Intramuscular fat (IMF) is an important trait influencing meat quality, and preadipocyte differentiation is a key factor affecting IMF deposition. Here we compared the transcriptome profiles of porcine intramuscular and subcutaneous preadipocytes during differentiation to gain insight into specific molecular and cellular events associated with intramuscular stromal vascular cell (MSVC) differentiation. RNA-Seq was used to screen for differentially expressed genes (DEGs) during the in vitro differentiation of MSVC and subcutaneous stromal vascular cell (ASVC) on days 0, 2 and 4. A total of 985 DEGs were identified during ASVC differentiation and 1469 DEGs during MSVC differentiation. Among these DEGs, 409 genes were specifically expressed during ASVC differentiation, 893 genes were specifically expressed during MSVC differentiation, and 576 DEGs were co-expressed during ASVC and MSVC differentiation. The expression profiles of DEGs during ASVC or MSVC differentiation were determined by cluster analysis based on Short Time-series Expression Miner (STEM). Four significant STEM profiles (profiles 1, 4, 5, and 14) were determined during ASVC differentiation, and four significant STEM profiles (profiles 1, 4, 11, and 14) were determined during MSVC differentiation. Gene ontology (GO) analysis indicated that DEGs related to adipocyte differentiation were identified to be significantly enriched in both adipose and muscle profile 14. In addition, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of DEGs in adipose profile 14 and muscle profiles 11 and 14 (STEM clustered them into one cluster) showed that the PPAR signaling pathway was significantly enriched in these profiles and four signaling pathways were specifically enriched in muscle profiles 11 and 14. Furthermore, analysis of transcription factor binding sites (TFBS) in the gene set revealed two over-represented transcription factors (NR3C4 and NR3C1), which were specifically significantly enriched in the promoter regions of genes within muscle gene expression profiles 11 and 14.
Cytotoxic-T-lymphocyte (CTL) escape mutations undermine the durability of effective human immunodeficiency virus type 1 (HIV-1)-specific CD8+ T cell responses. The rate of CTL escape from a given response is largely governed by the net of all escape-associated viral fitness costs and benefits. The observation that CTL escape mutations can carry an associated fitness cost in terms of reduced virus replication capacity (RC) suggests a fitness cost-benefit trade-off that could delay CTL escape and thereby prolong CD8 response effectiveness. However, our understanding of this potential fitness trade-off is limited by the small number of CTL escape mutations for which a fitness cost has been quantified. Here, we quantified the fitness cost of the 29 most common HIV-1B Gag CTL escape mutations using an in vitro RC assay. The majority (20/29) of mutations reduced RC by more than the benchmark M184V antiretroviral drug resistance mutation, with impacts ranging from 8% to 69%. Notably, the reduction in RC was significantly greater for CTL escape mutations associated with protective HLA class I alleles than for those associated with nonprotective alleles. To speed the future evaluation of CTL escape costs, we also developed an in silico approach for inferring the relative impact of a mutation on RC based on its computed impact on protein thermodynamic stability. These data illustrate that the magnitude of CTL escape-associated fitness costs, and thus the barrier to CTL escape, varies widely even in the conserved Gag proteins and suggest that differential escape costs may contribute to the relative efficacy of CD8 responses.
The study was conducted to investigate whether dietary fish oil could influence growth of piglets via regulating the expression of proinflammatory cytokines. A split-plot experimental design was used with sow diet effect in the main plots and differing piglet diet effect in the subplot. The results showed that suckling piglets from fish oil fed dams grew rapidly (P < 0.05) than control. It was also observed that these piglets had higher ADG, feed intake, and final body weight (P < 0.05) during postweaning than those piglets from lard fed dams. Furthermore, there was a significant decrease (P < 0.01) in the expression of interleukin 6 and tumor necrosis factor-α in longissimus dorsi muscle. In contrast, there was a tendency (P < 0.10) towards lower ADG and higher feed : gain in weaned piglets receiving fish oil compared with those receiving lard. Meanwhile, splenic proinflammatory cytokines expression was increased (P < 0.01) in piglets receiving fish oil during postweaning period. The results suggested that 7% fish oil addition to sows' diets alleviated inflammatory response via decreasing the proinflammatory cytokines expression in skeletal muscle and accelerated piglet growth. However, 7% fish oil addition to weaned piglets' diets might decrease piglet growth via increasing splenic proinflammatory cytokines expression.
