Jeff Piotrowski

A global genetic interaction network maps a wiring diagram of cellular function

INTRODUCTION Genetic interactions occur when mutations in two or more genes combine to generate an unexpected phenotype. An extreme negative or synthetic lethal genetic interaction occurs when two mutations, neither lethal individually, combine to cause cell death. Conversely, positive genetic interactions occur when two mutations produce a phenotype that is less severe than expected. Genetic interactions identify functional relationships between genes and can be harnessed for biological discovery and therapeutic target identification. They may also explain a considerable component of the undiscovered genetics associated with human diseases. Here, we describe construction and analysis of a comprehensive genetic interaction network for a eukaryotic cell. RATIONALE Genome sequencing projects are providing an unprecedented view of genetic variation. However, our ability to interpret genetic information to predict inherited phenotypes remains limited, in large part due to the extensive buffering of genomes, making most individual eukaryotic genes dispensable for life. To explore the extent to which genetic interactions reveal cellular function and contribute to complex phenotypes, and to discover the general principles of genetic networks, we used automated yeast genetics to construct a global genetic interaction network. RESULTS We tested most of the ~6000 genes in the yeast Saccharomyces cerevisiae for all possible pairwise genetic interactions, identifying nearly 1 million interactions, including ~550,000 negative and ~350,000 positive interactions, spanning ~90% of all yeast genes. Essential genes were network hubs, displaying five times as many interactions as nonessential genes. The set of genetic interactions or the genetic interaction profile for a gene provides a quantitative measure of function, and a global network based on genetic interaction profile similarity revealed a hierarchy of modules reflecting the functional architecture of a cell. Negative interactions connected functionally related genes, mapped core bioprocesses, and identified pleiotropic genes, whereas positive interactions often mapped general regulatory connections associated with defects in cell cycle progression or cellular proteostasis. Importantly, the global network illustrates how coherent sets of negative or positive genetic interactions connect protein complex and pathways to map a functional wiring diagram of the cell. CONCLUSION A global genetic interaction network highlights the functional organization of a cell and provides a resource for predicting gene and pathway function. This network emphasizes the prevalence of genetic interactions and their potential to compound phenotypes associated with single mutations. Negative genetic interactions tend to connect functionally related genes and thus may be predicted using alternative functional information. Although less functionally informative, positive interactions may provide insights into general mechanisms of genetic suppression or resiliency. We anticipate that the ordered topology of the global genetic network, in which genetic interactions connect coherently within and between protein complexes and pathways, may be exploited to decipher genotype-to-phenotype relationships. A global network of genetic interaction profile similarities. (Left) Genes with similar genetic interaction profiles are connected in a global network, such that genes exhibiting more similar profiles are located closer to each other, whereas genes with less similar profiles are positioned farther apart. (Right) Spatial analysis of functional enrichment was used to identify and color network regions enriched for similar Gene Ontology bioprocess terms. We generated a global genetic interaction network for Saccharomyces cerevisiae, constructing more than 23 million double mutants, identifying about 550,000 negative and about 350,000 positive genetic interactions. This comprehensive network maps genetic interactions for essential gene pairs, highlighting essential genes as densely connected hubs. Genetic interaction profiles enabled assembly of a hierarchical model of cell function, including modules corresponding to protein complexes and pathways, biological processes, and cellular compartments. Negative interactions connected functionally related genes, mapped core bioprocesses, and identified pleiotropic genes, whereas positive interactions often mapped general regulatory connections among gene pairs, rather than shared functionality. The global network illustrates how coherent sets of genetic interactions connect protein complex and pathway modules to map a functional wiring diagram of the cell.

A Comparative Genomic Approach for Identifying Synthetic Lethal Interactions in Human Cancer

Synthetic lethal interactions enable a novel approach for discovering specific genetic vulnerabilities in cancer cells that can be exploited for the development of therapeutics. Despite successes in model organisms such as yeast, discovering synthetic lethal interactions on a large scale in human cells remains a significant challenge. We describe a comparative genomic strategy for identifying cancer-relevant synthetic lethal interactions whereby candidate interactions are prioritized on the basis of genetic interaction data available in yeast, followed by targeted testing of candidate interactions in human cell lines. As a proof of principle, we describe two novel synthetic lethal interactions in human cells discovered by this approach, one between the tumor suppressor gene SMARCB1 and PSMA4, and another between alveolar soft-part sarcoma-associated ASPSCR1 and PSMC2. These results suggest therapeutic targets for cancers harboring mutations in SMARCB1 or ASPSCR1 and highlight the potential of a targeted, cross-species strategy for identifying synthetic lethal interactions relevant to human cancer.

