Whole-genome sequencing reveals genomic characterization of Listeria monocytogenes from food in China

IntroductionListeria monocytogenes is a foodborne bacterium that could persist in food and food processing environments for a long time. Understanding the population structure and genomic characterization of foodborne L. monocytogenes is essential for the prevention and control of listeriosis.MethodsA total of 322 foodborne L. monocytogenes isolates from 13 geographical locations and four food sources in China between 2000 and 2018 were selected for whole-genome sequencing.ResultsIn silico subtyping divided the 322 isolates into five serogroups, 35 sequence types (STs), 26 clonal complexes (CCs) and four lineages. Serogroup IIa was the most prevalent serogroup and ST9 was the most prevalent ST of foodborne L. monocytogenes strains isolated in China. The in-depth phylogenetic analysis on CC9 revealed that ST122 clone might be original from ST9 clone. Furthermore, 23 potentially relevant clusters were identified by pair-wised whole-genome single nucleotide polymorphism analysis, indicating that persistent- and/or cross-contamination had occurred in markets in China. ST8 and ST121 were the second and third top STs of L. monocytogenes in China, which had heterogeneity with that of L. monocytogenes isolates from other countries. The antibiotic resistance genes aacA4, tetM, tetS, dfrG carried by different mobile elements were found in L. monocytogenes strains. One lineage II strain carrying Listeria Pathogenicity Island 3 was first reported. In addition, a novel type of premature stop codon in inlA gene was identified in this study.DiscussionThese findings revealed the genomic characteristics and evolutionary relationship of foodborne L. monocytogenes in China on a scale larger than previous studies, which further confirmed that whole-genome sequencing analysis would be a helpful tool for routine surveillance and source-tracing investigation

The Future of Comparative and International Education in a Globalised World

Abstract – This article examines the history and future prospects of comparative and international education with particular reference to the impact of globalisation and Information and Communications Technologies (ICTs). Connections and interactions between comparative educationists and the technologies of printing and electronic communications are examined in a historical context. The global nature of commu-nications in comparative and international education is demonstrated both spatially and historically, using information from all regions of the world. The changing nature of technologies is noted to have broadened the audience for comparative insights. The development of textbooks, journals, conferences, international agencies, the Internet, web-based communications, and professional comparative education soci-eties is related to the themes of communications and globalisation. Zusammenfassung – In diesem Artikel werden die Geschichte und die künftigen Aussichten der vergleichenden und internationalen Bildung untersucht mit besonderem Augenmerk auf den Einfluss von Globalisierung und Informations- und Kom-munikationstechnologien. Verbindungen und Interaktionen zwischen vergleichende

Noise Estimation from Remote Sensing Images by Fractal Theory and Adaptive Image Block Division

A novel approach for additive noise estimation from highly textured optical remote sensing images has been proposed, which is based on fractal theory and adaptive image block division. Different from the conventional regular block division based noise estimation methods, the divided adaptive image blocks with the proposed method are adhering to the local image information, which are most likely to be homogeneous blocks. Combining with the week textured image region detection using fractal theory and noise standard deviation calculation using statistical analysis, the proposed method can automatically estimate additive noise intensity from optical remote sensing images. Quantified analysis of experiments with ZY-3 satellite images demonstrates that the proposed method is applicable to optical remote sensing images with various complexities and different noise levels. Meanwhile, the notion of week textured image region detection and adaptive image block division can also be applied to multiplicative noise estimation from radar images after modification

Compression of next-generation sequencing quality scores using memetic algorithm

BACKGROUND: The exponential growth of next-generation sequencing (NGS) derived DNA data poses great challenges to data storage and transmission. Although many compression algorithms have been proposed for DNA reads in NGS data, few methods are designed specifically to handle the quality scores. RESULTS: In this paper we present a memetic algorithm (MA) based NGS quality score data compressor, namely MMQSC. The algorithm extracts raw quality score sequences from FASTQ formatted files, and designs compression codebook using MA based multimodal optimization. The input data is then compressed in a substitutional manner. Experimental results on five representative NGS data sets show that MMQSC obtains higher compression ratio than the other state-of-the-art methods. Particularly, MMQSC is a lossless reference-free compression algorithm, yet obtains an average compression ratio of 22.82% on the experimental data sets. CONCLUSIONS: The proposed MMQSC compresses NGS quality score data effectively. It can be utilized to improve the overall compression ratio on FASTQ formatted files