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The looming antibiotic-resistance crisis has penetrated the consciousness of clinicians, researchers, policymakers, politicians and the public at large. The evolution and widespread distribution of antibiotic-resistance elements in bacterial pathogens has made diseases that were once easily treatable deadly again. Unfortunately, accompanying the rise in global resistance is a failure in antibacterial drug discovery. Lessons from the history of antibiotic discovery and fresh understanding of antibiotic action and the cell biology of microorganisms have the potential to deliver twenty-first century medicines that are able to control infection in the resistance era.

Genome-scale CRISPR-Cas9 viability screens performed in cancer cell lines provide a systematic approach to identify cancer dependencies and new therapeutic targets. As multiple large-scale screens become available, a formal assessment of the reproducibility of these experiments becomes necessary. We analyze data from recently published pan-cancer CRISPR-Cas9 screens performed at the Broad and Sanger Institutes. Despite significant differences in experimental protocols and reagents, we find that the screen results are highly concordant across multiple metrics with both common and specific dependencies jointly identified across the two studies. Furthermore, robust biomarkers of gene dependency found in one data set are recovered in the other. Through further analysis and replication experiments at each institute, we show that batch effects are driven principally by two key experimental parameters: the reagent library and the assay length. These results indicate that the Broad and Sanger CRISPR-Cas9 viability screens yield robust and reproducible findings. Integrating independent large-scale pharmacogenomic screens can enable unprecedented characterization of genetic vulnerabilities in cancers. Here, the authors show that the two largest independent CRISPR-Cas9 gene-dependency screens are concordant, paving the way for joint analysis of the data sets.

Naturally occurring human genetic variants that are predicted to inactivate protein-coding genes provide an in vivo model of human gene inactivation that complements knockout studies in cells and model organisms. Here we report three key findings regarding the assessment of candidate drug targets using human loss-of-function variants. First, even essential genes, in which loss-of-function variants are not tolerated, can be highly successful as targets of inhibitory drugs. Second, in most genes, loss-of-function variants are sufficiently rare that genotype-based ascertainment of homozygous or compound heterozygous ‘knockout’ humans will await sample sizes that are approximately 1,000 times those presently available, unless recruitment focuses on consanguineous individuals. Third, automated variant annotation and filtering are powerful, but manual curation remains crucial for removing artefacts, and is a prerequisite for recall-by-genotype efforts. Our results provide a roadmap for human knockout studies and should guide the interpretation of loss-of-function variants in drug development. Analysis of predicted loss-of-function variants from 125,748 human exomes and 15,708 whole genomes in the Genome Aggregation Database (gnomAD) provides a roadmap for human ‘knockout’ studies and a guide for future research into disease biology and drug-target selection.

The reverse transcription quantitative polymerase chain reaction (RT-qPCR) is a powerful and widely used technique for the measurement of gene expression. Reference genes, which serve as endogenous controls ensure that the results are accurate and reproducible, are vital for data normalization. To bolster the literature on reference gene selection in maize, ten candidate reference genes, including eight traditionally used internal control genes and two potential candidate genes from our microarray datasets, were evaluated for expression level in maize across abiotic stresses (cold, heat, salinity, and PEG), phytohormone treatments (abscisic acid, salicylic acid, jasmonic acid, ethylene, and gibberellins), and different tissue types. Three analytical software packages, geNorm, NormFinder, and Bestkeeper, were used to assess the stability of reference gene expression. The results revealed that elongation factor 1 alpha (EF1α), tubulin beta (β-TUB), cyclophilin (CYP), and eukaryotic initiation factor 4A (EIF4A) were the most reliable reference genes for overall gene expression normalization in maize, while GRP (Glycine-rich RNA-binding protein), GLU1(beta-glucosidase), and UBQ9 (ubiquitin 9) were the least stable and most unsuitable genes. In addition, the suitability of EF1α, β-TUB, and their combination as reference genes was confirmed by validating the expression of WRKY50 in various samples. The current study indicates the appropriate reference genes for the urgent requirement of gene expression normalization in maize across certain abiotic stresses, hormones, and tissue types.

