Early bending kinetics in response to geostimulation or unilateral IAA application in Lolium nodal segments

Abstract In Lolium multiflorum nodal segments, bending responses both to geostimulation and unilateral indole-3-acetic acid (IAA) application exhibited much variability in their lag times and speeds of early bending. Despite this variability, mean response curves to gravity and auxin stimulus were markedly similar with each having a phase of immediate, negative bending followed by phases of slow, positive bending and eventually more rapid, positive bending within 40 min of initial treatment. Comparison of lag times for response to geostimulation and unilateral IAA application, whether derived from the mean of individual replicates, or from mean curve data, showed that at least 4 min is available in this geotropic system for establishment of asymmetric auxin levels that could lead to differential growth. The hypothesis that variability in georesponse in Lolium nodal segments is linked to variable sensitivity of geosensitive tissue to auxin was tested using matching longitudinally-halved nodal segments and evidence was obtained in support of the hypothesis from lag time but not from early bending speed data. The implications of the findings for an involvement of endogenous IAA in shoot geotropism together with the necessity to understand better the complex behaviour of bending response in individual replicates are discussed.     

Historical and Contemporary NaCl Concentrations Affect the Duration and Distribution of Lag Times from Individual Spores of Nonproteolytic Clostridium botulinum

In this study we determined the effect of NaCl concentration during sporulation (0 or 3.0% [wt/vol] added NaCl) and subsequent growth (0 or 2.0% [wt/vol] added NaCl) on the distributions of times associated with various stages of the lag phase of individual spores of nonproteolytic Clostridium botulinum strain Eklund 17B. The effects of NaCl on the probability of germination and the probability of subsequent growth were also determined. Spore populations exhibited considerable heterogeneity at all stages of lag phase for each condition tested. Germination time did not correlate strongly with the times for later stages in the lag phase, such as outgrowth and doubling time. Addition of NaCl to either the sporulation or growth media increased the mean times for, and variability of, all the measured stages of the lag phase (germination, emergence, time to one mature cell, and time to first doubling). There was a synergistic interaction between the inhibitory effects of NaCl in the sporulation medium and the inhibitory effects of NaCl in the subsequent growth medium on the total lag time and each of its stages. Addition of NaCl to either the sporulation medium or the growth medium reduced both the probability of germination and the probability of a germinated spore developing into a mature cell, but the interaction was not synergistic. Spores formed in medium with added NaCl were not better adapted to subsequent growth in suboptimal osmotic conditions than spores formed in medium with no added NaCl were. Knowledge of the distribution of lag times for individual spores and quantification of the biovariability within lag time distributions may provide insight into the underlying mechanisms and can be used to improve predictions of growth in food and to refine risk assessments.     

Historical and contemporary NaCl concentrations affect the duration and distribution of lag times from individual spores of nonproteolytic clostridium botulinum

In this study we determined the effect of NaCl concentration during sporulation (0 or 3.0% [wt/vol] added NaCl) and subsequent growth (0 or 2.0% [wt/vol] added NaCl) on the distributions of times associated with various stages of the lag phase of individual spores of nonproteolytic Clostridium botulinum strain Eklund 17B. The effects of NaCl on the probability of germination and the probability of subsequent growth were also determined. Spore populations exhibited considerable heterogeneity at all stages of lag phase for each condition tested. Germination time did not correlate strongly with the times for later stages in the lag phase, such as outgrowth and doubling time. Addition of NaCl to either the sporulation or growth media increased the mean times for, and variability of, all the measured stages of the lag phase (germination, emergence, time to one mature cell, and time to first doubling). There was a synergistic interaction between the inhibitory effects of NaCl in the sporulation medium and the inhibitory effects of NaCl in the subsequent growth medium on the total lag time and each of its stages. Addition of NaCl to either the sporulation medium or the growth medium reduced both the probability of germination and the probability of a germinated spore developing into a mature cell, but the interaction was not synergistic. Spores formed in medium with added NaCl were not better adapted to subsequent growth in suboptimal osmotic conditions than spores formed in medium with no added NaCl were. Knowledge of the distribution of lag times for individual spores and quantification of the biovariability within lag time distributions may provide insight into the underlying mechanisms and can be used to improve predictions of growth in food and to refine risk assessments.     

