Nucleolar localization of aprataxin is dependent on interaction with nucleolin and on active ribosomal DNA transcription

The APTX gene, mutated in patients with the neurological disorder ataxia with oculomotor apraxia type 1 (AOA1), encodes a novel protein aprataxin. We describe here, the interaction and interdependence between aprataxin and several nucleolar proteins, including nucleolin, nucleophosmin and upstream binding factor-1 (UBF-1), involved in ribosomal RNA (rRNA) synthesis and cellular stress signalling. Interaction between aprataxin and nucleolin occurred through their respective N-terminal regions. In AOA1 cells lacking aprataxin, the stability of nucleolin was significantly reduced. On the other hand, down-regulation of nucleolin by RNA interference did not affect aprataxin protein levels but abolished its nucleolar localization suggesting that the interaction with nucleolin is involved in its nucleolar targeting. GFP-aprataxin fusion protein co-localized with nucleolin, nucleophosmin and UBF-1 in nucleoli and inhibition of ribosomal DNA transcription altered the distribution of aprataxin in the nucleolus, suggesting that the nature of the nucleolar localization of aprataxin is also dependent on ongoing rRNA synthesis. In vivo rRNA synthesis analysis showed only a minor decrease in AOA1 cells when compared with controls cells. These results demonstrate a cross-dependence between aprataxin and nucleolin in the nucleolus and while aprataxin does not appear to be directly involved in rRNA synthesis its nucleolar localization is dependent on this synthesis.

Subcellular localization of mammalian type II membrane proteins

Application of a computational membrane organization prediction pipeline, MemO, identified putative type II membrane proteins as proteins predicted to encode a single alpha-helical transmembrane domain (TMD) and no signal peptides. MemO was applied to RIKEN's mouse isoform protein set to identify 1436 non-overlapping genomic regions or transcriptional units (TUs), which encode exclusively type II membrane proteins. Proteins with overlapping predicted InterPro and TMDs were reviewed to discard false positive predictions resulting in a dataset comprised of 1831 transcripts in 1408 TUs. This dataset was used to develop a systematic protocol to document subcellular localization of type II membrane proteins. This approach combines mining of published literature to identify subcellular localization data and a high-throughput, polymerase chain reaction (PCR)-based approach to experimentally characterize subcellular localization. These approaches have provided localization data for 244 and 169 proteins. Type II membrane proteins are localized to all major organelle compartments; however, some biases were observed towards the early secretory pathway and punctate structures. Collectively, this study reports the subcellular localization of 26% of the defined dataset. All reported localization data are presented in the LOCATE database (http://www.locate.imb.uq.edu.au).

Endothelin A receptor localization in the internal mammary artery

Introduction: The vasoconstricting peptide endothelin-1 (ET-1) binds two G-protein-coupled receptor subtypes, the Endothelin A (ETA) and Endothelin B (ETB) receptors. The ETB receptor subtype has been predominantly localised to the arterial and venous endothelial cells both in-vivo and in culture. Stimulation of ET-1 through this receptor subtype can modulate the expression of endothelial nitric oxide and accelerate endothelial cell wound healing. In comparison the ETA receptor is abundantly expressed in medial vascular smooth muscle cells and mediates the vasoconstrictor action of ET-1 and is thought to play a key role in angiogenesis. Aims: To determine the levels of ETA receptor expression and localisation in the internal mammary artery (IMA). Methods: Twenty-four IMA sections were examined from patients undergoing coronary artery bypass (CABG) surgery (5F; 19M; mean age 67 years). And 14 organ donor IMA specimens were used as controls (7M; 7F; mean age 45 years. The tissue was fixed in formalin and processed for histology. Immunohistochemistry was performed on cross-sections of the left distal IMA to assess the areas of ETA receptor staining. The percentage are of ETA receptor staining in the media was calculated using image analysis software connected to an optical microscope and semiquantitative assessment was used to grade staining intensity, that is, mild (+), moderate (++) and strong (+++). Results: ETA receptor staining was significantly elevated in the media of the CABG specimens compared with the donor controls (46.88+/11.52% Vs 18.58+/7.65%, P = .0001). Interestingly, the endothelium (++) of the IMA, as well as the small microvessels in the adventitia (+++) stained positive for ETA receptor expression. Without using a haematoxylin counterstain, the nuclei of the cell stained more intensely (+++) with respect to the cytoplasm in both the medial smooth muscle (++) and endothelial cells (++). Fibroblasts in the medial adventitia junction were also positive for ETA receptor expression (+++). Further, this receptor subtype was also strongly expressed by inflammatory cells (monocytes and macrophages). Conclusions: These results demonstrate that the ETA receptor expression is increased in the medial SMC layer of the CABG IMA specimens and also present in the endothelium, vasa vasorum, fibroblasts and inflammatory cell types. Thus it is possible that in addition to affecting vascular tone, ET-1 may play an important role in IMA remodelling.

