Genetic markers in s. Paratyphi c reveal primary adaptation to pigs

Salmonella enterica with the identical antigenic formula 6,7:c:1,5 can be differentiated biochemically and by disease syndrome. One grouping, Salmonella Paratyphi C, is currently considered a typhoidal serovar, responsible for enteric fever in humans. The human-restricted typhoidal serovars (S. Typhi and Paratyphi A, B and C) typically display high levels of genome degradation and are cited as an example of convergent evolution for host adaptation in humans. However, S. Paratyphi C presents a different clinical picture to S. Typhi/Paratyphi A, in a patient group with predisposition, raising the possibility that its natural history is different, and that infection is invasive salmonellosis rather than enteric fever. Using whole genome sequencing and metabolic pathway analysis, we compared the genomes of 17 S. Paratyphi C strains to other members of the 6,7:c:1,5 group and to two typhoidal serovars: S. Typhi and Paratyphi A. The genome degradation observed in S. Paratyphi C was much lower than S. Typhi/Paratyphi A, but similar to the other 6,7:c:1,5 strains. Genomic and metabolic comparisons revealed little to no overlap between S. Paratyphi C and the other typhoidal serovars, arguing against convergent evolution and instead providing evidence of a primary adaptation to pigs in accordance with the 6,7:c:1.5 strains

Mycoplasma genitalium: whole genome sequence analysis, recombination and population structure.

BACKGROUND: Although Mycoplasma genitalium is a common sexually transmitted pathogen causing clinically distinct diseases both in male and females, few genomes have been sequenced up to now, due mainly to its fastidious nature and slow growth. Hence, we lack a robust phylogenetic framework to provide insights into the population structure of the species. Currently our understanding of the nature and diversity of M. genitalium relies on molecular tests targeting specific genes or regions of the genome and knowledge is limited by a general under-testing internationally. This is set against a background of drug resistance whereby M. genitalium has developed resistance to mainly all therapeutic antimicrobials. RESULTS: We sequenced 28 genomes of Mycoplasma genitalium from temporally (1980-2010) and geographically (Europe, Japan, Australia) diverse sources. All the strain showed essentially the same genomic content without any accessory regions found. However, we identified extensive recombination across their genomes with a total of 25 regions showing heightened levels of SNP density. These regions include the MgPar loci, associated with host interactions, as well as other genes that could also be involved in this role. Using these data, we generated a robust phylogeny which shows that there are two main clades with differing degrees of genomic variability. SNPs found in region V of 23S rRNA and parC were consistent with azithromycin/erythromycin and fluoroquinolone resistances, respectively, and with their phenotypic MIC data. CONCLUSIONS: The sequence data here generated is essential for designing rational approaches to type and track Mycoplasma genitalium as antibiotic resistance increases. It represents a first approach to its population genetics to better appreciate the role of this organism as a sexually transmitted pathogen

The secondary resistome of multidrug-resistant Klebsiella pneumoniae.

Klebsiella pneumoniae causes severe lung and bloodstream infections that are difficult to treat due to multidrug resistance. We hypothesized that antimicrobial resistance can be reversed by targeting chromosomal non-essential genes that are not responsible for acquired resistance but essential for resistant bacteria under therapeutic concentrations of antimicrobials. Conditional essentiality of individual genes to antimicrobial resistance was evaluated in an epidemic multidrug-resistant clone of K. pneumoniae (ST258). We constructed a high-density transposon mutant library of >430,000 unique Tn5 insertions and measured mutant depletion upon exposure to three clinically relevant antimicrobials (colistin, imipenem or ciprofloxacin) by Transposon Directed Insertion-site Sequencing (TraDIS). Using this high-throughput approach, we defined three sets of chromosomal non-essential genes essential for growth during exposure to colistin (n = 35), imipenem (n = 1) or ciprofloxacin (n = 1) in addition to known resistance determinants, collectively termed the "secondary resistome". As proof of principle, we demonstrated that inactivation of a non-essential gene not previously found linked to colistin resistance (dedA) restored colistin susceptibility by reducing the minimum inhibitory concentration from 8 to 0.5 μg/ml, 4-fold below the susceptibility breakpoint (S ≤ 2 μg/ml). This finding suggests that the secondary resistome is a potential target for developing antimicrobial "helper" drugs that restore the efficacy of existing antimicrobials

RNA-seq analysis of the influence of anaerobiosis and FNR on Shigella flexneri.

