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PubMed2005

An improved reverse transcription-polymerase chain reaction (RT-PCR) assay for the detection of two cherry flexiviruses in Prunus spp.

A one-step reverse transcription-polymerase chain reaction (RT-PCR) procedure was developed to detect Cherry green ring mottle virus (CGRMV) and Cherry necrotic rusty mottle virus (CNRMV) in woody indicators and naturally infected Prunus spp. Viral RNA suitable for RT-PCR was obtained by a simple trapping method that did not require either extraction of double-stranded RNA (dsRNA) or total RNA, availability of virus antibodies, or purification of viral particles. Consensus primers, degenerate primers and virus-specific primers, whose designs were based on alignments of available cherry flexivirus sequences, were tested to amplify viral genomic fragments of six CGRMV isolates and one CNRMV isolate. RT-PCR allowed CGRMV detection in total RNA and viral RNA preparations equivalent to 400mug and 4mug of infected leaf tissue, respectively. CGRMV was detected in tender shoots, leaves, bark and root tips, and the strongest bands were obtained using young leaves. Detection was less consistent in summer when the temperature was elevated and plant tissues were old. A direct comparison of the RT-PCR and grafting assays indicated that the RT-PCR assay is sensitive, rapid and reliable. The method will improve the routine diagnosis of cherry flexiviruses in Prunus spp.

Capsid Proteins↗
PubMed2006

Detection of human sapovirus by real-time reverse transcription-polymerase chain reaction.

Sapovirus (SaV) is an agent of gastroenteritis for humans and swine, and is divided into five distinct genogroups (GI-GV) based on its capsid gene sequences. Typical methods of SaV detection include electron microscopy (EM), enzyme-linked immunosorbent assay (ELISA), and reverse transcription-polymerase chain reaction (RT-PCR). A novel TaqMan-based real-time RT-PCR assay was developed that is sensitive and has the ability to detect the broad range of genetically diverse human SaV strains. A nucleotide alignment of 10 full-length SaV genome sequences was subjected to similarity plot analysis, which indicated that the most conserved site was the polymerase-capsid junction in open reading frame 1 (ORF1). Based on multiple alignments of the 27 available sequences encoding this junction, we designed sets of primers and TaqMan MGB probes that detect human SaV GI, GII, GIV, and GV sequences in a single tube. The reactivity was confirmed with SaV GI, GII, GIV, and GV control plasmids, and the efficiency ranged from 2.5 x 10(7) to 2.5 x 10(1) copies per tube. Analysis using clinical stool specimens revealed that the present system was capable of detecting SaV GI, GII, GIV, and GV sequences, and no cross-reactivity was observed against other enteric viruses, including norovirus (NoV), rotavirus, astrovirus, and adenovirus. This is the first real-time RT-PCR system that could detect all genogroups of human sapoviruses.

Australia↗
PubMed2005

A fractional programming approach to efficient DNA melting temperature calculation.

MOTIVATION: In a wide range of experimental techniques in biology, there is a need for an efficient method to calculate the melting temperature of pairings of two single DNA strands. Avoiding cross-hybridization when choosing primers for the polymerase chain reaction or selecting probes for large-scale DNA assays are examples where the exact determination of melting temperatures is important. Beyond being exact, the method has to be efficient, as these techniques often require the simultaneous calculation of melting temperatures of up to millions of possible pairings. The problem is to simultaneously determine the most stable alignment of two sequences, including potential loops and bulges, and calculate the corresponding melting temperature. RESULTS: As the melting temperature can be expressed as a fraction in terms of enthalpy and entropy differences of the corresponding annealing reaction, we propose to use a fractional programming algorithm, the Dinkelbach algorithm, to solve the problem. To calculate the required differences of enthalpy and entropy, the Nearest Neighbor model is applied. Using this model, the substeps of the Dinkelbach algorithm in our problem setting turn out to be calculations of alignments which optimize an additive score function. Thus, the usual dynamic programming techniques can be applied. The result is an efficient algorithm to determine melting temperatures of two DNA strands, suitable for large-scale applications such as primer or probe design. AVAILABILITY: The software is available for academic purposes from the authors. A web interface is provided at http://www.zaik.uni-koeln.de/bioinformatik/fptm.html

Algorithms↗
PubMed2005

Protein classification based on text document classification techniques.

