ProDomAs,protein domain assignment algorithm using center‐based clustering and independent dominating set

Decomposition of structural domains is an essential task in classifying protein structures, predicting protein function, and many other proteomics problems. As the number of known protein structures in PDB grows exponentially, the need for accurate automatic domain decomposition methods becomes more essential. In this article, we introduce a bottom‐up algorithm for assigning protein domains using a graph theoretical approach. This algorithm is based on a center‐based clustering approach. For constructing initial clusters, members of an independent dominating set for the graph representation of a protein are considered as the centers. A distance matrix is then defined for these clusters. To obtain final domains, these clusters are merged using the compactness principle of domains and a method similar to the neighbor‐joining algorithm considering some thresholds. The thresholds are computed using a training set consisting of 50 protein chains. The algorithm is implemented using C++ language and is named ProDomAs. To assess the performance of ProDomAs, its results are compared with seven automatic methods, against five publicly available benchmarks. The results show that ProDomAs outperforms other methods applied on the mentioned benchmarks. The performance of ProDomAs is also evaluated against 6342 chains obtained from ASTRAL SCOP 1.71. ProDomAs is freely available at http://www.bioinf.cs.ipm.ir/software/prodomas . Proteins 2014; 82:1937–1946. © 2014 Wiley Periodicals, Inc.     

Berberine Ameliorate Oxidative Stress and Astrogliosis in the Hippocampus of STZ-Induced Diabetic Rats

Diabetes mellitus increases the risk of central nervous system (CNS) disorders such as stroke, seizures, dementia, and cognitive impairment. Berberine, a natural isoquinoline alkaloid, is reported to exhibit beneficial effect in various neurodegenerative and neuropsychiatric disorders. Moreover, astrocytes are proving critical for normal CNS function, and alterations in their activity and impaired oxidative stress could contribute to diabetes-related cognitive dysfunction. Metabolic and oxidative insults often cause rapid changes in glial cells. Key indicators of this response are increased synthesis of glial fibrillary acidic protein (GFAP) as an astrocytic marker. Therefore, we examined the effects of berberine on glial reactivity of hippocampus in streptozotocin (STZ)-induced diabetic rats, using GFAP immunohistochemistry. Lipid peroxidation, superoxide dismutase (SOD) activity, and nitrite levels were assessed as the parameters of oxidative stress. Eight weeks after diabetes induction, we observed increased numbers of GFAP⁺ astrocytes immunostaining associated with increased lipid peroxidation, decreased superoxide dismutase activity, and elevated nitrite levels in the hippocampus of STZ-diabetic rats. In contrast, chronic treatment with berberine (50 and 100 mg/kg p.o. once daily) lowered hyperglycemia, reduced oxidative stress, and prevented the upregulation of GFAP in the brain of diabetic rats. In conclusion, the present study demonstrated that the treatment with berberine resulted in an obvious reduction of oxidative stress and GFAP-immunoreactive astrocytes in the hippocampus of STZ-induced diabetic rats.

A role for the proteasome in the turnover of Sup35p and in [PSI+] prion propagation

Yeast prions are superb models for understanding the mechanisms of self‐perpetuating protein aggregates formation. [PSI⁺] stands among the most documented yeast prions and results from self‐assembly of the translation termination factor Sup35p into protein fibrils. A plethora of cellular factors were shown to affect [PSI⁺] formation and propagation. Clearance of Sup35p prion particles is however poorly understood and documented. Here, we investigated the role of the proteasome in the degradation of Sup35p and in [PSI⁺] prion propagation. We found that cells lacking the RPN4 gene, which have reduced intracellular proteasome pools, accumulated Sup35p and have defects in [PSI⁺] formation and propagation. Sup35p is degraded in vitro by the 26S and 20S proteasomes in a ubiquitin‐independent manner, generating an array of amyloidogenic peptides derived from its prion‐domain. We also demonstrate the formation of a proteasome‐resistant fragment spanning residues 83–685 which is devoid of the prion‐domain that is essential for [PSI⁺] propagation. Most important was the finding that the 26S and 20S proteasomes degrade Sup35p fibrils in vitro and abolish their infectivity. Our results point to an overlooked role of the proteasome in clearing toxic protein aggregates, and have important implications for a better understanding of the life cycle of infectious protein assemblies.     

