Comparative Analysis of the Saccharomyces cerevisiae and Caenorhabditis elegans Protein Interaction Network

Protein interaction networks aim to summarize the complex interplay of proteins in an organism. Early studies suggested that the position of a protein in the network determines its evolutionary rate but there has been considerable disagreement as to what extent other factors, such as protein abundance, modify this reported dependence. We compare the genomes of Saccharomyces cerevisiae and Caenorhabditis elegans with those of closely related species to elucidate the recent evolutionary history of their respective protein interaction networks. Interaction and expression data are studied in the light of a detailed phylogenetic analysis. The underlying network structure is incorporated explicitly into the statistical analysis. The increased phylogenetic resolution, paired with high-quality interaction data, allows us to resolve the way in which protein interaction network structure and abundance of proteins affect the evolutionary rate. We find that expression levels are better predictors of the evolutionary rate than a protein's connectivity. Detailed analysis of the two organisms also shows that the evolutionary rates of interacting proteins are not sufficiently similar to be mutually predictive. It appears that meaningful inferences about the evolution of protein interaction networks require comparative analysis of reasonably closely related species. The signature of protein evolution is shaped by a protein's abundance in the organism and its function and the biological process it is involved in. Its position in the interaction networks and its connectivity may modulate this but they appear to have only minor influence on a protein's evolutionary rate.Comment: Accepted for publication in BMC Evolutionary Biolog

Processing political misinformation:comprehending the Trump phenomenon

his study investigated the cognitive processing of true and false political information. Specifically, it examined the impact of source credibility on the assessment of veracity when information comes from a polarizing source (Experiment 1), and effectiveness of explanations when they come from one's own political party or an opposition party (Experiment 2). These experiments were conducted prior to the 2016 Presidential election. Participants rated their belief in factual and incorrect statements that President Trump made on the campaign trail; facts were subsequently affirmed and misinformation retracted. Participants then re-rated their belief immediately or after a delay. Experiment 1 found that (i) if information was attributed to Trump, Republican supporters of Trump believed it more than if it was presented without attribution, whereas the opposite was true for Democrats and (ii) although Trump supporters reduced their belief in misinformation items following a correction, they did not change their voting preferences. Experiment 2 revealed that the explanation's source had relatively little impact, and belief updating was more influenced by perceived credibility of the individual initially purporting the information. These findings suggest that people use political figures as a heuristic to guide evaluation of what is true or false, yet do not necessarily insist on veracity as a prerequisite for supporting political candidates

Supporting future scholars of engaged research

Researchers in the UK are taking on new roles and responsibilities to meet the requirements of an expanded agenda for generating and evidencing social and economic impacts from research. Within this wider context, culture change programmes have identified learning as an important driver of change. Here we outline a professional development programme designed to train postgraduate researchers studying environmental sciences in core engagement, influence and impact, governance and organization skills for research. We argue that training is an important step in further catalysing progressive culture change. However, our research- and experience-informed critical reflections in supporting researchers suggest that there is still significant work to be done: (1) to offer consistent messages to researchers at all grades about social impacts from research and (2) to ensure that engagement is seen as an aspirational activity, embedded within research

Infrared Constraints on AGN Tori Models

This work focuses on the properties of dusty tori in active galactic nuclei (AGN) derived from the comparison of SDSS type 1 quasars with mid-Infrared (MIR) counterparts and a new, detailed torus model. The infrared data were taken by the Spitzer Wide-area InfraRed Extragalactic (SWIRE) Survey. Basic model parameters are constraint, such as the density law of the graphite and silicate grains, the torus size and its opening angle. A whole variety of optical depths is supported. The favoured models are those with decreasing density with distance from the centre, while there is no clear tendency as to the covering factor, ie small, medium and large covering factors are almost equally distributed. Based on the models that better describe the observed SEDs, properties such as the accretion luminosity, the mass of dust, the inner to outer radius ratio and the hydrogen column density are computed.Comment: 4 pages, 4 figures, to appear in "Infrared Diagnostics of Galaxy Evolution", ASP Conference Series, Pasadena, 14-16 November 200

