Orientation and conformation of a lipase at an interface studied by molecular dynamics simulations

Electron density profiles calculated from molecular dynamics trajectories are used to deduce the orientation and conformation of Thermomyces lanuginosa lipase and a mutant adsorbed at an air-water interface. It is demonstrated that the profiles display distinct fine structures, which uniquely characterize enzyme orientation and conformation. The density profiles are, on the nanosecond timescale, determined by the average enzyme conformation. We outline a computational scheme that from a single molecular dynamics trajectory allows for extraction of electron density profiles referring to different orientations of the lipase relative to an implicit interface. Profiles calculated for the inactive and active conformations of the lipase are compared with experimental electron density profiles measured by x-ray reflectivity for the lipase adsorbed at an air-water interface. The experimental profiles contain less fine structural information than the calculated profiles because the resolution of the experiment is limited by the intrinsic surface roughness of water. Least squares fits of the calculated profiles to the experimental profiles provide areas per adsorbed enzyme and suggest that Thermomyces lanuginosa lipase adsorbs to the air-water interface in a semiopen conformation with the lid oriented away from the interface.     

Prediction potential of candidate biomarker sets identified and validated on gene expression data from multiple datasets

Background  

Independently derived expression profiles of the same biological condition often have few genes in common. In this study, we created populations of expression profiles from publicly available microarray datasets of cancer (breast, lymphoma and renal) samples linked to clinical information with an iterative machine learning algorithm. ROC curves were used to assess the prediction error of each profile for classification. We compared the prediction error of profiles correlated with molecular phenotype against profiles correlated with relapse-free status. Prediction error of profiles identified with supervised univariate feature selection algorithms were compared to profiles selected randomly from a) all genes on the microarray platform and b) a list of known disease-related genes (a priori selection). We also determined the relevance of expression profiles on test arrays from independent datasets, measured on either the same or different microarray platforms.     

Use of plasmid profiles to detect changes in strains of Staphylococcus aureus during poultry processing

The plasmid profiles of Staphylococcus aureus strains isolated at different stages in three poultry processing plants have been examined. Changes in profiles were seen in two plants after the plucking stage and the appearance of these new profiles correlated with the presence of an endemic strain, as suggested previously by increases in bacterial counts and changes in biotypes at the same stage. A third plant in which such changes did not occur showed no change in profiles. Plasmid profiles are therefore a rapid and sensitive method for distinguishing endemic strains within a plant from the flora of the incoming birds. Certain profiles also appeared to correspond with particular biotypes and certain phage types.     

Use of plasmid profiles to detect changes in strains of Staphylococcus aureus during poultry processing

The plasmid profiles of Staphylococcus aureus strains isolated at different stages in three poultry processing plants have been examined. Changes in profiles were seen in two plants after the plucking stage and the appearance of these new profiles correlated with the presence of an endemic strain, as suggested previously by increases in bacterial counts and changes in biotypes at the same stage. A third plant in which such changes did not occur showed no change in profiles. Plasmid profiles are therefore a rapid and sensitive method for distinguishing endemic strains within a plant from the flora of the incoming birds. Certain profiles also appeared to correspond with particular biotypes and certain phage types.     

Multi-class cancer classification through gene expression profiles:microRNA versus mRNA

Both microRNA （miRNA） and mRNA expression profiles are important methods for cancer type classification. A comparative study of their classification performance will be helpful in choosing the means of classification. Here we evaluated the classification performance of miRNA and mRNA profiles using a new data mining approach based on a novel SVM （Support Vector Machines） based recursive fea- ture elimination （nRFE） algorithm. Computational experiments showed that information encoded in miRNAs is not sufficient to classify cancers; gut-derived samples cluster more accurately when using mRNA expression profiles compared with using miRNA profiles; and poorly differentiated tumors （PDT） could be classified by mRNA expression profiles at the accuracy of 100% versus 93.8% when using miRNA profiles. Furthermore, we showed that mRNA expression profiles have higher capacity in normal tissue classifications than miRNA. We concluded that classification performance using mRNA profiles is superior to that of miRNA profiles in multiple-class cancer classifications.     

Discrete profile comparison using information bottleneck

Sequence homologs are an important source of information about proteins. Amino acid profiles, representing the position-specific mutation probabilities found in profiles, are a richer encoding of biological sequences than the individual sequences themselves. However, profile comparisons are an order of magnitude slower than sequence comparisons, making profiles impractical for large datasets. Also, because they are such a rich representation, profiles are difficult to visualize. To address these problems, we describe a method to map probabilistic profiles to a discrete alphabet while preserving most of the information in the profiles. We find an informationally optimal discretization using the Information Bottleneck approach (IB). We observe that an 80-character IB alphabet captures nearly 90% of the amino acid occurrence information found in profiles, compared to the consensus sequence's 78%. Distant homolog search with IB sequences is 88% as sensitive as with profiles compared to 61% with consensus sequences (AUC scores 0.73, 0.83, and 0.51, respectively), but like simple sequence comparison, is 30 times faster. Discrete IB encoding can therefore expand the range of sequence problems to which profile information can be applied to include batch queries over large databases like SwissProt, which were previously computationally infeasible.     

