Mining for Class-Specific Motifs in Protein Sequence Classification

Background: In protein sequence classification, identification of the sequence motifs or n-grams that can precisely discriminate between classes is a more interesting scientific question than the classification itself. A number of classification methods aim at accurate classification but fail to explain which sequence features indeed contribute to the accuracy. We hypothesize that sequences in lower denominations (n-grams) can be used to explore the sequence landscape and to identify class-specific motifs that discriminate between classes during classification. Discriminative n-grams are short peptide sequences that are highly frequent in one class but are either minimally present or absent in other classes. In this study, we present a new substitution-based scoring function for identifying discriminative n-grams that are highly specific to a class. Results: We present a scoring function based on discriminative n-grams that can effectively discriminate between classes. The scoring function, initially, harvests the entire set of 4- to 8-grams from the protein sequences of different classes in the dataset. Similar n-grams of the same size are combined to form new n-grams, where the similarity is defined by positive amino acid substitution scores in the BLOSUM62 matrix. Substitution has resulted in a large increase in the number of discriminatory n-grams harvested. Due to the unbalanced nature of the dataset, the frequencies of the n-grams are normalized using a dampening factor, which gives more weightage to the n-grams that appear in fewer classes and vice-versa. After the n-grams are normalized, the scoring function identifies discriminative 4- to 8-grams for each class that are frequent enough to be above a selection threshold. By mapping these discriminative n-grams back to the protein sequences, we obtained contiguous n-grams that represent short class-specific motifs in protein sequences. Our method fared well compared to an existing motif finding method known as Wordspy. We have validated our enriched set of class-specific motifs against the functionally important motifs obtained from the NLSdb, Prosite and ELM databases. We demonstrate that this method is very generic; thus can be widely applied to detect class-specific motifs in many protein sequence classification tasks. Conclusion: The proposed scoring function and methodology is able to identify class-specific motifs using discriminative n-grams derived from the protein sequences. The implementation of amino acid substitution scores for similarity detection, and the dampening factor to normalize the unbalanced datasets have significant effect on the performance of the scoring function. Our multipronged validation tests demonstrate that this method can detect class-specific motifs from a wide variety of protein sequence classes with a potential application to detecting proteome-specific motifs of different organisms.

Adherence as a predictor of the development of class-specific resistance mutations: the Swiss HIV Cohort Study.

BACKGROUND: Non-adherence is one of the strongest predictors of therapeutic failure in HIV-positive patients. Virologic failure with subsequent emergence of resistance reduces future treatment options and long-term clinical success. METHODS: Prospective observational cohort study including patients starting new class of antiretroviral therapy (ART) between 2003 and 2010. Participants were naïve to ART class and completed ≥1 adherence questionnaire prior to resistance testing. Outcomes were development of any IAS-USA, class-specific, or M184V mutations. Associations between adherence and resistance were estimated using logistic regression models stratified by ART class. RESULTS: Of 314 included individuals, 162 started NNRTI and 152 a PI/r regimen. Adherence was similar between groups with 85% reporting adherence ≥95%. Number of new mutations increased with increasing non-adherence. In NNRTI group, multivariable models indicated a significant linear association in odds of developing IAS-USA (odds ratio (OR) 1.66, 95% confidence interval (CI): 1.04-2.67) or class-specific (OR 1.65, 95% CI: 1.00-2.70) mutations. Levels of drug resistance were considerably lower in PI/r group and adherence was only significantly associated with M184V mutations (OR 8.38, 95% CI: 1.26-55.70). Adherence was significantly associated with HIV RNA in PI/r but not NNRTI regimens. CONCLUSION: Therapies containing PI/r appear more forgiving to incomplete adherence compared with NNRTI regimens, which allow higher levels of resistance, even with adherence above 95%. However, in failing PI/r regimens good adherence may prevent accumulation of further resistance mutations and therefore help to preserve future drug options. In contrast, adherence levels have little impact on NNRTI treatments once the first mutations have emerged.

