Genomic characterization of the Yersinia genus

Seek and you shall find: Yersinia enterocolitica in Ireland's drinking water

INTRODUCTION

Three Yersinia species were identified from samples of drinking water from diverse geographic regions of Ireland. Conventional commercial biochemical identification systems classified them as Yersinia enterocolitica. Since this organism is the most common cause of bacterial gastroenteritis in some countries, further investigation was warranted. The aim of the study was to provide a microbial characterisation of three Yersinia species, to determine their pathogenicity, and to review the incidence rate of Yersinia enterocolitica detection in our region.

METHODS

Organism identification was performed using conventional commercial diagnostic systems MALDI-TOF, API 20E, API 50CHE, TREK Sensititre GNID and Vitek 2 GN, and whole genome sequencing (WGS) was performed. Historical data for detections was extracted from the lab system for 2008 to 2023.

RESULTS

All three isolates gave "good" identifications of Yersinia enterocolitica on conventional systems. Further analysis by WGS matched two of the isolates with recently described Yersinia proxima, and the third was a member of the non-pathogenic Yersinia enterocolitica clade 1Aa.

DISCUSSION

Our analysis of these three isolates deemed them to be Yersinia species not known currently to be pathogenic, but determining this necessitated the use of next-generation sequencing and advanced bioinformatics. Our work highlights the importance of having this technology available to public laboratories, either locally or in a national reference laboratory. The introduction of molecular technologies for the detection of Yersinia species may increase the rate of detections. Accurate identification of significant pathogens in environmental, public health and clinical microbiology laboratories is critically important for the protection of society.

CNV-FB: A Feature bagging strategy-based approach to detect copy number variants from NGS data

Copy number variation (CNV), as a type of genomic structural variation, accounts for a large proportion of structural variation and is related to the pathogenesis and susceptibility to some human diseases, playing an important role in the development and change of human diseases. The development of next-generation sequencing technology (NGS) provides strong support for the design of CNV detection algorithms. Although a large number of methods have been developed to detect CNVs using NGS data, it is still considered a difficult problem to detect CNVs with low purity and coverage. In this paper, a new calculation method CNV-FB is proposed to detect CNVs from NGS data. The core idea of CNV-FB is to randomly sample the read depth values of the genome fragment, and then each sample is individually detected for outliers, and finally combined into a final outlier score. The CNV-FB method was applied to simulation data and real data experiments and compared with the other five methods of the same type. The results show that the CNV-FB method has a better detection effect than other methods. Therefore, the CNV-FB method may be an effective algorithm for detecting genomic mutations.

Characterization of an aspartate aminotransferase encoded by YPO0623 with frequent nonsense mutations in Yersinia pestis

Yersinia pestis, the causative agent of plague, is a genetically monomorphic bacterial pathogen that evolved from Yersinia pseudotuberculosis approximately 7,400 years ago. We observed unusually frequent mutations in Y. pestis YPO0623, mostly resulting in protein translation termination, which implies a strong natural selection. These mutations were found in all phylogenetic lineages of Y. pestis, and there was no apparent pattern in the spatial distribution of the mutant strains. Based on these findings, we aimed to investigate the biological function of YPO0623 and the reasons for its frequent mutation in Y. pestis. Our in vitro and in vivo assays revealed that the deletion of YPO0623 enhanced the growth of Y. pestis in nutrient-rich environments and led to increased tolerance to heat and cold shocks. With RNA-seq analysis, we also discovered that the deletion of YPO0623 resulted in the upregulation of genes associated with the type VI secretion system (T6SS) at 26°C, which probably plays a crucial role in the response of Y. pestis to environment fluctuations. Furthermore, bioinformatic analysis showed that YPO0623 has high homology with a PLP-dependent aspartate aminotransferase in Salmonella enterica, and the enzyme activity assays confirmed its aspartate aminotransferase activity. However, the enzyme activity of YPO0623 was significantly lower than that in other bacteria. These observations provide some insights into the underlying reasons for the high-frequency nonsense mutations in YPO0623, and further investigations are needed to determine the exact mechanism.

Inhibitory Effect of Select Nitrocompounds and Chlorate against Yersinia ruckeri and Yersinia aleksiciae In Vitro

Yersinia ruckeri is an important fish pathogen causing enteric redmouth disease. Antibiotics have traditionally been used to control this pathogen, but concerns of antibiotic resistance have created a need for alternative interventions. Presently, chlorate and certain nitrocompounds were tested against Y. ruckeri as well as a related species within the genus, Y. aleksiciae, to assess the effects of these inhibitors. The results reveal that 9 mM chlorate had no inhibitory effect against Y. ruckeri, but inhibited growth rates and maximum optical densities of Y. aleksciciae by 20–25% from those of untreated controls (0.46 h−1 and 0.29 maximum optical density, respectively). The results further reveal that 2-nitropropanol and 2-nitroethanol (9 mM) eliminated the growth of both Y. ruckeri and Y. aleksiciae during anaerobic or aerobic culture. Nitroethane, ethyl nitroacetate and ethyl-2-nitropropionate (9 mM) were less inhibitory when tested similarly. Results from a mixed culture of Y. ruckeri with fish tank microbes and of Y. aleksiciae with porcine fecal microbes reveal that the anti-Yersinia activity of the tested nitrocompounds was bactericidal, with 2-nitropropanol and 2-nitroethanol being more potent than the other tested nitrocompounds. The anti-Yersinia activity observed with these tested compounds warrants further study to elucidate the mechanisms of action and strategies for their practical application.

HAYSTAC: A Bayesian framework for robust and rapid species identification in high-throughput sequencing data

Identification of specific species in metagenomic samples is critical for several key applications, yet many tools available require large computational power and are often prone to false positive identifications. Here we describe High-AccuracY and Scalable Taxonomic Assignment of MetagenomiC data (HAYSTAC), which can estimate the probability that a specific taxon is present in a metagenome. HAYSTAC provides a user-friendly tool to construct databases, based on publicly available genomes, that are used for competitive read mapping. It then uses a novel Bayesian framework to infer the abundance and statistical support for each species identification and provide per-read species classification. Unlike other methods, HAYSTAC is specifically designed to efficiently handle both ancient and modern DNA data, as well as incomplete reference databases, making it possible to run highly accurate hypothesis-driven analyses (i.e., assessing the presence of a specific species) on variably sized reference databases while dramatically improving processing speeds. We tested the performance and accuracy of HAYSTAC using simulated Illumina libraries, both with and without ancient DNA damage, and compared the results to other currently available methods (i.e., Kraken2/Bracken, KrakenUniq, MALT/HOPS, and Sigma). HAYSTAC identified fewer false positives than both Kraken2/Bracken, KrakenUniq and MALT in all simulations, and fewer than Sigma in simulations of ancient data. It uses less memory than Kraken2/Bracken, KrakenUniq as well as MALT both during database construction and sample analysis. Lastly, we used HAYSTAC to search for specific pathogens in two published ancient metagenomic datasets, demonstrating how it can be applied to empirical datasets. HAYSTAC is available from https://github.com/antonisdim/HAYSTAC.

