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Along with a strict determinism of early embryogenesis in most living organisms, some of them exhibit variability of cell fates and developmental pathways. Here we discuss the phenomena of determinism and variability of developmental pathways, defining its dependence upon cell potency, cell sensitivity to the external signals and cell signaling. We propose a set of conjectures on the phenomenon of variability of developmental pathways, and denote a difference between a normal (local) variability, leading to an invariant final structure (e.g., embryo shape), and fundamental one, which is a switching between different developmental pathways, leading to different possible structures. For illustrating our conjectures, we analyzed early developmental stages of plant embryos with different levels of variability of morphogenesis pathways, and provide a set of computational experiments by Morphogenesis Software.

The notions of positional information and positional value describe the role of cell position in cell development and pattern formation. Despite their frequent usage in literature, their definitions are blurry, and are interpreted differently by different researchers. Through reflection on previous definitions and usage, and analysis of related experiments, we propose three clear and verifiable criteria for positional information/value. Then we reviewed literature on molecular mechanisms of cell development and pattern formation, to search for a possible molecular basis of positional information/value, including those used in theoretical models. We conclude that although morphogen gradients and cell-to-cell contacts are involved in the pattern formation process, complete molecular explanations of positional information/value are still far from reality.

We review studies on tissue transplantation experiments for various species: one piece of the donor tissue is excised and transplanted into a slit in the host tissue, then observe the behavior of this grafted tissue. Although we have known the results of some transplantation experiments, there are many more possible experiments with unknown results. We develop a penalty function-based method that uses the known experimental results to infer the unknown experimental results. Similar experiments without similar results get penalized and correspond to smaller probability. This method can provide the most probable results of a group of experiments or the probability of a specific result for each experiment. This method is also generalized to other situations. Besides, we solve a problem: how to design experiments so that such a method can be applied most efficiently.

In most taxa of plant and animal kingdoms the initial steps of embryogenesis and the final morphology of an organism are strongly determined. However, these two phenomena do not correlate from phylogenetic point of view, namely, different unrelated taxa can have the same type of early embryogenesis, while there can be different types of cleavage inside one taxon. Here we discuss an approach enabling giving an insight into the understanding of this phenomenon. First, we propose a strategy for constructing developmental graphs (trees) that provide mathematical formalization of a process of embryogenesis. Second, we suggested an algorithm of trees comparison, developed specifically for this type of labeled graphs, which allows calculating a distance between two developmental trees, and thus clustering them into groups. Next we performed the analysis of correspondence between the obtained clusters and the inception of morphological characters in given clustered groups of organisms, which allows describing several particular cases of interrelation between developmental trends and formation of morphological structures. Here we present some illustrations of the suggested methodology on the analysis of plant angiosperm species belonging to different taxa of various ranks.

We build a theoretical model of morphogenesis. This model describes cell fate in the developing organism using the notion of epigenetic code of each cell. Namely, given the epigenetic spectra of a cell and its neighboring cells, we can determine the corresponding cell event it will perform. This means that the properties of a group of cells (comprising an embryo or its part) at any time point are also known, and thus, the evolution of an embryo can be described. By this strategy, it is possible to establish the tissue, organ, or embryo shapes at any time, starting from a zygote. As an essential part of the model, the formalization of the notion of cell potency is introduced, and the related properties are discussed.

The process of morphogenesis is an evolution of shape of an organism together with the differentiation of its parts. This process encompasses numerous biological processes ranging from embryogenesis to regeneration following crisis such as amputation or transplantation. A fundamental theoretical question is where exactly do these instructions for (re-)construction reside and how are they implemented? We have recently proposed a set of concepts, aiming to respond to these questions and to provide an appropriate mathematical formalization of the geometry of morphogenesis [1]. First, we consider a possibility that the evolution of shape is determined by epigenetic information, responsible for realization of different types of cell events. Second, we suggest a set of rules for converting this epigenetic information into instructive signals for cell event for each cell, as well as for transforming it after each cell event. Next we give notions of cell state, determined by its epigenetic array, and cell event, which is a change of cell state, and formalize development as a graph (tree) of cell states connected by 5 types of cell events, corresponding to the processes of cell division, cell growth, cell death, cell movement and cell differentiation. Here we present a Morphogenesis software capable to simulate an evolution of a 3D embryo starting from zygote, following a set of rules, based on our theoretical assumptions, and thus to provide a proof-of-concept of the hypothesis of epigenetic code regulation. The software creates a developing embryo and a corresponding graph of cell events according to the zygotic epigenetic spectrum and chosen parameters of the developmental rules. Variation of rules influencing the resulting shape of an embryo may help elucidating the principal laws underlying pattern formation., SCOPUS: ar.j, info:eu-repo/semantics/published

