Identification of the dominant translation start site in the attB1 sequence of the pET-DEST42 Gateway vector

Gateway technology is a powerful system for converting a single entry vector into a wide variety of expression vectors. We expressed recombinant influenza matrix protein M1 (FMP), a potent antigen for cytotoxic T cells, using the Gateway vector pET-DEST42 containing the FMP cDNA, and purified the expressed FMP as a single 32 kDa recombinant protein. N-terminal and internal protein sequencing, however, showed that the recombinant FMP contained an extra 10 amino acids fused to the N-terminal of native FMP. Further investigation of the DNA sequence adjacent to the 5'-FMP cDNA indicated that the TTG in the attB1 site (30bp upstream of the ATG in the 5'-FMP cDNA) behaved as a dominant translation start site, resulting in a 10 amino acid extension of the recombinant FMP. Thus, it is possible that recombinant proteins produced by this Gateway vector contain unexpected vector-derived peptides, which may affect experimental outcomes. (c) 2006 Elsevier Inc. All rights reserved.

Predicting residue-wise contact orders in proteins by support vector regression

Background: The residue-wise contact order (RWCO) describes the sequence separations between the residues of interest and its contacting residues in a protein sequence. It is a new kind of one-dimensional protein structure that represents the extent of long-range contacts and is considered as a generalization of contact order. Together with secondary structure, accessible surface area, the B factor, and contact number, RWCO provides comprehensive and indispensable important information to reconstructing the protein three-dimensional structure from a set of one-dimensional structural properties. Accurately predicting RWCO values could have many important applications in protein three-dimensional structure prediction and protein folding rate prediction, and give deep insights into protein sequence-structure relationships. Results: We developed a novel approach to predict residue-wise contact order values in proteins based on support vector regression (SVR), starting from primary amino acid sequences. We explored seven different sequence encoding schemes to examine their effects on the prediction performance, including local sequence in the form of PSI-BLAST profiles, local sequence plus amino acid composition, local sequence plus molecular weight, local sequence plus secondary structure predicted by PSIPRED, local sequence plus molecular weight and amino acid composition, local sequence plus molecular weight and predicted secondary structure, and local sequence plus molecular weight, amino acid composition and predicted secondary structure. When using local sequences with multiple sequence alignments in the form of PSI-BLAST profiles, we could predict the RWCO distribution with a Pearson correlation coefficient (CC) between the predicted and observed RWCO values of 0.55, and root mean square error (RMSE) of 0.82, based on a well-defined dataset with 680 protein sequences. Moreover, by incorporating global features such as molecular weight and amino acid composition we could further improve the prediction performance with the CC to 0.57 and an RMSE of 0.79. In addition, combining the predicted secondary structure by PSIPRED was found to significantly improve the prediction performance and could yield the best prediction accuracy with a CC of 0.60 and RMSE of 0.78, which provided at least comparable performance compared with the other existing methods. Conclusion: The SVR method shows a prediction performance competitive with or at least comparable to the previously developed linear regression-based methods for predicting RWCO values. In contrast to support vector classification (SVC), SVR is very good at estimating the raw value profiles of the samples. The successful application of the SVR approach in this study reinforces the fact that support vector regression is a powerful tool in extracting the protein sequence-structure relationship and in estimating the protein structural profiles from amino acid sequences.

Real-Time Gene-Expression Extraction with Fast Classification (FC) Networks

Fast Classification (FC) networks were inspired by a biologically plausible mechanism for short term memory where learning occurs instantaneously. Both weights and the topology for an FC network are mapped directly from the training samples by using a prescriptive training scheme. Only two presentations of the training data are required to train an FC network. Compared with iterative learning algorithms such as Back-propagation (which may require many hundreds of presentations of the training data), the training of FC networks is extremely fast and learning convergence is always guaranteed. Thus FC networks may be suitable for applications where real-time classification is needed. In this paper, the FC networks are applied for the real-time extraction of gene expressions for Chlamydia microarray data. Both the classification performance and learning time of the FC networks are compared with the Multi-Layer Proceptron (MLP) networks and support-vector-machines (SVM) in the same classification task. The FC networks are shown to have extremely fast learning time and comparable classification accuracy.

