Semiconductor nanostructures with photocatalytic activity have the potential for many applications including remediation of environmental pollutants and use in antibacterial products. An effective way for promoting photocatalytic activity is depositing noble metal nanoparticles (NPs) on a semiconductor. In this paper, we demonstrated the successful deposition of Au NPs, having sizes smaller than 3 nm, onto ZnO NPs. ZnO/Au hybrid nanostructures having different molar ratios of Au to ZnO were synthesized. It was found that Au nanocomponents even at a very low Au/ZnO molar ratio of 0.2% can greatly enhance the photocatalytic and antibacterial activity of ZnO. Electron spin resonance spectroscopy with spin trapping and spin labeling was used to investigate the enhancing effect of Au NPs on the generation of reactive oxygen species and photoinduced charge carriers. Deposition of Au NPs onto ZnO resulted in a dramatic increase in light-induced generation of hydroxyl radical, superoxide and singlet oxygen, and production of holes and electrons. The enhancing effect of Au was dependent on the molar ratio of Au present in the ZnO/Au nanostructures. Consistent with these results from ESR measurements, ZnO/Au nanostructures also exhibited enhanced photocatalytic and antibacterial activity. These results unveiled the enhanced mechanism of Au on ZnO and these materials have great potential for use in water purification and antibacterial products.

The FDA has created a United States-based open-source whole-genome sequencing network of state, federal, international, and commercial partners. The GenomeTrakr network represents a first-of-its-kind distributed genomic food shield for characterizing and tracing foodborne outbreak pathogens back to their sources. The GenomeTrakr network is leading investigations of outbreaks of foodborne illnesses and compliance actions with more accurate and rapid recalls of contaminated foods as well as more effective monitoring of preventive controls for food manufacturing environments. An expanded network would serve to provide an international rapid surveillance system for pathogen traceback, which is critical to support an effective public health response to bacterial outbreaks. R ecent devastating outbreaks associated with the consumption of fresh-cut produce have reinforced the notion that foodborne disease remains a substantial global challenge to public health. In the United States alone, one in six or an estimated 48 million people fall prey to foodborne pathogens, yielding 128,000 hospitalizations and 3,000 deaths per year (http://www.cdc.gov /foodborneburden). Economic burdens are estimated cumulatively at $152 billion dollars annually, $39 billion of which is attributed directly to the contamination of fresh, canned, and processed produce (see the Produce Safety Project, http://www .pewtrusts.org/en/about/news-room/press-releases/0001/01/01 /foodborne-illness-costs-nation-$152-billion-annually-nearly -$39-billion-loss-attributed-to-produce). Mitigating foodborne illness, at times, seems to be an intractable challenge.One longstanding problem is the ability to rapidly identify the food source of the contamination. Despite the best efforts of food safety experts, the previous technology, pulsed-field gel electrophoresis (PFGE), often lacks the resolution to effectively pinpoint the source of an outbreak. The promise of whole-genome sequencing (WGS) came in 2012 when scientists with the U.S. Food and Drug Administration's Center for Food Safety and Applied Nutrition (FDA-CFSAN) performed a retrospective outbreak study on a 2012 Salmonella outbreak that was linked to spicy tuna sushi rolls by PFGE. The clinical isolates, food isolates, and historical isolates of the same PFGE pattern were all sequenced on the Illumina MiSeq. In contrast to the PFGE results, where isolates from the current outbreak looked exactly the same as unrelated historical isolates, WGS uncovered a surprising level of resolution distinguishing all of the isolates. Moreover, the isolates from the outbreak were most closely related to a 5-year-old historical isolate that was linked to a processing facility only 8 km away from the source of the outbreak (1). This isolate was collected at the port of entry from an earlier inspection of contaminated seafood and, like many others, was saved in the freezer collection of the FDA-CFSAN. The idea that the FDA's historical isolates could all be sequenced, providing investigators with geographic clues from a ...