Many small-interfering (si)RNAs are toxic to cancer cells through a 6mer seed sequence (positions 2–7 of the guide strand). Here we performed an siRNA screen with all 4096 6mer seeds revealing a preference for guanine in positions 1 and 2 and a high overall G or C content in the seed of the most toxic siRNAs for four tested human and mouse cell lines. Toxicity of these siRNAs stems from targeting survival genes with C-rich 3′UTRs. The master tumor suppressor miRNA miR-34a-5p is toxic through such a G-rich 6mer seed and is upregulated in cells subjected to genotoxic stress. An analysis of all mature miRNAs suggests that during evolution most miRNAs evolved to avoid guanine at the 5′ end of the 6mer seed sequence of the guide strand. In contrast, for certain tumor-suppressive miRNAs the guide strand contains a G-rich toxic 6mer seed, presumably to eliminate cancer cells. Small interfering (siRNAs) can be toxic to cancer cells. Here the authors investigate the toxicity of microRNA in cancer cells by performing a siRNA screen that tests the miRNA activities of an extensive list of miRNAs with different 6mer seed sequences.

Computational inference of mutation effects is necessary for genetic studies in which many mutations must be considered as etiologic candidates. Programs such as PolyPhen-2 predict the relative severity of damage caused by missense mutations, but not the actual probability that a mutation will reduce/eliminate protein function. Based on genotype and phenotype data for 116,330 ENU-induced mutations in the Mutagenetix database, we calculate that putative null mutations, and PolyPhen-2-classified “probably damaging”, “possibly damaging”, or “probably benign” mutations have, respectively, 61%, 17%, 9.8%, and 4.5% probabilities of causing phenotypically detectable damage in the homozygous state. We use these probabilities in the estimation of genome saturation and the probability that individual proteins have been adequately tested for function in specific genetic screens. We estimate the proportion of essential autosomal genes in Mus musculus (C57BL/6J) and show that viable mutations in essential genes are more likely to induce phenotype than mutations in non-essential genes. Programs such as PolyPhen-2 predict the relative severity of damage by missense mutations. Here, Wang et al estimate probabilities that putative null or missense alleles would reduce protein function to cause detectable phenotype by analyzing data from ENU-induced mouse mutations.

The phylum Deinococcus-Thermus is a deeply-branching lineage of bacteria widely recognized as one of the most extremophilic. Members of the Thermus genus are of major interest due to both their bioremediation and biotechnology potentials. However, the molecular mechanisms associated with these key metabolic pathways remain unknown. Reverse-transcription quantitative PCR (RT-qPCR) is a high-throughput means of studying the expression of a large suite of genes over time and under different conditions. The selection of a stably-expressed reference gene is critical when using relative quantification methods, as target gene expression is normalized to expression of the reference gene. However, little information exists as to reference gene selection in extremophiles. This study evaluated 11 candidate reference genes for use with the thermophile Thermus scotoductus when grown under different culture conditions. Based on the combined stability values from BestKeeper and NormFinder software packages, the following are the most appropriate reference genes when comparing: (1) aerobic and anaerobic growth: TSC_c19900, polA2, gyrA, gyrB; (2) anaerobic growth with varied electron acceptors: TSC_c19900, infA, pfk, gyrA, gyrB; (3) aerobic growth with different heating methods: gyrA, gap, gyrB; (4) all conditions mentioned above: gap, gyrA, gyrB. The commonly-employed rpoC does not serve as a reliable reference gene in thermophiles, due to its expression instability across all culture conditions tested here. As extremophiles exhibit a tendency for polyploidy, absolute quantification was employed to determine the ratio of transcript to gene copy number in a subset of the genes. A strong negative correlation was found to exist between ratio and threshold cycle (CT) values, demonstrating that CT changes reflect transcript copy number, and not gene copy number, fluctuations. Even with the potential for polyploidy in extremophiles, the results obtained via absolute quantification indicate that relative quantification is appropriate for RT-qPCR studies with this thermophile.