Cancer Stem Cells (CSC), a subset of cancer cells resembling normal stem cells with self-renewal and asymmetric division capabilities, are present at various but low proportions in many tumors and are thought to be responsible for tumor relapses following conventional cancer therapies. In vitro, most intriguingly, when isolated, CSCs return to their original proportion level as shown by various investigators. This phenomenon still remains to be explained.We suggest a mathematical model of cancer cell population dynamics, based on the main parameters of cell population dynamics, including the proliferation rates, the rates of cell death and the frequency of symmetric and asymmetric cell divisions both in CSCs and in non-CSCs. This model should help elucidating some important factors underlying the dynamics of the two populations, first of all, the phenomena of cancer stem cell population stabilization.Author SummaryCancer Stem Cells (CSC) present a subset of cancer cells which is thought to be responsible for tumor growth. That is why CSC are also named “tumor initiation cells”. Additionally, it was shown that CSC are resistant to chemo- and radio-therapies which suggests that these cells can be responsible for tumor relapses after these treatments. Experimental data in cancer cell lines have shown the intriguing phenomena of CSC population stability, which means that isolated CSC population rapidly stabilizes at its characteristic level (the relative proportion of CSC in a whole cancer population). We suggest a mathematical model of cancer cell population dynamics, based on experimentally measured dynamics of CSC population stabilization and including main parameters of cell population growth.We have computationally predicted probability of different scenarios of cancer cell behavior for each experimental case with measurable growth parameters. Moreover, we provide an analytical tool for elucidating important biochemical factors responsible for a particular dynamics of CSC population.The results may have important implications in therapeutic, because the destroying of a set of factors underlying CSC stability may help to avoid tumor relapses.

A model of morphogenesis is proposed based on seven explicit postulates. The mathematical import and biological significance of the postulates are explored and discussed.

Functional genomics employs several experimental techniques to investigate gene functions. These techniques such as loss-of-function screening and transcriptome profiling performed in a high-throughput manner give as result a list of genes involved in the biological process of interest. There exist several computational methods for analysis and interpretation of the list. The most widespread methods aim at investigation of biological processes significantly represented in the list or at extracting significantly represented subnetworks. Here we present a new exploratory network analysis method that employs the shortest path approach and centrality measure to uncover members of active molecular pathways leading to the studied phenotype based on the results of functional genomics screening data. We present the method and we demonstrate what data can be retrieved by its application to the terminal muscle differentiation miRNA loss-of-function screening and transcriptomic profiling data and to the ‘druggable’ loss-of-function RNAi screening data of the DNA repair process.

A network is one of the most convenient way to represent interactions between biological entities in systems biology. A network of molecular interactions is a graph in which the vertices are biological component and the edges correspond to the interactions between them. Many notions and approaches for network analysis came to systems biology from the theory of graphs – a field of mathematics that study graphs. We focused on the study of the shortest path approach in this work. We investigated whether this approach yields valid molecular paths. To perform this, the shortest paths in the human interactome (derived from HPRD and HIPPIE databases) were found between all relevant combinations of proteins taken from eight well-studied highly conserved signaling pathways from the KEGG database (NF-kappa B, MAPK, Jak-STAT, mTOR, ErbB, Wnt, TGF-beta and the signaling part of the apoptotic process). Canonical paths were systematically compared with the shortest counterparts and centrality of vertices and paths in subnetworks induced by the shortest paths were analyzed. We found that the sets of the shortest paths contain the canonical counterparts only for very short canonical paths (length 2-3 interactions). We also found that high centrality vertices tend to belong to canonical counterparts, to less extent this can also be said about high centrality paths.