BACKGROUND: Shigella flexneri is an important human pathogen that has to adapt to the anaerobic environment in the gastrointestinal tract to cause dysentery. To define the influence of anaerobiosis on the virulence of Shigella, we performed deep RNA sequencing to identify transcriptomic differences that are induced by anaerobiosis and modulated by the anaerobic Fumarate and Nitrate Reduction regulator, FNR. RESULTS: We found that 528 chromosomal genes were differentially expressed in response to anaerobic conditions; of these, 228 genes were also influenced by FNR. Genes that were up-regulated in anaerobic conditions are involved in carbon transport and metabolism (e.g. ptsG, manX, murQ, cysP, cra), DNA topology and regulation (e.g. ygiP, stpA, hns), host interactions (e.g. yciD, nmpC, slyB, gapA, shf, msbB) and survival within the gastrointestinal tract (e.g. shiA, ospI, adiY, cysP). Interestingly, there was a marked effect of available oxygen on genes involved in Type III secretion system (T3SS), which is required for host cell invasion and pathogenesis. These genes, located on the large Shigella virulence plasmid, were down regulated in anaerobiosis in an FNR-dependent manner. We also confirmed anaerobic induction of csrB and csrC small RNAs in an FNR-independent manner. CONCLUSIONS: Anaerobiosis promotes survival and adaption strategies of Shigella, while modulating virulence plasmid genes involved in T3SS-mediated host cell invasion. The influence of FNR on this process is more extensive than previously appreciated, although aside from the virulence plasmid, this transcriptional regulator does not govern expression of genes on other horizontally acquired sequences on the chromosome such as pathogenicity islands

Deep auto-encoders with sequential learning for multimodal dimensional emotion recognition

Multimodal dimensional emotion recognition has drawn a great attention from the affective computing community and numerous schemes have been extensively investigated, making a significant progress in this area. However, several questions still remain unanswered for most of existing approaches including: (i) how to simultaneously learn compact yet representative features from multimodal data, (ii) how to effectively capture complementary features from multimodal streams, and (iii) how to perform all the tasks in an end-to-end manner. To address these challenges, in this paper, we propose a novel deep neural network architecture consisting of a two-stream auto-encoder and a long short term memory for effectively integrating visual and audio signal streams for emotion recognition. To validate the robustness of our proposed architecture, we carry out extensive experiments on the multimodal emotion in the wild dataset: RECOLA. Experimental results show that the proposed method achieves state-of-the-art recognition performance

The type III secretion system effector SeoC of salmonella enterica subsp. salamae and S. enterica subsp. arizonae ADP-Ribosylates Src and inhibits opsonophagocytosis

Salmonella species utilize type III secretion systems (T3SSs) to translocate effectors into the cytosol of mammalian host cells, subverting cell signaling and facilitating the onset of gastroenteritis. In this study, we compared a draft genome assembly of Salmonella enterica subsp. salamae strain 3588/07 against the genomes of S. enterica subsp. enterica serovar Typhimurium strain LT2 and Salmonella bongori strain 12419. S. enterica subsp. salamae encodes the Salmonella pathogenicity island 1 (SPI-1), SPI-2, and the locus of enterocyte effacement (LEE) T3SSs. Though several key S Typhimurium effector genes are missing (e.g., avrA, sopB, and sseL), S. enterica subsp. salamae invades HeLa cells and contains homologues of S. bongori sboK and sboC, which we named seoC SboC and SeoC are homologues of EspJ from enteropathogenic and enterohemorrhagic Escherichia coli (EPEC and EHEC, respectively), which inhibit Src kinase-dependent phagocytosis by ADP-ribosylation. By screening 73 clinical and environmental Salmonella isolates, we identified EspJ homologues in S. bongori, S. enterica subsp. salamae, and Salmonella enterica subsp. arizonae The β-lactamase TEM-1 reporter system showed that SeoC is translocated by the SPI-1 T3SS. All the Salmonella SeoC/SboC homologues ADP-ribosylate Src E310 in vitro Ectopic expression of SeoC/SboC inhibited phagocytosis of IgG-opsonized beads into Cos-7 cells stably expressing green fluorescent protein (GFP)-FcγRIIa. Concurrently, S. enterica subsp. salamae infection of J774.A1 macrophages inhibited phagocytosis of beads, in a seoC-dependent manner. These results show that S. bongori, S. enterica subsp. salamae, and S. enterica subsp. arizonae share features of the infection strategy of extracellular pathogens EPEC and EHEC and shed light on the complexities of the T3SS effector repertoires of Enterobacteriaceae

A simple method for directional transcriptome sequencing using Illumina technology.

