Substrate Binding Tunes Conformational Flexibility and Kinetic Stability of an Amino Acid Antiporter

We used single molecule dynamic force spectroscopy to unfold individual serine/threonine antiporters SteT from Bacillus subtilis. The unfolding force patterns revealed interactions and energy barriers that stabilized structural segments of SteT. Substrate binding did not establish strong localized interactions but appeared to be facilitated by the formation of weak interactions with several structural segments. Upon substrate binding, all energy barriers of the antiporter changed thereby describing the transition from brittle mechanical properties of SteT in the unbound state to structurally flexible conformations in the substrate-bound state. The lifetime of the unbound state was much shorter than that of the substrate-bound state. This leads to the conclusion that the unbound state of SteT shows a reduced conformational flexibility to facilitate specific substrate binding and a reduced kinetic stability to enable rapid switching to the bound state. In contrast, the bound state of SteT showed an increased conformational flexibility and kinetic stability such as required to enable transport of substrate across the cell membrane. This result supports the working model of antiporters in which alternate substrate access from one to the other membrane surface occurs in the substrate-bound state.The amino acid/polyamine/organocation (APC)² superfamily comprises about 250 members that occur in all phyla from prokaryotes to higher eukaryotes. These membrane proteins function as solute/cation symporters or solute/solute antiporters (1). One APC subfamily is established by l-amino acid transporters (LATs), which correspond to the light subunits of eukaryotic heteromeric amino acid transporters (2, 3). Heteromeric amino acid transporters are composed of a light subunit that provides transport activity and a disulfide-linked heavy subunit that shows responsibility for plasma membrane targeting. Genetic defects in light and heavy subunits cause a number of inherited human diseases. Mutations in the light as well as the heavy subunit of system b^0,+ lead to cystinuria (4, 5), whereas mutations in the light subunit y⁺LAT1 cause lysinuric protein intolerance (6, 7). Another light subunit, xCT that mediates cysteine uptake and glutamate efflux (8, 9), is involved in vivo in cocaine relapse (10) and maintenance of the plasma redox balance (11). LAT1, the light subunit of system L, is overexpressed in certain primary human tumors. It transports essential neutral amino acids with long, branched, or aromatic side chains required by tumor cells to support their unabated growth (12). Therefore, amino acid transporters like LAT1 are attractive anticancer drug targets.So far a high resolution structure of a eukaryotic LAT family member is not available. However, studies on xCT revealed a membrane topology of 12 transmembrane helices (TMHs) with cytosolic N and C termini and a re-entrant loop structure between TMHs II and III (13). The identified first prokaryotic member of the LAT family, SteT from Bacillus subtilis, is a serine/threonine antiporter, which shows high sequence identity (∼30%) to the light subunits of eukaryotic heteromeric amino acid transporters. Moreover SteT exhibits a similar putative membrane topology and sequential mode of obligate exchange (14). Thus, SteT is an excellent model for studying the structure-function relationship of LAT family members.According to current models, transport proteins undergo functionally related conformational changes. Transporters alternate between two conformations to expose their binding sites to the cytoplasmic and extracellular side (15–22). However, prior to conformational changes substrates have to be recognized and bound. If substrates are amino acids, three main features can be used for specific selection and binding: (i) the negatively charged α-carboxyl group, (ii) the positively charged α-amino group, and (iii) the electrostatic, hydrophobic, or spatial properties of the side chain (22–24). α-Carboxyl and α- amino groups of l-amino acids possess similar structural and chemical characteristics (except for proline); however, their side chains differ in shape, size, and electrostatic properties. Combinations of these features are assumed to establish different interactions within the side chain binding pocket, which determines the substrate specificity of the transporter. The two main substrates of SteT, l-serine and l-threonine, differ by only one methylene group in their side chain; thus they have similar properties. Additionally SteT transports aromatic l-amino acids (Trp, Tyr, and Phe) albeit less efficiently (14).Since its invention, the atomic force microscope (AFM) (25) has evolved from a surface imaging device to a versatile tool for studying interactions of manifold biological systems (26–31). Introduced to characterize interactions between receptor-ligand complexes (32, 33) and complementary DNA strands (34), AFM-based single molecule force spectroscopy (SMFS) has been exploited to explore antibody-antigen recognition (35) and unfolding and refolding of soluble proteins (29, 36) and to probe the adhesion of living cells at molecular resolution (37). Applied to membrane proteins, SMFS uses the AFM stylus to exert a mechanical pulling force to the terminal end of a protein that is embedded and anchored by the lipid membrane (see Fig. 1A) (38). Sufficiently high stretching forces initiate sequential unfolding of the membrane protein with each step indicating the unfolding of a structural segment (39). Recording the applied force over pulling distance results in a force-distance (F-D) curve in which individual force peaks represent the rupture of intra- and intermolecular interactions. The height of a force peak measures the strength of an interaction with piconewton accuracy, and the pulling distance, at which the force peak occurs, allows the interaction within the membrane protein structure to be located (38).Open in a separate windowFIGURE 1.SMFS