Serology of paracoccidioidomycosis. II. Correlation between class-specific antibodies and clinical forms of the disease

Untreated and previously treated patients with paracoccidioidomycosis were studied for: (i) serum levels of total IgG, IgM and IgA immunoglobulins, by radial immunodiffusion and Paracoccidioides brasiliensis (Pb) antibodies, by indirect immunofluorescence; (ii) correlation between their levels with the clinical forms of the disease; (iii) correlation between the serum titres obtained by tube precipitin with those of anti-Pb IgG, IgM and IgA. In the untreated group, serum IgG levels were significantly increased in patients with the more systemic forms of the disease, especially the acute progressive form. Serum IgA levels were significantly increased in all patients with no statistical difference between clinical forms. Serum IgM levels were normal in all patients. Anti-Pb IgG, IgA and IgM were detected in 97·5%, 32·5% and 45·0% of all cases, respectively. There was a sharp tendency towards higher levels of anti-Pb IgG among those with the acute progressive form (83·4%) in relation to the chronic, more localized forms, mixed form (68·0%) and isolated organic form (55·5%). In the untreated and previously treated group sera, there was positive correlation between the level of anti-Pb IgG and positivity for the tube precipitin test, suggesting that the precipitin-type antibodies are of the IgG class. Broadly, the present data demonstrate a polyclonal activation of the humoral immune system in paracoccidioidomycosis, with a positive relationship between serological results and severity of the disease. © 1984.

Class-specific metrics for multidimensional data projection applied to CBIR

Content-based image retrieval is still a challenging issue due to the inherent complexity of images and choice of the most discriminant descriptors. Recent developments in the field have introduced multidimensional projections to burst accuracy in the retrieval process, but many issues such as introduction of pattern recognition tasks and deeper user intervention to assist the process of choosing the most discriminant features still remain unaddressed. In this paper, we present a novel framework to CBIR that combines pattern recognition tasks, class-specific metrics, and multidimensional projection to devise an effective and interactive image retrieval system. User interaction plays an essential role in the computation of the final multidimensional projection from which image retrieval will be attained. Results have shown that the proposed approach outperforms existing methods, turning out to be a very attractive alternative for managing image data sets.

Adherence as a Predictor of the Development of Class-Specific Resistance Mutations: The Swiss HIV Cohort Study

Background Non-adherence is one of the strongest predictors of therapeutic failure in HIV-positive patients. Virologic failure with subsequent emergence of resistance reduces future treatment options and long-term clinical success. Methods Prospective observational cohort study including patients starting new class of antiretroviral therapy (ART) between 2003 and 2010. Participants were naïve to ART class and completed ≥1 adherence questionnaire prior to resistance testing. Outcomes were development of any IAS-USA, class-specific, or M184V mutations. Associations between adherence and resistance were estimated using logistic regression models stratified by ART class. Results Of 314 included individuals, 162 started NNRTI and 152 a PI/r regimen. Adherence was similar between groups with 85% reporting adherence ≥95%. Number of new mutations increased with increasing non-adherence. In NNRTI group, multivariable models indicated a significant linear association in odds of developing IAS-USA (odds ratio (OR) 1.66, 95% confidence interval (CI): 1.04-2.67) or class-specific (OR 1.65, 95% CI: 1.00-2.70) mutations. Levels of drug resistance were considerably lower in PI/r group and adherence was only significantly associated with M184V mutations (OR 8.38, 95% CI: 1.26-55.70). Adherence was significantly associated with HIV RNA in PI/r but not NNRTI regimens. Conclusion Therapies containing PI/r appear more forgiving to incomplete adherence compared with NNRTI regimens, which allow higher levels of resistance, even with adherence above 95%. However, in failing PI/r regimens good adherence may prevent accumulation of further resistance mutations and therefore help to preserve future drug options. In contrast, adherence levels have little impact on NNRTI treatments once the first mutations have emerged.