A listeriosis outbreak in the United States implicated contaminated ice cream produced by one company, which operated 3 facilities. We performed single nucleotide polymorphism (SNP)-based whole genome sequencing (WGS) analysis on Listeria monocytogenes from food, environmental and clinical sources, identifying two clusters and a single branch, belonging to PCR serogroup IIb and genetic lineage I. WGS Cluster I, representing one outbreak strain, contained 82 food and environmental isolates from Facility I and 4 clinical isolates. These isolates differed by up to 29 SNPs, exhibited 9 pulsed-field gel electrophoresis (PFGE) profiles and multilocus sequence typing (MLST) sequence type (ST) 5 of clonal complex 5 (CC5). WGS Cluster II contained 51 food and environmental isolates from Facility II, 4 food isolates from Facility I and 5 clinical isolates. Among them the isolates from Facility II and clinical isolates formed a clade and represented another outbreak strain. Isolates in this clade differed by up to 29 SNPs, exhibited 3 PFGE profiles and ST5. The only isolate collected from Facility III belonged to singleton ST489, which was in a single branch separate from Clusters I and II, and was not associated with the outbreak. WGS analyses clustered together outbreak-associated isolates exhibiting multiple PFGE profiles, while differentiating them from epidemiologically unrelated isolates that exhibited outbreak PFGE profiles. The complete genome of a Cluster I isolate allowed the identification and analyses of putative prophages, revealing that Cluster I isolates differed by the gain or loss of three putative prophages, causing the banding pattern differences among all 3 AscI-PFGE profiles observed in Cluster I isolates. WGS data suggested that certain ice cream varieties and/or production lines might have contamination sources unique to them. The SNP-based analysis was able to distinguish CC5 as a group from non-CC5 isolates and differentiate among CC5 isolates from different outbreaks/incidents.

In 2014, the identification of stone fruits contaminated with Listeria monocytogenes led to the subsequent identification of a multistate outbreak. Simultaneous detection and enumeration of L. monocytogenes were performed on 105 fruits, each weighing 127 to 145 g, collected from 7 contaminated lots. The results showed that 53.3% of the fruits yielded L. monocytogenes (lower limit of detection, 5 CFU/fruit), and the levels ranged from 5 to 2,850 CFU/fruit, with a geometric mean of 11.3 CFU/fruit (0.1 CFU/g of fruit). Two serotypes, IVb-v1 and 1/2b, were identified by a combination of PCR- and antiserum-based serotyping among isolates from fruits and their packing environment; certain fruits contained a mixture of both serotypes. Single nucleotide polymorphism (SNP)-based whole-genome sequencing (WGS) analysis clustered isolates from two case-patients with the serotype IVb-v1 isolates and distinguished outbreak-associated isolates from pulsed-field gel electrophoresis (PFGE)-matched, but epidemiologically unrelated, clinical isolates. The outbreak-associated isolates differed by up to 42 SNPs. All but one serotype 1/2b isolate formed another WGS cluster and differed by up to 17 SNPs. Fully closed genomes of isolates from the stone fruits were used as references to maximize the resolution and to increase our confidence in prophage analysis. Putative prophages were conserved among isolates of each WGS cluster. All serotype IVb-v1 isolates belonged to singleton sequence type 382 (ST382); all but one serotype 1/2b isolate belonged to clonal complex 5.IMPORTANCE WGS proved to be an excellent tool to assist in the epidemiologic investigation of listeriosis outbreaks. The comparison at the genome level contributed to our understanding of the genetic diversity and variations among isolates involved in an outbreak or isolates associated with food and environmental samples from one facility. Fully closed genomes increased our confidence in the identification and comparison of accessory genomes. The diversity among the outbreak-associated isolates and the inclusion of PFGE-matched, but epidemiologically unrelated, isolates demonstrate the high resolution of WGS. The prevalence and enumeration data could contribute to our further understanding of the risk associated with Listeria monocytogenes contamination, especially among high-risk populations.