Rapid prediction of multi-dimensional NMR data sets

We present a computational environment for Fast Analysis of multidimensional NMR DAta Sets (FANDAS) that allows assembling multidimensional data sets from a variety of input parameters and facilitates comparing and modifying such ??in silico?? data sets during the various stages of the NMR data analysis. The input parameters can vary from (partial) NMR assignments directly obtained from experiments to values retrieved from in silico prediction programs. The resulting predicted data sets enable a rapid evaluation of sample labeling in light of spectral resolution and structural content, using standard NMR software such as Sparky. In addition, direct comparison to experimental data sets can be used to validate NMR assignments, distinguish different molecular components, refine structural models or other parameters derived from NMR data. The method is demonstrated in the context of solid-state NMR data obtained for the cyclic nucleotide binding domain of a bacterial cyclic nucleotide-gated channel and on membrane-embedded sensory rhodopsin II. FANDAS is freely available as web portal under WeNMR (http://www.wenmr.eu/services/FANDAS).     

Rapid initial clustering of large data sets

Summary Multivariate analysis of plant community data has three goals: summarization of redundancy, identification of outliers, and elueidation of relationships. The first two are handled conveniently by initial fast clustering, and the third by subsequent ordination and hierarchical clustering, and perhaps table arrangement.Initial clustering algorithms should achieve withincluster homogeneity and require minimal computer resources. However, algorithmic uniqueness and a hierarchy are not needed. Computing time should be proportional to the amount of data, with no higher dependencies on the number of samples. A method is presented here meeting these requirements, called composite clustering and implemented in a FORTRAN program called COMPCLUS. The computer time required for COMPCLUS clustering is on the order of the time required merely to read the data, regardless of the number of samples.Several large field data sets were analyzed effectively by using COMPCLUS to reduce redundancy and identify outliers, and then ordinating the resulting composite clusters by detrended correspondence analysis (DECORANA). Various clusterings of the same data set can be compared using a percent mutual matches (PMM) index, and a matrix of such values can be ordinated for simultaneous comparison of a number of clusterings.This paper benefited at many points from discussions with Mark O. Hill and Robert H. Whittaker. Mark Hill suggested condensed data storage. This work was done under a National Science Foundation grant to Robert Whittaker. I also appreciate technical assistance from Timothy F. Mason and Steven B. Singer.     

Discrimination and scoring using small sets of genes for two-sample microarray data

Comparison of gene expression for two groups of individuals form an important subclass of microarray experiments. We study multivariate procedures, in particular use of Hotelling's T2 for discrimination between the groups with a special emphasis on methods based on few genes only. We apply the methods to data from an experiment with a group of atopic dermatitis patients compared with a control group. We also compare our methodology to other recently proposed methods on publicly available datasets. It is found that (i) use of several genes gives a much improved discrimination of the groups as compared to one gene only, (ii) the genes that play the most important role in the multivariate analysis are not necessarily those that rank first in univariate comparisons of the groups, (iii) Linear Discriminant Analysis carried out with sets of 2-5 genes selected according to their Hotelling T2 give results comparable to state-of-the-art methods using many more genes, a feature of our method which might be crucial in clinical applications. Finding groups of genes that together give optimal multivariate discrimination (given the size of the group) can identify crucial pathways and networks of genes responsible for a disease. The computer code that we developed to make computations is available as an R package.     