Hepatitis B virus(HBV) infection remains a global problem, despite the effectiveness of the Hepatitis B vaccine in preventing infection. The resolution of Hepatitis B virus infection has been believed to be attributable to virus-specific immunity. In vivo direct evaluation of anti-HBV immunity in the liver is currently not possible. We have developed a new assay system that detects HBV clearance in the liver after the hydrodynamic transfer of a reporter gene and over-length, linear HBV DNA into hepatocytes, followed by bioluminescence imaging of the reporter gene (Fluc). We employed bioluminescence detection of luciferase expression in HBV-infected hepatocytes to measure the Hepatitis B core antigen (HBcAg)-specific immune responses directed against these infected hepatocytes. Only HBcAg-immunized, but not mock-treated, animals decreased the amounts of luciferase expression, HBsAg and viral DNA from the liver at day 28 after hydrodynamic infection with over-length HBV DNA, indicating that control of luciferase expression correlates with viral clearance from infected hepatocytes.
Protein structure alignment is a fundamental problem in computational structure biology. Many programs have been developed for automatic protein structure alignment, but most of them align two protein structures purely based upon geometric similarity without considering evolutionary and functional relationship. As such, these programs may generate structure alignments which are not very biologically meaningful from the evolutionary perspective. This paper presents a novel method DeepAlign for automatic pairwise protein structure alignment. DeepAlign aligns two protein structures using not only spatial proximity of equivalent residues (after rigid-body superposition), but also evolutionary relationship and hydrogen-bonding similarity. Experimental results show that DeepAlign can generate structure alignments much more consistent with manually-curated alignments than other automatic tools especially when proteins under consideration are remote homologs. These results imply that in addition to geometric similarity, evolutionary information and hydrogen-bonding similarity are essential to aligning two protein structures.
Despite significant progress in recent years, ab initio folding is still one of the most challenging problems in structural biology. This paper presents a probabilistic graphical model for ab initio folding, which employs Conditional Random Fields (CRFs) and directional statistics to model the relationship between the primary sequence of a protein and its three-dimensional structure. Different from the widely-used fragment assembly method and the lattice model for protein folding, our graphical model can explore protein conformations in a continuous space according to their probability. The probability of a protein conformation reflects its stability and is estimated from PSI-BLAST sequence profile and predicted secondary structure. Experimental results indicate that this new method compares favorably with the fragment assembly method and the lattice model.
protein structure prediction; ab initio folding; conditional random fields (CRFs); directional statistics; fragment assembly; lattice model
Coat color in dog breeds is an excellent character for revealing the power of artificial selection, as it is extremely diverse and likely the result of recent domestication. Coat color is generated by melanocytes, which synthesize pheomelanin (a red or yellow pigment) or eumelanin (a black or brown pigment) through the pigment type-switching pathway, and is regulated by three genes in dogs: MC1R (melanocortin receptor 1), CBD103 (β-defensin 103), and ASIP (agouti-signaling protein precursor). The genotypes of these three gene loci in dog breeds are associated with coat color pattern. Here, we resequenced these three gene loci in two Kunming dog populations and analyzed these sequences using population genetic approaches to identify evolutionary patterns that have occurred at these loci during the recent domestication and breeding of the Kunming dog. The analysis showed that MC1R undergoes balancing selection in both Kunming dog populations, and that the Fst value for MC1R indicates significant genetic differentiation across the two populations. In contrast, similar results were not observed for CBD103 or ASIP. These results suggest that high heterozygosity and allelic differences at the MC1R locus may explain both the mixed color coat, of yellow and black, and the difference in coat colors in both Kunming dog populations.
Small molecules that can specifically bind to a DNA abasic site (AP site) have received much attention due to their importance in DNA lesion identification, drug discovery, and sensor design. Herein, the AP site binding behavior of sanguinarine (SG), a natural alkaloid, was investigated. In aqueous solution, SG has a short-wavelength alkanolamine emission band and a long-wavelength iminium emission band. At pH 8.3, SG experiences a fluorescence quenching for both bands upon binding to fully matched DNAs without the AP site, while the presence of the AP site induces a strong SG binding and the observed fluorescence enhancement for the iminium band are highly dependent on the nucleobases flanking the AP site, while the alkanolamine band is always quenched. The bases opposite the AP site also exert some modifications on the SG's emission behavior. It was found that the observed quenching for DNAs with Gs and Cs flanking the AP site is most likely caused by electron transfer between the AP site-bound excited-state SG and the nearby Gs. However, the flanking As and Ts that are not easily oxidized favor the enhanced emission. This AP site-selective enhancement of SG fluorescence accompanies a band conversion in the dominate emission from the alkanolamine to iminium band thus with a large emission shift of about 170 nm. Absorption spectra, steady-state and transient-state fluorescence, DNA melting, and electrolyte experiments confirm that the AP site binding of SG occurs and the stacking interaction with the nearby base pairs is likely to prevent the converted SG iminium form from contacting with water that is thus emissive when the AP site neighbors are bases other than guanines. We expect that this fluorophore would be developed as a promising AP site binder having a large emission shift.
