Browse
Submit Data
Databases
API
Help

Dataset Information

17 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Proteome-Based Serotyping of the Food-Borne Pathogens Salmonella Enterica by Label-Free Mass Spectrometry

ABSTRACT: Food-borne diseases caused by Salmonella enterica of 2500 serovars represent a serious public health problem worldwide. A quick identification for the pathogen serovars is critical for controlling food pollution and disease spreading. Here, we applied a mass spectrum-based proteomic profiling for identifying five epidemiologically important Salmonella enterica subsp. enterica serovars (Enteritidis, Typhimurium, London, Rissen and Derby) in China. By label-free analysis, the 53 most variable serovar-related peptides, which were almost all enzymes related to nucleoside phosphate and energy metabolism, were screened as potential peptide biomarkers, and based on which a C5.0 predicted model for Salmonella enterica serotyping with four predictor peptides was generated with the accuracy of 94.12%. In comparison to the classic gene patterns by PFGE analysis, the high-throughput proteomic fingerprints were also effective to determine the genotypic similarity among Salmonella enteric isolates according to each strain of proteome profiling, which is indicative of the potential breakout of food contamination. Generally, the proteomic dissection on Salmonella enteric serovars provides a novel insight and real-time monitoring of food-borne pathogens.

SUBMITTER: Wang X

PROVIDER: S-EPMC9321705 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

First Fully Closed Genome Sequence of Salmonella enterica subsp. enterica Serovar Cubana Associated with a Food-Borne Outbreak.

Project description:Salmonella enterica subsp. enterica serovar Cubana (Salmonella serovar Cubana) is associated with human and animal disease. Here, we used third-generation, single-molecule, real-time DNA sequencing to determine the first complete genome sequence of Salmonella serovar Cubana CFSAN002050, which was isolated from fresh alfalfa sprouts during a multistate outbreak in 2012.

| S-EPMC4214993 | biostudies-literature

Multilocus sequence typing as a replacement for serotyping in Salmonella enterica.

Project description:Salmonella enterica subspecies enterica is traditionally subdivided into serovars by serological and nutritional characteristics. We used Multilocus Sequence Typing (MLST) to assign 4,257 isolates from 554 serovars to 1092 sequence types (STs). The majority of the isolates and many STs were grouped into 138 genetically closely related clusters called eBurstGroups (eBGs). Many eBGs correspond to a serovar, for example most Typhimurium are in eBG1 and most Enteritidis are in eBG4, but many eBGs contained more than one serovar. Furthermore, most serovars were polyphyletic and are distributed across multiple unrelated eBGs. Thus, serovar designations confounded genetically unrelated isolates and failed to recognize natural evolutionary groupings. An inability of serotyping to correctly group isolates was most apparent for Paratyphi B and its variant Java. Most Paratyphi B were included within a sub-cluster of STs belonging to eBG5, which also encompasses a separate sub-cluster of Java STs. However, diphasic Java variants were also found in two other eBGs and monophasic Java variants were in four other eBGs or STs, one of which is in subspecies salamae and a second of which includes isolates assigned to Enteritidis, Dublin and monophasic Paratyphi B. Similarly, Choleraesuis was found in eBG6 and is closely related to Paratyphi C, which is in eBG20. However, Choleraesuis var. Decatur consists of isolates from seven other, unrelated eBGs or STs. The serological assignment of these Decatur isolates to Choleraesuis likely reflects lateral gene transfer of flagellar genes between unrelated bacteria plus purifying selection. By confounding multiple evolutionary groups, serotyping can be misleading about the disease potential of S. enterica. Unlike serotyping, MLST recognizes evolutionary groupings and we recommend that Salmonella classification by serotyping should be replaced by MLST or its equivalents.

| S-EPMC3380943 | biostudies-literature

Analysis of cell surface proteome changes via label-free, quantitative mass spectrometry.

Project description:We present a mass spectrometry-based strategy for the specific detection and quantification of cell surface proteome changes. The method is based on the label-free quantification of peptide patterns acquired by high mass accuracy mass spectrometry using new software tools and the cell surface capturing technology that selectively enriches glycopeptides exposed to the cell exterior. The method was applied to monitor dynamic protein changes in the cell surface glycoproteome of Drosophila melanogaster cells. The results led to the construction of a cell surface glycoprotein atlas consisting of 202 cell surface glycoproteins of D. melanogaster Kc167 cells and indicated relative quantitative changes of cell surface glycoproteins in four different cellular states. Furthermore we specifically investigated cell surface proteome changes upon prolonged insulin stimulation. The data revealed insulin-dependent cell surface glycoprotein dynamics, including insulin receptor internalization, and linked these changes to intracellular signaling networks.

| S-EPMC2667347 | biostudies-literature

Microbial diagnostic microarray for food- and water-borne pathogens.

Project description:A microbial diagnostic microarray for the detection of the most relevant bacterial food- and water-borne pathogens and indicator organisms was developed and thoroughly validated. The microarray platform based on sequence-specific end labelling of oligonucleotides and the pyhylogenetically robust gyrB marker gene allowed a highly specific (resolution on genus/species level) and sensitive (0.1% relative and 10(4) cfu absolute detection sensitivity) detection of the target pathogens. Validation was performed using a set of reference strains and a set of spiked environmental samples. Reliability of the obtained data was additionally verified by independent analysis of the samples via fluorescence in situ hybridization (FISH) and conventional microbiological reference methods. The applicability of this diagnostic system for food analysis was demonstrated through extensive validation using artificially and naturally contaminated spiked food samples. The microarray-based pathogen detection was compared with the corresponding microbiological reference methods (performed according to the ISO norm). Microarray results revealed high consistency with the reference microbiological data.

| S-EPMC3815810 | biostudies-other

Complete Genome Sequences of Salmonella enterica Serovar Heidelberg Strains Associated with a Multistate Food-Borne Illness Investigation.