Stops making sense: translational trade-offs and stop codon reassignment

Background Efficient gene expression involves a trade-off between (i) premature termination of protein synthesis; and (ii) readthrough, where the ribosome fails to dissociate at the terminal stop. Sense codons that are similar in sequence to stop codons are more susceptible to nonsense mutation, and are also likely to be more susceptible to transcriptional or translational errors causing premature termination. We therefore expect this trade-off to be influenced by the number of stop codons in the genetic code. Although genetic codes are highly constrained, stop codon number appears to be their most volatile feature. Results In the human genome, codons readily mutable to stops are underrepresented in coding sequences. We construct a simple mathematical model based on the relative likelihoods of premature termination and readthrough. When readthrough occurs, the resultant protein has a tail of amino acid residues incorrectly added to the C-terminus. Our results depend strongly on the number of stop codons in the genetic code. When the code has more stop codons, premature termination is relatively more likely, particularly for longer genes. When the code has fewer stop codons, the length of the tail added by readthrough will, on average, be longer, and thus more deleterious. Comparative analysis of taxa with a range of stop codon numbers suggests that genomes whose code includes more stop codons have shorter coding sequences. Conclusions We suggest that the differing trade-offs presented by alternative genetic codes may result in differences in genome structure. More speculatively, multiple stop codons may mitigate readthrough, counteracting the disadvantage of a higher rate of nonsense mutation. This could help explain the puzzling overrepresentation of stop codons in the canonical genetic code and most variants

Physiology of short-term verbal memory

These studies document a series of brain events accompanying short-term memory functions. For auditory verbal material the sequence involves at least two different sites within auditory cortex subserving sensory and cognitive processes of memorization. During the scanning of the short-term store structures within the medial temporal lobes, presumably the hippocampus, are active. There is an inconsistency between these results and the clinical observations of the need for an intact dominant parietal lobe for auditory short-term memory to function normally. Magnetic recordings showed no focal dipolar source of activity in the parietal lobe during any aspect of auditory short-term memory. The discrepancy could be accounted for by considering the parietal lobe lesion as "disconnecting" the lateral temporal cortex from the deep medial hippocampal structures thereby impeding auditory short-term functions (Geschwind, 1965). These studies show that the physiological analysis of brain events in the msec range can provide information about relatively complex cognitive processes underlying short-term memory. The magnetic and electrical recording methods provide a noninvasive way to study human brain functions involved in cognition that can then be correlated with behavioral measures of specific cognitive activities

The Mechanisms of Codon Reassignments in Mitochondrial Genetic Codes

Many cases of non-standard genetic codes are known in mitochondrial genomes. We carry out analysis of phylogeny and codon usage of organisms for which the complete mitochondrial genome is available, and we determine the most likely mechanism for codon reassignment in each case. Reassignment events can be classified according to the gain-loss framework. The gain represents the appearance of a new tRNA for the reassigned codon or the change of an existing tRNA such that it gains the ability to pair with the codon. The loss represents the deletion of a tRNA or the change in a tRNA so that it no longer translates the codon. One possible mechanism is Codon Disappearance, where the codon disappears from the genome prior to the gain and loss events. In the alternative mechanisms the codon does not disappear. In the Unassigned Codon mechanism, the loss occurs first, whereas in the Ambiguous Intermediate mechanism, the gain occurs first. Codon usage analysis gives clear evidence of cases where the codon disappeared at the point of the reassignment and also cases where it did not disappear. Codon disappearance is the probable explanation for stop to sense reassignments and a small number of reassignments of sense codons. However, the majority of sense to sense reassignments cannot be explained by codon disappearance. In the latter cases, by analysis of the presence or absence of tRNAs in the genome and of the changes in tRNA sequences, it is sometimes possible to distinguish between the Unassigned Codon and Ambiguous Intermediate mechanisms. We emphasize that not all reassignments follow the same scenario and that it is necessary to consider the details of each case carefully.Comment: 53 pages (45 pages, including 4 figures + 8 pages of supplementary information). To appear in J.Mol.Evo

Amino Acid Metabolic Origin as an Evolutionary Influence on Protein Sequence in Yeast

The metabolic cycle of Saccharomyces cerevisiae consists of alternating oxidative (respiration) and reductive (glycolysis) energy-yielding reactions. The intracellular concentrations of amino acid precursors generated by these reactions oscillate accordingly, attaining maximal concentration during the middle of their respective yeast metabolic cycle phases. Typically, the amino acids themselves are most abundant at the end of their precursor’s phase. We show that this metabolic cycling has likely biased the amino acid composition of proteins across the S. cerevisiae genome. In particular, we observed that the metabolic source of amino acids is the single most important source of variation in the amino acid compositions of functionally related proteins and that this signal appears only in (facultative) organisms using both oxidative and reductive metabolism. Periodically expressed proteins are enriched for amino acids generated in the preceding phase of the metabolic cycle. Proteins expressed during the oxidative phase contain more glycolysis-derived amino acids, whereas proteins expressed during the reductive phase contain more respiration-derived amino acids. Rare amino acids (e.g., tryptophan) are greatly overrepresented or underrepresented, relative to the proteomic average, in periodically expressed proteins, whereas common amino acids vary by a few percent. Genome-wide, we infer that 20,000 to 60,000 residues have been modified by this previously unappreciated pressure. This trend is strongest in ancient proteins, suggesting that oscillating endogenous amino acid availability exerted genome-wide selective pressure on protein sequences across evolutionary time