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Many studies have identified the influences of PM2.5. However, very little research has addressed the spatiotemporal dependence and heterogeneity in the relationships between impact factors and PM2.5. This study firstly utilizes spatial statistics and time series analysis to investigate the spatial and temporal dependence of PM2.5 at the city level in China using a three-year (2015–2017) dataset. Then, a new local regression model, multiscale geographically weighted regression (MGWR), is introduced, based on which we measure the influence of PM2.5. A spatiotemporal lag is constructed and included in MGWR to account for spatiotemporal dependence and spatial heterogeneity simultaneously. Results of MGWR are comprehensively compared with those of ordinary least square (OLS) and geographically weighted regression (GWR). Experimental results show that PM2.5 is autocorrelated in both space and time. Compared with existing approaches, MGWR with a spatiotemporal lag (MGWRL) achieves a higher goodness-of-fit and a more significant effect on eliminating residual spatial autocorrelation. Parameter estimates from MGWR demonstrate significant spatial heterogeneity, which traditional global models fail to detect. Results also indicate the use of MGWR for generating local spatiotemporal dependence evaluations which are conditioned on various covariates rather than being simple descriptions of a pattern. This study offers a more accurate method to model geographic events.

The rapid detection of foodborne microbial pathogens contaminating fresh fruits and vegetables during the intervening period between harvest and consumption could revolutionize microbial quality assurance of food usually consumed raw and those with a limited shelf life. We have developed a sensitive, shotgun whole genome sequencing protocol capable of detecting as few as 1 colony forming unit (cfu) of Salmonella enterica serovar Typhimurium spiked on 25 g of lettuce. The Ion Torrent sequencing platform was used to generate reads of globally amplified DNA from microbes recovered from the surface of lettuce followed by bioinformatic analyses of the nucleotide sequences to detect the presence of Salmonella. The test is rapid and sensitive, and appropriate for testing perishable foods, and those consumed raw, for Salmonella contamination. The test has the potential to be universally applicable to any microbial contaminant on lettuce as long as a suitable bioinformatics pipeline is available and validated. A universal test is expected to pave the way for preventive and precision food safety and the re-shaping of the entire spectrum of food safety investigations from the current disease-limiting, reactive procedure to a proactive, disease prevention process.

We have developed a targeted, amplicon-based next-generation sequencing method to detect and analyze 227 virulence genes (VG) of Salmonella (AmpliSeqSalm_227VG) for assessing the pathogenicity potential of Salmonella. The procedure was developed using 80 reference genomes representing 75 epidemiologically-relevant serovars associated with human salmonellosis. We applied the AmpliSeqSalm_227VG assay to (a) 35 previously characterized field strains of Salmonella consisting of serovars commonly incriminated in foodborne illnesses and (b) 34 Salmonella strains with undisclosed serological or virulence attributes, and were able to divide Salmonella VGs into two groups: core VGs and variable VGs. The commonest serovars causing foodborne illnesses such as Enteritidis, Typhimurium, Heidelberg and Newport had a high number of VGs (217–227). In contrast, serovars of subspecies not commonly associated with human illnesses, such as houtenae, arizonae and salame, tended to have fewer VGs (177–195). Variable VGs were not only infrequent but, when present, displayed considerable sequence variation: safC, sseL, sseD, sseE, ssaK and stdB showed the highest variation and were linked to strain pathogenicity. In a chicken infection model, VGs belonging to rfb and sse operons showed differences and were linked with pathogenicity. The high-throughput, targeted NGS-based AmpliSeqSalm_227VG procedure provided previously unknown information about variation in select virulence genes that can now be applied to a much larger population of Salmonella for evaluating pathogenicity of various serovars of Salmonella and for risk assessment of foodborne salmonellosis.

