Quantitative phenotyping via deep barcode sequencing

Screening the Saccharomyces cerevisiae Nonessential Gene Deletion Library Reveals Diverse Mechanisms of Action for Antifungal Plant Defensins

Plant defensins are a large family of proteins, most of which have antifungal activity against a broad spectrum of fungi. However, little is known about how they exert their activity. The mechanisms of action of only a few members of the family have been investigated and, in most cases, there are still a number of unknowns. To gain a better understanding of the antifungal mechanisms of a set of four defensins, NaD1, DmAMP1, NbD6, and SBI6, we screened a pooled collection of the nonessential gene deletion set of Saccharomyces cerevisiae Strains with increased or decreased ability to survive defensin treatment were identified based on the relative abundance of the strain-specific barcode as determined by MiSeq next-generation sequencing. Analysis of the functions of genes that are deleted in strains with differential growth in the presence of defensin provides insight into the mechanism of action. The screen identified a novel role for the vacuole in the mechanisms of action for defensins NbD6 and SBI6. The effect of these defensins on vacuoles was further confirmed by using confocal microscopy in both S. cerevisiae and the cereal pathogen Fusarium graminearum These results demonstrate the utility of this screening method to identify novel mechanisms of action for plant defensins.

Decyl Gallate as a Possible Inhibitor of N-Glycosylation Process in Paracoccidioides lutzii

The available antifungal therapeutic arsenal is limited. The search for alternative drugs with fewer side effects and new targets remains a major challenge. Decyl gallate (G14) is a derivative of gallic acid with a range of biological activities and broad-spectrum antifungal activity. Previously, our group demonstrated the promising anti-Paracoccidioides activity of G14. In this work, to evaluate the antifungal characteristics of G14 for Paracoccidioides lutzii, a chemical-genetic interaction analysis was conducted on a Saccharomyces cerevisiae model. N-glycosylation and/or the unfolded protein response pathway was identified as a high-confidence process for drug target prediction. The overactivation of unfolded protein response (UPR) signaling was confirmed using this model with IRE1/ATF6/PERK genes tagged with green fluorescent protein (GFP). In P. lutzii, this prediction was confirmed by the low activity of glycosylated enzymes [α-(1,3)-glucanase, N-acetyl-β-d-glucosaminidase (NAGase), and α-(1,4)-amylase], by hyperexpression of genes involved with the UPR and glycosylated enzymes, and by the reduction in the amounts of glycosylated proteins and chitin. All of these components are involved in fungal cell wall integrity and are dependent on the N-glycosylation process. This loss of integrity was confirmed by the reduction in mitochondrial activity, impaired budding, enhancement of wall permeability, and a decrease in viability. These events led to a reduction of the ability of fungi to adhere on human lung epithelial cells (A549) in vitro Therefore, G14 may have an important role in balancing the inflammatory reaction caused by fungal infection, without interfering with the microbicidal activity of nitric oxide. This work provides new information on the activity of G14, a potential anti-Paracoccidioides compound.

Global Transcriptional Programs in Archaea Share Features with the Eukaryotic Environmental Stress Response

The environmental stress response (ESR), a global transcriptional program originally identified in yeast, is characterized by a rapid and transient transcriptional response composed of large, oppositely regulated gene clusters. Genes induced during the ESR encode core components of stress tolerance, macromolecular repair, and maintenance of homeostasis. In this review, we investigate the possibility for conservation of the ESR across the eukaryotic and archaeal domains of life. We first re-analyze existing transcriptomics data sets to illustrate that a similar transcriptional response is identifiable in Halobacterium salinarum, an archaeal model organism. To substantiate the archaeal ESR, we calculated gene-by-gene correlations, gene function enrichment, and comparison of temporal dynamics. We note reported examples of variation in the ESR across fungi, then synthesize high-level trends present in expression data of other archaeal species. In particular, we emphasize the need for additional high-throughput time series expression data to further characterize stress-responsive transcriptional programs in the Archaea. Together, this review explores an open question regarding features of global transcriptional stress response programs shared across domains of life.

Chemogenomic study of gemcitabine using Saccharomyces cerevisiae as model cell-molecular insights about chemoresistance

Gemcitabine (GEM) is the drug used as first line to treat pancreatic cancer, one of the most devastating human tumors. This peculiar type of tumor develops resistance to several drugs, including GEM, due to its desmoplastic reaction and other features. The GEM chemoresistance has been investigated at molecular level aiming to find a pathway whose inhibition or activation should overcome it. Through next-generation sequencing was performed a chemogenomic assay of GEM using Saccharomyces cerevisiae as model cell and the results showed that more than 40% of genes related to GEM response in yeast possess unknown or dubious function. We choose two yeast mutants to individually validate the fitness defect results observed by chemogenomic assay, Δhmt1 and Δcsi1, and it was found that in addition to some already described pathways involved in GEM resistance, cells deficient in deneddylation enzyme Cop9 Signalosome Interactor 1 (Csi1p) presented a high sensitivity to GEM. This was confirmed by individual growth analyses of Δcsi1 cells exposed to GEM, and this phenotype was reverted with CSI1 complementation gene. Csi1p is a well-characterized homolog equivalent to human Csn6 subunit of COP9 signalosome (CSN) involved in deneddylation process. We highlighted too that epigenetic alterations, such as methylation mediated by protein arginine methyltransferase 1, play an important role in regulating gemcitabine treatment resistance. Our results point out new unexplored molecular pathways that can be used to overcome GEM resistance: the inhibition of CSN and the arginine methyltransferase activities.

High-throughput ultrastructure screening using electron microscopy and fluorescent barcoding

Genetic screens using high-throughput fluorescent microscopes have generated large datasets, contributing many cell biological insights. Such approaches cannot tackle questions requiring knowledge of ultrastructure below the resolution limit of fluorescent microscopy. Electron microscopy (EM) reveals detailed cellular ultrastructure but requires time-consuming sample preparation, limiting throughput. Here we describe a robust method for screening by high-throughput EM. Our approach uses combinations of fluorophores as barcodes to uniquely mark each cell type in mixed populations and correlative light and EM (CLEM) to read the barcode of each cell before it is imaged by EM. Coupled with an easy-to-use software workflow for correlation, segmentation, and computer image analysis, our method, called "MultiCLEM," allows us to extract and analyze multiple cell populations from each EM sample preparation. We demonstrate several uses for MultiCLEM with 15 different yeast variants. The methodology is not restricted to yeast, can be scaled to higher throughput, and can be used in multiple ways to enable EM to become a powerful screening technique.

Genetic dissection of a Leishmania flagellar proteome demonstrates requirement for directional motility in sand fly infections

The protozoan parasite Leishmania possesses a single flagellum, which is remodelled during the parasite’s life cycle from a long motile flagellum in promastigote forms in the sand fly to a short immotile flagellum in amastigotes residing in mammalian phagocytes. This study examined the protein composition and in vivo function of the promastigote flagellum. Protein mass spectrometry and label free protein enrichment testing of isolated flagella and deflagellated cell bodies defined a flagellar proteome for L. mexicana promastigote forms (available via ProteomeXchange with identifier PXD011057). This information was used to generate a CRISPR-Cas9 knockout library of 100 mutants to screen for flagellar defects. This first large-scale knockout screen in a Leishmania sp. identified 56 mutants with altered swimming speed (52 reduced and 4 increased) and defined distinct mutant categories (faster swimmers, slower swimmers, slow uncoordinated swimmers and paralysed cells, including aflagellate promastigotes and cells with curled flagella and disruptions of the paraflagellar rod). Each mutant was tagged with a unique 17-nt barcode, providing a simple barcode sequencing (bar-seq) method for measuring the relative fitness of L. mexicana mutants in vivo. In mixed infections of the permissive sand fly vector Lutzomyia longipalpis, paralysed promastigotes and uncoordinated swimmers were severely diminished in the fly after defecation of the bloodmeal. Subsequent examination of flies infected with a single paralysed mutant lacking the central pair protein PF16 or an uncoordinated swimmer lacking the axonemal protein MBO2 showed that these promastigotes did not reach anterior regions of the fly alimentary tract. These data show that L. mexicana need directional motility for successful colonisation of sand flies.

