Annotation of bacterial genomes using improved phylogenomic profiles

MOTIVATION: Phylogenomic profiling is a large-scale comparative genomic method used to infer protein function from evolutionary information first described in a binary form by Pellegrini et al. (1999). Here, we propose improvements of this approach including the use of normalized Blastp bit scores, a normalization of the matrix of profiles to take into account the evolutionary distances between bacteria, the definition of a phylogenomic neighborhood based on continuous pairwise distances between genes and an original annotation procedure including the computation of a p-value for each functional assignment. RESULTS: The method presented here increases the number of Ecocyc enzymes identified as being evolutionarily related by about 25% with respect to the original binary form (absent/present) method. The fraction of 'false' positives is shown to be smaller than 20%. Based on their phylogenomic relationships, genes of unknown function can then be automatically related to annotated genes. Each gene annotation predicted is associated with a p-value, i.e. its probability to be obtained by chance. The validity of this method was extensively tested on a large set of genes of known function using the MultiFun database. We find that 50% of 3122 function attributions that can be made at a p-value level of 10(-11) correspond to the actual gene annotation. The method can be readily applied to any newly sequenced microbial genome. In contrast to earlier work on the same topic, our approach avoids the use of arbitrary cut-off values, and provides a reliability estimate of the functional predictions in form of p-values.     

Computing tertiary structures of proteins

Using only data on sequence, a method of computing a low-resolution tertiary structure of a protein is described. The steps are: (a) Estimate the distances of individual residues from the centroid of the molecule, using data on hydrophobicity and additional geometrical constraints. (b) Using these distances, construct a two-valued matrix whose elements, the distances between residues, are greater or less thanR, the radius of the molecule. (c) Optimize to obtain a three-dimensional structure. This procedure requires modest computing facilities and is applicable to proteins with 164 residues and presumably more. It produces structures withr (correlation between inter-residue distances in the computed and native structures) between 0.5 and 0.7. Furthermore, correct inference of two or three long-range contacts suffices to yield structures withr values of 0.8–0.9. Because segments forming parallel or antiparallel folding structures intersect the radius vector at similar angles, from centroidal point distances it is possible to infer some of these long-range contacts by an elaboration of the procedure used to construct the input matrix. A criterion is also described which can be used to determine the quality of a proposed input matrix even when the native structure is not known.     

Computer-assisted pattern recognition model for the identification of slowly growing mycobacteria including Mycobacterium tuberculosis.

We present a computerized pattern recognition model used to speciate mycobacteria based on their restriction fragment length polymorphism (RFLP) banding patterns. DNA fragment migration distances were normalized to minimize lane-to-lane variability of band location both within and among gels through the inclusion of two internal size standards in each sample. The computer model used a library of normalized RFLP patterns derived from samples of known origin to create a probability matrix which was then used to classify the RFLP patterns from samples of unknown origin. The probability matrix contained the proportion of bands that fell within defined migration distance windows for each species in the library of reference samples. These proportions were then used to compute the likelihood that the banding pattern of an unknown sample corresponded to that of each species represented in the probability matrix. As a test of this process, we developed an automated, computer-assisted model for the identification of Mycobacterium species based on their normalized RFLP banding patterns. The probability matrix contained values for the M. tuberculosis complex, M. avium, M. intracellulare, M. kansasii and M. gordonae species. Thirty-nine independent strains of known origin, not included in the probability matrix, were used to test the accuracy of the method in classifying unknowns: 37 of 39 (94.9%) were classified correctly. An additional set of 16 strains of known origin representing species not included in the model were tested to gauge the robustness of the probability matrix. Every sample was correctly identified as an outlier, i.e. a member of a species not included in the original matrix.(ABSTRACT TRUNCATED AT 250 WORDS)     

Determination of Effective Transport Coefficients for Bacterial Migration in Sand Columns

A well-characterized experimental system was designed to evaluate the effect of porous media on macroscopic transport coefficients which are used to characterize the migration of bacterial populations. Bacterial density profiles of Pseudomonas putida PRS2000 were determined in the presence and absence of a chemical attractant (3-chlorobenzoate) gradient within sand columns having a narrow distribution of particle diameters. These experimental profiles were compared with theoretical predictions to evaluate the macroscopic transport coefficients. The effective random motility coefficient, used to quantify migration due to a random process in a porous medium, decreased nearly 20-fold as grain size in the columns decreased from 800 to 80 (mu)m. The effective random motility coefficient (mu)(infeff) was related to the random motility coefficient (mu), measured in a bulk aqueous system, according to (mu)(infeff) = ((epsilon)/(tau))(mu) with porosity (epsilon) and tortuosity (tau). Over the times and distances examined in these experiments, bacterial density profiles were unaffected by the presence of an attractant gradient. Theoretical profiles with the aqueous phase value of the chemotactic sensitivity coefficient (used to quantify migration due to a directed process) were consistent with this result and suggested that any chemotactic effect on bacterial migration was below the detection limits of our assay.     

