Month: September 2020

Therefore, the problem is formulated as finding all the strongly connected subgraphs in the graph. Moreover, since PCI-32765 proteins usually contain more than one domain, a practical algorithm must be able to find the overlapping subgraphs. In graph theory, a subgraph that is more highly connected than other parts of the graph is also called a community. The community-finding problem has received much attention since the seminal paper by Newman. Unfortunately, the overlapping community-finding problem has not been tackled in most of the traditional graph-based or clustering algorithms. In 2005, Palla et al. proposed a clique percolation method for uncovering overlapping communities. They defined the k-clique community as a set of nodes belonging to adjacent k-cliques, i.e., cliques with k nodes. Later, Kumpula et al. proposed a more efficient clique percolation algorithm to find the overlapping kcommunities, for a fixed k. Their algorithm works in a sequential manner. This algorithm can detect the overlapping kclique communities in linear time in terms of the number of kcliques in the graph. However, none of these algorithms can be directly applied to the domain finding problem. Both algorithms require the enumeration of all cliques with sizes smaller than kmax, where kmax is the size of the largest clique in the graph. This is not practical for proteome-scale domain detection, in which we have a dense graph of about 20,000-70,000 nodes. A populated domain can appear hundreds or even thousands of times in a genome. On the other hand, one may suggest using a small value instead of kmax to overcome this issue. However, this will cause irrelevant domains to be merged. Here, we propose a heuristic algorithm that does not enumerate all the small cliques by using the properties of the domain detection problem. First, from our protein sequence-indexing step, we extract and store all the sequences that share the same hash seeds. According to the way our graph is defined, all such sequences are connected to each other and thus form a clique. Second, the more frequently a hash seed appears, the higher the confidence assigned to this seed. Larger cliques therefore have higher confidence. According to these properties, in order to avoid the chain effect caused by the 2-clique, our algorithm is designed to work in a backward manner. It first eliminates all the edges with weights smaller than a pre-defined threshold. We use two as the default value, which means that two sequences are considered to be homologous if they contain at least two common hash seeds. The algorithm then begins with the largest clique in the graph, i.e., the one that corresponds to the most frequent hash seed. If there are other cliques with the same size kmax in the graph, our algorithm projects the cliques into kmax {cliques using the same method described in. Each connected component in this projection corresponds to a kmax{clique community. The communities are then compared with the communities with larger size. If the majority of the nodes of the smaller community are shared between the two, these two communities are merged.

EBV infection is associated with human malignancies. Among all EBVassociated epithelial malignancies, the association between EBV infection and nasopharyngeal carcinoma is the strongest. NPC is a common cancer in Southeast Asia, particularly in southern regions of China including Hong Kong. The incidence of NPC in ethnic Chinese living in southern China, including Hong Kong, is ranging 50 to 100 folds higher than non-Chinese populations in North America and Europe. In undifferentiated NPC, which is the typical histopathological type of NPC in southern China, EBV could be detected in most, if not all, NPC cells. EBV infection has been postulated to be a crucial etiological factor in NPC pathogenesis, yet the underlying oncogenic mechanisms of EBV in NPC remain elusive. Deletions in chromosomes 3p and 9p could be detected in dysplastic lesions and histologically normal nasopharyngeal epithelium of southern Chinese prior to EBV infection. This leads to the hypothesis that genetically altered premalignant nasopharyngeal epithelial cells support EBV infection, and expansion of a specific EBV-infected clone of premalignant nasopharyngeal epithelial cells with the expression of lytic and latent genes of EBV drives further genomic instability in the EBV-infected nasopharyngeal epithelial cells, eventually leading to tumorigenic transformation. Latent membrane protein 1 is a well-documented EBV-encoded oncogene. LMP1 expression resulted in tumorigenic transformation of rodent fibroblast cells. Transgenic mice expressing LMP1 developed B cell lymphoma. LMP1 is commonly expressed in Hodgkin’s lymphoma and nasal lymphoma. LMP1 expression could be detected in preinvasive NPC lesions infected with EBV. LMP1 expression facilitates immortalization of nasopharyngeal epithelial cells by telomerase. All these Wortmannin observations support an important role of LMP1 in the early pathogenesis of NPC. Furthermore, LMP1 modulates multiple cell signaling pathways through activation of nuclear factor-kappa-B, Janusactivated kinase/signal transducer and activator of transcription, mitogen-activated protein kinase, protein kinase B and other signaling pathways to induce survival, anti-apoptosis and invasive properties in EBV-infected cells. The G2 checkpoint is essential for cell survival and maintenance of genomic stability. It delays cell cycle progression from G2 to M phase to provide time for correction of DNA damage or replication errors. Defective G2 checkpoint allows cells that carry chromosome aberrations to exit G2 and enter mitosis, leading to genomic instability which facilitates carcinogenesis. The impact of LMP1 on G2 checkpoint in nasopharyngeal epithelial cells has not been previously examined. In this study, we found that LMP1 impaired G2 checkpoint in nasopharyngeal epithelial cells, leading to formation of unrepaired chromatid-type aberrations in metaphase cells. We further found that defective Chk1 activation was responsible for the induction of defect in G2 checkpoint in LMP1- expressing nasopharyngeal epithelial cells.

