Large-scale genetic perturbations reveal regulatory networks and an abundance of gene-specific repressors.

To understand regulatory systems, it would be useful to uniformly determine how different components contribute to the expression of all other genes. We therefore monitored mRNA expression genome-wide, for individual deletions of one-quarter of yeast genes, focusing on (putative) regulators. The resulting genetic perturbation signatures reflect many different properties. These include the architecture of protein complexes and pathways, identification of expression changes compatible with viability, and the varying responsiveness to genetic perturbation. The data are assembled into a genetic perturbation network that shows different connectivities for different classes of regulators. Four feed-forward loop (FFL) types are overrepresented, including incoherent type 2 FFLs that likely represent feedback. Systematic transcription factor classification shows a surprisingly high abundance of gene-specific repressors, suggesting that yeast chromatin is not as generally restrictive to transcription as is often assumed. The data set is useful for studying individual genes and for discovering properties of an entire regulatory system.

Functional overlap and regulatory links shape genetic interactions between signaling pathways.

To understand relationships between phosphorylation-based signaling pathways, we analyzed 150 deletion mutants of protein kinases and phosphatases in S. cerevisiae using DNA microarrays. Downstream changes in gene expression were treated as a phenotypic readout. Double mutants with synthetic genetic interactions were included to investigate genetic buffering relationships such as redundancy. Three types of genetic buffering relationships are identified: mixed epistasis, complete redundancy, and quantitative redundancy. In mixed epistasis, the most common buffering relationship, different gene sets respond in different epistatic ways. Mixed epistasis arises from pairs of regulators that have only partial overlap in function and that are coupled by additional regulatory links such as repression of one by the other. Such regulatory modules confer the ability to control different combinations of processes depending on condition or context. These properties likely contribute to the evolutionary maintenance of paralogs and indicate a way in which signaling pathways connect for multiprocess control.

Functional organization of the S. cerevisiae phosphorylation network.

Reversible protein phosphorylation is a signaling mechanism involved in all cellular processes. To create a systems view of the signaling apparatus in budding yeast, we generated an epistatic miniarray profile (E-MAP) comprised of 100,000 pairwise, quantitative genetic interactions, including virtually all protein and small-molecule kinases and phosphatases as well as key cellular regulators. Quantitative genetic interaction mapping reveals factors working in compensatory pathways (negative genetic interactions) or those operating in linear pathways (positive genetic interactions). We found an enrichment of positive genetic interactions between kinases, phosphatases, and their substrates. In addition, we assembled a higher-order map from sets of three genes that display strong interactions with one another: triplets enriched for functional connectivity. The resulting network view provides insights into signaling pathway regulation and reveals a link between the cell-cycle kinase, Cak1, the Fus3 MAP kinase, and a pathway that regulates chromatin integrity during transcription by RNA polymerase II.

A high-resolution gene expression atlas of epistasis between gene-specific transcription factors exposes potential mechanisms for genetic interactions.

BACKGROUND: Genetic interactions, or non-additive effects between genes, play a crucial role in many cellular processes and disease. Which mechanisms underlie these genetic interactions has hardly been characterized. Understanding the molecular basis of genetic interactions is crucial in deciphering pathway organization and understanding the relationship between genotype, phenotype and disease. RESULTS: To investigate the nature of genetic interactions between gene-specific transcription factors (GSTFs) in Saccharomyces cerevisiae, we systematically analyzed 72 GSTF pairs by gene expression profiling double and single deletion mutants. These pairs were selected through previously published growth-based genetic interactions as well as through similarity in DNA binding properties. The result is a high-resolution atlas of gene expression-based genetic interactions that provides systems-level insight into GSTF epistasis. The atlas confirms known genetic interactions and exposes new ones. Importantly, the data can be used to investigate mechanisms that underlie individual genetic interactions. Two molecular mechanisms are proposed, "buffering by induced dependency" and "alleviation by derepression". CONCLUSIONS: These mechanisms indicate how negative genetic interactions can occur between seemingly unrelated parallel pathways and how positive genetic interactions can indirectly expose parallel rather than same-pathway relationships. The focus on GSTFs is important for understanding the transcription regulatory network of yeast as it uncovers details behind many redundancy relationships, some of which are completely new. In addition, the study provides general insight into the complex nature of epistasis and proposes mechanistic models for genetic interactions, the majority of which do not fall into easily recognizable within- or between-pathway relationships.

MR1 encompasses at least six allele groups with coding region alterations.

Unlike classical HLA class I genes, MR1 is assumed to have limited polymorphic positions. We developed a MR1 specific PCR assay and sequenced 56 DNA samples from cells with a diverse set of HLA genotypes. In this relatively small panel we found six allele groups encoding for different MR1 proteins. The two most frequent allele groups found in this panel had a frequency of 71% (MR1*01) and 25% (MR1*02), respectively. Moreover, the panel contained many intronic SNPs and silent variants, with individual samples containing up to 15 heterozygous positions. The data presented here is consistent with marked variation in MR1.