Genetic variation and distances of five Italian native sheep breeds

Genetic distances among five of the most important Italian native sheep breeds were estimated by using gene frequencies of four blood group and seven blood protein loci and by three different computing methods. The values of the three distance matrices were highly correlated. Genetic distances were found within the range values reported in the literature for local breeds. Shorter distances fitted the historical evidence of migrations.     

Label-free kinase profiling using phosphate affinity polyacrylamide gel electrophoresis

Herein we describe three applications of label-free kinase profiling using a novel type of phosphate affinity polyacrylamide gel electrophoresis. The phosphate affinity site is a polyacrylamide-bound dinuclear Mn2+ complex that enables the mobility shift detection of phosphorylated proteins from their nonphosphorylated counterpart. The first application is in vitro kinase activity profiling for the analysis of varied phosphoprotein isotypes in phosphorylation status. The activity profiles of six kinds of kinases, glycogen synthase kinase-3beta, cyclin-dependent kinase 5/p35, protein kinase A, mitogen-activated protein kinase (MAPK), casein kinase II, and calmodulin-dependent protein kinase II, were determined using a substrate protein, Tau, which has a number of phosphorylation sites. Each kinase demonstrated characteristic multiple electrophoresis migration bands up-shifted from the nonphosphorylated Tau due to differences in the phosphorylation sites and stoichiometry. The second application is in vivo kinase activity profiling for the analysis of protein phosphorylation involved in intracellular signal transduction. The time course changes in the epidermal growth factor-induced phosphorylation levels of Shc and MAPK in A431 cells were visualized as highly up-shifted migration bands by subsequent immunoblotting with anti-Shc and anti-MAPK antibodies. The third application is in vitro kinase inhibition profiling for the quantitative screening of kinase-specific inhibitors. The inhibition profile of a tyrosine kinase, Abl (a histidine-tagged recombinant mouse Abl kinase), was determined using the substrate Abltide-GST (a fusion protein consisting of a specific substrate peptide for Abl and glutathione S-transferase) and the approved drug Glivec (an ATP competitor). In the kinase assay, the slower migration band, monophosphorylated Abltide-GST, increased time-dependently, whereas the faster migration band, nonphosphorylated Abltide-GST, decreased. The dose-dependent inhibition of Glivec was determined by a change in the ratio of the faster and slower migration bands, which showed an IC50 value of 1.6 microM in the presence of 0.10 mM ATP.     

Calcium-induced associations of the caseins: a thermodynamic linkage approach to precipitation and resolubilization

Calcium-induced changes in protein solubility play a role in a variety of important biological processes including the deposition of bone and dentin and the secretion of milk. The phenomena of salt-induced (calcium) precipitation of proteins (salting-out), and the resolubilization of these proteins at higher salt concentrations (salting-in) have been studied and quantitated using an approach based on the concepts of Wyman's thermodynamic linkage. Salting-out has been described by a salt-binding constant, k1, the number of moles of salt bound per mole of protein, n, and S1, the fraction soluble at saturation of n; salting-in has been described by corresponding constants k2, m, and S2. Analysis of salt-induced solubility profiles was performed using nonlinear regression analysis. Results of calcium-induced solubility profiles of two genetic variants of alpha s1-casein (alpha s1-A), (alpha s1-B), and beta-casein C (beta-C) at 37 degrees C, where hydrophobic interactions are maximized, showed no salting-in behavior and for salting-out, yielded k1 values of 157, 186, and 156 liters.mol-1 and n values of 8, 8, and 4, respectively. The values of k1 can be correlated with the apparent association constant for calcium binding to casein, while the values of n can be correlated with the number of calcium binding sites of the respective caseins. At 1 degree C, where hydrophobic interactions are minimized, nominally only hydrophilic and electrostatic interactions can be linked to the salt-induced solubility profiles; here beta-C is totally soluble at all calcium concentrations and alpha s1-B and alpha s1-A were now found to have salting-in parameters, k2 and m, of 2.5 liters.mol-1 and 4, and 11 liters.mol-1 and 8, respectively. alpha s1-A is more readily salted-in and studies on the variation of S1 with added KCl for this protein at 1 degree C indicated that salting-in is also mainly electrostatic in nature and may result from competition between K+ and Ca2+ for binding sites rather than from solute-solvent interactions as previously proposed. Comparison of k1 and k2 values between the two genetic variants, coupled with the known sequence differences (the A variant is a linear deletion of 13 amino acids) suggest the existence of a hydrophobically stabilized ion pair in alpha s1-B which is deleted in alpha s1-A; it is speculated that such bonds may play a role in other calcium-induced changes in protein solubility.     

