Cliques in mitotic spindle network bring kinetochore-associated complexes to form dependence pathway

Dhx38 is required for the maintenance and differentiation of erythro-myeloid progenitors and hematopoietic stem cells by alternative splicing

Mutations that occur in RNA-splicing machinery may contribute to hematopoiesis-related diseases. How splicing factor mutations perturb hematopoiesis, especially in the differentiation of erythro-myeloid progenitors (EMPs), remains elusive. Dhx38 is a pre-mRNA splicing-related DEAH box RNA helicase, for which the physiological functions and splicing mechanisms during hematopoiesis currently remain unclear. Here, we report that Dhx38 exerts a broad effect on definitive EMPs as well as the differentiation and maintenance of hematopoietic stem and progenitor cells (HSPCs). In dhx38 knockout zebrafish, EMPs and HSPCs were found to be arrested in mitotic prometaphase, accompanied by a ‘grape’ karyotype, owing to the defects in chromosome alignment. Abnormal alternatively spliced genes related to chromosome segregation, the microtubule cytoskeleton, cell cycle kinases and DNA damage were present in the dhx38 mutants. Subsequently, EMPs and HSPCs in dhx38 mutants underwent P53-dependent apoptosis. This study provides novel insights into alternative splicing regulated by Dhx38, a process that plays a crucial role in the proliferation and differentiation of fetal EMPs and HSPCs.

Construction and analysis of the protein-protein interaction networks based on gene expression profiles of Parkinson's disease

Background

Parkinson's Disease (PD) is one of the most prevailing neurodegenerative diseases. Improving diagnoses and treatments of this disease is essential, as currently there exists no cure for this disease. Microarray and proteomics data have revealed abnormal expression of several genes and proteins responsible for PD. Nevertheless, few studies have been reported involving PD-specific protein-protein interactions.

Results

Microarray based gene expression data and protein-protein interaction (PPI) databases were combined to construct the PPI networks of differentially expressed (DE) genes in post mortem brain tissue samples of patients with Parkinson's disease. Samples were collected from the substantia nigra and the frontal cerebral cortex. From the microarray data, two sets of DE genes were selected by 2-tailed t-tests and Significance Analysis of Microarrays (SAM), run separately to construct two Query-Query PPI (QQPPI) networks. Several topological properties of these networks were studied. Nodes with High Connectivity (hubs) and High Betweenness Low Connectivity (bottlenecks) were identified to be the most significant nodes of the networks. Three and four-cliques were identified in the QQPPI networks. These cliques contain most of the topologically significant nodes of the networks which form core functional modules consisting of tightly knitted sub-networks. Hitherto unreported 37 PD disease markers were identified based on their topological significance in the networks. Of these 37 markers, eight were significantly involved in the core functional modules and showed significant change in co-expression levels. Four (ARRB2, STX1A, TFRC and MARCKS) out of the 37 markers were found to be associated with several neurotransmitters including dopamine.

Conclusion

This study represents a novel investigation of the PPI networks for PD, a complex disease. 37 proteins identified in our study can be considered as PD network biomarkers. These network biomarkers may provide as potential therapeutic targets for PD applications development.

Analysis of schizophrenia and hepatocellular carcinoma genetic network with corresponding modularity and pathways: novel insights to the immune system

Background

Schizophrenic patients show lower incidences of cancer, implicating schizophrenia may be a protective factor against cancer. To study the genetic correlation between the two diseases, a specific PPI network was constructed with candidate genes of both schizophrenia and hepatocellular carcinoma. The network, designated schizophrenia-hepatocellular carcinoma network (SHCN), was analysed and cliques were identified as potential functional modules or complexes. The findings were compared with information from pathway databases such as KEGG, Reactome, PID and ConsensusPathDB.

Results

The functions of mediator genes from SHCN show immune system and cell cycle regulation have important roles in the eitology mechanism of schizophrenia. For example, the over-expressing schizophrenia candidate genes, SIRPB1, SYK and LCK, are responsible for signal transduction in cytokine production; immune responses involving IL-2 and TREM-1/DAP12 pathways are relevant for the etiology mechanism of schizophrenia. Novel treatments were proposed by searching the target genes of FDA approved drugs with genes in potential protein complexes and pathways. It was found that Vitamin A, retinoid acid and a few other immune response agents modulated by RARA and LCK genes may be potential treatments for both schizophrenia and hepatocellular carcinoma.

Conclusions

This is the first study showing specific mediator genes in the SHCN which may suppress tumors. We also show that the schizophrenic protein interactions and modulation with cancer implicates the importance of immune system for etiology of schizophrenia.

Cliques for the identification of gene signatures for colorectal cancer across population

Background

Colorectal cancer (CRC) is one of the most commonly diagnosed cancers worldwide. Studies have correlated risk of CRC development with dietary habits and environmental conditions. Gene signatures for any disease can identify the key biological processes, which is especially useful in studying cancer development. Such processes can be used to evaluate potential drug targets. Though recognition of CRC gene-signatures across populations is crucial to better understanding potential novel treatment options for CRC, it remains a challenging task.

