Regulation of cell cycle progression by cell-cell and cell-matrix forces

It has long been proposed that the cell cycle is regulated by physical forces at the cell-cell and cell-extracellular matrix (ECM) interfaces. However, the evolution of these forces during the cycle has never been measured in a tissue, and whether this evolution affects cell cycle progression is unknown. Here, we quantified cell-cell tension and cell-ECM traction throughout the complete cycle of a large cell population in a growing epithelium. These measurements unveil temporal mechanical patterns that span the entire cell cycle and regulate its duration, the G1-S transition and mitotic rounding. Cells subjected to higher intercellular tension exhibit a higher probability to transition from G1 to S, as well as shorter G1 and S-G2-M phases. Moreover, we show that tension and mechanical energy are better predictors of the duration of G1 than measured geometric properties. Tension increases during the cell cycle but decreases 3 hours before mitosis. Using optogenetic control of contractility, we show that this tension drop favours mitotic rounding. Our results establish that cell cycle progression is regulated cooperatively by forces between the dividing cell and its neighbours

Xarxes complexes en biologia cel·lular

A les cèl·lules, una mul tud de biomolècules canvien i interaccionen dinàmicament formant un entramat extraordinàriament complex que lliga metabolisme, proteoma i genoma entre si i amb l'entorn. Entendre com el conjunt de funcionalitats i comportaments cel·lulars emergeixen de tota aquesta complexitat d'interaccions en constant canvi i evolució és un dels grans reptes per al coneixement en el segle. La ciència de les xarxes complexes ens permet abordar l'estudi de la biologia cel·lular a gran escala més enllà dels constituents individuals. Des d'aquest enfocament, en aquest article repassarem breument alguns dels resultats més recents en la investigació dels sistemes cel·lulars, incloent-hi la redundància i plasticitat del metabolisme, mètodes capaços de detectar errors en la determinació experimental d'interaccions entre proteïnes, i l'explicació de fenòmens evolutius en termes del mapa genotip-fenotip

Control of cell-cell forces and collective cell dynamics by the intercellular adhesome

Dynamics of epithelial tissues determine key processes in development, tissue healing and cancer invasion. These processes are critically influenced by cell-cell adhesion forces. However, the identity of the proteins that resist and transmit forces at cell-cell junctions remains unclear, and how these proteins control tissue dynamics is largely unknown. Here we provide a systematic study of the interplay between cell-cell adhesion proteins, intercellular forces and epithelial tissue dynamics. We show that collective cellular responses to selective perturbations of the intercellular adhesome conform to three mechanical phenotypes. These phenotypes are controlled by different molecular modules and characterized by distinct relationships between cellular kinematics and intercellular forces. We show that these forces and their rates can be predicted by the concentrations of cadherins and catenins. Unexpectedly, we identified different mechanical roles for P-cadherin and E-cadherin; whereas P-cadherin predicts levels of intercellular force, E-cadherin predicts the rate at which intercellular force builds up

Effectiveness of Journal Ranking Schemes as a Tool for Locating Information

BACKGROUND: The rise of electronic publishing, preprint archives, blogs, and wikis is raising concerns among publishers, editors, and scientists about the present day relevance of academic journals and traditional peer review. These concerns are especially fuelled by the ability of search engines to automatically identify and sort information. It appears that academic journals can only remain relevant if acceptance of research for publication within a journal allows readers to infer immediate, reliable information on the value of that research. METHODOLOGY/PRINCIPAL FINDINGS: Here, we systematically evaluate the effectiveness of journals, through the work of editors and reviewers, at evaluating unpublished research. We find that the distribution of the number of citations to a paper published in a given journal in a specific year converges to a steady state after a journal-specific transient time, and demonstrate that in the steady state the logarithm of the number of citations has a journal-specific typical value. We then develop a model for the asymptotic number of citations accrued by papers published in a journal that closely matches the data. CONCLUSIONS/SIGNIFICANCE: Our model enables us to quantify both the typical impact and the range of impacts of papers published in a journal. Finally, we propose a journal-ranking scheme that maximizes the efficiency of locating high impact research

Scaling properties of protein family phylogenies

One of the classical questions in evolutionary biology is how evolutionary processes are coupled at the gene and species level. With this motivation, we compare the topological properties (mainly the depth scaling, as a characterization of balance) of a large set of protein phylogenies with a set of species phylogenies. The comparative analysis shows that both sets of phylogenies share remarkably similar scaling behavior, suggesting the universality of branching rules and of the evolutionary processes that drive biological diversification from gene to species level. In order to explain such generality, we propose a simple model which allows us to estimate the proportion of evolvability/robustness needed to approximate the scaling behavior observed in the phylogenies, highlighting the relevance of the robustness of a biological system (species or protein) in the scaling properties of the phylogenetic trees. Thus, the rules that govern the incapability of a biological system to diversify are equally relevant both at the gene and at the species level.Comment: Replaced with final published versio