This paper presents RaptorX, a statistical method for template-based protein modeling that improves alignment accuracy by exploiting structural information in a single or multiple templates. RaptorX consists of three major components: single-template threading, alignment quality prediction and multiple-template threading. This paper summarizes the methods employed by RaptorX and presents its CASP9 result analysis, aiming to identify major bottlenecks with RaptorX and template-based modeling and hopefully directions for further study. Our results show that template structural information helps a lot with both single-template and multiple-template protein threading especially when closely-related templates are unavailable and there is still large room for improvement in both alignment and template selection. The RaptorX web server is available at http://raptorx.uchicago.edu.
single-template threading; multiple-template threading; alignment quality prediction; probabilistic alignment; multiple protein alignment; CASP
The MyD88-independent pathway, one of the two crucial TLR signaling routes, is thought to be a vertebrate innovation. However, a novel Toll/interleukin-1 receptor (TIR) adaptor, designated bbtTICAM, which was identified in the basal chordate amphioxus, links this pathway to invertebrates. The protein architecture of bbtTICAM is similar to that of vertebrate TICAM1 (TIR-containing adaptor molecule-1, also known as TRIF), while phylogenetic analysis based on the TIR domain indicated that bbtTICAM is the oldest ortholog of vertebrate TICAM1 and TICAM2 (TIR-containing adaptor molecule-2, also known as TRAM). Similar to human TICAM1, bbtTICAM activates NF-κB in a MyD88-independent manner by interacting with receptor interacting protein (RIP) via its RHIM motif. Such activation requires bbtTICAM to form homodimers in endosomes, and it may be negatively regulated by amphioxus SARM (sterile α and armadillo motif-containing protein) and TRAF2. However, bbtTICAM did not induce the production of type I interferon. Thus, our study not only presents the ancestral features of vertebrate TICAM1 and TICAM2, but also reveals the evolutionary origin of the MyD88-independent pathway from basal chordates, which will aid in understanding the development of the vertebrate TLR network.
TLR; TICAM; MyD88-independent pathway; innate immunity; evolution
Motivation: Building an accurate alignment of a large set of distantly related protein structures is still very challenging.
Results: This article presents a novel method 3DCOMB that can generate a multiple structure alignment (MSA) with not only as many conserved cores as possible, but also high-quality pairwise alignments. 3DCOMB is unique in that it makes use of both local and global structure environments, combined by a statistical learning method, to accurately identify highly similar fragment blocks (HSFBs) among all proteins to be aligned. By extending the alignments of these HSFBs, 3DCOMB can quickly generate an accurate MSA without using progressive alignment. 3DCOMB significantly excels others in aligning distantly related proteins. 3DCOMB can also generate correct alignments for functionally similar regions among proteins of very different structures while many other MSA tools fail. 3DCOMB is useful for many real-world applications. In particular, it enables us to find out that there is still large improvement room for multiple template homology modeling while several other MSA tools fail to do so.
Availability: 3DCOMB is available at http://ttic.uchicago.edu/~jinbo/software.htm.
Supplementary Information: Supplementary data are available at Bioinformatics online.
Background & Aims
Cholestasis contributes to hepatocellular injury and promotes liver carcinogenesis. We created a mouse model of chronic cholestasis to study its effects on progression of cholangiocarcinoma and the oncogenes involved.
To induce chronic cholestasis, Balb/c mice were given 2 weekly intraperitoneal injections of diethylnitrosamine (DEN); 2 weeks later, some mice also received left and median bile duct ligation (LMBDL), and then 1 week later, were fed DEN, in corn oil, weekly by oral gavage (DLD). Liver samples were analyzed by immunohistochemical and biochemical assays; expression of Mnt and c-Myc were reduced by injection of small inhibitor RNAs.
