Ecological networks depict the interactions between species, mainly based on observations in the field. The information contained in such interaction matrices depends on the sampling design, and ...typically, compounds preferences (specialization) and abundances (activity). Null models are the primary vehicles to disentangle the effects of specialization from those of sampling and abundance, but they ignore the feedback of network structure on abundances. Hence, network structure, as exemplified here by modularity, is difficult to link to specific causes. Indeed, various processes lead to modularity and to specific interaction patterns more generally. Inferring (co)evolutionary dynamics is even more challenging, as competition and trait matching yield identical patterns of interactions. A satisfactory resolution of the underlying factors determining network structure will require substantial additional information, not only on independently assessed abundances, but also on traits, and ideally on fitness consequences as measured in experimental setups.
The increasing number of experimentally detected interactions between proteins makes it difficult for researchers to extract the interactions relevant for specific biological processes or diseases. ...This makes it necessary to accompany the large-scale detection of protein-protein interactions (PPIs) with strategies and tools to generate meaningful PPI subnetworks. To this end, we generated the Human Integrated Protein-Protein Interaction rEference or HIPPIE (http://cbdm.uni-mainz.de/hippie/). HIPPIE is a one-stop resource for the generation and interpretation of PPI networks relevant to a specific research question. We provide means to generate highly reliable, context-specific PPI networks and to make sense out of them. We just released the second major update of HIPPIE, implementing various new features. HIPPIE grew substantially over the last years and now contains more than 270 000 confidence scored and annotated PPIs. We integrated different types of experimental information for the confidence scoring and the construction of context-specific networks. We implemented basic graph algorithms that highlight important proteins and interactions. HIPPIE's graphical interface implements several ways for wet lab and computational scientists alike to access the PPI data.
The expression of most life history traits, such as immunity, growth and the development of sexual signals, is negatively affected by high levels of oxidative stress. Dietary antioxidants can reduce ...oxidative stress and have therefore been the focus of numerous studies in behavioural and evolutionary ecology in the last few decades. Most of this research has focused on carotenoids, neglecting a number of more common, more potent, and thereby potentially more important, antioxidants, such as polyphenolic antioxidants. However, the effects of several classes of antioxidants on different life history traits have been thoroughly investigated in medical and animal-breeding studies. We suggest that behavioural and evolutionary studies will benefit from incorporating these advances. By reviewing the literature on the effects of antioxidants on life history traits in fish, birds and mammals, we develop a broad framework for dietary antioxidants. Fundamental properties of antioxidants, in particular their biochemistry, their potency and the interactions between them affect their relative relevance for life history traits. Based on tissue affinity, we distinguish between two categories of dietary antioxidants: focal antioxidants that are intrinsically important for a given trait and nonfocal antioxidants that influence traits only indirectly. Furthermore, we show how temporal and spatial environmental variability in antioxidant availability, as well as individual variation in food selection, may generate interindividual differences in the expression of life history traits. Finally, we suggest future research lines and experimental designs that may provide basic information needed to advance our knowledge of the ecological and evolutionary relevance of dietary antioxidants.
Protein function is often modulated by protein-protein interactions (PPIs) and therefore defining the partners of a protein helps to understand its activity. PPIs can be detected through different ...experimental approaches and are collected in several expert curated databases. These databases are used by researchers interested in examining detailed information on particular proteins. In many analyses the reliability of the characterization of the interactions becomes important and it might be necessary to select sets of PPIs of different confidence levels. To this goal, we generated HIPPIE (Human Integrated Protein-Protein Interaction rEference), a human PPI dataset with a normalized scoring scheme that integrates multiple experimental PPI datasets. HIPPIE's scoring scheme has been optimized by human experts and a computer algorithm to reflect the amount and quality of evidence for a given PPI and we show that these scores correlate to the quality of the experimental characterization. The HIPPIE web tool (available at http://cbdm.mdc-berlin.de/tools/hippie) allows researchers to do network analyses focused on likely true PPI sets by generating subnetworks around proteins of interest at a specified confidence level.
Although chemical communication is the most widespread form of communication, its evolution and diversity are not well understood. By integrating studies of a wide range of terrestrial plants and ...animals, we show that many chemicals are emitted, which can unintentionally provide information (cues) and, therefore, act as direct precursors for the evolution of intentional communication (signals). Depending on the content, design and the original function of the cue, there are predictable ways that selection can enhance the communicative function of chemicals. We review recent progress on how efficacy-based selection by receivers leads to distinct evolutionary trajectories of chemical communication. Because the original function of a cue may channel but also constrain the evolution of functional communication, we show that a broad perspective on multiple selective pressures acting upon chemicals provides important insights into the origin and dynamic evolution of chemical information transfer. Finally, we argue that integrating chemical ecology into communication theory may significantly enhance our understanding of the evolution, the design and the content of signals in general.
