Genotoxicity biomarkers in aquatic bioindicators

Pollution of the aquatic environment is an ever-growing problem, as waters are the ultimate sink for the large number of xenobiotics from multiple sources. DNA damaging agents have a significant ecological relevance since they are implicated in many pathological processes and exert effects beyond that of individual being active through following generations. A large number of methods have been applied to evaluate genotoxic damage in different aquatic species. Comet assay, as method for de- tecting DNA alterations, and micronucleus test, as an index of chromosomal damage are the most widely applied and validated methods in field studies. These methods were applied in different vertebrate and invertebrate aquatic species, but only mollusk and fish species have been employed in routine biomonitoring programs. Mussels, due to their widely geographical distribution and the suitability for caging represent the bioindicator of choice in field studies. Mytilus species is the most used marine mussel. The use of fish is limited to specific geographic areas. The present review mainly focuses on the application of comet assay and micronucleus test in mussels. A number of biomonitoring studies in mussels, using comet assay or micronucleus test, revealed exposure to different classes of genotoxic compounds with a good discrimination power. The different evidence from the two as- says, reflects different biological mechanisms for the two genetic endpoints, DNA damage and chromosomal damage, suggesting their combined application in the field. Different endogenous and exogenous factors have been shown to modulate the genotoxic responses in mussels, acting as confounding factors in environmental monitoring. The use of standardized protocol for caging, sampling and genotoxity evaluation is critical in biomonitoring studies. The use of a multimarker approach coupling genotoxicity biomarkers with physiological and biochemical factors allows to have a complete picture of the environmental pollution [Current Zoology 60 （2）： 273-284, 2014].     

Methods for Analysis of Protein Glutathionylation and their Application to Photosynthetic Organisms

Protein S-glutathionylation, the reversible formation of a mixed-disulfide between glutathione and protein thiols, is involved in protection of protein cysteines from irreversible oxidation, but also in protein redox regulation. Recent studies have implicated S-glutathionylation as a cellular response to oxidative/nitrosative stress, likely playing an important role in signaling. Considering the potential importance of glutathionylation, a number of methods have been developed for identifying proteins undergoing glutathionylation. These methods, ranging from analysis of purified proteins in vitro to large-scale proteomic analyses in vivo, allowed identification of nearly 200 targets in mammals. By contrast, the number of known glutathionylated proteins is more limited in photosynthetic organisms, although they are severely exposed to oxidative stress. The aim of this review is to detail the methods available for identification and analysis of glutathionylated proteins in vivo and in vitro. The advantages and drawbacks of each technique will be discussed as well as their application to photosynthetic organisms. Furthermore, an overview of known glutathionylated proteins in photosynthetic organisms is provided and the physiological importance of this post-translational modification is discussed.     

Bioinformatics analyses for signal transduction networks

Research in signaling networks contributes to a deeper understanding of organism living activities. With the development of experimental methods in the signal transduction field, more and more mechanisms of signaling pathways have been discovered. This paper introduces such popular bioin-formatics analysis methods for signaling networks as the common mechanism of signaling pathways and database resource on the Internet, summerizes the methods of analyzing the structural properties of networks, including structural Motif finding and automated pathways generation, and discusses the modeling and simulation of signaling networks in detail, as well as the research situation and tendency in this area. Now the investigation of signal transduction is developing from small-scale experiments to large-scale network analysis, and dynamic simulation of networks is closer to the real system. With the investigation going deeper than ever, the bioinformatics analysis of signal transduction would have immense space for development and application.     

How Do Variable Substitution Rates Influence Ka and Ks Calculations？

The ratio of nonsynonymous substitution rate (Ka) to synonymous substitution rate (Ks) is widely used as an indicator of selective pressure at sequence level among different species, and diverse mutation models have been incorporated into several computing methods. We have previously developed a new γ-MYN method by capturing a key dynamic evolution trait of DNA nucleotide sequences, in consideration of varying mutation rates across sites. We now report a further improvement of NG, LWL, MLWL, LPB, MLPB, and ...     

Hidden Markov models incorporating fuzzy measures and integrals for protein sequence identification and alignment

Profile hidden Markov models （HMMs） based on classical HMMs have been widely applied for protein sequence identification. The formulation of the forward and backward variables in profile HMMs is made under statistical independence assumption of the probability theory. We propose a fuzzy profile HMM to overcome the limitations of that assumption and to achieve an improved alignment for protein sequences belonging to a given family. The proposed model fuzzifies the forward and backward variables by incorporating Sugeno fuzzy measures and Choquet integrals, thus further extends the generalized HMM. Based on the fuzzified forward and backward variables, we propose a fuzzy Baum-Welch parameter estimation algorithm for profiles. The strong correlations and the sequence preference involved in the protein structures make this fuzzy architecture based model as a suitable candidate for building profiles of a given family, since the fuzzy set can handle uncertainties better than classical methods.     

