Explore the vast range of titles available.

Background Genome-scale CRISPR interference (CRISPRi) has been used in human cell lines; however, the features of effective guide RNAs (gRNAs) in different organisms have not been well characterized. Here, we define rules that determine gRNA effectiveness for transcriptional repression in Saccharomyces cerevisiae . Results We create an inducible single plasmid CRISPRi system for gene repression in yeast, and use it to analyze fitness effects of gRNAs under 18 small molecule treatments. Our approach correctly identifies previously described chemical-genetic interactions, as well as a new mechanism of suppressing fluconazole toxicity by repression of the ERG25 gene. Assessment of multiple target loci across treatments using gRNA libraries allows us to determine generalizable features associated with gRNA efficacy. Guides that target regions with low nucleosome occupancy and high chromatin accessibility are clearly more effective. We also find that the best region to target gRNAs is between the transcription start site (TSS) and 200 bp upstream of the TSS. Finally, unlike nuclease-proficient Cas9 in human cells, the specificity of truncated gRNAs (18 nt of complementarity to the target) is not clearly superior to full-length gRNAs (20 nt of complementarity), as truncated gRNAs are generally less potent against both mismatched and perfectly matched targets. Conclusions Our results establish a powerful functional and chemical genomics screening method and provide guidelines for designing effective gRNAs, which consider chromatin state and position relative to the target gene TSS. These findings will enable effective library design and genome-wide programmable gene repression in many genetic backgrounds.

Many cellular functions are mediated by protein–protein interaction networks, which are environment dependent. However, systematic measurement of interactions in diverse environments is required to better understand the relative importance of different mechanisms underlying network dynamics. To investigate environment‐dependent protein complex dynamics, we used a DNA‐barcode‐based multiplexed protein interaction assay in Saccharomyces cerevisiae to measure in vivo abundance of 1,379 binary protein complexes under 14 environments. Many binary complexes (55%) were environment dependent, especially those involving transmembrane transporters. We observed many concerted changes around highly connected proteins, and overall network dynamics suggested that “concerted” protein‐centered changes are prevalent. Under a diauxic shift in carbon source from glucose to ethanol, a mass‐action‐based model using relative mRNA levels explained an estimated 47% of the observed variance in binary complex abundance and predicted the direction of concerted binary complex changes with 88% accuracy. Thus, we provide a resource of yeast protein interaction measurements across diverse environments and illustrate the value of this resource in revealing mechanisms of network dynamics. Synopsis A multiplexed assay measures abundance of 1,379 binary protein complexes in 14 environments. Many environment‐dependent changes were found, enabling exploration of the extent to which network dynamics can be explained by mRNA levels. A DNA‐barcode‐based multiplexed protein interaction assay measured in vivo abundance of 1,379 binary protein complexes under 14 diverse environments in Saccharomyces cerevisiae . More than half of binary complexes were found to be environment‐dependent, especially those among transmembrane transporters. Many binary complexes changed in a concerted, protein‐centric manner, and under a “diauxic” shift in carbon source from glucose to ethanol, mRNA levels predicted many of the observed changes. Graphical Abstract A multiplexed assay measures abundance of 1,379 binary protein complexes in 14 environments. Many environment‐dependent changes were found, enabling exploration of the extent to which network dynamics can be explained by mRNA levels.

Changes in protein–protein interactions that occur in response to environmental cues are difficult to uncover and have been poorly characterized to date. Here we describe a yeast-based assay that allows many binary protein interactions to be assessed in parallel and under various conditions. This method combines molecular barcoding and tag array technology with the murine dihydrofolate reductase-based protein-fragment complementation assay. A total of 238 protein-fragment complementation assay strains, each representing a unique binary protein complex, were tagged with molecular barcodes, pooled, and then interrogated against a panel of 80 diverse small molecules. Our method successfully identified specific disruption of the Hom3:Fpr1 interaction by the immunosuppressant FK506, illustrating the assay's capacity to identify chemical inhibitors of protein–protein interactions. Among the additional findings was specific cellular depletion of the Dst1:Rbp9 complex by the anthracycline drug doxorubicin, but not by the related drug idarubicin. The assay also revealed chemical-induced accumulation of several binary multidrug transporter complexes that largely paralleled increases in transcript levels. Further assessment of two such interactions (Tpo1:Pdr5 and Snq2:Pdr5) in the presence of 1,246 unique chemical compounds revealed a positive correlation between drug lipophilicity and the drug response in yeast.