High-throughput sequencing of cDNA has been used to study eukaryotic transcription on a genome-wide scale to single base pair resolution. In order to compensate for the high ribonuclease activity in bacterial cells, we have devised an equivalent technique optimized for studying complete prokaryotic transcriptomes that minimizes the manipulation of the RNA sample. This new approach uses Illumina technology to sequence single-stranded (ss) cDNA, generating information on both the direction and level of transcription throughout the genome. The protocol, and associated data analysis programs, are freely available from http://www.sanger.ac.uk/Projects/Pathogens/Transcriptome/. We have successfully applied this method to the bacterial pathogens Salmonella bongori and Streptococcus pneumoniae and the yeast Schizosaccharomyces pombe. This method enables experimental validation of genetic features predicted in silico and allows the easy identification of novel transcripts throughout the genome. We also show that there is a high correlation between the level of gene expression calculated from ss-cDNA and double-stranded-cDNA sequencing, indicting that ss-cDNA sequencing is both robust and appropriate for use in quantitative studies of transcription. Hence, this simple method should prove a useful tool in aiding genome annotation and gene expression studies in both prokaryotes and eukaryotes

What's in a Name? Species-Wide Whole-Genome Sequencing Resolves Invasive and Noninvasive Lineages of Salmonella enterica Serotype Paratyphi B

For 100 years, it has been obvious that Salmonella enterica strains sharing the serotype with the formula 1,4,[ 5], 12: b:1,2-now known as ParatyphiB-can cause diseases ranging from serious systemic infections to self-limiting gastroenteritis. Despite considerable predicted diversity between strains carrying the common Paratyphi B serotype, there remain few methods that subdivide the group into groups that are congruent with their disease phenotypes. Paratyphi B therefore represents one of the canonical examples in Salmonella where serotyping combined with classical microbiological tests fails to provide clinically informative information. Here, we use genomics to provide the first high-resolution view of this serotype, placing it into a wider genomic context of the Salmonella enterica species. These analyses reveal why it has been impossible to subdivide this serotype based upon phenotypic and limited molecular approaches. By examining the genomic data in detail, we are able to identify common features that correlate with strains of clinical importance. The results presented here provide new diagnostic targets, as well as posing important new questions about the basis for the invasive disease phenotype observed in a subset of strains. IMPORTANCE Salmonella enterica strains carrying the serotype Paratyphi B have long been known to possess Jekyll and Hyde characteristics; some cause gastroenteritis, while others cause serious invasive disease. Understanding what makes up the population of strains carrying this serotype, as well as the source of their invasive disease, is a 100-year-old puzzle that we address here using genomics. Our analysis provides the first high-resolution view of this serotype, placing strains carrying serotype Paratyphi B into the wider genomic context of the Salmonella enterica species. This work reveals a history of disease dating back to the middle ages, caused by a group of distinct lineages with various abilities to cause invasive disease. By quantifying the key genomic differences between the invasive and noninvasive populations, we are able to identify key virulence-related targets that can form the basis of simple, rapid, point-of-care tests.Peer reviewe

Low-Resolution Face Recognition

Whilst recent face-recognition (FR) techniques have made significant progress on recognising constrained high-resolution web images, the same cannot be said on natively unconstrained low-resolution images at large scales. In this work, we examine systematically this under-studied FR problem, and introduce a novel Complement Super-Resolution and Identity (CSRI) joint deep learning method with a unified end-to-end network architecture. We further construct a new large-scale dataset TinyFace of native unconstrained low-resolution face images from selected public datasets, because none benchmark of this nature exists in the literature. With extensive experiments we show there is a significant gap between the reported FR performances on popular benchmarks and the results on TinyFace, and the advantages of the proposed CSRI over a variety of state-of-the-art FR and super-resolution deep models on solving this largely ignored FR scenario. The TinyFace dataset is released publicly at: https://qmul-tinyface.github.io/.Comment: Accepted by 14th Asian Conference on Computer Visio