KaKs_Calculator： Calculating Ka and Ks Through Model Selection and Model Averaging

KaKs_Calculator is a software package that calculates nonsynonymous （Ka） and synonymous （Ks） substitution rates through model selection and model averaging. Since existing methods for this estimation adopt their specific mutation （substitution） models that consider different evolutionary features, leading to diverse estimates, KaKs_Calculator implements a set of candidate models in a maximum likelihood framework and adopts the Akaike information criterion to measure fitness between models and data, aiming to include as many features as needed for accurately capturing evolutionary information in protein-coding sequences. In addition, several existing methods for calculating Ka and Ks are also incorporated into this software. KaKs_Calculator, including source codes, compiled executables, and documentation, is freely available for academic use at http：//evolution.genomics.org.cn/software.htm.     

VICMpred： An SVM-based Method for the Prediction of Functional Proteins of Gram-negative Bacteria Using Amino Acid Patterns and Composition

In this study, an attempt has been made to predict the major functions of gramnegative bacterial proteins from their amino acid sequences. The dataset used for training and testing consists of 670 non-redundant gram-negative bacterial proteins （255 of cellular process, 60 of information molecules, 285 of metabolism, and 70 of virulence factors）. First we developed an SVM-based method using amino acid and dipeptide composition and achieved the overall accuracy of 52.39% and 47.01%, respectively. We introduced a new concept for the classification of proteins based on tetrapeptides, in which we identified the unique tetrapeptides significantly found in a class of proteins. These tetrapeptides were used as the input feature for predicting the function of a protein and achieved the overall accuracy of 68.66%. We also developed a hybrid method in which the tetrapeptide information was used with amino acid composition and achieved the overall accuracy of 70.75%. A five-fold cross validation was used to evaluate the performance of these methods. The web server VICMpred has been developed for predicting the function of gram-negative bacterial proteins （http：//www.imtech.res.in/raghava/vicmpred/）.     

Compression of FASTQ and SAM Format Sequencing Data

Storage and transmission of the data produced by modern DNA sequencing instruments has become a major concern, which prompted the Pistoia Alliance to pose the SequenceSqueeze contest for compression of FASTQ files. We present several compression entries from the competition, Fastqz and Samcomp/Fqzcomp, including the winning entry. These are compared against existing algorithms for both reference based compression (CRAM, Goby) and non-reference based compression (DSRC, BAM) and other recently published competition entries (Quip, SCALCE). The tools are shown to be the new Pareto frontier for FASTQ compression, offering state of the art ratios at affordable CPU costs. All programs are freely available on SourceForge. Fastqz: https://sourceforge.net/projects/fastqz/, fqzcomp: https://sourceforge.net/projects/fqzcomp/, and samcomp: https://sourceforge.net/projects/samcomp/.     

iPiG: Integrating Peptide Spectrum Matches into Genome Browser Visualizations

Proteogenomic approaches have gained increasing popularity, however it is still difficult to integrate mass spectrometry identifications with genomic data due to differing data formats. To address this difficulty, we introduce iPiG as a tool for the integration of peptide identifications from mass spectrometry experiments into existing genome browser visualizations. Thereby, the concurrent analysis of proteomic and genomic data is simplified and proteomic results can directly be compared to genomic data. iPiG is freely available from https://sourceforge.net/projects/ipig/. It is implemented in Java and can be run as a stand-alone tool with a graphical user-interface or integrated into existing workflows. Supplementary data are available at PLOS ONE online.     

OrthoRBH: A streamlined pipeline for mining large gene family sequences in related species

Plant and animal genomes are replete with large gene families, making the task of ortholog identification difficult and labor intensive. OrthoRBH is an automated reciprocal blast pipeline tool enabling the rapid identification of specific gene families of interest in related species, streamlining the collection of homologs prior to downstream molecular evolutionary analysis. The efficacy of OrthoRBH is demonstrated with the identification of the 13-member PYR/PYL/RCAR gene family in Hordeum vulgare using Oryza sativa query sequences. OrthoRBH runs on the Linux command line and is freely available at SourceForge.