Chronic cholestasis was induced by DLD and accelerated progression of cholangiocarcinoma, compared with mice given only DEN. Cystic hyperplasias, cystic atypical hyperplasias, cholangiomas, and cholangiocarcinoma developed in the DLD group at weeks 8, 12, 16 and 28, respectively. LMBDL repressed expression of microRNA (miR)-34a and Let-7a, upregulating Lin-28B, HIF-1α, HIF-2α, and miR-210. Upregulation of Lin-28B might inhibit let-7a, which is associated with development of cystic hyperplasias, cystic atypical hyperplasias, cholangiomas, and cholangiocarcinoma. Knockdown of c-Myc reduced progression of cholangiocarcinoma whereas knockdown of Mnt accelerated its progression. Downregulation of miR-34a expression might upregulate c-Myc. The upregulation of miR-210 via HIF-2α was involved in downregulation of Mnt. Activation of the miR-34a–c-Myc and HIF-2α–miR-210–Mnt pathways caused c-Myc to bind the E-box element of cyclin D1, instead of Mnt, resulting in cyclin D1 upregulation.
DLD induction of chronic cholestasis accelerated progression of cholangiocarcinoma, which is mediated by downregulation of miR-34a, upregulation miR-210, and replacement of Mnt by c-Myc in binding to cyclin D1.
Liver disease; transcriptional regulation; cell cycle; carcinogenesis; DNA binding
Motivation: Alignment errors are still the main bottleneck for current template-based protein modeling (TM) methods, including protein threading and homology modeling, especially when the sequence identity between two proteins under consideration is low (<30%).
Results: We present a novel protein threading method, CNFpred, which achieves much more accurate sequence–template alignment by employing a probabilistic graphical model called a Conditional Neural Field (CNF), which aligns one protein sequence to its remote template using a non-linear scoring function. This scoring function accounts for correlation among a variety of protein sequence and structure features, makes use of information in the neighborhood of two residues to be aligned, and is thus much more sensitive than the widely used linear or profile-based scoring function. To train this CNF threading model, we employ a novel quality-sensitive method, instead of the standard maximum-likelihood method, to maximize directly the expected quality of the training set. Experimental results show that CNFpred generates significantly better alignments than the best profile-based and threading methods on several public (but small) benchmarks as well as our own large dataset. CNFpred outperforms others regardless of the lengths or classes of proteins, and works particularly well for proteins with sparse sequence profiles due to the effective utilization of structure information. Our methodology can also be adapted to protein sequence alignment.
Supplementary data are available at Bioinformatics online.
Most threading methods predict the structure of a protein using only a single template. Due to the increasing number of solved structures, a protein without solved structure is very likely to have more than one similar template structures. Therefore, a natural question to ask is if we can improve modeling accuracy using multiple templates. This paper describes a new multiple-template threading method to answer this question. At the heart of this multiple-template threading method is a novel probabilistic-consistency algorithm that can accurately align a single protein sequence simultaneously to multiple templates. Experimental results indicate that our multiple-template method can improve pairwise sequence-template alignment accuracy and generate models with better quality than single-template models even if they are built from the best single templates (P-value<10-6) while many popular multiple sequence/structure alignment tools fail to do so. The underlying reason is that our probabilistic-consistency algorithm can generate accurate multiple sequence/template alignments. In another word, without an accurate multiple sequence/template alignment the modeling accuracy cannot be improved by simply using multiple templates to increase alignment coverage. Blindly tested on the CASP9 targets with more than one good template structures, our method outperforms all other CASP9 servers except two (Zhang-Server and QUARK of the same group). Our probabilistic-consistency algorithm can possibly be extended to align multiple protein/RNA sequences and structures.
protein modeling; multiple-template threading; probabilistic alignment matrix; probabilistic-consistency algorithm; multiple sequence/template alignment
Compared with the protein 3-class secondary structure (SS) prediction, the 8-class prediction gains less attention and is also much more challenging, especially for proteins with few sequence homologs. This paper presents a new probabilistic method for 8-class SS prediction using conditional neural fields (CNFs), a recently invented probabilistic graphical model. This CNF method not only models the complex relationship between sequence features and SS, but also exploits the interdependency among SS types of adjacent residues. In addition to sequence profiles, our method also makes use of non-evolutionary information for SS prediction. Tested on the CB513 and RS126 data sets, our method achieves Q8 accuracy of 64.9 and 64.7%, respectively, which are much better than the SSpro8 web server (51.0 and 48.0%, respectively). Our method can also be used to predict other structure properties (e.g. solvent accessibility) of a protein or the SS of RNA.
