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Mitochondria fulfil essential functions in respiration and metabolism as well as regulating stress responses and apoptosis. Most native mitochondrial proteins are encoded by nuclear genes and are imported into mitochondria via one of several receptors that recognize N-terminal signal peptides. The targeting of recombinant proteins to mitochondria therefore requires the presence of an appropriate N-terminal peptide, but little is known about mitochondrial import in monocotyledonous plants such as rice (Oryza sativa). To gain insight into this phenomenon, we targeted nuclear-encoded enhanced green fluorescent protein (eGFP) to rice mitochondria using six mitochondrial pre-sequences with diverse phylogenetic origins, and investigated their effectiveness by immunoblot analysis as well as confocal and electron microscopy. We found that the ATPA and COX4 (Saccharomyces cerevisiae), SU9 (Neurospora crassa), pFA (Arabidopsis thaliana) and OsSCSb (Oryza sativa) peptides successfully directed most of the eGFP to the mitochondria, whereas the MTS2 peptide (Nicotiana plumbaginifolia) showed little or no evidence of targeting ability even though it is a native plant sequence. Our data therefore indicate that the presence of particular recognition motifs may be required for mitochondrial targeting, whereas the phylogenetic origin of the pre-sequences probably does not play a key role in the success of mitochondrial targeting in dedifferentiated rice callus and plants.
相似文献Benthic surveys are a key component of monitoring and conservation efforts for coral reefs worldwide. While traditional image-based surveys rely on manual annotation of photographs to characterise benthic composition, automatic image annotation based on computer vision is becoming increasingly common. However, accurate classification of some benthic groups from reflectance images presents a challenge to local ecologists and computers alike. Most coral reef organisms produce one or a combination of fluorescent pigments, such as Green Fluorescent Protein (GFP)-like proteins found in corals, chlorophyll-a found in all photosynthetic organisms, and phycobiliproteins found in red macroalgae, crustose coralline algae (CCA) and cyanobacteria. Building on the potential of these pigments as a target for automatic image annotation, we developed a novel imaging method based on off-the-shelf components to improve classification of coral and other biotic substrates using a multi-excitation fluorescence (MEF) imaging system. We used RGB cameras to image the fluorescence emission of coral and algal pigments stimulated by narrow-waveband blue and green light, and then combined the information into three-channel pseudocolour images. Using a set of a priori rules defined by the relative pixel intensity produced in different channels, the method achieved successful classification of organisms into three categories based on the dominant fluorescent pigment expressed, facilitating discrimination of traditionally problematic groups. This work provides a conceptual foundation for future technological developments that will improve the cost, accuracy and speed of coral reef surveys.
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