Use of a mixed tissue RNA design for performance assessments on multiple microarray formats

The comparability and reliability of data generated using microarray technology would be enhanced by use of a common set of standards that allow accuracy, reproducibility and dynamic range assessments on multiple formats. We designed and tested a complex biological reagent for performance measurements on three commercial oligonucleotide array formats that differ in probe design and signal measurement methodology. The reagent is a set of two mixtures with different proportions of RNA for each of four rat tissues (brain, liver, kidney and testes). The design provides four known ratio measurements of >200 reference probes, which were chosen for their tissue-selectivity, dynamic range coverage and alignment to the same exemplar transcript sequence across all three platforms. The data generated from testing three biological replicates of the reagent at eight laboratories on three array formats provides a benchmark set for both laboratory and data processing performance assessments. Close agreement with target ratios adjusted for sample complexity was achieved on all platforms and low variance was observed among platforms, replicates and sites. The mixed tissue design produces a reagent with known gene expression changes within a complex sample and can serve as a paradigm for performance standards for microarrays that target other species

Cheaters allow cooperators to prosper

Cooperation based on the production of costly common goods is observed throughout nature. This is puzzling, as cooperation is vulnerable to exploitation by defectors which enjoy a fitness advantage by consuming the common good without contributing fairly. Depletion of the common good can lead to population collapse and the destruction of cooperation. However, population collapse implies small population size, which, in a structured population, is known to favor cooperation. This happens because small population size increases variability in cooperator frequency across different locations. Since individuals in cooperator-dominated locations (which are most likely cooperators) will grow more than those in defector-dominated locations (which are most likely defectors), cooperators can outgrow defectors globally despite defectors outgrowing cooperators in each location. This raises the possibility that defectors can lead to conditions that sometimes rescue cooperation from defector-induced destruction. We demonstrate multiple mechanisms through which this can occur, using an individual-based approach to model stochastic birth, death, migration, and mutation events. First, during defector-induced population collapse, defectors occasionally go extinct before cooperators by chance, which allows cooperators to grow. Second, empty locations, either preexisting or created by defector-induced population extinction, can favor cooperation because they allow cooperator but not defector migrants to grow. These factors lead to the counterintuitive result that the initial presence of defectors sometimes allows better survival of cooperation compared to when defectors are initially absent. Finally, we find that resource limitation, inducible by defectors, can select for mutations adaptive to resource limitation. When these mutations are initially present at low levels or continuously generated at a moderate rate, they can favor cooperation by further reducing local population size. We predict that in a structured population, small population sizes precipitated by defectors provide a "built-in" mechanism for the persistence of cooperation

Co-evolutionary dynamics of collective action with signaling for a quorum

Collective signaling for a quorum is found in a wide range of organisms that face collective action problems whose successful solution requires the participation of some quorum of the individuals present. These range from humans, to social insects, to bacteria. The mechanisms involved, the quorum required, and the size of the group may vary. Here we address the general question of the evolution of collective signaling at a high level of abstraction. We investigate the evolutionary dynamics of a population engaging in a signaling N-person game theoretic model. Parameter settings allow for loners and cheaters, and for costly or costless signals. We find a rich dynamics, showing how natural selection, operating on a population of individuals endowed with the simplest strategies, is able to evolve a costly signaling system that allows individuals to respond appropriately to different states of Nature. Signaling robustly promotes cooperative collective action, in particular when coordinated action is most needed and difficult to achieve. Two different signaling systems may emerge depending on Nature's most prevalent states.Funding: This research was supported by FEDER through POFC - COMPETE, FCT-Portugal through grants SFRH/BD/86465/2012, PTDC/MAT/122897/2010, EXPL/EEI-SII/2556/2013, and by multi-annual funding of CMAF-UL, CBMA-UM and INESC-ID (under the projects PEst-OE/BIA/UI4050/2014 and UID/CEC/50021/2013) provided by FCT-Portugal, and by Fundacao Calouste Gulbenkian through the "Stimulus to Research" program for young researchers. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.info:eu-repo/semantics/publishedVersio

HER-2 overexpression differentially alters transforming growth factor-β responses in luminal versus mesenchymal human breast cancer cells

INTRODUCTION: Amplification of the HER-2 receptor tyrosine kinase has been implicated in the pathogenesis and aggressive behavior of approximately 25% of invasive human breast cancers. Clinical and experimental evidence suggest that aberrant HER-2 signaling contributes to tumor initiation and disease progression. Transforming growth factor beta (TGF-β) is the dominant factor opposing growth stimulatory factors and early oncogene activation in many tissues, including the mammary gland. Thus, to better understand the mechanisms by which HER-2 overexpression promotes the early stages of breast cancer, we directly assayed the cellular and molecular effects of TGF-β1 on breast cancer cells in the presence or absence of overexpressed HER-2. METHODS: Cell proliferation assays were used to determine the effect of TGF-β on the growth of breast cancer cells with normal or high level expression of HER-2. Affymetrix microarrays combined with Northern and western blot analysis were used to monitor the transcriptional responses to exogenous TGF-β1 in luminal and mesenchymal-like breast cancer cells. The activity of the core TGF-β signaling pathway was assessed using TGF-β1 binding assays, phospho-specific Smad antibodies, immunofluorescent staining of Smad and Smad DNA binding assays. RESULTS: We demonstrate that cells engineered to over-express HER-2 are resistant to the anti-proliferative effect of TGF-β1. HER-2 overexpression profoundly diminishes the transcriptional responses induced by TGF-β in the luminal MCF-7 breast cancer cell line and prevents target gene induction by a novel mechanism that does not involve the abrogation of Smad nuclear accumulation, DNA binding or changes in c-myc repression. Conversely, HER-2 overexpression in the context of the mesenchymal MDA-MB-231 breast cell line potentiated the TGF-β induced pro-invasive and pro-metastatic gene signature. CONCLUSION: HER-2 overexpression promotes the growth and malignancy of mammary epithelial cells, in part, by conferring resistance to the growth inhibitory effects of TGF-β. In contrast, HER-2 and TGF-β signaling pathways can cooperate to promote especially aggressive disease behavior in the context of a highly invasive breast tumor model

Killing by type VI secretion drives genetic phase separation and correlates with increased cooperation

By nature of their small size, dense growth and frequent need for extracellular metabolism, microbes face persistent public goods dilemmas. Genetic assortment is the only general solution stabilizing cooperation, but all known mechanisms structuring microbial populations depend on the availability of free space, an often unrealistic constraint. Here we describe a class of self-organization that operates within densely packed bacterial populations. Through mathematical modelling and experiments with Vibrio cholerae, we show how killing adjacent competitors via the Type VI secretion system (T6SS) precipitates phase separation via the ‘Model A' universality class of order-disorder transition mediated by killing. We mathematically demonstrate that T6SS-mediated killing should favour the evolution of public goods cooperation, and empirically support this prediction using a phylogenetic comparative analysis. This work illustrates the twin role played by the T6SS, dealing death to local competitors while simultaneously creating conditions potentially favouring the evolution of cooperation with kin