International audience; CNOT6L is a deadenylase subunit belonging to the CCR4-NOT complex, a major deadenylase complex in eukaryotes involved at multiple levels in regulation of gene expression. While CNOT6L is expressed in skeletal muscle cells, its specific functions in this tissue are still largely unknown. Our previous work highlighted the functional of CNOT6L in skeletal muscle cell differentiation. To further explore how CNOT6L regulates myogenesis, we used here gene expression analysis to identify CNOT6L mRNA targets in human myoblasts. Among these novel targets, IL-8 (interleukin 8) mRNA was the most upregulated in CNOT6L knock-down (KD) cells. Biochemical approaches and poly (A) tail length assays showed that IL-8 mRNA is a direct target of CNOT6L, and further investigations by loss- and gain-of-function assays pointed out that IL-8 is an important effector of myogenesis. Therefore, we have characterized CNOT6L-IL-8 as a new signaling axis that regulates myogenesis.

Many cancer-associated genes and pathways remain to be identified in order to clarify the molecular mechanisms underlying cancer progression. In this area, genome-wide loss-of-function screens appear to be powerful biological tools, allowing the accumulation of large amounts of data. However, this approach currently lacks analytical tools to exploit the data with maximum efficiency, for which systems biology methods analyzing complex cellular networks may be extremely helpful. In this article we report such a systems biology strategy based on the construction of a Network for a biological process and specific for a given cell system (cell type). The networks are created from genome-wide loss-of-function screen datasets. We also propose tools to analyze network properties. As one of the tools, we suggest a mathematical model for discrimination between two distinct cell processes that may be affected by knocking down the activity of a gene, i. e., a decreased cell number may be caused by arrested cell proliferation or enhanced cell death. Next we show how this discrimination between the two cell processes helps to construct two corresponding subnetworks. Finally, we demonstrate an application of the proposed strategy to the identification and characterization of putative novel genes and pathways significant for the control of lung cancer cell growth, based on the results of a genome-wide proliferation/viability loss-of-function screen of human lung adenocarcinoma cells.

Recent discovery of cancer stem cells in tumorigenic tissues has raised many questions about their nature, origin, function and their behavior in cell culture. Most of current experiments reporting a dynamics of cancer stem cell populations in culture show the eventual stability of the percentages of these cell populations in the whole population of cancer cells, independently of the starting conditions. In this paper we propose a mathematical model of cancer stem cell population behavior, based on specific features of cancer stem cell divisions and including, as a mathematical formalization of cell-cell communications, an underlying field concept. We compare the qualitative behavior of mathematical models of stem cells evolution, without and with an underlying signal. In absence of an underlying field, we propose a mathematical model described by a system of ordinary differential equations, while in presence of an underlying field it is described by a system of delay differential equations, by admitting a delayed signal originated by existing cells. Under realistic assumptions on the parameters, in both cases (ODE without underlying field, and DDE with underlying field) we show in particular the stability of percentages, provided that the delay is sufficiently small. Further, for the DDE case (in presence of an underlying field) we show the possible existence of, either damped or standing, oscillations in the cell populations, in agreement with some existing mathematical literature. The outcomes of the analysis may offer to experimentalists a tool for addressing the issue regarding the possible non-stem to stem cells transition, by determining conditions under which the stability of cancer stem cells population can be obtained only in the case in which such transition can occur. Further, the provided description of the variable corresponding to an underlying field may stimulate further experiments for elucidating the nature of “instructive" signals for cell divisions, underlying a proper pattern of the biological system.

One of the most intriguing questions in life science is how living organisms develop and maintain their predominant form and shape via the cascade of the processes of differentiation starting from the single cell. Mathematical modeling of these developmental processes could be a very important tool to properly describe the complex processes of evolution and geometry of mor- phogenesis in time and space. Here, we summarize the most important biological knowledge on plant development, exploring the different layers of investigation in developmental processes such as plant morphology, genetics, plant physiology, molecular biology and epigenetics. As knowledge on the fundamentals of plant embryogenesis, growth and development is constantly improving, we gather here the latest data on genetic, molecular and hormonal regulation of plant development to- gether with the basic background knowledge. Special emphasis is placed on the regulation of cell cycle progression, on the role of the signal molecules phytohormones in plant development and on the details of plant meristems (loci containing plant stem cells) function. We also explore several proposed biological models regarding regulating plant development. The information presented here could be used as a basis for mathematical modeling and computer simulation of developmen- tal processes in plants.

