Antagonistic effect ofLactobacillusstrains againstEscherichia coliandListeria monocytogenesin milk

Aguilar, Catalina; Vanegas, Consuelo; Klotz, Bernadette

doi:10.1017/s0022029910000877

Cited by 37 publications

(26 citation statements)

References 32 publications

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“…In contrast, in the present study Salmonella was isolated from only 0.9% (1 of 109) of samples and L. monocytogenes was not found. However, Salmonella and L. monocytogenes counts can be difficult to determine because other microorganism in the milk may inhibit pathogen growth (1,25).…”

Section: Discussionmentioning

confidence: 99%

Microbiological Quality of Milk in Tanzania: From Maasai Stable to African Consumer Table

Schoder

Maichin

Lema³

et al. 2013

Journal of Food Protection

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In Tanzania, pastoralists such as the Maasai and small urban farmers are responsible for the country's milk production, and 95% of the national milk supply is sold without regulation. This study was conducted using hygiene checklists and milk sampling to investigate milk quality and safety at various steps throughout the milk production chain. In regions of Dar es Salaam and Lake Victoria, 196 milk samples were collected: 109 samples of raw milk, 41 samples of packed or open served heat-treated products, and 46 samples of fermented products. Samples were taken from (i) the production level (pastoralists and urban farmers), (ii) the collection level (middlemen and depots), (iii) processors (dairies), and (iv) retailers (kiosks). Samples were analyzed for hygiene criteria (total bacteria, total coliforms, Escherichia coli, and coagulase-positive staphylococci) and foodborne pathogens such as Salmonella, enterohemorrhagic E. coli O157:H7, and Listeria monocytogenes. Adequate heating of milk for drinking was determined via heat labile alkaline phosphatase and lactoperoxidase analysis. Total bacterial counts indicated that only 67% (73 of 109) of raw milk samples and 46% (19 of 41) of heat-treated samples met national Tanzanian standards. Bulk milk samples taken from the traditional milking vessels of Maasai pastoralists had the lowest total bacterial counts: ≥ 1 × 10(2) CFU/ml. Foodborne pathogens such as E. coli O157:H7 and Salmonella were isolated from 10.1% (11 of 109) of raw milk samples but were not detected in heat-treated or fermented products, and 83% of heat-treated milk samples were lactoperoxidase negative, indicating overpasteurization. Coliforms were detected in 41% (17 of 41) of processed milk samples, thus indicating a high rate of recontamination. A progressive decrease in microbial quality along the milk production chain was attributed to departures from traditional methods, inadequate milk containers, long transport distances, lack of cooling, and lack of a basic understanding of hygiene.

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Section: Discussionmentioning

confidence: 99%

Microbiological Quality of Milk in Tanzania: From Maasai Stable to African Consumer Table

Schoder

Maichin

Lema³

et al. 2013

Journal of Food Protection

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“…Certain milk bacterial strains have the capacity of inhibiting the growth of mastitis-causing bacteria in vitro, possibly through the production of bacteriocins, but this effect requires high concentrations of the interfering bacteria [80]. Yet the normal mammary microbiota is reported to comprise less than 3–4.7 log 10 CFU/mL [6, 20].…”

Section: An Implication Of Mammary Microbiota: Use Of Probiotics For mentioning

confidence: 99%

Mammary microbiota of dairy ruminants: fact or fiction?

Rainard

2017

Vet Res

103

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Explorations of how the complex microbial communities that inhabit different body sites might contribute to health and disease have prompted research on the ways the harmonious relationship between a host and its microbiota could be used to keep animals healthy in their production conditions. In particular, there is a growing interest in the bacterial signatures that can be found in the milk of healthy or mastitic dairy cows. The concept of sterility of the healthy mammary gland of dairy ruminants has been challenged by the results of studies using bacterial DNA-based methodology. The newly obtained data have led to the concept of the intramammary microbiota composed of a complex community of diverse bacteria. Accordingly, mammary gland infections are not mere infections by a bacterial pathogen, but the consequence of mammary dysbiosis. This article develops the logical implications of this paradigm shift and shows how this concept is incompatible with current knowledge concerning the innate and adaptive immune system of the mammary gland of dairy ruminants. It also highlights how the concept of mammary microbiota clashes with results of experimental infections induced under controlled conditions or large field experiments that demonstrated the efficacy of the current mastitis control measures.

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“…In order to estimate the effect of interaction between two strains of Lactobacillus plantarum and two food-borne pathogens, Listeria monocytogenes and Escherichia coli, Aguilar et al (2011) used whole UHT milk as experimental media at 37°C. To determine the type of interaction between the two bacterial populations in co-cultures and to evaluate the antagonistic activity of the lactic acid bacteria on the pathogenic bacteria, the growth curves, the kinetic parameters, and the pH profiles of mono and co-cultures were compared.…”

Section: Othersmentioning

confidence: 99%

Modelling the effects of natural antimicrobials as food preservatives

Jaiswal¹,

Jaiswal²

2015

Handbook of Natural Antimicrobials for Food Safety and Quality

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A predictive food microbiological model is a mathematical representation of mechanisms that describes the growth, survival, inactivation or biochemical process of an organism and are used in the food industry to predict food pathogen growth and to help in the evaluation of food safety. Furthermore, it reduces the number of expensive and time-consuming experiments; however, adequate statistical analysis is a crucial step during all phases of model development and validation. Therefore, present chapter is focused on the basic concept of mathematical modelling which can be applied to estimate the effects of natural antimicrobials as food preservatives. Initial section discusses about the importance of modelling in food preservation, brief introduction to types of modelling, model development and validation and the final section includes review of recent research in natural antimicrobials modelling.

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Antagonistic effect ofLactobacillusstrains againstEscherichia coliandListeria monocytogenesin milk

Cited by 37 publications

References 32 publications

Microbiological Quality of Milk in Tanzania: From Maasai Stable to African Consumer Table

Microbiological Quality of Milk in Tanzania: From Maasai Stable to African Consumer Table

Mammary microbiota of dairy ruminants: fact or fiction?

Modelling the effects of natural antimicrobials as food preservatives

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