Computational identification of new potential transcriptional partners of ERRα in breast cancer cells: specific partners for specific targets.

Estrogen related receptors are orphan members of the nuclear receptor superfamily acting as transcription factors (TFs). In contrast to classical nuclear receptors, the activities of the ERRs are not controlled by a natural ligand. Regulation of their activities thus relies on availability of transcriptional co-regulators. In this paper, we focus on ERRα, whose involvement in cancer progression has been broadly demonstrated. We propose a new approach to identify potential co-activators, starting from previously identified ERRα-activated genes in a breast cancer (BC) cell line. Considering mRNA gene expression from two sets of human BC cells as major endpoint, we used sparse partial least squares modeling to uncover new transcriptional regulators associated with ERRα. Among them, DDX21, MYBBP1A, NFKB1, and SETD7 are functionally relevant in MDA-MB-231 cells, specifically activating the expression of subsets of ERRα-activated genes. We studied SET7 in more details and showed its co-localization with ERRα and its ERRα-dependent transcriptional and phenotypic effects. Our results thus demonstrate the ability of a modeling approach to identify new transcriptional partners from gene expression. Finally, experimental results show that ERRα cooperates with distinct co-regulators to control the expression of distinct sets of target genes, thus reinforcing the combinatorial specificity of transcription.

[Variation feature of receptor binding sites of H1N1 influenza hemagglutinin in different hosts].

Recent outbreak of H1N1 virus worldwide has caused 16 226 deaths in over 213 countries and districts. Binding between the virus and the receptor on the host cell surface is the key initial event for the infection, which results in the fusion of viral host cell membrane. Hemagglutinin (HA) is the viral protein that mediates the receptor binding and membrane fusion. The receptor binding sites (RBSs) are located at the membrane-distal part of each subunit of the HA trimer and are formed by three secondary structure elements, 190 helix (residues 190 to 198), 130 loop (residues 135 to 138), and 220 loop (residues 221 to 228). HA1 with 327 amino acid sequences in length was collected from 1221 H1N1 viruses between 1918 and 2009, and bioinformatic studies were carried out through sequence comparison, entropy calculation for each amino acid residue, and 3D structure modeling. The results showed that the RBSs of different viruses with different hosts have different entropies, and the RBSs in HA1 with different hosts have different favorite amino acid sequences. The 3D modeling indicates the subtly conformation changes in the 190 helix region between different HA1s in H1N1. This study explores new characters of the RBS structure in different HA1s, and provides new information for the further investigation of the infection mechanism.

[Polymorphism of DYS287 on Y chromosome in 28 ethnic populations of China].

OBJECTIVE: To investigate the polymorphism of DYS287 among 28 ethnic populations in 9 provinces of China. METHOD: YAP element was detected by Touchdown PCR amplification and 2% agarose gel electrophoresis. RESULTS: YAP+ frequencies in these ethnic populations were as follows: Zang 36.7%, Tu 23.8%, Yi 18.4%, Pumi 11.3%, Tajik 7.4%, Bai 6.7%, Jino 5.1%, Shandong Han 4%, Mulao 2.7%, and Maonan 1.3%. The rest ethnic populations in our study, including Gansu Han, Yunnan Han, Zhuangzu, Daizu, Lizu, Nuzu, Lisu, Naxi, Lahu, Dulong, Hani, Shezu, Weiwuer, Sala, Kerkizi, Dongxiang, Vazu, and Korea didn't carry YAP + element. CONCLUSIONS: Zangzu, Tuzu, Yizu, Pumi, Jino, and Baizu, which belong to Sino-Tibetan language family, carry a high YAP + frequency. Sala, Tuzu, and Tajik, regarded as Central Asia by origin in history and linguistics, also have a high YAP + frequency. Mulao and Maonan, which origin from "Baiyue" ancient ethnic groups, also have a considerable YAP + frequency.

Computational methods for protein-protein interaction and their application.

Protein-protein interactions play a central role in numerous processes in cell and are one of the main research fields in current functional proteomics. The increase of finished genomic sequences has greatly stimulated the progress for detecting the functions of the genes and their encoded proteins. As complementary ways to the high through-put experimental methods, various methods of bioinformatics have been developed for the study of the protein-protein interaction. These methods range from the sequence homology-based to the genomic-context based. Recently, it tends to integrate the data from different methods to build the protein-protein interaction network, and to predict the protein function from the analysis of the network structure. Efforts are ongoing to improve these methods and to search for novel aspects in genomes that could be exploited for function prediction. This review highlights the recent advances of the bioinformatics methods in protein-protein interaction researches. In the end, the application of the protein-protein interaction has also been discussed.

