters corresponding to geographical regions. Sequence type (ST) ST411 and a single-locus variant ST5260 (n = 17) were primarily acquired in southern Europe, ST1954 (n = 15) in Africa, ST343 (n = 11) and ST2063 (n = 8) primarily in Asia. Part of the European cluster was further divided into a Greek (n = 10) and a Cypriot (n = 4) cluster. All isolates in the African cluster displayed resistance to ≥ 1 class of antimicrobials, while resistance was rare in the other clusters.

Whole genome sequencing of S. Chester in Norway showed four geographically distinct clusters, with a possible outbreak occurring during summer 2016 related to Greece. We recommend public health institutes to implement cgMLST-based real-time Salmonellaenterica surveillance for early and accurate detection of future outbreaks and further development of cluster cut-offs.

Water supply and air-conditioner cooling towers (ACCT) are potential sources of Legionella pneumophila infection in people. During outbreaks, traditional typing methods cannot sufficiently segregate L. pneumophila strains to reliably trace back transmissions to these artificial water systems. Moreover, because multiple L. pneumophila strains may be present within these systems, methods to adequately distinguish strains are needed. Whole genome sequencing (WGS) and core genome multilocus sequence typing (cgMLST), with their higher resolution are helpful in this respect. In summer 2017, the health administration of the city of Basel detected an increase of L. pneumophila infections compared with previous months, signalling an outbreak.

We aimed to identify L. pneumophila strains populating suspected environmental sources of the outbreak, and to assess the relations between these strains and clinical outbreak strains.

An epidemiological and WGS-based microbiological investigation was performed, involving isolates from the local water supply and two ACCTs (n = 60), clinical outbreak and non-outbreak related isolates from 2017 (n = 8) and historic isolates from 2003–2016 (n = 26).

In both ACCTs, multiple strains were found. Phylogenetic analysis of the ACCT isolates showed a diversity of a few hundred allelic differences in cgMLST. Furthermore, two isolates from one ACCT showed no allelic differences to three clinical isolates from 2017. Five clinical isolates collected in the Basel area in the last decade were also identical in cgMLST to recent isolates from the two ACCTs.

Current outbreak-related and historic isolates were linked to ACCTs, which form a complex environmental habitat where strains are conserved over years.

MALDI-TOF MS represents a new technological era for microbiology laboratories. Improved sample processing and expanded databases have facilitated rapid and direct identification of microorganisms from some clinical samples. Automated analysis of protein spectra from different microbial populations is emerging as a potential tool for epidemiological studies and is expected to impact public health.

To demonstrate how implementation of MALDI-TOF MS has changed the way microorganisms are identified, how its applications keep increasing and its impact on public health and hospital hygiene.

A review of the available literature in PubMED, published between 2009 and 2018, was carried out.

Of 9,709 articles retrieved, 108 were included in the review. They show that rapid identification of a growing number of microorganisms using MALDI-TOF MS has allowed for optimisation of patient management through prompt initiation of directed antimicrobial treatment. The diagnosis of Gram-negative bacteraemia directly from blood culture pellets has positively impacted antibiotic streamlining, length of hospital stay and costs per patient. The flexibility of MALDI-TOF MS has encouraged new forms of use, such as detecting antibiotic resistance mechanisms (e.g. carbapenemases), which provides valuable information in a reduced turnaround time. MALDI-TOF MS has also been successfully applied to bacterial typing.

MALDI-TOF MS is a powerful method for protein analysis. The increase in speed of pathogen detection enables improvement of antimicrobial therapy, infection prevention and control measures leading to positive impact on public health. For antibiotic susceptibility testing and bacterial typing, it represents a rapid alternative to time-consuming conventional techniques.