The emerging field of paleo-metagenomics (i.e., metagenomics from ancient DNA) holds great promise for novel discoveries in fields as diverse as pathogen evolution and paleoenvironmental reconstruction. However, there is presently a lack of computational methods for species identification from microbial communities in both degraded and nondegraded DNA material. Here, we present “HAYSTAC”, a user-friendly software package that implements a novel probabilistic model for species identification in metagenomic data obtained from both degraded and non-degraded DNA material. Through extensive benchmarking, we show that HAYSTAC can be used for accurately profiling the community composition, as well as for direct hypothesis testing for the presence of extremely low-abundance taxa, in complex metagenomic samples. After analysing simulated and publicly available datasets, HAYSTAC consistently produced the lowest number of false positive identifications during taxonomic profiling, produced robust results when databases of restricted size were used, and showed increased sensitivity for pathogen detection compared to other specialist methods. The newly proposed probabilistic model and software employed by HAYSTAC can have a substantial impact on the robust and rapid pathogen discovery in degraded/shallow sequenced metagenomic samples while optimising the use of computational resources.

Prostate cancer in omics era

Recent advances in omics technology have prompted extraordinary attempts to define the molecular changes underlying the onset and progression of a variety of complex human diseases, including cancer. Since the advent of sequencing technology, cancer biology has become increasingly reliant on the generation and integration of data generated at these levels. The availability of multi-omic data has transformed medicine and biology by enabling integrated systems-level approaches. Multivariate signatures are expected to play a role in cancer detection, screening, patient classification, assessment of treatment response, and biomarker identification. This review reports current findings and highlights a number of studies that are both novel and groundbreaking in their application of multi Omics to prostate cancer.

Anti-bacterial and Anti-biofilm Effects of Equol on Yersinia enterocolitica

Yersinia enterocolitica has clinical significance due to its etiological role in yersiniosis and gastroenteritis. This study was designed to assess anti-bacterial and anti-biofilm effects of equol on Y. enterocolitica via phenotypic and genetic analyses. To determine its anti-bacterial activity, minimum inhibitory concentrations (MICs) of equol against clinically isolated Y. enterocolitica strains were analyzed. Subsequently, it was confirmed that the sub-MIC90 value of equol could inhibit biofilm formation and reduce preformed biofilm. Furthermore, it was found that equol could reduce the expression of biofilm-related (hmsT) gene in Y. enterocolitica. This study also demonstrated that equol not only reduced levels of bacterial motility, but also decreased the expression of a motility-related (flhDC) gene in Y. enterocolitica. XTT [2,3-bis (2-metoxy-4-nitro-5-sulfophenyl)-2H-tetrazolium-5-carboxanilide] reduction analysis revealed that equol attenuated cellular metabolic activities in Y. enterocolitica biofilm. Additionally, changes in biomass and cell density in equol-treated biofilms were visualized using a confocal laser scanning microscope. In conclusion, this study suggests that equol is a potential anti-bacterial and anti-biofilm agent to treat Y. enterocolitica.

Improving environmental stress resilience in crops by genome editing: insights from extremophile plants

In basic and applied sciences, genome editing has become an indispensable tool, especially the versatile and adaptable CRISPR/Cas9 system. Using CRISPR/Cas9 in plants has enabled modifications of many valuable traits, including environmental stress tolerance, an essential aspect when it comes to ensuring food security under climate change pressure. The CRISPR toolbox enables faster and more precise plant breeding by facilitating: multiplex gene editing, gene pyramiding, and de novo domestication. In this paper, we discuss the most recent advances in CRISPR/Cas9 and alternative CRISPR-based systems, along with the technical challenges that remain to be overcome. A revision of the latest proof-of-concept and functional characterization studies has indeed provided more insight into the quantitative traits affecting crop yield and stress tolerance. Additionally, we focus on the applications of CRISPR/Cas9 technology in regard to extremophile plants, due to their significance on: industrial, ecological and economic levels. These still unexplored genetic resources could provide the means to harden our crops against the threat of climate change, thus ensuring food security over the next century.

TT-Mars: structural variants assessment based on haplotype-resolved assemblies

Variant benchmarking is often performed by comparing a test callset to a gold standard set of variants. In repetitive regions of the genome, it may be difficult to establish what is the truth for a call, for example, when different alignment scoring metrics provide equally supported but different variant calls on the same data. Here, we provide an alternative approach, TT-Mars, that takes advantage of the recent production of high-quality haplotype-resolved genome assemblies by providing false discovery rates for variant calls based on how well their call reflects the content of the assembly, rather than comparing calls themselves.

Fast and robust imputation for miRNA expression data using constrained least squares

BACKGROUND

High dimensional transcriptome profiling, whether through next generation sequencing techniques or high-throughput arrays, may result in scattered variables with missing data. Data imputation is a common strategy to maximize the inclusion of samples by using statistical techniques to fill in missing values. However, many data imputation methods are cumbersome and risk introduction of systematic bias.

RESULTS

We present a new data imputation method using constrained least squares and algorithms from the inverse problems literature and present applications for this technique in miRNA expression analysis. The proposed technique is shown to offer an imputation orders of magnitude faster, with greater than or equal accuracy when compared to similar methods from the literature.

CONCLUSIONS

This study offers a robust and efficient algorithm for data imputation, which can be used, e.g., to improve cancer prediction accuracy in the presence of missing data.

Computational graph pangenomics: a tutorial on data structures and their applications

Computational pangenomics is an emerging research field that is changing the way computer scientists are facing challenges in biological sequence analysis. In past decades, contributions from combinatorics, stringology, graph theory and data structures were essential in the development of a plethora of software tools for the analysis of the human genome. These tools allowed computational biologists to approach ambitious projects at population scale, such as the 1000 Genomes Project. A major contribution of the 1000 Genomes Project is the characterization of a broad spectrum of genetic variations in the human genome, including the discovery of novel variations in the South Asian, African and European populations-thus enhancing the catalogue of variability within the reference genome. Currently, the need to take into account the high variability in population genomes as well as the specificity of an individual genome in a personalized approach to medicine is rapidly pushing the abandonment of the traditional paradigm of using a single reference genome. A graph-based representation of multiple genomes, or a graph pangenome, is replacing the linear reference genome. This means completely rethinking well-established procedures to analyze, store, and access information from genome representations. Properly addressing these challenges is crucial to face the computational tasks of ambitious healthcare projects aiming to characterize human diversity by sequencing 1M individuals (Stark et al. 2019). This tutorial aims to introduce readers to the most recent advances in the theory of data structures for the representation of graph pangenomes. We discuss efficient representations of haplotypes and the variability of genotypes in graph pangenomes, and highlight applications in solving computational problems in human and microbial (viral) pangenomes.

Statistics or biology: the zero-inflation controversy about scRNA-seq data

Researchers view vast zeros in single-cell RNA-seq data differently: some regard zeros as biological signals representing no or low gene expression, while others regard zeros as missing data to be corrected. To help address the controversy, here we discuss the sources of biological and non-biological zeros; introduce five mechanisms of adding non-biological zeros in computational benchmarking; evaluate the impacts of non-biological zeros on data analysis; benchmark three input data types: observed counts, imputed counts, and binarized counts; discuss the open questions regarding non-biological zeros; and advocate the importance of transparent analysis.