Synthetic peptides derived from SARS coronavirus S protein with diagnostic and therapeutic potential.

The spike (S) protein of severe acute respiratory syndrome coronavirus (SARS-CoV) is an important viral structural protein. Based on bioinformatics analysis, 10 antigenic peptides derived from the S protein sequence were selected and synthesized. The antigenicity and immunoreactivity of all the peptides were tested in vivo and in vitro. Four peptides (P6, P8, P9 and P10) which contain B cell epitopes of the S protein were identified, and P8 peptide was confirmed in vivo to have a potential in serological diagnosis. By using a syncytia formation model, we tested the neutralization ability of all 10 peptides and their corresponding antibodies. It is interesting to find that P8 and P9 peptides inhibited syncytia formation, suggesting that the P8 and P9 spanning regions may provide a good target for anti-SARS-CoV drug design. Our data suggest that we have identified peptides derived from the S protein of SARS-CoV, which are useful for SARS treatment and diagnosis.

[Analysis and application of SNP and haplotype in the human genome].

Single nucleotide polymorphism (SNP) is the most common type of genetic variant in human genome. Haplotype, defined as a specific set of alleles observed on a single chromosome, or a part of a chromosome,has been an integral part of human genetics for decades. The goal of the international HapMap project is to determine the common patterns of DNA sequence variation and find the Tag SNPs representing all SNPs in the human genome. Some studies demonstrated that the analyses of haplotype defined by the grouping and interaction of several variants rather than any individual SNP correlated with complex phenotypes. Here, we describe the definitions of SNPs, genotype, haplotype and some information of the HapMap project. In this review, we summarize the current three haplotype-inference methods, including Clark' method, EM algorithm and Byes approach, and the different defining methods for haplotype block, as well as the methods for choosing tag SNPs and association studies of complex diseases using haplotype. The major public SNP databases and applications of SNPs and haplotype in common complex diseases and drug response are also introduced in the paper.

Identification of an epitope of SARS-coronavirus nucleocapsid protein.

The nucleocapsid (N) protein of severe acute respiratory syndrome-coronavirus (SARS-CoV) is a major virion structural protein. In this study, two epitopes (N1 and N2) of the N protein of SARS-CoV were predicted by bioinformatics analysis. After immunization with two peptides, the peptides-specific antibodies were isolated from the immunized rabbits. The further experiments demonstrated that N1 peptide-induced polyclonal antibodies had a high affinity to bind to E. coli expressed N protein of SARS-CoV. Furthermore, it was confirmed that N1 peptide-specific IgG antibodies were detectable in the sera of severe acute respiratory syndrome (SARS) patients. The results indicated that an epitope of the N protein has been identified and N protein specific Abs were produced by peptide immunization, which will be usefull for the study of SARS-CoV.

mRNA expression profiling reveals a role of Helicobacter pylori vacuolating toxin in escaping host defense.

AIM: To study the immune response of host to Helicobacter pylori VacA. METHODS: The monocyte/macrophage-like U937 cells were infected with Helicobacter pylori vacA-positive strain NCTC 11638 or isogenic vacA-negative mutant. Differentially expressed genes were identified at 2, 6, 10, and 24 h post-infection by cDNA microarray. Differential expressions of some genes were confirmed by Northern blot. RESULTS: More than 100 genes altered their mRNA expression at different time points respectively, many of which were identified to be related to immune evasion. CONCLUSION: VacA is a crucial element for H pylori to escape from host immune defense by means of differentially regulating the expression of some related genes. These genes, previously known or unknown to be involved in the mechanism of immune evasion, deserve further investigation to unearth much more information complicated in the immune response.

[Evaluating the current protocol of influenza A (H1N1) based on the epidemic situations of Zhengzhou,a middle-sized city in China].