Plant-derived antifungal agent poacic acid targets β-1,3-glucan

Significance The search for new antifungal compounds is struggling to keep pace with emerging fungicide resistance. Through chemoprospecting of an untapped reservoir of inhibitory compounds, lignocellulosic hydrolysates, we have identified a previously undescribed antifungal agent, poacic acid. Using both chemical genomics and morphological analysis together for the first time, to our knowledge, we identified the cellular target of poacic acid as β-1,3-glucan. Through its action on the glucan layer of fungal cell walls, poacic acid is a natural antifungal agent against economically significant fungi and oomycete plant pathogens. This work highlights the chemical diversity within lignocellulosic hydrolysates as a source of potentially valuable chemicals. A rise in resistance to current antifungals necessitates strategies to identify alternative sources of effective fungicides. We report the discovery of poacic acid, a potent antifungal compound found in lignocellulosic hydrolysates of grasses. Chemical genomics using Saccharomyces cerevisiae showed that loss of cell wall synthesis and maintenance genes conferred increased sensitivity to poacic acid. Morphological analysis revealed that cells treated with poacic acid behaved similarly to cells treated with other cell wall-targeting drugs and mutants with deletions in genes involved in processes related to cell wall biogenesis. Poacic acid causes rapid cell lysis and is synergistic with caspofungin and fluconazole. The cellular target was identified; poacic acid localized to the cell wall and inhibited β-1,3-glucan synthesis in vivo and in vitro, apparently by directly binding β-1,3-glucan. Through its activity on the glucan layer, poacic acid inhibits growth of the fungi Sclerotinia sclerotiorum and Alternaria solani as well as the oomycete Phytophthora sojae. A single application of poacic acid to leaves infected with the broad-range fungal pathogen S. sclerotiorum substantially reduced lesion development. The discovery of poacic acid as a natural antifungal agent targeting β-1,3-glucan highlights the potential side use of products generated in the processing of renewable biomass toward biofuels as a source of valuable bioactive compounds and further clarifies the nature and mechanism of fermentation inhibitors found in lignocellulosic hydrolysates.

Chemical genomic profiling via barcode sequencing to predict compound mode of action

Chemical genomics is an unbiased, whole-cell approach to characterizing novel compounds to determine mode of action and cellular target. Our version of this technique is built upon barcoded deletion mutants of Saccharomyces cerevisiae and has been adapted to a high-throughput methodology using next-generation sequencing. Here we describe the steps to generate a chemical genomic profile from a compound of interest, and how to use this information to predict molecular mechanism and targets of bioactive compounds.

Controlling microbial contamination during hydrolysis of AFEX-pretreated corn stover and switchgrass: effects on hydrolysate composition, microbial response and fermentation.

