Reoccurring Escherichia coli O157:H7 Strain Linked to Leafy Greens-Associated Outbreaks, 2016-2019.

Genomic characterization of an Escherichia coli O157:H7 strain linked to leafy greens-associated outbreaks dates its emergence to late 2015. One clade has notable accessory genomic content and a previously described mutation putatively associated with increased arsenic tolerance. This strain is a reoccurring, emerging, or persistent strain causing illness over an extended period.

Genomic Surveillance for SARS-CoV-2 Variants: Circulation of Omicron Lineages - United States, January 2022-May 2023.

CDC has used national genomic surveillance since December 2020 to monitor SARS-CoV-2 variants that have emerged throughout the COVID-19 pandemic, including the Omicron variant. This report summarizes U.S. trends in variant proportions from national genomic surveillance during January 2022-May 2023. During this period, the Omicron variant remained predominant, with various descendant lineages reaching national predominance (>50% prevalence). During the first half of 2022, BA.1.1 reached predominance by the week ending January 8, 2022, followed by BA.2 (March 26), BA.2.12.1 (May 14), and BA.5 (July 2); the predominance of each variant coincided with surges in COVID-19 cases. The latter half of 2022 was characterized by the circulation of sublineages of BA.2, BA.4, and BA.5 (e.g., BQ.1 and BQ.1.1), some of which independently acquired similar spike protein substitutions associated with immune evasion. By the end of January 2023, XBB.1.5 became predominant. As of May 13, 2023, the most common circulating lineages were XBB.1.5 (61.5%), XBB.1.9.1 (10.0%), and XBB.1.16 (9.4%); XBB.1.16 and XBB.1.16.1 (2.4%), containing the K478R substitution, and XBB.2.3 (3.2%), containing the P521S substitution, had the fastest doubling times at that point. Analytic methods for estimating variant proportions have been updated as the availability of sequencing specimens has declined. The continued evolution of Omicron lineages highlights the importance of genomic surveillance to monitor emerging variants and help guide vaccine development and use of therapeutics.

Genomic Surveillance for SARS-CoV-2 Variants: Predominance of the Delta (B.1.617.2) and Omicron (B.1.1.529) Variants - United States, June 2021-January 2022.

Genomic surveillance is a critical tool for tracking emerging variants of SARS-CoV-2 (the virus that causes COVID-19), which can exhibit characteristics that potentially affect public health and clinical interventions, including increased transmissibility, illness severity, and capacity for immune escape. During June 2021-January 2022, CDC expanded genomic surveillance data sources to incorporate sequence data from public repositories to produce weighted estimates of variant proportions at the jurisdiction level and refined analytic methods to enhance the timeliness and accuracy of national and regional variant proportion estimates. These changes also allowed for more comprehensive variant proportion estimation at the jurisdictional level (i.e., U.S. state, district, territory, and freely associated state). The data in this report are a summary of findings of recent proportions of circulating variants that are updated weekly on CDC's COVID Data Tracker website to enable timely public health action.† The SARS-CoV-2 Delta (B.1.617.2 and AY sublineages) variant rose from 1% to >50% of viral lineages circulating nationally during 8 weeks, from May 1-June 26, 2021. Delta-associated infections remained predominant until being rapidly overtaken by infections associated with the Omicron (B.1.1.529 and BA sublineages) variant in December 2021, when Omicron increased from 1% to >50% of circulating viral lineages during a 2-week period. As of the week ending January 22, 2022, Omicron was estimated to account for 99.2% (95% CI = 99.0%-99.5%) of SARS-CoV-2 infections nationwide, and Delta for 0.7% (95% CI = 0.5%-1.0%). The dynamic landscape of SARS-CoV-2 variants in 2021, including Delta- and Omicron-driven resurgences of SARS-CoV-2 transmission across the United States, underscores the importance of robust genomic surveillance efforts to inform public health planning and practice.

Effectiveness of two and three mRNA COVID-19 vaccine doses against Omicron- and Delta-Related outpatient illness among adults, October 2021-February 2022.

Background: We estimated SARS-CoV-2 Delta- and Omicron-specific effectiveness of two and three mRNA COVID-19 vaccine doses in adults against symptomatic illness in US outpatient settings. Methods: Between October 1, 2021, and February 12, 2022, research staff consented and enrolled eligible participants who had fever, cough, or loss of taste or smell and sought outpatient medical care or clinical SARS-CoV-2 testing within 10 days of illness onset. Using the test-negative design, we compared the odds of receiving two or three mRNA COVID-19 vaccine doses among SARS-CoV-2 cases versus controls using logistic regression. Regression models were adjusted for study site, age, onset week, and prior SARS-CoV-2 infection. Vaccine effectiveness (VE) was calculated as (1 - adjusted odds ratio) × 100%. Results: Among 3847 participants included for analysis, 574 (32%) of 1775 tested positive for SARS-CoV-2 during the Delta predominant period and 1006 (56%) of 1794 participants tested positive during the Omicron predominant period. When Delta predominated, VE against symptomatic illness in outpatient settings was 63% (95% CI: 51% to 72%) among mRNA two-dose recipients and 96% (95% CI: 93% to 98%) for three-dose recipients. When Omicron predominated, VE was 21% (95% CI: -6% to 41%) among two-dose recipients and 62% (95% CI: 48% to 72%) among three-dose recipients. Conclusions: In this adult population, three mRNA COVID-19 vaccine doses provided substantial protection against symptomatic illness in outpatient settings when the Omicron variant became the predominant cause of COVID-19 in the United States. These findings support the recommendation for a third mRNA COVID-19 vaccine dose.