Leishmania are protozoan parasites, transmitted between mammals by the bite of phlebotomine sand flies. Promastigote forms in the sand fly have a long flagellum, which is motile and used for anchoring the parasites to prevent clearance with the digested blood meal remnants. To dissect flagellar functions and their importance in life cycle progression, we generated here a comprehensive list of >300 flagellar proteins and produced a CRISPR-Cas9 gene knockout library of 100 mutant Leishmania. We studied their behaviour in vitro before examining their fate in the sand fly Lutzomyia longipalpis. Measuring mutant swimming speeds showed that about half behaved differently compared to the wild type: a few swam faster, many slower and some were completely paralysed. We also found a group of uncoordinated swimmers. To test whether flagellar motility is required for parasite migration from the fly midgut to the foregut from where they reach the next host, we infected sand flies with a mixed mutant population. Each mutant carried a unique tag and tracking these tags up to nine days after infection showed that paralysed and uncoordinated Leishmania were rapidly lost from flies. These data indicate that directional swimming is important for successful colonisation of sand flies.

Large-scale chemical-genetics yields new M. tuberculosis inhibitor classes

New antibiotics are needed to combat rising levels of resistance, with new Mycobacterium tuberculosis (Mtb) drugs having the highest priority. However, conventional whole-cell and biochemical antibiotic screens have failed. Here we develop a strategy termed PROSPECT (primary screening of strains to prioritize expanded chemistry and targets), in which we screen compounds against pools of strains depleted of essential bacterial targets. We engineered strains that target 474 essential Mtb genes and screened pools of 100-150 strains against activity-enriched and unbiased compound libraries, probing more than 8.5 million chemical-genetic interactions. Primary screens identified over tenfold more hits than screening wild-type Mtb alone, with chemical-genetic interactions providing immediate, direct target insights. We identified over 40 compounds that target DNA gyrase, the cell wall, tryptophan, folate biosynthesis and RNA polymerase, as well as inhibitors that target EfpA. Chemical optimization yielded EfpA inhibitors with potent wild-type activity, thus demonstrating the ability of PROSPECT to yield inhibitors against targets that would have eluded conventional drug discovery.

Measuring sequencer size bias using REcount: a novel method for highly accurate Illumina sequencing-based quantification

Quantification of DNA sequence tags from engineered constructs such as plasmids, transposons, or other transgenes underlies many functional genomics measurements. Typically, such measurements rely on PCR followed by next-generation sequencing. However, PCR amplification can introduce significant quantitative error. We describe REcount, a novel PCR-free direct counting method. Comparing measurements of defined plasmid pools to droplet digital PCR data demonstrates that REcount is highly accurate and reproducible. We use REcount to provide new insights into clustering biases due to molecule length across different Illumina sequencers and illustrate the impacts on interpretation of next-generation sequencing data and the economics of data generation.

Using BEAN-counter to quantify genetic interactions from multiplexed barcode sequencing experiments

The construction of genome-wide mutant collections has enabled high-throughput, high-dimensional quantitative characterization of gene and chemical function, particularly via genetic and chemical-genetic interaction experiments. As the throughput of such experiments increases with improvements in sequencing technology and sample multiplexing, appropriate tools must be developed to handle the large volume of data produced. Here, we describe how to apply our approach to high-throughput, fitness-based profiling of pooled mutant yeast collections using the BEAN-counter software pipeline (Barcoded Experiment Analysis for Next-generation sequencing) for analysis. The software has also successfully processed data from Schizosaccharomyces pombe, Escherichia coli, and Zymomonas mobilis mutant collections. We provide general recommendations for the design of large-scale, multiplexed barcode sequencing experiments. The procedure outlined here was used to score interactions for ~4 million chemical-by-mutant combinations in our recently published chemical-genetic interaction screen of nearly 14,000 chemical compounds across seven diverse compound collections. Here we selected a representative subset of these data on which to demonstrate our analysis pipeline. BEAN-counter is open source, written in Python, and freely available for academic use. Users should be proficient at the command line; advanced users who wish to analyze larger datasets with hundreds or more conditions should also be familiar with concepts in analysis of high-throughput biological data. BEAN-counter encapsulates the knowledge we have accumulated from, and successfully applied to, our multiplexed, pooled barcode sequencing experiments. This protocol will be useful to those interested in generating their own high-dimensional, quantitative characterizations of gene or chemical function in a high-throughput manner.

Iterative screening methodology enables isolation of strains with improved properties for a FACS-based screen and increased L-DOPA production

Optimizing microbial hosts for the large-scale production of valuable metabolites often requires multiple mutations and modifications to the host's genome. We describe a three-round screen for increased L-DOPA production in S. cerevisiae using FACS enrichment of an enzyme-coupled biosensor for L-DOPA. Multiple rounds of screening were enabled by a single build of a barcoded in vitro transposon-mediated disruption library. New background strains for screening were built for each iteration using results from previous iterations. The same in vitro transposon-mediated disruption library was integrated by homologous recombination into new background strains in each round of screening. Compared with creating new transposon insertions in each round, this method takes less time and saves the cost of additional sequencing to characterize transposon insertion sites. In the first two rounds of screening, we identified deletions that improved biosensor compartmentalization and, consequently, improved our ability to screen for L-DOPA production. In a final round, we discovered that deletion of heme oxygenase (HMX1) increases total heme concentration and increases L-DOPA production, using dopamine measurement as a proxy. We further demonstrated that deleting HMX1 may represent a general strategy for P450 function improvement by improving activity of a second P450 enzyme, BM3, which performs a distinct reaction.

Can Saccharomyces cerevisiae keep up as a model system in fungal azole susceptibility research?

The difficulty of manipulation and limited availability of genetic tools for use in many pathogenic fungi hamper fast and adequate investigation of cellular metabolism and consequent possibilities for antifungal therapies. S. cerevisiae is a model organism that is used to study many eukaryotic systems. In this review, we analyse the potency and relevance of this model system in investigating fungal susceptibility to azole drugs. Although many of the concepts apply to multiple pathogenic fungi, for the sake of simplicity, we will focus on the validity of using S. cerevisiae as a model organism for two Candida species, C. albicans and C. glabrata. Apart from the general benefits, we explore how S. cerevisiae can specifically be used to improve our knowledge on azole drug resistance and enables fast and efficient screening for novel drug targets in combinatorial therapy. We consider the shortcomings of the model system, yet conclude that it is still opportune to use S. cerevisiae as a model system for pathogenic fungi in this era.

Novel Discovery of LINE-1 in a Korean Individual by a Target Enrichment Method

Long interspersed element-1 (LINE-1 or L1) is an autonomous retrotransposon, which is capable of inserting into a new region of genome. Previous studies have reported that these elements lead to genomic variations and altered functions by affecting gene expression and genetic networks. Mounting evidence strongly indicates that genetic diseases or various cancers can occur as a result of retrotransposition events that involve L1s. Therefore, the development of methodologies to study the structural variations and interpersonal insertion polymorphisms by L1 element-associated changes in an individual genome is invaluable. In this study, we applied a systematic approach to identify human-specific L1s (i.e., L1Hs) through the bioinformatics analysis of high-throughput next-generation sequencing data. We identified 525 candidates that could be inferred to carry non-reference L1Hs in a Korean individual genome (KPGP9). Among them, we randomly selected 40 candidates and validated that approximately 92.5% of non-reference L1Hs were inserted into a KPGP9 genome. In addition, unlike conventional methods, our relatively simple and expedited approach was highly reproducible in confirming the L1 insertions. Taken together, our findings strongly support that the identification of non-reference L1Hs by our novel target enrichment method demonstrates its future application to genomic variation studies on the risk of cancer and genetic disorders.

