Biomedical subjects

N B Grover

Publications and source records attributed to N B Grover.

At least 19 recordsLinked to original sources

PubMed2001

Cell-cycle research with synchronous cultures: an evaluation.

The baby-machine system, which produces new-born Escherichia coli cells from cultures immobilized on a membrane, was developed many years ago in an attempt to attain optimal synchrony with minimal disturbance of steady-state growth. In the present article, we put forward a model to describe the behaviour of cells produced by this method, and provide quantitative evaluation of the parameters involved, at each of four different growth rates. Considering the high level of selection achievable with this technique and the natural dispersion in interdivision times, we believe that the output of the baby machine is probably close to optimal in terms of both quality and persistence of synchrony. We show that considerable information on events in the cell cycle can be obtained from populations with age distributions very much broader than those achieved with the baby machine and differing only modestly from steady state. The data presented here, together with the long and fruitful history of findings employing the baby-machine technique, suggest that minimisation of stress on cells is the single most important factor for successful cell-cycle analysis.

Amino Acids↗

PubMed2001

Dimensional regulation of cell-cycle events in Escherichia coli during steady-state growth.

Two opposing models have been put forward in the literature to describe the changes in the shape of individual Escherichia coli cells in steady-state growth that take place during the cell cycle: the Length model, which maintains that the regulating dimension is cell length, and the Volume model, which asserts it to be cell volume. In addition, the former model envisages cell diameter as decreasing with length up to constriction whereas the latter sees it as being constrained by the rigid cell wall. These two models differ in the correlations they predict between the various cellular dimensions (diameter, length, volume) not only across the entire population of bacteria but also, and especially, within subpopulations that define specific cell-cycle events (division, for example, or onset of constriction); the coefficients of variation at these specific events are also expected to be very different. Observations from cells prepared for electron microscopy (air-dried) and for phase-contrast microscopy (hydrated) appeared qualitatively largely in accordance with the predictions of the Length model. To obtain a more quantitative comparison, simulations were carried out of populations defined by each of the models; again, the results favoured the Length model. Finally, in age-selected cells using membrane elution, the diameter-length and diameter-volume correlations were in complete agreement with the Length model, as were the coefficients of variation. It is concluded that, at least with respect to cell-cycle events such as onset of constriction and cell division, length rather than volume is the controlling dimension.

Cell Cycle↗

PubMed1998

The significance of non-significance.

We discuss the implications of empirical results that are statistically non-significant. Figures illustrate the interrelations among effect size, sample sizes and their dispersion, and the power of the experiment. All calculations (detailed in Appendix) are based on actual noncentral t-distributions, with no simplifying mathematical or statistical assumptions, and the contribution of each tail is determined separately. We emphasize the importance of reporting, wherever possible, the a priori power of a study so that the reader can see what the chances were of rejecting a null hypothesis that was false. As a practical alternative, we propose that non-significant inference be qualified by an estimate of the sample size that would be required in a subsequent experiment in order to attain an acceptable level of power under the assumption that the observed effect size in the sample is the same as the true effect size in the population; appropriate plots are provided for a power of 0.8. We also point out that successive outcomes of independent experiments each of which may not be statistically significant on its own, can be easily combined to give an overall p value that often turns out to be significant. And finally, in the event that the p value is high and the power sufficient, a non-significant result may stand and be published as such.

Analysis of Variance↗

PubMed1996

Studies in psychoneuroimmunology: psychological, immunological, and neuroendocrinological parameters in Israeli civilians during and after a period of Scud missile attacks.

Twenty-two male volunteers in Jerusalem were subjected to a battery of psychological tests at the height of the Iraqi Scud missile attacks on Israeli cities during the 1991 Persian Gulf War and again after the cessation of hostilities. Venous blood samples were taken at each time point. The separated mononuclear cells and plasma were cryopreserved, and a spectrum of immunological and neuroendocrine assays were performed on the preserved samples. Psychological testing indicated levels of anxiety were higher during the war than they were after the war ended, and both anxiety and anger during the hostilities were significantly elevated in comparison with prewar data. During the war, specific war-related pressures were greater than everyday pressures, and problem-focused coping was more evident than emotion-focused coping. Natural-killer cell activity and cell-mediated lympholysis were significantly elevated during the war, as were plasma levels of adrenocorticotrophic hormone, neurotensin, and substance P. The only biological test parameter found to be reduced during the war period was mononuclear cell thymidine incorporated in nonstimulated cultures.