The major families are carboxyl esterases, glutathione s-transferase and the monooxygenases P450s. These enzymes can metabolize both endogenous compounds, which are produced by metabolism, and exogenous compounds present in environment, such as insecticides. Resistance to chemical insecticides as a consequence of increased metabolic capability of these enzymes is known as metabolic resistance, as the insecticide is metabolized or sequestered before reaching its target. In the last few years, many studies have demonstrated the molecular basis of metabolic resistance, and mechanisms such as co-amplification of genes, transposonmediated mutations, gene duplication and mutations in trans-regulatory elements have been reported. Li et al. have published a good review on this subject. One of the major threats to the control programmes of vector borne diseases is insecticide resistance, as most of the implemented strategies are based on the high throughput screening exclusive use of such compounds. Thus, managing resistance is fundamental to sustain these strategies. The design of molecular tools for screening alleles associated with target-site insensitivity in natural populations is feasible, because the molecules involved in this type of resistance are components of nervous system and thus are conserved across different taxa, allowing the detection of the same mutation in different species. On the other hand, as mentioned above, the nature of mutations in metabolic genes leading to resistance is diverse and, the development of molecular tools that could be used in a wide range of species to detect resistance alleles is a difficult task. Moreover, the amount of genes potentially involved in the metabolism of xenobiotics makes the task extremely challenging. The use of microarray analysis to measure and compare gene expression levels between resistant and susceptible mosquito strains has allowed the identification of genes that are involved in specific metabolic resistance mechanisms in Anopheles gambiae, Anopheles arabiensis and in Ae. aegypti. David et al. have constructed a microarray containing more than 200 detoxification gene specific for An. gambiae and have used this chip to investigate metabolic-based insecticide resistance. Similarly, Strode et al. developed the Ae. aegypti ‘Detox Chip’, which also contains more than 200 genes putatively involved with metabolic resistance. This Detox Chip has also been used to evaluate mosquito response to xenobiotic exposure. Almost half of the world’s population are believed to be at risk from Dengue and this is due in no small part to the fact that the vector Ae. aegypti is a mosquito which has superbly adapted to human activity and increasing urbanization. With no available vaccine, vector control is the only option in the fight against Dengue and insecticides are a vital weapon. Temephos is an organophosphate larvicide recommended by WHO to control Ae. aegypti larvae and is even sanctioned for use in potable water containers.