Dual-barcoded shotgun expression library sequencing for high-throughput characterization of functional traits in bacteria

A major challenge in genomics is the knowledge gap between sequence and its encoded function. Gain-of-function methods based on gene overexpression are attractive avenues for phenotype-based functional screens, but are not easily applied in high-throughput across many experimental conditions. Here, we present Dual Barcoded Shotgun Expression Library Sequencing (Dub-seq), a method that uses random DNA barcodes to greatly increase experimental throughput. As a demonstration of this approach, we construct a Dub-seq library with Escherichia coli genomic DNA, performed 155 genome-wide fitness assays in 52 experimental conditions, and identified overexpression phenotypes for 813 genes. We show that Dub-seq data is reproducible, accurately recapitulates known biology, and identifies hundreds of novel gain-of-function phenotypes for E. coli genes, a subset of which we verified with assays of individual strains. Dub-seq provides complementary information to loss-of-function approaches and will facilitate rapid and systematic functional characterization of microbial genomes.

Gain of function methods based on gene overexpression are not easily applied to high-throughput screening across different experimental conditions. Here, the authors present Dub-seq, which separates overexpression library characterization from functional screening and uses random DNA barcodes to increase the experimental throughput.

Epi-ID: Systematic and Direct Screening for Chromatin Regulators in Yeast by Barcode-ChIP-Seq

The assembly and regulation of chromatin requires coordinated activity of multiple mechanisms. Many factors feed into signaling networks that control the epigenome of a cell. It is this complexity that makes understanding the layers of epigenetic regulation a challenge. Genetic screens have been indispensable for studying chromatin processes. However, they can be laborious and the readout for chromatin changes is often indirect. Epi-ID is a screening strategy in yeast that enables the direct assessment of chromatin status in thousands of gene mutants in parallel. Epi-ID takes advantage of DNA sequences called DNA barcodes that are introduced into a library of yeast knockout mutants at a common chromosomal location in the genome. Chromatin immunoprecipitation on pools of barcoded mutant strains followed by barcode counting by high throughput sequencing will report on the abundance of the chromatin mark of interest in each mutant strain. Epi-ID is applicable to a wide range of chromatin proteins and modifications that are present and can be immunoprecipitated at or around the barcoded region.

Inducible Cell Fusion Permits Use of Competitive Fitness Profiling in the Human Pathogenic Fungus Aspergillus fumigatus

Antifungal agents directed against novel therapeutic targets are required for treating invasive, chronic, and allergic Aspergillus infections. Competitive fitness profiling technologies have been used in a number of bacterial and yeast systems to identify druggable targets; however, the development of similar systems in filamentous fungi is complicated by the fact that they undergo cell fusion and heterokaryosis. Here, we demonstrate that cell fusion in Aspergillus fumigatus under standard culture conditions is not predominately constitutive, as with most ascomycetes, but can be induced by a range of extracellular stressors. Using this knowledge, we have developed a barcode-free genetic profiling system that permits high-throughput parallel determination of strain fitness in a collection of diploid A. fumigatus mutants. We show that heterozygous cyp51A and arf2 null mutants have reduced fitness in the presence of itraconazole and brefeldin A, respectively, and a heterozygous atp17 null mutant is resistant to brefeldin A.

A collection of barcoded natural isolates of Saccharomyces paradoxus to study microbial evolutionary ecology

While the use of barcoded collections of laboratory microorganisms and the development of barcode-based cell tracking are rapidly developing in genetics and genomics research, tools to track natural populations are still lacking. The yeast Saccharomyces paradoxus is an emergent microbial model in ecology and evolution. More than five allopatric and sympatric lineages have been identified and hundreds of strains have been isolated for this species, allowing to assess the impact of natural diversity on complex traits. We constructed a collection of 550 barcoded and traceable strains of S. paradoxus, including all three North American lineages SpB, SpC, and SpC*. These strains are diploid, many have their genome fully sequenced and are barcoded with a unique 20 bp sequence that allows their identification and quantification. This yeast collection is functional for competitive experiments in pools as the barcodes allow to measure each lineage's and individual strains' fitness in common conditions. We used this tool to demonstrate that in the tested conditions, there are extensive genotype-by-environment interactions for fitness among S. paradoxus strains, which reveals complex evolutionary potential in variable environments. This barcoded collection provides a valuable resource for ecological genomics studies that will allow gaining a better understanding of S. paradoxus evolution and fitness-related traits.

Genomic, Phenotypic, and Virulence Analysis of Streptococcus sanguinis Oral and Infective-Endocarditis Isolates

Streptococcus sanguinis, an abundant and benign inhabitant of the oral cavity, is an important etiologic agent of infective endocarditis (IE), particularly in people with predisposing cardiac valvular damage. Although commonly isolated from patients with IE, little is known about the factors that make any particular S. sanguinis isolate more virulent than another or, indeed, whether significant differences in virulence exist among isolates. In this study, we compared the genomes of a collection of S. sanguinis strains comprised of both oral isolates and bloodstream isolates from patients diagnosed with IE. Oral and IE isolates could not be distinguished by phylogenetic analyses, and we did not succeed in identifying virulence genes unique to the IE strains. We then investigated the virulence of these strains in a rabbit model of IE using a variation of the Bar-seq (barcode sequencing) method wherein we pooled the strains and used Illumina sequencing to count unique barcodes that had been inserted into each isolate at a conserved intergenic region. After we determined that several of the genome sequences were misidentified in GenBank, our virulence results were used to inform our bioinformatic analyses, identifying genes that may explain the heterogeneity in virulence. We further characterized these strains by assaying for phenotypes potentially contributing to virulence. Neither strain competition via bacteriocin production nor biofilm formation showed any apparent relationship with virulence. Increased cell-associated manganese was, however, correlated with blood isolates. These results, combined with additional phenotypic assays, suggest that S. sanguinis virulence is highly variable and results from multiple genetic factors.

Comparative functional genomic screens of three yeast deletion collections reveal unexpected effects of genotype in response to diverse stress

The Yeast Knockout (YKO) collection has provided a wealth of functional annotations from genome-wide screens. An unintended consequence is that 76% of gene annotations derive from one genotype. The nutritional auxotrophies in the YKO, in particular, have phenotypic consequences. To address this issue, ‘prototrophic’ versions of the YKO collection have been constructed, either by introducing a plasmid carrying wild-type copies of the auxotrophic markers (Plasmid-Borne, PB_prot) or by backcrossing (Backcrossed, BC_prot) to a wild-type strain. To systematically assess the impact of the auxotrophies, genome-wide fitness profiles of prototrophic and auxotrophic collections were compared across diverse drug and environmental conditions in 250 experiments. Our quantitative profiles uncovered broad impacts of genotype on phenotype for three deletion collections, and revealed genotypic and strain-construction-specific phenotypes. The PB_prot collection exhibited fitness defects associated with plasmid maintenance, while BC_prot fitness profiles were compromised due to strain loss from nutrient selection steps during strain construction. The repaired prototrophic versions of the YKO collection did not restore wild-type behaviour nor did they clarify gaps in gene annotation resulting from the auxotrophic background. To remove marker bias and expand the experimental scope of deletion libraries, construction of a bona fide prototrophic collection from a wild-type strain will be required.

Cellular barcoding: lineage tracing, screening and beyond

Cellular barcoding is a technique in which individual cells are labeled with unique nucleic acid sequences, termed barcodes, so that they can be tracked through space and time. Cellular barcoding can be used to track millions of cells in parallel, and thus is an efficient approach for investigating heterogeneous populations of cells. Over the past 25 years, cellular barcoding has been used for fate mapping, lineage tracing and high-throughput screening, and has led to important insights into developmental biology and gene function. Driven by plummeting sequencing costs and the power of synthetic biology, barcoding is now expanding beyond traditional applications and into diverse fields such as neuroanatomy and the recording of cellular activity. In this review, we discuss the fundamental principles of cellular barcoding, including the underlying mathematics, and its applications in both new and established fields.

