Planning a serial dilution test with multiple dilutions

The dilutions used in a serial dilution test determine which concentrations it can estimate well. Two criteria help to select how many and which dilutions to use. The first criterion is a low probability of outcomes with either all growth or all non-growth tubes at the concentrations of interest. The second criterion considers how far the estimated concentration (MPN) is likely to be from the actual concentration.     

Estimating the precision of serial dilutions and viable bacterial counts

The propagation of error in serial dilutions was investigated theoretically and by means of computer simulations. The principal aim of the study was, given only the pipette manufacturer's specification, to estimate the variance of any step in a dilution series both of pure solutions and of homogeneous bacterial suspensions by means of simple formulae. The study was extended to include bacterial plate counts by both the standard and the Miles and Misra methods. It was found that such estimation was possible and that the distributions approximated the normal sufficiently for the construction of confidence intervals (Cls) by the usual method. Such intervals can be regarded as minima which could be inflated by other, possibly undetermined, factors. It is suggested that laboratories could construct tables such as that reported here for pipettes and methods in common use to facilitate estimation. While replication of the final sampling step of a plate count increases the precision of estimation, averaging across dilutions may decrease precision and is not recommended for the standard pour-plate count.     

Generation and characterization of four dilutions of diesel engine exhaust for a subchronic inhalation study

Exposure atmospheres for a rodent inhalation toxicology study were generated from the exhaust of a 2000 Cummins ISB 5.9L diesel engine coupled to a dynamometer and operated on a slightly modified heavy-duty Federal Test Procedure cycle. Exposures were conducted to one clean air control and four diesel exhaust levels maintained at four different dilution rates (300:1, 100:1, 30:1, 10:1) that yielded particulate mass concentrations of 30, 100, 300, and 1000 microg/m3. Exposures at the four dilutions were characterized for particle mass, particle size distribution (reported elsewhere), detailed chemical speciation of gaseous, semivolatile, and particle-phase inorganic and organic compounds. Target analytes included metals, inorganic ions and gases, organic and elemental carbon, alkanes, alkenes, aromatic and aliphatic acids, aromatic hydrocarbons, polycyclic aromatic hydrocarbons (PAH), oxygenated PAH, nitrogenated PAH, isoprenoids, carbonyls, methoxyphenols, sugar derivatives, and sterols. The majority of the mass of material in the exposure atmospheres was gaseous nitrogen oxides and carbon monoxide, with lesser amounts of volatile organics and particle mass (PM) composed of carbon (approximately 90% of PM) and ions (approximately 10% of PM). Measured particle organic species accounted for about 10% of total organic particle mass and were mostly alkanes and aliphatic acids. Several of the components in the exposure atmosphere scaled in concentration with dilution but did not scale precisely with the dilution rate because of background from the rodents and scrubbed dilution air, interaction of animal derived emissions with diesel exhaust components, and day-to-day variability in the output of the engine. Rodent-derived ammonia reacted with exhaust to form secondary inorganic particles (at different rates dependent on dilution), and rodent respiration accounted for volatile organics (especially carbonyls and acids) in the same range as the diesel exhaust at the lowest exhaust exposure concentrations. Day-to-day variability in the engine output was implicated partially for differences of several components, including some of the particle bound organics. Though these observations have likely occurred in nearly all inhalation exposure atmospheres that contain complex mixtures of material, the speciations conducted here illustrate many of them for the first time.     

Disaggregation kinetics of a peat humic acid: mechanism and pH effects

Fluorescence correlation spectroscopy was used to study the disaggregation kinetics of a peat humic acid (PPHA) at several pH. FCS measures diffusion coefficients of fluorescent molecules and aggregates, thus allowing for the determination of disaggregation rates with a temporal resolution of seconds to minutes. Disaggregation was initiated by dilution of a peat concentrate consisting of a mixture containing 80% large aggregates (average hydrodynamic radius, rH, of about 300 nm) and free monomers (average rH of about 1 nm). Upon dilution at different pH values, aggregate size decreased, and the proportion of free monomers in solution increased until complete disaggregation occurred. The mechanism appeared to involve the release of monomers from the surface of the aggregates. The pH markedly affected the disaggregation rate. Complete disaggregation took 1 month at pH 3.6, took less than 1 h at pH 5.6, and was extremely rapid in alkaline solutions. The results suggested that at least two processes were operating in parallel with the overall rate being the sum of both processes. At pH higher than 4.5, the disaggregation rate increased more than 3 orders of magnitude per pH unit increase. For concentrations lower than 30 mg L(-1), the equilibrium condition for the PPHA was complete disaggregation even for a pH as low as 3.6.     