Bioinformatics; Conditional neural fields; Eight class; Protein; Secondary structure prediction
Protein threading is one of the most successful protein structure prediction methods. Most protein threading methods use a scoring function linearly combining sequence and structure features to measure the quality of a sequence-template alignment so that a dynamic programming algorithm can be used to optimize the scoring function. However, a linear scoring function cannot fully exploit interdependency among features and thus, limits alignment accuracy.
This paper presents a nonlinear scoring function for protein threading, which not only can model interactions among different protein features, but also can be efficiently optimized using a dynamic programming algorithm. We achieve this by modeling the threading problem using a probabilistic graphical model Conditional Random Fields (CRF) and training the model using the gradient tree boosting algorithm. The resultant model is a nonlinear scoring function consisting of a collection of regression trees. Each regression tree models a type of nonlinear relationship among sequence and structure features. Experimental results indicate that this new threading model can effectively leverage weak biological signals and improve both alignment accuracy and fold recognition rate greatly.
protein threading; conditional random fields; gradient tree boosting; regression tree; nonlinear scoring function
We have previously reported that the expression of MAT2A (methionine adenosyltransferase 2A) is increased in human colon cancer and in colon cancer cells treated with IGF-1 (insulin-like growth factor-1), which was required for its mitogenic effect. The aim of the present study was to elucidate the molecular mechanisms of IGF-1-mediated MAT2A induction. Nuclear run-on analysis confirmed that the increase in MAT2A expression lies at the transcriptional level. DNase I footprinting of the MAT2A promoter region revealed a similar protein-binding pattern in colon cancer and IGF-1-treated RKO cells. IGF-1 induced MAT2A promoter activity and increased nuclear protein binding to USF (upstream stimulatory factor)/c-Myb, YY1 (Yin and Yang 1), E2F, AP-1 (activator protein 1) and NF-κB (nuclear factor κB) consensus elements. IGF-1 increased the expression of c-Jun, FosB, MafG, p65, c-Myb, E2F-1 and YY1 at the pre-translational level. Knockdown of p65, MafG, c-Myb or E2F-1 lowered basal MAT2A expression and blunted the inductive effect of IGF-1 on MAT2A, whereas knockdown of YY1 increased basal MAT2A expression and had no effect on IGF-1-mediated MAT2A induction. Consistently, mutation of AP-1, NF-κB, E2F and USF/c-Myb elements individually blunted the IGF-1-mediated increase in MAT2A promoter activity, and combined mutations completely prevented the increase. In conclusion, IGF-1 activates MAT2A transcription by both known and novel pathways. YY1 represses MAT2A expression.
c-Myb; colon cancer; E2F; insulin-like growth factor-1 (IGF-1); methionine adenosyltransferase 2A; Yin and Yang 1 (YY1)
The domestic pig (Sus scrofa), an important species in animal production industry, is a right model for studying adipogenesis and fat deposition. In order to expand the repertoire of porcine miRNAs and further explore potential regulatory miRNAs which have influence on adipogenesis, high-throughput Solexa sequencing approach was adopted to identify miRNAs in backfat of Large White (lean type pig) and Meishan pigs (Chinese indigenous fatty pig). We identified 215 unique miRNAs comprising 75 known pre-miRNAs, of which 49 miRNA*s were first identified in our study, 73 miRNAs were overlapped in both libraries, and 140 were novelly predicted miRNAs, and 215 unique miRNAs were collectively corresponding to 235 independent genomic loci. Furthermore, we analyzed the sequence variations, seed edits and phylogenetic development of the miRNAs. 17 miRNAs were widely conserved from vertebrates to invertebrates, suggesting that these miRNAs may serve as potential evolutional biomarkers. 9 conserved miRNAs with significantly differential expressions were determined. The expression of miR-215, miR-135, miR-224 and miR-146b was higher in Large White pigs, opposite to the patterns shown by miR-1a, miR-133a, miR-122, miR-204 and miR-183. Almost all novel miRNAs could be considered pig-specific except ssc-miR-1343, miR-2320, miR-2326, miR-2411 and miR-2483 which had homologs in Bos taurus, among which ssc-miR-1343, miR-2320, miR-2411 and miR-2483 were validated in backfat tissue by stem-loop qPCR. Our results displayed a high level of concordance between the qPCR and Solexa sequencing method in 9 of 10 miRNAs comparisons except for miR-1a. Moreover, we found 2 miRNAs, miR-135 and miR-183, may exert impacts on porcine backfat development through WNT signaling pathway. In conclusion, our research develops porcine miRNAs and should be beneficial to study the adipogenesis and fat deposition of different pig breeds based on miRNAs.