Predicting bioprocess targets of chemical compounds through integration of chemical-genetic and genetic interactions

Chemical-genetic interactions–observed when the treatment of mutant cells with chemical compounds reveals unexpected phenotypes–contain rich functional information linking compounds to their cellular modes of action. To systematically identify these interactions, an array of mutants is challenged with a compound and monitored for fitness defects, generating a chemical-genetic interaction profile that provides a quantitative, unbiased description of the cellular function(s) perturbed by the compound. Genetic interactions, obtained from genome-wide double-mutant screens, provide a key for interpreting the functional information contained in chemical-genetic interaction profiles. Despite the utility of this approach, integrative analyses of genetic and chemical-genetic interaction networks have not been systematically evaluated. We developed a method, called CG-TARGET (Chemical Genetic Translation via A Reference Genetic nETwork), that integrates large-scale chemical-genetic interaction screening data with a genetic interaction network to predict the biological processes perturbed by compounds. In a recent publication, we applied CG-TARGET to a screen of nearly 14,000 chemical compounds in Saccharomyces cerevisiae, integrating this dataset with the global S. cerevisiae genetic interaction network to prioritize over 1500 compounds with high-confidence biological process predictions for further study. We present here a formal description and rigorous benchmarking of the CG-TARGET method, showing that, compared to alternative enrichment-based approaches, it achieves similar or better accuracy while substantially improving the ability to control the false discovery rate of biological process predictions. Additional investigation of the compatibility of chemical-genetic and genetic interaction profiles revealed that one-third of observed chemical-genetic interactions contributed to the highest-confidence biological process predictions and that negative chemical-genetic interactions overwhelmingly formed the basis of these predictions. We also present experimental validations of CG-TARGET-predicted tubulin polymerization and cell cycle progression inhibitors. Our approach successfully demonstrates the use of genetic interaction networks in the high-throughput functional annotation of compounds to biological processes.

Understanding how chemical compounds affect biological systems is of paramount importance as pharmaceutical companies strive to develop life-saving medicines, governments seek to regulate the safety of consumer products and agrichemicals, and basic scientists continue to study the fundamental inner workings of biological organisms. One powerful approach to characterize the effects of chemical compounds in living cells is chemical-genetic interaction screening. Using this approach, a collection of cells–each with a different defined genetic perturbation–is tested for sensitivity or resistance to the presence of a compound, resulting in a quantitative profile describing the functional effects of that compound on the cells. The work presented here describes our efforts to integrate compounds’ chemical-genetic interaction profiles with reference genetic interaction profiles containing information on gene function to predict the cellular processes perturbed by the compounds. We focused on specifically developing a method that could scale to perform these functional predictions for large collections of thousands of screened compounds and robustly control the false discovery rate. With chemical-genetic and genetic interaction screens now underway in multiple species including human cells, the method described here can be generally applied to enable the characterization of compounds’ effects across the tree of life.

Mutation Analysis of Synthetic DNA Barcodes in a Fission Yeast Gene Deletion Library by Sanger Sequencing

Incorporation of unique barcodes into fission yeast gene deletion collections has enabled the identification of gene functions by growth fitness analysis. For fine tuning, it is important to examine barcode sequences, because mutations arise during strain construction. Out of 8,708 barcodes (4,354 strains) covering 88.5% of all 4,919 open reading frames, 7,734 barcodes (88.8%) were validated as high-fidelity to be inserted at the correct positions by Sanger sequencing. Sequence examination of the 7,734 high-fidelity barcodes revealed that 1,039 barcodes (13.4%) deviated from the original design. In total, 1,284 mutations (mutation rate of 16.6%) exist within the 1,039 mutated barcodes, which is comparable to budding yeast (18%). When the type of mutation was considered, substitutions accounted for 845 mutations (10.9%), deletions accounted for 319 mutations (4.1%), and insertions accounted for 121 mutations (1.6%). Peculiarly, the frequency of substitutions (67.6%) was unexpectedly higher than in budding yeast (∼28%) and well above the predicted error of Sanger sequencing (∼2%), which might have arisen during the solid-phase oligonucleotide synthesis and PCR amplification of the barcodes during strain construction. When the mutation rate was analyzed by position within 20-mer barcodes using the 1,284 mutations from the 7,734 sequenced barcodes, there was no significant difference between up-tags and down-tags at a given position. The mutation frequency at a given position was similar at most positions, ranging from 0.4% (32/7,734) to 1.1% (82/7,734), except at position 1, which was highest (3.1%), as in budding yeast. Together, well-defined barcode sequences, combined with the next-generation sequencing platform, promise to make the fission yeast gene deletion library a powerful tool for understanding gene function.

Transition between fermentation and respiration determines history-dependent behavior in fluctuating carbon sources

Cells constantly adapt to environmental fluctuations. These physiological changes require time and therefore cause a lag phase during which the cells do not function optimally. Interestingly, past exposure to an environmental condition can shorten the time needed to adapt when the condition re-occurs, even in daughter cells that never directly encountered the initial condition. Here, we use the molecular toolbox of Saccharomyces cerevisiae to systematically unravel the molecular mechanism underlying such history-dependent behavior in transitions between glucose and maltose. In contrast to previous hypotheses, the behavior does not depend on persistence of proteins involved in metabolism of a specific sugar. Instead, presence of glucose induces a gradual decline in the cells' ability to activate respiration, which is needed to metabolize alternative carbon sources. These results reveal how trans-generational transitions in central carbon metabolism generate history-dependent behavior in yeast, and provide a mechanistic framework for similar phenomena in other cell types.

Experimental Design, Population Dynamics, and Diversity in Microbial Experimental Evolution

In experimental evolution, laboratory-controlled conditions select for the adaptation of species, which can be monitored in real time. Despite the current popularity of such experiments, nature's most pervasive biological force was long believed to be observable only on time scales that transcend a researcher's life-span, and studying evolution by natural selection was therefore carried out solely by comparative means. Eventually, microorganisms' propensity for fast evolutionary changes proved us wrong, displaying strong evolutionary adaptations over a limited time, nowadays massively exploited in laboratory evolution experiments. Here, we formulate a guide to experimental evolution with microorganisms, explaining experimental design and discussing evolutionary dynamics and outcomes and how it is used to assess ecoevolutionary theories, improve industrially important traits, and untangle complex phenotypes. Specifically, we give a comprehensive overview of the setups used in experimental evolution. Additionally, we address population dynamics and genetic or phenotypic diversity during evolution experiments and expand upon contributing factors, such as epistasis and the consequences of (a)sexual reproduction. Dynamics and outcomes of evolution are most profoundly affected by the spatiotemporal nature of the selective environment, where changing environments might lead to generalists and structured environments could foster diversity, aided by, for example, clonal interference and negative frequency-dependent selection. We conclude with future perspectives, with an emphasis on possibilities offered by fast-paced technological progress. This work is meant to serve as an introduction to those new to the field of experimental evolution, as a guide to the budding experimentalist, and as a reference work to the seasoned expert.

A simple and inexpensive quantitative technique for determining chemical sensitivity in Saccharomyces cerevisiae

Chemical sensitivity, growth inhibition in response to a chemical, is a powerful phenotype that can reveal insight into diverse cellular processes. Chemical sensitivity assays are used in nearly every model system, however the yeast Saccharomyces cerevisiae provides a particularly powerful platform for discovery and mechanistic insight from chemical sensitivity assays. Here we describe a simple and inexpensive approach to determine chemical sensitivity quantitatively in yeast in the form of half maximal inhibitory concentration (IC50) using common laboratory equipment. We demonstrate the utility of this method using chemicals commonly used to monitor changes in membrane traffic. When compared to traditional agar-based plating methods, this method is more sensitive and can detect defects not apparent using other protocols. Additionally, this method reduces the experimental protocol from five days to 18 hours for the toxic amino acid canavanine. Furthermore, this method provides reliable results using lower amounts of chemicals. Finally, this method is easily adapted to additional chemicals as demonstrated with an engineered system that activates the spindle assembly checkpoint in response to rapamycin with differing efficiencies. This approach provides researchers with a cost-effective method to perform chemical genetic profiling without specialized equipment.