OBJECTIVE: From May 2009-January 2010, a total of 3768 biosamples were tested for influenza A (H1N1) infection at Zhengzhou center for disease control and prevention, China. 1452 cases were laboratory confirmed H1N1 infection and 2316 were considered suspected victims. To evaluate the current protocol of influenza A (H1N1) based on the epidemic situations of Zhengzhou, relationships among features were explored and whether additional clinical characteristics should be part of H1N1 diagnosis protocols were determined. METHODS: Both clinical and epidemiologic findings as well as statistical analyses were described in this article. Test for independence between features related to the disease diagnosis has been proposed. Furthermore, logistic regression was carried out to measure the association among features and latent class analysis was performed to identify additional crucial features in laboratory confirmed H1N1 by building various latent models with different combinatorial features. RESULTS: The mean generation time for H1N1 was estimated as 3.59 +/- 1.41 days (range = 2.01-7.26). The estimated infection rate was 0.258 +/- 0.088 3, and reproduction number was 1.94 (95% CI = 1.12-3.18). Our results revealed that the six features, including molecular detections using three separate primer/probe sets, gender, age and temperature, are all associated with clinical diagnosis of H1N1, and that three separate primer/probe sets for laboratory confirmed H1N1, age and temperature are associated with each other. CONCLUSION: Additional clinical features applied into the H1N1 diagnosis with current three primers/probe sets can increase the diagnostic efficiency.

Gene expression profiling-based in silico approach to identify potential vaccine candidates and drug targets against B. pertussis and B. parapertussis.

Whooping cough (pertussis) caused by B. pertussis (B.p) is still serious public health threat. B. parapertussis (B.pp), closely related to B.p, also causes whooping cough. The incidence of B.pp infections has been increasing over the last decades, partly because pertussis vaccines have low efficiency against B.pp infections. Moreover, because the majority of pertussis patients are infants, common antimicrobial agents producing serious adverse reactions in infants are not fully satisfactory. Therefore, we try to identify potential vaccine candidates and alternative drug targets against both B.p and B.pp. This preliminary work integrates several different kinds of data from in silico analysis, comparative genomic hybridization, global transcriptional profiling, and protein-protein interaction (PPI) network to screen potential vaccine candidates and drug targets against the two species. Finally, 191 potential crossprotective vaccine candidates are identified. They have high transcriptional levels in both species, or are associated with virulence and pathogenesis. Moreover, these proteins are not only potentially surface-exposed in the bacteria, but also well conserved among the 165 B.p and B.pp strains. Among them, 22 candidates with high essentiality in the two PPI networks of B.p and B.pp are regarded as suitable drug targets against the two species. We just selected Bordetella as an example to develop a rapid and reliable approach for screening alternative drug targets that associated with novel protein pathways, complexes, and cellular functions against these antibiotic-resistant pathogens. Further researches focusing on the 191 vaccine candidates could accelerate the development of more effective vaccines and drug therapy against B.p and B.pp infection.

Construction of a chloroplast protein interaction network and functional mining of photosynthetic proteins in Arabidopsis thaliana.

Chloroplast is a typical plant cell organelle where photosynthesis takes place. In this study, a total of 1,808 chloroplast core proteins in Arabidopsis thaliana were reliably identified by combining the results of previously published studies and our own predictions. We then constructed a chloroplast protein interaction network primarily based on these core protein interactions. The network had 22,925 protein interaction pairs which involved 2,214 proteins. A total of 160 previously uncharacterized proteins were annotated in this network. The subunits of the photosynthetic complexes were modularized, and the functional relationships among photosystem I (PSI), photosystem II (PSII), light harvesting complex of photosystem I (LHC I) and light harvesting complex of photosystem I (LHC II) could be deduced from the predicted protein interactions in this network. We further confirmed an interaction between an unknown protein AT1G52220 and a photosynthetic subunit PSI-D2 by yeast two-hybrid analysis. Our chloroplast protein interaction network should be useful for functional mining of photosynthetic proteins and investigation of chloroplast-related functions at the systems biology level in Arabidopsis.

Association between alcohol, smoking and HLA-DQA1*0201 genotype in psoriasis.

Psoriasis is a chronic skin disease triggered by genetic, environment or other risk factors such as infection, drugs, stress, moisture, alcohol, and smoking. A major psoriasis susceptibility locus at 6p21.3 has been identified. Further studies found that HLA-DQA1*0201 allele was associated with psoriasis. However, there were few data exploring an association between the environmental factors and susceptibility genes. In this study, the samples of 189 patients with psoriasis and 333 healthy controls were collected with their consent and were carried on analysis through polymerase chain reaction sequence-specific primer (PCR-SSP) method. The proportion of male psoriasis patients engaging in the smoking and alcohol was much higher than that of the control group (P<0.005). The HLA-DQA1*0201 allele was present at significantly higher frequency in the patients with psoriasis (OR=4.25, P<1.0 x 10(-6)). Association was found between smoking, alcohol and HLA-DQA1*0201 in male patients with psoriasis (OR>6.91, P<1.0 x 10(-4)).