A major determinant of plant architecture is the arrangement of branches around the stem, known as phyllotaxis. However, the specific form of branching conditions is not known. Here we discuss this question and suggest a branching model which seems to be in agreement with biological observations.Recently, a number of models connected with the genetic network or molecular biology regulation of the processes of pattern formation appeared. Most of these models consider the plant hormone, auxin, transport and distribution in the apical meristem as the main factors for pattern formation and phyllotaxis. However, all these models do not take into consideration the whole plant morphogenesis, concentrating on the events in the shoot or root apex. On the other hand, other approaches for modeling phyllotaxis, where the whole plant is considered, usually are mostly phenomenological, and due to it, do not describe the details of plant growth and branching mechanism. In this work, we develop a mathematical model and study pattern formation of the whole, though simplified, plant organism where the main physiological factors of plant growth and development are taken into consideration. We model a growing plant as a system of intervals, which we will consider as branches. We assume that the number and location of the branches are not given a priori, but appear and grow according to certain rules, elucidated by the application of mathematical modeling. Four variables are included in our model: concentrations of the plant hormones auxin and cytokinin, proliferation and growth factor, and nutrients-we observe a wide variety of plant forms and study more specifically the involvement of each variable in the branching process. Analysis of the numerical simulations shows that the process of pattern formation in plants depends on the interaction of all these variables. While concentrations of auxin and cytokinin determine the appearance of a new bud, its growth is determined by the concentrations of nutrients and proliferation factors. Possible mechanisms of apical domination in the frame of our model are discussed.

The conserved modular complex TRAPP is a guanine nucleotide exchanger (GEF) for the yeast Golgi Ypt-GTPase gatekeepers. TRAPP I and TRAPP II share seven subunits and act as GEFs for Ypt1 and Ypt31/32, respectively, which in turn regulate transport into and out of the Golgi. Trs65/Kre11 is one of three TRAPP II-specific subunits. Unlike the other two subunits, Trs120 and Trs130, Trs65 is not essential for viability, is conserved only among some fungi, and its contribution to TRAPP II function is unclear. Here, we provide genetic, biochemical, and cellular evidence for the role of Trs65 in TRAPP II function. First, like Trs130, Trs65 localizes to the trans-Golgi. Second, TRS65 interacts genetically with TRS120 and TRS130. Third, Trs65 interacts physically with Trs120 and Trs130. Finally, trs65 mutant cells have low levels of Trs130 protein, and they are defective in the GEF activity of TRAPP II and the intracellular distribution of Ypt1 and Ypt31/32. Together, these results show that Trs65 plays a role in the Ypt GEF activity of TRAPP II in concert with the two other TRAPP II-specific subunits. Elucidation of the role played by Trs65 in intracellular trafficking is important for understanding how this process is coordinated with two other processes in which Trs65 is implicated: cell wall biogenesis and stress response.

Selenocysteine incorporation in eukaryotes occurs cotranslationally at UGA codons via the interactions of RNA-protein complexes, one comprised of selenocysteyl (Sec)-tRNA([Ser]Sec) and its specific elongation factor, EFsec, and another consisting of the SECIS element and SECIS binding protein, SBP2. Other factors implicated in this pathway include two selenophosphate synthetases, SPS1 and SPS2, ribosomal protein L30, and two factors identified as binding tRNA([Ser]Sec), termed soluble liver antigen/liver protein (SLA/LP) and SECp43. We report that SLA/LP and SPS1 interact in vitro and in vivo and that SECp43 cotransfection increases this interaction and redistributes all three proteins to a predominantly nuclear localization. We further show that SECp43 interacts with the selenocysteyl-tRNA([Ser]Sec)-EFsec complex in vitro, and SECp43 coexpression promotes interaction between EFsec and SBP2 in vivo. Additionally, SECp43 increases selenocysteine incorporation and selenoprotein mRNA levels, the latter presumably due to circumvention of nonsense-mediated decay. Thus, SECp43 emerges as a key player in orchestrating the interactions and localization of the other factors involved in selenoprotein biosynthesis. Finally, our studies delineating the multiple, coordinated protein-nucleic acid interactions between SECp43 and the previously described selenoprotein cotranslational factors resulted in a model of selenocysteine biosynthesis and incorporation dependent upon both cytoplasmic and nuclear supramolecular complexes.

