Protein evolution is faster outside the cell

Some proteins are highly conserved across all species, whereas others diverge significantly even between closely related species. Attempts have been made to correlate the rate of protein evolution to amino acid composition, protein dispensability, and the number of protein-protein interactions, but in all cases, conflicting studies have shown that the theories are hard to confirm experimentally. The only correlation that is undisputed so far is that highly/broadly expressed proteins seem to evolve at a lower rate. Consequently, it has been suggested that correlations between evolution rate and factors like protein dispensability or the number of protein-protein interactions could be just secondary effects due to differences in expression. The purpose of this study was to analyze mammalian proteins/genes with known subcellular location for variations in evolution rates. We show that proteins that are exported (extracellular proteins) evolve faster than proteins that reside inside the cell (intracellular proteins). We find weak, but significant, correlations between evolution rates and expression levels, percentage of tissues in which the proteins are expressed (expression broadness), and the number of protein interaction partners. More important, we show that the observed difference in evolution rate between extra- and intracellular proteins is largely independent of expression levels, expression broadness, and the number of protein-protein interactions. We also find that the difference is not caused by an overrepresentation of immunological proteins or disulfide bridge-containing proteins among the extracellular data set. We conclude that the subcellular location of a mammalian protein has a larger effect on its evolution rate than any of the other factors studied in this paper, including expression levels/patterns. We observe a difference in evolution rates between extracellular and intracellular proteins for a yeast data set as well and again show that it is completely independent of expression levels.     

Prediction of protein subcellular localization

Because the protein's function is usually related to its subcellular localization, the ability to predict subcellular localization directly from protein sequences will be useful for inferring protein functions. Recent years have seen a surging interest in the development of novel computational tools to predict subcellular localization. At present, these approaches, based on a wide range of algorithms, have achieved varying degrees of success for specific organisms and for certain localization categories. A number of authors have noticed that sequence similarity is useful in predicting subcellular localization. For example, Nair and Rost (Protein Sci 2002;11:2836-2847) have carried out extensive analysis of the relation between sequence similarity and identity in subcellular localization, and have found a close relationship between them above a certain similarity threshold. However, many existing benchmark data sets used for the prediction accuracy assessment contain highly homologous sequences-some data sets comprising sequences up to 80-90% sequence identity. Using these benchmark test data will surely lead to overestimation of the performance of the methods considered. Here, we develop an approach based on a two-level support vector machine (SVM) system: the first level comprises a number of SVM classifiers, each based on a specific type of feature vectors derived from sequences; the second level SVM classifier functions as the jury machine to generate the probability distribution of decisions for possible localizations. We compare our approach with a global sequence alignment approach and other existing approaches for two benchmark data sets-one comprising prokaryotic sequences and the other eukaryotic sequences. Furthermore, we carried out all-against-all sequence alignment for several data sets to investigate the relationship between sequence homology and subcellular localization. Our results, which are consistent with previous studies, indicate that the homology search approach performs well down to 30% sequence identity, although its performance deteriorates considerably for sequences sharing lower sequence identity. A data set of high homology levels will undoubtedly lead to biased assessment of the performances of the predictive approaches-especially those relying on homology search or sequence annotations. Our two-level classification system based on SVM does not rely on homology search; therefore, its performance remains relatively unaffected by sequence homology. When compared with other approaches, our approach performed significantly better. Furthermore, we also develop a practical hybrid method, which combines the two-level SVM classifier and the homology search method, as a general tool for the sequence annotation of subcellular localization.     

Kinase activity and subcellular distribution of a chimeric green fluorescent protein-tagged Janus kinase 2