Rapid infant weight gain predicts childhood overweight

Objective : To determine among a contemporary cohort whether rapid weight gain between birth and 6 months is associated with risk of childhood overweight and if this risk differs by ethnicity and/or breast‐feeding history. Research Methods and Procedures : This was a cross‐sectional survey in 1999 to 2000 of parents/guardians of children participating in the Special Supplemental Nutrition Program for Women, Infants, and Children in New York State. Measurements were abstracted by chart review, including weight at birth and 6 months, and height and weight at time of survey and every 6 months subsequently. Overweight at 4 years of age was defined as a BMI ≥ 95th age‐ and sex‐specific percentiles. Results : The study sample was 32% Hispanic, 19% black, and 49% white; 17% of children were overweight. Rate of infant weight gain (expressed in terms of 100 g/mo) was significantly associated with being overweight at 4 years (odds ratio, 1.4; 95% confidence interval, 1.3 to 1.6 after adjusting for history of breast‐feeding, birth weight, and ethnicity). The odds of being overweight at 4 years of age for Hispanic children were twice those of non‐Hispanic children (odds ratio, 2.2; 95% confidence interval, 1.5 to 3.3). The population‐attributable risk of overweight at 4 years of age was 19% for children in the highest quintile of infant weight gain. Discussion : Among this contemporary, multi‐ethnic cohort, rapid infant weight gain was associated with increased risk of being overweight at 4 years of age, independently of potential confounders. Identification of the risk factors contributing to rapid weight gain during infancy might improve early recognition and guide strategies for optimal nutrition to prevent the development of childhood overweight.     

Relation between weight matrix and substitution matrix: motif search by similarity

MOTIVATION: The discovery of patterns shared by several sequences that differ greatly is a basic task in sequence analysis, and still a challenge. Several methods have been developed for detecting patterns. Methods commonly used for motif search include the Gibbs sampler, Expectation-Maximization (EM) algorithm and some intuitive greedy approaches. One cannot guarantee the optimality of the result produced by the Gibbs sampler in a single run. The deterministic EM methods tend to get trapped by local optima. Solutions found by greedy approaches are rarely sufficiently good. RESULTS: A simple model describing a motif or a portion of local multiple sequence alignment is the weight matrix model, in which a motif is characterized with position-specific probabilities. Two substitution matrices are proposed to relate the sequence similarity with the weight matrix. Combining the substitution matrix and weight matrix, we examine three typical sets of protein sequences with increasing complexity. At a low score threshold for pair similarity, sliding windows are compared with a seed window to find the score sum, which provides a measure of statistical significance for multiple sequence comparison. Such a similarity analysis reveals many aspects of motifs. Blocks determined by similarity can be used to deduce a primary weight matrix or an improved substitution matrix. The algorithm successfully obtains the optimal solution for the test sets by just greedy iteration.     

Three sets of weight training superior to 1 set with equal intensity for eliciting strength

The purpose of this study was to compare single and multiple sets of weight training for strength gains in recreationally trained individuals. Sixteen men (age = 21 +/- 2.0) were randomly assigned to 1 set (S-1; n = 8) or 3 set (S-3; n = 8) groups and trained 3 days per week for 12 weeks. One repetition maximum (1RM) was recorded for bench press and leg press at pre-, mid-, and posttest. Subjects trained according to daily undulating periodization (DUP), involving the bench press and leg press exercises between 4RM and 8RM. Training intensity was equated for both groups. Analysis of variance with repeated measures revealed statistically significant differences favoring S-3 in the leg press (p < 0.05, effect size [ES] = 6.5) and differences approaching significance in the bench press (p = 0.07, ES = 2.3). The results demonstrate that for recreationally trained individuals using DUP training, 3 sets of training are superior to 1 set for eliciting maximal strength gains.     

Trendtests with adaptive scoring

The concept of adaptive two‐stage designs is applied to the problem of testing the equality of several normal means against an ordered (monotone) alternative. The likelihood‐ratio‐test proposed by Bartholomew is known to have favorable power properties when testing against a monotonic trend. Tests based on contrasts provide a flexible way to incorporate available information regarding the pattern of the unknown true means through appropriate specification of the scores. The basic idea of the presented concept is the combination of Bartholomew 's test (first stage) with an “adaptive score test” (second stage) which utilizes the information resulting from isotonic regression estimation at the first stage. In a Monte Carlo simulation study the adaptive scoring procedure is compared to the non‐adaptive two‐stage procedure using the Bartholomew test at both stages. We found that adaptive scoring may improve the power of the two stage design, in particular if the sample size at the first stage is considerably larger than at the second stage.     