Availability

http://sourceforge.net/projects/ orthorbh/     

PHYSICO2: an UNIX based standalone procedure for computation of physicochemical,window-dependent and substitution based evolutionary properties of protein sequences along with automated block preparation tool,version 2

AvailabilityPHYSICO2: is freely available at http://sourceforge.net/projects/physico2/ along with its documentation at https://sourceforge.net/projects/physico2/files/Documentation.pdf/download for all users.     

Reduced CSF Water Influx in Alzheimer’s Disease Supporting the β-Amyloid Clearance Hypothesis

Objective

To investigate whether water influx into cerebrospinal fluid (CSF) space is reduced in Alzheimer’s patients as previously shown in the transgenic mouse model for Alzheimer’s disease.

Methods

Ten normal young volunteers (young control, 21-30 years old), ten normal senior volunteers (senior control, 60-78 years old, MMSE ≥ 29), and ten Alzheimer’s disease (AD) patients (study group, 59-84 years old, MMSE: 13-19) participated in this study. All AD patients were diagnosed by neurologists specializing in dementia based on DSM-IV criteria. CSF dynamics were analyzed using positron emission tomography (PET) following an intravenous injection of 1,000 MBq [¹⁵O]H₂O synthesized on-line.

Results

Water influx into CSF space in AD patients, expressed as influx ratio, (0.755 ± 0.089) was significantly reduced compared to young controls (1.357 ± 0.185; p < 0.001) and also compared to normal senior controls (0.981 ± 0.253, p < 0.05). Influx ratio in normal senior controls was significantly reduced compared to young controls (p < 0.01).

Conclusion

Water influx into the CSF is significantly reduced in AD patients. β-amyloid clearance has been shown to be dependent on interstitial flow and CSF production. The current study indicates that reduction in water influx into the CSF may disturb the clearance rate of β-amyloid, and therefore be linked to the pathogenesis of AD.

Trial Registration

UMIN Clinical Trials Registry UMIN000011939     

SEWAL: an open-source platform for next-generation sequence analysis and visualization

Next-generation DNA sequencing platforms provide exciting new possibilities for in vitro genetic analysis of functional nucleic acids. However, the size of the resulting data sets presents computational and analytical challenges. We present an open-source software package that employs a locality-sensitive hashing algorithm to enumerate all unique sequences in an entire Illumina sequencing run (∼10⁸ sequences). The algorithm results in quasilinear time processing of entire Illumina lanes (∼10⁷ sequences) on a desktop computer in minutes. To facilitate visual analysis of sequencing data, the software produces three-dimensional scatter plots similar in concept to Sewall Wright and John Maynard Smith’s adaptive or fitness landscape. The software also contains functions that are particularly useful for doped selections such as mutation frequency analysis, information content calculation, multivariate statistical functions (including principal component analysis), sequence distance metrics, sequence searches and sequence comparisons across multiple Illumina data sets. Source code, executable files and links to sample data sets are available at http://www.sourceforge.net/projects/sewal.     

GPU-FS-kNN: A Software Tool for Fast and Scalable kNN Computation Using GPUs

Background

The analysis of biological networks has become a major challenge due to the recent development of high-throughput techniques that are rapidly producing very large data sets. The exploding volumes of biological data are craving for extreme computational power and special computing facilities (i.e. super-computers). An inexpensive solution, such as General Purpose computation based on Graphics Processing Units (GPGPU), can be adapted to tackle this challenge, but the limitation of the device internal memory can pose a new problem of scalability. An efficient data and computational parallelism with partitioning is required to provide a fast and scalable solution to this problem.

Results

We propose an efficient parallel formulation of the k-Nearest Neighbour (kNN) search problem, which is a popular method for classifying objects in several fields of research, such as pattern recognition, machine learning and bioinformatics. Being very simple and straightforward, the performance of the kNN search degrades dramatically for large data sets, since the task is computationally intensive. The proposed approach is not only fast but also scalable to large-scale instances. Based on our approach, we implemented a software tool GPU-FS-kNN (GPU-based Fast and Scalable k-Nearest Neighbour) for CUDA enabled GPUs. The basic approach is simple and adaptable to other available GPU architectures. We observed speed-ups of 50–60 times compared with CPU implementation on a well-known breast microarray study and its associated data sets.

Conclusion

Our GPU-based Fast and Scalable k-Nearest Neighbour search technique (GPU-FS-kNN) provides a significant performance improvement for nearest neighbour computation in large-scale networks. Source code and the software tool is available under GNU Public License (GPL) at https://sourceforge.net/p/gpufsknn/.