25 research outputs found

    Population dynamics of a salmonella lytic phage and its host : implications of the host bacterial growth rate in modelling

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    The prevalence and impact of bacteriophages in the ecology of bacterial communities coupled with their ability to control pathogens turn essential to understand and predict the dynamics between phage and bacteria populations. To achieve this knowledge it is essential to develop mathematical models able to explain and simulate the population dynamics of phage and bacteria. We have developed an unstructured mathematical model using delay-differential equations to predict the interactions between a broad-host-range Salmonella phage and its pathogenic host. The model takes into consideration the main biological parameters that rule phage-bacteria interactions likewise the adsorption rate, latent period, burst size, bacterial growth rate, and substrate uptake rate, among others. The experimental validation of the model was performed with data from phage-interaction studies in a 5 L bioreactor. The key and innovative aspect of the model was the introduction of variations in the latent period and adsorption rate values that are considered as constants in previous developed models. By modelling the latent period as a normal distribution of values and the adsorption rate as a function of the bacterial growth rate it was possible to accurately predict the behaviour of the phage-bacteria population. The model was shown to predict simulated data with a good agreement with the experimental observations and explains how a lytic phage and its host bacteria are able to coexist.Financial support was received through the Strategic Project PEst-OE/EQB/LA0023/2013 from the FCT-Fundacao para a Ciencia e Tecnologia (http://www.fct.pt) and the projects "BioHealth - Biotechnology and Bioengineering approaches to improve health quality'', Ref. NORTE-07-0124 FEDER-000027, co-funded by the Programa Operacional Regional do Norte (ON.2 - O Novo Norte), QREN, FEDER and "Consolidating Research Expertise and Resources on Cellular and Molecular Biotechnology at CEB/IBB'', Ref. FCOMP-01-0124-FEDER-027462. Silvio B. Santos was supported by the grant SFRH/BPD/75311/2010 and Carla Carvalho was supported by the grant SFRH/BPD/79365/2011 both from the FCT-Fundacao para a Ciencia e Tecnologia (http://www.fct.pt). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

    Comparing recovering efficiency of immunomagnetic separation and centrifugation of mycobacteria in metalworking fluids

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    The accurate detection and enumeration of Mycobacterium immunogenum in metalworking fluids (MWFs) is imperative from an occupational health and industrial fluids management perspective. We report here a comparison of immunomagnetic separation (IMS) coupled to flow-cytometric enumeration, with traditional centrifugation techniques for mycobacteria in a semisynthetic MWF. This immunolabeling involves the coating of laboratory-synthesized nanometer-scale magnetic particles with protein A, to conjugate a primary antibody (Ab), specific to Mycobacterium spp. By using magnetic separation and flow-cytometric quantification, this approach enabled much higher recovery efficiency and fluorescent light intensities in comparison to the widely applied centrifugation technique. This IMS technique increased the cell recovery efficiency by one order of magnitude, and improved the fluorescence intensity of the secondary Ab conjugate by 2-fold, as compared with traditional techniques. By employing nanometer-scale magnetic particles, IMS was found to be compatible with flow cytometry (FCM), thereby increasing cell detection and enumeration speed by up to two orders of magnitude over microscopic techniques. Moreover, the use of primary Ab conjugated magnetic nanoparticles showed better correlation between epifluorescent microscopy counts and FCM analysis than that achieved using traditional centrifugation techniques. The results strongly support the applicability of the flow-cytometric IMS for microbial detection in complex matrices.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47949/1/10295_2005_Article_238.pd
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