A gating motif in the translocation channel sets the hydrophobicity threshold for signal sequence function

A critical event in protein translocation across the endoplasmic reticulum is the structural transition between the closed and open conformations of Sec61, the eukaryotic translocation channel. Channel opening allows signal sequence insertion into a gap between the N- and C-terminal halves of Sec61. We have identified a gating motif that regulates the transition between the closed and open channel conformations. Polar amino acid substitutions in the gating motif cause a gain-of-function phenotype that permits translocation of precursors with marginally hydrophobic signal sequences. In contrast, hydrophobic substitutions at certain residues in the gating motif cause a protein translocation defect. We conclude that the gating motif establishes the hydrophobicity threshold for functional insertion of a signal sequence into the Sec61 complex, thereby allowing the wild-type translocation channel to discriminate between authentic signal sequences and the less hydrophobic amino acid segments in cytosolic proteins. Bioinformatic analysis indicates that the gating motif is conserved between eubacterial and archaebacterial SecY and eukaryotic Sec61.     

Rapid identification of malaria vaccine candidates based on alpha-helical coiled coil protein motif

To identify malaria antigens for vaccine development, we selected alpha-helical coiled coil domains of proteins predicted to be present in the parasite erythrocytic stage. The corresponding synthetic peptides are expected to mimic structurally "native" epitopes. Indeed the 95 chemically synthesized peptides were all specifically recognized by human immune sera, though at various prevalence. Peptide specific antibodies were obtained both by affinity-purification from malaria immune sera and by immunization of mice. These antibodies did not show significant cross reactions, i.e., they were specific for the original peptide, reacted with native parasite proteins in infected erythrocytes and several were active in inhibiting in vitro parasite growth. Circular dichroism studies indicated that the selected peptides assumed partial or high alpha-helical content. Thus, we demonstrate that the bioinformatics/chemical synthesis approach described here can lead to the rapid identification of molecules which target biologically active antibodies, thus identifying suitable vaccine candidates. This strategy can be, in principle, extended to vaccine discovery in a wide range of other pathogens.     

Rapid and accurate prediction and scoring of water molecules in protein binding sites

Water plays a critical role in ligand-protein interactions. However, it is still challenging to predict accurately not only where water molecules prefer to bind, but also which of those water molecules might be displaceable. The latter is often seen as a route to optimizing affinity of potential drug candidates. Using a protocol we call WaterDock, we show that the freely available AutoDock Vina tool can be used to predict accurately the binding sites of water molecules. WaterDock was validated using data from X-ray crystallography, neutron diffraction and molecular dynamics simulations and correctly predicted 97% of the water molecules in the test set. In addition, we combined data-mining, heuristic and machine learning techniques to develop probabilistic water molecule classifiers. When applied to WaterDock predictions in the Astex Diverse Set of protein ligand complexes, we could identify whether a water molecule was conserved or displaced to an accuracy of 75%. A second model predicted whether water molecules were displaced by polar groups or by non-polar groups to an accuracy of 80%. These results should prove useful for anyone wishing to undertake rational design of new compounds where the displacement of water molecules is being considered as a route to improved affinity.     

Rapid isolation of high molecular weight plant DNA.

A method is presented for the rapid isolation of high molecular weight plant DNA (50,000 base pairs or more in length) which is free of contaminants which interfere with complete digestion by restriction endonucleases. The procedure yields total cellular DNA (i.e. nuclear, chloroplast, and mitochondrial DNA). The technique is ideal for the rapid isolation of small amounts of DNA from many different species and is also useful for large scale isolations.     