Biologically inspired visual landmark processing for simultaneous localization and mapping

This paper illustrates a method for finding useful visual landmarks for performing simultaneous localization and mapping (SLAM). The method is based loosely on biological principles, using layers of filtering and pooling to create learned templates that correspond to different views of the environment. Rather than using a set of landmarks and reporting range and bearing to the landmark, this system maps views to poses. The challenge is to produce a system that produces the same view for small changes in robot pose, but provides different views for larger changes in pose. The method has been developed to interface with the RatSLAM system, a biologically inspired method of SLAM. The paper describes the method of learning and recalling visual landmarks in detail, and shows the performance of the visual system in real robot tests.

A modified particle filter for simultaneous robot localization and landmark tracking in an indoor environment

This paper presents the implementation of a modified particle filter for vision-based simultaneous localization and mapping of an autonomous robot in a structured indoor environment. Through this method, artificial landmarks such as multi-coloured cylinders can be tracked with a camera mounted on the robot, and the position of the robot can be estimated at the same time. Experimental results in simulation and in real environments show that this approach has advantages over the extended Kalman filter with ambiguous data association and various levels of odometric noise.

Evaluation and comparison of mammalian subcellular localization prediction methods

Background: Determination of the subcellular location of a protein is essential to understanding its biochemical function. This information can provide insight into the function of hypothetical or novel proteins. These data are difficult to obtain experimentally but have become especially important since many whole genome sequencing projects have been finished and many resulting protein sequences are still lacking detailed functional information. In order to address this paucity of data, many computational prediction methods have been developed. However, these methods have varying levels of accuracy and perform differently based on the sequences that are presented to the underlying algorithm. It is therefore useful to compare these methods and monitor their performance. Results: In order to perform a comprehensive survey of prediction methods, we selected only methods that accepted large batches of protein sequences, were publicly available, and were able to predict localization to at least nine of the major subcellular locations (nucleus, cytosol, mitochondrion, extracellular region, plasma membrane, Golgi apparatus, endoplasmic reticulum (ER), peroxisome, and lysosome). The selected methods were CELLO, MultiLoc, Proteome Analyst, pTarget and WoLF PSORT. These methods were evaluated using 3763 mouse proteins from SwissProt that represent the source of the training sets used in development of the individual methods. In addition, an independent evaluation set of 2145 mouse proteins from LOCATE with a bias towards the subcellular localization underrepresented in SwissProt was used. The sensitivity and specificity were calculated for each method and compared to a theoretical value based on what might be observed by random chance. Conclusion: No individual method had a sufficient level of sensitivity across both evaluation sets that would enable reliable application to hypothetical proteins. All methods showed lower performance on the LOCATE dataset and variable performance on individual subcellular localizations was observed. Proteins localized to the secretory pathway were the most difficult to predict, while nuclear and extracellular proteins were predicted with the highest sensitivity.

Probabilistic visual recognition of artificial landmarks for simultaneous localization and mapping

Probabilistic robotics most often applied to the problem of simultaneous localisation and mapping (SLAM), requires measures of uncertainty to accompany observations of the environment. This paper describes how uncertainty can be characterised for a vision system that locates coloured landmarks in a typical laboratory environment. The paper describes a model of the uncertainty in segmentation, the internal cameral model and the mounting of the camera on the robot. It explains the implementation of the system on a laboratory robot, and provides experimental results that show the coherence of the uncertainty model.