Stereological study of the synaptic profiles belonging to interneurons in the dorsal lateral geniculate nucleus of the rabbit.

This study is concerned with some characteristics of the interneurons belonging to the dLGN (dorsal Lateral Geniculate Nucleus) of the rabbit. The work deals with the distribution of such cells in the alpha E sector of the nucleus and their F1 and F2 presynaptic contacts. The F1 and the F2 profiles are present in all three of the alpha E zones studied. The F1 profiles are significantly more numerous in the upper zone (57 +/- 2 profiles per 10(4) microns2 of section) and the middle zone (59 +/- 3 profiles per 10(4) microns2 of section) than in the lower one (41 +/- 2 profiles per 10(4) microns2 of section). The F2 profiles are more abundant in the alpha E sector than the F1 ones are, particularly in the lower zone, where F2 profiles (104 +/- 4 profiles per 10(4) microns2 of section) are not only significantly more numerous than F1 profiles but also more abundant than the F2 profiles in the middle zone (84 +/- 3 profiles per 10(4) microns2 of section) and upper zone (88 +/- 2 profiles per 10(4) microns2 of section). These results and their comments reveal diverse density of the element distribution from the dorsal to the ventral part of the alpha E sector as well as the possible relationship or independence from the extranuclear afferent inputs.     

The fine structure of the dorsal column nucleus and the nucleus of bischoff of the python (Python reticulatus)

Three types of neuronal perikaryal profiles were identified in the dorsal column nucleus and the nucleus of Bischoff of the python (Python reticulatus). Type I neuronal profiles are large (diameters 12–20 μm) with a deeply indented uncleus. The cisterns of rough endoplasmic reticulum (rER) are mostly randomly dispersed. Axosomatic synapses are few. Type II neuronal profiles (9–11 μm) have a smooth, round, or slightly oval nucleus. Several small stacks of rER are present. Type III neuronal profiles (8–10 μm) have little cytoplasm. The nuclear margin is irregular but not deeply infolded. The rER usually consists of a single long perinuclear ribosome-studded cistern. Two types of astrocytic profiles have been identified. Both types contain abundant filaments. Type I astrocytes are large cells, and the nucleus is very irregular in shape. Type II astrocytes are smaller and are found among the myelinated axons in the dorsal funiculus. Two classes of axon terminals have been identified. One class contains round synaptic vesicles (R profiles) and the other flattened vesicles (F profiles). Some R profiles are small (SR profiles), others are large (LR profiles). Some R profiles also contain a few large, dense-cored vesicles. The R and F profiles establish axodendritic and axoaxonal synapses, some of which are located in the synaptic glomeruli and others in the extraglomerular neuropil. In most of the axoaxonal synapses, the presynaptic element is an F profile and the post synaptic element an LR profile. Occasionally, LR profiles are presynaptic to F profiles. The findings in the python are compared with those of the dorsal column nuclei of the rat, cat, and monkey.     

DNA image cytometry on machine-selected breast cancer cells and a comparison between flow cytometry and scanning cytophotometry

A DNA image cytometry method, implemented on the LEYTAS image processing system, has been applied to acriflavine-Feulgen-stained breast cancer cytology specimens. An essential feature of the LEYTAS image cytometry method (LCM) is the automated selection of single nuclei according to predetermined specifications. Visual interaction has been used to reject remaining artefacts like overlapping nuclei. DNA profiles obtained with LCM have been compared with DNA profiles obtained by scanning cytophotometry (SCM) or flow cytometry (FCM). The resolution of DNA profiles obtained with LCM is similar to that from SCM but lower than that from FCM. However, a high correlation is found for the DNA indices measured with LCM and FCM (r = 0.97). The LCM profiles of aneuploid tumours generally showed lower accessory diploid fractions than FCM profiles due to the automated rejection of leukocyte nuclei. Also, LCM profiles frequently showed the presence of minor subpopulations of highly aneuploid/polyploid tumour cells that could not be identified by FCM. Therefore, LCM appears to be supplementary to FCM for studying tumour cell stemline heterogeneity.     