Adaptation, Psychological↗

PubMed1995

Characterization of cell-cycle-specific events in synchronous cultures of Escherichia coli: a theoretical evaluation.

Synchronous growth studies are often used to assess the presence, timing and duration of periodic phenomena in the bacterial cell cycle. In an effort to evaluate the quality and quantity of information on cycle-specific events that can reasonably be expected from such inquiries, a model was constructed of a synchronous culture of Escherichia coli cells as would be derived from a growing population immobilized on a surface, and applied to the case of one stable and one unstable cellular component. The results indicated that, while the presence of cycle-specific events may be easily detectable, their timing and duration are very difficult to establish in synchronous growth experiments. Furthermore, differences in timing can be misconstrued as differences in duration, and vice versa, when interpretations are based on the qualitative analysis of the data.

Cell Cycle↗

PubMed1995

On microbial states of growth.

It is crucial to the reproducibility of results and their proper interpretation that the conditions under which experiments are carried out be defined with rigour and consistency. In this review we attempt to clarify the differences and interrelationships among steady, balanced and exponential states of culture growth. Basic thermodynamic concepts are used to introduce the idea of steady-state growth in open, biological systems. The classical, sometimes conflicting, definitions of steady-state and balanced growth are presented, and a consistent terminology is proposed. The conditions under which a culture in balanced growth is also in exponential growth and in steady-state growth are indicated. It is pointed out that steady-state growth always implies both balanced and exponential growth, and examples in which the converse does not hold are described. More complex situations are then characterized and the terminology extended accordingly. This leads to the notion of normal growth and growth that can be synchronous or otherwise unbalanced but still reproducible, and to the condition of approximate steady state manifested by growth in batch culture and by asymmetrically dividing cells, which is analysed in some detail.

Bacteria↗

PubMed1994

Nucleoid partitioning and the division plane in Escherichia coli.

Escherichia coli nucleoids were visualized after the DNA of OsO4-fixed but hydrated cells was stained with the fluorochrome DAPI (4',6-diamidino-2-phenylindole dihydrochloride hydrate). In slowly growing cells, the nucleoids are rod shaped and seem to move along the major cell axis, whereas in rapidly growing, wider cells they consist of two- to four-lobed structures that often appear to advance along axes lying perpendicular or oblique to the major axis of the cell. To test the idea that the increase in cell diameter following nutritional shift-up is caused by the increased amount of DNA in the nucleoid, the cells were subjected to DNA synthesis inhibition. In the absence of DNA replication, the nucleoids continued to move in the growing filaments and were pulled apart into small domains along the length of the cell. When these cells were then transferred to a richer medium, their diameters increased, especially in the region enclosing the nucleoid. It thus appears that the nucleoid motive force does not depend on DNA synthesis and that cell diameter is determined not by the amount of DNA per chromosome but rather by the synthetic activity surrounding the nucleoid. Under the non-steady-state but balanced growth conditions induced by thymine limitation, nucleoids become separated into small lobules, often lying in asymmetric configurations along the cell periphery, and oblique and asymmetric division planes occur in more than half of the constricting cells. We suggest that such irregular DNA movement affects both the angle of the division plane and its position.

Cell Division↗

PubMed1993

Shape changes in Escherichia coli B/r A during agar filtration.

We have investigated the phenomenon of shape distortion in a sample of 1,552 Escherichia coli B/r A cells in balanced exponential growth, during preparation for electron microscopy by agar filtration. Mixed preparations of bacterial cells and polystyrene latex spheres were shadow cast at low angle and the resulting shadows used to obtain quantitative estimates for the dimensions of the dehydrated cells; these then serve as a basis for a model of its shape in three dimensions. A statistical analysis of the projections of clustered cells and the intervening fissures, in nonshadow-cast preparations, provides an estimate of the effects of drying. The average width of the dehydrated cell (450 nm) is about 20 nm greater than the diameter of the live bacterium, whereas its length (1,398 nm) is approximately 40 nm less.

Agar↗

PubMed1993

Control of mini-R1 plasmid replication: a computer simulation.