Determination of the molecular weight of DNA-bound protein(s) responsible for gel electrophoretic mobility shift of linear DNA fragments examplified with purified viral myb protein.

A protein-DNA complex has less gel electrophoretic mobility than the free DNA fragment. One parameter for the degree of retardation of a linear DNA fragment in a protein-DNA complex is the molecular weight of the bound protein(s). The quotient of the migration distances of free DNA (m) and protein-DNA complex (m') is a function of the molecular weight (MW) of the bound protein(s). Based on the evaluation of the lac repressor induced mobility shift of a 203 bp DNA fragment containing the lac operator in a 5% non-denaturating polyacrylamide gel a direct proportionality could be shown between (m/m'-1) and MW with the proportionality factor K = 215 kDa. The factor K depends on the acrylamide concentration in the gel, getting lower values with increasing acrylamide concentrations. A calculation is given to determine the molecular weight of DNA-binding factors responsible for the decreased electrophoretic mobility of a linear DNA fragment. As an example this calculation was used in order to analyse DNA-binding of the isolated viral myb protein. It could be demonstrated that the viral myb protein binds to DNA as a monomer and as a dimer.     

An improved profile-level domain linker propensity index for protein domain boundary prediction

Protein domain boundary prediction is critical for understanding protein structure and function. In this study, we present a novel method, an order profile domain linker propensity index (OPI), which uses the evolutionary information extracted from the protein sequence frequency profiles calculated from the multiple sequence alignments. A protein sequence is first converted into smooth and normalized numeric order profiles by OPI, from which the domain linkers can be predicted. By discriminating the different frequencies of the amino acids in the protein sequence frequency profiles, OPI clearly shows better performance than our previous method, a binary profile domain linker propensity index (PDLI). We tested our new method on two different datasets, SCOP-1 dataset and SCOP-2 dataset, and we were able to achieve a precision of 0.82 and 0.91 respectively. OPI also outperforms other residue-level, profile-level indexes as well as other state-of-the-art methods.     

Toward the complete characterization of host cell proteins in biotherapeutics via affinity depletions,LC-MS/MS,and multivariate analysis

Host cell protein (HCP) impurities are generated by the host organism during the production of therapeutic recombinant proteins, and are difficult to remove completely. Though commonly present in small quantities, if levels are not controlled, HCPs can potentially reduce drug efficacy and cause adverse patient reactions. A high resolution approach for thorough HCP characterization of therapeutic monoclonal antibodies is presented herein. In this method, antibody samples are first depleted via affinity enrichment (e.g., Protein A, Protein L) using milligram quantities of material. The HCP-containing flow-through is then enzymatically digested, analyzed using nano-UPLC-MS/MS, and proteins are identified through database searching. Nearly 700 HCPs were identified from samples with very low total HCP levels (< 1 ppm to ～10 ppm) using this method. Quantitation of individual HCPs was performed using normalized spectral counting as the number of peptide spectrum matches (PSMs) per protein is proportional to protein abundance. Multivariate analysis tools were utilized to assess similarities between HCP profiles by: 1) quantifying overlaps between HCP identities; and 2) comparing correlations between individual protein abundances as calculated by spectral counts. Clustering analysis using these measures of dissimilarity between HCP profiles enabled high resolution differentiation of commercial grade monoclonal antibody samples generated from different cell lines, cell culture, and purification processes.     