The need for accurate, automated protein classification methods continues to increase as advances in biotechnology uncover new proteins. G-protein coupled receptors (GPCRs) are a particularly difficult superfamily of proteins to classify due to extreme diversity among its members. Previous comparisons of BLAST, k-nearest neighbor (k-NN), hidden markov model (HMM) and support vector machine (SVM) using alignment-based features have suggested that classifiers at the complexity of SVM are needed to attain high accuracy. Here, analogous to document classification, we applied Decision Tree and Naive Bayes classifiers with chi-square feature selection on counts of n-grams (i.e. short peptide sequences of length n) to this classification task. Using the GPCR dataset and evaluation protocol from the previous study, the Naive Bayes classifier attained an accuracy of 93.0 and 92.4% in level I and level II subfamily classification respectively, while SVM has a reported accuracy of 88.4 and 86.3%. This is a 39.7 and 44.5% reduction in residual error for level I and level II subfamily classification, respectively. The Decision Tree, while inferior to SVM, outperforms HMM in both level I and level II subfamily classification. For those GPCR families whose profiles are stored in the Protein FAMilies database of alignments and HMMs (PFAM), our method performs comparably to a search against those profiles. Finally, our method can be generalized to other protein families by applying it to the superfamily of nuclear receptors with 94.5, 97.8 and 93.6% accuracy in family, level I and level II subfamily classification respectively.

Algorithms↗
PubMed1999

A probabilistic treatment of phylogeny and sequence alignment.

Carrying out simultaneous tree-building and alignment of sequence data is a difficult computational task, and the methods currently available are either limited to a few sequences or restricted to highly simplified models of alignment and phylogeny. A method is given here for overcoming these limitations by Bayesian sampling of trees and alignments simultaneously. The method uses a standard substitution matrix model for residues together with a hidden Markov model structure that allows affine gap penalties. It escapes the heavy computational burdens of other models by using an approximation called the "*" rule, which replaces missing data by a sum over all possible values of variables. The behavior of the model is demonstrated on test sets of globins.

Bayes Theorem↗
PubMed1997

Predicting protein structure using hidden Markov models.

We discuss how methods based on hidden Markov models performed in the fold-recognition section of the CASP2 experiment. Hidden Markov models were built for a representative set of just over 1,000 structures from the Protein Data Bank (PDB). Each CASP2 target sequence was scored against this library of HMMs. In addition, an HMM was built for each of the target sequences and all of the sequences in PDB were scored against that target model, with a good score on both methods indicating a high probability that the target sequence is homologous to the structure. The method worked well in comparison to other methods used at CASP2 for targets of moderate difficulty, where the closest structure in PDB could be aligned to the target with at least 15% residue identity.

Markov Chains↗
PubMed2002

A sequence-profile-based HMM for predicting and discriminating beta barrel membrane proteins.

MOTIVATION: Membrane proteins are an abundant and functionally relevant subset of proteins that putatively include from about 15 up to 30% of the proteome of organisms fully sequenced. These estimates are mainly computed on the basis of sequence comparison and membrane protein prediction. It is therefore urgent to develop methods capable of selecting membrane proteins especially in the case of outer membrane proteins, barely taken into consideration when proteome wide analysis is performed. This will also help protein annotation when no homologous sequence is found in the database. Outer membrane proteins solved so far at atomic resolution interact with the external membrane of bacteria with a characteristic beta barrel structure comprising different even numbers of beta strands (beta barrel membrane proteins). In this they differ from the membrane proteins of the cytoplasmic membrane endowed with alpha helix bundles (all alpha membrane proteins) and need specialised predictors. RESULTS: We develop a HMM model, which can predict the topology of beta barrel membrane proteins using, as input, evolutionary information. The model is cyclic with 6 types of states: two for the beta strand transmembrane core, one for the beta strand cap on either side of the membrane, one for the inner loop, one for the outer loop and one for the globular domain state in the middle of each loop. The development of a specific input for HMM based on multiple sequence alignment is novel. The accuracy per residue of the model is 83% when a jack knife procedure is adopted. With a model optimisation method using a dynamic programming algorithm seven topological models out of the twelve proteins included in the testing set are also correctly predicted. When used as a discriminator, the model is rather selective. At a fixed probability value, it retains 84% of a non-redundant set comprising 145 sequences of well-annotated outer membrane proteins. Concomitantly, it correctly rejects 90% of a set of globular proteins including about 1200 chains with low sequence identity (<30%) and 90% of a set of all alpha membrane proteins, including 188 chains.