Phylogenetic Relatedness and Genome Structure of Yersinia ruckeri Revealed by Whole Genome Sequencing and a Comparative Analysis

Yersinia ruckeri is the causative agent of enteric redmouth disease (ERM), a serious infection that affects global aquaculture with high economic impact. The present study used whole genome sequences to perform a comparative analysis on 10 Y. ruckeri strains and to explore their genetic relatedness to other members of the genus. Y. ruckeri, Yersinia entomophaga, and Yersinia nurmii formed a species complex that constitutes the most basal lineage of the genus. The results showed that the taxonomy of Y. ruckeri strains is better defined by using a core genome alignment and phylogenetic analysis. The distribution of accessory genes in all Yersinia species revealed the presence of 303 distinctive genes in Y. ruckeri. Of these, 169 genes were distributed in 17 genomic islands potentially involved in the pathogenesis of ERM via (1) encoding virulence factors such as Afp18, Yrp1, phage proteins and (2) improving the metabolic capabilities by enhancing utilization and metabolism of iron, amino acids (specifically, arginine and histidine), and carbohydrates. The genome of Y. ruckeri is highly conserved regarding gene structure, gene layout and functional categorization of genes. It contains various components of mobile genetic elements but lacks the CRISPR-Cas system and possesses a stable set of virulence genes possibly playing a critical role in pathogenicity. Distinct virulence plasmids were exclusively restricted to a specific clonal group of Y. ruckeri (CG4), possibly indicating a selective advantage. Phylogenetic analysis of Y. ruckeri genomes revealed the co-presence of multiple genetically distant lineages of Y. ruckeri strains circulating in Germany. Our results also suggest a possible dissemination of a specific group of strains in the United States, Peru, Germany, and Denmark. In conclusion, this study provides new insights into the taxonomy and evolution of Y. ruckeri and contributes to a better understanding of the pathogenicity of ERM in aquaculture. The genomic analysis presented here offers a framework for the development of more efficient control strategies for this pathogen.

SVDNVLDA: predicting lncRNA-disease associations by Singular Value Decomposition and node2vec

Background

Numerous studies on discovering the roles of long non-coding RNAs (lncRNAs) in the occurrence, development and prognosis progresses of various human diseases have drawn substantial attentions. Since only a tiny portion of lncRNA-disease associations have been properly annotated, an increasing number of computational methods have been proposed for predicting potential lncRNA-disease associations. However, traditional predicting models lack the ability to precisely extract features of biomolecules, it is urgent to find a model which can identify potential lncRNA-disease associations with both efficiency and accuracy.

Results

In this study, we proposed a novel model, SVDNVLDA, which gained the linear and non-linear features of lncRNAs and diseases with Singular Value Decomposition (SVD) and node2vec methods respectively. The integrated features were constructed from connecting the linear and non-linear features of each entity, which could effectively enhance the semantics contained in ultimate representations. And an XGBoost classifier was employed for identifying potential lncRNA-disease associations eventually.

Conclusions

We propose a novel model to predict lncRNA-disease associations. This model is expected to identify potential relationships between lncRNAs and diseases and further explore the disease mechanisms at the lncRNA molecular level.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04457-1.

CircRNAs as potent biomarkers in ovarian cancer: a systematic scoping review

More powerful prognostic and diagnostic tools are urgently needed for identifying and treating ovarian cancer (OC), which is the most fatal malignancy in women in developed countries. Circular RNAs (circRNAs) are conservative and stable looped molecules that can regulate gene expression by competing with other endogenous microRNA sponges. This discovery provided new insight into novel methods for regulating genes that are involved in many disorders and cancers. This review focuses on the dysregulated expression of circRNAs as well as their diagnostic and prognostic values in OC. We found that studies have identified twenty-one downregulated circRNAs and fifty-seven upregulated ones. The results of these studies confirm that circRNAs might be potent biomarkers with diagnostic, prognostic and therapeutic target value for OC. We also consider the connection between circRNAs and OC cell proliferation, apoptosis, metastasis, and chemotherapy resistance and sensitivity.

Yersinia pseudotuberculosis YopJ Limits Macrophage Response by Downregulating COX-2-Mediated Biosynthesis of PGE2 in a MAPK/ERK-Dependent Manner

Prostaglandin E2 (PGE2) is an essential immunomodulatory lipid released by cells in response to infection with many bacteria, yet its function in macrophage-mediated bacterial clearance is poorly understood. Yersinia overall inhibits the inflammatory circuit, but its effect on PGE2 production is unknown. We hypothesized that one of the Yersinia effector proteins is responsible for the inhibition of PGE2 biosynthesis. We identified that yopB-deficient Y. enterocolitica and Y. pseudotuberculosis deficient in the secretion of virulence proteins via a type 3 secretion system (T3SS) failed to inhibit PGE2 biosynthesis in macrophages. Consistently, COX-2-mediated PGE2 biosynthesis is upregulated in cells treated with heat-killed or T3SS-deficient Y. pseudotuberculosis but diminished in the presence of a MAPK/ERK inhibitor. Mutants expressing catalytically inactive YopJ induce similar levels of PGE2 as heat-killed or ΔyopB Y. pseudotuberculosis, reversed by YopJ complementation. Shotgun proteomics discovered host pathways regulated in a YopJ-mediated manner, including pathways regulating PGE2 synthesis and oxidative phosphorylation. Consequently, this study identified that YopJ-mediated inhibition of MAPK signal transduction serves as a mechanism targeting PGE2, an alternative means of inflammasome inhibition by Yersinia. Finally, we showed that EP4 signaling supports macrophage function in clearing intracellular bacteria. In summary, our unique contribution was to determine a bacterial virulence factor that targets COX-2 transcription, thereby enhancing the intracellular survival of yersiniae. Future studies should investigate whether PGE2 or its stable synthetic derivatives could serve as a potential therapeutic molecule to improve the outcomes of specific bacterial infections. Since other pathogens encode YopJ homologs, this mechanism is expected to be present in other infections. IMPORTANCE PGE2 is a critical immunomodulatory lipid, but its role in bacterial infection and pathogen clearance is poorly understood. We previously demonstrated that PGE2 leads to macrophage polarization toward the M1 phenotype and stimulates inflammasome activation in infected macrophages. Finally, we also discovered that PGE2 improved the clearance of Y. enterocolitica. The fact that Y. enterocolitica hampers PGE2 secretion in a type 3 secretion system (T3SS)-dependent manner and because PGE2 appears to assist macrophage in the clearance of this bacterium indicates that targeting of the eicosanoid pathway by Yersinia might be an adaption used to counteract host defenses. Our study identified a mechanism used by Yersinia that obstructs PGE2 biosynthesis in human macrophages. We showed that Y. pseudotuberculosis interferes with PGE2 biosynthesis by using one of its T3SS effectors, YopJ. Specifically, YopJ targets the host COX-2 enzyme responsible for PGE2 biosynthesis, which happens in a MAPK/ER-dependent manner. Moreover, in a shotgun proteomics study, we also discovered other pathways that catalytically active YopJ targets in the infected macrophages. YopJ was revealed to play a role in limiting host LPS responses, including repression of EGR1 and JUN proteins, which control transcriptional activation of proinflammatory cytokine production such as interleukin-1β. Since YopJ has homologs in other bacterial species, there are likely other pathogens that target and inhibit PGE2 biosynthesis. In summary, our study's unique contribution was to determine a bacterial virulence factor that targets COX-2 transcription. Future studies should investigate whether PGE2 or its stable synthetic derivatives could serve as a potential therapeutic target.