A comparison of the bioscreen method and microscopy for the determination of lag times of individual cells of listeria monocytogenes

Lag phase durations (tLag) of individual Listeria monocytogenes cells were analysed using the NightOwl Molecular Imaging System, and results were compared with mean individual cell lag times (tL) obtained from the detection time (td) method using Bioscreen. With Bioscreen, an average tL of 6.39+/-0.89 h was obtained from five separate experiments. With the NightOwl method, an average tLag of 2.73+/-0.06 h was obtained from three experiments consisting of eight total replicates. Lag values from the NightOwl and Bioscreen are related by the equation: tLag = tL + DT, where DT is the doubling time. The equivalent tLag mean value for the Bioscreen method was 7.11+/-0.84 h. Individual lag times measured by both methods were normally distributed (r2 for Bioscreen and NightOwl ranged from 0.951 to 0.999 and from 0.884 to 0.982, respectively). The results suggest that the NightOwl method can provide accurate estimates of individual cell lag times, which will facilitate the development of combined discrete continuous models for bacterial growth.     

Influence of stress on individual lag time distributions of Listeria monocytogenes

The effects of nine common food industry stresses on the times to the turbidity (T(d)) distribution of Listeria monocytogenes were determined. It was established that the main source of the variability of T(d) for stressed cells was the variability of individual lag times. The distributions of T(d) revealed that there was a noticeable difference in response to the stresses encountered by the L. monocytogenes cells. The applied stresses led to significant changes of the shape, the mean, and the variance of the distributions. The variance of T(d) of wells inoculated with single cells issued from a culture in the exponential growth phase was multiplied by at least 6 and up to 355 for wells inoculated with stressed cells. These results suggest stress-induced variability may be important in determining the reliability of predictive microbiological models.     

Connection between stochastic and deterministic modelling of microbial growth

We present in this paper various links between individual and population cell growth. Deterministic models of the lag and subsequent growth of a bacterial population and their connection with stochastic models for the lag and subsequent generation times of individual cells are analysed. We derived the individual lag time distribution inherent in population growth models, which shows that the Baranyi model allows a wide range of shapes for individual lag time distribution. We demonstrate that individual cell lag time distributions cannot be retrieved from population growth data. We also present the results of our investigation on the effect of the mean and variance of the individual lag time and the initial cell number on the mean and variance of the population lag time. These relationships are analysed theoretically, and their consequence for predictive microbiology research is discussed.     

Urinary 6-Sulfatoxymelatonin Cycle-To-Cycle Variability

For either clinical or research purposes, the timing of the nocturnal onset in production of the urinary melatonin metabolite 6-sulfatoxymelatonin (UaMT6s-onset), has been proposed as a reliable and robust marker of circa-dian phase. However, given that most circadian rhythms show cycle-to-cycle variability, the statistical reliability of phase estimates obtained from a single study using UaMT6s-onset remains to be determined. Following 2 weeks of sleep diary and wrist actigraphy, 15 young, healthy good sleepers participated in four UaMT6s sampling sessions spaced 1 day apart. During the sampling sessions subjects remained indoors under low light conditions and hourly urine samples were collected from 19:00 to 02:00 h. Samples were subsequently assayed for UaMT6s using standard radioimmunographic techniques. UaMT6s-onset was determined by the time at which melatonin production exceeded the average of three proceeding trials by 100%. Sleep onset times were derived from sleep diary and actigraphic measures taken before the melatonin collection nights. We found that there was no significant variation between nights in group mean UaMT6s-onset times, and intraindividual variability was small. In addition, UaMT6s-onset times were highly and significantly correlated between nights (grand mean r = 0.804). Our results suggest that within 95% confidence interval limits, individual UaMT6s-onset estimates obtained from a single night UaMT6s-onset study can be used to predict subsequent UaMT6s-onset times within ±97 min. A close temporal relationship was also found between the timing of UaMT6s-onset and sleep onset. Overall, our results suggest that under entrained conditions single-session UaMT6s-onset studies can provide reliable individual UaMT6s-onset phase estimates and that the protocol described in this study is a practical and noninvasive methodology. (Chronobiology International, 13(6), 411–421, 1996)     