Algorithms↗
PubMed1998

Improved stability and yield of a Fv-toxin fusion protein by computer design and protein engineering of the Fv.

The conversion of the anti-mesothelin monoclonal antibody K1 to a single-chain Fv (scFv) that is fused to a truncated form of Pseudomonas exotoxin A (PE) results in a fusion protein (immunotoxin) that is unstable and refolds very inefficiently. We have devised a method that identifies candidate residues in the framework region of K1 Fv that, when mutated, improved the yield and stability of the protein. The method works by initially aligning the framework sequences of K1 VH and VL with those of other scFvs that are stable and give a good yield as immunotoxins. Then we assigned a character to each residue that indicates its state of exposure based on the known crystal structures of Fabs. This identifies residues that are not compatible with their environment in the folded state of the protein. Next we calculated the frequencies of different amino acids for each position of the Fvs based on the available sequence database. This identifies residues that are not commonly present in the conserved positions. If these residues are compatible with their exposure profile they are left unaltered. Otherwise, they are identified as candidate residues for mutation. We identified two such residues in the VH (T82 and A85) and two in the VL (H36 and V60) of K1 that did not seem appropriate for their respective positions. By mutating these residues in K1 into those that occur most commonly in the sequence database or in stable scFvs, we significantly improved the stability and yield of the K1 scFv immunotoxins. By making single and combined mutations we assessed the relative contribution of mutations at these four sites towards the stability and yield of K1 scFv immunotoxins. The method we devised is probably general and can be used to improve other scFvs.

Amino Acid Sequence↗
PubMed2002

Purification, N-terminal sequencing, crystallization and preliminary X-ray diffraction analysis of atratoxin, a new short-chain alpha-neurotoxin from the venom of Naja naja atra.

Atratoxin, a new alpha-neurotoxin purified to homogeneity by a series of liquid chromatographies from the venom of Naja naja atra (mainland Chinese cobra), is a small single-polypeptide alkaline protein with a pI of about 9.5 and molecular weight of 6952 Da estimated by mass spectrometry. Although the sequencing of the N-terminal 15 residues (LECHNQQTTQQPEGG) shows that this neurotoxic protein contains most of the residues, especially at the conserved positions, of the consensus sequence of short-chain alpha-neurotoxins, the natural mutations in the N-terminal Loop-1 presented by the sequence alignment may have structural or functional implications for the interactions between alpha-neurotoxins and related receptors. Single crystals of atratoxin have been grown from drops containing the necessary Cu(2+) ions by the conventional hanging-drop vapour-diffusion method. The crystals diffract X-rays to 1.6 A resolution and belong to space group C222(1), with unit-cell parameters a = 47.36, b = 47.83, c = 91.31 A, corresponding to a volume-to-mass ratio of 1.85 A(3) Da(-1) and two molecules in each asymmetric unit.

Amino Acid Sequence↗
PubMed2004

A multiplex RT-PCR assay capable of distinguishing beet necrotic yellow vein virus types A and B.