Background : Insects appear to have diverged from both higher and lower organisms in their defense mechanisms against oxidative damage. They do not encode glutathione peroxidases or glutathione reductases, and their thioredoxin reductases exhibit distinct properties from those of higher and lower species. Nonetheless, appropriate balance of antioxidants and pro-oxidants, and protection from damaging reactive oxygen species are clearly crucial in insects for viability, normal functioning of signalling pathways and morphogenesis, and have been implicated in studies on longevity in flies and other organisms. We have used RNAi in D. melanogaster embryos and in Schneider S2 cells to inhibit expression of these proteins. We report that inhibition of either dselH or dselK expression significantly reduces viability in embryos. We further show that dselH silencing decreases total anti-oxidant capacity in embryos and Schneider cells, and increases lipid peroxidation in cells. Conversely, transient expression of dselH in the cell line decreases lipid peroxidation, and reverses the toxic effects of a glutathione-depleting drug. The latter correlates with sparing of glutathione levels.

The remarkable regeneration capacity of plant cells is based on their capability to dedifferentiate. We recently reported that cellular dedifferentiation proceeds through two distinct phases, each accompanied by chromatin decondensation: acquisition of competence for fate switch followed by a signal-dependent reentry into S phase. The purpose of this study was to (1) characterize changes in chromatin factors associated with chromatin decondensation, and (2) study the relationship between chromatin decondensation and transcriptional activation of pRb/E2F-regulated genes. We show that plant cells competent for fate switch display a disruption of nucleolar domain appearance associated with condensation of 18S ribosomal DNA, as well as modifications of histone H3 and redistribution of heterochromatin protein 1 (HP1). We further show that the pRb/E2F-target genes RNR2 and PCNA are condensed and silent in differentiated leaf cells but become decondensed, although not yet activated, as cells acquire competence for fate switch; transcriptional activation becomes evident during progression into S phase, concomitantly with pRb phosphorylation. We propose that chromatin reorganization is central for reversion of the differentiation process leading to resetting of the gene expression program and activation of silent genes.

This paper is devoted to computer modelling of the development and regeneration of multicellular biological structures. Some species (e.g., planaria and salamanders) are able to regenerate parts of their body after amputation damage, but the global rules governing cooperative cell behaviour during morphogenesis are not known. Here, we consider a simplified model organism, which consists of tissues formed around special cells that can be interpreted as stem cells. We assume that stem cells communicate with each other by a set of signals, and that the values of these signals depend on the distance between cells. Thus the signal distribution characterizes location of stem cells. If the signal distribution is changed, then the difference between the initial and the current signal distribution affects the behaviour of stem cells – e.g. as a result of an amputation of a part of tissue the signal distribution changes which stimulates stem cells to migrate to new locations, appropriate for regeneration of the proper pattern. Moreover, as stem cells divide and form tissues around them, they control the form and the size of regenerating tissues. This two-level organization of the model organism, with global regulation of stem cells and local regulation of tissues, allows its reproducible development and regeneration.

Cellular dedifferentiation is the major process underlying totipotency, regeneration, and formation of new stem cell lineages in multicellular organisms. In animals it is often associated with carcinogenesis. Here, we used tobacco protoplasts (plant cells devoid of cell wall) to study changes in chromatin structure in the course of dedifferentiation of mesophyll cells. Using flow cytometry and micrococcal nuclease analyses, we identified two phases of chromatin decondensation prior to entry of cells into S phase. The first phase takes place in the course of protoplast isolation, following treatment with cell wall degrading enzymes, whereas the second occurs only after protoplasts are induced with phytohormones to re-enter the cell cycle. In the absence of hormonal application, protoplasts undergo cycles of chromatin condensation/decondensation and die. The ubiquitin proteolytic system was found indispensable for protoplast progression into S phase, being required for the second but not the first phase of chromatin decondensation. The emerging model suggests that cellular dedifferentiation proceeds by two functionally distinct phases of chromatin decondensation: the first is a transitory phase that confers competence for cell fate switch, which is followed, under appropriate conditions, by a second proteasome-dependent phase representing a commitment for the mitotic cycle. These findings might have implications for a wide range of dedifferentiation-driven cellular processes in higher eukaryotes.

