Shiga Toxin-Producing Escherichia coli Testing in New York 2011-2022 Reveals Increase in Non-O157 Identifications.

Shiga toxin-producing Escherichia coli (STEC) are an important cause of bacterial enteric infection. STEC strains cause serious human gastrointestinal disease, which may result in life-threatening complications such as hemolytic uremic syndrome. They have the potential to impact public health due to diagnostic challenges of identifying non-O157 strains in the clinical laboratory. The Wadsworth Center (WC), the public health laboratory of the New York State Department of Health, has isolated and identified non-O157 STEC for decades. A shift from initially available enzyme immunoassay testing to culture-independent diagnostic tests (CIDTs) has increased the uptake of testing at clinical microbiology laboratories. This testing change has resulted in an increased number of specimen submissions to WC. During a 12-year period between 2011 and 2022, WC received 5037 broths and/or stool specimens for STEC confirmation from clinical microbiology laboratories. Of these, 3992 were positive for Shiga toxin genes (stx1 and/or stx2) by real-time PCR. Furthermore, culture methods were utilized to isolate, identify, and characterize 2925 STEC from these primary specimens. Notably, WC observed a >200% increase in the number of STEC specimens received in 2021-2022 compared with 2011-2012 and an 18% increase in the number of non-O157 STEC identified using the same methodologies. During the past decade, the WC testing algorithm has been updated to manage the increase in specimens received, while also navigating the novel COVID-19 pandemic, which took priority over other testing for a period of time. This report summarizes updated methods for confirmation, surveillance, and outbreak detection of STEC and describes findings that may be related to our algorithm updates and the increased use of CIDTs, which is starting to elucidate the true incidence of non-O157 STEC.

Implementation of a high-throughput whole genome sequencing approach with the goal of maximizing efficiency and cost effectiveness to improve public health.

This manuscript describes the development of a streamlined, cost-effective laboratory workflow to meet the demands of increased whole genome sequence (WGS) capacity while achieving mandated quality metrics. From 2020 to 2021, the Wadsworth Center Bacteriology Laboratory (WCBL) used a streamlined workflow to sequence 5,743 genomes that contributed sequence data to nine different projects. The combined use of the QIAcube HT, Illumina DNA Prep using quarter volume reactions, and the NextSeq allowed the WCBL to process all samples that required WGS while also achieving a median turn-around time of 7 days (range 4 to 10 days) and meeting minimum sequence quality requirements. Public Health Laboratories should consider implementing these methods to aid in meeting testing requirements within budgetary restrictions. IMPORTANCE: Public Health Laboratories that implement whole genome sequencing (WGS) technologies may struggle to find the balance between sample volume and cost effectiveness. We present a method that allows for sequencing of a variety of bacterial isolates in a cost-effective manner. This report provides specific strategies to implement high-volume WGS, including an innovative, low-cost solution utilizing a novel quarter volume sequencing library preparation. The methods described support the use of high-throughput DNA extraction and WGS within budgetary constraints, strengthening public health responses to outbreaks and disease surveillance.

Challenges Associated with Investigating Salmonella Enteritidis with Low Genomic Diversity in New York State: The Impact of Adjusting Analytical Methods and Correlation with Epidemiological Data.

Defining investigation-worthy genomic clusters among strains of Salmonella Enteritidis is challenging because of their highly clonal nature. We investigated a cluster identified by core genome multilocus sequence typing (cgMLST) consisting of 265 isolates with isolation dates spanning two and a half years. This cluster experienced chaining, growing to a range of 14 alleles. The volume of isolates and broad allele range of this cluster made it difficult to ascertain whether it represented a common-source outbreak. We explored laboratory-based methods to subdivide and refine this cluster. These methods included using cgMLST with a narrower allele range, whole genome multilocus sequence typing (wgMLST) and high-quality single-nucleotide polymorphism (hqSNP) analysis. At each analysis level, epidemiologists retroactively reviewed exposures, geography, and temporality for potential commonalities. Lowering the threshold to 0 alleles using cgMLST proved an effective method to refine this analysis, resulting in this large cluster being subdivided into 34 smaller clusters. Additional analysis by wgMLST and hqSNP provided enhanced cluster resolution, with the majority of clusters being further refined. These analysis methods combined with more stringent allele thresholds and layering of epidemiologic data proved useful in helping to subdivide this large cluster into actionable subclusters.

Spatiotemporal localization of proteins in mycobacteria.

Although prokaryotic organisms lack traditional organelles, they must still organize cellular structures in space and time, challenges that different species solve differently. To systematically define the subcellular architecture of mycobacteria, we perform high-throughput imaging of a library of fluorescently tagged proteins expressed in Mycobacterium smegmatis and develop a customized computational pipeline, MOMIA and GEMATRIA, to analyze these data. Our results establish a spatial organization network of over 700 conserved mycobacterial proteins and reveal a coherent localization pattern for many proteins of known function, including those in translation, energy metabolism, cell growth and division, as well as proteins of unknown function. Furthermore, our pipeline exploits morphologic proxies to enable a pseudo-temporal approximation of protein localization and identifies previously uncharacterized cell-cycle-dependent dynamics of essential mycobacterial proteins. Collectively, these data provide a systems perspective on the subcellular organization of mycobacteria and provide tools for the analysis of bacteria with non-standard growth characteristics.