ORFeus: Detection of distant homology using sequence profiles and predicted secondary structure

ORFeus is a fully automated, sensitive protein sequence similarity search server available to the academic community via the Structure Prediction Meta Server (http://BioInfo.PL/Meta/). The goal of the development of ORFeus was to increase the sensitivity of the detection of distantly related protein families. Predicted secondary structure information was added to the information about sequence conservation and variability, a technique known from hybrid threading approaches. The accuracy of the meta profiles created this way is compared with profiles containing only sequence information and with the standard approach of aligning a single sequence with a profile. Additionally, the alignment of meta profiles is more sensitive in detecting remote homology between protein families than if aligning two sequence-only profiles or if aligning a profile with a sequence. The specificity of the alignment score is improved in the lower specificity range compared with the robust sequence-only profiles.     

THREE-DIMENSIONAL DIVING BEHAVIORS OF RINGED SEALS (PHOCA HISPIDA)

Dives of five freely diving ringed seals were classified into three-dimentional movement types. Horizontally convoluted dives, defined as dives with angular velocity > 15°/sec, appeared to be foraging or social dives. Simple dives that did not include convoluted movements (angular velocity < 10°/sec) were considered to be exploration dives. Directional dives with nearly linear horizontal travel (horizontal directionality >0.6, on a scale of 0–1) were presumed to be travel dives. Each three-dimensional dive type was observed with similar frequency in dives with two distinct time-depth profiles: V-shaped profiles in which ascent immediately followed descent, and U-shaped profiles in which >7 sec were spent at depth between descent and ascent. The lack of behavioral differences between dives with distinct time-depth profiles suggested that time-depth profiles are not a reliable means of inferring dive behaviors for ringed seals.     

Analysis of binding site similarity, small-molecule similarity and experimental binding profiles in the human cytosolic sulfotransferase family

MOTIVATION: In the present work we combine computational analysis and experimental data to explore the extent to which binding site similarities between members of the human cytosolic sulfotransferase family correlate with small-molecule binding profiles. Conversely, from a small-molecule point of view, we explore the extent to which structural similarities between small molecules correlate to protein binding profiles. RESULTS: The comparison of binding site structural similarities and small-molecule binding profiles shows that proteins with similar small-molecule binding profiles tend to have a higher degree of binding site similarity but the latter is not sufficient to predict small-molecule binding patterns, highlighting the difficulty of predicting small-molecule binding patterns from sequence or structure. Likewise, from a small-molecule perspective, small molecules with similar protein binding profiles tend to be topologically similar but topological similarity is not sufficient to predict their protein binding patterns. These observations have important consequences for function prediction and drug design.     

Development of a random amplification of polymorphic DNA typing method for Listeria monocytogenes.

The 10-mer primer OPM-01 (5'-GTT GGT GGC T-3') was used to generate random amplification of polymorphic DNA (RAPD) profiles by polymerase chain reaction for 91 strains of Listeria monocytogenes from raw milk, food, and veterinary, medical, and food-environmental sources. The profiles obtained contained 1 to 10 bands within the molecular size range of 0.5 to 5.0 kbp. Reproducibility was enhanced by annealing at low stringency and introducing a 1-min ramp time between annealing and extension temperatures. Thirty-three RAPD profiles were observed, with specific profiles being observed for strains from each source. RAPD profiles allowed discrimination within serogroups, although five RAPD profiles which were not confined to one serotype were found. Within food strains, one RAPD profile was more common than others, suggesting this to be a common type among strains from this source.     

An eco-informatics tool for microbial community studies: supervised classification of Amplicon Length Heterogeneity (ALH) profiles of 16S rRNA

Support vector machines (SVM) and K-nearest neighbors (KNN) are two computational machine learning tools that perform supervised classification. This paper presents a novel application of such supervised analytical tools for microbial community profiling and to distinguish patterning among ecosystems. Amplicon length heterogeneity (ALH) profiles from several hypervariable regions of 16S rRNA gene of eubacterial communities from Idaho agricultural soil samples and from Chesapeake Bay marsh sediments were separately analyzed. The profiles from all available hypervariable regions were concatenated to obtain a combined profile, which was then provided to the SVM and KNN classifiers. Each profile was labeled with information about the location or time of its sampling. We hypothesized that after a learning phase using feature vectors from labeled ALH profiles, both these classifiers would have the capacity to predict the labels of previously unseen samples. The resulting classifiers were able to predict the labels of the Idaho soil samples with high accuracy. The classifiers were less accurate for the classification of the Chesapeake Bay sediments suggesting greater similarity within the Bay's microbial community patterns in the sampled sites. The profiles obtained from the V1+V2 region were more informative than that obtained from any other single region. However, combining them with profiles from the V1 region (with or without the profiles from the V3 region) resulted in the most accurate classification of the samples. The addition of profiles from the V 9 region appeared to confound the classifiers. Our results show that SVM and KNN classifiers can be effectively applied to distinguish between eubacterial community patterns from different ecosystems based only on their ALH profiles.     