A multiplex culture system for the long‐term growth of fission yeast cells

Maintenance of long‐term cultures of yeast cells is central to a broad range of investigations, from metabolic studies to laboratory evolution assays. However, repeated dilutions of batch cultures lead to variations in medium composition, with implications for cell physiology. In Saccharomyces cerevisiae, powerful miniaturized chemostat setups, or ministat arrays, have been shown to allow for constant dilution of multiple independent cultures. Here we set out to adapt these arrays for continuous culture of a morphologically and physiologically distinct yeast, the fission yeast Schizosaccharomyces pombe, with the goal of maintaining constant population density over time. First, we demonstrated that the original ministats are incompatible with growing fission yeast for more than a few generations, prompting us to modify different aspects of the system design. Next, we identified critical parameters for sustaining unbiased vegetative growth in these conditions. This requires deletion of the gsf2 flocculin‐encoding gene, along with addition of galactose to the medium and lowering of the culture temperature. Importantly, we improved the flexibility of the ministats by developing a piezo‐pump module for the independent regulation of the dilution rate of each culture. This made it possible to easily grow strains that have different generation times in the same assay. Our system therefore allows for maintaining multiple fission yeast cultures in exponential growth, adapting the dilution of each culture over time to keep constant population density for hundreds of generations. These multiplex culture systems open the door to a new range of long‐term experiments using this model organism. © 2017 The Authors. Yeast published by John Wiley & Sons, Ltd.     

Proposal of a novel parameter to describe the influence of pH on the lag phase of Listeria monocytogenes

Predictive models for lag phase duration (lambda) have been less reliable than specific growth rate (mu) models due, in part, to the influence of the pre-growth environment on lambda. A discrete modelling approach was taken to more completely define the response of individual cells to new environments. Time to detection (td) data was obtained from serial twofold dilutions of Listeria monocytogenes growing in a Bioscreen at 30 degrees C. Comparison of the inoculum densities required to achieve maximum td at growth pH values from 7.2 to 4.7 revealed that, as the growth pH decreased, fewer cells were capable of making the transition to the exponential phase. The proportion of these cells (termed "adaptable cells") in the original inoculum was used to define a new parameter (r0) which, when combined with the constant mean individual cell physiological state parameter (p0), the variation in p0 (SDp0), the inital inoculum (N0) and the maximum population density (Nmax) was able to simulate a complete growth curve. Power transformations with rescaled explanatory variables provided suitable models for the influence of pH on mu, r0, and SDp0, (r2>0.70).     

Antibacterial action of vegetable extracts on the growth of pathogenic bacteria

Under controlled conditions, extracts of garlic, onion, turnip, green peppers and radishes were used to inhibit Escherichia coli, Salmonella typhosa, Shigella dysentriae and Staphylococcus aureus, which are all pathogenic bacteria. It was found that 1–4% by vol. of garlic extract completely inhibited the growth of all the bacteria used. 4% by vol. of onion extract completely inhibited the growth of both Shigella dysentriae and Staphylococcus aureus at 10^–6 dilution. Salmonella typhosa and E. coli were not completely inhibited; the inhibition was 48·3% for E. coli and 95·3% for Salmonella typhosa. At 10^–4 bacterial dilution, onion extract decreased the colony number substantially in all four bacteria. 4% extracts from turnip, green peppers and radishes did not show a definite antibacterial action against any bacterium at the given dilutions. On the contrary some growth stimulating activity of these extracts on some bacteria was observed.     

A combined discrete-continuous model describing the lag phase of Listeria monocytogenes

Food microbiologists generally use continuous sigmoidal functions such as the empirical Gompertz equation to obtain the kinetic parameters specific growth rate (mu) and lag phase duration (lambda) from bacterial growth curves. This approach yields reliable information on mu; however, values for lambda are difficult to determine accurately due, in part, to our poor understanding of the physiological events taking place during adaptation of cells to new environments. Existing models also assume a homogeneous population of cells, thus there is a need to develop discrete event models which can account for the behavior of individual cells. Time to detection (t(d)) values were determined for Listeria monocytogenes using an automated turbidimetric instrument, and used to calculate mu. Mean individual cell lag times (tL) were calculated as the difference between the observed t(d) and the theoretical value estimated using mu. Variability in tL for individual cells in replicate wells was estimated using serial dilutions. A discrete stochastic model was applied to the individual cells, and combined with a deterministic population-level growth model. This discrete-continuous model incorporating tL and the variability in tL (expressed as standard deviation; S.D.(L)) predicted a reduced variability between wells with increased number of cells per well, in agreement with experimental findings. By combining the discrete adaptation step with a continuous growth function it was possible to generate a model which accurately described the transition from lag to exponential phase. This new model may serve as a useful tool for describing individual cell behavior, and thus increasing our knowledge of events occurring during the lag phase.     

