A method to improve protein subcellular localization prediction by integrating various biological data sources

<p>Abstract</p> <p>Background</p> <p>Protein subcellular localization is crucial information to elucidate protein functions. Owing to the need for large-scale genome analysis, computational method for efficiently predicting protein subcellular localization is highly required. Although many previous works have been done for this task, the problem is still challenging due to several reasons: the number of subcellular locations in practice is large; distribution of protein in locations is imbalanced, that is the number of protein in each location remarkably different; and there are many proteins located in multiple locations. Thus it is necessary to explore new features and appropriate classification methods to improve the prediction performance.</p> <p>Results</p> <p>In this paper we propose a new predicting method which combines two key ideas: 1) Information of neighbour proteins in a probabilistic gene network is integrated to enrich the prediction features. 2) Fuzzy k-NN, a classification method based on fuzzy set theory is applied to predict protein locating in multiple sites. Experiment was conducted on a dataset consisting of 22 locations from Budding yeast proteins and significant improvement was observed.</p> <p>Conclusion</p> <p>Our results suggest that the neighbourhood information from functional gene networks is predictive to subcellular localization. The proposed method thus can be integrated and complementary to other available prediction methods.</p

Snap evaporation of droplets on smooth topographies

Droplet evaporation on solid surfaces is important in many applications including printing, micro-patterning and cooling. While seemingly simple, the configuration of evaporating droplets on solids is difficult to predict and control. This is because evaporation typically proceeds as a “stick-slip” sequence—a combination of pinning and de-pinning events dominated by static friction or “pinning”, caused by microscopic surface roughness. Here we show how smooth, pinning-free, solid surfaces of non-planar topography promote a different process called snap evaporation. During snap evaporation a droplet follows a reproducible sequence of configurations, consisting of a quasi-static phase-change controlled by mass diffusion interrupted by out-of-equilibrium snaps. Snaps are triggered by bifurcations of the equilibrium droplet shape mediated by the underlying non-planar solid. Because the evolution of droplets during snap evaporation is controlled by a smooth topography, and not by surface roughness, our ideas can inspire programmable surfaces that manage liquids in heat- and mass-transfer applications

An incremental approach to automated protein localisation

Tscherepanow M, Jensen N, Kummert F. An incremental approach to automated protein localisation. BMC Bioinformatics. 2008;9(1): 445.Background: The subcellular localisation of proteins in intact living cells is an important means for gaining information about protein functions. Even dynamic processes can be captured, which can barely be predicted based on amino acid sequences. Besides increasing our knowledge about intracellular processes, this information facilitates the development of innovative therapies and new diagnostic methods. In order to perform such a localisation, the proteins under analysis are usually fused with a fluorescent protein. So, they can be observed by means of a fluorescence microscope and analysed. In recent years, several automated methods have been proposed for performing such analyses. Here, two different types of approaches can be distinguished: techniques which enable the recognition of a fixed set of protein locations and methods that identify new ones. To our knowledge, a combination of both approaches – i.e. a technique, which enables supervised learning using a known set of protein locations and is able to identify and incorporate new protein locations afterwards – has not been presented yet. Furthermore, associated problems, e.g. the recognition of cells to be analysed, have usually been neglected. Results: We introduce a novel approach to automated protein localisation in living cells. In contrast to well-known techniques, the protein localisation technique presented in this article aims at combining the two types of approaches described above: After an automatic identification of unknown protein locations, a potential user is enabled to incorporate them into the pre-trained system. An incremental neural network allows the classification of a fixed set of protein location as well as the detection, clustering and incorporation of additional patterns that occur during an experiment. Here, the proposed technique achieves promising results with respect to both tasks. In addition, the protein localisation procedure has been adapted to an existing cell recognition approach. Therefore, it is especially well-suited for high-throughput investigations where user interactions have to be avoided. Conclusion: We have shown that several aspects required for developing an automatic protein localisation technique – namely the recognition of cells, the classification of protein distribution patterns into a set of learnt protein locations, and the detection and learning of new locations – can be combined successfully. So, the proposed method constitutes a crucial step to render image-based protein localisation techniques amenable to large-scale experiments

Autism as a disorder of neural information processing: directions for research and targets for therapy