Summary Janus kinase 2 (JAK2) is an essential intracellular signal transducer for numerous cytokines and hormones. To examine how JAK2 structural modifications can affect cellular physiology, we created expression vectors for chimeric proteins containing an enhanced green fluorescent protein (EGFP) fused to rat JAK2 (EGFP/rJAK2), and a kinase-inactive variant, EGFP/rJAK2(K882E). The properties of EGFP/rJAK2 were examined following transient transfection of COS-7 cells. EGFP/rJAK2 was expressed throughout the cell, and was found in subcellular membrane, cytosolic and nuclear fractions. Interestingly, EGFP/rJAK2 phosphorylated other proteins in situ without additional cytokine stimulation. Furthermore, despite a much higher level of tyrosine phosphorylation arising from in situ autophosphorylation, the in vitro radiolabelling autokinase activity of EGFP/rJAK2 was significantly less than that of the endogenous JAK2. These results reveal a technical limitation of the application of the “conventional” in vitro radiolabelling autokinase assay to hyperphosphorylated forms of the enzyme and illustrate the potential weaknesses in individual assays commonly used to determine JAK2’s enzymatic activity and subcellular distribution. We also suggest that the EGFP/rJAK2 model can be very useful in studying JAK2-related cancers, because its ubiquitous distribution and abnormal constitutive hyperphosphorylation may distinguish it from the cytokine-regulated, membrane-proximal form of JAK2 associated with normal physiology.     

Rapid,combinatorial analysis of membrane compartments in intact plants with a multicolor marker set

Plant membrane compartments and trafficking pathways are highly complex, and are often distinct from those of animals and fungi. Progress has been made in defining trafficking in plants using transient expression systems. However, many processes require a precise understanding of plant membrane trafficking in a developmental context, and in diverse, specialized cell types. These include defense responses to pathogens, regulation of transporter accumulation in plant nutrition or polar auxin transport in development. In all of these cases a central role is played by the endosomal membrane system, which, however, is the most divergent and ill‐defined aspect of plant cell compartmentation. We have designed a new vector series, and have generated a large number of stably transformed plants expressing membrane protein fusions to spectrally distinct, fluorescent tags. We selected lines with distinct subcellular localization patterns, and stable, non‐toxic expression. We demonstrate the power of this multicolor ‘Wave’ marker set for rapid, combinatorial analysis of plant cell membrane compartments, both in live‐imaging and immunoelectron microscopy. Among other findings, our systematic co‐localization analysis revealed that a class of plant Rab1‐homologs has a much more extended localization than was previously assumed, and also localizes to trans‐Golgi/endosomal compartments. Constructs that can be transformed into any genetic background or species, as well as seeds from transgenic Arabidopsis plants, will be freely available, and will promote rapid progress in diverse areas of plant cell biology.     

Protein mislocalization in plant cells using a GFP‐binding chromobody

A key challenge in cell biology is to directly link protein localization to function. The green fluorescent protein (GFP)‐binding protein, GBP, is a 13‐kDa soluble protein derived from a llama heavy chain antibody that binds with high affinity to GFP as well as to some GFP variants such as yellow fluorescent protein (YFP). A GBP fusion to the red fluorescent protein (RFP), a molecule termed a chromobody, was previously used to trace in vivo the localization of various animal antigens. In this study, we extend the use of chromobody technology to plant cells and develop several applications for the in vivo study of GFP‐tagged plant proteins. We took advantage of Agrobacterium tumefaciens‐mediated transient expression assays (agroinfiltration) and virus expression vectors (agroinfection) to express functional GBP:RFP fusion (chromobody) in the model plant Nicotiana benthamiana. We showed that the chromobody is effective in binding GFP‐ and YFP‐tagged proteins in planta. Most interestingly, GBP:RFP can be applied to interfere with the function of GFP fusion protein and to mislocalize (trap) GFP fusions to the plant cytoplasm in order to alter the phenotype mediated by the targeted proteins. Chromobody technology, therefore, represents a new alternative technique for protein interference that can directly link localization of plant proteins to in vivo function.     

植物脂肪氧化酶的研究进展

植物脂肪氧化酶(LOX)是一个多基因家族, 是由单一的多肽链组成的含有非血红素铁、不含硫的过氧化物酶。LOX催化具有顺, 顺-1, 4-戊二烯结构的多元不饱和脂肪酸的双加氧反应。植物中, 不同脂肪氧化酶的最适pH、pI、底物和产物特异性、时空表达特性、亚细胞定位等存在差异。LOX参与的生理过程涉及损伤、病原攻击、种子萌芽、果实熟化、植物衰老、脱落酸和茉莉酸合成, LOX也在正常的植物生长和生殖生长过程中作为营养储藏蛋白, 参与脂类迁移、响应营养胁迫、调节“源”与“库”的分配。对LOX家族的深入理解,将有助于LOX在作物新品种的选育、新型植保素的开发、食品加工等方面得到广泛的应用。