VariantStore: an index for large-scale genomic variant search

Efficiently scaling genomic variant search indexes to thousands of samples is computationally challenging due to the presence of multiple coordinate systems to avoid reference biases. We present VariantStore, a system that indexes genomic variants from multiple samples using a variation graph and enables variant queries across any sample-specific coordinate system. We show the scalability of VariantStore by indexing genomic variants from the TCGA project in 4 h and the 1000 Genomes project in 3 h. Querying for variants in a gene takes between 0.002 and 3 seconds using memory only 10% of the size of the full representation.

Current cancer driver variant predictors learn to recognize driver genes instead of functional variants

BACKGROUND

Identifying variants that drive tumor progression (driver variants) and distinguishing these from variants that are a byproduct of the uncontrolled cell growth in cancer (passenger variants) is a crucial step for understanding tumorigenesis and precision oncology. Various bioinformatics methods have attempted to solve this complex task.

RESULTS

In this study, we investigate the assumptions on which these methods are based, showing that the different definitions of driver and passenger variants influence the difficulty of the prediction task. More importantly, we prove that the data sets have a construction bias which prevents the machine learning (ML) methods to actually learn variant-level functional effects, despite their excellent performance. This effect results from the fact that in these data sets, the driver variants map to a few driver genes, while the passenger variants spread across thousands of genes, and thus just learning to recognize driver genes provides almost perfect predictions.

CONCLUSIONS

To mitigate this issue, we propose a novel data set that minimizes this bias by ensuring that all genes covered by the data contain both driver and passenger variants. As a result, we show that the tested predictors experience a significant drop in performance, which should not be considered as poorer modeling, but rather as correcting unwarranted optimism. Finally, we propose a weighting procedure to completely eliminate the gene effects on such predictions, thus precisely evaluating the ability of predictors to model the functional effects of single variants, and we show that indeed this task is still open.

Crosstalk between codon optimality and cis-regulatory elements dictates mRNA stability

BACKGROUND

The regulation of messenger RNA (mRNA) stability has a profound impact on gene expression dynamics during embryogenesis. For example, in animals, maternally deposited mRNAs are degraded after fertilization to enable new developmental trajectories. Regulatory sequences in 3' untranslated regions (3'UTRs) have long been considered the central determinants of mRNA stability. However, recent work indicates that the coding sequence also possesses regulatory information. Specifically, translation in cis impacts mRNA stability in a codon-dependent manner. However, the strength of this mechanism during embryogenesis, as well as its relationship with other known regulatory elements, such as microRNA, remains unclear.

RESULTS

Here, we show that codon composition is a major predictor of mRNA stability in the early embryo. We show that this mechanism works in combination with other cis-regulatory elements to dictate mRNA stability in zebrafish and Xenopus embryos as well as in mouse and human cells. Furthermore, we show that microRNA targeting efficacy can be affected by substantial enrichment of optimal (stabilizing) or non-optimal (destabilizing) codons. Lastly, we find that one microRNA, miR-430, antagonizes the stabilizing effect of optimal codons during early embryogenesis in zebrafish.

CONCLUSIONS

By integrating the contributions of different regulatory mechanisms, our work provides a framework for understanding how combinatorial control of mRNA stability shapes the gene expression landscape.

Tuning parameters of dimensionality reduction methods for single-cell RNA-seq analysis

BACKGROUND

Many computational methods have been developed recently to analyze single-cell RNA-seq (scRNA-seq) data. Several benchmark studies have compared these methods on their ability for dimensionality reduction, clustering, or differential analysis, often relying on default parameters. Yet, given the biological diversity of scRNA-seq datasets, parameter tuning might be essential for the optimal usage of methods, and determining how to tune parameters remains an unmet need.

RESULTS

Here, we propose a benchmark to assess the performance of five methods, systematically varying their tunable parameters, for dimension reduction of scRNA-seq data, a common first step to many downstream applications such as cell type identification or trajectory inference. We run a total of 1.5 million experiments to assess the influence of parameter changes on the performance of each method, and propose two strategies to automatically tune parameters for methods that need it.

CONCLUSIONS

We find that principal component analysis (PCA)-based methods like scran and Seurat are competitive with default parameters but do not benefit much from parameter tuning, while more complex models like ZinbWave, DCA, and scVI can reach better performance but after parameter tuning.

Mutational Effects on Carbapenem Hydrolysis of YEM-1, a New Subclass B2 Metallo-β-Lactamase from Yersinia mollaretii

Analysis of the genome sequence of Yersinia mollaretii ATCC 43969 identified the bla _YEM gene, encoding YEM-1, a putative subclass B2 metallo-β-lactamase. The objectives of our work were to produce and purify YEM-1 and to complete its kinetic characterization. YEM-1 displayed the narrowest substrate range among known subclass B2 metallo-β-lactamases, since it can hydrolyze imipenem, but not other carbapenems, such as biapenem, meropenem, doripenem, and ertapenem, with high catalytic efficiency. A possible explanation of this activity profile is the presence of tyrosine at residue 67 (loop L1), threonine at residue 156 (loop L2), and serine at residue 236 (loop L3). We showed that replacement of Y67 broadened the activity profile of the enzyme for all carbapenems but still resulted in poor activity toward the other β-lactam classes.

Analysis of biosorption and biotransformation mechanism of Pseudomonas chengduensis strain MBR under Cd(II) stress from genomic perspective

Microbial treatment of heavy metal-polluted sites is considered an environmentally friendly bioremediation technology with high potential. This study shows that Pseudomonas chengduensis strain MBR, a bacterium that can potentially be applied in the treatment of heavy metal pollution, is most affected by Cd(II) stress at the beginning of its growth. Up to 100% of total Cd(II) adsorption occurs in the first 48 h after treatment of stationary phase cells with Cd(II). A biofilm forms on the cell surface, Cd(II) adsorbs, and is reduced to Cd (0) in the form of nanoscale particles. The genome of strain MBR was sequenced, annotated and analyzed. We identified various genes potentially related to cadmium resistance, transport and metabolism. Analysis of the strain MBR genome is helpful to explore the mechanism of Cd(II) resistance, and can provide new ideas for cadmium pollution control.

Conservation of Rhodococcus equi (Magnusson 1923) Goodfellow and Alderson 1977 and rejection of Rhodococcus hoagii (Morse 1912) Kämpfer et al. 2014

A recent taxonomic study confirmed the synonymy of Rhodococcus equi (Magnusson 1923) Goodfellow and Alderson 1977 and Corynebacterium hoagii (Morse 1912) Eberson 1918. As a result, both R. equi and C. hoagii were reclassified as Rhodococcus hoagii comb. nov. in application of the principle of priority of the Prokaryotic Code. Because R. equi is a well-known animal and zoonotic human pathogen, and a bacterial name solidly established in the veterinary and medical literature, we and others argued that the nomenclatural change may cause error and confusion and be potentially perilous. We have now additionally found that the nomenclatural type of the basonym C. hoagii, ATCC 7005^T, does not correspond with the original description of the species C. hoagii in the early literature. Its inclusion as the C. hoagii type on the Approved Lists 1980 results in a change in the characters of the taxon and in C. hoagii designating two different bacteria. Moreover, ATCC 7005, the only strain in circulation under the name C. hoagii, does not have a well documented history; it is unclear why it was deposited as C. hoagii and a possible mix-up with a Corynebacterium (Rhodococcus) equi isolate is a reasonable assumption. We therefore request the rejection of Rhodococcus hoagii as a nomen ambiguum, nomen dubium and nomen perplexum in addition to nomen periculosum, and conservation of the name Rhodococcus equi, according to Rules 56ab of the Code.