Abstract
While large-scale studies applying various statistical approaches have identified hundreds of mutated driver genes across various cancer types, the contribution of epigenetic changes to ...cancer remains more enigmatic. This is partly due to the fact that certain regions of the cancer genome, due to their genomic and epigenomic properties, are more prone to dysregulated DNA methylation than others. Thus, it has been difficult to distinguish which promoter methylation changes are really driving carcinogenesis from those that are mostly just a reflection of their genomic location. By developing a novel method that corrects for epigenetic covariates, we reveal a small, concise set of potential epigenetic driver events. Interestingly, those changes suggest different modes of epigenetic carcinogenesis: first, we observe recurrent inactivation of known cancer genes across tumour types suggesting a higher convergence on common tumour suppressor pathways than previously anticipated. Second, in prostate cancer, a cancer type with few recurrently mutated genes, we demonstrate how the epigenome primes tumours towards higher tolerance of other aberrations.
RNA splicing is widely dysregulated in cancer, frequently due to altered expression or activity of splicing factors (SFs). Microexons are extremely small exons (3-27 nucleotides long) that are highly ...evolutionarily conserved and play critical roles in promoting neuronal differentiation and development. Inclusion of microexons in mRNA transcripts is mediated by the SF Serine/Arginine Repetitive Matrix 4 (SRRM4), whose expression is largely restricted to neural tissues. However, microexons have been largely overlooked in prior analyses of splicing in cancer, as their small size necessitates specialized computational approaches for their detection. Here, we demonstrate that despite having low expression in normal nonneural tissues, SRRM4 is further silenced in tumors, resulting in the suppression of normal microexon inclusion. Remarkably, SRRM4 is the most consistently silenced SF across all tumor types analyzed, implying a general advantage of microexon down-regulation in cancer independent of its tissue of origin. We show that this silencing is favorable for tumor growth, as decreased SRRM4 expression in tumors is correlated with an increase in mitotic gene expression, and up-regulation of SRRM4 in cancer cell lines dose-dependently inhibits proliferation in vitro and in a mouse xenograft model. Further, this proliferation inhibition is accompanied by induction of neural-like expression and splicing patterns in cancer cells, suggesting that SRRM4 expression shifts the cell state away from proliferation and toward differentiation. We therefore conclude that SRRM4 acts as a proliferation brake, and tumors gain a selective advantage by cutting off this brake.
Mimicry involves adaptive resemblance between a mimic and a model. However, despite much recent research, it remains contentious in plants. Here, we review recent progress on studying deception by ...flowers, distinguishing between plants relying on mimicry to achieve pollination and those relying on the exploitation of the perceptual biases of animals. We disclose fundamental differences between both mechanisms and explain why the evolution of exploitation is less constrained than that of mimicry. Exploitation of perceptual biases might thus be a precursor for the gradual evolution of mimicry. Increasing knowledge on the sensory and cognitive filters in animals, and on the selective pressures that maintain them, should aid researchers in tracing the evolutionary dynamics of deception in plants.
World governments have committed to halting human-induced extinctions and safeguarding important sites for biodiversity by 2020, but the financial costs of meeting these targets are largely unknown. ...We estimate the cost of reducing the extinction risk of all globally threatened bird species (by > 1 International Union for Conservation of Nature Red List category) to be U.S. $0.875 to $1.23 billion annually over the next decade, of which 12% is currently funded. Incorporating threatened nonavian species increases this total to U.S. $3.41 to $4.76 billion annually. We estimate that protecting and effectively managing all terrestrial sites of global avian conservation significance (11,731 Important Bird Areas) would cost U.S. $ 65.1 billion annually. Adding sites for other taxa increases this to U.S. $76.1 billion annually. Meeting these targets will require conservation funding to increase by at least an order of magnitude.
Cancers evolve under the accumulation of thousands of somatic mutations and chromosomal aberrations. While most coding mutations are deleterious, almost all protein-coding genes lack detectable ...signals of negative selection. This raises the question of how tumors tolerate such large amounts of deleterious mutations. Using 8,690 tumor samples from The Cancer Genome Atlas, we demonstrate that copy number amplifications frequently cover haploinsufficient genes in mutation-prone regions. This could increase tolerance towards the deleterious impact of mutations by creating safe copies of wild-type regions and, hence, protecting the genes therein. Our findings demonstrate that these potential buffering events are highly influenced by gene functions, essentiality, and mutation impact and that they occur early during tumor evolution. We show how cancer type-specific mutation landscapes drive copy number alteration patterns across cancer types. Ultimately, our work paves the way for the detection of novel cancer vulnerabilities by revealing genes that fall within amplifications likely selected during evolution to mitigate the effect of mutations.
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