Urinary 6-Sulfatoxymelatonin Cycle-To-Cycle Variability

For either clinical or research purposes, the timing of the nocturnal onset in production of the urinary melatonin metabolite 6-sulfatoxymelatonin (UaMT6s-onset), has been proposed as a reliable and robust marker of circa-dian phase. However, given that most circadian rhythms show cycle-to-cycle variability, the statistical reliability of phase estimates obtained from a single study using UaMT6s-onset remains to be determined. Following 2 weeks of sleep diary and wrist actigraphy, 15 young, healthy good sleepers participated in four UaMT6s sampling sessions spaced 1 day apart. During the sampling sessions subjects remained indoors under low light conditions and hourly urine samples were collected from 19:00 to 02:00 h. Samples were subsequently assayed for UaMT6s using standard radioimmunographic techniques. UaMT6s-onset was determined by the time at which melatonin production exceeded the average of three proceeding trials by 100%. Sleep onset times were derived from sleep diary and actigraphic measures taken before the melatonin collection nights. We found that there was no significant variation between nights in group mean UaMT6s-onset times, and intraindividual variability was small. In addition, UaMT6s-onset times were highly and significantly correlated between nights (grand mean r = 0.804). Our results suggest that within 95% confidence interval limits, individual UaMT6s-onset estimates obtained from a single night UaMT6s-onset study can be used to predict subsequent UaMT6s-onset times within ±97 min. A close temporal relationship was also found between the timing of UaMT6s-onset and sleep onset. Overall, our results suggest that under entrained conditions single-session UaMT6s-onset studies can provide reliable individual UaMT6s-onset phase estimates and that the protocol described in this study is a practical and noninvasive methodology. (Chronobiology International, 13(6), 411-421, 1996)     

Distribution of turbidity detection times produced by single cell-generated bacterial populations

The distributions of the times to turbidity for wells inoculated with single cells of Listeria innocua were determined in different environmental conditions (pH 4.5 to 7 and with 0.5% to 8% of NaCl at 30 degrees C). It was established by statistical analysis that the main source of the variability of the detection times, T, is the variability of individual lag times. A linear relation dev(T) approximately T was observed between the detection times and their standard deviation. At slow growth, other sources of variability became increasingly significant.     

Spectroscopic evidence for the existence of an obligate pre-fibrillar oligomer during glucagon fibrillation

The 29-residue peptide hormone glucagon has been used as a model system for the study of amyloid-like fibrils. Atomic force microscopy (AFM) studies have detected putative oligomeric species during this lag phase, but this has not been confirmed by any spectroscopic technique. Here we use an attached pyrene group to detect association (excimer formation) between individual glucagon molecules. Our data show that excimer formation precedes fibrillation both at different pHs and with sulfate, and support our original proposal that glucagon fibril formation is preceded by oligomer formation. We suggest that pyrene-labelling may be a useful way to monitor oligomer formation during protein fibrillation.     

Heterogeneity of times required for germination and outgrowth from single spores of nonproteolytic Clostridium botulinum

Knowledge of the distribution of growth times from individual spores and quantification of this biovariability are important if predictions of growth in food are to be improved, particularly when, as for Clostridium botulinum, growth is likely to initiate from low numbers of spores. In this study we made a novel attempt to determine the distributions of times associated with the various stages of germination and subsequent growth from spores and the relationships between these stages. The time to germination (t(germ)), time to emergence (t(emerg)), and times to reach the lengths of one (t(C1)) and two (t(C2)) mature cells were quantified for individual spores of nonproteolytic C. botulinum Eklund 17B using phase-contrast microscopy and image analysis. The times to detection for wells inoculated with individual spores were recorded using a Bioscreen C automated turbidity reader and were compatible with the data obtained microscopically. The distributions of times to events during germination and subsequent growth showed considerable variability, and all stages contributed to the overall variability in the lag time. The times for germination (t(germ)), emergence (t(emerg) - t(germ)), cell maturation (t(C1) - t(emerg)), and doubling (t(C2) - t(C1)) were not found to be correlated. Consequently, it was not possible to predict the total duration of the lag phase from information for just one of the stages, such as germination. As the variability in postgermination stages is relatively large, the first spore to germinate will not necessarily be the first spore to produce actively dividing cells and start neurotoxin production. This information can make a substantial contribution to improved predictive modeling and better quantitative microbiological risk assessment.     

Human alpha-satellite DNA specific to chromosomes 13 and 21: use for the analysis of polymorphism of acrocentric chromosomes and the origin of the additional chromosome 21 in Down's syndrome]

Chromosomal distribution of cloned human alpha-satellite DNA alpha R1-6 has been studied by in situ hybridization technique. The sequence under study has been shown to be predominantly located in the centromeric regions of chromosomes 13 and 21. Intercellular variability of labelling patterns in every person under analysis being insignificant, there exists strong individual variability of interchromosomal distribution of the satellite. This variability leads to the differences of the chromosome labelling density (i.e. the number of satellite DNA copies) both between and within chromosome pairs. The difference in the copy number between two homologues chromosomes, 13 and 21 reaches up to 5 times. No correlation between nondisjunction and the number of copies of alpha-satellite DNA was found. Analysis of individual distribution of satellite between homologues of chromosome 21 provides new possibilities for determination of the origin of extra chromosome in the patients with trisomy 21.     