Radial and tangential dispersion patterns in the mouse retina are cell-class specific.

The retina is derived from a pseudostratified germinal zone in which the relative position of a progenitor cell is believed to determine the position of the progeny aligned in the radial axis. Such a developmental mechanism would ensure that radial arrays of cells which comprise functional units in the mature central nervous system are also clonally related. The present study has tested this hypothesis by using X chromosome-inactivation transgenic mosaic mice. We report that the retina shows a conspicuous distinction for clonally related neuroblasts of different laminar and functional fates: the rod photoreceptor, Müller, and bipolar cells are aligned in the radial axis, whereas the cone photoreceptor, horizontal, amacrine, and ganglion cells are tangentially displaced with respect to them. These results indicate that the dispersion of cell classes across the retinal surface is differentially constrained. Some classes of retinal neuroblast exhibit a significant tangential, as well as radial, component in their dispersion from the germinal zone, whereas others disperse only in the radial dimension. Consequently, the majority of radial columns within the mature retina must be derived from multiple progenitors. Because the cone photoreceptor, horizontal, amacrine, and ganglion cells establish nonrandom matrices in their cellular distributions within the respective retinal layers, tangential dispersion may be the means by which these matrices are constructed.

Estimates of sex- and age-class-specific survival probabilities for a southern Great Barrier Reef green sea turtle population

Sex- and age-class-specific survival probabilities of a southern Great Barrier Reef green sea turtle population were estimated using a capture - mark - recapture (CMR) study and a Cormack - Jolly - Seber (CJS) modelling approach. The CMR history profiles for 954 individual turtles tagged over a 9-year period ( 1984 - 1992) were classified into three age classes ( adult, subadult, juvenile) based on somatic growth and reproductive traits. Reduced-parameter CJS models, accounting for constant survival and time-specific recapture, fitted best for all age classes. There were no significant sex-specific differences in either survival or recapture probabilities for any age class. Mean annual adult survival was estimated at 0.9482 (95% CI: 0.92 - 0.98) and was significantly higher than survival for either subadults or juveniles. Mean annual subadult survival was 0.8474 ( 95% CI: 0.79 - 0.91), which was not significantly different from mean annual juvenile survival estimated at 0.8804 ( 95% CI: 0.84 - 0.93). The time-specific adult recapture probabilities were a function of sampling effort but this was not the case for either juveniles or subadults. The sampling effort effect was accounted for explicitly in the estimation of adult survival and recapture probabilities. These are the first comprehensive sex- and age-class-specific survival and recapture probability estimates for a green sea turtle population derived from a long-term CMR program.

Positional bias of general and tissue-specific regulatory motifs in mouse gene promoters

Background: The arrangement of regulatory motifs in gene promoters, or promoterarchitecture, is the result of mutation and selection processes that have operated over manymillions of years. In mammals, tissue-specific transcriptional regulation is related to the presence ofspecific protein-interacting DNA motifs in gene promoters. However, little is known about therelative location and spacing of these motifs. To fill this gap, we have performed a systematic searchfor motifs that show significant bias at specific promoter locations in a large collection ofhousekeeping and tissue-specific genes.Results: We observe that promoters driving housekeeping gene expression are enriched inparticular motifs with strong positional bias, such as YY1, which are of little relevance in promotersdriving tissue-specific expression. We also identify a large number of motifs that show positionalbias in genes expressed in a highly tissue-specific manner. They include well-known tissue-specificmotifs, such as HNF1 and HNF4 motifs in liver, kidney and small intestine, or RFX motifs in testis,as well as many potentially novel regulatory motifs. Based on this analysis, we provide predictionsfor 559 tissue-specific motifs in mouse gene promoters.Conclusion: The study shows that motif positional bias is an important feature of mammalianproximal promoters and that it affects both general and tissue-specific motifs. Motif positionalconstraints define very distinct promoter architectures depending on breadth of expression andtype of tissue.