Rapid changes in weight and growth potential during childhood

The close resemblance between the skin of Goeldi's marmoset (Callimico goeldii) and that of the genus Saguinus (Hoffmannsegg) suggests that C. goeldii be placed in the family Callithricidae (Thomas, '03) as originally proposed by Pocock in 1920 and not in the family Cebidae (Swainson, 1835). Recent karyological evidence supports this point of view. The skin is characterized by (1) a melanin-laden epidermis and aggregates of melanocytes in the upper dermis; (2) nonglandular skin in the gular region distinguished by a sparsely haired, pebbly, granular surface; (3) cholinesterase-positive Meissner corpuscles and papillary nerve end-organs; (4) groups of 3 to 5 hair follicles in linear perfect sets; (5) sinus hairs on the ventral ulnar wrist; (6) manubrial, sternal, genitopubic, and circumanal sebaceous-apocrine glandular concentrations rich in phosphorylase and alkaline phosphatase; (7) eccrine glands, restricted to volar friction surfaces, whose clear and dark secretory cells contain phosphorylase but no glycogen; and (8) eccrine glomeruli surrounded by many acetyl- but few butyrylcholinesterase-reactive nerves.     

How well do multivariate data sets match? The advantages of a Procrustean superimposition approach over the Mantel test

The Mantel test provides a means to test the association between distance matrices and has been widely used in ecological and evolutionary studies. Recently, another permutation test based on a Procrustes statistic (PROTEST) was developed to compare multivariate data sets. Our study contrasts the effectiveness, in terms of power and type I error rates, of the Mantel test and PROTEST. We illustrate the application of Procrustes superimposition to visually examine the concordance of observations for each dimension separately and how to conduct hypothesis testing in which the association between two data sets is tested while controlling for the variation related to other sources of data. Our simulation results show that PROTEST is as powerful or more powerful than the Mantel test for detecting matrix association under a variety of possible scenarios. As a result of the increased power of PROTEST and the ability to assess the match for individual observations (not available with the Mantel test), biologists now have an additional and powerful analytical tool to study ecological and evolutionary relationships.     

A novel microtubule-binding motif identified in a high molecular weight microtubule-associated protein from Trypanosoma brucei

The major component of the cytoskeleton of the parasitic hemoflagellate Trypanosoma brucei is a membrane skeleton which consists of a single layer of tightly spaced microtubules. This array encloses the entire cell body, and it is apposed to, and connected with, the overlying cell membrane. The microtubules of this array contain numerous microtubule-associated proteins. Prominent among those is a family of high molecular weight, repetitive proteins which consist to a large extent of tandemly arranged 38-amino acid repeat units. The binding of one of these proteins, MARP-1, to microtubules has now been characterized in vitro and in vivo. MARP-1 binds to microtubules via tubulin domains other than the COOH-termini used by microtubule-associated proteins from mammalian brain, e.g., MAP2 or Tau. In vitro binding assays using recombinant protein, as well as transfection of mammalian cell lines, have established that the repetitive 38-amino acid repeat units represent a novel microtubule-binding motif. This motif is very similar in length to those of the mammalian microtubule-associated proteins Tau, MAP2, and MAP-U, but both its sequence and charge are different. The observation that the microtubule-binding motifs both of the neural and the trypanosomal proteins are of similar length may reflect the fact that both mediate binding to the same repetitive surface, the microtubule, while their sequence and charge differences are in agreement with the observation that they interact with different domains of the tubulins.     

Protein motif extraction with neuro-fuzzy optimization

MOTIVATION: It is attempted to improve the speed and flexibility of protein motif identification. The proposed algorithm is able to extract both rigid and flexible protein motifs. RESULTS: In this work, we present a new algorithm for extracting the consensus pattern, or motif, from a group of related protein sequences. This algorithm involves a statistical method to find short patterns with high frequency and then neural network training to optimize the final classification accuracies. Fuzzy logic is used to increase the flexibility of protein motifs. C2H2 Zinc Finger Protein and epidermal growth factor protein sequences are used to demonstrate the capability of the proposed algorithm in finding motifs. AVAILABILITY: This program is freely available for academic use by request.