A study of oesophageal structure in a nematode, Aphelenchoides blastophthorus (Aphelenchida), using computer graphics reconstruction from serial thin sections

It can be difficult to visualize the shape and disposition of components in biological material from serial sections. They can be reconstructed by tracing outlines from sections onto an acetate sheet and stacking the sheets, but this method provides only a static model in which the elements cannot be manipulated or accurately measured. A more versatile method uses an interactive computer program. Data are entered via a digitizing tablet and the model may be displayed in any desired orientation and with any combination of elements presented. In this two-part paper we describe this technique and explain how it was used to elucidate the cellular composition of part of the feeding apparatus of a plant-infesting nematode. The oesophageal metacorpus of Aphelenchoides blastophthorus was found to consist of 43 cell bodies: 24 muscle, six epithelial and 13 nerve cells. The wide biological applicability of the technique is discussed and, in particular, its use in studying taxonomy and phylogeny of nematodes.     

Computer model for glucose-limited growth of a single cell of Escherichia coli B/r-A

A computer model is described which is capable of predicting changes in cell composition, cell size, cell shape, and the timing of chromosome synthesis in response to changes in external glucose limitation. The model is constructed primarily from information on unrestricted growth in glucose minimal medium. The ability of the model to make reasonable quantitative predictions under glucose-limitation is a test of the plausibility of the basic biochemical mechanisms included in the model. Such a model should be of use in differentiating among competing hypotheses for biological mechanisms and in suggesting as yet unobserved phenomena. The last two points are illustrated with the testing of a mechanism for the control of the initiation of DNA synthesis and predictions on cellwidth variations during the division cycle.     

Computer model for glucose-limited growth of a single cell of Escherichia coli B/r-A. Reprinted from Biotechnology and Bioengineering, Vol. 26, Issue 3, Pp 203-216 (1984)

A computer model is described which is capable of predicting changes in cell composition, cell size, cell shape, and the timing of chromosome synthesis in response to changes in external glucose limitation. The model is constructed primarily from information on unrestricted growth in glucose minimal medium. The ability of the model to make reasonable quantitative predictions under glucose-limitation is a test of the plausibility of the basic biochemical mechanisms included in the model. Such a model should be of use in differentiating among competing hypotheses for biological mechanisms and in suggesting as yet unobserved phenomena. The last two points are illustrated with the testing of a mechanism for the control of the initiation of DNA synthesis and predictions on cell-width variations during the division cycle.     

Clonal variation and aging of diploid fibroblasts : Cinematographic studies of cell pedigrees

Time-lapse cinematographic (TLC) analysis of clones of human diploid fibroblasts indicate heterogeneity in clonal division behaviour. Variations are noted in interdivision time, clone size and generations per clone. Correlation coefficients for interdivision times of sister pairs are high in young clones and generally low in aged clones. A consistent division pattern at all population doubling levels is one of low average interdivision time for early and late generations of a clone and high average interdivision time for the middle range of generations of a clone. The clonal division patterns observed experimentally have been duplicated in computer simulated pedigrees. The computer model is based on an oscillating system which allows for flux of regulator substances. The critical concentrations of regulator substances determine the clonal division pattern for a given progenitor cell.     

Computer simulation of compartment maintenance in the Drosophila wing imaginal disc

A new method for modelling cell division is reported which uses a cellular representation based on graph theory. This allows us to model the adjacencies of non-regular dividing cells accurately, avoiding the rigid geometrical constraints present in earlier simulations. We use this system to simulate compartment boundary maintenance in the Drosophila wing imaginal disc. We show that a boundary of minimum length between two growing polyclones of cells could depend on sorting between cells in the different polyclones. We also investigate the response of the model to differential cell division rates within polyclones. This is the first demonstration that cell sorting can generate a smooth boundary in a dividing cell mass. We suggest that biological analogs of our computer sorting rules are responsible for the similar straight polyclone borders seen in the real wing disc. A possible strategy for showing the existence of these analogs is also given.     

Validation of a computer software program for statistical analysis of accelerated stability studies on biological standards.

Long-term stability is an essential requirement for biological measurement standards and it has been evaluated by applying the Arrhenius model to the data obtained from accelerated thermostability studies. A computer program DEGTEST suited to a mainframe computer has been used for evaluating the stability of biological standards for more than a decade. This paper describes the validation of a computer program executable in a personal computer Microsoft Windows XP environment for the analysis of accelerated thermostability study data.     