of SteT. A, pushing the AFM stylus onto the proteoliposomes promotes contacting single transporters to the stylus. This molecular link allows exertion of a mechanical pulling force that initiates stepwise unfolding of SteT. During the experiments, sample and cantilever are immersed in buffer solution. B, F-D curves recorded while unfolding single substrate-free SteT molecules. C, superimpositions of F-D curves recorded while unfolding SteT in buffer lacking any substrate (top) and supplemented with 5 mm l-serine (middle) or 5 mm l-threonine (bottom). Superimpositions are represented as density plots, each calculated from 60 F-D curves. Gray lines represent WLC curves with a persistence length of 0.4 nm and contour length (in amino acids) as indicated by the numbers next to the lines. The contour lengths were obtained from the Gaussian fits shown in D. F-D curves were obtained at room temperature at a pulling velocity of 654 nm/s in buffer solution (150 mm NaCl, 20 mm Tris-HCl, pH 8.0, substrate as indicated). D, frequency of force peaks detected at different positions of the stretched polypeptide. Every force peak detected in individual F-D curves (B) was fitted using the WLC model with the contour length of the stretched polypeptide as the only fitting parameter. The frequency at which the force peaks appeared is plotted in the histogram: substrate-free, n = 132; 5 mm l-serine, n = 128; and 5 mm l-threonine, n = 127. The bin size of the histograms is 3 aa and reflects the accuracy of fitting the WLC model (55) to individual force peaks. Error bars representing the S.E. were calculated using S.E. = (p(1 − p)/n)^0.5 where p is the probability and n is the total number of F-D curves. The width of each force peak distribution is given by the experimental noise, conformational variability of the structural segments, and fitting accuracy of the force peaks (53, 99–102). The gray solid curve represents the sum of seven Gaussian fits to the seven main peaks from the histograms and superimpositions (C). Numbers next to peaks denote peak positions (measured in amino acids) obtained from Gaussian fits.Besides quantification and localization of molecular interactions in membrane proteins, SMFS provides information about their energy landscape. For that purpose, the interactions of membrane proteins are probed over a range of different time scales by dynamic force spectroscopy (DFS). Bell (40) and Evans and co-worker (41, 42) provided the most commonly used theoretical framework to analyze DFS data. Their model describes the deformation of the energy landscape by an externally applied force, F. Such force-induced deformations reduce the energy barriers that separate bound and unbound states (see Fig. 2). Consequently transition rates over such energy barriers are force-dependent. Probing the interactions at different pulling velocities and thus at different force loading rates, r_f, leads to a so-called dynamic force spectrum in which the most probable force, F*, of rupture is plotted versus the logarithm of r_f. In these dynamic force spectra, each linear regime represents an energy barrier. Energy barriers located closer to the bound state are probed at higher pulling velocities because the energy barriers located further from the bound state are suppressed by increasingly applied forces (see Fig. 2) (41). The slope of each linear regime measures the distance from the ground state to the transition state, whereas extrapolation of a linear regime to zero force provides the rate constant of crossing the corresponding barrier in the absence of any load. These two parameters allow an estimate of the rigidity of the probed structure (43, 44).Open in a separate windowFIGURE 2.Energy landscape tilted by force. Schematic representation of the free energy profile along the reaction coordinate and applied force according to the Bell-Evans theory (40–42). The potential along the reaction coordinate (vector of force) in the absence of force (black curve) exhibits two energy barriers separating the folded from the unfolded state. Application of an external force, F, changes the thermal likelihood of reaching the top of the energy barrier(s). Although for a sharp barrier the position, x_u, of the energy barrier relative to the folded state is not changed, the thermally averaged projection of the energy profile along the pulling direction is tilted by the mechanical energy (−F·cos θ)x (long-dashed line). This tilt decreases the energy barriers (short-dashed curve). Consequently the relevant energy barrier that has to be overcome is the outermost barrier. At slow pulling velocities, the thermal contribution is higher, and therefore, the mechanical energy required to overcome the barrier is smaller. With increasing pulling velocities, the barriers are further lowered. At some velocity, the height of the outer barrier will be lower than that of the inner barrier (short-dashed curve), which then becomes the relevant energy barrier to be overcome. Each energy barrier manifests as a linear regime in dynamic force spectra (Fig. 3).In this study, we applied SMFS to characterize molecular interactions that stabilize SteT in the absence and in the presence of its substrates, l-serine and l-threonine. We used DFS to characterize how substrate binding changes the energy landscape and the mechanical properties of the antiporter. It was observed that the structural regions stabilized within SteT did not depend on substrate binding. However, substrate binding dynamically changed the energy landscape of these structures. In the absence of substrate all structural regions within SteT were stabilized by a narrow inner energy barrier and co-stabilized by a second outer energy barrier. The unique properties of these energy barriers restricted the conformation of SteT thereby trapping the antiporter in a kinetically instable and mechanically rigid conformation. In contrast, substrate binding sets SteT into a different energy minimum that significantly increased the kinetic stability and conformational flexibility of the antiporter.     