Isolates of Microbotryum violaceum from North American host species are phylogenetically distinct from their European host-derived counterparts.

Microbotryum violaceum is a basidiomycete that infects the anthers of its Caryophyllaceae host species. Individual fungal isolates are host limited, though they are not morphologically distinct. This study used variable regions of the highly conserved gamma-tubulin, beta-tubulin, and ribosomal RNA-encoding genes to determine the relationships among M. violaceum fungal isolates from different host species and different geographical locations. Phylogenetic trees from intron nucleotide sequences in two protein-coding genes were compared to trees produced from internal transcribed spacers (ITS) of rDNA. Phylogenetic analyses suggested that there are two clades, one from North America and one from Europe. Isolates from both clades grouped according to host species, although in some analyses isolates from closely related host species were placed together. These results are consistent with the view that M. violaceum has experienced cospeciation with its hosts.

Identification of probable genomic packaging signal sequence from SARS-CoV genome by bioinformatics analysis.

AIM: To predict the probable genomic packaging signal of SARS-CoV by bioinformatics analysis. The derived packaging signal may be used to design antisense RNA and RNA interfere (RNAi) drugs treating SARS. METHODS: Based on the studies about the genomic packaging signals of MHV and BCoV, especially the information about primary and secondary structures, the putative genomic packaging signal of SARS-CoV were analyzed by using bioinformatic tools. Multi-alignment for the genomic sequences was performed among SARS-CoV, MHV, BCoV, PEDV and HCoV 229E. Secondary structures of RNA sequences were also predicted for the identification of the possible genomic packaging signals. Meanwhile, the N and M proteins of all five viruses were analyzed to study the evolutionary relationship with genomic packaging signals. RESULTS: The putative genomic packaging signal of SARS-CoV locates at the 3' end of ORF1b near that of MHV and BCoV, where is the most variable region of this gene. The RNA secondary structure of SARS-CoV genomic packaging signal is very similar to that of MHV and BCoV. The same result was also obtained in studying the genomic packaging signals of PEDV and HCoV 229E. Further more, the genomic sequence multi-alignment indicated that the locations of packaging signals of SARS-CoV, PEDV, and HCoV overlaped each other. It seems that the mutation rate of packaging signal sequences is much higher than the N protein, while only subtle variations for the M protein. CONCLUSIONS: The probable genomic packaging signal of SARS-CoV is analogous to that of MHV and BCoV, with the corresponding secondary RNA structure locating at the similar region of ORF1b. The positions where genomic packaging signals exist have suffered rounds of mutations, which may influence the primary structures of the N and M proteins consequently.

Small envelope protein E of SARS: cloning, expression, purification, CD determination, and bioinformatics analysis.

AIM: To obtain the pure sample of SARS small envelope E protein (SARS E protein), study its properties and analyze its possible functions. METHODS: The plasmid of SARS E protein was constructed by the polymerase chain reaction (PCR), and the protein was expressed in the E coli strain. The secondary structure feature of the protein was determined by circular dichroism (CD) technique. The possible functions of this protein were annotated by bioinformatics methods, and its possible three-dimensional model was constructed by molecular modeling. RESULTS: The pure sample of SARS E protein was obtained. The secondary structure feature derived from CD determination is similar to that from the secondary structure prediction. Bioinformatics analysis indicated that the key residues of SARS E protein were much conserved compared to the E proteins of other coronaviruses. In particular, the primary amino acid sequence of SARS E protein is much more similar to that of murine hepatitis virus (MHV) and other mammal coronaviruses. The transmembrane (TM) segment of the SARS E protein is relatively more conserved in the whole protein than other regions. CONCLUSION: The success of expressing the SARS E protein is a good starting point for investigating the structure and functions of this protein and SARS coronavirus itself as well. The SARS E protein may fold in water solution in a similar way as it in membrane-water mixed environment. It is possible that beta-sheet I of the SARS E protein interacts with the membrane surface via hydrogen bonding, this beta-sheet may uncoil to a random structure in water solution.