The broad variation in phenotypes and severities within autism spectrum disorders suggests the involvement of multiple predisposing factors, interacting in complex ways with normal developmental courses and gradients. Identification of these factors, and the common developmental path into which theyfeed, is hampered bythe large degrees of convergence from causal factors to altered brain development, and divergence from abnormal brain development into altered cognition and behaviour. Genetic, neurochemical, neuroimaging and behavioural findings on autism, as well as studies of normal development and of genetic syndromes that share symptoms with autism, offer hypotheses as to the nature of causal factors and their possible effects on the structure and dynamics of neural systems. Such alterations in neural properties may in turn perturb activity-dependent development, giving rise to a complex behavioural syndrome many steps removed from the root causes. Animal models based on genetic, neurochemical, neurophysiological, and behavioural manipulations offer the possibility of exploring these developmental processes in detail, as do human studies addressing endophenotypes beyond the diagnosis itself

Enhanced neuronal Met signalling levels in ALS mice delay disease onset

Signalling by receptor tyrosine kinases (RTKs) coordinates basic cellular processes during development and in adulthood. Whereas aberrant RTK signalling can lead to cancer, reactivation of RTKs is often found following stress or cell damage. This has led to the common belief that RTKs can counteract degenerative processes and so strategies to exploit them for therapy have been extensively explored. An understanding of how RTK stimuli act at cellular levels is needed, however, to evaluate their mechanism of therapeutic action. In this study, we genetically explored the biological and functional significance of enhanced signalling by the Met RTK in neurons, in the context of a neurodegenerative disease. Conditional met-transgenic mice, namely Rosa26LacZ−stop−Met, have been engineered to trigger increased Met signalling in a temporal and tissue-specific regulated manner. Enhancing Met levels in neurons does not affect either motor neuron (MN) development or maintenance. In contrast, increased neuronal Met in amyotrophic lateral sclerosis (ALS) mice prolongs life span, retards MN loss, and ameliorates motor performance, by selectively delaying disease onset. Thus, our studies highlight the properties of RTKs to counteract toxic signals in a disease characterized by dysfunction of multiple cell types by acting in MNs. Moreover, they emphasize the relevance of genetically assessing the effectiveness of agents targeting neurons during ALS evolution

TESTLoc: protein subcellular localization prediction from EST data

Abstract Background The eukaryotic cell has an intricate architecture with compartments and substructures dedicated to particular biological processes. Knowing the subcellular location of proteins not only indicates how bio-processes are organized in different cellular compartments, but also contributes to unravelling the function of individual proteins. Computational localization prediction is possible based on sequence information alone, and has been successfully applied to proteins from virtually all subcellular compartments and all domains of life. However, we realized that current prediction tools do not perform well on partial protein sequences such as those inferred from Expressed Sequence Tag (EST) data, limiting the exploitation of the large and taxonomically most comprehensive body of sequence information from eukaryotes. Results We developed a new predictor, TESTLoc, suited for subcellular localization prediction of proteins based on their partial sequence conceptually translated from ESTs (EST-peptides). Support Vector Machine (SVM) is used as computational method and EST-peptides are represented by different features such as amino acid composition and physicochemical properties. When TESTLoc was applied to the most challenging test case (plant data), it yielded high accuracy (~85%). Conclusions TESTLoc is a localization prediction tool tailored for EST data. It provides a variety of models for the users to choose from, and is available for download at http://megasun.bch.umontreal.ca/~shenyq/TESTLoc/TESTLoc.html</p

Collagen fleeces do not improve colonic anastomotic strength but increase bowel obstructions in an experimental rat model

