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.

Summary Quantitative high throughput cell array phenotyping (Q-HTCP) is applied to the genomic collection of yeast gene deletion mutants for systematic, comprehensive assessment of the contribution of genes and gene combinations to any phenotype of interest (phenomic analysis). Interacting gene networks influence every phenotype. Genetic buffering refers to how gene interaction networks stabilize or destabilize a phenotype. Like genomics, phenomics varies in its resolution with there being a tradeoff allocating a greater number of measurements per sample to enhance quantification of the phenotype vs. increasing the number of different samples by obtaining fewer measurement per sample. The Q-HTCP protocol we describe assesses 50,000–70,000 cultures per experiment by obtaining kinetic growth curves from time series imaging of agar cell arrays. This approach was developed for the yeast gene deletion strains, but it could be applied as well to other microbial mutant arrays grown on solid agar media. The methods we describe are for creation and maintenance of frozen stocks, liquid source array preparation, agar destination plate printing, image scanning, image analysis, curve fitting and evaluation of gene interaction.

A genomic collection of haploid Saccharomyces cerevisiae deletion strains provides a unique resource for systematic analysis of gene interactions. Double-mutant haploid strains can be constructed by the synthetic genetic array (SGA) method, wherein a query mutation is introduced by mating to mutant arrays, selection of diploid double mutants, induction of meiosis, and selection of recombinant haploid doublemutant progeny. The mechanism of haploid selection is mating-type-regulated auxotrophy (MRA), by which prototrophy is restricted to a particular haploid genotype generated only as a result of meiosis. MRA escape leads to false-negative genetic interaction results because postmeiotic haploids that are supposed to be under negative selection instead proliferate and mate, forming diploids that are heterozygous at interacting loci, masking phenotypes that would be observed in a pure haploid double-mutant culture. This work identified factors that reduce MRA escape, including insertion of terminator and repressor sequences upstream of the MRA cassette, deletion of silent mating-type loci, and utilization of a-type instead of a-type MRA. Modifications engineered to reduce haploid MRA escape reduced false negative results in SGA-type analysis, resulting in .95% sensitivity for detecting gene-gene interactions.

Bunyamwera virus (BUNV) is the prototype of the Bunyaviridae family of RNA viruses. BUNV genomic strands are templates for both replication and transcription, whereas the antigenomic RNAs serve only as templates for replication. By mutagenesis of model templates, we showed that the BUNV transcription promoter comprises elements within both the 3 and the 5 nontranslated regions. Using this information, we designed a model ambisense BUNV segment that transcribed BUNV S mRNA from the genomic strand and green fluorescent protein (GFP) mRNA from the antigenome. Demonstration of GFP expression showed that this ambisense strategy represents a viable approach for generating BUNV segments able to express additional proteins.The Bunyaviridae family of RNA viruses comprises five genera, namely, Orthobunyavirus, Hantavirus, Nairovirus, Phlebovirus, and Tospovirus. Many bunyaviruses cause life-threatening human disease and consequently are described by the Centers for Disease Control and Prevention as category A, B, and C priority pathogens. The prototype of the Bunyaviridae family is Bunyamwera virus (BUNV), which serves as a model for the many pathogens within this family.The BUNV genome comprises three segments of negativesense RNA, designated small (S), medium (M), and large (L). The S segment encodes the nucleocapsid (N) and nonstructural proteins (NSs) expressed from overlapping open reading frames (ORFs) on the same mRNA (8,11,12). The M segment encodes a polyprotein that is cleaved to yield Gn, Gc, and NSm proteins (6,12,13). The L segment encodes the RNA-dependent RNA polymerase (RdRp) (7).The ORFs of each segment are flanked by nontranslated regions (NTRs) that direct the RdRp to perform two distinct RNA synthesis activities: (i) transcription to generate a single mRNA and (ii) replication to generate antigenomes that are replicated to generate further genomes. The BUNV S-segment genome is a template for both replication and transcription, whereas the antigenome serves only as a template for replication (5,14). This division of template activity, in which a functional mRNA is transcribed only from the genomic strand, is not a universal feature of all bunyavirus members. Many viruses within this group perform ambisense transcription, in which both genome and antigenomes are transcriptionally active. The ambisense strategy of gene expression is a feature of the segmented arenaviruses and recently has been artificially bestowed upon several nonsegmented negative-sense RNA viruses (9, 18).The fundamental difference in activity of the BUNV genomic and antigenomic RNAs suggests that these strands are recognized differently by the BUNV RdRp, which is likely due to critical nucleotide differences within the 3Ј and 5Ј NTRs of these RNAs. For the BUNV S segment, the 3Ј and 5Ј NTRs are 85 and 170 nucleotides in length, respectively. To facilitate our search for nucleotides responsible for the different strand activities, we constructed WT(25/25), which comprises nucleotides 1 to 25 of 3Ј and 5Ј NTRs surrounding the intact BUN...