In addition, they can incur large protein losses and artifactual contamination. A fifth less documented enrichment method, phase separation, is not widely known in proteomics, yet it offers huge potential for routine enrichment and purification of membrane proteins prior to LCMS/MS. Triton X-114 separation was first introduced by Bordier in the early 1980’s and has traditionally been used to enrich for and study membrane proteins in bacteria, although more recently it has been applied to yeast, mouse liver, human cardiac tissue, and porcine brain. To our knowledge, this is the first time phase separation using the Triton X-114 detergent has been applied to human post-mortem brain. Partitioning of the membrane and aqueous proteins is achieved by heating the Triton X-114 to temperatures above 20uC, until it reaches its cloud point. The detergent enters and partitions the lipid bilayer releasing the otherwise insoluble transmembrane proteins. A simple lowspeed centrifugation step recovers the membrane proteins in the detergent phase as an oily pellet, while aqueous proteins are resolved in the supernatant. As protocols with detergent/ membrane combinations have not been well documented or qualified for human brain tissue, the aim of this study was to 1) perform phase separation of detergent and aqueous phase proteins in human post-mortem brain using Triton X-114, and 2) confirm enrichment for membrane proteins in the detergent phase using proteomics. The various proteomic strategies applied in this manuscript are outlined in the study design in Figure 1. Analysis of sub-proteomes and otherwise undetectable protein classes is becoming increasingly important in the field of neuroproteomics, where recent investigations have enriched for and studied the post-synaptic density, lipid rafts, the myelin proteome, neuromelanin granules, and the calmodulin-binding proteome, in human post mortem brain. In this study, we propose a paradigm to enrich for and study membrane proteins in human post-mortem brain. As integral membrane proteins are at the interface between the cell and external environment, and sub-cellular structures, they are important mediators of cell-to –cell signalling, synaptic transmission, cellular transport, and neuroleptic activity. Analysis of this sub-proteome in patients and disease models will greatly aid pathophysiological investigations, yet such studies have not been broadly applied due to the difficulty in recovering and Ponatinib resolving transmembrane proteins. We applied Triton X-114 phase separation to human cortical tissue and confirmed phase separation into DT and AQ phases by comparing the protein banding pattern between control nonenriched tissue and DT and AQ phases. In support, western blotting showed increased expression of transmembrane spanning protein MBP in the DT phase in comparison to the AQ phase, while cytosolic protein GAPDH was depleted in the DT phase and enriched in the AQ phase, as expected. Our LC-MS/MS experiment identified a total of 1154 unique DT phase proteins, and confirmed enrichment where 54% were of membrane protein ontology.

These miRNAs mostly showed significant reduced expression in tumors comparing to normal breast tissue. One of these miRNAs, miR-30c, potentially contributes to breast malignancy formation through release of KRAS suppression suggesting that this miRNA, and likely other miRNAs also targeting KRAS/MAPK signaling, may function as tumor suppressors in breast cancer. Despite intensive surveillance for infected cases during the pandemic, it is still very likely that the case reports underestimated the true infection rate in the population due to the mis-counting of the asymptomatic and mild cases. Many studies have been performed to examine although few of them were aimed at tracking the temporal trends of the seroprevalence in the pandemic. As all pandemics in history are different and the temporal trends in one may not be the case in other pandemics, research on the temporal fluctuations of pH1N1 is important to give a comprehensive insight into the transmission feature throughout the duration of the pandemic.

The purpose of this study is to understand the impact of the 2009 winter wave of the pH1N1 epidemic and the effect of the free pH1N1 vaccination program implemented from October 2009 in Guangdong, to evaluate the risk of recurrence in the 2010 summer wave, and to explore underlying influencing factors. We conducted three consecutive serological surveys on randomly selected sample populations from Guangdong in January, March-April and August-September of 2010 respectively. Combining the findings from these three surveys will provide valuable information about the likelihood of potential recurrence and future outbreaks. It will guide us in formulating vaccination and treatment strategies during the post-pandemic period. WHO Director-General Dr. Margaret Chan announced on August 10, 2010 that the global H1N1 influenza virus had moved into the post-pandemic phase. In recent years, a number of clinical observations using PXR activators have linked PXR to lipid metabolism and energy homeostasis. Notably, treating with rifampicin, a PXR ligand, can influence lipid metabolism. Similarly, treating children with antiepileptic drugs carbamazipine and phenobarbital for an extended time, could activate PXR and increase cholesterol levels.

Transgenic mice expressing constitutively activated PXR showed hepatic steatosis. However, PXR also modulated sterol regulatory element binding protein 1 by inducing Insig1 expression, resulting in decreased levels of active SREBP-1 and reduced triglyceride synthesis. Although additional studies are needed to resolve the seemingly contradictory effects of PXR activation in lipid homeostasis, the results from these studies firmly establish the role of PXR in regulating lipid and energy Bortezomib homeostasis at multiple levels. Confirmation of the functional role of PXR in lipid metabolism has provided an opportunity to explore the mechanisms through which PXR agonists may impact energy homeostasis.