Identification and characterization of protein interactions with the major Niemann-Pick type C disease protein in yeast reveals pathways of therapeutic potential

Niemann-Pick type C (NP-C) disease is a rare lysosomal storage disease caused by mutations in NPC1 (95% cases) or NPC2 (5% cases). These proteins function together in cholesterol egress from the lysosome, whereby upon mutation, cholesterol and other lipids accumulate causing major pathologies. However, it is not fully understood how cholesterol is transported from NPC1 residing at the lysosomal membrane to the endoplasmic reticulum (ER) and plasma membrane. The yeast ortholog of NPC1, Niemann-Pick type C-related protein-1 (Ncr1), functions similarly to NPC1; when transfected into a mammalian cell lacking NPC1, Ncr1 rescues the diagnostic hallmarks of cholesterol and sphingolipid accumulation. Here, we aimed to identify and characterize protein-protein interactions (PPIs) with the yeast Ncr1 protein. A genome-wide split-ubiquitin membrane yeast two-hybrid (MYTH) protein interaction screen identified 11 ER membrane-localized, full-length proteins interacting with Ncr1 at the lysosomal/vacuolar membrane. These highlight the importance of ER-vacuole membrane interface and include PPIs with the Cyb5/Cbr1 electron transfer system, the ceramide synthase complex, and the Sec61/Sbh1 protein translocation complex. These PPIs were not detected in a sterol auxotrophy condition and thus depend on normal sterol metabolism. To provide biological context for the Ncr1-Cyb5 PPI, a yeast strain lacking this PPI (via gene deletions) exhibited altered levels of sterols and sphingolipids including increased levels of glucosylceramide that mimic NP-C disease. Overall, the results herein provide new physical and genetic interaction models to further use the yeast model of NP-C disease to better understand human NP-C disease.

Identifying Genes Related to Acute Myocardial Infarction Based on Network Control Capability

Identifying genes significantly related to diseases is a focus in the study of disease mechanisms. In this paper, from the perspective of integrated analysis and dynamic control, a method for identifying genes significantly related to diseases based on logic networks constructed by the LAPP method, referred to as NCCM, is proposed and applied to the study of the mechanism of acute myocardial infarction (AMI). It is found that 82.35% of 17 differential control capability genes (DCCGs) identified by NCCM are significantly correlated with AMI/MI in the literature and DISEASES database. The enrichment analysis of DCCGs shows that AMI is closely related to the positive regulation of vascular-associated smooth muscle cell proliferation and regulation of cytokine production involved in the immune response, in which HBEGF, THBS1, NR4A3, NLRP3, EDN1, and MMP9 play a crucial role. In addition, although the expression levels of CNOT6L and ACYP1 are not significantly different between the control group and the AMI group, NCCM shows that they are significantly associated with AMI. Although this result still needs further verification, it shows that the method can not only identify genes with large differences in expression but also identify genes that are associated with diseases but with small changes in expression.

Hsp90 Co-chaperones Form Plastic Genetic Networks Adapted to Client Maturation

Heat shock protein 90 (Hsp90) is a molecular chaperone regulating the activity of diverse client proteins together with a plethora of different co-chaperones. Whether these functionally cooperate has remained enigmatic. We analyze all double mutants of 11 Saccharomyces cerevisiae Hsp90 co-chaperones in vivo concerning effects on cell physiology and the activation of specific client proteins. We find that client activation is supported by a genetic network with weak epistasis between most co-chaperones and a few modules with strong genetic interactions. These include an epistatic module regulating protein translation and dedicated epistatic networks for specific clients. For kinases, the bridging of Hsp70 and Hsp90 by Sti1/Hop is essential for activation, whereas for steroid hormone receptors, an epistatic module regulating their dwell time on Hsp90 is crucial, highlighting the specific needs of different clients. Thus, the Hsp90 system is characterized by plastic co-chaperone networks fine-tuning the conformational processing in a client-specific manner.