Impact of whole-genome amplification on the reliability of pre-transfer cattle embryo breeding value estimates

Background

Genome-wide profiling of single-nucleotide polymorphisms is receiving increasing attention as a method of pre-implantation genetic diagnosis in humans and of commercial genotyping of pre-transfer embryos in cattle. However, the very small quantity of genomic DNA in biopsy material from early embryos poses daunting technical challenges. A reliable whole-genome amplification (WGA) procedure would greatly facilitate the procedure.

Results

Several PCR-based and non-PCR based WGA technologies, namely multiple displacement amplification, quasi-random primed library synthesis followed by PCR, ligation-mediated PCR, and single-primer isothermal amplification were tested in combination with different DNA extractions protocols for various quantities of genomic DNA inputs. The efficiency of each method was evaluated by comparing the genotypes obtained from 15 cultured cells (representative of an embryonic biopsy) to unamplified reference gDNA. The gDNA input, gDNA extraction method and amplification technology were all found to be critical for successful genome-wide genotyping. The selected WGA platform was then tested on embryo biopsies (n = 226), comparing their results to that of biopsies collected after birth. Although WGA inevitably leads to a random loss of information and to the introduction of erroneous genotypes, following genomic imputation the resulting genetic index of both sources of DNA were highly correlated (r = 0.99, P<0.001).

Conclusion

It is possible to generate high-quality DNA in sufficient quantities for successful genome-wide genotyping starting from an early embryo biopsy. However, imputation from parental and population genotypes is a requirement for completing and correcting genotypic data. Judicious selection of the WGA platform, careful handling of the samples and genomic imputation together, make it possible to perform extremely reliable genomic evaluations for pre-transfer embryos.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-889) contains supplementary material, which is available to authorized users.     

Validation and assessment of variant calling pipelines for next-generation sequencing

Background

The processing and analysis of the large scale data generated by next-generation sequencing (NGS) experiments is challenging and is a burgeoning area of new methods development. Several new bioinformatics tools have been developed for calling sequence variants from NGS data. Here, we validate the variant calling of these tools and compare their relative accuracy to determine which data processing pipeline is optimal.

Results

We developed a unified pipeline for processing NGS data that encompasses four modules: mapping, filtering, realignment and recalibration, and variant calling. We processed 130 subjects from an ongoing whole exome sequencing study through this pipeline. To evaluate the accuracy of each module, we conducted a series of comparisons between the single nucleotide variant (SNV) calls from the NGS data and either gold-standard Sanger sequencing on a total of 700 variants or array genotyping data on a total of 9,935 single-nucleotide polymorphisms. A head to head comparison showed that Genome Analysis Toolkit (GATK) provided more accurate calls than SAMtools (positive predictive value of 92.55% vs. 80.35%, respectively). Realignment of mapped reads and recalibration of base quality scores before SNV calling proved to be crucial to accurate variant calling. GATK HaplotypeCaller algorithm for variant calling outperformed the UnifiedGenotype algorithm. We also showed a relationship between mapping quality, read depth and allele balance, and SNV call accuracy. However, if best practices are used in data processing, then additional filtering based on these metrics provides little gains and accuracies of >99% are achievable.

Conclusions

Our findings will help to determine the best approach for processing NGS data to confidently call variants for downstream analyses. To enable others to implement and replicate our results, all of our codes are freely available at http://metamoodics.org/wes.

     

Modelling Individual Differences in the Form of Pavlovian Conditioned Approach Responses: A Dual Learning Systems Approach with Factored Representations

Reinforcement Learning has greatly influenced models of conditioning, providing powerful explanations of acquired behaviour and underlying physiological observations. However, in recent autoshaping experiments in rats, variation in the form of Pavlovian conditioned responses (CRs) and associated dopamine activity, have questioned the classical hypothesis that phasic dopamine activity corresponds to a reward prediction error-like signal arising from a classical Model-Free system, necessary for Pavlovian conditioning. Over the course of Pavlovian conditioning using food as the unconditioned stimulus (US), some rats (sign-trackers) come to approach and engage the conditioned stimulus (CS) itself – a lever – more and more avidly, whereas other rats (goal-trackers) learn to approach the location of food delivery upon CS presentation. Importantly, although both sign-trackers and goal-trackers learn the CS-US association equally well, only in sign-trackers does phasic dopamine activity show classical reward prediction error-like bursts. Furthermore, neither the acquisition nor the expression of a goal-tracking CR is dopamine-dependent. Here we present a computational model that can account for such individual variations. We show that a combination of a Model-Based system and a revised Model-Free system can account for the development of distinct CRs in rats. Moreover, we show that revising a classical Model-Free system to individually process stimuli by using factored representations can explain why classical dopaminergic patterns may be observed for some rats and not for others depending on the CR they develop. In addition, the model can account for other behavioural and pharmacological results obtained using the same, or similar, autoshaping procedures. Finally, the model makes it possible to draw a set of experimental predictions that may be verified in a modified experimental protocol. We suggest that further investigation of factored representations in computational neuroscience studies may be useful.     

