Effect of correlations on network controllability

A dynamical system is controllable if by imposing appropriate external signals on a subset of its nodes, it can be driven from any initial state to any desired state in finite time. Here we study the impact of various network characteristics on the minimal number of driver nodes required to control a network. We find that clustering and modularity have no discernible impact, but the symmetries of the underlying matching problem can produce linear, quadratic or no dependence on degree correlation coefficients, depending on the nature of the underlying correlations. The results are supported by numerical simulations and help narrow the observed gap between the predicted and the observed number of driver nodes in real networks

A diVIsive Shuffling Approach (VIStA) for gene expression analysis to identify subtypes in Chronic Obstructive Pulmonary Disease

Background: An important step toward understanding the biological mechanisms underlying a complex disease is a refined understanding of its clinical heterogeneity. Relating clinical and molecular differences may allow us to define more specific subtypes of patients that respond differently to therapeutic interventions. Results: We developed a novel unbiased method called diVIsive Shuffling Approach (VIStA) that identifies subgroups of patients by maximizing the difference in their gene expression patterns. We tested our algorithm on 140 subjects with Chronic Obstructive Pulmonary Disease (COPD) and found four distinct, biologically and clinically meaningful combinations of clinical characteristics that are associated with large gene expression differences. The dominant characteristic in these combinations was the severity of airflow limitation. Other frequently identified measures included emphysema, fibrinogen levels, phlegm, BMI and age. A pathway analysis of the differentially expressed genes in the identified subtypes suggests that VIStA is capable of capturing specific molecular signatures within in each group. Conclusions: The introduced methodology allowed us to identify combinations of clinical characteristics that correspond to clear gene expression differences. The resulting subtypes for COPD contribute to a better understanding of its heterogeneity

Environmental arginine controls multinuclear giant cell metabolism and formation

Multinucleated giant cells (MGCs) are implicated in many diseases including schistosomiasis, sarcoidosis and arthritis. MGC generation is energy intensive to enforce membrane fusion and cytoplasmic expansion. Using receptor activator of nuclear factor kappa-Beta ligand (RANKL) induced osteoclastogenesis to model MGC formation, here we report RANKL cellular programming requires extracellular arginine. Systemic arginine restriction improves outcome in multiple murine arthritis models and its removal induces preosteoclast metabolic quiescence, associated with impaired tricarboxylic acid (TCA) cycle function and metabolite induction. Effects of arginine deprivation on osteoclastogenesis are independent of mTORC1 activity or global transcriptional and translational inhibition. Arginine scarcity also dampens generation of IL-4 induced MGCs. Strikingly, in extracellular arginine absence, both cell types display flexibility as their formation can be restored with select arginine precursors. These data establish how environmental amino acids control the metabolic fate of polykaryons and suggest metabolic ways to manipulate MGC-associated pathologies and bone remodelling. Multinucleated giant cells (MGCs) are important in the pathogenesis of various diseases. Here, the authors demonstrate that extracellular presence of the amino acid arginine is required for MGC formation and metabolism, suggesting a translational impact for strategies utilizing systemic arginine depletion in MGC-mediated diseases

A divisive Shuffling Approach (VIStA) for gene expression analysis to identify subtypes in Chronic Obstructive Pulmonary Disease

An important step toward understanding the biological mechanisms underlying a complex disease is a refined understanding of its clinical heterogeneity. Relating clinical and molecular differences may allow us to define more specific subtypes of patients that respond differently to therapeutic interventions. Results We developed a novel unbiased method called diVIsive Shuffling Approach (VIStA) that identifies subgroups of patients by maximizing the difference in their gene expression patterns. We tested our algorithm on 140 subjects with Chronic Obstructive Pulmonary Disease (COPD) and found four distinct, biologically and clinically meaningful combinations of clinical characteristics that are associated with large gene expression differences. The dominant characteristic in these combinations was the severity of airflow limitation. Other frequently identified measures included emphysema, fibrinogen levels, phlegm, BMI and age. A pathway analysis of the differentially expressed genes in the identified subtypes suggests that VIStA is capable of capturing specific molecular signatures within in each group. Conclusions The introduced methodology allowed us to identify combinations of clinical characteristics that correspond to clear gene expression differences. The resulting subtypes for COPD contribute to a better understanding of its heterogeneity

