GC‐MS Based Metabolomics for Rapid Simultaneous Detection of Escherichia coli O157:H7, Salmonella Typhimurium, Salmonella Muenchen, and Salmonella Hartford in Ground Beef and Chicken

Cevallos-Cevallos, Juan Manuel; Danyluk, Michelle D.; Reyes‐De‐Corcuera, José I.

doi:10.1111/j.1750-3841.2011.02132.x

Cited by 71 publications

(39 citation statements)

References 41 publications

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“…In the category of animal products, bovine-based studies had the most articles published (16 articles) relative to all other groups. Some of the more interesting applications of metabolomics found in our survey include the use of metabolomics for quality control of animal products [46; 47], evaluating nutritional value and impact of various feed sources on animal health and products [25], investigating disease biology by using animal models of human disease [48; 49], investigation of potential metabolite biomarkers of animal disease [22; 23], assessment of production traits [50; 51], reproductive performance [29], and general metabolome characterization [52; 53]. …”

Section: Resultsmentioning

confidence: 99%

Livestock metabolomics and the livestock metabolome: A systematic review

Goldansaz¹,

Guo²,

Sajed³

et al. 2017

PLoS ONE

269

247

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Metabolomics uses advanced analytical chemistry techniques to comprehensively measure large numbers of small molecule metabolites in cells, tissues and biofluids. The ability to rapidly detect and quantify hundreds or even thousands of metabolites within a single sample is helping scientists paint a far more complete picture of system-wide metabolism and biology. Metabolomics is also allowing researchers to focus on measuring the end-products of complex, hard-to-decipher genetic, epigenetic and environmental interactions. As a result, metabolomics has become an increasingly popular “omics” approach to assist with the robust phenotypic characterization of humans, crop plants and model organisms. Indeed, metabolomics is now routinely used in biomedical, nutritional and crop research. It is also being increasingly used in livestock research and livestock monitoring. The purpose of this systematic review is to quantitatively and objectively summarize the current status of livestock metabolomics and to identify emerging trends, preferred technologies and important gaps in the field. In conducting this review we also critically assessed the applications of livestock metabolomics in key areas such as animal health assessment, disease diagnosis, bioproduct characterization and biomarker discovery for highly desirable economic traits (i.e., feed efficiency, growth potential and milk production). A secondary goal of this critical review was to compile data on the known composition of the livestock metabolome (for 5 of the most common livestock species namely cattle, sheep, goats, horses and pigs). These data have been made available through an open access, comprehensive livestock metabolome database (LMDB, available at http://www.lmdb.ca). The LMDB should enable livestock researchers and producers to conduct more targeted metabolomic studies and to identify where further metabolome coverage is needed.

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Section: Resultsmentioning

confidence: 99%

Livestock metabolomics and the livestock metabolome: A systematic review

Goldansaz¹,

Guo²,

Sajed³

et al. 2017

PLoS ONE

269

247

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“…38, 39 On average, 245 unique metabolite features (annotated with measured mass spectra and retention indices) were detected across 18 GC-MS analyses, and 124 of these were initially matched to entries in the Agilent Fiehn Metabolomics RTL Library. After manual validation of database matches (i.e., inspection of mass spectral and retention index matches), 66 metabolites were found to be confidently identified, representing the broadest coverage of the S. Typhimurium metabolome reported to date when compared to recent analyses of volatile 30, 32 or soluble 25, 29, 31 metabolites from this organism. A data matrix of identified metabolites and their abundances is provided as Supplemental Table S1.…”

Section: Resultsmentioning

confidence: 99%

Salmonella modulates metabolism during growth under conditions that induce expression of virulence genes

Kim

Schmidt²,

Kidwai

et al. 2013

Mol. BioSyst.