Precise, automated control of conditions for high-throughput growth of yeast and bacteria with eVOLVER

Precise control over microbial cell growth conditions could enable detection of minute phenotypic changes, which would improve our understanding of how genotypes are shaped by adaptive selection. Although automated cell-culture systems such as bioreactors offer strict control over liquid culture conditions, they often do not scale to high-throughput or require cumbersome redesign to alter growth conditions. We report the design and validation of eVOLVER, a scalable DIY framework that can be configured to carry out high-throughput growth experiments in molecular evolution, systems biology, and microbiology. We perform high-throughput evolution of yeast across systematically varied population density niches to show how eVOLVER can precisely characterize adaptive niches. We describe growth selection using time-varying temperature programs on a genome-wide yeast knockout library to identify strains with altered sensitivity to changes in temperature magnitude or frequency. Inspired by large-scale integration of electronics and microfluidics, we also demonstrate millifluidic multiplexing modules that enable multiplexed media routing, cleaning, vial-to-vial transfers and automated yeast mating.

Systematic identification of factors mediating accelerated mRNA degradation in response to changes in environmental nitrogen

Cellular responses to changing environments frequently involve rapid reprogramming of the transcriptome. Regulated changes in mRNA degradation rates can accelerate reprogramming by clearing or stabilizing extant transcripts. Here, we measured mRNA stability using 4-thiouracil labeling in the budding yeast Saccharomyces cerevisiae during a nitrogen upshift and found that 78 mRNAs are subject to destabilization. These transcripts include Nitrogen Catabolite Repression (NCR) and carbon metabolism mRNAs, suggesting that mRNA destabilization is a mechanism for targeted reprogramming of the transcriptome. To explore the molecular basis of destabilization we implemented a SortSeq approach to screen the pooled deletion collection library for trans factors that mediate rapid GAP1 mRNA repression. We combined low-input multiplexed Barcode sequencing with branched-DNA single-molecule mRNA FISH and Fluorescence-activated cell sorting (BFF) to identify the Lsm1-7p/Pat1p complex and general mRNA decay machinery as important for GAP1 mRNA clearance. We also find that the decapping modulators EDC3 and SCD6, translation factor eIF4G2, and the 5' UTR of GAP1 are factors that mediate rapid repression of GAP1 mRNA, suggesting that translational control may impact the post-transcriptional fate of mRNAs in response to environmental changes.

Mutant phenotypes for thousands of bacterial genes of unknown function

One-third of all protein-coding genes from bacterial genomes cannot be annotated with a function. Here, to investigate the functions of these genes, we present genome-wide mutant fitness data from 32 diverse bacteria across dozens of growth conditions. We identified mutant phenotypes for 11,779 protein-coding genes that had not been annotated with a specific function. Many genes could be associated with a specific condition because the gene affected fitness only in that condition, or with another gene in the same bacterium because they had similar mutant phenotypes. Of the poorly annotated genes, 2,316 had associations that have high confidence because they are conserved in other bacteria. By combining these conserved associations with comparative genomics, we identified putative DNA repair proteins; in addition, we propose specific functions for poorly annotated enzymes and transporters and for uncharacterized protein families. Our study demonstrates the scalability of microbial genetics and its utility for improving gene annotations.

Enabling multiplexed testing of pooled donor cells through whole-genome sequencing

We describe a method that enables the multiplex screening of a pool of many different donor cell lines. Our method accurately predicts each donor proportion from the pool without requiring the use of unique DNA barcodes as markers of donor identity. Instead, we take advantage of common single nucleotide polymorphisms, whole-genome sequencing, and an algorithm to calculate the proportions from the sequencing data. By testing using simulated and real data, we showed that our method robustly predicts the individual proportions from a mixed-pool of numerous donors, thus enabling the multiplexed testing of diverse donor cells en masse.

More information is available at https://pgpresearch.med.harvard.edu/poolseq/

Discovery of a Novel Dibromoquinoline Compound Exhibiting Potent Antifungal and Antivirulence Activity That Targets Metal Ion Homeostasis

Globally, invasive fungal infections pose a significant challenge to modern human medicine due to the limited number of antifungal drugs and the rise in resistance to current antifungal agents. A vast majority of invasive fungal infections are caused by species of Candida, Cryptococcus, and Aspergillus. Novel antifungal molecules consisting of unexploited chemical scaffolds with a unique mechanism are a pressing need. The present study identifies a dibromoquinoline compound (4b) with broad-spectrum antifungal activity that inhibits the growth of pertinent species of Candida (chiefly C. albicans), Cryptococcus, and Aspergillus at a concentration of as low as 0.5 μg/mL. Furthermore, 4b, at a subinhibitory concentration, interfered with the expression of two key virulence factors (hyphae and biofilm formation) involved in C. albicans pathogenesis. Three yeast deletion strains ( cox17Δ, ssa1Δ, and aft2Δ) related to metal ion homeostasis were found to be highly sensitive to 4b in growth assays, indicating that the compound exerts its antifungal effect through a unique, previously unexploited mechanism. Supplementing the media with either copper or iron ions reversed the strain sensitivity to 4b, further corroborating that the compound targets metal ion homeostasis. 4b's potent antifungal activity was validated in vivo, as the compound enhanced the survival of Caenorhabditis elegans infected with fluconazole-resistant C. albicans. The present study indicates that 4b warrants further investigation as a novel antifungal agent.

Genomics of cellular proliferation in periodic environmental fluctuations

Living systems control cell growth dynamically by processing information from their environment. Although responses to a single environmental change have been intensively studied, little is known about how cells react to fluctuating conditions. Here, we address this question at the genomic scale by measuring the relative proliferation rate (fitness) of 3,568 yeast gene deletion mutants in out-of-equilibrium conditions: periodic oscillations between two environmental conditions. In periodic salt stress, fitness and its genetic variance largely depended on the oscillating period. Surprisingly, dozens of mutants displayed pronounced hyperproliferation under short stress periods, revealing unexpected controllers of growth under fast dynamics. We validated the implication of the high-affinity cAMP phosphodiesterase and of a regulator of protein translocation to mitochondria in this group. Periodic oscillations of extracellular methionine, a factor unrelated to salinity, also altered fitness but to a lesser extent and for different genes. The results illustrate how natural selection acts on mutations in a dynamic environment, highlighting unsuspected genetic vulnerabilities to periodic stress in molecular processes that are conserved across all eukaryotes.

Large-scale profiling of noncoding RNA function in yeast

Noncoding RNAs (ncRNAs) are emerging as key regulators of cellular function. We have exploited the recently developed barcoded ncRNA gene deletion strain collections in the yeast Saccharomyces cerevisiae to investigate the numerous ncRNAs in yeast with no known function. The ncRNA deletion collection contains deletions of tRNAs, snoRNAs, snRNAs, stable unannotated transcripts (SUTs), cryptic unstable transcripts (CUTs) and other annotated ncRNAs encompassing 532 different individual ncRNA deletions. We have profiled the fitness of the diploid heterozygous ncRNA deletion strain collection in six conditions using batch and continuous liquid culture, as well as the haploid ncRNA deletion strain collections arrayed individually onto solid rich media. These analyses revealed many novel environmental-specific haplo-insufficient and haplo-proficient phenotypes providing key information on the importance of each specific ncRNA in every condition. Co-fitness analysis using fitness data from the heterozygous ncRNA deletion strain collection identified two ncRNA groups required for growth during heat stress and nutrient deprivation. The extensive fitness data for each ncRNA deletion strain has been compiled into an easy to navigate database called Yeast ncRNA Analysis (YNCA). By expanding the original ncRNA deletion strain collection we identified four novel essential ncRNAs; SUT527, SUT075, SUT367 and SUT259/691. We defined the effects of each new essential ncRNA on adjacent gene expression in the heterozygote background identifying both repression and induction of nearby genes. Additionally, we discovered a function for SUT527 in the expression, 3' end formation and localization of SEC4, an essential protein coding mRNA. Finally, using plasmid complementation we rescued the SUT075 lethal phenotype revealing that this ncRNA acts in trans. Overall, our findings provide important new insights into the function of ncRNAs.