Results

We developed a topological and biological feature-based network approach for identifying the gene signatures across populations. In this work, we propose a novel approach of using cliques to understand the variability within population. Cliques are more conserved and co-expressed, therefore allowing identification and comparison of cliques across a population which can help researchers study gene variations. Our study was based on four publicly available expression datasets belonging to four different populations across the world. We identified cliques of various sizes (0 to 7) across the four population networks. Cliques of size seven were further analyzed across populations for their commonality and uniqueness. Forty-nine common cliques of size seven were identified. These cliques were further analyzed based on their connectivity profiles. We found associations between the cliques and their connectivity profiles across networks. With these clique connectivity profiles (CCPs), we were able to identify the divergence among the populations, important biological processes (cell cycle, signal transduction, and cell differentiation), and related gene pathways. Therefore the genes identified in these cliques and their connectivity profiles can be defined as the gene-signatures across populations. In this work we demonstrate the power and effectiveness of cliques to study CRC across populations.

Conclusions

We developed a new approach where cliques and their connectivity profiles helped elucidate the variation and similarity in CRC gene profiles across four populations with unique dietary habits.

Identification of novel mitosis regulators through data mining with human centromere/kinetochore proteins as group queries

Background

Proteins functioning in the same biological pathway tend to be transcriptionally co-regulated or form protein-protein interactions (PPI). Multiple spatially and temporally regulated events are coordinated during mitosis to achieve faithful chromosome segregation. The molecular players participating in mitosis regulation are still being unravelled experimentally or using in silico methods.

Results

An extensive literature review has led to a compilation of 196 human centromere/kinetochore proteins, all with experimental evidence supporting the subcellular localization. Sixty-four were designated as “core” centromere/kinetochore components based on peak expression and/or well-characterized functions during mitosis. By interrogating and integrating online resources, we have mined for genes/proteins that display transcriptional co-expression or PPI with the core centromere/kinetochore components. Top-ranked hubs in either co-expression or PPI network are not only enriched with known mitosis regulators, but also contain candidates whose mitotic functions are not yet established. Experimental validation found that KIAA1377 is a novel centrosomal protein that also associates with microtubules and midbody; while TRIP13 is a novel kinetochore protein and directly interacts with mitotic checkpoint silencing protein p31^comet.

Conclusions

Transcriptional co-expression and PPI network analyses with known human centromere/kinetochore proteins as a query group help identify novel potential mitosis regulators.

RED, a spindle pole-associated protein, is required for kinetochore localization of MAD1, mitotic progression, and activation of the spindle assembly checkpoint

The spindle assembly checkpoint (SAC) is essential for ensuring the proper attachment of kinetochores to the spindle and, thus, the precise separation of paired sister chromatids during mitosis. The SAC proteins are recruited to the unattached kinetochores for activation of the SAC in prometaphase. However, it has been less studied whether activation of the SAC also requires the proteins that do not localize to the kinetochores. Here, we show that the nuclear protein RED, also called IK, a down-regulator of human leukocyte antigen (HLA) II, interacts with the human SAC protein MAD1. Two RED-interacting regions identified in MAD1 are from amino acid residues 301-340 and 439-480, designated as MAD1(301-340) and MAD1(439-480), respectively. Our observations reveal that RED is a spindle pole-associated protein that colocalizes with MAD1 at the spindle poles in metaphase and anaphase. Depletion of RED can cause a shorter mitotic timing, a failure in the kinetochore localization of MAD1 in prometaphase, and a defect in the SAC. Furthermore, the RED-interacting peptides MAD1(301-340) and MAD1(439-480), fused to enhanced green fluorescence protein, can colocalize with RED at the spindle poles in prometaphase, and their expression can abrogate the SAC. Taken together, we conclude that RED is required for kinetochore localization of MAD1, mitotic progression, and activation of the SAC.

Construction and analysis of the protein-protein interaction networks for schizophrenia, bipolar disorder, and major depression

BACKGROUND

Schizophrenia, bipolar disorder, and major depression are devastating mental diseases, each with distinctive yet overlapping epidemiologic characteristics. Microarray and proteomics data have revealed genes which expressed abnormally in patients. Several single nucleotide polymorphisms (SNPs) and mutations are associated with one or more of the three diseases. Nevertheless, there are few studies on the interactions among the disease-associated genes and proteins.

RESULTS

This study, for the first time, incorporated microarray and protein-protein interaction (PPI) databases to construct the PPI network of abnormally expressed genes in postmortem brain samples of schizophrenia, bipolar disorder, and major depression patients. The samples were collected from Brodmann area (BA) 10 of the prefrontal cortex. Abnormally expressed disease genes were selected by t-tests comparing the disease and control samples. These genes were involved in housekeeping functions (e.g. translation, transcription, energy conversion, and metabolism), in brain specific functions (e.g. signal transduction, neuron cell differentiation, and cytoskeleton), or in stress responses (e.g. heat shocks and biotic stress).The diseases were interconnected through several "switchboard"-like nodes in the PPI network or shared abnormally expressed genes. A "core" functional module which consisted of a tightly knitted sub-network of clique-5 and -4s was also observed. These cliques were formed by 12 genes highly expressed in both disease and control samples.