The retrograde delivery of adenovirus vector carrying the gene for brain-derived neurotrophic factor protects neurons and oligodendrocytes from apoptosis in the chronically compressed spinal cord of twy/twy mice

STUDY DESIGN: The twy/twy mouse undergoes spontaneous chronic mechanical compression of the spinal cord; this in vivo model system was used to examine the effects of retrograde adenovirus (adenoviral vector [AdV])-mediated brain-derived neurotrophic factor (BDNF) gene delivery to spinal neural cells. OBJECTIVE: To investigate the targeting and potential neuroprotective effect of retrograde AdV-mediated BDNF gene transfection in the chronically compressed spinal cord in terms of prevention of apoptosis of neurons and oligodendrocytes. SUMMARY OF BACKGROUND DATA: Several studies have investigated the neuroprotective effects of neurotrophins, including BDNF, in spinal cord injury. However, no report has described the effects of retrograde neurotrophic factor gene delivery in compressed spinal cords, including gene targeting and the potential to prevent neural cell apoptosis. METHODS: AdV-BDNF or AdV-LacZ (as a control gene) was injected into the bilateral sternomastoid muscles of 18-week old twy/twy mice for retrograde gene delivery via the spinal accessory motor neurons. Heterozygous Institute of Cancer Research mice (+/twy), which do not undergo spontaneous spinal compression, were used as a control for the effects of such compression on gene delivery. The localization and cell specificity of ß-galactosidase expression (produced by LacZ gene transfection) and BDNF expression in the spinal cord were examined by coimmunofluorescence staining for neural cell markers (NeuN, neurons; reactive immunology protein, oligodendrocytes; glial fibrillary acidic protein, astrocytes; OX-42, microglia) 4 weeks after gene injection. The possible neuroprotection afforded by retrograde AdV-BDNF gene delivery versus AdV-LacZ-transfected control mice was assessed by scoring the prevalence of apoptotic cells (terminal deoxynucleotidyl transferase-mediated dUTP-biotin nick end labeling-positive cells) and immunoreactivity to active caspases -3, -8, and -9, p75, neurofilament 200 kD (NF), and for the oligodendroglial progenitor marker, NG2. RESULTS.: Four weeks after injection, the retrograde delivery of the LacZ marker gene was identified in cervical spinal neurons and some glial cells, including oligodendrocytes in the white matter of the spinal cord, in both the twy/twy mouse and the heterozygous Institute of Cancer Research mouse (+/twy). In the compressed spinal cord of twy/twy mouse, AdV-BDNF gene transfection resulted in a significant decrease in the number of terminal deoxynucleotidyl transferase-mediated dUTP-biotin nick end labeling-positive cells present in the spinal cord and a downregulation in the caspase apoptotic pathway compared with AdV-LacZ (control) gene transfection. There was a marked and significant increase in the areas of the spinal cord of AdV-BDNF-injected mice that were NF- and NG2-immunopositive compared with AdV-LacZ-injected mice, indicating the increased presence of neurons and oligodendrocytes in response to BDNF transfection. CONCLUSION: Our results demonstrate that targeted retrograde BDNF gene delivery suppresses apoptosis in neurons and oligodendrocytes in the chronically compressed spinal cord of twy/twy mouse. Further work is required to establish whether this method of gene delivery may provide neuroprotective effects in other situations of compressive spinal cord injury.