Magic Pools: Parallel Assessment of Transposon Delivery Vectors in Bacteria

Molecular genetics is indispensable for interrogating the physiology of bacteria. However, the development of a functional genetic system for any given bacterium can be time-consuming. Here, we present a streamlined approach for identifying an effective transposon mutagenesis system for a new bacterium. Our strategy first involves the construction of hundreds of different transposon vector variants, which we term a “magic pool.” The efficacy of each vector in a magic pool is monitored in parallel using a unique DNA barcode that is introduced into each vector design. Using archived DNA “parts,” we next reassemble an effective vector for making a whole-genome transposon mutant library that is suitable for large-scale interrogation of gene function using competitive growth assays. Here, we demonstrate the utility of the magic pool system to make mutant libraries in five genera of bacteria.

Transposon mutagenesis coupled to next-generation sequencing (TnSeq) is a powerful approach for discovering the functions of bacterial genes. However, the development of a suitable TnSeq strategy for a given bacterium can be costly and time-consuming. To meet this challenge, we describe a part-based strategy for constructing libraries of hundreds of transposon delivery vectors, which we term “magic pools.” Within a magic pool, each transposon vector has a different combination of upstream sequences (promoters and ribosome binding sites) and antibiotic resistance markers as well as a random DNA barcode sequence, which allows the tracking of each vector during mutagenesis experiments. To identify an efficient vector for a given bacterium, we mutagenize it with a magic pool and sequence the resulting insertions; we then use this efficient vector to generate a large mutant library. We used the magic pool strategy to construct transposon mutant libraries in five genera of bacteria, including three genera of the phylum Bacteroidetes.

IMPORTANCE Molecular genetics is indispensable for interrogating the physiology of bacteria. However, the development of a functional genetic system for any given bacterium can be time-consuming. Here, we present a streamlined approach for identifying an effective transposon mutagenesis system for a new bacterium. Our strategy first involves the construction of hundreds of different transposon vector variants, which we term a “magic pool.” The efficacy of each vector in a magic pool is monitored in parallel using a unique DNA barcode that is introduced into each vector design. Using archived DNA “parts,” we next reassemble an effective vector for making a whole-genome transposon mutant library that is suitable for large-scale interrogation of gene function using competitive growth assays. Here, we demonstrate the utility of the magic pool system to make mutant libraries in five genera of bacteria.

Synthetic Biology to Improve the Production of Lipases and Esterases (Review)

Synthetic biology is an emergent field of research whose aim is to make biology an engineering discipline, thus permitting to design, control, and standardize biological processes. Synthetic biology is therefore expected to boost the development of biotechnological processes such as protein production and enzyme engineering, which can be significantly relevant for lipases and esterases.

Dissecting Nucleosome Function with a Comprehensive Histone H2A and H2B Mutant Library

Using a comprehensive library of histone H2A and H2B mutants, we assessed the biological function of each amino acid residue involved in various stress conditions including exposure to different DNA damage-inducing reagents, different growth temperatures, and other chemicals. H2B N- and H2A C-termini were critical for maintaining nucleosome function and mutations in these regions led to pleiotropic phenotypes. Additionally, two screens were performed using this library, monitoring heterochromatin gene silencing and genome stability, to identify residues that could compromise normal function when mutated. Many distinctive regions within the nucleosome were revealed. Furthermore, we used the barcode sequencing (bar-seq) method to profile the mutant composition of many libraries in one high-throughput sequencing experiment, greatly reducing the labor and increasing the capacity. This study not only demonstrates the applications of the versatile histone library, but also reveals many previously unknown functions of histone H2A and H2B.

Construction of Comprehensive Dosage-Matching Core Histone Mutant Libraries for Saccharomyces cerevisiae

Saccharomyces cerevisiae contains two genes for each core histone, which are presented as pairs under the control of a divergent promoter, i.e., HHT1-HHF1, HHT2-HHF2, HTA1-HTB1 and HTA2-HTB2HHT1-HHF1, and HHT2-HHF2 encode histone H3 and H4 with identical amino acid sequences but under the control of differently regulated promoters. Previous mutagenesis studies were carried out by deleting one pair and mutating the other one. Here, we present the design and construction of three additional libraries covering HTA1-HTB1, HTA2-HTB2, and HHT1-HHF1 respectively. Together with the previously described library of HHT2-HHF2 mutants, a systematic and complete collection of mutants for each of the eight core S. cerevisiae histone genes becomes available. Each designed mutant was incorporated into the genome, generating three more corresponding libraries of yeast strains. We demonstrated that, although, under normal growth conditions, strains with single-copy integrated histone genes lacked phenotypes, in some growth conditions, growth deficiencies were observed. Specifically, we showed that addition of a second copy of the mutant histone gene could rescue the lethality in some previously known mutants that cannot survive with a single copy. This resource enables systematic studies of function of each nucleosome residue in plasmid, single-copy, and double-copy integrated formats.

Large-scale DNA Barcode Library Generation for Biomolecule Identification in High-throughput Screens

High-throughput screens allow for the identification of specific biomolecules with characteristics of interest. In barcoded screens, DNA barcodes are linked to target biomolecules in a manner allowing for the target molecules making up a library to be identified by sequencing the DNA barcodes using Next Generation Sequencing. To be useful in experimental settings, the DNA barcodes in a library must satisfy certain constraints related to GC content, homopolymer length, Hamming distance, and blacklisted subsequences. Here we report a novel framework to quickly generate large-scale libraries of DNA barcodes for use in high-throughput screens. We show that our framework dramatically reduces the computation time required to generate large-scale DNA barcode libraries, compared with a naїve approach to DNA barcode library generation. As a proof of concept, we demonstrate that our framework is able to generate a library consisting of one million DNA barcodes for use in a fragment antibody phage display screening experiment. We also report generating a general purpose one billion DNA barcode library, the largest such library yet reported in literature. Our results demonstrate the value of our novel large-scale DNA barcode library generation framework for use in high-throughput screening applications.

Systematic Identification of Determinants for Single-Strand Annealing-Mediated Deletion Formation in Saccharomyces cerevisiae

To ensure genomic integrity, living organisms have evolved diverse molecular processes for sensing and repairing damaged DNA. If improperly repaired, DNA damage can give rise to different types of mutations, an important class of which are genomic structural variants (SVs). In spite of their importance for phenotypic variation and genome evolution, potential contributors to SV formation in Saccharomyces cerevisiae (budding yeast), a highly tractable model organism, are not fully recognized. Here, we developed and applied a genome-wide assay to identify yeast gene knockout mutants associated with de novo deletion formation, in particular single-strand annealing (SSA)-mediated deletion formation, in a systematic manner. In addition to genes previously linked to genome instability, our approach implicates novel genes involved in chromatin remodeling and meiosis in affecting the rate of SSA-mediated deletion formation in the presence or absence of stress conditions induced by DNA-damaging agents. We closely examined two candidate genes, the chromatin remodeling gene IOC4 and the meiosis-related gene MSH4, which when knocked-out resulted in gene expression alterations affecting genes involved in cell division and chromosome organization, as well as DNA repair and recombination, respectively. Our high-throughput approach facilitates the systematic identification of processes linked to the formation of a major class of genetic variation.