Development of genome-wide DNA polymorphism database for map-based cloning of rice genes.

DNA polymorphism is the basis to develop molecular markers that are widely used in genetic mapping today. A genome-wide rice (Oryza sativa) DNA polymorphism database has been constructed in this work using the genomes of Nipponbare, a cultivar of japonica, and 93-11, a cultivar of indica. This database contains 1,703,176 single nucleotide polymorphisms (SNPs) and 479,406 Insertion/Deletions (InDels), approximately one SNP every 268 bp and one InDel every 953 bp in rice genome. Both SNPs and InDels in the database were experimentally validated. Of 109 randomly selected SNPs, 107 SNPs (98.2%) are accurate. PCR analysis indicated that 90% (97 of 108) of InDels in the database could be used as molecular markers, and 68% to 89% of the 97 InDel markers have polymorphisms between other indica cultivars (Guang-lu-ai 4 and Long-te-pu B) and japonica cultivars (Zhong-hua 11 and 9522). This suggests that this database can be used not only for Nipponbare and 93-11, but also for other japonica and indica cultivars. While validating InDel polymorphisms in the database, a set of InDel markers with each chromosome 3 to 5 marker was developed. These markers are inexpensive and easy to use, and can be used for any combination of japonica and indica cultivars used in this work. This rice DNA polymorphism database will be a valuable resource and important tool for map-based cloning of rice gene, as well as in other various research on rice (http://shenghuan.shnu.edu.cn/ricemarker).

Putative hAPN receptor binding sites in SARS_CoV spike protein.

AIM: To obtain the information of ligand-receptor binding between the S protein of SARS-CoV and CD13, identify the possible interacting domains or motifs related to binding sites, and provide clues for studying the functions of SARS proteins and designing anti-SARS drugs and vaccines. METHODS: On the basis of comparative genomics, the homology search, phylogenetic analyses, and multi-sequence alignment were used to predict CD13 related interacting domains and binding sites in the S protein of SARS-CoV. Molecular modeling and docking simulation methods were employed to address the interaction feature between CD13 and S protein of SARS-CoV in validating the bioinformatics predictions. RESULTS: Possible binding sites in the SARS-CoV S protein to CD13 have been mapped out by using bioinformatics analysis tools. The binding for one protein-protein interaction pair (D757-R761 motif of the SARS-CoV S protein to P585-A653 domain of CD13) has been simulated by molecular modeling and docking simulation methods. CONCLUSION: CD13 may be a possible receptor of the SARS-CoV S protein, which may be associated with the SARS infection. This study also provides a possible strategy for mapping the possible binding receptors of the proteins in a genome.

A 3D model of SARS_CoV 3CL proteinase and its inhibitors design by virtual screening.

AIM: To constructed a three-dimensional (3D) model for the 3C like (3CL) proteinase of SARS coronavirus (SARS-CoV), and to design inhibitors of the 3CL proteinase based on the 3D model. METHODS: Bioinformatics analyses were performed to search the homologous proteins of the SARS-CoV 3CL proteinase from the GenBank and PDB database. A 3D model of the proteinase was constructed by using homology modeling technique. Targeting to the 3D model and its X-ray crystal structure of the main proteinase (Mpro) of transmissible gastroenteritis virus (TGEV), virtual screening was performed employing molecular docking method to identify possible 3CL proteinase inhibitors from small molecular databases. RESULTS: Sequence alignment indicated that the SARS-CoV 3CL proteinase was extremely homologous to TGEV Mpro, especially the substrate-binding pocket (active site). Accordingly, a 3D model for the SARS-CoV 3CL proteinase was constructed based on the crystal structure of TGEV Mpro. The 3D model adopts a similar fold of the TGEV Mpro, its structure and binding pocket feature are almost as same as that of TGEV Mpro. The tested virtual screening indicated that 73 available proteinase inhibitors in the MDDR database might dock into both the binding pockets of the TGEV Mpro and the SARS-CoV 3CL proteinase. CONCLUSIONS: Either the 3D model of the SARS-CoV 3CL proteinase or the X-ray crystal structure of the TGEV Mpro may be used as a starting point for design anti-SARS drugs. Screening the known proteinase inhibitors may be an appreciated shortcut to discover anti-SARS drugs.