BackgroundThe overall influence of gene interaction in human disease is unknown. In cystic fibrosis (CF) a single allele of the cystic fibrosis transmembrane conductance regulator (CFTR-ΔF508) accounts for most of the disease. In cell models, CFTR-ΔF508 exhibits defective protein biogenesis and degradation rather than proper trafficking to the plasma membrane where CFTR normally functions. Numerous genes function in the biogenesis of CFTR and influence the fate of CFTR-ΔF508. However it is not known whether genetic variation in such genes contributes to disease severity in patients. Nor is there an easy way to study how numerous gene interactions involving CFTR-ΔF would manifest phenotypically.MethodsTo gain insight into the function and evolutionary conservation of a gene interaction network that regulates biogenesis of a misfolded ABC transporter, we employed yeast genetics to develop a 'phenomic' model, in which the CFTR-ΔF508-equivalent residue of a yeast homolog is mutated (Yor1-ΔF670), and where the genome is scanned quantitatively for interaction. We first confirmed that Yor1-ΔF undergoes protein misfolding and has reduced half-life, analogous to CFTR-ΔF. Gene interaction was then assessed quantitatively by growth curves for approximately 5,000 double mutants, based on alteration in the dose response to growth inhibition by oligomycin, a toxin extruded from the cell at the plasma membrane by Yor1.ResultsFrom a comparative genomic perspective, yeast gene interactions influencing Yor1-ΔF biogenesis were representative of human homologs previously found to modulate processing of CFTR-ΔF in mammalian cells. Additional evolutionarily conserved pathways were implicated by the study, and a ΔF-specific pro-biogenesis function of the recently discovered ER membrane complex (EMC) was evident from the yeast screen. This novel function was validated biochemically by siRNA of an EMC ortholog in a human cell line expressing CFTR-ΔF508. The precision and accuracy of quantitative high throughput cell array phenotyping (Q-HTCP), which captures tens of thousands of growth curves simultaneously, provided powerful resolution to measure gene interaction on a phenomic scale, based on discrete cell proliferation parameters.ConclusionWe propose phenomic analysis of Yor1-ΔF as a model for investigating gene interaction networks that can modulate cystic fibrosis disease severity. Although the clinical relevance of the Yor1-ΔF gene interaction network for cystic fibrosis remains to be defined, the model appears to be informative with respect to human cell models of CFTR-ΔF. Moreover, the general strategy of yeast phenomics can be employed in a systematic manner to model gene interaction for other diseases relating to pathologies that result from protein misfolding or potentially any disease involving evolutionarily conserved genetic pathways.

Objectives: Opioids and benzodiazepines are commonly used to provide analgesia and sedation for critically ill children with cardiac disease. These medications have been associated with adverse effects including delirium, dependence, withdrawal, bowel dysfunction, and potential neurodevelopmental abnormalities. Our objective was to implement a risk-stratified opioid and benzodiazepine weaning protocol to reduce the exposure to opioids and benzodiazepines in pediatric patients with cardiac disease. Design: A prospective pre- and postinterventional study. Patients: Critically ill patients less than or equal to 21 years old with acquired or congenital cardiac disease exposed to greater than or equal to 7 days of scheduled opioids ± scheduled benzodiazepines between January 2013 and February 2015. Setting: A 24-bed pediatric cardiac ICU and 21-bed cardiovascular acute ward of an urban stand-alone children’s hospital. Intervention: We implemented an evidence-based opioid and benzodiazepine weaning protocol using educational and quality improvement methodology. Measurements and Main Results: One-hundred nineteen critically ill children met the inclusion criteria (64 post intervention, 55 pre intervention). Demographics and risk factors did not differ between groups. Patients in the postintervention period had shorter duration of opioids (19.0 vs 30.0 d; p < 0.01) and duration of benzodiazepines (5.3 vs 22.7 d; p < 0.01). Despite the shorter duration of wean, there was a decrease in withdrawal occurrence (% Withdrawal Assessment Tool score ≥ 4, 4.9% vs 14.1%; p < 0.01). There was an 8-day reduction in hospital length of stay (34 vs 42 d; p < 0.01). There was a decrease in clonidine use (14% vs 32%; p = 0.02) and no change in dexmedetomidine exposure (59% vs 75%; p = 0.08) in the postintervention period. Conclusions: We implemented a risk-stratified opioid and benzodiazepine weaning protocol for critically ill cardiac children that resulted in reduction in opioid and benzodiazepine duration and dose exposure, a decrease in symptoms of withdrawal, and a reduction in hospital length of stay.

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Bunyamwera virus (BUNV) is the prototype of the family Bunyaviridae, which comprises segmented RNA viruses. Each of the BUNV negative-strand segments, small (S), medium (M) and large (L), serves as template for two distinct RNA-synthesis activities: (i) replication to generate antigenomes that are in turn replicated to yield further genomes; and (ii) transcription to generate a single species of mRNA. BUNV mRNAs are truncated at their 39 ends relative to the genome template, presumably because the BUNV transcriptase terminates transcription before reaching the 59 terminus of the genomic template. Here, identification of the transcription termination signal responsible for 39-end truncation of BUNV S-segment mRNA was carried out. It was shown that efficient transcription termination was signalled by a 33 nt sequence within the 59 non-translated region (NTR) of the S segment. A 6 nt region (39-GUCGAC-59) within this sequence was found to play a major role in termination signalling, with other nucleotides possessing individually minor, but collectively significant, signalling ability. By abrogating the signalling ability of these 33 nt, we identified a second, functionally independent termination signal located 32 nt downstream. This downstream signal was 9 nt in length and contained a pentanucleotide sequence, 39-UGUCG-59, that overlapped the 6 nt major signalling component of the upstream signal. The pentanucleotide sequence was also found within the 59 NTR of the BUNV L segment and in several other members of the genus Orthobunyavirus, suggesting that the mechanism responsible for BUNV transcription termination may be common to other orthobunyaviruses.

The genome project increased appreciation of genetic complexity underlying disease phenotypes: many genes contribute each phenotype and each gene contributes multiple phenotypes. The aspiration of predicting common disease in individuals has evolved from seeking primary loci to marginal risk assignments based on many genes. Genetic interaction, defined as contributions to a phenotype that are dependent upon particular digenic allele combinations, could improve prediction of phenotype from complex genotype, but it is difficult to study in human populations. High throughput, systematic analysis of S. cerevisiae gene knockouts or knockdowns in the context of disease-relevant phenotypic perturbations provides a tractable experimental approach to derive gene interaction networks, in order to deduce by cross-species gene homology how phenotype is buffered against disease-risk genotypes. Yeast gene interaction network analysis to date has revealed biology more complex than previously imagined. This has motivated the development of more powerful yeast cell array phenotyping methods to globally model the role of gene interaction networks in modulating phenotypes (which we call yeast phenomic analysis). The article illustrates yeast phenomic technology, which is applied here to quantify gene X media interaction at higher resolution and supports use of a human-like media for future applications of yeast phenomics for modeling human disease.