Network analysis of intra- and interspecific freshwater fish interactions using year-around tracking.

A long-term, yet detailed view into the social patterns of aquatic animals has been elusive. With advances in reality mining tracking technologies, a proximity-based social network (PBSN) can capture detailed spatio-temporal underwater interactions. We collected and analysed a large dataset of 108 freshwater fish from four species, tracked every few seconds over 1 year in their natural environment. We calculated the clustering coefficient of minute-by-minute PBSNs to measure social interactions, which can happen among fish sharing resources or habitat preferences (positive/neutral interactions) or in predator and prey during foraging interactions (agonistic interactions). A statistically significant coefficient compared to an equivalent random network suggests interactions, while a significant aggregated clustering across PBSNs indicates prolonged, purposeful social behaviour. Carp (Cyprinus carpio) displayed within- and among-species interactions, especially during the day and in the winter, while tench (Tinca tinca) and catfish (Silurus glanis) were solitary. Perch (Perca fluviatilis) did not exhibit significant social behaviour (except in autumn) despite being usually described as a predator using social facilitation to increase prey intake. Our work illustrates how methods for building a PBSN can affect the network's structure and highlights challenges (e.g. missing signals, different burst frequencies) in deriving a PBSN from reality mining technologies.

Complete Genome Sequence of Rhodococcus sp. Strain W8901, a Human Clinical Specimen, Assembled Using MiSeq and MinION Sequence Data.

Rhodococcus sp. strain W8901 is a Gram-positive, aerobic, mycolic acid-containing coccobacillus obtained from a patient with acute lymphocytic leukemia. Here, we report on the complete, circular genome sequence obtained using Illumina MiSeq and Oxford Nanopore Technologies MinION reads in order to better resolve the phylogeny of a rare pathogen.

Clade-specific chromosomal rearrangements and loss of subtelomeric adhesins in Candida auris.

Candida auris is an emerging fungal pathogen of rising concern due to global spread, the ability to cause healthcare-associated outbreaks, and antifungal resistance. Genomic analyses revealed that early contemporaneously detected cases of C. auris were geographically stratified into four major clades. While Clades I, III, and IV are responsible for ongoing outbreaks of invasive and multidrug-resistant infections, Clade II, also termed the East Asian clade, consists primarily of cases of ear infection, is often susceptible to all antifungal drugs, and has not been associated with outbreaks. Here, we generate chromosome-level assemblies of twelve isolates representing the phylogenetic breadth of these four clades and the only isolate described to date from Clade V. This Clade V genome is highly syntenic with those of Clades I, III, and IV, although the sequence is highly divergent from the other clades. Clade II genomes appear highly rearranged, with translocations occurring near GC-poor regions, and large subtelomeric deletions in most chromosomes, resulting in a substantially different karyotype. Rearrangements and deletion lengths vary across Clade II isolates, including two from a single patient, supporting ongoing genome instability. Deleted subtelomeric regions are enriched in Hyr/Iff-like cell-surface proteins, novel candidate cell wall proteins, and an ALS-like adhesin. Cell wall proteins from these families and other drug-related genes show clade-specific signatures of selection in Clades I, III, and IV. Subtelomeric dynamics and the conservation of cell surface proteins in the clades responsible for global outbreaks causing invasive infections suggest an explanation for the different phenotypes observed between clades.

Analysis of the initial lot of the CDC 2019-Novel Coronavirus (2019-nCoV) real-time RT-PCR diagnostic panel.

At the start of the COVID-19 pandemic, the Centers for Disease Control and Prevention (CDC) designed, manufactured, and distributed the CDC 2019-Novel Coronavirus (2019-nCoV) Real-Time RT-PCR Diagnostic Panel for SARS-CoV-2 detection. The diagnostic panel targeted three viral nucleocapsid gene loci (N1, N2, and N3 primers and probes) to maximize sensitivity and to provide redundancy for virus detection if mutations occurred. After the first distribution of the diagnostic panel, state public health laboratories reported fluorescent signal in the absence of viral template (false-positive reactivity) for the N3 component and to a lesser extent for N1. This report describes the findings of an internal investigation conducted by the CDC to identify the cause(s) of the N1 and N3 false-positive reactivity. For N1, results demonstrate that contamination with a synthetic template, that occurred while the "bulk" manufactured materials were located in a research lab for quality assessment, was the cause of false reactivity in the first lot. Base pairing between the 3' end of the N3 probe and the 3' end of the N3 reverse primer led to amplification of duplex and larger molecules resulting in false reactivity in the N3 assay component. We conclude that flaws in both assay design and handling of the "bulk" material, caused the problems with the first lot of the 2019-nCoV Real-Time RT-PCR Diagnostic Panel. In addition, within this study, we found that the age of the examined diagnostic panel reagents increases the frequency of false positive results for N3. We discuss these findings in the context of improvements to quality control, quality assurance, and assay validation practices that have since been improved at the CDC.

Complete and Circularized Genome Assemblies of the Kroppenstedtia eburnea Genus Type Strain and the Kroppenstedtia pulmonis Species Type Strain with MiSeq and MinION Sequence Data.

Kroppenstedtia eburnea DSM 45196T and Kroppenstedtia pulmonis W9323T are aerobic, Gram-positive, filamentous, chemoorganotrophic thermoactinomycetes. Here, we report on the complete and circular genome assemblies generated using Illumina MiSeq and Oxford Nanopore Technologies MinION reads. Putative gene clusters predicted to be involved in the production of secondary metabolites were also identified.