Deciphering the Genic Basis of Yeast Fitness Variation by Simultaneous Forward and Reverse Genetics

The budding yeast Saccharomyces cerevisiae is the best studied eukaryote in molecular and cell biology, but its utility for understanding the genetic basis of phenotypic variation in natural populations is limited by inefficient association mapping due to strong and complex population structure. To overcome this challenge, we generated genome sequences for 85 strains and performed a comprehensive population genomic survey of a total of 190 diverse strains. We identified considerable variation in population structure among chromosomes and identified 181 genes that are absent from the reference genome. Many of these nonreference genes are expressed and we functionally confirmed that two of these genes confer increased resistance to antifungals. Next, we simultaneously measured the growth rates of over 4,500 laboratory strains, each of which lacks a nonessential gene, and 81 natural strains across multiple environments using unique DNA barcode present in each strain. By combining the genome-wide reverse genetic information gained from the gene deletion strains with a genome-wide association analysis from the natural strains, we identified genomic regions associated with fitness variation in natural populations. To experimentally validate a subset of these associations, we used reciprocal hemizygosity tests, finding that while the combined forward and reverse genetic approaches can identify a single causal gene, the phenotypic consequences of natural genetic variation often follow a complicated pattern. The resources and approach provided outline an efficient and reliable route to association mapping in yeast and significantly enhance its value as a model for understanding the genetic mechanisms underlying phenotypic variation and evolution in natural populations.

Quantitative analysis of protein interaction network dynamics in yeast

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.

Yeast genetic interaction screen of human genes associated with amyotrophic lateral sclerosis: identification of MAP2K5 kinase as a potential drug target

To understand disease mechanisms, a large-scale analysis of human–yeast genetic interactions was performed. Of 1305 human disease genes assayed, 20 genes exhibited strong toxicity in yeast. Human–yeast genetic interactions were identified by en masse transformation of the human disease genes into a pool of 4653 homozygous diploid yeast deletion mutants with unique barcode sequences, followed by multiplexed barcode sequencing to identify yeast toxicity modifiers. Subsequent network analyses focusing on amyotrophic lateral sclerosis (ALS)-associated genes, such as optineurin (OPTN) and angiogenin (ANG), showed that the human orthologs of the yeast toxicity modifiers of these ALS genes are enriched for several biological processes, such as cell death, lipid metabolism, and molecular transport. When yeast genetic interaction partners held in common between human OPTN and ANG were validated in mammalian cells and zebrafish, MAP2K5 kinase emerged as a potential drug target for ALS therapy. The toxicity modifiers identified in this study may deepen our understanding of the pathogenic mechanisms of ALS and other devastating diseases.

A scalable double-barcode sequencing platform for characterization of dynamic protein-protein interactions

Several large-scale efforts have systematically catalogued protein-protein interactions (PPIs) of a cell in a single environment. However, little is known about how the protein interactome changes across environmental perturbations. Current technologies, which assay one PPI at a time, are too low throughput to make it practical to study protein interactome dynamics. Here, we develop a highly parallel protein-protein interaction sequencing (PPiSeq) platform that uses a novel double barcoding system in conjunction with the dihydrofolate reductase protein-fragment complementation assay in Saccharomyces cerevisiae. PPiSeq detects PPIs at a rate that is on par with current assays and, in contrast with current methods, quantitatively scores PPIs with enough accuracy and sensitivity to detect changes across environments. Both PPI scoring and the bulk of strain construction can be performed with cell pools, making the assay scalable and easily reproduced across environments. PPiSeq is therefore a powerful new tool for large-scale investigations of dynamic PPIs.

Heterosis as a consequence of regulatory incompatibility

BACKGROUND

The merging of genomes in inter-specific hybrids can result in novel phenotypes, including increased growth rate and biomass yield, a phenomenon known as heterosis. Heterosis is typically viewed as the opposite of hybrid incompatibility. In this view, the superior performance of the hybrid is attributed to heterozygote combinations that compensate for deleterious mutations accumulating in each individual genome, or lead to new, over-dominating interactions with improved performance. Still, only fragmented knowledge is available on genes and processes contributing to heterosis.

RESULTS

We describe a budding yeast hybrid that grows faster than both its parents under different environments. Phenotypically, the hybrid progresses more rapidly through cell cycle checkpoints, relieves the repression of respiration in fast growing conditions, does not slow down its growth when presented with ethanol stress, and shows increased signs of DNA damage. A systematic genetic screen identified hundreds of S. cerevisiae alleles whose deletion reduced growth of the hybrid. These growth-affecting alleles were condition-dependent, and differed greatly from alleles that reduced the growth of the S. cerevisiae parent.

CONCLUSIONS

Our results define a budding yeast hybrid that is perturbed in multiple regulatory processes but still shows a clear growth heterosis. We propose that heterosis results from incompatibilities that perturb regulatory mechanisms, which evolved to protect cells against damage or prepare them for future challenges by limiting cell growth.

Quantitative Tracking of Combinatorially Engineered Populations with Multiplexed Binary Assemblies

Advances in synthetic biology and genomics have enabled full-scale genome engineering efforts on laboratory time scales. However, the absence of sufficient approaches for mapping engineered genomes at system-wide scales onto performance has limited the adoption of more sophisticated algorithms for engineering complex biological systems. Here we report on the development and application of a robust approach to quantitatively map combinatorially engineered populations at scales up to several dozen target sites. This approach works by assembling genome engineered sites with cell-specific barcodes into a format compatible with high-throughput sequencing technologies. This approach, called barcoded-TRACE (bTRACE) was applied to assess E. coli populations engineered by recursive multiplex recombineering across both 6-target sites and 31-target sites. The 31-target library was then tracked throughout growth selections in the presence and absence of isopentenol (a potential next-generation biofuel). We also use the resolution of bTRACE to compare the influence of technical and biological noise on genome engineering efforts.

Identification of the fitness determinants of budding yeast on a natural substrate

The budding yeasts are prime models in genomics and cell biology, but the ecological factors that determine their success in non-human-associated habitats is poorly understood. In North America Saccharomyces yeasts are present on the bark of deciduous trees, where they feed on bark and sap exudates. In the North East, Saccharomyces paradoxus is found on maples, which makes maple sap a natural substrate for this species. We measured growth rates of S. paradoxus natural isolates on maple sap and found variation along a geographical gradient not explained by the inherent variation observed under optimal laboratory conditions. We used a functional genomic screen to reveal the ecologically relevant genes and conditions required for optimal growth in this substrate. We found that the allantoin degradation pathway is required for optimal growth in maple sap, in particular genes necessary for allantoate utilization, which we demonstrate is the major nitrogen source available to yeast in this environment. Growth with allantoin or allantoate as the sole nitrogen source recapitulated the variation in growth rates in maple sap among strains. We also show that two lineages of S. paradoxus display different life-history traits on allantoin and allantoate media, highlighting the ecological relevance of this pathway.

A Chemogenomic Screening Platform Used to Identify Chemotypes Perturbing HSP90 Pathways

Compounds that modulate the heat shock protein (HSP) network have potential in a broad range of research applications and diseases. A yeast-based liquid culture assay that measured time-dependent turbidity enabled the high-throughput screening of different Saccharomyces cerevisae strains to identify HSP modulators with unique molecular mechanisms. A focused set of four strains, with differing sensitivities to Hsp90 inhibitors, was used to screen a compound library of 3680 compounds. Computed turbidity curve functions were used to classify strain responses and sensitivity to chemical effects across the compound library. Filtering based on single-strain selectivity identified nine compounds as potential heat shock modulators, including the known Hsp90 inhibitor macbecin. Haploid yeast deletion strains (360), mined from previous Hsp90 inhibitor yeast screens and heat shock protein interaction data, were screened for differential sensitivities to known N-terminal ATP site-directed Hsp90 inhibitors to reveal functional distinctions. Strains demonstrating differential sensitivity (13) to Hsp90 inhibitors were used to prioritize primary screen hit compounds, with NSC145366 emerging as the lead hit. Our follow-up biochemical and functional studies show that NSC145366 directly interacts and inhibits the C-terminus of Hsp90, validating the platform as a powerful approach for early-stage identification of bioactive modulators of heat shock-dependent pathways.