Contrasting Effects of Heat Treatment and Incubation Temperature on Germination and Outgrowth of Individual Spores of Nonproteolytic Clostridium botulinum Bacteria

In this study, we determined the effects of incubation temperature and prior heat treatment on the lag-phase kinetics of individual spores of nonproteolytic Clostridium botulinum Eklund 17B. The times to germination (t_germ), one mature cell (t_C1), and two mature cells (t_C2) were measured for individual unheated spores incubated at 8, 10, 15, or 22°C and used to calculate the t_germ, the outgrowth time (t_C1 − t_germ), and the first doubling time (t_C2 − t_C1). Measurements were also made at 22°C of spores that had previously been heated at 80°C for 20 s. For unheated spores, outgrowth made a greater contribution to the duration and variability of the lag phase than germination. Decreasing incubation temperature affected germination less than outgrowth; thus, the proportion of lag associated with germination was less at lower incubation temperatures. Heat treatment at 80°C for 20 s increased the median germination time of surviving spores 16-fold and greatly increased the variability of spore germination times. The shape of the lag-time (t_C1) and outgrowth (t_C1 − t_germ) distributions were the same for unheated spores, but heat treatment altered the shape of the lag-time distribution, so it was no longer homogeneous with the outgrowth distribution. Although heat treatment mainly extended germination, there is also evidence of damage to systems required for outgrowth. However, this damage was quickly repaired and was not evident by the time the cells started to double. The results presented here combined with previous findings show that the stage of lag most affected, and the extent of any effect in terms of duration or variability, differs with both historical treatment and the growth conditions.Clostridium botulinum is a group of four physiologically and phylogenetically distinct anaerobic spore-forming bacteria (known as groups I, II, III, and IV) that produce the highly toxic botulinum neurotoxin (12). The severity of the intoxication, botulism, ensures considerable effort is directed at preventing the growth of this pathogen in food. Nonproteolytic (group II) C. botulinum is one of the two groups most frequently associated with food-borne botulism. It forms heat-resistant spores and can germinate, grow, and produce toxin at 3°C (8); thus, nonproteolytic C. botulinum is a particular concern in mild heat-treated chilled foods (16, 17).Spores formed by pathogens such as C. botulinum are a significant food safety issue since they are able to resist many of the processes, such as cooking, used to kill vegetative cells. Understanding the transformation from a dormant spore to active vegetative cells is an important part of quantifying the risk associated with such organisms. Considerable effort has been targeted at measuring and relating the kinetic responses of populations of C. botulinum to environmental conditions and such data have been used to create predictive models, for example, ComBase (www.combase.cc). Such approaches have made a considerable contribution to ensuring food safety but problems with using population based predictions may arise when an initial inoculum is very small or additional information beyond point values is required. Spores typically contaminate foods at low concentrations so that growth of C. botulinum, when it occurs, is likely to initiate from just a few spores. In these circumstances the distribution of times to growth in packs will reflect the heterogeneity of times to growth from the contaminating individual spores. There is an intrinsic variability between individual spores within a population, and the relationship between population lag and individual lag is complex. Consequently, individual lag times cannot be predicted from population measurements (3). Knowledge of the underlying distribution would allow greater refinement of risk assessments.The lag period between a spore being exposed to conditions suitable for growth and the start of exponential growth will reflect the combined times of germination, emergence, elongation, and first cell division. Currently, very little is known about the variability and duration of these stages and any relationships between them. Measuring the kinetics of spore germination is usually achieved by measuring a population to identify time to percent completion. Such germination curves represent the summation of responses by individual spores. Some authors have measured the biovariability associated with individual spores, but most studies have examined only germination (4-7, 11, 22) and not subsequent outgrowth. More recently, we have used phase-contrast microscopy and image analysis to follow individual spores of nonproteolytic C. botulinum from dormancy, through germination and emergence, to cell division (21, 23). These experiments showed there is very little, or no, relationship between the time spent in each stage by individual spores. We have now extended this work to determine distributions of times for different stages in lag phase as affected by heat treatment and incubation temperature.     

Influence of Stress on Individual Lag Time Distributions of Listeria monocytogenes

The effects of nine common food industry stresses on the times to the turbidity (T_d) distribution of Listeria monocytogenes were determined. It was established that the main source of the variability of T_d for stressed cells was the variability of individual lag times. The distributions of T_d revealed that there was a noticeable difference in response to the stresses encountered by the L. monocytogenes cells. The applied stresses led to significant changes of the shape, the mean, and the variance of the distributions. The variance of T_d of wells inoculated with single cells issued from a culture in the exponential growth phase was multiplied by at least 6 and up to 355 for wells inoculated with stressed cells. These results suggest stress-induced variability may be important in determining the reliability of predictive microbiological models.     