Single-cell ATAC-seq signal extraction and enhancement with SCATE

Single-cell sequencing assay for transposase-accessible chromatin (scATAC-seq) is the state-of-the-art technology for analyzing genome-wide regulatory landscapes in single cells. Single-cell ATAC-seq data are sparse and noisy, and analyzing such data is challenging. Existing computational methods cannot accurately reconstruct activities of individual cis-regulatory elements (CREs) in individual cells or rare cell subpopulations. We present a new statistical framework, SCATE, that adaptively integrates information from co-activated CREs, similar cells, and publicly available regulome data to substantially increase the accuracy for estimating activities of individual CREs. We demonstrate that SCATE can be used to better reconstruct the regulatory landscape of a heterogeneous sample.

Comprehensive Laboratory Evaluation of a Lateral Flow Assay for the Detection of Yersinia pestis

We conducted a comprehensive, multiphase laboratory evaluation of the Plague BioThreat Alert® (BTA) test, a lateral flow immunoassay (LFA), for the rapid detection of Yersinia pestis. The study was conducted in 7 phases at 2 sites to assess the performance of the LFA. The limit of detection (LOD) was determined using both a virulent and avirulent strain of Y. pestis, CO99-3015 (105 CFU/ml) and A1122 (104 CFU/ml), respectively. In the other phases, 18 Y. pestis strains, 20 phylogenetic near-neighbor strains, 61 environmental background microorganisms, 26 white powders, and a pooled aerosol sample were also tested. A total of 1,110 LFA test results were obtained, and their analysis indicates that this LFA had a sensitivity of 97.65% and specificity of 96.57%. These performance data are important for accurate interpretation of qualitative results arising from testing suspicious white powders and aerosol samples in the field. Any positive specimen in this assay is considered presumptive positive and should be referred to the Centers for Disease Control and Prevention Laboratory Response Network for additional testing, confirmation, and characterization for an appropriate public health response.

Genome Sequencing of Mesonia algae K4-1 Reveals Its Adaptation to the Arctic Ocean

The special ecological environment of the Arctic has brought about a large number of salt-tolerant and psychrotolerant microorganisms. We isolated two culturable bacterial strains of the genus Mesonia; one from the Arctic ocean, Mesonia algae K4-1, and one from the tropical sea, Mesonia sp. HuA40. Our genome analysis and phenotypic experiments indicated that Mesonia algae K4-1 is a moderately halophilic and psychrophilic bacterium. Mesonia algae K4-1 can tolerate 3–14% NaCl and grow at a wide range of temperatures from 4 to 50°C. Mesonia sp. HuA40 is a mesophilic bacterium that can only grow with 3–9% NaCl. In addition, the salt adaptation strategy of Mesonia algae K4-1 accumulates organic osmolytes in the cell. RNA helicases, glutathione and organic compatible solutes may play important roles in maintaining the metabolism and physiological function of Mesonia algae K4-1 under cold stress. Moreover, the ability of Mesonia algae K4-1 to adapt to an oligotrophic marine environment is likely due to the synthesis of a large number of extracellular polysaccharides and the secretion of various families of extracellular proteases. This study systematically analyzed the relationship between genomic differentiation and environmental factors of the Mesonia genus and revealed the possible adaptation mechanism of Mesonia algae K4-1 in the extreme Arctic marine environment at the genomic level.

A Recombinant Attenuated Yersinia pseudotuberculosis Vaccine Delivering a Y. pestis YopENt138-LcrV Fusion Elicits Broad Protection against Plague and Yersiniosis in Mice

In this study, a novel recombinant attenuated Yersinia pseudotuberculosis PB1+ strain (χ10069) engineered with ΔyopK ΔyopJ Δasd triple mutations was used to deliver a Y. pestis fusion protein, YopE amino acid 1 to 138-LcrV (YopENt138-LcrV), to Swiss Webster mice as a protective antigen against infections by yersiniae. χ10069 bacteria harboring the pYA5199 plasmid constitutively synthesized the YopENt138-LcrV fusion protein and secreted it via the type 3 secretion system (T3SS) at 37°C under calcium-deprived conditions. The attenuated strain χ10069(pYA5199) was manifested by the establishment of controlled infection in different tissues without developing conspicuous signs of disease in histopathological analysis of microtome sections. A single-dose oral immunization of χ10069(pYA5199) induced strong serum antibody titers (log10 mean value, 4.2), secretory IgA in bronchoalveolar lavage (BAL) fluid from immunized mice, and Yersinia-specific CD4+ and CD8+ T cells producing high levels of tumor necrosis factor alpha (TNF-α), gamma interferon (IFN-γ), and interleukin 2 (IL-2), as well as IL-17, in both lungs and spleens of immunized mice, conferring comprehensive Th1- and Th2-mediated immune responses and protection against bubonic and pneumonic plague challenges, with 80% and 90% survival, respectively. Mice immunized with χ10069(pYA5199) also exhibited complete protection against lethal oral infections by Yersinia enterocolitica WA and Y. pseudotuberculosis PB1+. These findings indicated that χ10069(pYA5199) as an oral vaccine induces protective immunity to prevent bubonic and pneumonic plague, as well as yersiniosis, in mice and would be a promising oral vaccine candidate for protection against plague and yersiniosis for human and veterinary applications.

Yersinia kristensenii subsp. rochesterensis subsp. nov., isolated from human feces

A single bacterial isolate, EPLC-04^T, was isolated from human feces and identified as representing a member of the genus Yersinia on the basis of phenotypic characteristics, matrix assisted laser desorption ionization time-of-flight mass spectrometry and partial 16S rRNA gene sequencing. The isolate's phenotypic profile differed from that described for the most closely related species, Yersinia kristensenii, by exhibiting lipase production and lacking pyrazinamidase activity. Multiple genetic targets, including the complete (1465 bp) 16S rRNA gene sequence and partial sequences of groEL (539 bp), gyrB (935 bp), glnA (525 bp) and recA (535 bp) indicated that the isolate exhibited 98.91, 92.16, 90.81, 92.78 and 89.01 % identity with Yersinia aldovae, 98.98, 91.99, 90.17, 89.77 and 89.55 % identity with Yersinia intermedia, and 99.66, 98.11, 98.50, 98.49 and 98.51 % identity with Y. kristensenii, respectively. Phylogenetic reconstructions based on the combination of the four housekeeping genes indicated that the isolate formed a unique branch, supported by a bootstrap value of 100 %. Digital DNA-DNA homology and 16S rRNA gene sequencing identified EPLC-04^T as representing Y. kristensenii. However, the unique phenotypic traits and results of phylogenetic analysis indicate that it represents a novel subspecies of Y. kristensenii. The name Yersinia kristenseniisubsp. rochesterensis subsp. nov. is proposed for this novel taxon (type strain EPLC-04^T=ATCC BAA-2637^T, DSMZ 28595^T).