Computable visually observed phenotype ontological framework for plants

Background

Gene regulatory networks have an essential role in every process of life. In this regard, the amount of genome-wide time series data is becoming increasingly available, providing the opportunity to discover the time-delayed gene regulatory networks that govern the majority of these molecular processes.

Results

This paper aims at reconstructing gene regulatory networks from multiple genome-wide microarray time series datasets. In this sense, a new model-free algorithm called GRNCOP2 (Gene Regulatory Network inference by Combinatorial OPtimization 2), which is a significant evolution of the GRNCOP algorithm, was developed using combinatorial optimization of gene profile classifiers. The method is capable of inferring potential time-delay relationships with any span of time between genes from various time series datasets given as input. The proposed algorithm was applied to time series data composed of twenty yeast genes that are highly relevant for the cell-cycle study, and the results were compared against several related approaches. The outcomes have shown that GRNCOP2 outperforms the contrasted methods in terms of the proposed metrics, and that the results are consistent with previous biological knowledge. Additionally, a genome-wide study on multiple publicly available time series data was performed. In this case, the experimentation has exhibited the soundness and scalability of the new method which inferred highly-related statistically-significant gene associations.

Conclusions

A novel method for inferring time-delayed gene regulatory networks from genome-wide time series datasets is proposed in this paper. The method was carefully validated with several publicly available data sets. The results have demonstrated that the algorithm constitutes a usable model-free approach capable of predicting meaningful relationships between genes, revealing the time-trends of gene regulation.     