Hepatocellular carcinoma (HCC) is considered as a disease of dysfunction of the stem cells. Studies on stem cells have demonstrated that Oct4 plays a pivotal role in embryo regulation. In order to understand the role of Oct4 in HCC and the relationship among Oct4 and wnt/β-catenin and TGF-β signal pathways, we have detected the expression of Oct4, Nanog, Sox2, STAT3 as well as the genes in wnt/β-catenin, and TGF-β families in HCC cell lines and in tumor specimens from HCC patients. The authors found that Oct4 was expressed in all of the four HCC cell lines and the tumor specimens from HCC patients. Some other genes were also expressed in them with different level including Nanog, Sox2, STAT3 and TCF3, wnt10b, β-catenin, ELF, Smad3 and Smad4. The ability of the clone formation and migration of the HepG2 decreased after Oct4 was knockdowned. Silencing of Oct4 and TCF3 in HCC cell line HepG2 revealed that there were complicated relationships among Oct4, wnt/β-catenin family and TGF-β family genes. Knockdowning Oct4 reduced the expression of TGF-β family genes ELF, Smad3, Smad4 and wnt/β-catenin family genes, wnt10b, and β-catenin but increased TCF3. In reverse, knockdowning TCF3 led to the increased expression of Oct4 and TGF-β family genes. In conclusion, the expression of Oct4 in HCC may play an important role as in stem cell. Because Oct4 improves not only the function of wnt/β-catenin, but also the TGF-β signal pathways, the significance of its expression in HCC might be more complicated than we evinced before. [ABSTRACT FROM AUTHOR]

Non-typhoidal Salmonella is a leading cause of foodborne illness worldwide. Prompt and accurate identification of the sources of Salmonella responsible for disease outbreaks is crucial to minimize infections and eliminate ongoing sources of contamination. Current subtyping tools including single nucleotide polymorphism (SNP) typing may be inadequate, in some instances, to provide the required discrimination among epidemiologically unrelated Salmonella strains. Prophage genes represent the majority of the accessory genes in bacteria genomes and have potential to be used as high discrimination markers in Salmonella. In this study, the prophage sequence diversity in different Salmonella serovars and genetically related strains was investigated. Using whole genome sequences of 1,760 isolates of S. enterica representing 151 Salmonella serovars and 66 closely related bacteria, prophage sequences were identified from assembled contigs using PHASTER. We detected 154 different prophages in S. enterica genomes. Prophage sequences were highly variable among S. enterica serovars with a median ± interquartile range (IQR) of 5 ± 3 prophage regions per genome. While some prophage sequences were highly conserved among the strains of specific serovars, few regions were lineage specific. Therefore, strains belonging to each serovar could be clustered separately based on their prophage content. Analysis of S. Enteritidis isolates from seven outbreaks generated distinct prophage profiles for each outbreak. Taken altogether, the diversity of the prophage sequences correlates with genome diversity. Prophage repertoires provide an additional marker for differentiating S. enterica subtypes during foodborne outbreaks.

The Salmonella Syst-OMICS consortium is sequencing 4,500 Salmonella genomes and building an analysis pipeline for the study of Salmonella genome evolution, antibiotic resistance and virulence genes. Metadata, including phenotypic as well as genomic data, for isolates of the collection are provided through the Salmonella Foodborne Syst-OMICS database (SalFoS), at https://salfos.ibis.ulaval.ca/. Here, we present our strategy and the analysis of the first 3,377 genomes. Our data will be used to draw potential links between strains found in fresh produce, humans, animals and the environment. The ultimate goals are to understand how Salmonella evolves over time, improve the accuracy of diagnostic methods, develop control methods in the field, and identify prognostic markers for evidence-based decisions in epidemiology and surveillance.

The use of treated municipal wastewater residues (biosolids) as fertilizers is an attractive, inexpensive option for growers and farmers. Various regulatory bodies typically employ indicator organisms (fecal coliforms, E. coli and Salmonella) to assess the adequacy and efficiency of the wastewater treatment process in reducing pathogen loads in the final product. Molecular detection approaches can offer some advantages over culture-based methods as they can simultaneously detect a wider microbial species range, including non-cultivable microorganisms. However, they cannot directly assess the viability of the pathogens. Here, we used bacterial enumeration methods together with molecular methods including qPCR, 16S rRNA and cpn60 gene amplicon sequencing and shotgun metagenomic sequencing to compare pre- and post-treatment biosolids from two Canadian wastewater treatment plants (WWTPs). Our results show that an anaerobic digestion WWTP was unsuccessful at reducing the live indicator organism load (coliforms, generic E. coli and Salmonella) below acceptable regulatory criteria, while biosolids from a dewatering/pelletization WWTP met these criteria. DNA from other pathogens was detected by the molecular methods, but these species were considered less abundant. Clostridium DNA increased significantly following anaerobic digestion treatments. In addition to pathogen DNA, genes related to virulence and antibiotic resistance were identified in treated biosolids. Shotgun metagenomics revealed the widest range of pathogen DNA and, among the approaches used here, was the only approach that could access functional gene information in treated biosolids. Overall, our results highlight the potential usefulness of amplicon sequencing and shotgun metagenomics as complementary screening methods that could be used in parallel with culture-based methods, although more detailed comparisons across a wider range of sites would be needed.