The low costs of array‐synthesized oligonucleotide libraries are empowering rapid advances in quantitative and synthetic biology. However, high synthesis error rates, uneven representation, and lack of access to individual oligonucleotides limit the true potential of these libraries. We have developed a cost‐effective method called Recombinase Directed Indexing (REDI), which involves integration of a complex library into yeast, site‐specific recombination to index library DNA, and next‐generation sequencing to identify desired clones. We used REDI to generate a library of ~3,300 DNA probes that exhibited > 96% purity and remarkable uniformity (> 95% of probes within twofold of the median abundance). Additionally, we created a collection of ~9,000 individually accessible CRISPR interference yeast strains for > 99% of genes required for either fermentative or respiratory growth, demonstrating the utility of REDI for rapid and cost‐effective creation of strain collections from oligonucleotide pools. Our approach is adaptable to any complex DNA library, and fundamentally changes how these libraries can be parsed, maintained, propagated, and characterized. Synopsis Recombinase Directed Indexing (REDI), a new method that facilitates parsing and purification of array‐synthesized oligonucleotide pools, is presented. REDI is applied to produce a high‐quality DNA probe library and an arrayed collection of CRISPRi strains for essential yeast genes. A protocol and requisite strain resources are developed for Recombinase Directed Indexing (REDI), a method enabling parsing and purifying complex DNA libraries in yeast. The method is used to produce a highly uniform, sequence‐verified pool of ˜3,300 oligonucleotide probes for bacterial detection. The method is also used to create an arrayed collection of ˜9,000 CRISPR interference strains for conditional repression of yeast genes essential for fermentative or respiratory growth. Graphical Abstract Recombinase Directed Indexing (REDI), a new method that facilitates parsing and purification of array‐synthesized oligonucleotide pools, is presented. REDI is applied to produce a high‐quality DNA probe library and an arrayed collection of CRISPRi strains for essential yeast genes.

Background Copper is essential for the survival of aerobic organisms. If copper is not properly regulated in the body however, it can be extremely cytotoxic and genetic mutations that compromise copper homeostasis result in severe clinical phenotypes. Understanding how cells maintain optimal copper levels is therefore highly relevant to human health. Results We found that addition of copper (Cu) to culture medium leads to increased respiratory growth of yeast, a phenotype which we then systematically and quantitatively measured in 5050 homozygous diploid deletion strains. Cu’s positive effect on respiratory growth was quantitatively reduced in deletion strains representing 73 different genes, the function of which identify increased iron uptake as a cause of the increase in growth rate. Conversely, these effects were enhanced in strains representing 93 genes. Many of these strains exhibited respiratory defects that were specifically rescued by supplementing the growth medium with Cu. Among the genes identified are known and direct regulators of copper homeostasis, genes required to maintain low vacuolar pH, and genes where evidence supporting a functional link with Cu has been heretofore lacking. Roughly half of the genes are conserved in man, and several of these are associated with Mendelian disorders, including the Cu-imbalance syndromes Menkes and Wilson’s disease. We additionally demonstrate that pharmacological agents, including the approved drug disulfiram, can rescue Cu-deficiencies of both environmental and genetic origin. Conclusions A functional screen in yeast has expanded the list of genes required for Cu-dependent fitness, revealing a complex cellular system with implications for human health. Respiratory fitness defects arising from perturbations in this system can be corrected with pharmacological agents that increase intracellular copper concentrations.