A molecular model for the control of plasmid R1 replication has been proposed by Nordström, Molin and Light (Plasmid 12, 71-90, 1984), involving three genes: repA, copA, copB. RepA codes for a polypeptide whose synthesis is required for initiation; replication is controlled by regulating this synthesis. CopA encodes a small, unstable, untranslated RNA molecule that inhibits translation of the repA message whereas copB produces a protein that inhibits transcription from the repA promoter. We have recast this model into precise mathematical terms and tested it by computer simulation of a synchronous culture in steady-state balanced growth, composed of individual Escherichia coli cells harboring the small, unstable derivative, mini-R1. All single-cell steady-state distributions obtained are independent of initial conditions, and the average values of various plasmid-related variables are similar to those measured experimentally. The relationship between the number of replication events per cell and the copy number at birth, as predicted by the model, mitigates against a sensitive correction mechanism for cells born with other than average copy number and is much closer quantitatively to a nonresponse system, although there is a weak dependence on copy number. The effect of the convergent transcription initiated at the repA and copB promoters on the expression of the copA gene is found to contribute little to the stability of mini-R1 replicons under steady-state growth conditions or to their potential for survival following infection. In fact, the role of the entire CopB control loop is shown to be quite minor, both in steady state and after infection. It is pointed out that genetic manipulations are far more easily performed in silico than in vivo but that results of the kind presented here are very often possible only when simulating individual cells.

Computer Simulation↗

PubMed1993

Partition of plasmid R1: a computer simulation.

A computer-simulated population of individual Escherichia coli cells harboring plasmid R1 parA+/parB- has been used to analyze three possible modes of plasmid segregation: equi-partition, in which plasmids are partitioned equally to daughter cells at cell division; single-site inheritance, in which the products of the most recent replication event are partitioned equally and the remaining plasmids are distributed randomly; and pair-site partition, in which a single, randomly chosen plasmid is actively partitioned to each daughter cell at division and the rest are distributed randomly. Comparison between predicted and experimental plasmid loss-frequency enabled us to rule out the first of these models as a likely mode of action in R1 but was inconclusive regarding the other two. The parA region would therefore seem to partition actively only one pair of plasmids to each daughter cell, the precise selection rule involved remaining unresolved. This question is not easily decided with current technology, as we show, but our simulation results also predict that the isolation of rep(Ts) mutants will provide an experimental system in which a clear distinction is possible between two plasmids that are the products of the most recent replication event and two that are chosen strictly at random.

Computer Simulation↗

PubMed1993

Dimensional rearrangement of Escherichia coli B/r cells during a nutritional shift-down.

In a search for the mechanism underlying dimensional changes in bacteria, the glucose analogue methyl alpha-D-glucoside was used to effect a rapid reduction in the mass growth rate of Escherichia coli by competitively inhibiting glucose uptake, a so-called nutritional shift-down. The new steady-state cell mass and volume were reached after 1 h, during which the rate of cell division was maintained; rearrangement of the linear dimensions (cell length, diameter), however, required an additional 2 h and caused an undershoot in cell length, consistent with the view that E. coli is slow to modify its diameter. The results are compared with the overshoot in cell length that occurs following nutritional shift-up.

Cell Division↗

PubMed1992

Aggregation of Escherichia coli B/r A during agar filtration: effect on morphometric measurements.

We have investigated the phenomenon of particle aggregation in a sample of 71,038 Escherichia coli B/r A cells in balanced exponential growth, during preparation for electron microscopy by agar filtration. The bacteria were photographed in a transmission electron microscope and the dimensions and spatial relationships among all the members of each aggregate were recorded using an interactive image processing system. The proportion of aggregated cells, 22%, is much greater than that found by direct count in a light microscope (7%), implying that most aggregation takes place during the preparation stages. The aggregated cells are about 1% narrower than the free cells, because of mutual compression, and 1.5% longer, because of a selection bias in favor of longer cells. From a statistical analysis of the data, we conclude that the clustering of cells into aggregates in the course of sample preparation is the result of random encounters during the settling on the collodion membrane and of the changing surface tension during the drying process. A method is proposed to correct morphometric measurements for the distortion caused by cellular aggregation of this kind.

Agar↗

PubMed1992

Relationship between size of parent at cell division and relative size of its progeny in Escherichia coli.