Cell cycle dynamics inferred from the static properties of cells in balanced growth

The duration of a morphological phase of the cell cycle is reflected in the steady state distribution of the sizes of cells in that phase. Relationships presented here provide a method for estimating the timing and variability of any cell cycle phase. It is shown that the mean size of cells initiating and finishing any phase can be estimated from (1) the frequency of cells exhibiting the distinguishing morphological or autoradiographic features of the phase; (2) the mean size of cells in the phase; and (3) their coefficient of variation. The calculations are based on a submodel of the Koch-Schaechter Growth Controlled Model which assumes that (i) the distribution of division sizes is Gaussian; (ii) there is no correlation in division sizes between successive generations; and (iii) every cell division gives rise to two daughter cells of equal size. The calculations should be useful for a wider range of models, however, because the extrapolation factors are not sensitive to the chosen model. Criteria are proposed to allow the user to check the method's applicability for any experimental case. The method also provides a more efficient test of the dependence of growth on cell size than does the Collins-Richmond method. This is because the method uses the mean and coefficient of variation of the size of the total population, in conjunction with those of the cells in a final phase of the cell cycle, to test potential growth laws. For Escherichia coli populations studied by electron microscopy, an exponential growth model provided much better agreement than did a linear growth model. The computer simulations were used to generate rules for three types of cell phases: those that end at cell division, those that start at cell division, and those totally contained within a single cell cycle. For the last type, additional criteria are proposed to establish if the phase is well enough contained for the formulae and graphs to be used. The most useful rule emerging from these computer studies is that the fraction of the cell cycle time occupied by a phase is the product of the frequency of the phase and the ratio of the mean size of cells in that phase to the mean size of all cells in the population. A further advantage of the techniques presented here is that they use the 'extant' distributions that were actually measured, and not hypothesized distributions nor the special distributions needed for Collins-Richmond method that can only be calculated from the observed distributions of dividing or newborn cells on the basis of an assumed growth law.     

Monte Carlo simulation of malignant growth. Examples of the behavior of chloroleukemia after specific perturbations

This paper describes a stochastic model of cell population growth constructed to simulate biological reality in different experimental conditions. Using the computer program developed, the behavior of the cell population and of several experimentally measurable kinetic parameters was studied after specific perturbations, especially those involving sudden changes in the duration of the G₁ phase of the cell cycle (chalone action). It was demonstrated that mere prolongation of the G₁ phase can lead to tumor regression. The results also showed that it is sometimes difficult, if not impossible, intuitively to reach a correct interpretation of seemingly unequivocal biological data and, hence, that conclusions regarding cell population kinetics are hazardous without the aid of a rigorous model.     

A theory for developmental control by a program encoded in the genome

A new genetic mechanism is proposed to explain the evident order seen in embryonic development. This theory postulates control DNA, a set of genetic elements activated in a specific sequence, one at a time. With each cell division, control of gene expression passes to the next control unit in the series. The complete series of control units would constitute the encoded (and inherited) development program of an organism.     

Regulation of senescence by eukaryotic translation initiation factor 5A: implications for plant growth and development

Regulation of protein synthesis is increasingly being recognized as an important determinant of cell proliferation and senescence. In particular, recent evidence indicates that eukaryotic translation initiation factor 5A (eIF-A) plays a pivotal role in this determination. Separate isoforms of eIF-5A appear to facilitate the translation of mRNAs required for cell division and cell death. This raises the possibility that eIF-5A isoforms are elements of a biological switch that is in one position in dividing cells and in another position in dying cells. Changes in the position of this putative switch in response to physiological and environmental cues are likely to have a significant impact on plant growth and development.     

