Shashanka Murthy’s research while affiliated with The Ohio State University and other places

Background: Candida auris is an emerging threat to hospitalized patients and invasive disease is associated with high mortality. This study describes clinical and microbiological characteristics of nine patients identified with C. auris at Ohio State Wexner Medical Center discovered through active surveillance or clinical investigation and uses whole genome sequencing (WGS) to compare isolates. Methods: In November 2022, an active C. auris surveillance program was implemented to screen patients admitted to high-risk units (intensive care units and progressive care units). Bilateral axilla and groin swabs were obtained upon unit admission and, if positive, were submitted for C. auris polymerase chain reaction (PCR) with culture and sensitivity testing. Patients with a positive screening or clinical isolate from November 2022 to November 2023 underwent chart review for clinical characteristics, microbiologic data, and index admission information. For each isolate, DNA was extracted and WGS was performed. Core single nucleotide polymorphism (SNP) variation identified from the sequence data was used to infer genetic relationships among the isolates. Results: Nine patients were identified between November 2022 and November 2023. The clinical and microbiologic characteristics are summarized in Table 1. All patients were hospitalized at various acute care facilities across the state at least once in the preceding 12 months. C. auris was determined to be present on admission for 6 patients. For 5 of these patients, it was their first interaction with our healthcare system. Three patients were not in contact isolation for >3 days before C. auris was identified. Unit wide point-prevalence screening was completed in these cases and no evidence of transmission was found. WGS showed eight of the nine isolates were related with 28 or less core SNP differences between isolates (Figure 1). One isolate (8) was genetically distinct with >45000 core SNP differences. Five isolates were highly related with a range of 4-15 SNP differences. No temporal or spatial overlap at our institution was identified among these five patients. Conclusions: The active surveillance program identified several patients colonized with C. auris in addition to those found through clinical testing. Multiple risk factors for C. auris were identified with high patient mortality (67%). Majority of the isolates were closely related without association with a known outbreak or epidemiologic link, suggesting a possible diffuse common reservoir. Next steps with surveillance in acute care and long-term care facilities will be critical for early detection to halt transmission of this organism.

Background: Whole genome sequencing (WGS) is a relatively new method for analyzing outbreaks and modes of transmission, particularly for multidrug resistant bacteria. This study sought to investigate clusters of patients with genetically related Vancomycin-Resistant Enterococcus spp. (VRE) bacteremia for shared hospital environmental exposures. Methods: All VRE blood culture isolates from patients from July 1, 2021 to June 30, 2022 underwent Illumina WGS. Core single nucleotide polymorphisms (SNPs) were identified, and multi-locus sequence typing (MLST) was performed across the VRE isolates. Clusters were defined as isolates with 15 or fewer core genome SNPs and were investigated for potential transmission routes. For each cluster, patients were evaluated in the 12 weeks before and after the first VRE isolate for shared hospital environmental exposures (hospital unit, patient rooms, procedural rooms, and radiology suites). Hospital units were comprised of patient rooms located geographically together on the same floor of the hospital. Results: A total of 82 VRE isolates underwent WGS. Thirty-eight (46%) clustered genetically with at least one other isolate. Clusters included 2 to 15 patients per group and represented 10 distinct MLST subgroups (Figure 1). Nine hundred and thirty-nine hospital environmental exposures were identified across the 38 patients. For each cluster, there was a total of 341 (36.3%) shared exposures. Shared environmental exposures occurred in radiology suites (35, 38.5%), patient rooms (32, 35.6%) and procedural rooms (23, 25.6%). Of the patients who shared the same hospital unit, 10 (31.3%) had the same patient room with 7 (70%) of them being in the emergency department (ED). Overall, the ED represented 7 (21.9%) of the shared hospital units. Each cluster had at least one shared hospital environmental exposure found. Conclusions: Use of WGS can help investigate outbreak clusters of resistant organisms such as VRE. In this study, nearly half of all VRE blood isolates were able to be segregated into clusters with at least one other isolate. Although VRE colonization of hospital rooms is well described, patient rooms represented the smallest proportion of shared hospital environmental exposures. This study thus suggests other environmental transmission routes such as radiology suites and procedural rooms warrant closer investigation.

Background Cancer is a leading cause of mortality worldwide. By 2040, over 30 million new cancers are predicted, with the greatest cancer burden in low-income countries. In 2015, the UN passed the Sustainable Development Goal 3.4 (SDG 3.4) to tackle the rising burden of non-communicable diseases, which calls for a reduction by a third in premature mortality from non-communicable diseases, including cancer, by 2030. However, there is a paucity of data on premature mortality rates by cancer type. In this study, we examine annual rates of change for cancer-specific premature mortality and classify whether countries are on track to reach SDG 3.4 targets. Methods This is a retrospective, cross-sectional, population-based study investigating premature mortality trends from 2000–19 using the WHO Global Health Estimates data. All cancers combined and thirteen individual cancers in 183 countries were examined by WHO region, World Bank income level, and sex. The risk of premature mortality was calculated for ages 30–69 years, independent of other competing causes of death, using standard life table methods. The primary objective was to compute average annual rate of change in premature mortality from 2000 to 2019. Secondary objectives assessed whether this annual rate of change would be sufficient to reach SDG 3.4. targets for premature mortality by 2030. Findings This study was conducted using data retrieved for the years 2000–19. Premature mortality rates decreased in 138 (75%) of 183 countries across all World Bank income levels and WHO regions, however only eight (4%) countries are likely to meet the SDG 3.4 targets for all cancers combined. Cancers where early detection strategies exist, such as breast and colorectal cancer, have higher declining premature mortality rates in high-income countries (breast cancer 48 [89%] of 54 and colorectal cancer 45 [83%]) than in low-income countries (seven [24%] of 29 and four [14%]). Cancers with primary prevention programmes, such as cervical cancer, have more countries with declining premature mortality rates (high-income countries 50 [93%] of 54 and low-income countries 26 [90%] of 29). Sex-related disparities in premature mortality rates vary across WHO regions, World Bank income groups, and by cancer type. Interpretation There is a greater reduction in premature mortality for all cancers combined and for individual cancer types in high-income countries compared with lower-middle-income and low-income countries. However, most countries will not reach the SDG 3.4 target. Cancers with early detection strategies in place, such as breast and colorectal cancers, are performing poorly in premature mortality compared with cancers with primary prevention measures, such as cervical cancer. Investments toward prevention, early detection, and treatment can potentially accelerate declines in premature mortality. Funding WHO.

