An Antipersister Strategy for Treatment of Chronic Pseudomonas aeruginosa Infections.

Bacterial persisters are a quasidormant subpopulation of cells that are tolerant to antibiotic treatment. The combination of the aminoglycoside tobramycin with fumarate as an antibacterial potentiator utilizes an antipersister strategy that is aimed at reducing recurrent Pseudomonas aeruginosa infections by enhancing the killing of P. aeruginosa persisters. Stationary-phase cultures of P. aeruginosa were used to generate persister cells. A range of tobramycin concentrations was tested with a range of metabolite concentrations to determine the potentiation effect of the metabolite under a variety of conditions, including a range of pH values and in the presence of azithromycin or cystic fibrosis (CF) patient sputum. In addition, 96-well dish biofilm and colony biofilm assays were performed, and the cytotoxicity of the tobramycin-fumarate combination was determined utilizing a lactate dehydrogenase (LDH) assay. Enhanced killing of up to 6 orders of magnitude of P. aeruginosa persisters over a range of CF isolates, including mucoid and nonmucoid strains, was observed for the tobramycin-fumarate combination compared to killing with tobramycin alone. Furthermore, significant fumarate-mediated potentiation was seen in the presence of azithromycin or CF patient sputum. Fumarate also reduced the cytotoxicity of tobramycin-treated P. aeruginosa to human epithelial airway cells. Finally, in mucoid and nonmucoid CF isolates, complete eradication of P. aeruginosa biofilm was observed in the colony biofilm assay due to fumarate potentiation. These data suggest that a combination of tobramycin with fumarate as an antibacterial potentiator may be an attractive therapeutic for eliminating recurrent P. aeruginosa infections in CF patients through the eradication of bacterial persisters.

Genome-Scale Networks Link Neurodegenerative Disease Genes to α-Synuclein through Specific Molecular Pathways.

Numerous genes and molecular pathways are implicated in neurodegenerative proteinopathies, but their inter-relationships are poorly understood. We systematically mapped molecular pathways underlying the toxicity of alpha-synuclein (α-syn), a protein central to Parkinson's disease. Genome-wide screens in yeast identified 332 genes that impact α-syn toxicity. To "humanize" this molecular network, we developed a computational method, TransposeNet. This integrates a Steiner prize-collecting approach with homology assignment through sequence, structure, and interaction topology. TransposeNet linked α-syn to multiple parkinsonism genes and druggable targets through perturbed protein trafficking and ER quality control as well as mRNA metabolism and translation. A calcium signaling hub linked these processes to perturbed mitochondrial quality control and function, metal ion transport, transcriptional regulation, and signal transduction. Parkinsonism gene interaction profiles spatially opposed in the network (ATP13A2/PARK9 and VPS35/PARK17) were highly distinct, and network relationships for specific genes (LRRK2/PARK8, ATXN2, and EIF4G1/PARK18) were confirmed in patient induced pluripotent stem cell (iPSC)-derived neurons. This cross-species platform connected diverse neurodegenerative genes to proteinopathy through specific mechanisms and may facilitate patient stratification for targeted therapy.

The reprogramming of tumor stroma by HSF1 is a potent enabler of malignancy.

Stromal cells within the tumor microenvironment are essential for tumor progression and metastasis. Surprisingly little is known about the factors that drive the transcriptional reprogramming of stromal cells within tumors. We report that the transcriptional regulator heat shock factor 1 (HSF1) is frequently activated in cancer-associated fibroblasts (CAFs), where it is a potent enabler of malignancy. HSF1 drives a transcriptional program in CAFs that complements, yet is completely different from, the program it drives in adjacent cancer cells. This CAF program is uniquely structured to support malignancy in a non-cell-autonomous way. Two central stromal signaling molecules-TGF-ß and SDF1-play a critical role. In early-stage breast and lung cancer, high stromal HSF1 activation is strongly associated with poor patient outcome. Thus, tumors co-opt the ancient survival functions of HSF1 to orchestrate malignancy in both cell-autonomous and non-cell-autonomous ways, with far-reaching therapeutic implications.

Tight coordination of protein translation and HSF1 activation supports the anabolic malignant state.

