Evolutionary Rate Covariation Identifies New Members of a Protein Network Required for Drosophila melanogaster Female Post-Mating Responses

Seminal fluid proteins transferred from males to females during copulation are required for full fertility and can exert dramatic effects on female physiology and behavior. In Drosophila melanogaster, the seminal protein sex peptide (SP) affects mated females by increasing egg production and decreasing receptivity to courtship. These behavioral changes persist for several days because SP binds to sperm that are stored in the female. SP is then gradually released, allowing it to interact with its female-expressed receptor. The binding of SP to sperm requires five additional seminal proteins, which act together in a network. Hundreds of uncharacterized male and female proteins have been identified in this species, but individually screening each protein for network function would present a logistical challenge. To prioritize the screening of these proteins for involvement in the SP network, we used a comparative genomic method to identify candidate proteins whose evolutionary rates across the Drosophila phylogeny co-vary with those of the SP network proteins. Subsequent functional testing of 18 co-varying candidates by RNA interference identified three male seminal proteins and three female reproductive tract proteins that are each required for the long-term persistence of SP responses in females. Molecular genetic analysis showed the three new male proteins are required for the transfer of other network proteins to females and for SP to become bound to sperm that are stored in mated females. The three female proteins, in contrast, act downstream of SP binding and sperm storage. These findings expand the number of seminal proteins required for SP's actions in the female and show that multiple female proteins are necessary for the SP response. Furthermore, our functional analyses demonstrate that evolutionary rate covariation is a valuable predictive tool for identifying candidate members of interacting protein networks. © 2014 Findlay et al

Effect of Correlated tRNA Abundances on Translation Errors and Evolution of Codon Usage Bias

Despite the fact that tRNA abundances are thought to play a major role in determining translation error rates, their distribution across the genetic code and the resulting implications have received little attention. In general, studies of codon usage bias (CUB) assume that codons with higher tRNA abundance have lower missense error rates. Using a model of protein translation based on tRNA competition and intra-ribosomal kinetics, we show that this assumption can be violated when tRNA abundances are positively correlated across the genetic code. Examining the distribution of tRNA abundances across 73 bacterial genomes from 20 different genera, we find a consistent positive correlation between tRNA abundances across the genetic code. This work challenges one of the fundamental assumptions made in over 30 years of research on CUB that codons with higher tRNA abundances have lower missense error rates and that missense errors are the primary selective force responsible for CUB

Entrepreneurial role models, fear of failure, and institutional approval of entrepreneurship: A tale of two regions

Studies on the influence of entrepreneurial role models (peers) on the decision to start a firm ar-gue that entrepreneurial role models in the local environment (1) provide opportunities to learn about entrepreneurial tasks and capabilities, and (2) signal that entrepreneurship is a favorable career option thereby reducing uncertainty that potential entrepreneurs face. However, these studies remain silent about the role of institutional context for these mechanisms. Applying an ex-tended sender-receiver model, we hypothesize that observing entrepreneurs reduces fear of fail-ure in others in environments where approval of entrepreneurship is high while this effect is signif-icantly weaker in low approval environments. Taking advantage of the natural experiment from recent German history and using data from the Global Entrepreneurship Monitor Project (GEM), we find considerable support for our hypotheses

Evaluation of prognostic risk models for postoperative pulmonary complications in adult patients undergoing major abdominal surgery: a systematic review and international external validation cohort study

Background Stratifying risk of postoperative pulmonary complications after major abdominal surgery allows clinicians to modify risk through targeted interventions and enhanced monitoring. In this study, we aimed to identify and validate prognostic models against a new consensus definition of postoperative pulmonary complications. Methods We did a systematic review and international external validation cohort study. The systematic review was done in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We searched MEDLINE and Embase on March 1, 2020, for articles published in English that reported on risk prediction models for postoperative pulmonary complications following abdominal surgery. External validation of existing models was done within a prospective international cohort study of adult patients (≥18 years) undergoing major abdominal surgery. Data were collected between Jan 1, 2019, and April 30, 2019, in the UK, Ireland, and Australia. Discriminative ability and prognostic accuracy summary statistics were compared between models for the 30-day postoperative pulmonary complication rate as defined by the Standardised Endpoints in Perioperative Medicine Core Outcome Measures in Perioperative and Anaesthetic Care (StEP-COMPAC). Model performance was compared using the area under the receiver operating characteristic curve (AUROCC). Findings In total, we identified 2903 records from our literature search; of which, 2514 (86·6%) unique records were screened, 121 (4·8%) of 2514 full texts were assessed for eligibility, and 29 unique prognostic models were identified. Nine (31·0%) of 29 models had score development reported only, 19 (65·5%) had undergone internal validation, and only four (13·8%) had been externally validated. Data to validate six eligible models were collected in the international external validation cohort study. Data from 11 591 patients were available, with an overall postoperative pulmonary complication rate of 7·8% (n=903). None of the six models showed good discrimination (defined as AUROCC ≥0·70) for identifying postoperative pulmonary complications, with the Assess Respiratory Risk in Surgical Patients in Catalonia score showing the best discrimination (AUROCC 0·700 [95% CI 0·683–0·717]). Interpretation In the pre-COVID-19 pandemic data, variability in the risk of pulmonary complications (StEP-COMPAC definition) following major abdominal surgery was poorly described by existing prognostication tools. To improve surgical safety during the COVID-19 pandemic recovery and beyond, novel risk stratification tools are required. Funding British Journal of Surgery Society