BackgroundMicrobial conversion of lignocellulosic feedstocks into biofuels remains an attractive means to produce sustainable energy. It is essential to produce lignocellulosic hydrolysates in a consistent manner in order to study microbial performance in different feedstock hydrolysates. Because of the potential to introduce microbial contamination from the untreated biomass or at various points during the process, it can be difficult to control sterility during hydrolysate production. In this study, we compared hydrolysates produced from AFEX-pretreated corn stover and switchgrass using two different methods to control contamination: either by autoclaving the pretreated feedstocks prior to enzymatic hydrolysis, or by introducing antibiotics during the hydrolysis of non-autoclaved feedstocks. We then performed extensive chemical analysis, chemical genomics, and comparative fermentations to evaluate any differences between these two different methods used for producing corn stover and switchgrass hydrolysates.ResultsAutoclaving the pretreated feedstocks could eliminate the contamination for a variety of feedstocks, whereas the antibiotic gentamicin was unable to control contamination consistently during hydrolysis. Compared to the addition of gentamicin, autoclaving of biomass before hydrolysis had a minimal effect on mineral concentrations, and showed no significant effect on the two major sugars (glucose and xylose) found in these hydrolysates. However, autoclaving elevated the concentration of some furanic and phenolic compounds. Chemical genomics analyses using Saccharomyces cerevisiae strains indicated a high correlation between the AFEX-pretreated hydrolysates produced using these two methods within the same feedstock, indicating minimal differences between the autoclaving and antibiotic methods. Comparative fermentations with S. cerevisiae and Zymomonas mobilis also showed that autoclaving the AFEX-pretreated feedstocks had no significant effects on microbial performance in these hydrolysates.ConclusionsOur results showed that autoclaving the pretreated feedstocks offered advantages over the addition of antibiotics for hydrolysate production. The autoclaving method produced a more consistent quality of hydrolysate, and also showed negligible effects on microbial performance. Although the levels of some of the lignocellulose degradation inhibitors were elevated by autoclaving the feedstocks prior to enzymatic hydrolysis, no significant effects on cell growth, sugar utilization, or ethanol production were seen during bacterial or yeast fermentations in hydrolysates produced using the two different methods.

Unbiased screening of marine sponge extracts for anti-inflammatory agents combined with chemical genomics identifies girolline as an inhibitor of protein synthesis.

Toll-like receptors (TLRs) play a critical role in innate immunity, but activation of TLR signaling pathways is also associated with many harmful inflammatory diseases. Identification of novel anti-inflammatory molecules targeting TLR signaling pathways is central to the development of new treatment approaches for acute and chronic inflammation. We performed high-throughput screening from crude marine sponge extracts on TLR5 signaling and identified girolline. We demonstrated that girolline inhibits signaling through both MyD88-dependent and -independent TLRs (i.e., TLR2, 3, 4, 5, and 7) and reduces cytokine (IL-6 and IL-8) production in human peripheral blood mononuclear cells and macrophages. Using a chemical genomics approach, we identified Elongation Factor 2 as the molecular target of girolline, which inhibits protein synthesis at the elongation step. Together these data identify the sponge natural product girolline as a potential anti-inflammatory agent acting through inhibition of protein synthesis.

Modeling Microbial Growth Curves with GCAT

In this work, we introduce the Growth Curve Analysis Tool (GCAT). GCAT is designed to enable efficient analysis of high-throughput microbial growth curve data collected from cultures grown in microtiter plates. GCAT is accessible through a web browser, making it easy to use and operating system independent. GCAT implements fitting of global sigmoid curve models and local regression (LOESS) model. We assess the relative merits of these approaches using experimental data. Additionally, GCAT implements heuristics to deal with some peculiarities of growth curve data commonly encountered in bioenergy research. GCAT server is publicly available at http://gcat-pub.glbrc.org/. The source code is available at http://code.google.com/p/gcat-hts/.

Water-soluble phenolic compounds produced from extractive ammonia pretreatment exerted binary inhibitory effects on yeast fermentation using synthetic hydrolysate

Biochemical conversion of lignocellulosic biomass to liquid fuels requires pretreatment and enzymatic hydrolysis of the biomass to produce fermentable sugars. Degradation products produced during thermochemical pretreatment, however, inhibit the microbes with regard to both ethanol yield and cell growth. In this work, we used synthetic hydrolysates (SynH) to study the inhibition of yeast fermentation by water-soluble components (WSC) isolated from lignin streams obtained after extractive ammonia pretreatment (EA). We found that SynH with 20g/L WSC mimics real hydrolysate in cell growth, sugar consumption and ethanol production. However, a long lag phase was observed in the first 48 h of fermentation of SynH, which is not observed during fermentation with the crude extraction mixture. Ethyl acetate extraction was conducted to separate phenolic compounds from other water-soluble components. These phenolic compounds play a key inhibitory role during ethanol fermentation. The most abundant compounds were identified by Liquid Chromatography followed by Mass Spectrometry (LC-MS) and Gas Chromatography followed by Mass Spectrometry (GC-MS), including coumaroyl amide, feruloyl amide and coumaroyl glycerol. Chemical genomics profiling was employed to fingerprint the gene deletion response of yeast to different groups of inhibitors in WSC and AFEX-Pretreated Corn Stover Hydrolysate (ACSH). The sensitive/resistant genes cluster patterns for different fermentation media revealed their similarities and differences with regard to degradation compounds.