Emergent Stem Cell Homeostasis in the C.?elegans Germline Is Revealed by Hybrid Modeling

The establishment of homeostasis among cell growth, differentiation, and apoptosis is of key importance for organogenesis. Stem cells respond to temporally and spatially regulated signals by switching from mitotic proliferation to asymmetric cell division and differentiation. Executable computer models of signaling pathways can accurately reproduce a wide range of biological phenomena by reducing detailed chemical kinetics to a discrete, finite form. Moreover, coordinated cell movements and physical cell-cell interactions are required for the formation of three-dimensional structures that are the building blocks of organs. To capture all these aspects, we have developed a hybrid executable/physical model describing stem cell proliferation, differentiation, and homeostasis in the Caenorhabditis elegans germline. Using this hybrid model, we are able to track cell lineages and dynamic cell movements during germ cell differentiation. We further show how apoptosis regulates germ cell homeostasis in the gonad, and propose a role for intercellular pressure in developmental control. Finally, we use the model to demonstrate how an executable model can be developed from the hybrid system, identifying a mechanism that ensures invariance in fate patterns in the presence of instability.     

Universal rules for division plane selection in plants

Coordinated cell divisions and cell expansion are the key processes that command growth in all organisms. The orientation of cell divisions and the direction of cell expansion are critical for normal development. Symmetric divisions contribute to proliferation and growth, while asymmetric divisions initiate pattern formation and differentiation. In plants these processes are of particular importance since their cells are encased in cellulosic walls that determine their shape and lock their position within tissues and organs. Several recent studies have analyzed the relationship between cell shape and patterns of symmetric cell division in diverse organisms and employed biophysical and mathematical considerations to develop computer simulations that have allowed accurate prediction of cell division patterns. From these studies, a picture emerges that diverse biological systems follow simple universal rules of geometry to select their division planes and that the microtubule cytoskeleton takes a major part in sensing the geometric information and translates this information into a specific division outcome. In plant cells, the division plane is selected before mitosis, and spatial information of the division plane is preserved throughout division by the presence of reference molecules at a distinct region of the plasma membrane, the cortical division zone. The recruitment of these division zone markers occurs multiple times by several mechanisms, suggesting that the cortical division zone is a highly dynamic region.     

Proliferation controls in a linear growth system: theoretical studies of cell division in the cartilage growth plate

The columnar arrangement of dividing cells in the epiphyseal cartilage plates of growing bones provides a model of a linear proliferation system. One factor which determines the rate of cell production, and hence the rate of growth, is the size of the proliferating population. In this one dimensional system this size is equal to the length of the proliferation zone. Two possible mechanisms for a differentiation control that sets a limit to the length of this zone have been tested in computer simulations. While a diffusion gradient control is consistent with cell kinetic measurements a division limit based on an inheritable growth substance is shown to require further development before the model fits experimental data.Cell division in the columns produces linear clones of cells. If the final length of a bone is set by a limit on the number of divisions that the cartilage stem cells can make, then the number of cells per clone is crucial in determining overall bone growth. The parameters that affect linear clone size have been investigated in computer simulations. Clone size depends largely on the relative division rate of stem cells to proliferation zone cells — but the data on stem cell division rates are generally unreliable.The analysis could be applied to other linear proliferating systems.     

Fractal geometry of mosaic pattern demonstrates liver regeneration is a self-similar process.

Partial hepatectomy causes compensatory, nonneoplastic growth and regeneration in mammalian liver. Compensatory liver growth can be used to examine aspects of patterns of cell division in regenerating tissue. Chimeric animals provide markers of cell lineage which are independent of growth and can be used to follow cell division patterns. Previous experimental evidence suggests that compensatory liver growth is uniform, without focal centers of proliferation. In this study we have extended that observation to include genes important in regeneration and cell cycle control in order to establish that nascent growth centers are not present in regenerating liver. There is a uniform spatial distribution of expression of these genes which is not related to mosaic pattern in the chimeras. While these genes may help regulate hepatocyte proliferation they do not appear to regulate patch pattern in the chimeras. With this information confirming uniform growth it was possible to use fractal analysis to test various hypothesized patterns of regenerative growth in the liver. The results of this analysis indicate that mosaic pattern does not change substantially during the regenerative process. Patch area and perimeter (the area occupied by or perimeter around cells of like lineage) increase during compensatory liver growth in chimeric rats without alteration of the geometric complexity of patch boundaries (boundaries around cells of like lineage). These tissue findings are consistent with previously reported computer models of growth in which repetitive application of simple decisions assuming uniform growth created complex mosaic patterns. They support the notion that an iterating (repeating), self-similar (a pattern in which parts are representative of, but not identical to the whole) cell division program is sufficient for the regeneration of liver tissue following partial hepatectomy. Iterating, self-similar cell division programs are important because they suggest a way in which complex patterns (or morphogenesis) can be efficiently created from a small amount of stored information.     