Simple luminosity normalization of greenness, yellowness and redness/greenness for comparison of leaf spectral profiles in multi-temporally acquired remote sensing images

Observation of leaf colour (spectral profiles) through remote sensing is an effective method of identifying the spatial distribution patterns of abnormalities in leaf colour, which enables appropriate plant management measures to be taken. However, because the brightness of remote sensing images varies with acquisition time, in the observation of leaf spectral profiles in multi-temporally acquired remote sensing images, changes in brightness must be taken into account. This study identified a simple luminosity normalization technique that enables leaf colours to be compared in remote sensing images over time. The intensity values of green and yellow (green+red) exhibited strong linear relationships with luminosity (R2 greater than 0.926) when various invariant rooftops in Bangkok or Tokyo were spectralprofiled using remote sensing images acquired at different time points. The values of the coefficient and constant or the coefficient of the formulae describing the intensity of green or yellow were comparable among the single Bangkok site and the two Tokyo sites, indicating the technique's general applicability. For single rooftops, the values of the coefficient of variation for green, yellow, and red/green were 16% or less (n=6-11), indicating an accuracy not less than those of well-established remote sensing measures such as the normalized difference vegetation index. After obtaining the above linear relationships, raw intensity values were normalized and a temporal comparison of the spectral profiles of the canopies of evergreen and deciduous tree species in Tokyo was made to highlight the changes in the canopies' spectral profiles. Future aspects of this technique are discussed herein.     

Inferring landscape resistance to gene flow when genetic drift is spatially heterogeneous

In connectivity models, land cover types are assigned cost values characterizing their resistance to species movements. Landscape genetic methods infer these values from the relationship between genetic differentiation and cost distances. The spatial heterogeneity of population sizes, and consequently genetic drift, is rarely included in this inference although it influences genetic differentiation. Similarly, migration rates and population spatial distributions potentially influence this inference. Here, we assessed the reliability of cost value inference under several migration rates, population spatial patterns and degrees of population size heterogeneity. Additionally, we assessed whether considering intra-population variables, here using gravity models, improved the inference when drift is spatially heterogeneous. We simulated several gene flow intensities between populations with varying local sizes and spatial distributions. We then fit gravity models of genetic distances as a function of (i) the ‘true’ cost distances driving simulations or alternative cost distances, and (ii) intra-population variables (population sizes, patch areas). We determined the conditions making the identification of the ‘true’ costs possible and assessed the contribution of intra-population variables to this objective. Overall, the inference ranked cost scenarios reliably in terms of similarity with the ‘true’ scenario (cost distance Mantel correlations), but this ‘true’ scenario rarely provided the best model goodness of fit. Ranking inaccuracies and failures to identify the ‘true’ scenario were more pronounced when migration was very restricted (<4 dispersal events/generation), population sizes were most heterogeneous and some populations were spatially aggregated. In these situations, considering intra-population variables helps identify cost scenarios reliably, thereby improving cost value inference from genetic data.     

Two-level heterogenous energy migration. Modeling and application to purple bacteria

The dynamics of migration of electronic excitations and the efficiency of their trapping in two-dimensional ensembles of molecules were analyzed. Molecules were characterized using the following parameters: the width of long-wavelength bands, the values of extinction and rate constant of deactivation of electronic excitations, critical distances of migration close to those of dye molecules, in particular, bacteriochlorophyll a and purple bacteria. A comparative analysis of two-dimensional models of energy migration made it possible to chose a model with an optimum light-harvesting on traps from the largest numbers of light-absorbing molecules. It was shown that in ensembles of molecules having different spectral characteristics (spectral shifts between the short- and long-wavelength fractions of the molecules are hear 800 cm-1) the efficiency of excitation trapping is approximately 90 and 80% for the number of light-harvesting molecules per one trap 210 and 580, respectively.     

Measurement of Mandibular Growth Using Cone-Beam Computed Tomography: A Miniature Pig Model Study

The purpose of this study was to measure the long-term growth of the mandible in miniature pigs using 3D Cone-Beam Computerized Tomography (CBCT). The mandibles of the pigs were scanned monthly over 12 months using CBCT and the 3D mandibular models were reconstructed from the data. Seventeen anatomical landmarks were identified and classified into four groups of line segments, namely anteroposterior, superoinferior, mediolateral and anteroinferior. The inter-marker distances, inter-segmental angles, volume, monthly distance changes and percentage of changes were calculated to describe mandibular growth. The total changes of inter-marker distances were normalized to the initial values. All inter-marker distances increased over time, with the greatest mean normalized total changes in the superoinferior and anteroposterior groups (p<0.05). Monthly distance changes were greatest during the first four months and then reduced over time. Percentages of inter-marker distance changes were similar among the groups, reaching half of the overall growth around the 4^th month. The mandibular volume growth increased non-linearly with time, accelerating during the first five months and slowing during the remaining months. The growth of the mandible was found to be anisotropic and non-homogeneous within the bone and non-linear over time, with faster growth in the ramus than in the body. These growth patterns appeared to be related to the development of the dentition, providing necessary space for the teeth to grow upward for occlusion and for the posterior teeth to erupt.     