The ribosome is centrally situated to sense metabolic states, but whether its activity, in turn, coherently rewires transcriptional responses is unknown. Here, through integrated chemical-genetic analyses, we found that a dominant transcriptional effect of blocking protein translation in cancer cells was inactivation of heat shock factor 1 (HSF1), a multifaceted transcriptional regulator of the heat-shock response and many other cellular processes essential for anabolic metabolism, cellular proliferation, and tumorigenesis. These analyses linked translational flux to the regulation of HSF1 transcriptional activity and to the modulation of energy metabolism. Targeting this link with translation initiation inhibitors such as rocaglates deprived cancer cells of their energy and chaperone armamentarium and selectively impaired the proliferation of both malignant and premalignant cells with early-stage oncogenic lesions.

Quantitative analysis of HSP90-client interactions reveals principles of substrate recognition.

HSP90 is a molecular chaperone that associates with numerous substrate proteins called clients. It plays many important roles in human biology and medicine, but determinants of client recognition by HSP90 have remained frustratingly elusive. We systematically and quantitatively surveyed most human kinases, transcription factors, and E3 ligases for interaction with HSP90 and its cochaperone CDC37. Unexpectedly, many more kinases than transcription factors bound HSP90. CDC37 interacted with kinases, but not with transcription factors or E3 ligases. HSP90::kinase interactions varied continuously over a 100-fold range and provided a platform to study client protein recognition. In wild-type clients, HSP90 did not bind particular sequence motifs, but rather associated with intrinsically unstable kinases. Stabilization of the kinase in either its active or inactive conformation with diverse small molecules decreased HSP90 association. Our results establish HSP90 client recognition as a combinatorial process: CDC37 provides recognition of the kinase family, whereas thermodynamic parameters determine client binding within the family.

HSF1 drives a transcriptional program distinct from heat shock to support highly malignant human cancers.

Heat-Shock Factor 1 (HSF1), master regulator of the heat-shock response, facilitates malignant transformation, cancer cell survival, and proliferation in model systems. The common assumption is that these effects are mediated through regulation of heat-shock protein (HSP) expression. However, the transcriptional network that HSF1 coordinates directly in malignancy and its relationship to the heat-shock response have never been defined. By comparing cells with high and low malignant potential alongside their nontransformed counterparts, we identify an HSF1-regulated transcriptional program specific to highly malignant cells and distinct from heat shock. Cancer-specific genes in this program support oncogenic processes: cell-cycle regulation, signaling, metabolism, adhesion and translation. HSP genes are integral to this program, however, many are uniquely regulated in malignancy. This HSF1 cancer program is active in breast, colon and lung tumors isolated directly from human patients and is strongly associated with metastasis and death. Thus, HSF1 rewires the transcriptome in tumorigenesis, with prognostic and therapeutic implications.

Poly-glutamine expanded huntingtin dramatically alters the genome wide binding of HSF1.

In Huntington's disease (HD), polyglutamine expansions in the huntingtin (Htt) protein cause subtle changes in cellular functions that, over-time, lead to neurodegeneration and death. Studies have indicated that activation of the heat shock response can reduce many of the effects of mutant Htt in disease models, suggesting that the heat shock response is impaired in the disease. To understand the basis for this impairment, we have used genome-wide chromatin immunoprecipitation followed by massively parallel sequencing (ChIP-Seq) to examine the effects of mutant Htt on the master regulator of the heat shock response, HSF1. We find that, under normal conditions, HSF1 function is highly similar in cells carrying either wild-type or mutant Htt. However, polyQ-expanded Htt severely blunts the HSF1-mediated stress response. Surprisingly, we find that the HSF1 targets most affected upon stress are not directly associated with proteostasis, but with cytoskeletal binding, focal adhesion and GTPase activity. Our data raise the intriguing hypothesis that the accumulated damage from life-long impairment in these stress responses may contribute significantly to the etiology of Huntington's disease.

Computational integration of homolog and pathway gene module expression reveals general stemness signatures.