CONCLUSIONS

Several previously unidentified disease marker genes and drug targets, such as SBNO2 (schizophrenia), SEC24C (bipolar disorder), and SRRT (major depression), were identified based on statistical and topological analyses of the PPI network. The shared or interconnecting marker genes may explain the shared symptoms of the studied diseases. Furthermore, the "switchboard" genes, such as APP, UBC, and YWHAZ, are proposed as potential targets for developing new treatments due to their functional and topological significance.

Gene expression-based chemical genomics identifies potential therapeutic drugs in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is an aggressive tumor with a poor prognosis. Currently, only sorafenib is approved by the FDA for advanced HCC treatment; therefore, there is an urgent need to discover candidate therapeutic drugs for HCC. We hypothesized that if a drug signature could reverse, at least in part, the gene expression signature of HCC, it might have the potential to inhibit HCC-related pathways and thereby treat HCC. To test this hypothesis, we first built an integrative platform, the "Encyclopedia of Hepatocellular Carcinoma genes Online 2", dubbed EHCO2, to systematically collect, organize and compare the publicly available data from HCC studies. The resulting collection includes a total of 4,020 genes. To systematically query the Connectivity Map (CMap), which includes 6,100 drug-mediated expression profiles, we further designed various gene signature selection and enrichment methods, including a randomization technique, majority vote, and clique analysis. Subsequently, 28 out of 50 prioritized drugs, including tanespimycin, trichostatin A, thioguanosine, and several anti-psychotic drugs with anti-tumor activities, were validated via MTT cell viability assays and clonogenic assays in HCC cell lines. To accelerate their future clinical use, possibly through drug-repurposing, we selected two well-established drugs to test in mice, chlorpromazine and trifluoperazine. Both drugs inhibited orthotopic liver tumor growth. In conclusion, we successfully discovered and validated existing drugs for potential HCC therapeutic use with the pipeline of Connectivity Map analysis and lab verification, thereby suggesting the usefulness of this procedure to accelerate drug repurposing for HCC treatment.

From NPC therapeutic target identification to potential treatment strategy

Nasopharyngeal carcinoma (NPC) is relatively rare in Western countries but is a common cancer in southern Asia. Many differentially expressed genes have been linked to NPC; however, how to prioritize therapeutic targets and potential drugs from unsorted gene lists remains largely unknown. We first collected 558 upregulated and 993 downregulated NPC genes from published microarray data and the primary literatures. We then postulated that conversion of gene signatures into the protein-protein interaction network and analyzing the network topologically could provide insight into key regulators involved in tumorigenesis of NPC. Of particular interest was the presence of cliques, called fully connected subgraphs, in the inferred NPC networks. These clique-based hubs, connecting with more than three queries and ranked higher than other nodes in the NPC protein-protein interaction network, were further narrowed down by pathway analysis to retrieve 24 upregulated and 6 downregulated bottleneck genes for predicting NPC carcinogenesis. Moreover, additional oncogenes, tumor suppressor genes, genes involved in protein complexes, and genes obtained after functional profiling were merged with the bottleneck genes to form the final gene signature of 38 upregulated and 10 downregulated genes. We used the initial and final NPC gene signatures to query the Connectivity Map, respectively, and found that target reduction through our pipeline could efficiently uncover potential drugs with cytotoxicity to NPC cancer cells. An integrative Web site (http://140.109.23.188:8080/NPC) was established to facilitate future NPC research. This in silico approach, from target prioritization to potential drugs identification, might be an effective method for various cancer researches.

The impact of miR-34a on protein output in hepatocellular carcinoma HepG2 cells

MicroRNAs are small non-coding RNA molecules that play essential roles in biological processes ranging from cell cycle to cell migration and invasion. Accumulating evidence suggests that miR-34a, as a key mediator of p53 tumor suppression, is aberrantly expressed in human cancers. In the present study, we aimed to explore the precise biological role of miR-34a and the global protein changes in HCC cell line HepG2 cells transiently transfected with miR-34a. Transfection of miR-34a into HepG2 cells caused suppression of cell proliferation, inhibition of cell migration and invasion. It also induced an accumulation of HepG2 cells in G1 phase. Among 116 protein spots with differential expression separated by 2-DE method, 34 proteins were successfully identified by MALDI-TOF/TOF analysis. Of these, 15 downregulated proteins may be downstream targets of miR-34a. Bioinformatics analysis produced a protein-protein interaction network, which revealed that the p53 signaling pathway and cell cycle pathway were two major hubs containing most of the proteins regulated by miR-34a. Cytoskeletal proteins such as LMNA, GFAP, MACF1, ALDH2, and LOC100129335 are potential targets of miR-34a. In conclusion, abrogation of miR-34a function could cause downstream molecules to switch on or off, leading to HCC development.