Zinc transporter-8 (ZnT8) was recently identified as a novel autoantigen in human type 1 diabetes (T1D). Autoantibody to ZnT8 (ZnT8A) were detected in up to 80% of new-onset T1D and 26% of T1D patients otherwise classified as negative on the basis of existing markers. Since no data of ZnT8A in Chinese has been reported, we aim to evaluate the utility of ZnT8A for diagnosis of autoimmune T1D in Chinese relative to other autoantibody markers.
Radioligand binding assays were performed on 539 T1D sera using human ZnT8 carboxyterminal 325Arg construct or a dimer incorporating 325Arg and 325Trp alongside antibodies to glutamic acid decarboxylase (GADA) or insulinoma-associated protein 2 (IA-2A). The antigenic specificity was analyzed in the context of clinical characteristics of the patients.
ZnT8A were present in 24.1% (130/539) of T1D patients versus 1.8% (10/555) (P<0.001) in type 2 diabetes. At diagnosis, ZnT8A and IA-2A were less prevalent in Chinese T1D subjects than in Caucasian populations (both P<0.001), but similar to Japanese. The diagnostic sensitivity of combined GADA, IA-2A and ZnT8A measurements reached 65.5% with ZnT8A detected in 13.5% (29/215) of GADA and/or IA-2A negative subjects. ZnT8A prevalence was lower in older and fatter patients. ZnT8A+ alone patients were distinguished from Ab- ones (P<0.05~0.001) on the basis of higher insulin requirement and lower systolic blood pressure level.
ZnT8A is an independent marker for T1D in Chinese and combined with GADA and IA-2A enhances diagnostic sensitivity. ZnT8A may be associated with different clinical phenotypes than GADA or IA-2A.
ZnT8 autoantibody; GAD autoantibody; IA-2 autoantibody; type 1 diabetes; diagnosis
Phospholipase C-γ1 (PLC-γ1), a tyrosine kinase substrate, has been implicated in the pathway for the epidermal growth factor receptor (EGFR)-induced cell migration. However, the underlying mechanism by which PLC-γ1 mediates EGFR-induced cell migration remains elusive. In the present study, we sought to determine whether the lipase activity of PLC-γ1 is required for EGFR-induced cell migration. We found that overexpression of PLC-γ1 in squamous cell carcinoma SCC4 cells markedly enhanced EGF-induced PLC-γ1 activation, intracellular calcium rise and cell migration. This enhancement was abolished by mutational inactivation of the catalytic domain of PLC-γ1. Inhibition of the downstream signaling processes mediated by the activity of phospholipase C (PLC) using IP3 receptor inhibitor or intracellular calcium chelator blocked EGF-induced cell migration. These data indicate that EGF-induced cell migration is mediated by the lipase domain of PLC-γ1 and the subsequent IP3 generation and intracellular calcium mobilization.
Epidermal growth factor receptor; phospholipase C-γ1; migration; catalytic activity
One of the major challenges with protein template-free modeling is an efficient sampling algorithm that can explore a huge conformation space quickly. The popular fragment assembly method constructs a conformation by stringing together short fragments extracted from the Protein Data Base (PDB). The discrete nature of this method may limit generated conformations to a subspace in which the native fold does not belong. Another worry is that a protein with really new fold may contain some fragments not in the PDB. This article presents a probabilistic model of protein conformational space to overcome the above two limitations. This probabilistic model employs directional statistics to model the distribution of backbone angles and 2nd-order Conditional Random Fields (CRFs) to describe sequence-angle relationship. Using this probabilistic model, we can sample protein conformations in a continuous space, as opposed to the widely used fragment assembly and lattice model methods that work in a discrete space. We show that when coupled with a simple energy function, this probabilistic method compares favorably with the fragment assembly method in the blind CASP8 evaluation, especially on alpha or small beta proteins. To our knowledge, this is the first probabilistic method that can search conformations in a continuous space and achieves favorable performance. Our method also generated three-dimensional (3D) models better than template-based methods for a couple of CASP8 hard targets. The method described in this article can also be applied to protein loop modeling, model refinement, and even RNA tertiary structure prediction.