Repurposing Approach Identifies Auranofin with Broad Spectrum Antifungal Activity That Targets Mia40-Erv1 Pathway

Current antifungal therapies have limited effectiveness in treating invasive fungal infections. Furthermore, the development of new antifungal is currently unable to keep pace with the urgent demand for safe and effective new drugs. Auranofin, an FDA-approved drug for the treatment of rheumatoid arthritis, inhibits growth of a diverse array of clinical isolates of fungi and represents a new antifungal agent with a previously unexploited mechanism of action. In addition to auranofin's potent antifungal activity against planktonic fungi, this drug significantly reduces the metabolic activity of Candida cells encased in a biofilm. Unbiased chemogenomic profiling, using heterozygous S. cerevisiae deletion strains, combined with growth assays revealed three probable targets for auranofin's antifungal activity—mia40, acn9, and coa4. Mia40 is of particular interest given its essential role in oxidation of cysteine rich proteins imported into the mitochondria. Biochemical analysis confirmed auranofin targets the Mia40-Erv1 pathway as the drug inhibited Mia40 from interacting with its substrate, Cmc1, in a dose-dependent manner similar to the control, MB-7. Furthermore, yeast mitochondria overexpressing Erv1 were shown to exhibit resistance to auranofin as an increase in Cmc1 import was observed compared to wild-type yeast. Further in vivo antifungal activity of auranofin was examined in a Caenorhabditis elegans animal model of Cryptococcus neoformans infection. Auranofin significantly reduced the fungal load in infected C. elegans. Collectively, the present study provides valuable evidence that auranofin has significant promise to be repurposed as a novel antifungal agent and may offer a safe, effective, and quick supplement to current approaches for treating fungal infections.

iSeq: A New Double-Barcode Method for Detecting Dynamic Genetic Interactions in Yeast

Systematic screens for genetic interactions are a cornerstone of both network and systems biology. However, most screens have been limited to characterizing interaction networks in a single environment. Moving beyond this static view of the cell requires a major technological advance to increase the throughput and ease of replication in these assays. Here, we introduce iSeq-a platform to build large double barcode libraries and rapidly assay genetic interactions across environments. We use iSeq in yeast to measure fitness in three conditions of nearly 400 clonal strains, representing 45 possible single or double gene deletions, including multiple replicate strains per genotype. We show that iSeq fitness and interaction scores are highly reproducible for the same clonal strain across replicate cultures. However, consistent with previous work, we find that replicates with the same putative genotype have highly variable genetic interaction scores. By whole-genome sequencing 102 of our strains, we find that segregating variation and de novo mutations, including aneuploidy, occur frequently during strain construction, and can have large effects on genetic interaction scores. Additionally, we uncover several new environment-dependent genetic interactions, suggesting that barcode-based genetic interaction assays have the potential to significantly expand our knowledge of genetic interaction networks.

Microbiome Helper: a Custom and Streamlined Workflow for Microbiome Research

As the microbiome field continues to grow, a multitude of researchers are learning how to conduct proper microbiome experiments. We outline here a streamlined and custom approach to processing samples from detailed sequencing library construction to step-by-step bioinformatic standard operating procedures. This allows for rapid and reliable microbiome analysis, allowing researchers to focus more on their experiment design and results. Our sequencing protocols, bioinformatic tutorials, and bundled software are freely available through Microbiome Helper. As the microbiome research field continues to evolve, Microbiome Helper will be updated with new protocols, scripts, and training materials.

Sequence-based approaches to study microbiomes, such as 16S rRNA gene sequencing and metagenomics, are uncovering associations between microbial taxa and a myriad of factors. A drawback of these approaches is that the necessary sequencing library preparation and bioinformatic analyses are complicated and continuously changing, which can be a barrier for researchers new to the field. We present three essential components to conducting a microbiome experiment from start to finish: first, a simplified and step-by-step custom gene sequencing protocol that requires limited lab equipment, is cost-effective, and has been thoroughly tested and utilized on various sample types; second, a series of scripts to integrate various commonly used bioinformatic tools that is available as a standalone installation or as a single downloadable virtual image; and third, a set of bioinformatic workflows and tutorials to provide step-by-step guidance and education for those new to the microbiome field. This resource will provide the foundations for those newly entering the microbiome field and will provide much-needed guidance and best practices to ensure that quality microbiome research is undertaken. All protocols, scripts, workflows, tutorials, and virtual images are freely available through the Microbiome Helper website (https://github.com/mlangill/microbiome_helper/wiki).

IMPORTANCE As the microbiome field continues to grow, a multitude of researchers are learning how to conduct proper microbiome experiments. We outline here a streamlined and custom approach to processing samples from detailed sequencing library construction to step-by-step bioinformatic standard operating procedures. This allows for rapid and reliable microbiome analysis, allowing researchers to focus more on their experiment design and results. Our sequencing protocols, bioinformatic tutorials, and bundled software are freely available through Microbiome Helper. As the microbiome research field continues to evolve, Microbiome Helper will be updated with new protocols, scripts, and training materials.

Competitive Growth Enhances Conditional Growth Mutant Sensitivity to Antibiotics and Exposes a Two-Component System as an Emerging Antibacterial Target in Burkholderia cenocepacia

Chemogenetic approaches to profile an antibiotic mode of action are based on detecting differential sensitivities of engineered bacterial strains in which the antibacterial target (usually encoded by an essential gene) or an associated process is regulated. We previously developed an essential-gene knockdown mutant library in the multidrug-resistant Burkholderia cenocepacia by transposon delivery of a rhamnose-inducible promoter. In this work, we used Illumina sequencing of multiplex-PCR-amplified transposon junctions to track individual mutants during pooled growth in the presence of antibiotics. We found that competition from nontarget mutants magnified the hypersensitivity of a clone underexpressing gyrB to novobiocin by 8-fold compared with hypersensitivity measured during clonal growth. Additional profiling of various antibiotics against a pilot library representing most categories of essential genes revealed a two-component system with unknown function, which, upon depletion of the response regulator, sensitized B. cenocepacia to novobiocin, ciprofloxacin, tetracycline, chloramphenicol, kanamycin, meropenem, and carbonyl cyanide 3-chlorophenylhydrazone, but not to colistin, hydrogen peroxide, and dimethyl sulfoxide. We named the gene cluster esaSR for enhanced sensitivity to antibiotics sensor and response regulator. Mutational analysis and efflux activity assays revealed that while esaS is not essential and is involved in antibiotic-induced efflux, esaR is an essential gene and regulates efflux independently of antibiotic-mediated induction. Furthermore, microscopic analysis of cells stained with propidium iodide provided evidence that depletion of EsaR has a profound effect on the integrity of cell membranes. In summary, we unraveled a previously uncharacterized two-component system that can be targeted to reduce antibiotic resistance in B. cenocepacia.

Genome-wide functional analysis using the barcode sequence alignment and statistical analysis (Barcas) tool

BACKGROUND

Pooled library screen analysis using shRNAs or CRISPR-Cas9 hold great promise to genome-wide functional studies. While pooled library screens are effective tools, erroneous barcodes can potentially be generated during the production of many barcodes. However, no current tools can distinguish erroneous barcodes from PCR or sequencing errors in a data preprocessing step.

RESULTS

We developed the Barcas program, a specialized program for the mapping and analysis of multiplexed barcode sequencing (barcode-seq) data. For fast and efficient mapping, Barcas uses a trie data structure based imperfect matching algorithm which generates precise mapping results containing mismatches, shifts, insertions and deletions (indel) in a flexible manner. Barcas provides three functions for quality control (QC) of a barcode library and distinguishes erroneous barcodes from PCR or sequencing errors. It also provides useful functions for data analysis and visualization.

CONCLUSIONS

Barcas is an all-in-one package providing useful functions including mapping, data QC, library QC, statistical analysis and visualization in genome-wide pooled screens.