This article examines the empirical basis for the assumption of independence between the relative size (length or surface area) of a newborn cell w and the absolute size of its mother at cell division. Random samples from two strains of Escherichia coli B/r cells in steady-state exponential growth, covering a range of doubling times, were fixed in osmium tetroxide and prepared for electron microscopy by agar filtration. Length and diameter of over 3000 constricted cells were measured from the electron micrographs and cell surface area computed by assuming an idealized geometry of right circular cylinders with hemispherical polar caps. In general, these strains were found to divide into two daughter cells with a precision that is independent of the size of the mother. In addition, both a normal and a symmetrical beta-distribution were shown to fit the observed size distributions of w rather well; theoretical grounds for preferring the latter are discussed.

Cell Division↗

PubMed1990

Analysis of a model for minichromosome segregation in Escherichia coli.

The present article contains a theoretical, quantitative analysis of the implications of the Helmstetter-Leonard model (1987, J. molec. Biol. 197, 195-204.) for the segregation of chromosomal DNA in Escherichia coli, on the expected copy-number distribution of minichromosomes in a culture in steady-state exponential growth. According to the model, two determinants are involved in the mechanism of chromosome segregation: a partition system that assures the equal allotment of chromosomes between daughter cells at cell division, and a locus within the minimal oriC region that specifies the attachment site of the chromosomes to the cell envelope at initiation of replication. There are many parameters that must be taken into account in such a study, and since some of them are probabilistic in nature, a strictly analytical approach is not feasible and we had to resort to computer simulation. A wide range of parameter values was tested, in all combinations. The minichromosome copy-number distributions obtained all had a prominent mode equal to the number of oriC binding sites and their main features were determined essentially by that and very little by any of the other parameters of the model. In order to avoid the unrealistic situation in which this one feature completely dominates the results, the original model was modified so that each individual minichromosome is no longer required to replicate during every cell generation, by introducing a limit to the number of unsuccessful attempts to locate a suitable binding site. The copy-number distributions predicted by this version of the model are quantitatively and qualitatively very different and depend on all the components of the model. The simulation results are sufficiently well-behaved to allow consideration as to whether a particular empirical minichromosome copy-number distribution--when such data become available--could in fact be governed by the proposed model; it may even be possible to get a rough estimate for the different parameters involved.

Computer Simulation↗

PubMed1988

Surface-limited growth: a model for the synchronization of a growing bacterial culture through periodic starvation.

This article analyses the Surface-Limited Growth Model put forward to explain the very tight synchrony, over more than ten division cycles, obtained experimentally by subjecting a growing bacterial culture to alternating periods of starvation and dilution, using inorganic phosphate as the limiting substrate. The Model states that when an essential nutrient is in limited supply, the rate of growth of an individual cell will be proportional to its surface area (and the current concentration of the limiting substance) rather than to its volume. This decrease in dimensionality from volume to surface is expected to favor the smaller cells and so result ultimately in a narrower size distribution. The Surface-Limited Growth Model deals with cell growth under unusual nutritional conditions, and its predictions depend on how the cell replication cycle is assumed to behave under these same circumstances. Two alternatives are considered: the volume at which cells divide is the same during the starvation phase as during steady-state exponential growth, and the cells adjust immediately to the changing growth rate. In the latter case, we have tested both C + D constant with time and C + D variable (where C + D is the time between initiation of chromosome replication and the corresponding cell division), the incremental value at any instant being computed separately for each individual cell from its current effective growth rate. The simulation results are of two sorts depending on the auxiliary assumptions used. Either the dilution-starvation cycles have no effect whatsoever on the cell volume distribution, or the width of the distribution decreases gradually with time, approaching zero slowly and asymptotically, but the mean cell volume decreases as well--directly contradicting experimental observations. We conclude that the Surface-Limited Growth Model is incapable of explaining the synchronization of cells by periodic starvation of a growing bacterial culture.

Bacteria↗

PubMed1987

Predicted steady-state cell size distributions for various growth models.