Occurrence of Yersinia rohdei among feral reindeer (Rangifer t. tarandus) and kelp gulls (Larus dominicanus) on the Sub-Antarctic island South Georgia

Introduction: During a research expedition in 2012, faecal samples were collected from feral reindeer and kelp gulls on the main island of South Georgia in the Sub-Antarctic region of the Atlantic. The samples were analysed for bacteria of the genus Yersinia with the aim of identifying isolates to the species level. Materials and Methods: A total of 11 reindeer samples and 26 Kelp Gull samples were retrieved from the location of Stromness, kept refrigerated and cultivated for gram-negative bacteria. Results: Three of the samples showed growth of Yersinia rohdei, as confirmed by biochemical typing, MALDI-TOF and 16S rRNA sequencing. The isolates were indistinguishable from each other by 16S sequencing, and differed by a single base pair from the type strain of Y. rohdei. Discussion: The Yersinia genus contains well-known pathogens of significance to both human and veterinary medicine, but the public health and animal health relevance of Y. rohdei is unknown. Although it is clear that Y. rhodei is present in the south Georgian biotope, its importance and relevance for biological diversity is unknown, as is if this presence is merely a reflection of human activities.

The Infection Process of Yersinia ruckeri: Reviewing the Pieces of the Jigsaw Puzzle

Finding the keys to understanding the infectious process of Yersinia ruckeri was not a priority for many years due to the prompt development of an effective biotype 1 vaccine which was used mainly in Europe and USA. However, the gradual emergence of outbreaks in vaccinated fish, which have been reported since 2003, has awakened interest in the mechanism of virulence in this pathogen. Thus, during the last two decades, a large number of studies have considerably enriched our knowledge of many aspects of the pathogen and its interaction with the host. By means of both conventional and a variety of novel strategies, such as cell GFP tagging, bioluminescence imaging and optical projection tomography, it has been possible to determine three putative Y. ruckeri infection routes, the main point of entry for the bacterium being the gill lamellae. Moreover, a wide range of potential virulence factors have been highlighted by specific gene mutagenesis strategies or genome-wide transposon/plasmid insertion-based screening approaches, such us in vivo expression technology (IVET) and signature tagged mutagenesis (STM). Finally, recent proteomic and whole genomic analyses have allowed many of the genes and systems that are potentially implicated in the organism's pathogenicity and its adaptation to the host environmental conditions to be elucidated. Altogether, these studies contribute to a better understanding of the infectious process of Y. ruckeri in fish, which is crucial for the development of more effective strategies for preventing or treating enteric redmouth disease (ERM).

Modeling and correct the GC bias of tumor and normal WGS data for SCNA based tumor subclonal population inferring

BACKGROUND

Somatic copy number alternations (SCNAs) can be utilized to infer tumor subclonal populations in whole genome seuqncing studies, where usually their read count ratios between tumor-normal paired samples serve as the inferring proxy. Existing SCNA based subclonal population inferring tools consider the GC bias of tumor and normal sample is of the same fature, and could be fully offset by read count ratio. However, we found that, the read count ratio on SCNA segments presents a Log linear biased pattern, which influence existing read count ratios based subclonal inferring tools performance. Currently no correction tools take into account the read ratio bias.

RESULTS

We present Pre-SCNAClonal, a tool that improving tumor subclonal population inferring by correcting GC-bias at SCNAs level. Pre-SCNAClonal first corrects GC bias using Markov chain Monte Carlo probability model, then accurately locates baseline DNA segments (not containing any SCNAs) with a hierarchy clustering model. We show Pre-SCNAClonal's superiority to exsiting GC-bias correction methods at any level of subclonal population.

CONCLUSIONS

Pre-SCNAClonal could be run independently as well as serving as pre-processing/gc-correction step in conjuntion with exsiting SCNA-based subclonal inferring tools.

Detection of CNVs in NGS Data Using VS-CNV

Copy number variations have been linked to numerous genetic diseases including cancer, Parkinson's disease, pancreatitis, and lupus. While current best practices for CNV detection often require using microarrays for detecting large CNVs or multiplex ligation-dependent probe amplification (MLPA) for gene-sized CNVs, new methods have been developed with the goal of replacing both of these specialized assays with bioinformatic analysis applied to next-generation sequencing (NGS) data. Because NGS is already used by clinical labs to detect small coding variants, this approach reduces associated costs, resources, and analysis time. This chapter provides an overview of the various approaches to CNV detection via NGS data, and examines VS-CNV, a commercial tool developed by Golden Helix, which provides robust CNV calling capabilities for both gene panel and exome data.

Brief Protocol for EDGE Bioinformatics: Analyzing Microbial and Metagenomic NGS Data

Next-generation sequencing (NGS) offers unparalleled resolution for untargeted organism detection and characterization. However, the majority of NGS analysis programs require users to be proficient in programming and command-line interfaces. EDGE bioinformatics was developed to offer scientists with little to no bioinformatics expertise a point-and-click platform for analyzing sequencing data in a rapid and reproducible manner. EDGE (Empowering the Development of Genomics Expertise) v1.0 released in January 2017, is an intuitive web-based bioinformatics platform engineered for the analysis of microbial and metagenomic NGS-based data ( Li et al., 2017 ). The EDGE bioinformatics suite combines vetted publicly available tools, and tracks settings to ensure reliable and reproducible analysis workflows. To execute the EDGE workflow, only raw sequencing reads and a project ID are necessary. Users can access in-house data, or run analyses on samples deposited in Sequence Read Archive. Default settings offer a robust first-glance and are often sufficient for novice users. All analyses are modular; users can easily turn workflows on/off, and modify parameters to cater to project needs. Results are compiled and available for download in a PDF-formatted report containing publication quality figures. We caution that interpreting results still requires in-depth scientific understanding, however report visuals are often informative, even to novice users.

Enabling the democratization of the genomics revolution with a fully integrated web-based bioinformatics platform

Continued advancements in sequencing technologies have fueled the development of new sequencing applications and promise to flood current databases with raw data. A number of factors prevent the seamless and easy use of these data, including the breadth of project goals, the wide array of tools that individually perform fractions of any given analysis, the large number of associated software/hardware dependencies, and the detailed expertise required to perform these analyses. To address these issues, we have developed an intuitive web-based environment with a wide assortment of integrated and cutting-edge bioinformatics tools in pre-configured workflows. These workflows, coupled with the ease of use of the environment, provide even novice next-generation sequencing users with the ability to perform many complex analyses with only a few mouse clicks and, within the context of the same environment, to visualize and further interrogate their results. This bioinformatics platform is an initial attempt at Empowering the Development of Genomics Expertise (EDGE) in a wide range of applications for microbial research.