Recent studies have revealed that antidepressants affect the expression of constitutively expressed \"housekeeping genes\" commonly used as normalizing reference genes in quantitative polymerase chain reaction (qPCR) experiments. There has yet to be an investigation however on the effects of mood-stabilizers on housekeeping gene stability. The current study utilized lymphoblastoid cell lines (LCLs) derived from patients with mood disorders to investigate the effects of a range of doses of lithium (0, 1, 2 and 5mM) and sodium valproate (0, 0.06, 0.03 and 0.6mM) on the stability of 12 housekeeping genes. RNA was extracted from LCLs and qPCR was used to generate cycle threshold (Ct) values which were input into RefFinder analyses. The study revealed drug-specific effects on housekeeping gene stability. The most stable housekeeping genes in LCLs treated: acutely with sodium valproate were ACTB and RPL13A; acutely with lithium were GAPDH and ATP5B; chronically with lithium were ATP5B and CYC1. The stability of GAPDH and B2M were particularly affected by duration of lithium treatment. The study adds to a growing literature that the selection of appropriate housekeeping genes is important for the accurate normalization of target gene expression in experiments investigating the molecular effects of mood disorder pharmacotherapies. Copyright © 2014 John Wiley & Sons, Ltd.

The flatworm species Schmidtea mediterranea and Macrostomum lignano have become new and innovative model organisms in stem cell, regeneration and tissue homeostasis research. Because of their unique stem cell system, (lab) technical advantages and their phylogenetic position within the Metazoa, they are also ideal candidate model organisms for toxicity assays. As stress and biomarker screenings are often performed at the transcriptional level, the aim of this study was to establish a set of reference genes for qPCR experiments for these two model organisms in different stress situations. We examined the transcriptional stability of nine potential reference genes ( actb , tubb , ck2 , cox4 , cys , rpl13 , gapdh , gm2ap , plscr1 ) to assess those that are most stable during altered stress conditions (exposure to carcinogenic metals and salinity stress). The gene expression stability was evaluated by means of geNorm and NormFinder algorithms. Sets of best reference genes in these analyses varied between different stress situations, although gm2ap and actb were stably transcribed during all tested combinations. In order to demonstrate the impact of bad normalisation, the stress-specific gene hsp90 was normalised to different sets of reference genes. In contrast to the normalisation according to GeNorm and NormFinder , normalisation of hsp90 in Macrostomum lignano during cadmium stress did not show a significant difference when normalised to only gapdh . On the other hand an increase of variability was noticed when normalised to all nine tested reference genes together. Testing appropriate reference genes is therefore strongly advisable in every new experimental condition.

Abstract Validation of bactericidal profiles owing to a deficiency of target bacterial molecule provides opportunities to discover antimicrobial drug candidates. In this study, we constructed genetic-engineered Escherichia coli strains, in which the target gene expression is conditionally regulated by a tryptophan promoter, while the target protein expression is regulated by N-end rule-based proteolysis. Among 10 genes, whose correspondent proteins are target candidates of antibiotics for community acquired respiratory tract infection, it was clearly demonstrated that the suppression of DnaB, GlmU, or DnaX results in a bactericidal profile, while the suppression of FabB, PyrG, DnaG, Der, PyrH, Era, or IspA leads to a bacteriostatic profile. This study is the first to predict the antibacterial inhibition profiles of Der, DnaG, DnaX, Era, GlmU, IspA, PyrG, and PyrH, and confirms previous findings for DnaB and FabB. The results suggested that the system constructed in this study is a novel and useful tool to validate whether the target bacterial molecule has appropriate properties as a target of antimicrobial agents.