RUNX2/CBFB modulates the response to MEK inhibitors through activation of receptor tyrosine kinases in KRAS-mutant colorectal cancer.

Intrinsic and acquired resistances are major hurdles preventing the effective use of MEK inhibitors for treatment of colorectal cancer (CRC). Some 35-45% of colorectal cancers are KRAS-mutant and their treatment remains challenging as these cancers are refractory to MEK inhibitor treatment, because of feedback activation of receptor tyrosine kinases (RTKs). We reported previously that loss of ERN1 sensitizes a subset of KRAS-mutant colon cancer cells to MEK inhibition. Here we show that the loss of RUNX2 or its cofactor CBFB can confer MEK inhibitor resistance in CRC cells. Mechanistically, we find that cells with genetically ablated RUNX2 or CBFB activate multiple RTKs, which coincides with high SHP2 phosphatase activity, a phosphatase that relays signals from the cell membrane to downstream pathways governing growth and proliferation. Moreover, we show that high activity of SHP2 is causal to loss of RUNX2-induced MEK inhibitor resistance, as a small molecule SHP2 inhibitor reinstates sensitivity to MEK inhibitor in RUNX2 knockout cells. Our results reveal an unexpected role for loss of RUNX2/CBFB in regulating RTK activity in colon cancer, resulting in reduced sensitivity to MEK inhibitors.

A role for the unfolded protein response stress sensor ERN1 in regulating the response to MEK inhibitors in KRAS mutant colon cancers.

BACKGROUND: Mutations in KRAS are frequent in human cancer, yet effective targeted therapeutics for these cancers are still lacking. Attempts to drug the MEK kinases downstream of KRAS have had limited success in clinical trials. Understanding the specific genomic vulnerabilities of KRAS-driven cancers may uncover novel patient-tailored treatment options. METHODS: We first searched for synthetic lethal (SL) genetic interactions with mutant RAS in yeast with the ultimate aim to identify novel cancer-specific targets for therapy. Our method used selective ploidy ablation, which enables replication of cancer-specific gene expression changes in the yeast gene disruption library. Second, we used a genome-wide CRISPR/Cas9-based genetic screen in KRAS mutant human colon cancer cells to understand the mechanistic connection between the synthetic lethal interaction discovered in yeast and downstream RAS signaling in human cells. RESULTS: We identify loss of the endoplasmic reticulum (ER) stress sensor IRE1 as synthetic lethal with activated RAS mutants in yeast. In KRAS mutant colorectal cancer cell lines, genetic ablation of the human ortholog of IRE1, ERN1, does not affect growth but sensitizes to MEK inhibition. However, an ERN1 kinase inhibitor failed to show synergy with MEK inhibition, suggesting that a non-kinase function of ERN1 confers MEK inhibitor resistance. To investigate how ERN1 modulates MEK inhibitor responses, we performed genetic screens in ERN1 knockout KRAS mutant colon cancer cells to identify genes whose inactivation confers resistance to MEK inhibition. This genetic screen identified multiple negative regulators of JUN N-terminal kinase (JNK) /JUN signaling. Consistently, compounds targeting JNK/MAPK8 or TAK1/MAP3K7, which relay signals from ERN1 to JUN, display synergy with MEK inhibition. CONCLUSIONS: We identify the ERN1-JNK-JUN pathway as a novel regulator of MEK inhibitor response in KRAS mutant colon cancer. The notion that multiple signaling pathways can activate JUN may explain why KRAS mutant tumor cells are traditionally seen as highly refractory to MEK inhibitor therapy. Our findings emphasize the need for the development of new therapeutics targeting JUN activating kinases, TAK1 and JNK, to sensitize KRAS mutant cancer cells to MEK inhibitors.

MAP3K1 and MAP2K4 mutations are associated with sensitivity to MEK inhibitors in multiple cancer models.

Activation of the mitogen-activated protein kinase (MAPK) pathway is frequent in cancer. Drug development efforts have been focused on kinases in this pathway, most notably on RAF and MEK. We show here that MEK inhibition activates JNK-JUN signaling through suppression of DUSP4, leading to activation of HER Receptor Tyrosine Kinases. This stimulates the MAPK pathway in the presence of drug, thereby blunting the effect of MEK inhibition. Cancers that have lost MAP3K1 or MAP2K4 fail to activate JNK-JUN. Consequently, loss-of-function mutations in either MAP3K1 or MAP2K4 confer sensitivity to MEK inhibition by disabling JNK-JUN-mediated feedback loop upon MEK inhibition. In a panel of 168 Patient Derived Xenograft (PDX) tumors, MAP3K1 and MAP2K4 mutation status is a strong predictor of response to MEK inhibition. Our findings suggest that cancers having mutations in MAP3K1 or MAP2K4, which are frequent in tumors of breast, prostate and colon, may respond to MEK inhibitors. Our findings also suggest that MAP3K1 and MAP2K4 are potential drug targets in combination with MEK inhibitors, in spite of the fact that they are encoded by tumor suppressor genes.