Protein trapping leads to altered synaptic proteostasis in synucleinopathies

Parkinson's disease (PD) is associated with the accumulation of alpha-synuclein (aSyn) in intracellular inclusions known as Lewy bodies and Lewy neurites. Under physiological conditions, aSyn is found at the presynaptic terminal and exists in a dynamic equilibrium between soluble, membrane-associated and aggregated forms. Emerging evidence suggests that, under pathological conditions, aSyn begins to accumulate and acquire a toxic function at the synapse, impairing their normal function and connectivity. However, the precise molecular mechanisms linking aSyn accumulation and synaptic dysfunction are still elusive. Here, we provide an overview of our current findings and discuss the hypothesis that certain aSyn aggregates may interact with proteins with whom aSyn normally does not interact with, thereby trapping them and preventing them from performing their normal functions in the cell. We posit that such abnormal interactions start to occur during the prodromal stages of PD, eventually resulting in the overt manifestation of clinical features. Therefore, understanding the nature and behaviour of toxic aSyn species and their contribution to aSyn-mediated toxicity is crucial for the development of therapeutic strategies capable of modifying disease progression in PD and other synucleinopathies.

Molecular mechanisms in chaperonopathies: clues to understanding the histopathological abnormalities and developing novel therapies

Molecular chaperones, many of which are heat shock proteins (Hsps), are components of the chaperoning system and when defective can cause disease, the chaperonopathies. Chaperone-gene variants cause genetic chaperonopathies, whereas in the acquired chaperonopathies the genes are normal, but their protein products are not, due to aberrant post-transcriptional mechanisms, e.g. post-translational modifications (PTMs). Since the chaperoning system is widespread in the body, chaperonopathies affect various tissues and organs, making these diseases of interest to a wide range of medical specialties. Genetic chaperonopathies are uncommon but the acquired ones are frequent, encompassing various types of cancer, and inflammatory and autoimmune disorders. The clinical picture of chaperonopathies is known. Much less is known on the impact that pathogenic mutations and PTMs have on the properties and functions of chaperone molecules. Elucidation of these molecular alterations is necessary for understanding the mechanisms underpinning the tissue and organ abnormalities occurring in patients. To illustrate this issue, we discuss structural-functional alterations caused by mutation in the chaperones CCT5 and HSPA9, and PTM effects on Hsp60. The data provide insights into what may happen when CCT5 and HSPA9 malfunction in patients, e.g. accumulation of cytotoxic protein aggregates with tissue destruction; or for Hsp60 with aberrant PTM, degradation and/or secretion of the chaperonin with mitochondrial damage. These and other possibilities are now open for investigation. © 2019 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Computational Inference of Gene Co-Expression Networks for the identification of Lung Carcinoma Biomarkers: An Ensemble Approach

Gene Networks (GN), have emerged as an useful tool in recent years for the analysis of different diseases in the field of biomedicine. In particular, GNs have been widely applied for the study and analysis of different types of cancer. In this context, Lung carcinoma is among the most common cancer types and its short life expectancy is partly due to late diagnosis. For this reason, lung cancer biomarkers that can be easily measured are highly demanded in biomedical research. In this work, we present an application of gene co-expression networks in the modelling of lung cancer gene regulatory networks, which ultimately served to the discovery of new biomarkers. For this, a robust GN inference was performed from microarray data concomitantly using three different co-expression measures. Results identified a major cluster of genes involved in SRP-dependent co-translational protein target to membrane, as well as a set of 28 genes that were exclusively found in networks generated from cancer samples. Amongst potential biomarkers, genes N C K A P 1 L and D M D are highlighted due to their implications in a considerable portion of lung and bronchus primary carcinomas. These findings demonstrate the potential of GN reconstruction in the rational prediction of biomarkers.

Genetic interaction networks mediate individual statin drug response in Saccharomyces cerevisiae

Eukaryotic genetic interaction networks (GINs) are extensively described in the Saccharomyces cerevisiae S288C model using deletion libraries, yet being limited to this one genetic background, not informative to individual drug response. Here we created deletion libraries in three additional genetic backgrounds. Statin response was probed with five queries against four genetic backgrounds. The 20 resultant GINs representing drug–gene and gene–gene interactions were not conserved by functional enrichment, hierarchical clustering, and topology-based community partitioning. An unfolded protein response (UPR) community exhibited genetic background variation including different betweenness genes that were network bottlenecks, and we experimentally validated this UPR community via measurements of the UPR that were differentially activated and regulated in statin-resistant strains relative to the statin-sensitive S288C background. These network analyses by topology and function provide insight into the complexity of drug response influenced by genetic background.

