Systematic Evaluation of Whole Genome Sequence-Based Predictions of Salmonella Serotype and Antimicrobial Resistance.

Whole-genome sequencing (WGS) is used increasingly in public-health laboratories for typing and characterizing foodborne pathogens. To evaluate the performance of existing bioinformatic tools for in silico prediction of antimicrobial resistance (AMR) and serotypes of Salmonella enterica, WGS-based genotype predictions were compared with the results of traditional phenotyping assays. A total of 111 S. enterica isolates recovered from a Canadian baseline study on broiler chicken conducted in 2012-2013 were selected based on phenotypic resistance to 15 different antibiotics and isolates were subjected to WGS. Both SeqSero2 and SISTR accurately determined S. enterica serotypes, with full matches to laboratory results for 87.4 and 89.2% of isolates, respectively, and partial matches for the remaining isolates. Antimicrobial resistance genes (ARGs) were identified using several bioinformatics tools including the Comprehensive Antibiotic Resistance Database - Resistance Gene Identifier (CARD-RGI), Center for Genomic Epidemiology (CGE) ResFinder web tool, Short Read Sequence Typing for Bacterial Pathogens (SRST2 v 0.2.0), and k-mer alignment method (KMA v 1.17). All ARG identification tools had ≥ 99% accuracy for predicting resistance to all antibiotics tested except streptomycin (accuracy 94.6%). Evaluation of ARG detection in assembled versus raw-read WGS data found minimal observable differences that were gene- and coverage- dependent. Where initial phenotypic results indicated isolates were sensitive, yet ARGs were detected, repeat AMR testing corrected discrepancies. All tools failed to find resistance-determining genes for one gentamicin- and two streptomycin-resistant isolates. Further investigation found a single nucleotide polymorphism (SNP) in the nuoF coding region of one of the isolates which may be responsible for the observed streptomycin-resistant phenotype. Overall, WGS-based predictions of AMR and serotype were highly concordant with phenotype determination regardless of computational approach used.

ConFindr: rapid detection of intraspecies and cross-species contamination in bacterial whole-genome sequence data.

Whole-genome sequencing (WGS) of bacterial pathogens is currently widely used to support public-health investigations. The ability to assess WGS data quality is critical to underpin the reliability of downstream analyses. Sequence contamination is a quality issue that could potentially impact WGS-based findings; however, existing tools do not readily identify contamination from closely-related organisms. To address this gap, we have developed a computational pipeline, ConFindr, for detection of intraspecies contamination. ConFindr determines the presence of contaminating sequences based on the identification of multiple alleles of core, single-copy, ribosomal-protein genes in raw sequencing reads. The performance of this tool was assessed using simulated and lab-generated Illumina short-read WGS data with varying levels of contamination (0-20% of reads) and varying genetic distance between the designated target and contaminant strains. Intraspecies and cross-species contamination was reliably detected in datasets containing 5% or more reads from a second, unrelated strain. ConFindr detected intraspecies contamination with higher sensitivity than existing tools, while also being able to automatically detect cross-species contamination with similar sensitivity. The implementation of ConFindr in quality-control pipelines will help to improve the reliability of WGS databases as well as the accuracy of downstream analyses. ConFindr is written in Python, and is freely available under the MIT License at github.com/OLC-Bioinformatics/ConFindr.

Draft Genome Sequences of Salmonella enterica subsp. enterica Serovar Berta ATCC 8392 and a Nalidixic Acid-Resistant Isolate of This Strain.

ITALIC! Salmonella entericasubspecies ITALIC! entericaserovar Berta has been isolated in multiple animal species and has been implicated in human disease. Here, we report a 4.7-Mbp draft genome sequence of ITALIC! S. entericaserovar Berta (ATCC strain 8392) and a nalidixic acid-resistant isolate derived from this strain.

Comparative Evaluation of Genomic and Laboratory Approaches for Determination of Shiga Toxin Subtypes in Escherichia coli.