Whole genome analysis of Yersinia ruckeri isolated over 27 years in Australia and New Zealand reveals geographical endemism over multiple lineages and recent evolution under host selection

Yersinia ruckeri is a salmonid pathogen with widespread distribution in cool-temperate waters including Australia and New Zealand, two isolated environments with recently developed salmonid farming industries. Phylogenetic comparison of 58 isolates from Australia, New Zealand, USA, Chile, Finland and China based on non-recombinant core genome SNPs revealed multiple deep-branching lineages, with a most recent common ancestor estimated at 18 500 years BP (12 355–24 757 95% HPD) and evidence of Australasian endemism. Evolution within the Tasmanian Atlantic salmon serotype O1b lineage has been slow, with 63 SNPs describing the variance over 27 years. Isolates from the prevailing lineage are poorly/non-motile compared to a lineage pre-vaccination, introduced in 1997, which is highly motile but has not been isolated since from epizootics. A non-motile phenotype has arisen independently in Tasmania compared to Europe and USA through a frameshift in fliI, encoding the ATPase of the flagella cluster. We report for the first time lipopolysaccharide O-antigen serotype O2 isolates in Tasmania. This phenotype results from deletion of the O-antigen cluster and consequent loss of high-molecular-weight O-antigen. This phenomenon has occurred independently on three occasions on three continents (Australasia, North America and Asia) as O2 isolates from the USA, China and Tasmania share the O-antigen deletion but occupy distant lineages. Despite the European and North American origins of the Australasian salmonid stocks, the lineages of Y. ruckeri in Australia and New Zealand are distinct from those of the northern hemisphere, suggesting they are pre-existing ancient strains that have emerged and evolved with the introduction of susceptible hosts following European colonization.

Molecular Evolution of the Yersinia Major Outer Membrane Protein C (OmpC)

The genus Yersinia includes species with a wide range of eukaryotic hosts (from fish, insects, and plants to mammals and humans). One of the major outer membrane proteins, the porin OmpC, is preferentially expressed in the host gut, where osmotic pressure, temperature, and the concentrations of nutrients and toxic products are relatively high. We consider here the molecular evolution and phylogeny of Yersinia ompC. The maximum likelihood gene tree reflects the macroevolution processes occurring within the genus Yersinia. Positive selection and horizontal gene transfer are the key factors of ompC diversification, and intraspecies recombination was revealed in two Yersinia species. The impact of recombination on ompC evolution was different from that of another major porin gene, ompF, possibly due to the emergence of additional functions and conservation of the basic transport function. The predicted antigenic determinants of OmpC were located in rapidly evolving regions, which may indicate the evolutionary mechanisms of Yersinia adaptation to the host immune system.

'Add, stir and reduce': Yersinia spp. as model bacteria for pathogen evolution

Pathogenic species in the Yersinia genus have historically been targets for research aimed at understanding how bacteria evolve into mammalian pathogens. The advent of large-scale population genomic studies has greatly accelerated the progress in this field, and Yersinia pestis, Yersinia pseudotuberculosis and Yersinia enterocolitica have once again acted as model organisms to help shape our understanding of the evolutionary processes involved in pathogenesis. In this Review, we highlight the gene gain, gene loss and genome rearrangement events that have been identified by genomic studies in pathogenic Yersinia species, and we discuss how these findings are changing our understanding of pathogen evolution. Finally, as these traits are also found in the genomes of other species in the Enterobacteriaceae, we suggest that they provide a blueprint for the evolution of enteropathogenic bacteria.

Genome Sequence of the Fish Pathogen Yersinia ruckeri SC09 Provides Insights into Niche Adaptation and Pathogenic Mechanism

Yersinia ruckeri is the etiologic agent of enteric red mouth disease (ERM), a severe fish disease prevailing in worldwide aquaculture industries. Here we report for the first time the complete genome of Y. ruckeri (Yersinia ruckeri) SC09, a highly virulent strain isolated from Ictalurus punctatus with severe septicemia. SC09 possesses a single chromosome of 3,923,491 base pairs, which contains 3651 predicted protein coding sequences (CDS), 19 rRNA genes, and 79 tRNA genes. Among the CDS, we have identified a Ysa locus containing genes encoding all the components of a type III secretion system (T3SS). Comparative analysis suggest that SC09-Ysa share extensive similarity in sequence, gene content, and gene arrangement with Salmonella enterica pathogenicity island 1 (SPI1) and chromosome-encoded T3SS from Yersinia enterocolitica biotype 1B. Furthermore, phylogenetic analysis shown that SC09-Ysa and SPI1-T3SS belong on the same branch of the phylogenetic tree. These results suggest that SC09-Ysa and SPI1-T3SS appear to mediate biological function to adapt to specific hosts with a similar niche, and both of them are likely to facilitate the development of an intracellular niche. In addition, our analysis also indicated that a substantial part of the SC09 genome might contribute to adaption in the intestinal microenvironment, including a number of proteins associated with aerobic or anaerobic respiration, signal transduction, and various stress reactions. Genomic analysis of the bacterium offered insights into the pathogenic mechanism associated with intracellular infection and intestinal survivability, which constitutes an important first step in understanding the pathogenesis of Y. ruckeri.

Genome and Evolution of Yersinia pestis

This chapter summarizes researches on genome and evolution features of Yersinia pestis, the young pathogen that evolved from Y. pseudotuberculosis at least 5000 years ago. Y. pestis is a highly clonal bacterial species with closed pan-genome. Comparative genomic analysis revealed that genome of Y. pestis experienced highly frequent rearrangement and genome decay events during the evolution. The genealogy of Y. pestis includes five major branches, and four of them seemed raised from a "big bang" node that is associated with the Black Death. Although whole genome-wide variation of Y. pestis reflected a neutral evolutionary process, the branch length in the genealogical tree revealed over dispersion, which was supposedly caused by varied historical molecular clock that is associated with demographical effect by alternate cycles of enzootic disease and epizootic disease in sylvatic plague foci. In recent years, palaeomicrobiology researches on victims of the Black Death, and Justinian's plague verified that two historical pandemics were indeed caused by Y. pestis, but the etiological lineages might be extinct today.

Yersinia ruckeri, the causative agent of enteric redmouth disease in fish

Enteric redmouth disease (ERM) is a serious septicemic bacterial disease of salmonid fish species. It is caused by Yersinia ruckeri, a Gram-negative rod-shaped enterobacterium. It has a wide host range, broad geographical distribution, and causes significant economic losses in the fish aquaculture industry. The disease gets its name from the subcutaneous hemorrhages, it can cause at the corners of the mouth and in gums and tongue. Other clinical signs include exophthalmia, darkening of the skin, splenomegaly and inflammation of the lower intestine with accumulation of thick yellow fluid. The bacterium enters the fish via the secondary gill lamellae and from there it spreads to the blood and internal organs. Y. ruckeri can be detected by conventional biochemical, serological and molecular methods. Its genome is 3.7 Mb with 3406–3530 coding sequences. Several important virulence factors of Y. ruckeri have been discovered, including haemolyin YhlA and metalloprotease Yrp1. Both non-specific and specific immune responses of fish during the course of Y. ruckeri infection have been well characterized. Several methods of vaccination have been developed for controlling both biotype 1 and biotype 2 Y. ruckeri strains in fish. This review summarizes the current state of knowledge regarding enteric redmouth disease and Y. ruckeri: diagnosis, genome, virulence factors, interaction with the host immune responses, and the development of vaccines against this pathogen.

A survey on the developmental intestinal microbiota research in China: The history, funding, and frontiers of gut bacteria

Up to 100 trillion bacteria are harbored in the human intestine with a mutualistic and interdependent relationship with the host during a long period of co-evolution. The so-called intestinal microbiota (IM) fulfill important metabolic tasks and the impaired stability may lead to IM-related diseases, including inflammatory bowel disease (IBD), colorectal cancer (CRC), metabolic syndrome (MS), liver diseases, and so on. Here, we review the past and development of IM research in China, including the achievements that Chinese researchers have made both in basic and clinical scientific field. Moreover, we evaluate the contributions of the National Natural Science Foundation of China (NSFC), the 973 National Basic Research Program of China (973 Program), the 863 National High Technology Research and Development Program of China (863 Program), and funds from the public health industry in the field of IM research.