Toward the complete characterization of host cell proteins in biotherapeutics via affinity depletions,LC-MS/MS,and multivariate analysis

Host cell protein (HCP) impurities are generated by the host organism during the production of therapeutic recombinant proteins, and are difficult to remove completely. Though commonly present in small quantities, if levels are not controlled, HCPs can potentially reduce drug efficacy and cause adverse patient reactions. A high resolution approach for thorough HCP characterization of therapeutic monoclonal antibodies is presented herein. In this method, antibody samples are first depleted via affinity enrichment (e.g., Protein A, Protein L) using milligram quantities of material. The HCP-containing flow-through is then enzymatically digested, analyzed using nano-UPLC-MS/MS, and proteins are identified through database searching. Nearly 700 HCPs were identified from samples with very low total HCP levels (< 1 ppm to ∼10 ppm) using this method. Quantitation of individual HCPs was performed using normalized spectral counting as the number of peptide spectrum matches (PSMs) per protein is proportional to protein abundance. Multivariate analysis tools were utilized to assess similarities between HCP profiles by: 1) quantifying overlaps between HCP identities; and 2) comparing correlations between individual protein abundances as calculated by spectral counts. Clustering analysis using these measures of dissimilarity between HCP profiles enabled high resolution differentiation of commercial grade monoclonal antibody samples generated from different cell lines, cell culture, and purification processes.     

Differentiation of Staphylococcal and Micrococcal Proteinases by Electrophoresis

The electrophoretic separation of the proteinases produced by staphylococci and micrococci was studied in four buffers. The duration of electrophoresis was based on the migration of a marker dye for a predetermined distance. The migration distances of the enzymes and dye were measured, and enzyme-dye values were calculated. A comparison of enzyme-dye values showed that complete separation of eight serologically different proteinases did not occur in any one buffer; however, in most instances, their relative order of migration was the same in all buffers. Certain strains of Staphylococcus epidermidis produced two proteinases that were different serologically as well as electrophoretically. Staphylococcus aureus strains, on the other hand, produced up to four proteinases that were serologically the same. The proteinases of staphylococci and micrococci can be best characterized by both electrophoretic and serological methods.     

Separation of histones from Physarum polycephalum by ion-paired, reverse-phase high-performance liquid chromatography

A rapid, one-step method for the efficient purification of murine monoclonal antibodies from tissue culture supernatants is described. This process is based on affinity chromatography on protein A-Sepharose columns. It was found that murine monoclonal antibodies raised against tick-borne encephalitis virus frequently eluted at more than one pH value and these pH values did not always correspond to those of antibodies of the same subclass from polyclonal mouse sera. The two populations of antibody molecule eluting at different pH values showed no variation in molecular weight, isoelectric profiles, specific enzyme-linked immunosorbent assay titer, or antibody subclass.     

Population structure in the Connecticut Valley: II. A comparison of multidimensional scaling solutions of migration matrices and isonymy

In a previous paper (Swedlund et al., 1984) we have described the population structure of the historical Connecticut River Valley of Massachusetts in terms of matrimonial migration matrices. Using procedures described by Morton (1973), Harpending and Jenkins (1974), Jorde (1980), and others the exchanges between subdivisions which make up the matrices are made column stochastic and analyzed to predict genetic kinship. Subsequently the kinship estimates within and between subdivisions can be interpreted as genetic covariance and compared to the actual geographic distances between the respective subdivisions using a principal components analysis. In the present paper we extend these results by applying nonmetric multidimensional scaling to the migration matrices, and to isonymy matrices based on the same communities. We demonstrate that the multidimensional scaling configurations of marital migration represent the actual geographic relationships between the communities quite effectively for this particular case study from historical Massachusetts. Moreover, we argue that while these migration data may provide good estimates of social and genetic exchange between the subdivisions, surname analysis may also be informative of processes not revealed in the migration matrices alone.