We introduce a formalism for the geometry of eukaryotic cells and organisms.Cells are taken to be star-convex with good biological reason. This allows for a convenient description of their extent in space as well as all manner of cell surface gradients. We assume that a spectrum of such cell surface markers determines an epigenetic code for organism shape. The union of cells in space at a moment in time is by definition the organism taken as a metric subspace of Euclidean space, which can be further equipped with an arbitrary measure. Each cell determines a point in space thus assigning a finite configuration of distinct points in space to an organism, and a bundle over this configuration space is introduced with fiber a Hilbert space recording specific epigenetic data. On this bundle, a Lagrangian formulation of morphogenetic dynamics is proposed based on Gromov-Hausdorff distance which at once describes both embryo development and regenerative growth.

MiRNAs impact on the control of cell fate by regulating gene expression at the post-transcriptional level. Here, using mammalian muscle differentiation as a model and a phenotypic loss-of-function screen, we explored the function of miRNAs at the genome-wide level. We found that the depletion of a high number of miRNAs (63) impacted on differentiation of human muscle precursors, underscoring the importance of this post-transcriptional mechanism of gene regulation. Interestingly, a comparison with miRNA expression profiles revealed that most of the hit miRNAs did not show any significant variations of expression during differentiation. These constitutively expressed miRNAs might be required for basic and/or essential cell function, or else might be regulated at the post-transcriptional level. MiRNA inhibition yielded a variety of phenotypes, reflecting the widespread miRNA involvement in differentiation. Using a functional screen (the STarS - Suppressor Target Screen – approach, i. e. concomitant knockdown of miRNAs and of candidate target proteins), we discovered miRNA protein targets that are previously uncharacterized controllers of muscle-cell terminal differentiation. Our results provide a strategy for functional annotation of the human miRnome.

MicroRNAs can affect the protein translation using nine mechanistically different mechanisms, including repression of initiation and degradation of the transcript. There is a hot debate in the current literature about which mechanism and in which situations has a dominant role in living cells. The worst, same experimental systems dealing with the same pairs of mRNA and miRNA can provide ambiguous evidences about which is the actual mechanism of translation repression observed in the experiment. We start with reviewing the current knowledge of various mechanisms of miRNA action and suggest that mathematical modeling can help resolving some of the controversial interpretations. We describe three simple mathematical models of miRNA translation that can be used as tools in interpreting the experimental data on the dynamics of protein synthesis. The most complex model developed by us includes all known mechanisms of miRNA action. It allowed us to study possible dynamical patterns corresponding to different miRNA-mediated mechanisms of translation repression and to suggest concrete recipes on determining the dominant mechanism of miRNA action in the form of kinetic signatures. Using computational experiments and systematizing existing evidences from the literature, we justify a hypothesis about co-existence of distinct miRNA-mediated mechanisms of translation repression. The actually observed mechanism will be that acting on or changing the sensitive parameters of the translation process. The limiting place can vary from one experimental setting to another. This model explains the majority of existing controversies reported.

MicroRNAs can affect the protein translation using nine mechanistically different mechanisms, including repression of initiation and degradation of the transcript. There is a hot debate in the current literature about which mechanism and in which situations has a dominant role in living cells. The worst, same experimental systems dealing with the same pairs of mRNA and miRNA can provide ambiguous evidences about which is the actual mechanism of translation repression observed in the experiment. We start with reviewing the current knowledge of various mechanisms of miRNA action and suggest that mathematical modeling can help resolving some of the controversial interpretations. We describe three simple mathematical models of miRNA translation that can be used as tools in interpreting the experimental data on the dynamics of protein synthesis. The most complex model developed by us includes all known mechanisms of miRNA action. It allowed us to study possible dynamical patterns corresponding to different miRNA-mediated mechanisms of translation repression and to suggest concrete recipes on determining the dominant mechanism of miRNA action in the form of kinetic signatures. Using computational experiments and systematizing existing evidences from the literature, we justify a hypothesis about co-existence of distinct miRNA-mediated mechanisms of translation repression. The actually observed mechanism will be that acting on or changing the limiting "place" of the translation process. The limiting place can vary from one experimental setting to another. This model explains the majority of existing controversies reported.