Constrained indicator species analysis (COINSPAN): an extension of TWINSPAN

Abstract. A new vegetation classification method, COnstrained-INdicator-SPecies-ANalysis (COINSPAN) is introduced as an elaboration of Two-Way-INdicator-SPecies-ANalysis (TWINSPAN). Instead of operating on the bisection of a primary Correspondence Analysis ordination axis, at each level of division, COINSPAN bisects a primary Canonical Correspondence Analysis axis. The associated computer program, of the same name, performs both analyses as options. COINSPAN is applied to a simple model data set, with two constraining gradients, and to a pine forest vegetation survey in order to illustrate the functioning and utility of the method.     

A stochastic model to analyze clonal data on multi-type cell populations

This article presents a stochastic model designed to analyze experimental data on the development of cell clones composed of two (or more) distinct types of cells. The proposed model is an extension of the traditional multi-type Bellman-Harris branching stochastic process allowing for nonidentical time-to-transformation distributions defined for different cell types. A simulated pseudo likelihood method has been developed for the parametric statistical inference from experimental data on cell clones under the proposed model. The method uses simulation-based approximations of the means and the variance-covariance matrices of cell counts. The proposed estimator for the vector of unknown parameters is strongly consistent and asymptotically normal under mild regularity conditions, while its variance-covariance matrix is estimated by the parametric bootstrap. A Monte Carlo Wald test is proposed for the test of hypotheses. Finite sample properties of the estimator have been studied by computer simulations. The model and associated methods of parametric inference have been applied to the analysis of proliferation and differentiation of cultured O-2A progenitor cells that play a key role in the development of the central nervous system. It follows from this analysis that the time to division of the progenitor cell and the time to its differentiation (into an oligodendrocyte) are not identically distributed. This biological finding suggests that a molecular event determining the type of cell transformation is more likely to occur at the start rather than at the end of the mitotic cycle.     

Regulation of retrotransposition in Saccharomyces cerevisiae

Retrotransposons are a widely distributed group of eukaryotic mobile genetic elements that transpose through an RNA intermediate. The element Ty (Transposon yeast), found in the yeast Saccharomyces cerevisiae, is a model system for the study of retrotransposons because of the experimental tools that exist to manipulate and detect transposition. Ty transposition can be elevated to levels exceeding one transposition event per cell when an element is expressed from an inducible yeast promoter. In addition, individual genomic Ty elements can be tagged with a retrotransposition indicator gene that allows transposition events occurring at a rate of 10(-5) to 10(-7) per element per cell division to be detected phenotypically. These systems are being used to elucidate the mechanism of Ty transposition and clarify how Ty transposition is controlled.     

Requirement of a cell division step for stalk formation in Caulobacter crescentus.

Penicillin G at low concentrations blocked cell division in Caulobacter crescentus without inhibiting cell growth. The long filamentous cells formed after two to three generations under these conditions had a stalk at one pole and usually one or more flagella at the opposite pole. The failure of the filaments to form a second stalk at the flagellated pole indicates that stalk formation was dependent upon completion of a step that was also required for cell division. Two observations support this conclusion. (i) Penicillin did not stop the normal development of synchronous swarmer cells into stalked initiation and stalk elongation. (ii) When the action of penicillin was reversed by the addition of penicillinase to cultures of filaments, stalks were not formed at the nonstalked pole until after cell division had occurred; thus the normal order of development events was maintained: cell division leads to stalk formation. These results are consistent with a model in which the organization of the developmental program for stalk formation occurs before cell division as a consequence of steps that branch from the cell division pathway.     

Stochastic computer model of the cell microtubule dynamics

To study the effect of various factors on the microtubule system, one of the main cytoskeletal elements in the cell, which organizes the intracellular transport of different organelles and is necessary for mitosis and meiosis, a computer model of this system is created. Using a stochastic approach, the model describes the microtubule assembly/disassembly as a set of chemical reactions with certain rate constants. Microtubules are visualized in the computer program field, which makes the model vivid. The program imitates the dynamics and structure of the microtubule system with high reliability. The parameters calculated by the model correlate with the corresponding parameters of microtubules in living cells. This approach to modeling microtubules and similar systems continues to be developed so that the models would better describe living systems and the effect of a still broader range of factors could be studied.