Application of polymyxin-coated polyester cloth to the semi-quantitation of Salmonella in processed foods.

A rapid and economical semi-quantitative test for Salmonella cells in foods is proposed. Food samples containing different levels of Salmonella cells were homogenized and serially diluted in enrichment broths and then incubated for about 20 h at 37 degrees C. The presence of Salmonella cells in each dilution was assayed by capturing deoxycholate-extracted Salmonella lipopolysaccharides on a sheet of polymyxin-coated polyester cloth, followed by colorimetric detection with an anti-Salmonella antibody-enzyme conjugate. The minimum dilutions which resulted in no detectable growth were correlated with the extent of Salmonella contamination in the food samples.     

加权平均法表述菌落总数测定的数学模型与 测量不确定度的评定

摘 要 目的:建立食品菌落总数测定的通用数学模型和测量不确定度的评定方法。方法：按照加权平均的算法对菌落总数计算公式进行推导,建立了菌落总数计数方法的通用数学模型。以某橙汁饮料菌落总数的测定过程为例,从三个方面分析并量化了各不确度的分量,分别为：不同稀释度平板上菌落数的分布（以同一稀释度上两个平板计数结果的相对相差表示）,样品移取和稀释过程（以各量具的容量允差及稀释过程对稀释倍数贡献的相对不确度表示）,数字修约（以修约间隔引入的粗大误差表示）。按照均方根法则,将各计数平板的测量不确度进行加和,即为总测量不确度。结果：本例中该橙汁饮料菌落总数的扩展不确度U=0.2×104 CFU/mL, k =2。结论：建立了简便准确的食品菌落数测量不确定度的评定方法。     

Growth kinetics of Listeria monocytogenes in broth and beef frankfurters--determination of lag phase duration and exponential growth rate under isothermal conditions

ABSTRACT:  The objective of this study was to develop a new kinetic model to describe the isothermal growth of microorganisms. The new model was tested with Listeria monocytogenes in tryptic soy broth and frankfurters, and compared with 2 commonly used models—Baranyi and modified Gompertz models. Bias factor (BF), accuracy factor (AF), and root mean square errors (RMSE) were used to evaluate the 3 models. Either in broth or in frankfurter samples, there were no significant differences in BF (approximately 1.0) and AF (1.02 to 1.04) among the 3 models. In broth, the mean RMSE of the new model was very close to that of the Baranyi model, but significantly lower than that of the modified Gompertz model. However, in frankfurters, there were no significant differences in the mean RMSE values among the 3 models. These results suggest that these models are equally capable of describing isothermal bacterial growth curves. Almost identical to the Baranyi model in the exponential and stationary phases, the new model has a more identifiable lag phase and also suggests that the bacteria population would increase exponentially until the population approaches to within 1 to 2 logs from the stationary phase. In general, there is no significant difference in the means of the lag phase duration and specific growth rate between the new and Baranyi models, but both are significantly lower than those determined from the modified Gompertz models. The model developed in this study is directly derived from the isothermal growth characteristics and is more accurate in describing the kinetics of bacterial growth in foods.     

Correlation between the change in the kinetics of the ribosomal RNA rrnB P2 promoter and the transition from lag to exponential phase with Pseudomonas fluorescens

Developing accurate mathematical models to describe the pre-exponential lag phase in food-borne pathogens presents a considerable challenge to food microbiologists. While the growth rate is influenced by current environmental conditions, the lag phase is affected in addition by the history of the inoculum. A deeper understanding of physiological changes taking place during the lag phase would improve accuracy of models, and in earlier studies a strain of Pseudomonas fluorescens containing the Tn7-luxCDABE gene cassette regulated by the rRNA promoter rrnB P2 was used to measure the influence of starvation, growth temperature and sub-lethal heating on promoter expression and subsequent growth. The present study expands the models developed earlier to include a model which describes the change from exponential to linear increase in promoter expression with time when the exponential phase of growth commences. A two-phase linear model with Poisson weighting was used to estimate the lag (LPDLin) and the rate (RLin) for this linear increase in bioluminescence. The Spearman rank correlation coefficient (r=0.830) between the LPDLin and the growth lag phase (LPDOD) was extremely significant (P相似文献   