A multiplex reverse-transcription polymerase chain assay (mRT-PCR) was developed, based on primers designed to distinguish the A and B types of beet necrotic yellow vein virus (BNYVV). RNA was extracted from 72 BNYVV isolates from Asia, Europe and North America, and the type of each isolate determined using an established detection method based on single strand conformation polymorphisms (SSCPs). An area of the 'triple gene block' region on RNA 2 was amplified and sequenced from 16 isolates of the A and B types. These sequences were aligned and two sets of PCR primers were designed to amplify unique areas common to each type. The A type assay produced a single 324 base-pair RT-PCR fragment when positive samples were amplified. The B type assay produced a 178 base-pair product from positive samples. No amplification was observed from healthy Chenopodium quinoa or sugar beet plants and from plants infected by others sugar beet soil-borne viruses. Fragment length differed sufficiently to allow both assays to be run in a single PCR tube. The results obtained using the new multiplex RT-PCR assay were consistent with those from the established SSCP method for all 72 reference samples.

Base Sequence↗
PubMed2001

Typing of human papillomavirus by pyrosequencing.

The possibility of using a new bioluminometric DNA sequencing technique, called pyrosequencing, for typing of human papillomaviruses (HPV) was investigated. A blinded pyrosequencing test was performed on an HPV test panel of 67 GP5+/GP6+ PCR-derived amplification products. The 67 clinical DNA samples were sequenced up to 25 bases and sequences were searched using BLAST. All of the samples were correctly genotyped by pyrosequencing and the results were unequivocally in accordance with the results obtained from conventional DNA sequencing. Pyrosequencing was found to be a fast and efficient tool for identifying individual HPV types. Furthermore, pyrosequencing has the capability of determining novel HPV types as well as HPV sequence variants harboring mutation(s). The method is robust and well suited for large-scale programs.

Base Sequence↗
PubMedDate not supplied

A discriminative framework for detecting remote protein homologies.

A new method for detecting remote protein homologies is introduced and shown to perform well in classifying protein domains by SCOP superfamily. The method is a variant of support vector machines using a new kernel function. The kernel function is derived from a generative statistical model for a protein family, in this case a hidden Markov model. This general approach of combining generative models like HMMs with discriminative methods such as support vector machines may have applications in other areas of biosequence analysis as well.

Biometry↗
PubMed1990

A new concept of fibrin formation based upon the linear growth of interlacing and branching polymers and molecular alignment into interlocked single-stranded segments.

In a previous electron microscopic study of early fibrin polymers processed by freeze drying and rotatory shadowing, a large proportion of loosely constructed, frequently branching linear molecular chains was observed; their structural organization was inconsistent with a half-staggered double-stranded model for fibrin polymerization. These conflicting results prompted us to investigate the structure of early fibrin polymers prepared according to a large variety of methods currently used for electron microscopy of macromolecules. By use of a systematic random sampling procedure, fibrin polymers were photographically recorded. They were classified according to their morphological form, and the frequency of occurrence of each configuration was determined. Half-staggered double-stranded forms accounted for less than 1% of all types encountered. Interpretation of the structural organization manifested in the diverse polymer forms observed necessitated the construction of a new interlocked single-strand model for fibrin polymerization. The fibrin polymerization process combines simultaneous propagation of linear growth, branching, and lateral interlocking (leading to lateral association), resulting in the rapid formation of a fibrin network. The structural pattern developing during growth of fibrin polymers appears to be determined principally by the enzymatic mechanism and not solely by the intrinsic molecular structure of fibrinogen. The validity of the interlocked single-strand model was tested by selective fibrinopeptide-B-releasing experiments. Under such activation conditions, the polymer forms predicted according to this and the half-staggered double-strand models should differ; the structures observed were indeed consistent with the interlocked single-strand hypothesis. The compatibility of existing data with this model is discussed.

Fibrin↗
PubMed1993

Using Dirichlet mixture priors to derive hidden Markov models for protein families.

A Bayesian method for estimating the amino acid distributions in the states of a hidden Markov model (HMM) for a protein family or the columns of a multiple alignment of that family is introduced. This method uses Dirichlet mixture densities as priors over amino acid distributions. These mixture densities are determined from examination of previously constructed HMMs or multiple alignments. It is shown that this Bayesian method can improve the quality of HMMs produced from small training sets. Specific experiments on the EF-hand motif are reported, for which these priors are shown to produce HMMs with higher likelihood on unseen data, and fewer false positives and false negatives in a database search task.