Map of synthetic rescue interactions for the Fanconi anemia DNA repair pathway identifies USP48

Genome Instability and Cance

Neighbours of cancer-related proteins have key influence on pathogenesis and could increase the drug target space for anticancer therapies

Even targeted chemotherapies against solid cancers show a moderate success increasing the need to novel targeting strategies. To address this problem, we designed a systems-level approach investigating the neighbourhood of mutated or differentially expressed cancer-related proteins in four major solid cancers (colon, breast, liver and lung). Using signalling and protein–protein interaction network resources integrated with mutational and expression datasets, we analysed the properties of the direct and indirect interactors (first and second neighbours) of cancer-related proteins, not found previously related to the given cancer type. We found that first neighbours have at least as high degree, betweenness centrality and clustering coefficient as cancer-related proteins themselves, indicating a previously unknown central network position. We identified a complementary strategy for mutated and differentially expressed proteins, where the affect of differentially expressed proteins having smaller network centrality is compensated with high centrality first neighbours. These first neighbours can be considered as key, so far hidden, components in cancer rewiring, with similar importance as mutated proteins. These observations strikingly suggest targeting first neighbours as a novel strategy for disrupting cancer-specific networks. Remarkably, our survey revealed 223 marketed drugs already targeting first neighbour proteins but applied mostly outside oncology, providing a potential list for drug repurposing against solid cancers. For the very central first neighbours, whose direct targeting would cause several side effects, we suggest a cancer-mimicking strategy by targeting their interactors (second neighbours of cancer-related proteins, having a central protein affecting position, similarly to the cancer-related proteins). Hence, we propose to include first neighbours to network medicine based approaches for (but not limited to) anticancer therapies

Cryopreservation Effect on Proliferative and Chondrogenic Potential of Human Chondrocytes Isolated from Superficial and Deep Cartilage

[Abstract] Objectives: To compare the proliferative and chondrogenic potential of fresh and frozen chondrocytes isolated from superficial and deep articular cartilage biopsies. Materials and Methodology: The study included 12 samples of fresh and frozen healthy human knee articular cartilage. Cell proliferation was tested at 3, 6 and 9 days. Studies of mRNA quantification, protein expression and immunofluorescence for proliferation and chondrogenic markers were performed. Results: Stimulation of fresh and frozen chondrocytes from both superficial and deep cartilage with fetal bovine serum produced an increase in the proliferative capacity compared to the non-stimulated control group. In the stimulated fresh cells group, the proliferative capacity of cells from the deep biopsy was greater than that from cells from the superficial biopsy (0.046 vs 0.028, respectively, p<0.05). There was also a significant difference between the proliferative capacity of superficial zone fresh (0.028) and frozen (0.051) chondrocytes (p<0.05). CCND1 mRNA and protein expression levels, and immunopositivity for Ki67 revealed a higher proliferative capacity for fresh articular chondrocytes from deep cartilage. Regarding the chondrogenic potential, stimulated fresh cells showed higher SOX9 and Col II expression in chondrocytes from deep than from superficial zone (p<0.05, T student test). Conclusions: The highest rate of cell proliferation and chondrogenic potential of fresh chondrocytes was found in cells obtained from deep cartilage biopsies, whereas there were no statistically significant differences in proliferative and chondrogenic capacity between biopsy origins with frozen chondrocytes. These results indicate that both origin and cryopreservation affect the proliferative and chondrogenic potential of chondrocytes.Servizo Galego de Saúde; PS07/84Instituto de Salud Carlos III; CIBER BBN CB06-01-0040Ministerio Ciencia e Innovacion; PLE2009-0144Ministerio Ciencia e Innovación; PI 08/202