The determination of Shiga toxin (ST) subtypes can be an important element in the risk characterization of foodborne ST-producing Escherichia coli (STEC) isolates for making risk management decisions. ST subtyping methods include PCR techniques based on electrophoretic or pyrosequencing analysis of amplicons and in silico techniques based on whole genome sequence analysis using algorithms that can be readily incorporated into bioinformatics analysis pipelines for characterization of isolates by their genetic composition. The choice of technique will depend on the performance characteristics of the method and an individual laboratory's access to specialized equipment or personnel. We developed two whole genome sequence-based ST subtyping tools: (i) an in silico PCR algorithm requiring genome assembly to replicate a reference PCR-based method developed by the Statens Serum Institut (SSI) and (ii) an assembly-independent routine in which raw sequencing results are mapped to a database of known ST subtype sequence variants (V-Typer). These tools were evaluated alongside the SSI reference PCR method and a recently described PCR-based pyrosequencing technique. The V-Typer method results corresponded closely with the reference method in the analysis of 67 STEC cultures obtained from a World Health Organization National Reference Laboratory. In contrast, the in silico PCR method failed to detect ST subtypes in several cases, a result which we attribute to assembly-induced errors typically encountered with repetitive gene sequences. The V-Typer can be readily integrated into bioinformatics protocols used in the identification and characterization of foodborne STEC isolates.

Draft Genome Sequence of Salmonella enterica subsp. enterica Serovar Mishmarhaemek Isolated from Bovine Feces.

Salmonella enterica subsp. enterica serovar Mishmarhaemek is a Gram-negative, non-spore-forming, rod-shaped bacterium implicated in human clinical disease. Here, we report a 4.8-Mbp draft genome sequence of a nalidixic acid-resistant isolate of S. serovar Mishmarhaemek.

Draft Genome Sequence of Escherichia coli O157:H7 ATCC 35150 and a Nalidixic Acid-Resistant Mutant Derivative.

Shiga toxin-producing Escherichia coli strains, occasionally isolated from food, are of public health importance. Here, we report on the 5.30-Mbp draft genome sequence of E. coli O157:H7 EDL931 (strain ATCC 35150) and the 5.32-Mbp draft genome sequence of a nalidixic acid-resistant mutant derivative used as a distinguishable control strain in food-testing laboratories.

GeneSippr: a rapid whole-genome approach for the identification and characterization of foodborne pathogens such as priority Shiga toxigenic Escherichia coli.

The timely identification and characterization of foodborne bacteria for risk assessment purposes is a key operation in outbreak investigations. Current methods require several days and/or provide low-resolution characterization. Here we describe a whole-genome-sequencing (WGS) approach (GeneSippr) enabling same-day identification of colony isolates recovered from investigative food samples. The identification of colonies of priority Shiga-toxigenic Escherichia coli (STEC) (i.e., serogroups O26, O45, O103, O111, O121, O145 and O157) served as a proof of concept. Genomic DNA was isolated from single colonies and sequencing was conducted on the Illumina MiSeq instrument with raw data sampling from the instrument following 4.5 hrs of sequencing. Modeling experiments indicated that datasets comprised of 21-nt reads representing approximately 4-fold coverage of the genome were sufficient to avoid significant gaps in sequence data. A novel bioinformatic pipeline was used to identify the presence of specific marker genes based on mapping of the short reads to reference sequence libraries, along with the detection of dispersed conserved genomic markers as a quality control metric to assure the validity of the analysis. STEC virulence markers were correctly identified in all isolates tested, and single colonies were identified within 9 hrs. This method has the potential to produce high-resolution characterization of STEC isolates, and whole-genome sequence data generated following the GeneSippr analysis could be used for isolate identification in place of lengthy biochemical characterization and typing methodologies. Significant advantages of this procedure include ease of adaptation to the detection of any gene marker of interest, as well as to the identification of other foodborne pathogens for which genomic markers have been defined.

Seed storage proteins of the globulin family are cleaved post-translationally in wheat embryos.

BACKGROUND: The 7S globulins are plant seed storage proteins that have been associated with the development of a number of human diseases, including peanut allergy. Immune reactivity to the wheat seed storage protein globulin-3 (Glo-3) has been associated with the development of the autoimmune disease type 1 diabetes in diabetes-prone rats and mice, as well as in a subset of human patients. FINDINGS: The present study characterized native wheat Glo-3 in salt-soluble wheat seed protein extracts. Glo-3-like peptides were observed primarily in the wheat embryo. Glo-3-like proteins varied significantly in their molecular masses and isoelectric points, as determined by two dimensional electrophoresis and immunoblotting with anti-Glo-3A antibodies. Five major polypeptide spots were identified by mass spectrometry and N-terminal sequencing as belonging to the Glo-3 family. CONCLUSIONS: These results in combination with our previous findings have allowed for the development of a hypothetical model of the post-translational events contributing to the wheat 7S globulin profile in mature wheat kernels.