Genes are wired together in functional genetic interaction networks (GINs) specific for different traits. We asked a simple question: do GINs for particular traits vary with individuals? The trait we investigated was response to statins, cholesterol-lowering drugs prescribed to 30 million people worldwide. Building comprehensive GINs requires a library of cells with a different gene deleted covering the entire genome that is available only in Saccharomyces cerevisiae (Baker’s yeast), a well-defined model for human genetics. However, the yeast libraries being limited to one genetic background are not informative of individuals. Therefore, we constructed GINs in additional genetic backgrounds and showed statin-specific GINs were not conserved, albeit there was a common fundamental process mediating statin-resistance. Our results identify a mechanism to further investigate in the millions of people that do not respond to statins and the methodology will enhance the discovery and development of drugs to treat other major diseases.

The Co-chaperone Cns1 and the Recruiter Protein Hgh1 Link Hsp90 to Translation Elongation via Chaperoning Elongation Factor 2

The Hsp90 chaperone machinery in eukaryotes comprises a number of distinct accessory factors. Cns1 is one of the few essential co-chaperones in yeast, but its structure and function remained unknown. Here, we report the X-ray structure of the Cns1 fold and NMR studies on the partly disordered, essential segment of the protein. We demonstrate that Cns1 is important for maintaining translation elongation, specifically chaperoning the elongation factor eEF2. In this context, Cns1 interacts with the novel co-factor Hgh1 and forms a quaternary complex together with eEF2 and Hsp90. The in vivo folding and solubility of eEF2 depend on the presence of these proteins. Chaperoning of eEF2 by Cns1 is essential for yeast viability and requires a defined subset of the Hsp90 machinery as well as the identified eEF2 recruiting factor Hgh1.

Bridging human chaperonopathies and microbial chaperonins

Chaperonins are molecular chaperones that play critical physiological roles, but they can be pathogenic. Malfunctional chaperonins cause chaperonopathies of great interest within various medical specialties. Although the clinical-genetic aspects of many chaperonopathies are known, the molecular mechanisms causing chaperonin failure and tissue lesions are poorly understood. Progress is necessary to improve treatment, and experimental models that mimic the human situation provide a promising solution. We present two models: one prokaryotic (the archaeon Pyrococcus furiosus) with eukaryotic-like chaperonins and one eukaryotic (Chaetomium thermophilum), both convenient for isolation-study of chaperonins, and report illustrative results pertaining to a pathogenic mutation of CCT5.

Network Analyses of Integrated Differentially Expressed Genes in Papillary Thyroid Carcinoma to Identify Characteristic Genes

Papillary thyroid carcinoma (PTC) is the most common type of thyroid cancer. Identifying characteristic genes of PTC are of great importance to reveal its potential genetic mechanisms. In this paper, we proposed a framework, as well as a measure named Normalized Centrality Measure (NCM), to identify characteristic genes of PTC. The framework consisted of four steps. First, both up-regulated genes and down-regulated genes, collectively called differentially expressed genes (DEGs), were screened and integrated together from four datasets, that is, GSE3467, GSE3678, GSE33630, and GSE58545; second, an interaction network of DEGs was constructed, where each node represented a gene and each edge represented an interaction between linking nodes; third, both traditional measures and the NCM measure were used to analyze the topological properties of each node in the network. Compared with traditional measures, more genes related to PTC were identified by the NCM measure; fourth, by mining the high-density subgraphs of this network and performing Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, several meaningful results were captured, most of which were demonstrated to be associated with PTC. The experimental results proved that this network framework and the NCM measure are useful for identifying more characteristic genes of PTC.

Multiple functionalities of molecular chaperones revealed through systematic mapping of their interaction networks

Chaperones are a highly interactive group of proteins that function globally in many cellular processes involved in maintaining protein homeostasis. Traditional biochemical assays typically do not provide a complete view of the intricate networks through which chaperones collaborate to promote proteostasis. Recent advances in high-throughput systematic analyses of chaperone interactions have uncovered that chaperones display a remarkable cooperativity in their interactions with numerous client proteins. This cooperativity has been found to be a fundamental aspect of a properly functioning cell. Aberrant formation or improper regulation of these interactions can easily lead to disease states. Herein, we provide an overview of the use of large-scale interaction assays, whether physical (protein-protein) or genetic (epistatic), to study chaperone interaction networks. Importantly, we discuss the ongoing need for such studies to determine the mechanisms by which protein homeostasis is controlled in the cell.