Amino Acid Sequence↗
PubMed2004

Investigating fatty acids inserted into magnetically aligned phospholipid bilayers using EPR and solid-state NMR spectroscopy.

This is the first time (2)H solid-state NMR spectroscopy and spin-labeled EPR spectroscopy have been utilized to probe the structural orientation and dynamics of a stearic acid incorporated into magnetically aligned phospholipid bilayers or bicelles. The data gleaned from the two different techniques provide a more complete description of the bilayer membrane system. Both methods provided similar qualitative information on the phospholipid bilayer, high order, and low motion for the hydrocarbon segment close to the carboxyl groups of the stearic acid and less order and more rapid motion at the end towards the terminal methyl groups. However, the segmental order parameters differed markedly due to the different orientations that the nitroxide and C-D bond axes transform with the various stearic acid acyl chain conformations, and because of the difference in dynamic sensitivity between NMR and EPR over the timescales examined. 5-, 7-, 12-, and 16-doxylstearic acids spin-labels were used in the EPR experiments and stearic acid-d(35) was used in the solid-state NMR experiments. The influence of the addition of cholesterol and the variation of temperature on the fatty acid hydrocarbon chain ordering in the DMPC/DHPC phospholipid bilayers was also studied. Cholesterol increased the degree of ordering of the hydrocarbon chains. Conversely, as the temperature of the magnetically aligned phospholipid bilayers increased, the order parameters decreased due to the higher random motion of the acyl chain of the stearic acid. The results indicate that magnetically aligned phospholipid bilayers are an excellent model membrane system and can be used for both NMR and EPR studies.

Dimyristoylphosphatidylcholine↗
PubMed1993

Protein fold refinement: building models from idealized folds using motif constraints and multiple sequence data.

A general solution to the problem of directly incorporating data from multiple sequence alignments into the construction of molecular models was approached through the calculation of an estimated pairwise distance based on conserved hydrophobicity. A scaling method was developed that allowed the required bulk geometric properties of the estimated pair-wise distances (mean and mean squared) to mimic those expected in a globular protein. These properties were maintained independently of the composition, length, number or degree of conservation of the original sequences. Despite being a poor estimate for individual distances were found to be compatible with the native structure and could be weighted highly. While the estimated distances provided a general drive towards hydrophobic packing, more specific structure (including secondary structures and motifs) were induced by regularization towards an ideal form. These constraints were used to refine an outline starting structure (derived only from secondary structure axes) towards a compact form that was sufficiently protein-like for side chains to be added with almost no further adjustment of the alpha-carbon positions. This process allows rough folds based on abstract representations of protein architecture to be rapidly converted to a form where they can be analysed by the growing number of methods designed to assess molecular models.

Chemical Phenomena↗
PubMed2000

Keratin orientation in wool and feathers by polarized raman spectroscopy.

Good quality polarized Raman spectra of a single wool fiber and an intact feather barbule are presented. The intensity ratio of the alpha-helix component of the amide I band measured parallel and perpendicular to the wool fiber axis was 0.39 +/- 0.05. This is consistent with theoretical predictions based on orientational calculations using the normal Raman polarizability tensor for an alpha-helical amide I band where the protein strands are aligned roughly parallel with the fiber axis. However, the depolarized spectral intensity of the alpha-helix mode was greater than expected. For the feather barbule, despite high quality spectra, a unique orientation of the beta-sheet structure could not be determined using the Raman intensity ratios of the amide I band alone. Using previously developed methods, the protein chains were found to be oriented between 60 and 90 degrees from the long axis of the barbule compared to an angle of 51 degrees calculated from polarized IR spectra of the same barbule. The Raman tensor methods for the determination of protein orientation in these fibers was found to be constrained by the complexity of the materials and the limitations of the band fitting methods used to apportion the intensity among the various vibrational modes of their spectra. Other advantages and limitations of polarized Raman microscopic methods of structural determination are discussed.

Animals↗