Curcumin Chemosensitizes 5-Fluorouracil Resistant MMR-Deficient Human Colon Cancer Cells in High Density Cultures

Objective

Treatment of colorectal cancer (CRC) remains a clinical challenge, as more than 15% of patients are resistant to 5-Fluorouracil (5-FU)-based chemotherapeutic regimens, and tumor recurrence rates can be as high as 50–60%. Cancer stem cells (CSC) are capable of surviving conventional chemotherapies that permits regeneration of original tumors. Therefore, we investigated the effectiveness of 5-FU and plant polyphenol (curcumin) in context of DNA mismatch repair (MMR) status and CSC activity in 3D cultures of CRC cells.

Methods

High density 3D cultures of CRC cell lines HCT116, HCT116+ch3 (complemented with chromosome 3) and their corresponding isogenic 5-FU-chemo-resistant derivative clones (HCT116R, HCT116+ch3R) were treated with 5-FU either without or with curcumin in time- and dose-dependent assays.

Results

Pre-treatment with curcumin significantly enhanced the effect of 5-FU on HCT116R and HCR116+ch3R cells, in contrast to 5-FU alone as evidenced by increased disintegration of colonospheres, enhanced apoptosis and by inhibiting their growth. Curcumin and/or 5-FU strongly affected MMR-deficient CRC cells in high density cultures, however MMR-proficient CRC cells were more sensitive. These effects of curcumin in enhancing chemosensitivity to 5-FU were further supported by its ability to effectively suppress CSC pools as evidenced by decreased number of CSC marker positive cells, highlighting the suitability of this 3D culture model for evaluating CSC marker expression in a close to vivo setting.

Conclusion

Our results illustrate novel and previously unrecognized effects of curcumin in enhancing chemosensitization to 5-FU-based chemotherapy on DNA MMR-deficient and their chemo-resistant counterparts by targeting the CSC sub-population. (246 words in abstract).     

Antiproliferative Effects and Mechanisms of Liver X Receptor Ligands in Pancreatic Ductal Adenocarcinoma Cells

Pancreatic ductal adenocarcinoma (PDAC) is difficult to detect early and is often resistant to standard chemotherapeutic options, contributing to extremely poor disease outcomes. Members of the nuclear receptor superfamily carry out essential biological functions such as hormone signaling and are successfully targeted in the treatment of endocrine-related malignancies. Liver X receptors (LXRs) are nuclear receptors that regulate cholesterol homeostasis, lipid metabolism, and inflammation, and LXR agonists have been developed to regulate LXR function in these processes. Intriguingly, these compounds also exhibit antiproliferative activity in diverse types of cancer cells. In this study, LXR agonist treatments disrupted proliferation, cell-cycle progression, and colony-formation of PDAC cells. At the molecular level, treatments downregulated expression of proteins involved in cell cycle progression and growth factor signaling. Microarray experiments further revealed changes in expression profiles of multiple gene networks involved in biological processes and pathways essential for cell growth and proliferation following LXR activation. These results establish the antiproliferative effects of LXR agonists and potential mechanisms of action in PDAC cells and provide evidence for their potential application in the prevention and treatment of PDAC.     

Magnetic nanoparticle-based immunosensor for electrochemical detection of hepatitis B surface antigen

An electrochemical immunosensor was developed for the detection of hepatitis B surface antigen (HBsAg). The biotinylated hepatitis B surface antibody was immobilized on streptavidin magnetic nanoparticles and used for targeting the HBsAg. By the addition of horseradish peroxidase conjugated with secondary antibody (HRP–HBsAb), a sandwich-type immunoassay format was formed. Aminophenol as substrate for conjugated HRP was enzymatically changed into 3-aminophenoxazone (3-APZ). This electroactive enzymatic production (3-APZ) was transferred into an electrochemical cell and monitored by cyclic voltammetry. Under optimal conditions, the cathodic current response of 3-APZ, which was proportional to the HBsAg concentration, was measured by a glassy carbon electrode. The immunosensor response was linear toward HBsAg in the concentration range from 0.001 to 0.015 ng/ml with a detection limit of 0.9 pg/ml at a signal/noise ratio of 3.