Project description:Next-generation sequencing is being evaluated for use with food-borne illness investigations, especially when the outbreak strains produce patterns that cannot be discriminated from non-outbreak strains using conventional procedures. Here we report complete genome assemblies of two Salmonella enterica serovar Heidelberg strains with a common pulsed-field gel electrophoresis pattern isolated during an outbreak investigation.

| S-EPMC4047461 | biostudies-literature

freeQuant: A Mass Spectrometry Label-Free Quantification Software Tool for Complex Proteome Analysis.

Project description:Study of complex proteome brings forward higher request for the quantification method using mass spectrometry technology. In this paper, we present a mass spectrometry label-free quantification tool for complex proteomes, called freeQuant, which integrated quantification with functional analysis effectively. freeQuant consists of two well-integrated modules: label-free quantification and functional analysis with biomedical knowledge. freeQuant supports label-free quantitative analysis which makes full use of tandem mass spectrometry (MS/MS) spectral count, protein sequence length, shared peptides, and ion intensity. It adopts spectral count for quantitative analysis and builds a new method for shared peptides to accurately evaluate abundance of isoforms. For proteins with low abundance, MS/MS total ion count coupled with spectral count is included to ensure accurate protein quantification. Furthermore, freeQuant supports the large-scale functional annotations for complex proteomes. Mitochondrial proteomes from the mouse heart, the mouse liver, and the human heart were used to evaluate the usability and performance of freeQuant. The evaluation showed that the quantitative algorithms implemented in freeQuant can improve accuracy of quantification with better dynamic range.

| S-EPMC4667154 | biostudies-literature

Experimental promoter identification of a representative food-borne pathogen Salmonella enterica serovar Typhimurium LT2 with near single base-pair resolution

Project description:RpoD is a houskeeping sigma factor and RpoN is an alternative one. It was identified their intragenic and intergenic binding sites and association with the RNA polymerase.

2023-12-15 | GSE119965 | GEO

Experimental promoter identification of a representative food-borne pathogen Salmonella enterica serovar Typhimurium LT2 with near single base-pair resolution

Project description:This SuperSeries is composed of the SubSeries listed below.

2023-12-14 | GSE119967 | GEO

Detection and Identification of Salmonella enterica, Escherichia coli, and Shigella spp. via PCR-electrospray ionization mass spectrometry: isolate testing and analysis of food samples.

Project description:An assay to identify the common food-borne pathogens Salmonella, Escherichia coli, Shigella, and Listeria monocytogenes was developed in collaboration with Ibis Biosciences (a division of Abbott Molecular) for the Plex-ID biosensor system, a platform that uses electrospray ionization mass spectroscopy (ESI-MS) to detect the base composition of short PCR amplicons. The new food-borne pathogen (FBP) plate has been experimentally designed using four gene segments for a total of eight amplicon targets. Initial work built a DNA base count database that contains more than 140 Salmonella enterica, 139 E. coli, 11 Shigella, and 36 Listeria patterns and 18 other Enterobacteriaceae organisms. This assay was tested to determine the scope of the assay's ability to detect and differentiate the enteric pathogens and to improve the reference database associated with the assay. More than 800 bacterial isolates of S. enterica, E. coli, and Shigella species were analyzed. Overall, 100% of S. enterica, 99% of E. coli, and 73% of Shigella spp. were detected using this assay. The assay was also able to identify 30% of the S. enterica serovars to the serovar level. To further characterize the assay, spiked food matrices and food samples collected during regulatory field work were also studied. While analysis of preenrichment media was inconsistent, identification of S. enterica from selective enrichment media resulted in serovar-level identifications for 8 of 10 regulatory samples. The results of this study suggest that this high-throughput method may be useful in clinical and regulatory laboratories testing for these pathogens.

| S-EPMC3497367 | biostudies-literature

Cell Surface Proteome of Dental Pulp Stem Cells Identified by Label-Free Mass Spectrometry.

Project description:Multipotent mesenchymal stromal cells (MSCs) are promising tools for regenerative medicine. They can be isolated from different sources based on their plastic-adherence property. The identification of reliable cell surface markers thus becomes the Holy Grail for their prospective isolation. Here, we determine the cell surface proteomes of human dental pulp-derived MSCs isolated from single donors after culture expansion in low (2%) or high (10%) serum-containing media. Cell surface proteins were tagged on intact cells using cell impermeable, cleavable sulfo-NHS-SS-biotin, which allows their enrichment by streptavidin pull-down. For the proteomic analyses, we first compared label-free methods to analyze cell surface proteomes i.e. composition, enrichment and proteomic differences, and we developed a new mathematical model to determine cell surface protein enrichment using a combinatorial gene ontology query. Using this workflow, we identified 101 cluster of differentiation (CD) markers and 286 non-CD cell surface proteins. Based on this proteome profiling, we identified 14 cell surface proteins, which varied consistently in abundance when cells were cultured under low or high serum conditions. Collectively, our analytical methods provide a basis for identifying the cell surface proteome of dental pulp stem cells isolated from single donors and its evolution during culture or differentiation. Our data provide a comprehensive cell surface proteome for the precise identification of dental pulp-derived MSC populations and their isolation for potential therapeutic intervention.

| S-EPMC4973913 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data