Identifying DNA-binding proteins by combining support vector machine and PSSM distance transformation

Background: DNA-binding proteins play a pivotal role in various intra- and extra-cellular activities ranging from DNA replication to gene expression control. Identification of DNA-binding proteins is one of the major challenges in the field of genome annotation. There have been several computational methods proposed in the literature to deal with the DNA-binding protein identification. However, most of them can't provide an invaluable knowledge base for our understanding of DNA-protein interactions. Results: We firstly presented a new protein sequence encoding method called PSSM Distance Transformation, and then constructed a DNA-binding protein identification method (SVM-PSSM-DT) by combining PSSM Distance Transformation with support vector machine (SVM). First, the PSSM profiles are generated by using the PSI-BLAST program to search the non-redundant (NR) database. Next, the PSSM profiles are transformed into uniform numeric representations appropriately by distance transformation scheme. Lastly, the resulting uniform numeric representations are inputted into a SVM classifier for prediction. Thus whether a sequence can bind to DNA or not can be determined. In benchmark test on 525 DNA-binding and 550 non DNA-binding proteins using jackknife validation, the present model achieved an ACC of 79.96%, MCC of 0.622 and AUC of 86.50%. This performance is considerably better than most of the existing state-of-the-art predictive methods. When tested on a recently constructed independent dataset PDB186, SVM-PSSM-DT also achieved the best performance with ACC of 80.00%, MCC of 0.647 and AUC of 87.40%, and outperformed some existing state-of-the-art methods. Conclusions: The experiment results demonstrate that PSSM Distance Transformation is an available protein sequence encoding method and SVM-PSSM-DT is a useful tool for identifying the DNA-binding proteins. A user-friendly web-server of SVM-PSSM-DT was constructed, which is freely accessible to the public at the web-site on http://bioinformatics.hitsz.edu.cn/PSSM-DT/.

Comparing the expression of human DNA topoisomerase I in KM71H and X33 strains of Pichia pastoris

Background: Human is an essential cellular enzyme that is found in all human cells. As this enzyme is upregulated in cancer cells exceedingly, it is used as a target for cancer chemotherapeutic drug development. As such, producing the in-house enzyme for the purpose to speed up the search for more cost-effective and target specific hTopoI inhibitors is warranted. This study aims to compare the optimised conditions for the expression of hTopoI in KM71H (MutS) and X33 (Mut+) strains of Pichia pastoris P. pastoris transfected with an hTopoI recombinant vector was used for the optimization of a higher level of hTopoI expression. Results: In the process, fed-batch cultivation parameters that influence the expression of hTopoI, such as culture temperature, methanol induction and feeding strategy, were optimised in the transfected KM71H and X33 P. pastoris strains in a shake flask system. The cell density and total protein concentration (protein level) of transfected P. pastoris were compared to determine the optimum culture conditions for each transfected P. pastoris strain. A higher hTopoI level was observed in the transfected KM71H culture supernatant (2.26 ng/mL) when the culture was incubated in the optimum conditions. Conclusions: This study demonstrated that MutS strain (KM71H) expressed and secreted a higher level of hTopoI heterologous protein in the presence of methanol compared to the Mut+ strain; X33 (0.75 ng/mL). However, other aspects of optimization, such as pH, should also be considered in the future, to obtain the optimum expression level of hTopoI in P. pastoris.

The Expanded Human Kallikrein (KLK) gene family : genomic organisation, tissue specific expression and potential functions

The tissue kallikreins are serine proteases encoded by highly conserved multigene families. The rodent kallikrein (KLK) families are particularly large, consisting of 13 26 genes clustered in one chromosomal locus. It has been recently recognised that the human KLK gene family is of a similar size (15 genes) with the identification of another 12 related genes (KLK4-KLK15) within and adjacent to the original human KLK locus (KLK1-3) on chromosome 19q13.4. The structural organisation and size of these new genes is similar to that of other KLK genes except for additional exons encoding 5 or 3 untranslated regions. Moreover, many of these genes have multiple mRNA transcripts, a trait not observed with rodent genes. Unlike all other kallikreins, the KLK4-KLK15 encoded proteases are less related (25–44%) and do not contain a conventional kallikrein loop. Clusters of genes exhibit high prostatic (KLK2-4, KLK15) or pancreatic (KLK6-13) expression, suggesting evolutionary conservation of elements conferring tissue specificity. These genes are also expressed, to varying degrees, in a wider range of tissues suggesting a functional involvement of these newer human kallikrein proteases in a diverse range of physiological processes.