Parameter estimation for the distribution of single cell lag times

In Quantitative Microbial Risk Assessment, it is vital to understand how lag times of individual cells are distributed over a bacterial population. Such identified distributions can be used to predict the time by which, in a growth-supporting environment, a few pathogenic cells can multiply to a poisoning concentration level.We model the lag time of a single cell, inoculated into a new environment, by the delay of the growth function characterizing the generated subpopulation. We introduce an easy-to-implement procedure, based on the method of moments, to estimate the parameters of the distribution of single cell lag times. The advantage of the method is especially apparent for cases where the initial number of cells is small and random, and the culture is detectable only in the exponential growth phase.     

Toxoplasma gondii-Vertebrate Cell Interactions. II. The Intracellular Reproductive Phase

SYNOPSIS.
The reproduction of Toxoplasma gondii RH-strain in vertebrate cells was studied in a controlled-environment culture system. The lag period before reproduction and the doubling time of individual parasites were determined using a least-squares linear regression method of analysis which does not artificially constrain the data. In the majority of cases, the time intercept of the linear regression line was either zero, implying the lack of a lag phase before reproduction, or negative, implying the parasite had completed part of its reproductive cycle before entering the host cell. The mean doubling time of T. gondii is 10.9 h in bovine embryo skeletal muscle cells and 8.3 h in HeLa cells. This difference is not significant at the 5% level. The population doubling times of mouse-derived parasites is best described by a gamma distribution.     

Toxoplasma gondii-vertebrate cell interactions. II. The intracellular reproductive phase.

The reproduction of Toxoplasma gondii RH-strain in vertebrate cells was studied in a controlled-environment culture system. The lag period before reproduction and the doubling time of individual parasites were determined using a least-squares linear regression method of analysis which does not artificially constrain the data. In the majority of cases, the time intercept of the linear regression line was either zero, implying the lack of a lag phase before reproduction, or negative, implying the parasite had completed part of its reproductive cycle before entering the host cell. The mean doubling time of T. gondii is 10.9 h in bovine embryo skeletal muscle cells and 8.3 h in HeLa cells. This difference is not significant at the 5% level. The population doubling times of mouse-derived parasites is best described by a gamma distribution.     

Sensitivity of flow cytometric data to variations in cell cycle parameters

Abstract We investigated to what extent flow cytometric DNA histograms are informative of cell cycle parameters. We created a computer program to simulate cell cycle progression in a generic and flexible way. Various scenarios, characterized by different models and distributions of cell cycle phase transit times, have been analysed in order to obtain the percentages of cells in the different cell cycle phases during exponential growth and their time course after mitotic block.
Cell percentages during exponential growth were insensitive to intercell variability in phase transit times and thus can be employed to estimate the relative mean phase transit times, even in the presence of non-cycling cells. However, this information is ambiguous if re-entry of such cells into the cycling status is permitted. The stathmokinetic outline gives the mean phase transit times, but also provides information about the spread, but not the form, of the phase transit time distributions, being particularly sensitive to the spread of G1 phase duration. The stathmokinetic outline also helps distinguish between scenarios considering only cycling cells, those forecasting a fraction of definitively non-cycling cells and those admitting a Go status with first-order output kinetics.     

Development of a dynamic continuous-discrete-continuous model describing the lag phase of individual bacterial cells

AIMS: A previous model for adaptation and growth of individual bacterial cells was not dynamic in the lag phase, and could not be used to perform simulations of growth under non-isothermal conditions. The aim of the present study was to advance this model by adding a continuous adaptation step, prior to the discrete step, to form a continuous-discrete-continuous (CDC) model. METHODS AND RESULTS: The revised model uses four parameters: N(0), initial population; N(max), maximum population; p0, mean initial individual cell physiological state; SD(p0), standard deviation of the distribution of individual physiological states. A truncated normal distribution was used to generate tables of distributions to allow fitting of the CDC model to viable count data for Listeria monocytogenes grown at 5 degrees C to 35 degrees C. The p0 values increased with increasing SD(p0) and were, on average, greater than the corresponding population physiological states (h0); p0 and h0 were equivalent for individual cells. CONCLUSION: The CDC model has improved the ability to simulate the behaviour of individual bacterial cells by using a physiological state parameter and a distribution function to handle inter-cell variability. The stages of development of this model indicate the importance of physiological state parameters over the population lag concept, and provide a potential approach for making growth models more mechanistic by incorporating actual physiological events. SIGNIFICANCE AND IMPACT OF THE STUDY: Individual cell behaviour is important in modelling bacterial growth in foods. The CDC model provides a means of improving existing growth models, and increases the value of mathematical modelling to the food industry.