International audience; Argonaute proteins play a major part in transcriptional gene silencing in many organisms, but their role in the nucleus of somatic mammalian cells remains elusive. Here, we have immunopurified human Argonaute-1 and Argonaute-2 (AGO1 and AGO2) chromatin-embedded proteins and found them associated with chromatin modifiers and, notably, with splicing factors. Using the CD44 gene as a model, we show that AGO1 and AGO2 facilitate spliceosome recruitment and modulate RNA polymerase II elongation rate, thereby affecting alternative splicing. Proper AGO1 and AGO2 recruitment to CD44 transcribed regions required the endonuclease Dicer and the chromobox protein HP1γ, and resulted in increased histone H3 lysine 9 methylation on variant exons. Our data thus uncover a new model for the regulation of alternative splicing, in which Argonaute proteins couple RNA polymerase II elongation to chromatin modification.

MicroRNAs (miRNAs) are key regulators of all important biological processes, including development, differentiation, and cancer. Although remarkable progress has been made in deciphering the mechanisms used by miRNAs to regulate translation, many contradictory findings have been published that stimulate active debate in this field. Here we contribute to this discussion in three ways. First, based on a comprehensive analysis of the existing literature, we hypothesize a model in which all proposed mechanisms of microRNA action coexist, and where the apparent mechanism that is detected in a given experiment is determined by the relative values of the intrinsic characteristics of the target mRNAs and associated biological processes. Among several coexisting miRNA mechanisms, the one that will effectively be measurable is that which acts on or changes the sensitive parameters of the translation process. Second, we have created a mathematical model that combines nine known mechanisms of miRNA action and estimated the model parameters from the literature. Third, based on the mathematical modeling, we have developed a computational tool for discriminating among different possible individual mechanisms of miRNA action based on translation kinetics data that can be experimentally measured (kinetic signatures). To confirm the discriminatory power of these kinetic signatures and to test our hypothesis, we have performed several computational experiments with the model in which we simulated the coexistence of several miRNA action mechanisms in the context of variable parameter values of the translation.

The process of morphogenesis, which can be defined as an evolution of the form of an organism, is one of the most intriguing mysteries in the life sciences. The discovery and description of the spatial–temporal distribution of the gene expression pattern during morphogenesis, together with its key regulators, is one of the main recent achievements in developmental biology. Nevertheless, gene expression patterns cannot explain the development of the precise geometry of an organism and its parts in space. Here, we suggest a set of postulates and possible approaches for discovering the correspondence between molecular biological information and its realization in a given geometry of an organism in space–time.

Protein synthesis is one of the most fundamental biological processes, which consumes a significant amount of cellular resources. Despite existence of multiple mathematical models of translation, varying in the level of mechanistical details, surprisingly, there is no basic and simple chemical kinetic model of this process, derived directly from the detailed kinetic model. One of the reasons for this is that the translation process is characterized by indefinite number of states, thanks to existence of polysomes. We bypass this difficulty by applying a trick consisting in lumping multiple states of translated mRNA into few dynamical variables and by introducing a variable describing the pool of translating ribosomes. The simplest model can be solved analytically under some assumptions. The basic and simple model can be extended, if necessary, to take into account various phenomena such as the interaction between translating ribosomes, limited amount of ribosomal units or regulation of translation by microRNA. The model can be used as a building block (translation module) for more complex models of cellular processes. We demonstrate the utility of the model in two examples. First, we determine the critical parameters of the single protein synthesis for the case when the ribosomal units are abundant. Second, we demonstrate intrinsic bi-stability in the dynamics of the ribosomal protein turnover and predict that a minimal number of ribosomes should pre-exists in a living cell to sustain its protein synthesis machinery, even in the absence of proliferation., 22 pages, 9 figures

Recent discovery of cancer stem cells in tumorigenic tissues has raised many questions about their nature, origin, function and their behavior in cell culture. Most of current experiments reporting a dynamics of cancer stem cell populations in culture show the eventual stability of the percentages of these cell populations in the whole population of cancer cells, independently of the starting conditions. In this report we present a review about a class of mathematical models of cancer stem cell population behavior, based on specific features of cancer stem cell divisions and including, as a mathematical formalization of cell-cell communications, an underlying field concept. We compare the qualitative behavior of mathematical models of stem cells evolution, without and with an underlying signal. In presence of an underlying field the model is described by a system of delay differential equations, by admitting a possibly delayed signal originated by existing cells. Under a variety of assumptions on the parameters, in all cases we show that the stability of percentages can be recovered, provided that the delay is sufficiently small. Further, for the DDE case we show the possible existence of, either damped or standing, oscillations in the cell populations. The outcomes of the analysis may offer to experimentalists a tool for addressing the issue regarding the possible non-stem to stem cells transition. Further, they may stimulate further experiments for elucidating the nature of “instructive” signals for cell divisions.