To investigate whether a collagen fleece kept in place by fibrin glue might seal off a colorectal anastomosis, provide reinforcement, and subsequently improve anastomotic healing. Wistar rats underwent a 1-cm left-sided colonic resection followed by a 4-suture end-to-end anastomosis. They were then randomly assigned to one of three treatment groups: no additional intervention (control, n = 20), the anastomosis covered with fibrin glue (fibrin glue, n = 20), the anastomosis covered with a collagen fleece, kept in place with fibrin glue (collagen fleece, n = 21). At either 3 or 7 days follow-up, anastomotic bursting pressure was measured and tissue was obtained for histology and collagen content assessment after which animals were sacrificed. Three rats in the control (15%), three in the fibrin glue (15%), and one in the collagen group (4.8%) died due to anastomotic complications (P = 0.497). Anastomotic bursting pressures were not significantly different between groups at 3 and 7 days follow-up (P = 0.659 and P = 0.427, respectively). However, bowel obstructions occurred significantly more often in the collagen group compared to the control group (14/21 vs. 3/20, P = 0.003). Collagen contents were not different between groups, but histology showed a more severe inflammation in the collagen group compared to the other groups at both 3 and 7 days follow-up. A collagen fleece kept in place by fibrin glue does not improve healing of colonic anastomoses in rats. Moreover, this technique induces significantly more bowel obstructions in rats, warranting further study before being translated to a clinical settin

Narrow-band imaging does not improve detection of colorectal polyps when compared to conventional colonoscopy: a randomized controlled trial and meta-analysis of published studies

<p>Abstract</p> <p>Background</p> <p>A colonoscopy may frequently miss polyps and cancers. A number of techniques have emerged to improve visualization and to reduce the rate of adenoma miss.</p> <p>Methods</p> <p>We conducted a randomized controlled trial (RCT) in two clinics of the Gastrointestinal Department of the Sanitas University Foundation in Bogota, Colombia. Eligible adult patients presenting for screening or diagnostic elective colonoscopy were randomlsy allocated to undergo conventional colonoscopy or narrow-band imaging (NBI) during instrument withdrawal by three experienced endoscopists. For the systematic review, studies were identified from the Cochrane Library, PUBMED and LILACS and assessed using the Cochrane risk of bias tool.</p> <p>Results</p> <p>We enrolled a total of 482 patients (62.5% female), with a mean age of 58.33 years (SD 12.91); 241 into the intervention (NBI) colonoscopy and 241 into the conventional colonoscopy group. Most patients presented for diagnostic colonoscopy (75.3%). The overall rate of polyp detection was significantly higher in the conventional group compared to the NBI group (RR 0.75, 95%CI 0.60 to 0.96). However, no significant differences were found in the mean number of polyps (MD -0.1; 95%CI -0.25 to 0.05), and the mean number of adenomas (MD 0.04 95%CI -0.09 to 0.17). Meta-analysis of studies (regardless of indication) did not find any significant differences in the mean number of polyps (5 RCT, 2479 participants; WMD -0.07 95% CI -0.21 to 0.07; I2 68%), the mean number of adenomas (8 RCT, 3517 participants; WMD -0.08 95% CI -0.17; 0.01 to I2 62%) and the rate of patients with at least one adenoma (8 RCT, 3512 participants, RR 0.96 95% CI 0.88 to 1,04;I2 0%).</p> <p>Conclusion</p> <p>NBI does not improve detection of colorectal polyps when compared to conventional colonoscopy (Australian New Zealand Clinical Trials Registry <a href="http://www.anzctr.org.au/ACTRN12610000456055.aspx">ACTRN12610000456055</a>).</p

Oscillatory Dynamics of Cell Cycle Proteins in Single Yeast Cells Analyzed by Imaging Cytometry

Progression through the cell division cycle is orchestrated by a complex network of interacting genes and proteins. Some of these proteins are known to fluctuate periodically during the cell cycle, but a systematic study of the fluctuations of a broad sample of cell-cycle proteins has not been made until now. Using time-lapse fluorescence microscopy, we profiled 16 strains of budding yeast, each containing GFP fused to a single gene involved in cell cycle regulation. The dynamics of protein abundance and localization were characterized by extracting the amplitude, period, and other indicators from a series of images. Oscillations of protein abundance could clearly be identified for Cdc15, Clb2, Cln1, Cln2, Mcm1, Net1, Sic1, and Whi5. The period of oscillation of the fluorescently tagged proteins is generally in good agreement with the inter-bud time. The very strong oscillations of Net1 and Mcm1 expression are remarkable since little is known about the temporal expression of these genes. By collecting data from large samples of single cells, we quantified some aspects of cell-to-cell variability due presumably to intrinsic and extrinsic noise affecting the cell cycle