Structure-system correlation identifies a gene regulatory Mediator submodule.

A combination of crystallography, biochemistry, and gene expression analysis identifies the coactivator subcomplex Med8C/18/20 as a functionally distinct submodule of the Mediator head module. Med8C forms a conserved alpha-helix that tethers Med18/20 to the Mediator. Deletion of Med8C in vivo results in dissociation of Med18/20 from Mediator and in loss of transcription activity of extracts. Deletion of med8C, med18, or med20 causes similar changes in the yeast transcriptome, establishing Med8C/18/20 as a predominantly positive, gene-specific submodule required for low transcription levels of nonactivated genes, including conjugation genes. The presented structure-based system perturbation is superior to gene deletion analysis of gene regulation.

Gene transactivation without direct DNA binding defines a novel gain-of-function for PML-RARalpha.

PML-RARalpha is the causative oncogene in 5% to 10% of the cases of acute myeloid leukemia. At physiological concentrations of retinoic acid, PML-RARalpha silences RARalpha target genes, blocking differentiation of the cells. At high concentrations of ligand, it (re)activates the transcription of target genes, forcing terminal differentiation. The study of RARalpha target genes that mediate this differentiation has identified several genes that are important for proliferation and differentiation control in normal and malignant hematopoietic cells. In this paper, we show that the PML-RARalpha fusion protein not only interferes with the transcription of regular RARalpha target genes. We show that the ID1 and ID2 promoters are activated by PML-RARalpha but, unexpectedly, not by wild-type RARalpha/RXR. Our data support a model in which the PML-RARalpha fusion protein regulates a novel class of target genes by interaction with the Sp1 and NF-Y transcription factors, without directly binding to the DNA, defining a gain-of-function for the oncoprotein.

Isolation of FRET-positive cells using single 408-nm laser flow cytometry.

BACKGROUND: Flow cytometry may be used to isolate large amounts of living, fluorescently labeled cells. Certain fluorescent labels, like enhanced cyan fluorescent protein (ECFP) and enhanced yellow fluorescent protein (EYFP), allow the assessment of direct protein-protein interaction in situ, by fluorescence resonance energy transfer (FRET). However, current flow cytometric methods either require elaborate technical adaptations or, using a single laser protocol, are hampered by background signal. We optimized a single 408-nm laser protocol to detect FRET between ECFP/EYFP-tagged proteins. METHODS: Cell lines stably expressing ECFP and/or EYFP or an EYFP-ECFP fusion protein were used to design the settings for the flow cytometer to detect FRET-positive cells using a single 408-nm laser. Using these settings, interactions between the subunits of the transcription factor NF-Y were studied. RESULTS: Flow cytometric analysis of the cells expressing an EYFP-ECFP fusion protein yielded a discrete FRET-positive population. Using the same settings, in cells expressing NF-YB-CFP and NF-YC-YFP fusion proteins, FRET could also be detected. These cells were sorted and FRET was confirmed by confocal microscopy. CONCLUSION: FRET-positive cells, expressing ECFP- and EYFP-tagged proteins, can be detected using single 408-nm laser excitation, with low background signal. This allows high-throughput analysis and isolation of viable FRET-positive and -negative cells for subsequent biological experiments.

A lophotrochozoan twist gene is expressed in the ectomesoderm of the gastropod mollusk Patella vulgata.

The twist gene is known to be involved in mesoderm formation in two of the three clades of bilaterally symmetrical animals: viz. deuterostomes (such as vertebrates) and ecdysozoans (such as arthropods and nematodes). There are currently no data on the spatiotemporal expression of this gene in the third clade, the lophotrochozoans (such as mollusks and annelids). To approach the question of mesoderm homology across bilaterians, we decided to analyze orthologs of this gene in the gastropod mollusk Patella vulgata that belongs to the lophotrochozoans. We present here the cloning, characterization, and phylogenetic analysis of a Patella twist ortholog, Pv-twi, and determine the early spatiotemporal expression pattern of this gene. Pv-twi expression was found in the trochophore larva in a subset of the ectomesoderm, one of the two sources of mesoderm in Patella. These data support the idea that twist genes were ancestrally involved in mesoderm differentiation. The absence of Pv-twi in the second mesodermal source, the endomesoderm, suggests that also other genes must be involved in lophotrochozoan mesoderm differentiation. It therefore remains a question if the mesoderm of all bilaterians is homologous.