EnDNA-Prot:identification of DNA-binding proteins by applying ensemble learning

DNA-binding proteins are crucial for various cellular processes, such as recognition of specific nucleotide, regulation of transcription, and regulation of gene expression. Developing an effective model for identifying DNA-binding proteins is an urgent research problem. Up to now, many methods have been proposed, but most of them focus on only one classifier and cannot make full use of the large number of negative samples to improve predicting performance. This study proposed a predictor called enDNA-Prot for DNA-binding protein identification by employing the ensemble learning technique. Experiential results showed that enDNA-Prot was comparable with DNA-Prot and outperformed DNAbinder and iDNA-Prot with performance improvement in the range of 3.97-9.52% in ACC and 0.08-0.19 in MCC. Furthermore, when the benchmark dataset was expanded with negative samples, the performance of enDNA-Prot outperformed the three existing methods by 2.83-16.63% in terms of ACC and 0.02-0.16 in terms of MCC. It indicated that enDNA-Prot is an effective method for DNA-binding protein identification and expanding training dataset with negative samples can improve its performance. For the convenience of the vast majority of experimental scientists, we developed a user-friendly web-server for enDNA-Prot which is freely accessible to the public. © 2014 Ruifeng Xu et al.

Identifying DNA-binding proteins by combining support vector machine and PSSM distance transformation

Background: DNA-binding proteins play a pivotal role in various intra- and extra-cellular activities ranging from DNA replication to gene expression control. Identification of DNA-binding proteins is one of the major challenges in the field of genome annotation. There have been several computational methods proposed in the literature to deal with the DNA-binding protein identification. However, most of them can't provide an invaluable knowledge base for our understanding of DNA-protein interactions. Results: We firstly presented a new protein sequence encoding method called PSSM Distance Transformation, and then constructed a DNA-binding protein identification method (SVM-PSSM-DT) by combining PSSM Distance Transformation with support vector machine (SVM). First, the PSSM profiles are generated by using the PSI-BLAST program to search the non-redundant (NR) database. Next, the PSSM profiles are transformed into uniform numeric representations appropriately by distance transformation scheme. Lastly, the resulting uniform numeric representations are inputted into a SVM classifier for prediction. Thus whether a sequence can bind to DNA or not can be determined. In benchmark test on 525 DNA-binding and 550 non DNA-binding proteins using jackknife validation, the present model achieved an ACC of 79.96%, MCC of 0.622 and AUC of 86.50%. This performance is considerably better than most of the existing state-of-the-art predictive methods. When tested on a recently constructed independent dataset PDB186, SVM-PSSM-DT also achieved the best performance with ACC of 80.00%, MCC of 0.647 and AUC of 87.40%, and outperformed some existing state-of-the-art methods. Conclusions: The experiment results demonstrate that PSSM Distance Transformation is an available protein sequence encoding method and SVM-PSSM-DT is a useful tool for identifying the DNA-binding proteins. A user-friendly web-server of SVM-PSSM-DT was constructed, which is freely accessible to the public at the web-site on http://bioinformatics.hitsz.edu.cn/PSSM-DT/.

Rapid tonicity induced re-localisation of endogenous aquaporin 4 in primary rat astrocytes - a therapeutic target for cytotoxic brain oedema?

It is estimated that 69-75 million people worldwide will suffer a traumatic brain injury (TBI) or stroke each year. Brain oedema caused by TBI or following a stroke, together with other disorders of the brain cost Europe €770 billion in 2014. Aquaporins (AQP) are transmembrane water channels involved in many physiologies and are responsible for the maintenance of water homeostasis. They react rapidly to changes in osmolarity by transporting water through their highly selective central pore to maintain tonicity and aid in cell volume regulation. We have previously shown that recombinant AQP1-GFP trafficking occurs in a proteinkinase C-microtubule dependant manner in HEK-293 cells in response to hypotonicity. This trafficking mechanism is also reliant on the presence of calcium and its messenger-binding protein calmodulin and results in increased cell surface expression of AQP1 in a time-scale of ~30 seconds. There is currently very little research into the trafficking mechanisms of endogenous AQPs in primary cells. AQP4 is the most abundantly expressed AQP within the brain, it is localised to the astrocytic end-feet, in contact with the blood vessels at the blood-brain-barrier. In situations where the exquisitely-tuned osmotic balance is disturbed, high water permeability can become detrimental. AQP4-mediated water influx causes rapid brain swelling, resulting in death or long term brain damage. Previous research has shown that AQP4 knock-out mice were protected from the formation of cytotoxic brain oedema in a stroke model, highlighting AQP4 as a key drug target for this pathology. As there are currently no treatments available to restrict the flow of water through AQP4 as all known inhibitors are either cytotoxic or non-specific, controlling the mechanisms involved in the regulation of AQP4 in the brain could provide a therapeutic solution to such diseases. Using cell surface biontinylation of endogenous AQP4 in primary rat astrocytes followed by neutraavidin based ELISA we have shown that AQP4 cell surface localisation increases by 2.7 fold after 5 minutes hypotonic treatment at around 85 mOsm/kg H2O. We have also shown that this rapid relocalisation of AQP4 is regulated by PKA, calmodulin, extra-cellular calcium and actin. In summary we have shown that rapid translocation of endogenous AQP4 occurs in primary rat astrocytes in response to hypotonic stimuli; this mechanism is PKA, calcium, actin and calmodulin dependant. AQP4 has the potential to provide a treatment for the development of brain oedema.