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A CURE for Meat: Comparing Bacterial Contaminants on Different Ground Beef Sources Emphasizes Process of Science and Quantitative Reasoning.

ABSTRACT: To broaden and emphasize the educational benefits of research to more biology majors in a course setting, we developed and assessed a microbiology-focused course-based undergraduate research experience that utilizes culture-based bacterial enumeration to compare contamination present on different ground beef sources (conventional vs. organic). During the final 3 weeks of the quarter, students learned and practiced common microbiology techniques like dilution math, selective and differential media-based identification, and statistical analysis to evaluate data and test hypotheses. Students were assessed primarily via a formal lab report and a lab practical focused on evaluating process of science and quantitative reasoning skills. The majority of students could write hypotheses and describe variables but were challenged when asked to describe the limitations of the experiments that were conducted as part of this research project. Most students could perform Excel-based graphing and a t test, but many could not solve the complex dilution math required for this project. The greatest barriers to skills mastery represented microbiology-focused concepts, like understanding selective media biases and the nuances of multistep viable counting procedures and outcomes.

SUBMITTER: Boomer SM

PROVIDER: S-EPMC8060146 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundEnterohemorrhagic Escherichia coli (EHEC) are zoonotic agents associated with outbreaks worldwide. Growth of EHEC strains in ground beef could be inhibited by background microbiota that is present initially at levels greater than that of the pathogen E. coli. However, how the microbiota outcompetes the pathogenic bacteria is unknown. Our objective was to identify metabolic pathways of EHEC that were altered by natural microbiota in order to improve our understanding of the mechanisms controlling the growth and survival of EHECs in ground beef.ResultsBased on 16S metagenomics analysis, we identified the microbial community structure in our beef samples which was an essential preliminary for subtractively analyzing the gene expression of the EHEC strains. Then, we applied strand-specific RNA-seq to investigate the effects of this microbiota on the global gene expression of EHEC O2621765 and O157EDL933 strains by comparison with their behavior in beef meat without microbiota. In strain O2621765, the expression of genes connected with nitrate metabolism and nitrite detoxification, DNA repair, iron and nickel acquisition and carbohydrate metabolism, and numerous genes involved in amino acid metabolism were down-regulated. Further, the observed repression of ftsL and murF, involved respectively in building the cytokinetic ring apparatus and in synthesizing the cytoplasmic precursor of cell wall peptidoglycan, might help to explain the microbiota's inhibitory effect on EHECs. For strain O157EDL933, the induced expression of the genes implicated in detoxification and the general stress response and the repressed expression of the peR gene, a gene negatively associated with the virulence phenotype, might be linked to the survival and virulence of O157:H7 in ground beef with microbiota.ConclusionIn the present study, we show how RNA-Seq coupled with a 16S metagenomics analysis can be used to identify the effects of a complex microbial community on relevant functions of an individual microbe within it. These findings add to our understanding of the behavior of EHECs in ground beef. By measuring transcriptional responses of EHEC, we could identify putative targets which may be useful to develop new strategies to limit their shedding in ground meat thus reducing the risk of human illnesses.

Project description:Improved greenhouse gas (GHG) emission efficiency of production has been proposed as one of the biggest potential advantages of cultured meat over conventional livestock production systems. Comparisons with beef are typically highlighted, as it is a highly emissions intensive food product. In this study we present a more rigorous comparison of the potential climate impacts of cultured meat and cattle production than has previously been made. Warming impacts are evaluated using a simple climate model that simulates the different behaviours of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O), rather than relying on carbon dioxide equivalent (CO2e) metrics. We compare the temperature impact of beef cattle and cultured meat production at all times to 1000 years in the future, using four synthetic meat GHG footprints currently available in the literature and three different beef production systems studied in an earlier climate modelling paper. Cattle systems are associated with the production of all three GHGs above, including significant emissions of CH4, while cultured meat emissions are almost entirely CO2 from energy generation. Under continuous high global consumption, cultured meat results in less warming than cattle initially, but this gap narrows in the long term and in some cases cattle production causes far less warming, as CH4 emissions do not accumulate, unlike CO2. We then model a decline in meat consumption to more sustainable levels following high consumption, and show that although cattle systems generally result in greater peak warming than cultured meat, the warming effect declines and stabilises under the new emission rates of cattle systems, while the CO2 based warming from cultured meat persists and accumulates even under reduced consumption, again overtaking cattle production in some scenarios. We conclude that cultured meat is not prima facie climatically superior to cattle production; its relative impact instead depends on the availability of decarbonised energy generation and the specific production systems that are realised.

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A CURE for Meat: Comparing Bacterial Contaminants on Different Ground Beef Sources Emphasizes Process of Science and Quantitative Reasoning.

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