Integrated soybean transcriptomics, metabolomics, and chemical genomics reveal the importance of the phenylpropanoid pathway and antifungal activity in resistance to the broad host range pathogen Sclerotinia sclerotiorum

Sclerotinia sclerotiorum, a predominately necrotrophic fungal pathogen with a broad host range, causes a significant yield limiting disease of soybean called Sclerotinia stem rot (SSR). Resistance mechanisms against SSR are poorly understood, thus hindering the commercial deployment of SSR resistant varieties. We used a multiomic approach utilizing RNA-sequencing, Gas chromatography-mass spectrometry-based metabolomics and chemical genomics in yeast to decipher the molecular mechanisms governing resistance to S. sclerotiorum in soybean. Transcripts and metabolites of two soybean recombinant inbred lines, one resistant, and one susceptible to S. sclerotiorum were analyzed in a time course experiment. The combined results show that resistance to S. sclerotiorum in soybean is associated in part with an early accumulation of JA-Ile ((+)-7-iso-Jasmonoyl-L-isoleucine), a bioactive jasmonate, increased ability to scavenge reactive oxygen species (ROS), and importantly, a reprogramming of the phenylpropanoid pathway leading to increased antifungal activities. Indeed, we noted that phenylpropanoid pathway intermediates such as, 4-hydroxybenzoate, ferulic acid and caffeic acid were highly accumulated in the resistant line. In vitro assays show that these metabolites and total stem extracts from the resistant line clearly affect S. sclerotiorum growth and development. Using chemical genomics in yeast, we further show that this antifungal activity targets ergosterol biosynthesis in the fungus, by disrupting enzymes involved in lipid and sterol biosynthesis. Overall, our results are consistent with a model where resistance to S. sclerotiorum in soybean coincides with an early recognition of the pathogen, leading to the modulation of the redox capacity of the host and the production of antifungal metabolites. Author Summary Resistance to plant fungal pathogens with predominately necrotrophic lifestyles is poorly understood. In this study, we use Sclerotinia sclerotiorum and soybean as a model system to identify key resistance components in this crop plant. We employed a variety of omics approaches in combination with functional studies to identify plant processes associated with resistance to S. sclerotiorum. Our results suggest that resistance to this pathogen is associated in part with an earlier induction of jasmonate signaling, increased ability to scavenge reactive oxygen species, and importantly, a reprogramming of the phenylpropanoid pathway resulting in increased antifungal activities. These findings provide specific plant targets that can exploited to confer resistance to S. sclerotiorum and potentially other pathogens with similar lifestyle.

A New Natural Product Analog of Blasticidin S Reveals Cellular Uptake Facilitated by the NorA Multidrug Transporter

ABSTRACT The permeation of antibiotics through bacterial membranes to their target site is a crucial determinant of drug activity but in many cases remains poorly understood. During screening efforts to discover new broad-spectrum antibiotic compounds from marine sponge samples, we identified a new analog of the peptidyl nucleoside antibiotic blasticidin S that exhibited up to 16-fold-improved potency against a range of laboratory and clinical bacterial strains which we named P10. Whole-genome sequencing of laboratory-evolved strains of Staphylococcus aureus resistant to blasticidin S and P10, combined with genome-wide assessment of the fitness of barcoded Escherichia coli knockout strains in the presence of the antibiotics, revealed that restriction of cellular access was a key feature in the development of resistance to this class of drug. In particular, the gene encoding the well-characterized multidrug efflux pump NorA was found to be mutated in 69% of all S. aureus isolates resistant to blasticidin S or P10. Unexpectedly, resistance was associated with inactivation of norA, suggesting that the NorA transporter facilitates cellular entry of peptidyl nucleosides in addition to its known role in the efflux of diverse compounds, including fluoroquinolone antibiotics.