The stemness hypothesis states that all stem cells use common mechanisms to regulate self-renewal and multi-lineage potential. However, gene expression meta-analyses at the single gene level have failed to identify a significant number of genes selectively expressed by a broad range of stem cell types. We hypothesized that stemness may be regulated by modules of homologs. While the expression of any single gene within a module may vary from one stem cell type to the next, it is possible that the expression of the module as a whole is required so that the expression of different, yet functionally-synonymous, homologs is needed in different stem cells. Thus, we developed a computational method to test for stem cell-specific gene expression patterns from a comprehensive collection of 49 murine datasets covering 12 different stem cell types. We identified 40 individual genes and 224 stemness modules with reproducible and specific up-regulation across multiple stem cell types. The stemness modules included families regulating chromatin remodeling, DNA repair, and Wnt signaling. Strikingly, the majority of modules represent evolutionarily related homologs. Moreover, a score based on the discovered modules could accurately distinguish stem cell-like populations from other cell types in both normal and cancer tissues. This scoring system revealed that both mouse and human metastatic populations exhibit higher stemness indices than non-metastatic populations, providing further evidence for a stem cell-driven component underlying the transformation to metastatic disease.

Molecular signatures of quiescent, mobilized and leukemia-initiating hematopoietic stem cells.

Hematopoietic stem cells (HSC) are rare, multipotent cells capable of generating all specialized cells of the blood system. Appropriate regulation of HSC quiescence is thought to be crucial to maintain their lifelong function; however, the molecular pathways controlling stem cell quiescence remain poorly characterized. Likewise, the molecular events driving leukemogenesis remain elusive. In this study, we compare the gene expression profiles of steady-state bone marrow HSC to non-self-renewing multipotent progenitors; to HSC treated with mobilizing drugs that expand the HSC pool and induce egress from the marrow; and to leukemic HSC in a mouse model of chronic myelogenous leukemia. By intersecting the resulting lists of differentially regulated genes we identify a subset of molecules that are downregulated in all three circumstances, and thus may be particularly important for the maintenance and function of normal, quiescent HSC. These results identify potential key regulators of HSC and give insights into the clinically important processes of HSC mobilization for transplantation and leukemic development from cancer stem cells.

A global analysis of genetic interactions in Caenorhabditis elegans.

BACKGROUND: Understanding gene function and genetic relationships is fundamental to our efforts to better understand biological systems. Previous studies systematically describing genetic interactions on a global scale have either focused on core biological processes in protozoans or surveyed catastrophic interactions in metazoans. Here, we describe a reliable high-throughput approach capable of revealing both weak and strong genetic interactions in the nematode Caenorhabditis elegans. RESULTS: We investigated interactions between 11 'query' mutants in conserved signal transduction pathways and hundreds of 'target' genes compromised by RNA interference (RNAi). Mutant-RNAi combinations that grew more slowly than controls were identified, and genetic interactions inferred through an unbiased global analysis of the interaction matrix. A network of 1,246 interactions was uncovered, establishing the largest metazoan genetic-interaction network to date. We refer to this approach as systematic genetic interaction analysis (SGI). To investigate how genetic interactions connect genes on a global scale, we superimposed the SGI network on existing networks of physical, genetic, phenotypic and coexpression interactions. We identified 56 putative functional modules within the superimposed network, one of which regulates fat accumulation and is coordinated by interactions with bar-1(ga80), which encodes a homolog of beta-catenin. We also discovered that SGI interactions link distinct subnetworks on a global scale. Finally, we showed that the properties of genetic networks are conserved between C. elegans and Saccharomyces cerevisiae, but that the connectivity of interactions within the current networks is not. CONCLUSIONS: Synthetic genetic interactions may reveal redundancy among functional modules on a global scale, which is a previously unappreciated level of organization within metazoan systems. Although the buffering between functional modules may differ between species, studying these differences may provide insight into the evolution of divergent form and function.

SAM-T04: what is new in protein-structure prediction for CASP6.

The SAM-T04 method for predicting protein structures uses a single protocol across the entire range of targets, from comparative modeling to new folds. This protocol is similar to the SAM-T02 protocol used in CASP5, but has improvements in the iterative search for similar sequences in finding and aligning templates, in creating fragment libraries, in generating protein conformations, and in scoring the conformations. The automatic procedure made some improvements over simply selecting an alignment to the highest-scoring template, and human intervention made substantial improvements over the automatic procedure. The main improvements made by human intervention were from adding constraints to build (or retain) beta-sheets and from splitting multidomain proteins into separate domains. The uniform protocol was moderately successful across the entire range of target difficulty, but was somewhat less successful than other approaches in CASP6 on the comparative modeling targets.