Scaling, growth and cyclicity in biology: a new computational approach

Background

The Phenomenological Universalities approach has been developed by P.P. Delsanto and collaborators during the past 2–3 years. It represents a new tool for the analysis of experimental datasets and cross-fertilization among different fields, from physics/engineering to medicine and social sciences. In fact, it allows similarities to be detected among datasets in totally different fields and acts upon them as a magnifying glass, enabling all the available information to be extracted in a simple way. In nonlinear problems it allows the nonscaling invariance to be retrieved by means of suitable redefined fractal-dimensioned variables.

Results

The main goal of the present contribution is to extend the applicability of the new approach to the study of problems of growth with cyclicity, which are of particular relevance in the fields of biology and medicine.

Conclusion

As an example of its implementation, the method is applied to the analysis of human growth curves. The excellent quality of the results (R ² = 0.988) demonstrates the usefulness and reliability of the approach.     

Analysis of coronary angiography related psychophysiological responses

Background

Numerous studies have been conducted regarding a heartbeat classification algorithm over the past several decades. However, many algorithms have also been studied to acquire robust performance, as biosignals have a large amount of variation among individuals. Various methods have been proposed to reduce the differences coming from personal characteristics, but these expand the differences caused by arrhythmia.

Methods

In this paper, an arrhythmia classification algorithm using a dedicated wavelet adapted to individual subjects is proposed. We reduced the performance variation using dedicated wavelets, as in the ECG morphologies of the subjects. The proposed algorithm utilizes morphological filtering and a continuous wavelet transform with a dedicated wavelet. A principal component analysis and linear discriminant analysis were utilized to compress the morphological data transformed by the dedicated wavelets. An extreme learning machine was used as a classifier in the proposed algorithm.

Results

A performance evaluation was conducted with the MIT-BIH arrhythmia database. The results showed a high sensitivity of 97.51%, specificity of 85.07%, accuracy of 97.94%, and a positive predictive value of 97.26%.

Conclusions

The proposed algorithm achieves better accuracy than other state-of-the-art algorithms with no intrasubject between the training and evaluation datasets. And it significantly reduces the amount of intervention needed by physicians.     

An algorithm and program for finding sequence specific oligo-nucleotide probes for species identification

Background

The identification of species or species groups with specific oligo-nucleotides as molecular signatures is becoming increasingly popular for bacterial samples. However, it shows also great promise for other small organisms that are taxonomically difficult to tract.

Results

We have devised here an algorithm that aims to find the optimal probes for any given set of sequences. The program requires only a crude alignment of these sequences as input and is optimized for performance to deal also with very large datasets. The algorithm is designed such that the position of mismatches in the probes influences the selection and makes provision of single nucleotide outloops. Program implementations are available for Linux and Windows.     

Surgical treatment of scoliosis: a review of techniques currently applied

Background Context

Research employing gait measurements indicate asymmetries in ground reaction forces and suggest relationships between these asymmetries, neurological dysfunction and spinal deformity. Although, studies have documented the use of centre of pressure (CoP) and net joint moments in gait assessment and have assessed centre of mass (CoM)-CoP distance relationships in clinical conditions, there is a paucity of information relating to the moments about CoM. It is commonly considered that CoM is situated around S2 vertebra in normal upright posture and hence this study uses S2 vertebral prominence as reference point relative to CoM.

Purpose

To assess and establish asymmetry in the CoP pattern and moments about S2 vertebral prominence during level walking and its relationship to spinal deformity in adolescents with scoliosis.

Patient sample

Nine Adolescent Idiopathic Scoliosis subjects (8 females and 1 male with varying curve magnitudes and laterality) scheduled for surgery within 2–3 days after data collection, took part in this study.

Outcome measures

Kinetic and Kinematic Gait assessment was performed with an aim to estimate the CoP displacement and the moments generated by the ground reaction force about the S2 vertebral prominence during left and right stance during normal walking.

Methods

The study employed a strain gauge force platform to estimate the medio-lateral and anterior-posterior displacement of COP and a six camera motion analysis system to track the reflective markers to assess the kinematics. The data were recorded simultaneously.

