Salmonellosis Outbreak Detected by Automated Spatiotemporal Analysis - New York City, May-June 2019.

In May 2019, the New York City Department of Health and Mental Hygiene (NYCDOHMH) detected an unusual cluster of five salmonellosis patients via automated spatiotemporal analysis of notifiable diseases using free SaTScan software (1). Within 1 day of cluster detection, graduate student interviewers determined that three of the patients had eaten prepared food from the same grocery store (establishment A) located inside the cluster area. NYCDOHMH initiated an investigation to identify additional cases, establish the cause, and provide control recommendations. Overall, 15 New York City (NYC) residents with laboratory-diagnosed salmonellosis who reported eating food from establishment A were identified. The most commonly consumed food item was chicken, reported by 10 patients. All 11 clinical isolates available were serotyped as Salmonella Blockley, sequenced, and analyzed by core genome multilocus sequence typing; isolates had a median difference of zero alleles. Environmental assessments revealed food not held at the proper temperature, food not cooled properly, and potential cross-contamination during chicken preparation. Elevated fecal coliform counts were found in two of four ready-to-eat food samples collected from establishment A, and Bacillus cereus was detected in three. The outbreak strain of Salmonella was isolated from one patient's leftover chicken. Establishing automated spatiotemporal cluster detection analyses for salmonellosis and other reportable diseases could aid in the detection of geographically focused, community-acquired outbreaks even before laboratory subtyping results become available.

Large-scale chemical-genetics yields new M. tuberculosis inhibitor classes.

New antibiotics are needed to combat rising levels of resistance, with new Mycobacterium tuberculosis (Mtb) drugs having the highest priority. However, conventional whole-cell and biochemical antibiotic screens have failed. Here we develop a strategy termed PROSPECT (primary screening of strains to prioritize expanded chemistry and targets), in which we screen compounds against pools of strains depleted of essential bacterial targets. We engineered strains that target 474 essential Mtb genes and screened pools of 100-150 strains against activity-enriched and unbiased compound libraries, probing more than 8.5 million chemical-genetic interactions. Primary screens identified over tenfold more hits than screening wild-type Mtb alone, with chemical-genetic interactions providing immediate, direct target insights. We identified over 40 compounds that target DNA gyrase, the cell wall, tryptophan, folate biosynthesis and RNA polymerase, as well as inhibitors that target EfpA. Chemical optimization yielded EfpA inhibitors with potent wild-type activity, thus demonstrating the ability of PROSPECT to yield inhibitors against targets that would have eluded conventional drug discovery.

Opposing reactions in coenzyme A metabolism sensitize Mycobacterium tuberculosis to enzyme inhibition.

Mycobacterium tuberculosis (Mtb) is the leading infectious cause of death in humans. Synthesis of lipids critical for Mtb's cell wall and virulence depends on phosphopantetheinyl transferase (PptT), an enzyme that transfers 4'-phosphopantetheine (Ppt) from coenzyme A (CoA) to diverse acyl carrier proteins. We identified a compound that kills Mtb by binding and partially inhibiting PptT. Killing of Mtb by the compound is potentiated by another enzyme encoded in the same operon, Ppt hydrolase (PptH), that undoes the PptT reaction. Thus, loss-of-function mutants of PptH displayed antimicrobial resistance. Our PptT-inhibitor cocrystal structure may aid further development of antimycobacterial agents against this long-sought target. The opposing reactions of PptT and PptH uncover a regulatory pathway in CoA physiology.

Validation of mathematical models for Salmonella growth in raw ground beef under dynamic temperature conditions representing loss of refrigeration.

Temperature is a primary factor in controlling the growth of microorganisms in food. The current U. S. Food and Drug Administration Model Food Code guidelines state that food can be kept out of temperature control for up to 4 h without qualifiers, or up to 6 h, if the food product starts at an initial 41 °F (5 °C) temperature and does not exceed 70 °F (21 °C) at 6 h. This project validates existing ComBase computer models for Salmonella growth under changing temperature conditions modeling scenarios using raw ground beef as a model system. A cocktail of Salmonella serovars isolated from different meat products ( Salmonella Copenhagen, Salmonella Montevideo, Salmonella Typhimurium, Salmonella Saintpaul, and Salmonella Heidelberg) was made rifampin resistant and used for all experiments. Inoculated samples were held in a programmable water bath at 4.4 °C (40 °F) and subjected to linear temperature changes to different final temperatures over various lengths of time and then returned to 4.4 °C (40 °F). Maximum temperatures reached were 15.6, 26.7, or 37.8 °C (60, 80, or 100 °F), and the temperature increases took place over 4, 6, and 8 h, with varying cooling times. Our experiments show that when maximum temperatures were lower (15.6 or 26.7 °C), there was generally good agreement between the ComBase models and experiments: when temperature increases of 15.6 or 26.7 °C occurred over 8 h, experimental data were within 0.13 log CFU of the model predictions. When maximum temperatures were 37 °C, predictive models were fail-safe. Overall bias of the models was 1.11. and accuracy was 2.11. Our experiments show the U.S. Food and Drug Administration Model Food Code guidelines for holding food out of temperature control are quite conservative. Our research also shows that the ComBase models for Salmonella growth are accurate or fail-safe for dynamic temperature conditions as might be observed due to power loss from natural disasters or during transport out of temperature control.

Kangiella spongicola sp. nov., a halophilic marine bacterium isolated from the sponge Chondrilla nucula.

A novel halophilic bacterium of the genus Kangiella was isolated from a marine sponge collected from the Florida Keys, USA. Strain A79(T), an aerobic, Gram-negative, non-motile, rod-shaped bacterium, grew in 2-15 % (w/v) NaCl, at a temperature of 10-49 °C and at pH 4.5-10. Phylogenetic analysis placed strain A79(T) in the family Alcanivoraceae in the class Gammaproteobacteria. Strain A79(T) showed 98.5 % 16S rRNA gene sequence similarity to Kangiella japonica KMM 3899(T), 96.6 % similarity to Kangiella koreensis DSM 16069(T) and 95.6 % similarity to Kangiella aquimarina DSM 16071(T). The major cellular fatty acids were iso-C(11 : 0), iso-C(11 : 0) 3-OH, iso-C(15 : 0), iso-C(17 : 0) and iso-C(17 : 1)ω9c and the G+C content of the genomic DNA was 44.9 mol%. On the basis of physiological, chemotaxonomic and phylogenetic comparisons, strain A79(T) represents a novel species in the genus Kangiella, for which the name Kangiella spongicola sp. nov. is proposed. The type strain is A79(T) ( = ATCC BAA-2076(T) = DSM 23219(T)).