Oxygen profiles in membranes

Transmembrane profiles of molecular oxygen in lipid bilayers are not only significant for membrane physiology and pathology, but also are essential to the determination of membrane protein structure by site-directed spin labeling. Oxygen profiles obtained with spin-labeled lipid chains have a Boltzmann sigmoidal dependence on the depth into each lipid leaflet, which represents a two-compartment distribution between outer and inner regions of the membrane, with a transfer free energy that depends linearly on distance from the dividing planes. Transmembrane profiles for intramembrane polarity, and for water penetration into the membrane, have an identical form, but are of the reverse sign. Comparison with recently published oxygen profiles from a site-specifically spin-labeled alpha-helical transmembrane peptide validates the use of spin-labeled lipids for all these profiles and provides the necessary bridge to generate the full bilayer from a single lipid leaflet.     

The organization of taste sensibilities in hamster chorda tympani nerve fibers

Electrophysiological measurements of nerve impulse frequencies were used to explore the organization of taste sensibilities in single fibers of the hamster chorda tympani nerve. Moderately intense taste solutions that are either very similar or easily discriminated were applied to the anterior lingual surface. 40 response profiles or 13 stimulus activation patterns were considered variables and examined with multivariate statistical techniques. Three kinds of response profiles were seen in fibers that varied in their overall sensitivity to taste solutions. One profile (S) showed selectivity for sweeteners, a second (N) showed selectivity for sodium salts, and a third (H) showed sensitivity to salts, acids, and other compounds. Hierarchical cluster analysis indicated that profiles fell into discrete classes. Responses to many pairs of effective stimuli were covariant across profiles within a class, but some acidic stimuli had more idiosyncratic effects. Factor analysis of profiles identified two common factors, accounting for 77% of the variance. A unipolar factor was identified with the N profile, and a bipolar factor was identified with the S profile and its opposite, the H profile. Three stimulus activation patterns were elicited by taste solutions that varied in intensity of effect. Hierarchical cluster analysis indicated that the patterns fell into discrete classes. Factor analysis of patterns identified three common unipolar factors accounting for 82% of the variance. Eight stimuli (MgSO4, NH4Cl, KCl, citric acid, acetic acid, urea, quinine HCl, HCl) selectively activated fibers with H profiles, three stimuli (fructose, Na saccharin, sucrose) selectively activated fibers with S profiles, and two stimuli (NaNO3, NaCl) activated fibers with N profiles more strongly than fibers with H profiles. Stimuli that evoke different patterns taste distinct to hamsters. Stimuli that evoke the same pattern taste more similar. It was concluded that the hundreds of peripheral taste neurons that innervate the anterior tongue play one of three functional roles, providing information about one of three features that are shared by different chemical solutions.     

Histochemical study of skeletal muscles of the frog, Rana temporaria

Histochemical profiles of muscles were identified based on staining for myosin ATPase activity. They reveal typical arrangement of muscular fibres with a zoned pattern. Tonic fibres have a unique histochemical profile and are mixed with the most oxydative fast fibres to form toxic zones. Muscles show fast profiles in thigh and tonic or mixed profiles in fore-arm.     

Comparative Analysis of Proteome and Transcriptome in Human Hepatocellular Carcinoma using 2D-DIGE and SAGE

Proteome analysis of human hepatocellular carcinoma was conducted using two-dimensional difference gel electrophoresis, and the protein expression profiles were compared to the mRNA expression profiles made from serial analysis of gene expression (SAGE) in identical samples from a single patient. Image-to-image analysis of protein abundances together with protein identification by peptide mass fingerprinting yielded the protein expression profiles. A total of 188 proteins were identified, and the expression profiles of 164 proteins which had the corresponding SAGE data were compared to the mRNA expression profiles. Among them, 40 proteins showed significant differences in the mRNA expression levels between non HCC and HCC. We compared expression changes of proteins with those of mRNAs. We found that the expression tendency of 24 proteins were similar to that of mRNA, whereas 16 proteins showed different or opposite tendency to the mRNA expression.     

Theoretical melting profiles and denaturation maps of DNA with known sequence: fdDNA.

Differential melting profiles and denaturation maps are calculated for fdDNA whose sequence of nucleotides has been determined recently. The melting profiles for the total DNA and a number of its restriction fragments are compared with experimental data taken from literature. The comparison enables one to correlate a number of peaks on experimental melting profiles with the melting out of concrete regions of the nucleotide sequence. For three fragments very strong end effects are demonstrated on both theoretical and experimental profiles. These anomalous end effects are shown to be connected with a region highly enriched with AT-pairs. A possible influence of the heterogeneity of stacking interaction on the results obtained is discussed in detail.