Results

Results indicate wide variations in the medio lateral direction CoP, which could be related to the laterality of both the main and compensation curves. This variation is not evident in the anterior-posterior direction. Similar results were recorded for moments about S2 vertebral prominence. Subjects with higher left compensation curve had greater displacement to the left.

Conclusion

Although further longitudinal studies are needed, results indicate that the variables identified in this study are applicable to initial screening and surgical evaluation of scoliosis.     

UMARS: Un-MAppable Reads Solution

Background

Few high-resolution structures of integral membranes proteins are available, as crystallization of such proteins needs yet to overcome too many technical limitations. Nevertheless, prediction of their transmembrane (TM) structure by bioinformatics tools provides interesting insights on the topology of these proteins.

Methods

We describe here how to extract new information from the analysis of hydrophobicity variations or hydrophobic pulses (HPulses) in the sequence of integral membrane proteins using the Hydrophobic Pulse Predictor, a new tool we developed for this purpose. To analyze the primary sequence of 70 integral membrane proteins we defined two levels of analysis: G1-HPulses for sliding windows of n = 2 to 6 and G2-HPulses for sliding windows of n = 12 to 16.

Results

The G2-HPulse analysis of 541 transmembrane helices allowed the definition of the new concept of transmembrane unit (TMU) that groups together transmembrane helices and segments with potential adjacent structures. In addition, the G1-HPulse analysis identified helix irregularities that corresponded to kinks, partial helices or unannotated structural events. These irregularities could represent key dynamic elements that are alternatively activated depending on the channel status as illustrated by the crystal structures of the lactose permease in different conformations.

Conclusions

Our results open a new way in the understanding of transmembrane secondary structures: hydrophobicity through hydrophobic pulses strongly impacts on such embedded structures and is not confined to define the transmembrane status of amino acids.     

Multiscale Hy3S: Hybrid stochastic simulation for supercomputers

Background

DNA copy number alterations are one of the main characteristics of the cancer cell karyotype and can contribute to the complex phenotype of these cells. These alterations can lead to gains in cellular oncogenes as well as losses in tumor suppressor genes and can span small intervals as well as involve entire chromosomes. The ability to accurately detect these changes is central to understanding how they impact the biology of the cell.

Results

We describe a novel algorithm called CARAT (Copy Number Analysis with Regression And Tree) that uses probe intensity information to infer copy number in an allele-specific manner from high density DNA oligonuceotide arrays designed to genotype over 100, 000 SNPs. Total and allele-specific copy number estimations using CARAT are independently evaluated for a subset of SNPs using quantitative PCR and allelic TaqMan reactions with several human breast cancer cell lines. The sensitivity and specificity of the algorithm are characterized using DNA samples containing differing numbers of X chromosomes as well as a test set of normal individuals. Results from the algorithm show a high degree of agreement with results from independent verification methods.

Conclusion

Overall, CARAT automatically detects regions with copy number variations and assigns a significance score to each alteration as well as generating allele-specific output. When coupled with SNP genotype calls from the same array, CARAT provides additional detail into the structure of genome wide alterations that can contribute to allelic imbalance.     

A novel application of capnography during controlled human exposure to air pollution

Background

A detailed contrast bolus propagation model is essential for optimizing bolus-chasing Computed Tomography Angiography (CTA). Bolus characteristics were studied using bolus-timing datasets from Magnetic Resonance Angiography (MRA) for adaptive controller design and validation.

Methods

MRA bolus-timing datasets of the aorta in thirty patients were analyzed by a program developed with MATLAB. Bolus characteristics, such as peak position, dispersion and bolus velocity, were studied. The bolus profile was fit to a convolution function, which would serve as a mathematical model of bolus propagation in future controller design.

Results

The maximum speed of the bolus in the aorta ranged from 5–13 cm/s and the dwell time ranged from 7–13 seconds. Bolus characteristics were well described by the proposed propagation model, which included the exact functional relationships between the parameters and aortic location.

Conclusion

The convolution function describes bolus dynamics reasonably well and could be used to implement the adaptive controller design.     