Highly specific protein sequence motifs for genome analysis

We present a method for discovering conserved sequence motifs from families of aligned protein sequences. The method has been implemented as a computer program called emotif (http://motif.stanford.edu/emotif). Given an aligned set of protein sequences, emotif generates a set of motifs with a wide range of specificities and sensitivities. emotif also can generate motifs that describe possible subfamilies of a protein superfamily. A disjunction of such motifs often can represent the entire superfamily with high specificity and sensitivity. We have used emotif to generate sets of motifs from all 7,000 protein alignments in the blocks and prints databases. The resulting database, called identify (http://motif.stanford.edu/identify), contains more than 50,000 motifs. For each alignment, the database contains several motifs having a probability of matching a false positive that range from 10−10 to 10−5. Highly specific motifs are well suited for searching entire proteomes, while generating very few false predictions. identify assigns biological functions to 25–30% of all proteins encoded by the Saccharomyces cerevisiae genome and by several bacterial genomes. In particular, identify assigned functions to 172 of proteins of unknown function in the yeast genome.

Who thinks what about capitalism? Class consciousness and attitudes to economic institutions

Attitudes to the fundamental economic institutions of capitalism, private ownership of productive property, markets as arenas for securing economic outcomes, and working class rights to associate and to strike, are key dimensions of class consciousness. This paper investigates how class location shapes these attitudes in combination with other factors like employment sector and trade union membership. Using data from the 1995 National Social Science Survey, the paper finds systematic class variation on attitudes to economic institutions that is consistent with respondents endorsing or rejecting class-specific strategies of interest realisation according to their own class circumstances. On some attitudes, class structural effects are additionally moderated by organisational norms associated with public sector employment and mediated by the impact of trade union membership.

The Individual is Nothing, the Class Everything: Psychophysics and Modeling of Recognition in Obect Classes

Most psychophysical studies of object recognition have focussed on the recognition and representation of individual objects subjects had previously explicitely been trained on. Correspondingly, modeling studies have often employed a 'grandmother'-type representation where the objects to be recognized were represented by individual units. However, objects in the natural world are commonly members of a class containing a number of visually similar objects, such as faces, for which physiology studies have provided support for a representation based on a sparse population code, which permits generalization from the learned exemplars to novel objects of that class. In this paper, we present results from psychophysical and modeling studies intended to investigate object recognition in natural ('continuous') object classes. In two experiments, subjects were trained to perform subordinate level discrimination in a continuous object class - images of computer-rendered cars - created using a 3D morphing system. By comparing the recognition performance of trained and untrained subjects we could estimate the effects of viewpoint-specific training and infer properties of the object class-specific representation learned as a result of training. We then compared the experimental findings to simulations, building on our recently presented HMAX model of object recognition in cortex, to investigate the computational properties of a population-based object class representation as outlined above. We find experimental evidence, supported by modeling results, that training builds a viewpoint- and class-specific representation that supplements a pre-existing repre-sentation with lower shape discriminability but possibly greater viewpoint invariance.

Purification and Molecular Genetic Characterization of ZPU1, a Pullulanase-Type Starch-Debranching Enzyme from Maize1

This study identified and purified specific isoamylase- and pullulanase-type starch-debranching enzymes (DBEs) present in developing maize (Zea mays L.) endosperm. The cDNA clone Zpu1 was isolated based on its homology with a rice (Oryza sativa L.) cDNA coding for a pullulanase-type DBE. Comparison of the protein product, ZPU1, with 18 other DBEs identified motifs common to both isoamylase- and pullulanase-type enzymes, as well as class-specific sequence blocks. Hybridization of Zpu1 to genomic DNA defined a single-copy gene, zpu1, located on chromosome 2. Zpu1 mRNA was abundant in endosperm throughout starch biosynthesis, but was not detected in the leaf or the root. Anti-ZPU1 antiserum specifically recognized the approximately 100-kD ZPU1 protein in developing endosperm, but not in leaves. Pullulanase- and isoamylase-type DBEs were purified from extracts of developing maize kernels. The pullulanase-type activity was identified as ZPU1 and the isoamylase-type activity as SU1. Mutations of the sugary1 (su1) gene are known to cause deficiencies of SU1 isoamylase and a pullulanase-type DBE. ZPU1 activity, protein level, and electrophoretic mobility were altered in su1-mutant kernels, indicating that it is the affected pullulanase-type DBE. The Zpu1 transcript levels were equivalent in nonmutant and su1-mutant kernels, suggesting that coordinated regulation of ZPU1 and SU1 occurs posttranscriptionally.