A new logistic model for bacterial growth

A new logistic model for bacterial growth was developed in this study. The model is based on a logistic model, which is often applied for biological and ecological population kinetics. The new model is described by a differential equation and contains an additional term for suppression of the growth rate during the lag phase, compared with the original logistic equation. The new model successfully described sigmoidal growth curves of Escherichia coli and Salmonella under various initial conditions. Data for E. coli were obtained from our experiments and data for Salmonella from the literature. When the new model was compared with a modified Gompertz model, which is widely used by many predictive microbiology researchers, it proved to be superior to the Gompertz model. Further, Salmonella growth at varying temperature could be well simulated by the new model. These results indicate that the new model will be a useful tool to predict bacterial growth under various temperature profiles.     

Effect of natural microbiota on growth of Salmonella spp. in fresh pork – A predictive microbiology approach

This study was undertaken to model and predict growth of Salmonella and the dominating natural microbiota, and their interaction in ground pork. Growth of Salmonella in sterile ground pork at constant temperatures between 4 °C and 38 °C was quantified and used for developing predictive models for lag time, max. specific growth rate and max. population density. Data from literature were used to develop growth models for the natural pork microbiota. Challenge tests at temperatures from 9.4 to 24.1 °C and with Salmonella inoculated in ground pork were used for evaluation of interaction models. The existing Jameson-effect and Lotka–Volterra species interaction models and a new expanded Jameson-effect model were evaluated. F-test indicated lack-of-fit for the classical Jameson-effect model at all of the tested temperatures and at 14.1–20.2 °C this was caused by continued growth of Salmonella after the natural microbiota had reached their max. population density. The new expanded Jameson-effect model and the Lotka–Volterra model performed better and appropriately described the continued but reduced growth of Salmonella after the natural microbiota had reached their max. population density. The expanded Jameson-effect model is a new and simple species interaction model, which performed as well as the more complex Lotka–Volterra model.     

Effects of washing procedure,particle size and dilution on the distribution between non‐washable,insoluble washable and soluble washable fractions in concentrate ingredients

The effects of washing procedure, particle size and dilution on the distribution of non‐washable (NWF), insoluble washable (ISWF) and soluble washable (SWF) fractions were studied. The effects of three washing procedures (Yang (Y), Melin (M) and in situ (IS)) on the size of NWF, ISWF and SWF in six concentrate ingredients (maize, barley, milo, peas, lupins and faba beans), ground at two different particle sizes, were compared. Method M was further developed (method SM) by reducing the dilution ratio; its effect on NWF, ISWF and SWF was compared. A new washing method was developed (method AA) which involved continuous washing of nylon bags in a centrifuge beaker; its effect on NWF, ISWF and SWF at different dilutions with water was compared with the IS, M, SM and Y methods. The effects of different dilutions on SWF and soluble true protein (STP) in six concentrate ingredients were studied. The effects of grain, washing method and particle size on the size of NWF and ISWF were significant, with significant interactions between grain and particle size, grain and washing method, particle size and washing method, but no interaction between grain type, washing method and particle size. In method Y the size of NWF was smaller than in the other methods. The results showed that, except in lupins, NWF in grains was significantly higher than in legume seeds. Increasing the particle size significantly increased NWF, whereas ISWF was decreased. The size of SWF in legume seeds was higher than in the grains. Increasing the dilution, increased STP in legume seeds, but not in grains. Copyright © 2007 Society of Chemical Industry     

Estimating the precision of serial dilutions and colony counts: contribution of laboratory re-calibration of pipettes

The basic (inherent) precision of serial dilutions and of colony counts made from them may be reliably estimated by reference solely to the pipette-manufacturer's specifications. Such estimates do not include external sources of variation and may be regarded as minima. The quality of estimation can be improved by using information gained by laboratory ('in-house') re-calibration of the pipettes. The degree of improvement was assessed by comparison with similar series made without re-calibration. It was found that improvement was minimal for colony counts but worthwhile for homogeneous solutions.     

How disaggregated should information be for a sound food security policy?

