Glycopeptides such as vancomycin are the treatment of choice for infections due to methicillin-resistant Staphylococcus aureus. This study describes the identification of high-level vancomycin-resistant S. aureus (VRSA) isolates in a polymicrobial biofilm within an indwelling nephrostomy tube in a patient in New York. S. aureus, Enterococcus faecalis, Enterococcus faecium, Micrococcus species, Morganella morganii, and Pseudomonas aeruginosa were isolated from the biofilm. For VRSA isolates, vancomycin MICs ranged from 32 to >128 g/ml. VRSA isolates were also resistant to aminoglycosides, fluoroquinolones, macrolides, penicillin, and tetracycline but remained susceptible to chloramphenicol, linezolid, rifampin, and trimethoprim-sulfamethoxazole. The vanA gene was localized to a plasmid of ϳ100 kb in VRSA and E. faecium isolates from the biofilm. Plasmid analysis revealed that the VRSA isolate acquired the 100-kb E. faecium plasmid, which was then maintained without integration into the MRSA plasmid. The tetracycline resistance genes tet(U) and tet(S), not previously detected in S. aureus isolates, were identified in the VRSA isolates. Additional resistance elements in the VRSA isolate included a multiresistance gene cluster, ermB-aadE-sat4-aphA-3, msrA (macrolide efflux), and the bifunctional aminoglycoside resistance gene aac(6)-aph(2؆)-Ia. Multiple combinations of resistance genes among the various isolates of staphylococci and enterococci, including vanA, tet(S), and tet(U), illustrate the dynamic nature of gene acquisition and loss within and between bacterial species throughout the course of infection. The potential for interspecies transfer of antimicrobial resistance genes, including resistance to vancomycin, may be enhanced by the microenvironment of a biofilm.

Whole-genome sequencing (WGS) is a newer alternative for tuberculosis (TB) diagnostics and is capable of providing rapid drug resistance profiles while performing species identification and capturing the data necessary for genotyping. Our laboratory developed and validated a comprehensive and sensitive WGS assay to characterize Mycobacterium tuberculosis and other M. tuberculosis complex (MTBC) strains, composed of a novel DNA extraction, optimized library preparation, pairedend WGS, and an in-house-developed bioinformatics pipeline. This new assay was assessed using 608 MTBC isolates, with 146 isolates during the validation portion of this study and 462 samples received prospectively. In February 2016, this assay was implemented to test all clinical cases of MTBC in New York State, including isolates and early positive Bactec mycobacterial growth indicator tube (MGIT) 960 cultures from primary specimens. Since the inception of the assay, we have assessed the accuracy of identification of MTBC strains to the species level, concordance with culture-based drug susceptibility testing (DST), and turnaround time. Species identification by WGS was determined to be 99% accurate. Concordance between drug resistance profiles generated by WGS and culture-based DST methods was 96% for eight drugs, with an average resistance-predictive value of 93% and susceptiblepredictive value of 96%. This single comprehensive WGS assay has replaced seven molecular assays and has resulted in resistance profiles being reported to physicians an average of 9 days sooner than with culture-based DST for first-line drugs and 32 days sooner for second-line drugs.

For Salmonella enterica serovar Enteritidis, 85% of isolates can be classified into 5 pulsed-field gel electrophoresis (PFGE) types. However, PFGE has limited discriminatory power for outbreak detection. Although whole-genome sequencing has been found to improve discrimination of outbreak clusters, whether this procedure can be used in real-time in a public health laboratory is not known. Therefore, we conducted a retrospective and prospective analysis. The retrospective study investigated isolates from 1 confirmed outbreak. Additional cases could be attributed to the outbreak strain on the basis of whole-genome data. The prospective study included 58 isolates obtained in 2012, including isolates from 1 epidemiologically defined outbreak. Whole-genome sequencing identified additional isolates that could be attributed to the outbreak, but which differed from the outbreak-associated PFGE type. Additional putative outbreak clusters were detected in the retrospective and prospective analyses. This study demonstrates the practicality of implementing this approach for outbreak surveillance in a state public health laboratory.