A proof of the DBRF-MEGN method, an algorithm for deducing minimum equivalent gene networks

Background

We previously developed the DBRF-MEGN (difference-based regulation finding-minimum equivalent gene network) method, which deduces the most parsimonious signed directed graphs (SDGs) consistent with expression profiles of single-gene deletion mutants. However, until the present study, we have not presented the details of the method's algorithm or a proof of the algorithm.

Results

We describe in detail the algorithm of the DBRF-MEGN method and prove that the algorithm deduces all of the exact solutions of the most parsimonious SDGs consistent with expression profiles of gene deletion mutants.

Conclusions

The DBRF-MEGN method provides all of the exact solutions of the most parsimonious SDGs consistent with expression profiles of gene deletion mutants.     

HotSwap for bioinformatics: A STRAP tutorial

Background

Bioinformatics applications are now routinely used to analyze large amounts of data. Application development often requires many cycles of optimization, compiling, and testing. Repeatedly loading large datasets can significantly slow down the development process. We have incorporated HotSwap functionality into the protein workbench STRAP, allowing developers to create plugins using the Java HotSwap technique.

Results

Users can load multiple protein sequences or structures into the main STRAP user interface, and simultaneously develop plugins using an editor of their choice such as Emacs. Saving changes to the Java file causes STRAP to recompile the plugin and automatically update its user interface without requiring recompilation of STRAP or reloading of protein data. This article presents a tutorial on how to develop HotSwap plugins. STRAP is available at http://strapjava.de and http://www.charite.de/bioinf/strap.

Conclusion

HotSwap is a useful and time-saving technique for bioinformatics developers. HotSwap can be used to efficiently develop bioinformatics applications that require loading large amounts of data into memory.     

Membrane-Protein Unfolding Intermediates Detected with Enhanced Precision Using a Zigzag Force Ramp

Precise quantification of the energetics and interactions that stabilize membrane proteins in a lipid bilayer is a long-sought goal. Toward this end, atomic force microscopy has been used to unfold individual membrane proteins embedded in their native lipid bilayer, typically by retracting the cantilever at a constant velocity. Recently, unfolding intermediates separated by as few as two amino acids were detected using focused-ion-beam-modified ultrashort cantilevers. However, unambiguously discriminating between such closely spaced states remains challenging, in part because any individual unfolding trajectory only occupies a subset of the total number of intermediates. Moreover, structural assignment of these intermediates via worm-like-chain analysis is hindered by brief dwell times compounded with thermal and instrumental noise. To overcome these issues, we moved the cantilever in a sawtooth pattern of 6–12 nm, offset by 0.25–1 nm per cycle, generating a “zigzag” force ramp of alternating positive and negative loading rates. We applied this protocol to the model membrane protein bacteriorhodopsin (bR). In contrast to conventional studies that extract bR’s photoactive retinal along with the first transmembrane helix, we unfolded bR in the presence of its retinal. To do so, we introduced a previously developed enzymatic-cleavage site between helices E and F and pulled from the top of the E helix using a site-specific, covalent attachment. The resulting zigzag unfolding trajectories occupied 40% more states per trajectory and occupied those states for longer times than traditional constant-velocity records. In total, we identified 31 intermediates during the unfolding of five helices of EF-cleaved bR. These included a previously reported, mechanically robust intermediate located between helices C and B that, with our enhanced resolution, is now shown to be two distinct states separated by three amino acids. Interestingly, another intermediate directly interacted with the retinal, an interaction confirmed by removing the retinal.     

Recognizing brain activities by functional near-infrared spectroscope signal analysis

Background

Noninvasive recording of movements caused by the heartbeat and the blood circulation is known as ballistocardiography. Several studies have shown the capability of a force plate to detect cardiac activity in the human body. The aim of this paper is to present a new method based on differential geometry of curves to handle multivariate time series obtained by ballistocardiographic force plate measurements.