The starch granule associated proteomes of commercially purified starch reference materials from rice and maize.

Commercially available reference materials are integral components of many experimental protocols, as it is critical to compare one's results to those derived from well-characterized standards. Most reference materials are well defined, with all their components being cataloged. However, certain reference materials, such as commercially prepared starch samples, can have undefined components, potentially limiting their usefulness as standards. The proteome of commercially prepared starch has not been documented, and to that end, we initiated a mass spectrometry-based survey of the proteins associated with starch granules in commercially prepared rice and maize starch samples. We performed direct trypsin treatments of starch samples and sequenced both the water-soluble peptides liberated into the aqueous supernatant and the peptides released from the starch granule surface by isopropanol solvent washing. We discovered that the majority of proteins, in both rice and maize samples, were involved in either carbohydrate metabolism or storage. We also documented proteins that are markers for seed maturity and for starch mobilization.

Euglena light-harvesting complexes are encoded by multifarious polyprotein mRNAs that evolve in concert.

Light-harvesting complexes (LHCs) are a superfamily of chlorophyll- and carotenoid-binding proteins that are responsible for the capture of light energy and its transfer to the photosynthetic reaction centers. Unlike those of most eukaryotes, the LHCs of Euglena gracilis are translated from large mRNAs, producing polyprotein precursors consisting of multiple concatenated LHC subunits that are separated by conserved decapeptide linkers. These precursors are posttranslationally targeted to the chloroplast and cleaved into individual proteins. We analyzed expressed sequence tags from Euglena to further characterize the structural features of the LHC polyprotein-coding genes and to examine the evolution of this multigene family. Of the 19 different LHC transcriptional units we detected, 17 encoded polyproteins composed of both tandem and nontandem repeats of LHC subunits; organizations that likely occurred through unequal crossing-over. Of the 2 nonpolyprotein-encoding LHC transcripts detected, 1 evolved from the truncation of a polyprotein-coding gene. Duplication of LHC polyprotein-coding genes was particularly important in the LHCI gene family where multiple paralogous sequences were detected. Intriguingly, several of the individual LHC-coding subunits both within and between transcriptional units appeared to be evolving in concert, suggesting that gene conversion has been a significant mechanism for LHC evolution in Euglena.

Tracing the evolution of the light-harvesting antennae in chlorophyll a/b-containing organisms.

The light-harvesting complexes (LHCs) of land plants and green algae have essential roles in light capture and photoprotection. Though the functional diversity of the individual LHC proteins are well described in many land plants, the extent of this family in the majority of green algal groups is unknown. To examine the evolution of the chlorophyll a/b antennae system and to infer its ancestral state, we initiated several expressed sequence tag projects from a taxonomically broad range of chlorophyll a/b-containing protists. This included representatives from the Ulvophyceae (Acetabularia acetabulum), the Mesostigmatophyceae (Mesostigma viride), and the Prasinophyceae (Micromonas sp.), as well as one representative from each of the Euglenozoa (Euglena gracilis) and Chlorarachniophyta (Bigelowiella natans), whose plastids evolved secondarily from a green alga. It is clear that the core antenna system was well developed prior to green algal diversification and likely consisted of the CP29 (Lhcb4) and CP26 (Lhcb5) proteins associated with photosystem II plus a photosystem I antenna composed of proteins encoded by at least Lhca3 and two green algal-specific proteins encoded by the Lhca2 and 9 genes. In organisms containing secondary plastids, we found no evidence for orthologs to the plant/algal antennae with the exception of CP29. We also identified PsbS homologs in the Ulvophyceae and the Prasinophyceae, indicating that this distinctive protein appeared prior to green algal diversification. This analysis provides a snapshot of the antenna systems in diverse green algae, and allows us to infer the changing complexity of the antenna system during green algal evolution.