This study aimed to answer the question whether disaggregating micro data on food security conditions yielded sufficient new information to improve food security policies. To answer this question, we proposed and implemented a conceptual model that comprised three successive levels of disaggregation. The model was implemented for the Punjab province of Pakistan for which primary data was collected from 1,152 rural households. To measure the food security status of households, the Dietary Intake Assessment (DIA) method was used. Furthermore, the determinants of food security were identified using a Logit Regression model. Comparing the results of this model suggested that disaggregation yields sufficient new information to warrant the extra effort. We found that food security of different household categories and micro-regions were statistically different from each other; moreover, household categories differed in their food security status even within regions. Basing potential policies on analysis of too aggregated data a level can lead to biased conclusions. An implication is that a blanket policy for ensuring rural household food security, as currently implemented in Pakistan, is not an efficient approach.     

Mathematical modeling of growth of non-O157 Shiga toxin-producing Escherichia coli in raw ground beef

Abstract: The objective of this study was to investigate the growth of Shiga toxin‐producing Escherichia coli (STEC, including serogroups O45, O103, O111, O121, and O145) in raw ground beef and to develop mathematical models to describe the bacterial growth under different temperature conditions. Three primary growth models were evaluated, including the Baranyi model, the Huang 2008 model, and a new growth model that is based on the communication of messenger signals during bacterial growth. A 5 strain cocktail of freshly prepared STEC was inoculated to raw ground beef samples and incubated at temperatures ranging from 10 to 35 °C at 5 °C increments. Minimum relative growth (<1 log₁₀ cfu/g) was observed at 10 °C, whereas at other temperatures, all 3 phases of growth were observed. Analytical results showed that all 3 models were equally suitable for describing the bacterial growth under constant temperatures. The maximum cell density of STEC in raw ground beef increased exponentially with temperature, but reached a maximum of 8.53 log₁₀ cfu/g of ground beef. The specific growth rates estimated by the 3 primary models were practically identical and can be evaluated by either the Ratkowsky square‐root model or a Bělehrádek‐type model. The temperature dependence of lag phase development for all 3 primary models was also developed. The results of this study can be used to estimate the growth of STEC in raw ground beef at temperatures between 10 and 35 °C. Practical Application: Incidents of foodborne infections caused by non‐O157 Shiga toxin‐producing Escherichia coli (STEC) have increased in recent years. This study reports the growth kinetics and mathematical modeling of STEC in ground beef. The mathematical models can be used in risk assessment of STEC in ground beef.     

Lactic acid production using waste generated from sweet potato processing

Organic waste generated from industrial sweet potato canning is estimated to be 30% of incoming raw material with significant residual carbohydrate content. The purpose of this study was to evaluate the potential of waste generated from sweet potato processing material to support the growth of lactic acid bacteria and the production of lactic acid. The waste was comprised of 16.5% solids consisting of 18.5% ash, 4.4% protein, 20.5% simple sugars and 19% soluble starch. Following a screening of three lactic acid bacteria strains, Lactobacillus rhamnosus was deemed the best candidate for lactic acid production. The potential of various dilutions of the enzyme‐hydrolysed waste, with and without pH control, as a fermentation substrate was evaluated. Lactic acid production was highest in hydrolysed waste (without dilution) at pH set point 5.0, yielding 10 g L^?1 in 72 h. Thus, lactic acid, a valuable organic compound, can be generated from sweet potato waste.     

Sample Dilution Influences the Determination of Antioxidant Capacity in Food: How to Minimize It?

The influence of sample dilution on the measurement of antioxidant capacity was analyzed. To ensure the reproducibility of results, it is necessary to realize such scarce investigations. This study focuses on different antioxidant capacity assays commonly used for the analysis of pure substances and food extracts. For all compounds and foods tested in most of the four assays (Trolox equivalent antioxidant capacity, 2,2-diphenyl-1-picrylhydrazyl, and oxygen radical absorbance capacity), effects of sample dilution on the measured (and recalculated) antioxidant capacity were observed, with differences up to 28 % between dilutions. An extrapolation method was proposed to obtain a “real value” thus to minimize the effects of the sample dilution. This extrapolation method is relatively simple, based on a linear regression of 4 or 5 appropriate dilutions of the sample and applicable to the various assays. The use of such a method will improve the consistency of interlaboratory antioxidant capacity data and thus permit better comparisons. In contrast, there was no dilution problem with ferric reducing antioxidant power assays.