Results

We show that the recoils of the body caused by cardiac motion and blood circulation provide a noninvasive method of displaying the motions of the heart muscle and the propagation of the pulse wave along the aorta and its branches. The results are compared with the data obtained invasively during a cardiac catheterization. We show that the described noninvasive method is able to determine the moment of a particular heart movement or the time when the pulse wave reaches certain morphological structure.

Conclusions

Monitoring of heart movements and pulse wave propagation may be used e.g. to estimate the aortic pulse wave velocity, which is widely accepted as an index of aortic stiffness with the application of predicting risk of heart disease in individuals. More extended analysis of the method is however needed to assess its possible clinical application.     

Impact of RNA degradation on gene expression profiling

Background

Cancer is a heterogeneous disease caused by genomic aberrations and characterized by significant variability in clinical outcomes and response to therapies. Several subtypes of common cancers have been identified based on alterations of individual cancer genes, such as HER2, EGFR, and others. However, cancer is a complex disease driven by the interaction of multiple genes, so the copy number status of individual genes is not sufficient to define cancer subtypes and predict responses to treatments. A classification based on genome-wide copy number patterns would be better suited for this purpose.

Method

To develop a more comprehensive cancer taxonomy based on genome-wide patterns of copy number abnormalities, we designed an unsupervised classification algorithm that identifies genomic subgroups of tumors. This algorithm is based on a modified genomic Non-negative Matrix Factorization (gNMF) algorithm and includes several additional components, namely a pilot hierarchical clustering procedure to determine the number of clusters, a multiple random initiation scheme, a new stop criterion for the core gNMF, as well as a 10-fold cross-validation stability test for quality assessment.

Result

We applied our algorithm to identify genomic subgroups of three major cancer types: non-small cell lung carcinoma (NSCLC), colorectal cancer (CRC), and malignant melanoma. High-density SNP array datasets for patient tumors and established cell lines were used to define genomic subclasses of the diseases and identify cell lines representative of each genomic subtype. The algorithm was compared with several traditional clustering methods and showed improved performance. To validate our genomic taxonomy of NSCLC, we correlated the genomic classification with disease outcomes. Overall survival time and time to recurrence were shown to differ significantly between the genomic subtypes.

Conclusions

We developed an algorithm for cancer classification based on genome-wide patterns of copy number aberrations and demonstrated its superiority to existing clustering methods. The algorithm was applied to define genomic subgroups of three cancer types and identify cell lines representative of these subgroups. Our data enabled the assembly of representative cell line panels for testing drug candidates.     

Interpreting the ash trend within ombrotrophic bog profiles: atmospheric dust depositions vs. mineralization processes. The Etang de la Gruère case study

Introduction

Ash peaks along ombrotrophic bog profiles may arise from several different processes. In a recent paper, Leifeld and co-authors (Plant Soil 341:349–361, 2011) argued that ash peaks along the Etang de la Gruère (EGr) peat bog profiles are signs of previous periods of higher peat decomposition rather that an indication of periods of elevated dust inputs.

Aims and methods

Here we question the approach and scrutinize results using published data on several peat cores from EGr, demonstrating that peaks in ash content at EGr are very reproducible when cores are carefully collected (e.g., using the Wardenaar corer), and age dated (using ²¹⁰Pb and ¹⁴C).

Results

Data clearly show that variations in ash content along bog profiles cannot be attributed simply, or exclusively, to differences in organic matter mineralization rate, and that averaging the ash contents and normalizing to a single ash peak leads to losses in valuable information and defeats the purpose of detailed paleoenvironmental reconstructions.

Conclusions

Comparing results obtained using sensitive spectroscopic and isotopic tools with the ash content profiles at EGr shows clearly that the distribution of ash and/or acid-insoluble ash cannot be used as a surrogate for the intensity of processes including organic matter mineralization, decomposition and/or humification.     

Learning probabilistic models of hydrogen bond stability from molecular dynamics simulation trajectories

Background

The estimation of individual ancestry from genetic data has become essential to applied population genetics and genetic epidemiology. Software programs for calculating ancestry estimates have become essential tools in the geneticist's analytic arsenal.