The geranium industry, valued at $4 million annually, faces an ongoing Xanthomonas hortorum pv. pelargonii (Xhp) pathogen outbreak. To track and describe the outbreak, we compared the genome structure across historical and globally distributed isolates. Our research revealed Xhp population has not had chromosome rearrangements since 1974 and has three distinct plasmids. In 2012, we found all three plasmids in individual Xhp isolates. However, in 2022, the three plasmids co-integrated into one plasmid named p93. p93 retained putative fitness genes but lost extraneous genomic material. Our findings show that the 2022 strain group of the bacterial plant pathogen Xanthomonas hortorum underwent a plasmid reduction. We also observed several Xanthomonas species from different years, hosts, and continents have similar plasmids to p93, possibly due to shared agricultural settings. We noticed parallels between genome efficiency and reduction that we see across millennia with obligate parasites with increased niche specificity.

Background: Multidrug-resistant organisms (MDROs) are increasingly implicated in nosocomial outbreaks worldwide. We evaluated whole-genome sequencing (WGS) as an adjunctive epidemiological tool to identify infection clusters and MDRO transmission in the healthcare setting. Methods: Clinical isolates of carbapenem-resistant Enterobacterales (CRE) from July 1, 2021, to June 30, 2022, underwent Illumina WGS. Assembled genomes were taxonomically classified with GTDB-Tk software and were typed using multilocus sequence typing (MLST). Average nucleotide identity (ANI) was calculated between genomes. Numbers of differences among core single-nucleotide polymorphisms (SNPs) were calculated for pairs within taxonomic groups, and the data were evaluated in the context of patient dates and locations of care obtained from the electronic medical record. Results: In total, 39 CRE isolates underwent WGS (Fig. 1). Klebsiella pneumoniae represented the largest number of isolates (n = 18). Using MLST, 2 distinct groups of K. pneumoniae were identified (ST307 and ST258) with 5 and 4 isolates, respectively (Fig. 2). Within ST307, SNP differences ranged between 8 and 115. 3 isolates (CRE8, CRE10, and CRE12) were collected within 4 weeks of each other and had ≤26 pairwise SNP differences. Notably, CRE8 and CRE10 were located on the same unit at the same time and used the same MRI scanner on the same day. CRE35 had >95 SNP differences and was admitted 8 months prior to others in ST307 but had surgery in the same OR as CRE8. Within ST258, pairwise comparison of samples revealed 139–588 SNP differences. CRE21, CRE31, and CRE33 had SNP differences of ≤150. These patients were in the same hospital room (CRE33 and CRE21) and unit (CRE31 and CRE33), but they did not overlap temporally. CRE37 had >580 SNP differences, with no overlap in hospitalization dates or locations with other patients. Conclusions: Two closely related K. pneumoniae isolate populations were identified using WGS. Strong temporal and spatial commonalities were identified among isolates with few SNP differences. Isolate pairs with intermediate SNP differences shared spatial commonalities, suggesting possible indirect transmission between patients. No common exposures were identified for pairs with large numbers of SNP differences. WGS is an evolving tool to detect outbreak clonal populations of MDRO not identified through traditional epidemiologic techniques. WGS can provide insight into transmission patterns and the role of environmental contamination in propagating these nosocomial infections. More studies are needed to define the role and clinical significance of isolates with intermediate SNP differences in transmission of these pathogens between hosts and the healthcare environment. Disclosures: None

Quickly understanding the genomic changes that lead to pathogen emergence is necessary to launch mitigation efforts and reduce harm. Often the evolutionary events that result in an epidemic typically remain elusive long after an outbreak, which is particularly true for plant pathogens. To rapidly define the consequential evolutionary events result in pathogen emergence, we tracked in real-time a 2022 bacterial plant disease outbreak in US geranium (Pelargonium x hortorum) caused by Xhp2022, a novel lineage of Xanthomonas hortorum. Genomes from 31 Xhp2022 isolates from seven states showed limited chromosomal variation, and all contained a single plasmid (p93). Time tree and SNP whole genome analysis estimated that Xhp2022 emerged in the early 2020s. Phylogenomic analysis determined that p93 resulted from cointegration of three plasmids (p31, p45, and p66) present in a 2012 outbreak. p31, p45 and p66 were individually found in varying abundance across X. hortorum isolates from historical outbreaks dating to 1974 suggesting these plasmids were maintained in the broader metapopulation. p93 specifically arose from two co-integration events from homologous and Tn3 and XerC-mediated site-specific recombination. Although p93 suffered a 49kb nucleotide reduction, it maintained critical fitness gene functions encoding, for example, metal resistance and virulence factors, which were likely selected by the ornamental production system. Overall we demonstrate how rapid sequencing of current and historical isolates track the evolutionary history of an emerging, ongoing threat. We show a recent, tractable event of genome reduction for niche adaptation typically observed over millennia in obligate and fastidious pathogens.