YersiniaBase: a genomic resource and analysis platform for comparative analysis of Yersinia

BACKGROUND

Yersinia is a Gram-negative bacteria that includes serious pathogens such as the Yersinia pestis, which causes plague, Yersinia pseudotuberculosis, Yersinia enterocolitica. The remaining species are generally considered non-pathogenic to humans, although there is evidence that at least some of these species can cause occasional infections using distinct mechanisms from the more pathogenic species. With the advances in sequencing technologies, many genomes of Yersinia have been sequenced. However, there is currently no specialized platform to hold the rapidly-growing Yersinia genomic data and to provide analysis tools particularly for comparative analyses, which are required to provide improved insights into their biology, evolution and pathogenicity.

DESCRIPTION

To facilitate the ongoing and future research of Yersinia, especially those generally considered non-pathogenic species, a well-defined repository and analysis platform is needed to hold the Yersinia genomic data and analysis tools for the Yersinia research community. Hence, we have developed the YersiniaBase, a robust and user-friendly Yersinia resource and analysis platform for the analysis of Yersinia genomic data. YersiniaBase has a total of twelve species and 232 genome sequences, of which the majority are Yersinia pestis. In order to smooth the process of searching genomic data in a large database, we implemented an Asynchronous JavaScript and XML (AJAX)-based real-time searching system in YersiniaBase. Besides incorporating existing tools, which include JavaScript-based genome browser (JBrowse) and Basic Local Alignment Search Tool (BLAST), YersiniaBase also has in-house developed tools: (1) Pairwise Genome Comparison tool (PGC) for comparing two user-selected genomes; (2) Pathogenomics Profiling Tool (PathoProT) for comparative pathogenomics analysis of Yersinia genomes; (3) YersiniaTree for constructing phylogenetic tree of Yersinia. We ran analyses based on the tools and genomic data in YersiniaBase and the preliminary results showed differences in virulence genes found in Yersinia pestis and Yersinia pseudotuberculosis compared to other Yersinia species, and differences between Yersinia enterocolitica subsp. enterocolitica and Yersinia enterocolitica subsp. palearctica.

CONCLUSIONS

YersiniaBase offers free access to wide range of genomic data and analysis tools for the analysis of Yersinia. YersiniaBase can be accessed at http://yersinia.um.edu.my .

Complete Genome Sequence of the Fish Pathogen Yersinia ruckeri Strain SC09, Isolated from Diseased Ictalurus punctatus in China

Yersinia ruckeri SC09 is a Gram-negative bacterium isolated from a moribund Ictalurus punctatus collected in Jianyang, China. Here, we report the complete genome sequence of this microorganism to facilitate the investigation of its pathogenicity and to reevaluate its taxonomic position.

Comparative genomics of the marine bacterial genus Glaciecola reveals the high degree of genomic diversity and genomic characteristic for cold adaptation

To what extent the genomes of different species belonging to one genus can be diverse and the relationship between genomic differentiation and environmental factor remain unclear for oceanic bacteria. With many new bacterial genera and species being isolated from marine environments, this question warrants attention. In this study, we sequenced all the type strains of the published species of Glaciecola, a recently defined cold-adapted genus with species from diverse marine locations, to study the genomic diversity and cold-adaptation strategy in this genus.The genome size diverged widely from 3.08 to 5.96 Mb, which can be explained by massive gene gain and loss events. Horizontal gene transfer and new gene emergence contributed substantially to the genome size expansion. The genus Glaciecola had an open pan-genome. Comparative genomic research indicated that species of the genus Glaciecola had high diversity in genome size, gene content and genetic relatedness. This may be prevalent in marine bacterial genera considering the dynamic and complex environments of the ocean. Species of Glaciecola had some common genomic features related to cold adaptation, which enable them to thrive and play a role in biogeochemical cycle in the cold marine environments.

Draft Genome Sequence of the Fish Pathogen Yersinia ruckeri Strain 37551, Serotype O1b, Isolated from Diseased, Vaccinated Atlantic Salmon (Salmo salar) in Chile

We sequenced the genome of a motile O1b Yersinia ruckeri field isolate from Chile, which is causing enteric redmouth disease (ERM) in vaccinated Atlantic salmon (Salmo salar). The draft genome has 3,775,486 bp, a G+C content of 47.1%, and is predicted to contain 3,406 coding sequences.

Multiplex primer-extension assay for identification of Yersinia species

A multiplex primer-extension reaction (PER) assay, was specifically designed for the identification of ten Yersinia species. The assay, directed towards the tufA (elongation factor Tu) gene, was tested on a total of 42 samples representing Yersinia species and non-Yersinia species. The primers used in the preliminary PCR, designed in highly conserved regions upstream and downstream of the diagnosis sites, successfully amplified a 587 bp fragment. The diagnosis sites were simultaneously interrogated using a multiplex PER and the results were confirmed by fragment sequencing. The proposed test provides an appropriate tool to monitor the presence of Yersinia spp. in food samples and to evaluate the potential hazard for consumers.

Parallel independent evolution of pathogenicity within the genus Yersinia

The genus Yersinia has been used as a model system to study pathogen evolution. Using whole-genome sequencing of all Yersinia species, we delineate the gene complement of the whole genus and define patterns of virulence evolution. Multiple distinct ecological specializations appear to have split pathogenic strains from environmental, nonpathogenic lineages. This split demonstrates that contrary to hypotheses that all pathogenic Yersinia species share a recent common pathogenic ancestor, they have evolved independently but followed parallel evolutionary paths in acquiring the same virulence determinants as well as becoming progressively more limited metabolically. Shared virulence determinants are limited to the virulence plasmid pYV and the attachment invasion locus ail. These acquisitions, together with genomic variations in metabolic pathways, have resulted in the parallel emergence of related pathogens displaying an increasingly specialized lifestyle with a spectrum of virulence potential, an emerging theme in the evolution of other important human pathogens.

From food to cell: nutrient exploitation strategies of enteropathogens

Upon entering the human gastrointestinal tract, foodborne bacterial enteropathogens encounter, among numerous other stress conditions, nutrient competition with the host organism and the commensal microbiota. The main carbon, nitrogen and energy sources exploited by pathogens during proliferation in, and colonization of, the gut have, however, not been identified completely. In recent years, a huge body of literature has provided evidence that most enteropathogens are equipped with a large set of specific metabolic pathways to overcome nutritional limitations in vivo, thus increasing bacterial fitness during infection. These adaptations include the degradation of myo-inositol, ethanolamine cleaved from phospholipids, fucose derived from mucosal glycoconjugates, 1,2-propanediol as the fermentation product of fucose or rhamnose and several other metabolites not accessible for commensal bacteria or present in competition-free microenvironments. Interestingly, the data reviewed here point to common metabolic strategies of enteric pathogens allowing the exploitation of nutrient sources that not only are present in the gut lumen, the mucosa or epithelial cells, but also are abundant in food. An increased knowledge of the metabolic strategies developed by enteropathogens is therefore a key factor to better control foodborne diseases.