Whole-Genome Single-Nucleotide Polymorphism (SNP) Analysis Applied Directly to Stool for Genotyping Shiga Toxin-Producing Escherichia coli: an Advanced Molecular Detection Method for Foodborne Disease Surveillance and Outbreak Tracking.

Whole-genome sequencing (WGS) of pathogens from pure culture provides unparalleled accuracy and comprehensive results at a cost that is advantageous compared with traditional diagnostic methods. Sequencing pathogens directly from a primary clinical specimen would help circumvent the need for culture and, in the process, substantially shorten the time to diagnosis and public health reporting. Unfortunately, this approach poses significant challenges because of the mixture of multiple sequences from a complex fecal biomass. The aim of this project was to develop a proof of concept protocol for the sequencing and genotyping of Shiga toxin-producing Escherichia coli (STEC) directly from stool specimens. We have developed an enrichment protocol that reliably achieves a substantially higher DNA yield belonging to E. coli, which provides adequate next-generation sequencing (NGS) data for downstream bioinformatics analysis. A custom bioinformatics pipeline was created to optimize and remove non-E. coli reads, assess the STEC versus commensal E. coli population in the samples, and build consensus sequences based on population allele frequency distributions. Side-by-side analysis of WGS from paired STEC isolates and matched primary stool specimens reveal that this method can reliably be implemented for many clinical specimens to directly genotype STEC and accurately identify clusters of disease outbreak when no STEC isolate is available for testing.

Polar assembly and scaffolding proteins of the virulence-associated ESX-1 secretory apparatus in mycobacteria.

The ESX-1 secretion system is required for pathogenicity of Mycobacterium tuberculosis (Mtb). Despite considerable research, little is known about the structural components of ESX-1, or how these proteins are assembled into the active secretion apparatus. Here, we exploit the functionally related ESX-1 apparatus of Mycobacterium smegmatis (Ms) to show that fluorescently tagged proteins required for ESX-1 activity consistently localize to the cell pole, identified by time-lapse fluoro-microscopy as the non-septal (old) pole. Deletions in Msesx1 prevented polar localization of tagged proteins, indicating the need for specific protein-protein interactions in polar trafficking. Remarkably, expression of the Mtbesx1 locus in Msesx1 mutants restored polar localization of tagged proteins, indicating establishment of the MtbESX-1 apparatus in M. smegmatis. This observation illustrates the cross-species conservation of protein interactions governing assembly of ESX-1, as well as polar localization. Importantly, we describe novel non-esx1-encoded proteins, which affect ESX-1 activity, which colocalize with ESX-1, and which are required for ESX-1 recruitment and assembly. This analysis provides new insights into the molecular assembly of this important determinant of Mtb virulence.

Sporosarcina newyorkensis sp. nov. from clinical specimens and raw cow's milk.

Twelve independent isolates of a gram-positive, endospore-forming rod were recovered from clinical specimens in New York State, USA, and from raw milk in Flanders, Belgium. The 16S rRNA gene sequences for all isolates were identical. The closest species with a validly published name, based on 16S rRNA gene sequence, is Sporosarcina koreensis (97.13 % similarity). DNA-DNA hybridization studies demonstrate that the new isolates belong to a species distinct from their nearest phylogenetic neighbours. The partial sequences of the 23S rRNA gene for the novel strains and their nearest neighbours also provide support for the novel species designation. Maximum-likelihood phylogenetic analysis of the 16S rRNA gene sequences confirmed that the new isolates are in the genus Sporosarcina. The predominant menaquinone is MK-7, the peptidoglycan has the type A4α L-Lys-Gly-D-Glu, and the polar lipids consist of diphosphatidylglycerol, phosphatidylglycerol and phosphatidylethanolamine. The predominant fatty acids are iso-C(14 : 0), iso-C(15 : 0) and anteiso-C(15 : 0). In addition, biochemical and morphological analyses support designation of the twelve isolates as representatives of a single new species within the genus Sporosarcina, for which the name Sporosarcina newyorkensis sp. nov. (type strain 6062(T)  = DSM 23544(T)  = CCUG 59649(T)  = LMG 26022(T)) is proposed.

Psychrobacter sanguinis sp. nov., recovered from four clinical specimens over a 4-year period.

An analysis of 16S rRNA gene sequences from archived clinical reference specimens identified a novel species of the genus Psychrobacter, of which four strains have been independently isolated from human blood. On the basis of 16S rRNA gene sequence similarity, the closest relatives with validly published names were Psychrobacter arenosus R7(T) (98.7%), P. pulmonis CECT 5989(T) (97.7%), P. faecalis Iso-46(T) (97.6%) and P. lutiphocae IMMIB L-1110(T) (97.2%). Maximum-likelihood phylogenetic analysis of 16S rRNA gene sequences showed that the isolates belonged to the genus Psychrobacter and were members of a cluster associated with Psychrobacter sp. PRwf-1, isolated from a silk snapper fish. DNA-DNA relatedness and partial 23S rRNA gene sequences also supported the finding that the isolates belonged to a species distinct from its closest phylogenetic neighbours. The predominant cellular fatty acids were C(18:1)ω9c, C(16:0), summed feature 3 (C(16:1)ω7c and/or iso-C(15:0) 2-OH), summed feature 5 (C(18:2)ω6,9c and/or anteiso-C(18:0)) and C(18:0). Biochemical and morphological analysis further supported the assignment of the four isolates to a novel species. The name Psychrobacter sanguinis sp. nov. is proposed. The type strain is 13983(T) (=DSM 23635(T)=CCUG 59771(T)).