conditional random fields (CRFs); directional statistics; fragment assembly; lattice model; protein structure prediction; template-free modeling
A rare case of intrasellar mixed gangliocytoma–adenoma including ependymal component, which presented clinically with acromegaly and menstrual disorder, is described here. The tumour was totally removed via trans-sphenoidal surgery. A histological examination of the resected specimen showed that the tumour was composed of ganglion cells, adenomatous cells and ependymal cells. Most intrasellar gangliocytomas are composed of two components: adenomatous cells and ganglion cells. In this case, in addition to mixed adenomatous and ganglion cells, focal ependymal cells forming small cysts were found. Based on these histopathological findings, it was inferred that stem cells existed in the pituitary gland during embryonic development. The stem cells were able to differentiate into three directions: ganglion cells, adenomatous cells and ependymal cells, and as a result an intrasellar mixed gangliocyto-adenoma including ependymal component developed.
YueF is a novel putative tumor suppressor gene that can inhibit proliferation and induce apoptosis in hepatoma cells, but its role in renal cell carcinoma (RCC) remains unclear. Here, we examined the expression of the YueF gene in RCC tissues and the effect of YueF on cell proliferation in RCC 786-0 cells. The results showed that YueF was expressed at high levels in normal kidney tissues and cell lines but was reduced or absent in RCC tissues and 786-0 cells. Lentivirus-mediated YueF overexpression in RCC 786-0 cells caused cell-cycle arrest in the G1 phase and dramatically reduced proliferation in culture. YueF overexpression resulted in increased protein levels of p53 and p21WAF1/Cip1, whereas the protein levels of cyclin D1 and pRb were decreased. The proliferation defects caused by YueF overexpression could be partially rescued by the expression of p21 siRNA. These findings suggest a critical role for p21 in the YueF-induced growth inhibition of 786-0 cells and provide novel insights into the mechanism underlying the tumor-suppressive action of YueF.
YueF; clear cell RCC; p53; p21
AIM: To develop a sensitive assay for screening compounds against hepatitis C virus (HCV).
METHODS: The proteolytic cleavage of NS3/4A on enhanced yellow fluorescent protein (eYFP)-mitochondrial antiviral signaling protein (MAVS) was examined by reporter enzyme secreted placental alkaline phosphatase (SEAP), which enabled us to perform ongoing monitoring of anti-HCV drugs through repeated chemiluminescence. Subcellular localization of eYFP-MAVS was assessed by fluorescence microscopy. Cellular localization and protein levels were examined by Western blotting.
RESULTS: HCV NS3/4A protease cleaved eYFP-MAVS from mitochondria to block the activation of interferon (IFN)-β promoter, thus resulting in downregulation of SEAP activity. The decrease in SEAP activity was proportional to the dose of active NS3/4A protease. Also this reporter assay was used to detect anti-HCV activity of IFN-α and cyclosporine A.
CONCLUSION: Our data show that this reporter system is a sensitive and quantitative reporter of anti-HCV inhibitors. This system will constitute a new tool to allow the efficient screening of HCV inhibitors.
Mitochondrial antiviral signaling protein; Hepatitis C virus; Interferon-β; Drug screening
The development of small molecule inhibitors of hepatitis C virus (HCV) core protein as antiviral agents has been intensively pursued as a viable strategy to eradicate HCV infection. However, lack of a robust and convenient small animal model has hampered the assessment of in vivo efficacy of any antiviral compound.
The objective of this work was to develop a novel method to screen anti-core protein siRNA in the mouse liver by bioluminescence imaging. The inhibitory effect of two shRNAs targeting the highly conserved core region of the HCV genome, shRNA452 and shRNA523, was examined using this method. In the transient mouse model, the effect of shRNA-523 was detectable at as early as 24 h and became even more pronounced at later time points. The effect of shRNA-452 was not detectable until 48 h post-transduction. In a stable mouse model, shRNA523 reduced luciferase levels by up to 76.4±26.0% and 91.8±8.0% at 6 h and 12 h after injection respectively, and the inhibitory effect persisted for 1 day after a single injection while shRNA-Scramble did not seem to have an effect on the luciferase activity in vivo.
Thus, we developed a simple and quantitative assay for real-time monitoring of HCV core protein inhibitors in mice.