Mesoscopic organization reveals the constraints governing C. elegans nervous system

One of the biggest challenges in biology is to understand how activity at the cellular level of neurons, as a result of their mutual interactions, leads to the observed behavior of an organism responding to a variety of environmental stimuli. Investigating the intermediate or mesoscopic level of organization in the nervous system is a vital step towards understanding how the integration of micro-level dynamics results in macro-level functioning. In this paper, we have considered the somatic nervous system of the nematode Caenorhabditis elegans, for which the entire neuronal connectivity diagram is known. We focus on the organization of the system into modules, i.e., neuronal groups having relatively higher connection density compared to that of the overall network. We show that this mesoscopic feature cannot be explained exclusively in terms of considerations, such as optimizing for resource constraints (viz., total wiring cost) and communication efficiency (i.e., network path length). Comparison with other complex networks designed for efficient transport (of signals or resources) implies that neuronal networks form a distinct class. This suggests that the principal function of the network, viz., processing of sensory information resulting in appropriate motor response, may be playing a vital role in determining the connection topology. Using modular spectral analysis, we make explicit the intimate relation between function and structure in the nervous system. This is further brought out by identifying functionally critical neurons purely on the basis of patterns of intra- and inter-modular connections. Our study reveals how the design of the nervous system reflects several constraints, including its key functional role as a processor of information.Comment: Published version, Minor modifications, 16 pages, 9 figure

Remission of obesity and insulin resistance is not sufficient to restore mitochondrial homeostasis in visceral adipose tissue

Metabolic plasticity is the ability of a biological system to adapt its metabolic phenotype to different environmental stressors. We used a whole-body and tissue-specific phenotypic, functional, proteomic, metabolomic and transcriptomic approach to systematically assess metabolic plasticity in diet-induced obese mice after a combined nutritional and exercise intervention. Although most obesity and overnutrition-related pathological features were successfully reverted, we observed a high degree of metabolic dysfunction in visceral white adipose tissue, characterized by abnormal mitochondrial morphology and functionality. Despite two sequential therapeutic interventions and an apparent global healthy phenotype, obesity triggered a cascade of events in visceral adipose tissue progressing from mitochondrial metabolic and proteostatic alterations to widespread cellular stress, which compromises its biosynthetic and recycling capacity. In humans, weight loss after bariatric surgery showed a transcriptional signature in visceral adipose tissue similar to our mouse model of obesity reversion. Overall, our data indicate that obesity prompts a lasting metabolic fingerprint that leads to a progressive breakdown of metabolic plasticity in visceral adipose tissue

A unified data representation theory for network visualization, ordering and coarse-graining

Representation of large data sets became a key question of many scientific disciplines in the last decade. Several approaches for network visualization, data ordering and coarse-graining accomplished this goal. However, there was no underlying theoretical framework linking these problems. Here we show an elegant, information theoretic data representation approach as a unified solution of network visualization, data ordering and coarse-graining. The optimal representation is the hardest to distinguish from the original data matrix, measured by the relative entropy. The representation of network nodes as probability distributions provides an efficient visualization method and, in one dimension, an ordering of network nodes and edges. Coarse-grained representations of the input network enable both efficient data compression and hierarchical visualization to achieve high quality representations of larger data sets. Our unified data representation theory will help the analysis of extensive data sets, by revealing the large-scale structure of complex networks in a comprehensible form.Comment: 13 pages, 5 figure

Human Endometrial Side Population Cells Exhibit Genotypic, Phenotypic and Functional Features of Somatic Stem Cells

During reproductive life, the human endometrium undergoes around 480 cycles of growth, breakdown and regeneration should pregnancy not be achieved. This outstanding regenerative capacity is the basis for women's cycling and its dysfunction may be involved in the etiology of pathological disorders. Therefore, the human endometrial tissue must rely on a remarkable endometrial somatic stem cells (SSC) population. Here we explore the hypothesis that human endometrial side population (SP) cells correspond to somatic stem cells. We isolated, identified and characterized the SP corresponding to the stromal and epithelial compartments using endometrial SP genes signature, immunophenotyping and characteristic telomerase pattern. We analyzed the clonogenic activity of SP cells under hypoxic conditions and the differentiation capacity in vitro to adipogenic and osteogenic lineages. Finally, we demonstrated the functional capability of endometrial SP to develop human endometrium after subcutaneous injection in NOD-SCID mice. Briefly, SP cells of human endometrium from epithelial and stromal compartments display genotypic, phenotypic and functional features of SSC