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Salmonella enterica serovar Typhimurium (S. Typhimurium) is a facultative pathogen that uses complex mechanisms to invade and proliferate within mammalian host cells. To investigate possible contributions of metabolic processes to virulence in S. Typhimurium grown under conditions known to induce expression of virulence genes, we used a metabolomics-driven systems biology approach coupled with genome scale modeling. First, we identified distinct metabolite profiles associated with bacteria grown in either rich or virulence-inducing media and report the most comprehensive coverage of the S. Typhimurium metabolome to date. Second, we applied an omics-informed genome scale modeling analysis of the functional consequences of adaptive alterations in S. Typhimurium metabolism during growth under our conditions. Modeling efforts highlighted a decreased cellular capability to both produce and utilize intracellular amino acids during stationary phase culture in virulence conditions, despite significant abundance increases for these molecules as observed by our metabolomics measurements. Furthermore, analyses of omics data in the context of the metabolic model indicated rewiring of the metabolic network to support pathways associated with virulence. For example, cellular concentrations of polyamines were perturbed, as well as the predicted capacity for secretion and uptake.

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“…Culture-independent 16S rRNA gene sequencing of stool samples from 4 to 16 days of life was utilized to identify microbial community signatures. Because intestinal bacteria can influence the metabolic profiles of their hosts [25-29], we pursued urinary metabolomics to identify surrogate biomarkers of NEC.…”

Section: Introductionmentioning

confidence: 99%

Early microbial and metabolomic signatures predict later onset of necrotizing enterocolitis in preterm infants

et al. 2013

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BackgroundNecrotizing enterocolitis (NEC) is a devastating intestinal disease that afflicts 10% of extremely preterm infants. The contribution of early intestinal colonization to NEC onset is not understood, and predictive biomarkers to guide prevention are lacking. We analyzed banked stool and urine samples collected prior to disease onset from infants <29 weeks gestational age, including 11 infants who developed NEC and 21 matched controls who survived free of NEC. Stool bacterial communities were profiled by 16S rRNA gene sequencing. Urinary metabolomic profiles were assessed by NMR.ResultsDuring postnatal days 4 to 9, samples from infants who later developed NEC tended towards lower alpha diversity (Chao1 index, P = 0.086) and lacked Propionibacterium (P = 0.009) compared to controls. Furthermore, NEC was preceded by distinct forms of dysbiosis. During days 4 to 9, samples from four NEC cases were dominated by members of the Firmicutes (median relative abundance >99% versus <17% in the remaining NEC and controls, P < 0.001). During postnatal days 10 to 16, samples from the remaining NEC cases were dominated by Proteobacteria, specifically Enterobacteriaceae (median relative abundance >99% versus 38% in the other NEC cases and 84% in controls, P = 0.01). NEC preceded by Firmicutes dysbiosis occurred earlier (onset, days 7 to 21) than NEC preceded by Proteobacteria dysbiosis (onset, days 19 to 39). All NEC cases lacked Propionibacterium and were preceded by either Firmicutes (≥98% relative abundance, days 4 to 9) or Proteobacteria (≥90% relative abundance, days 10 to 16) dysbiosis, while only 25% of controls had this phenotype (predictive value 88%, P = 0.001). Analysis of days 4 to 9 urine samples found no metabolites associated with all NEC cases, but alanine was positively associated with NEC cases that were preceded by Firmicutes dysbiosis (P < 0.001) and histidine was inversely associated with NEC cases preceded by Proteobacteria dysbiosis (P = 0.013). A high urinary alanine:histidine ratio was associated with microbial characteristics (P < 0.001) and provided good prediction of overall NEC (predictive value 78%, P = 0.007).ConclusionsEarly dysbiosis is strongly involved in the pathobiology of NEC. These striking findings require validation in larger studies but indicate that early microbial and metabolomic signatures may provide highly predictive biomarkers of NEC.

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GC‐MS Based Metabolomics for Rapid Simultaneous Detection of Escherichia coli O157:H7, Salmonella Typhimurium, Salmonella Muenchen, and Salmonella Hartford in Ground Beef and Chicken

Cited by 71 publications

References 41 publications

Livestock metabolomics and the livestock metabolome: A systematic review

Livestock metabolomics and the livestock metabolome: A systematic review

Salmonella modulates metabolism during growth under conditions that induce expression of virulence genes

Early microbial and metabolomic signatures predict later onset of necrotizing enterocolitis in preterm infants

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