Crystal structure of an H-2Kb-ovalbumin peptide complex reveals the interplay of primary and secondary anchor positions in the major histocompatibility complex binding groove.

Sequence analysis of peptides naturally presented by major histocompatibility complex (MHC) class I molecules has revealed allele-specific motifs in which the peptide length and the residues observed at certain positions are restricted. Nevertheless, peptides containing the standard motif often fail to bind with high affinity or form physiologically stable complexes. Here we present the crystal structure of a well-characterized antigenic peptide from ovalbumin [OVA-8, ovalbumin-(257-264), SIINFEKL] in complex with the murine MHC class I H-2Kb molecule at 2.5-A resolution. Hydrophobic peptide residues Ile-P2 and Phe-P5 are packed closely together into binding pockets B and C, suggesting that the interplay of peptide anchor (P5) and secondary anchor (P2) residues can couple the preferred sequences at these positions. Comparison with the crystal structures of H-2Kb in complex with peptides VSV-8 (RGYVYQGL) and SEV-9 (FAPGNYPAL), where a Tyr residue is used as the C pocket anchor, reveals that the conserved water molecule that binds into the B pocket and mediates hydrogen bonding from the buried anchor hydroxyl group could not be likewise positioned if the P2 side chain were of significant size. Based on this structural evidence, H-2Kb has at least two submotifs: one with Tyr at P5 (or P6 for nonamer peptides) and a small residue at P2 (i.e., Ala or Gly) and another with Phe at P5 and a medium-sized hydrophobic residue at P2 (i.e., Ile). Deciphering of these secondary submotifs from both crystallographic and immunological studies of MHC peptide binding should increase the accuracy of T-cell epitope prediction.

N-terminal amino acid sequences of the major outer membrane proteins from a Neisseria meningitidis group B strain isolated in Brazil

The four dominant outer membrane proteins (46, 38, 33 and 28 kDa) were detected by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) in a semi-purified preparation of vesicle membranes of a Neisseria meningitidis (N44/89, B:4:P1.15:P5.5,7) strain isolated in Brazil. The N-terminal amino acid sequence for the 46 kDa and 28 kDa proteins matched that reported by others for class 1 and 5 proteins respectively, whereas the sequence (25 amino acids) for the 38 kDa (class 3) protein was similar to class 1 meningococcal proteins. The sequence for the 33 kDa (class 4) was unique and not homologous to any known protein.

MAMOT: hidden Markov modeling tool.

Hidden Markov models (HMMs) are probabilistic models that are well adapted to many tasks in bioinformatics, for example, for predicting the occurrence of specific motifs in biological sequences. MAMOT is a command-line program for Unix-like operating systems, including MacOS X, that we developed to allow scientists to apply HMMs more easily in their research. One can define the architecture and initial parameters of the model in a text file and then use MAMOT for parameter optimization on example data, decoding (like predicting motif occurrence in sequences) and the production of stochastic sequences generated according to the probabilistic model. Two examples for which models are provided are coiled-coil domains in protein sequences and protein binding sites in DNA. A wealth of useful features include the use of pseudocounts, state tying and fixing of selected parameters in learning, and the inclusion of prior probabilities in decoding. AVAILABILITY: MAMOT is implemented in C++, and is distributed under the GNU General Public Licence (GPL). The software, documentation, and example model files can be found at http://bcf.isb-sib.ch/mamot