The question of how an individual bacterial cell grows during its life cycle remains controversial. In 1962 Collins and Richmond derived a very general expression relating the size distributions of newborn, dividing and extant cells in steady-state growth and their growth rate; it represents the most powerful framework currently available for the analysis of bacterial growth kinetics. The Collins-Richmond equation is in effect a statement of the conservation of cell numbers for populations in steady-state exponential growth. It has usually been used to calculate the growth rate from a measured cell size distribution under various assumptions regarding the dividing and newborn cell distributions, but can also be applied in reverse--to compute the theoretical cell size distribution from a specified growth law. This has the advantage that it is not limited to models in which growth rate is a deterministic function of cell size, such as in simple exponential or linear growth, but permits evaluation of far more sophisticated hypotheses. Here we employed this reverse approach to obtain theoretical cell size distributions for two exponential and six linear growth models. The former differ as to whether there exists in each cell a minimal size that does not contribute to growth, the latter as to when the presumptive doubling of the growth rate takes place: in the linear age models, it is taken to occur at a particular cell age, at a fixed time prior to division, or at division itself; in the linear size models, the growth rate is considered to double with a constant probability from cell birth, with a constant probability but only after the cell has reached a minimal size, or after the minimal size has been attained but with a probability that increases linearly with cell size. Each model contains a small number of adjustable parameters but no assumptions other than that all cells obey the same growth law. In the present article, the various growth laws are described and rigorous mathematical expressions developed to predict the size distribution of extant cells in steady-state exponential growth; in the following paper, these predictions are tested against high-quality experimental data.

Bacteria↗

PubMed1987

Elongation and surface extension of individual cells of Escherichia coli B/r: comparison of theoretical and experimental size distributions.

The way individual cells grow and divide uniquely determines the (time-invariant) cell size distribution of populations in steady-state exponential growth. In the preceding article, theoretical distributions were derived for two exponential and six linear models containing a small number of adjustable parameters but no assumptions other than that all cells obey the same growth law. The linear models differ from each other with respect to the timing of the presumptive doubling in their growth rate, the exponential models--according to whether there is or is not a part of the cell that does not contribute to the growth rate. Here we compared the size distributions predicted by each of these models with those of cell length and surface area measured by electron microscopy; the quality of the fit, as determined by the mean-square successive-differences test and the chi 2 goodness-of-fit test, was taken as a measure of the adequacy of the model. The actual data came from two slow-growing E. coli B/r cultures, an A strain (pi = 125 min) and a K strain (pi = 106 min), and a correction was introduced in each to account for the distortion caused by the finite size of the picture frame. The parameter estimates produced by the various models are quite reliable (cv less than 0.1%); we discuss them briefly and compare their values in the two strains. All the length extension models were rejected outright whereas most of the surface growth versions were not. When the same models were tested on A-strain data from a faster growing culture (tau = 21 min), those models that provided an adequate fit to the cell surface area data proved equally satisfactory in the case of cell length. These findings are evaluated and shown to be consistent with cell surface area rather than cell length being the dimension under active control. Three surface area models, all linear, are rejected--those in which doubling of the growth rate occurs with a constant probability from cell birth, at a particular cell age, and precisely at cell division. The evidence in the literature that appears to contradict this last result, rejection of the simple linear surface growth model, is shown to be faulty. The 16 original models are here reduced to five, two involving exponential surface growth and three linear, and possible reasons are presented for our inability to discriminate further at this stage.

Cell Division↗

PubMed1987

Initiation of chromosome replication in bacteria: analysis of an inhibitor control model.

This article contains an analysis of a version of the well-known inhibitor-dilution model for the control of initiation of chromosome replication in bacteria. According to this model, an unstable inhibitor interacts with an initiation primer in a hit-and-destroy fashion to prevent successful initiation; both constituents are presumed to be RNA species that are synthesized constitutively. The model further postulates that the inhibitor interacts cooperatively with the primer, that the inhibitor gene is removed some distance from the origin of replication, and that an eclipse period exists during which the chromosome origin is not able to reinitiate. This unstable-inhibitor version is characterized by four parameters: the inhibitor half-life, the cooperativity index, the location of the inhibitor gene, and the eclipse period; computer simulations are used to study the effect of each of these on the DNA and interdivision time distributions in exponentially growing steady-state cultures. In neither case was any combination of parameter values found that could provide even moderately satisfactory agreement between the simulation results and experimental data. From the examples furnished and the associated discussion, it appears that there are none--that no combination of parameter values exists that can reasonably be expected to produce a significantly better fit than those tested. We conclude that the model in its present form cannot be a valid description of chromosome replication control in bacteria. It is pointed out that this does not necessarily apply to negative initiation control models in general, or even to all inhibitor-dilution systems, merely to the particular ColE1-like mechanism considered here. Nevertheless, recent experimental results, which can only be understood in terms of a very high degree of initiation synchrony within individual cells, offer strong evidence against stochastic models of this kind for the control of chromosome replication.

Bacteria↗