Results

Here we describe four enhancements to ADMIXTURE, a high-performance tool for estimating individual ancestries and population allele frequencies from SNP (single nucleotide polymorphism) data. First, ADMIXTURE can be used to estimate the number of underlying populations through cross-validation. Second, individuals of known ancestry can be exploited in supervised learning to yield more precise ancestry estimates. Third, by penalizing small admixture coefficients for each individual, one can encourage model parsimony, often yielding more interpretable results for small datasets or datasets with large numbers of ancestral populations. Finally, by exploiting multiple processors, large datasets can be analyzed even more rapidly.

Conclusions

The enhancements we have described make ADMIXTURE a more accurate, efficient, and versatile tool for ancestry estimation.     

3DMolNavi: A web-based retrieval and navigation tool for flexible molecular shape comparison

Background

As Next-Generation Sequencing data becomes available, existing hardware environments do not provide sufficient storage space and computational power to store and process the data due to their enormous size. This is and will be a frequent problem that is encountered everyday by researchers who are working on genetic data. There are some options available for compressing and storing such data, such as general-purpose compression software, PBAT/PLINK binary format, etc. However, these currently available methods either do not offer sufficient compression rates, or require a great amount of CPU time for decompression and loading every time the data is accessed.

Results

Here, we propose a novel and simple algorithm for storing such sequencing data. We show that, the compression factor of the algorithm ranges from 16 to several hundreds, which potentially allows SNP data of hundreds of Gigabytes to be stored in hundreds of Megabytes. We provide a C++ implementation of the algorithm, which supports direct loading and parallel loading of the compressed format without requiring extra time for decompression. By applying the algorithm to simulated and real datasets, we show that the algorithm gives greater compression rate than the commonly used compression methods, and the data-loading process takes less time. Also, The C++ library provides direct-data-retrieving functions, which allows the compressed information to be easily accessed by other C++ programs.

Conclusions

The SpeedGene algorithm enables the storage and the analysis of next generation sequencing data in current hardware environment, making system upgrades unnecessary.     

An interactional network of genes involved in chitin synthesis in Saccharomyces cerevisiae

Background

The identification of disease-associated genes using single nucleotide polymorphisms (SNPs) has been increasingly reported. In particular, the Affymetrix Mapping 10 K SNP microarray platform uses one PCR primer to amplify the DNA samples and determine the genotype of more than 10,000 SNPs in the human genome. This provides the opportunity for large scale, rapid and cost-effective genotyping assays for linkage analysis. However, the analysis of such datasets is nontrivial because of the large number of markers, and visualizing the linkage scores in the context of genome maps remains less automated using the current linkage analysis software packages. For example, the haplotyping results are commonly represented in the text format.

Results

Here we report the development of a novel software tool called CompareLinkage for automated formatting of the Affymetrix Mapping 10 K genotype data into the "Linkage" format and the subsequent analysis with multi-point linkage software programs such as Merlin and Allegro. The new software has the ability to visualize the results for all these programs in dChip in the context of genome annotations and cytoband information. In addition we implemented a variant of the Lander-Green algorithm in the dChipLinkage module of dChip software (V1.3) to perform parametric linkage analysis and haplotyping of SNP array data. These functions are integrated with the existing modules of dChip to visualize SNP genotype data together with LOD score curves. We have analyzed three families with recessive and dominant diseases using the new software programs and the comparison results are presented and discussed.

Conclusions

The CompareLinkage and dChipLinkage software packages are freely available. They provide the visualization tools for high-density oligonucleotide SNP array data, as well as the automated functions for formatting SNP array data for the linkage analysis programs Merlin and Allegro and calling these programs for linkage analysis. The results can be visualized in dChip in the context of genes and cytobands. In addition, a variant of the Lander-Green algorithm is provided that allows parametric linkage analysis and haplotyping.