A method to introduce defined mutations into the yeast genome enables saturation mutagenesis of a gene and genome-scale introduction of genetic variants. Our understanding of how genotype controls phenotype is limited by the scale at which we can precisely alter the genome and assess the phenotypic consequences of each perturbation. Here we describe a CRISPR–Cas9-based method for multiplexed accurate genome editing with short, trackable, integrated cellular barcodes (MAGESTIC) in Saccharomyces cerevisiae. MAGESTIC uses array-synthesized guide–donor oligos for plasmid-based high-throughput editing and features genomic barcode integration to prevent plasmid barcode loss and to enable robust phenotyping. We demonstrate that editing efficiency can be increased more than fivefold by recruiting donor DNA to the site of breaks using the LexA–Fkh1p fusion protein. We performed saturation editing of the essential gene SEC14 and identified amino acids critical for chemical inhibition of lipid signaling. We also constructed thousands of natural genetic variants, characterized guide mismatch tolerance at the genome scale, and ascertained that cryptic Pol III termination elements substantially reduce guide efficacy. MAGESTIC will be broadly useful to uncover the genetic basis of phenotypes in yeast.

A subset of individuals exposed to Mycobacterium tuberculosis ( Mtb ) that we refer to as ‘resisters’ (RSTR) show evidence of IFN-γ − T cell responses to Mtb -specific antigens despite serially negative results on clinical testing. Here we found that Mtb -specific T cells in RSTR were clonally expanded, confirming the priming of adaptive immune responses following Mtb exposure. RSTR CD4 + T cells showed enrichment of T H 17 and regulatory T cell-like functional programs compared to Mtb -specific T cells from individuals with latent Mtb infection. Using public datasets, we showed that these T H 17 cell-like functional programs were associated with lack of progression to active tuberculosis among South African adolescents with latent Mtb infection and with bacterial control in nonhuman primates. Our findings suggested that RSTR may successfully control Mtb following exposure and immune priming and established a set of T cell biomarkers to facilitate further study of this clinical phenotype. Seshadri, Davis and colleagues show that individuals who do not develop an infection with Mycobacterium tuberculosis ( Mtb ), despite exposure to the bacteria and expansion of CD4 + T cell clones specific to Mtb antigens, show enrichment of T H 17 cell and T regulatory functional programs.

Genome-wide characterization of the in vivo cellular response to perturbation is fundamental to understanding how cells survive stress. Identifying the proteins and pathways perturbed by small molecules affects biology and medicine by revealing the mechanisms of drug action. We used a yeast chemogenomics platform that quantifies the requirement for each gene for resistance to a compound in vivo to profile 3250 small molecules in a systematic and unbiased manner. We identified 317 compounds that specifically perturb the function of 121 genes and characterized the mechanism of specific compounds. Global analysis revealed that the cellular response to small molecules is limited and described by a network of 45 major chemogenomic signatures. Our results provide a resource for the discovery of functional interactions among genes, chemicals, and biological processes.

Bioactive compounds are widely used to modulate protein function and can serve as important leads for drug development. Identifying the in vivo targets of these compounds remains a challenge. Using yeast, we integrated three genome-wide gene-dosage assays to measure the effect of small molecules in vivo . A single TAG microarray was used to resolve the fitness of strains derived from pools of (i) homozygous deletion mutants, (ii) heterozygous deletion mutants and (iii) genomic library transformants. We demonstrated, with eight diverse reference compounds, that integration of these three chemogenomic profiles improves the sensitivity and specificity of small-molecule target identification. We further dissected the mechanism of action of two protein phosphatase inhibitors and in the process developed a framework for the rational design of multidrug combinations to sensitize cells with specific genotypes more effectively. Finally, we applied this platform to 188 novel synthetic chemical compounds and identified both potential targets and structure-activity relationships.