Protein translation is a multistep process which can be represented as a cascade of biochemical reactions (initiation, ribosome assembly, elongation, etc.), the rate of which can be regulated by small non-coding microRNAs through multiple mechanisms. It remains unclear what mechanisms of microRNA action are most dominant: moreover, many experimental reports deliver controversal messages on what is the concrete mechanism actually observed in the experiment. Parker and Nissan (Parker and Nissan, RNA, 2008) demonstrated that it is impossible to distinguish alternative biological hypotheses using the steady state data on the rate of protein synthesis. For their analysis they used two simple kinetic models of protein translation. In contrary, we show that dynamical data allow to discriminate some of the mechanisms of microRNA action. We demonstrate this using the same models as in (Parker and Nissan, RNA, 2008) for the sake of comparison but the methods developed (asymptotology of biochemical networks) can be used for other models. As one of the results of our analysis, we formulate a hypothesis that the effect of microRNA action is measurable and observable only if it affects the dominant system (generalization of the limiting step notion for complex networks) of the protein translation machinery. The dominant system can vary in different experimental conditions that can partially explain the existing controversy of some of the experimental data., Comment: submited to BMC Syst Biol

Ypt–Rab GTPases are key regulators of the various steps of intracellular trafficking. Guanine nucleotide-exchange factors (GEFs) regulate the conversion of Ypt–Rabs to the GTP-bound state, in which they interact with effectors that mediate all the known aspects of vesicular transport1,2,3. An interesting possibility is that Ypt–Rabs coordinate separate steps of the transport pathways4. The conserved modular complex TRAPP is a GEF for the Golgi gatekeepers Ypt1 and Ypt31/32 (Refs 5–7). However, it is not known how Golgi entry and exit are coordinated. TRAPP comes in two configurations: the seven-subunit TRAPPI is required for endoplasmic reticulum-to-Golgi transport, whereas the ten-subunit TRAPPII functions in late Golgi8,9,10. The two essential TRAPPII-specific subunits Trs120 and Trs130 have been identified as Ypt31/32 genetic interactors11,12,13. Here, we show that they are required for switching the GEF specificity of TRAPP from Ypt1 to Ypt31. Moreover, a trs130ts mutation confers opposite effects on the intracellular localization of these GTPases. We suggest that the Trs120–Trs130 subcomplex joins TRAPP in the late Golgi to switch its GEF activity from Ypt1 to Ypt31/32. Such a 'switchable' GEF could ensure sequential activation of these Ypts, thereby coordinating Golgi entry and exit.

Recoding of UGA from a stop codon to selenocysteine poses a dilemma for the protein translation machinery. In eukaryotes, two factors that are crucial to this recoding process are the mRNA binding protein of the Sec insertion sequence, SBP2, and the specialized elongation factor, EFsec. We sought to determine the subcellular localization of these selenoprotein synthesis factors in mammalian cells and thus gain insight into how selenoprotein mRNAs might circumvent nonsense-mediated decay. Intriguingly, both EFsec and SBP2 localization differed depending on the cell line but significant colocalization of the two proteins was observed in cells where SBP2 levels were detectable. We identify functional nuclear localization and export signals in both proteins, demonstrate that SBP2 undergoes nucleocytoplasmic shuttling, and provide evidence that SBP2 levels and localization may influence EFsec localization. Our results suggest a mechanism for the nuclear assembly of the selenocysteine incorporation machinery that could allow selenoprotein mRNAs to circumvent nonsense-mediated decay, thus providing new insights into the mechanism of selenoprotein translation.

Early studies in the field of eukaryotic selenoprotein synthesis established that a functional selenocysteine insertion sequence (SECIS) element linked downstream of an open reading frame would direct selenocysteine incorporation at any upstream in-frame UGA codon. Characterization of the activities of multiple wildtype SECIS elements and of site-directed mutants resulted in determination of the critical features for optimal SECIS function. This information provides a means of introducing selenocysteine at any desired position in any protein. Subsequent studies have revealed additional conditions and factors that allow for increased efficiency of selenoprotein expression. The goals of this article are to describe the criteria and assays used for identifying SECIS elements and for evaluating relative SECIS function, and the conditions established for optimal expression of selenoproteins in transiently transfected cells