Protein Subcellular Localization Research Articles

Using the Arabidopsis Information Resource (TAIR) to Find Information About Arabidopsis Genes.

The Arabidopsis Information Resource (TAIR; http://arabidopsis.org) is a comprehensive web resource of Arabidopsis biology for plant scientists. TAIR curates and integrates information about genes, proteins, gene function, orthologs, gene expression, mutant phenotypes, biological materials such as clones and seed stocks, genetic markers, genetic and physical maps, genome organization, images of mutant plants, protein sub-cellular localizations, publications, and the research community. The various data types are extensively interconnected and can be accessed through a variety of web-based search and display tools. This article primarily focuses on some basic methods for searching, browsing, visualizing, and analyzing information about Arabidopsis genes and genomes. Additionally, we describe how members of the community can share data via JBrowse and the Generic Online Annotation Submission Tool (GOAT) in order to make their published research more accessible and visible. © 2022 Wiley Periodicals LLC. Basic Protocol 1: TAIR homepage, sitemap, and navigation Basic Protocol 2: Finding comprehensive information about Arabidopsis genes Basic Protocol 3: Using the Arabidopsis genome browser: JBrowse Basic Protocol 4: Using the Gene Ontology annotations for gene discovery and gene function analysis Basic Protocol 5: Using gene lists to download bulk datasets Basic Protocol 6: Using TAIR's analysis tools to find short sequences and motifs Basic Protocol 7: Using the TAIR generic online annotation tool (GOAT) to submit functional annotations for Arabidopsis (or any other species) genes Basic Protocol 8: Using PhyloGenes to visualize gene families and predict functions Basic Protocol 9: Using TAIR to browse Arabidopsis literature Basic Protocol 10: Using the synteny viewer to find and display syntenic regions from Arabidopsis and other plant species.

Genome-Wide Analysis and Expression Profiling of Glutathione Reductase Gene Family in Oat (Avena sativa) Indicate Their Responses to Abiotic Stress during Seed Imbibition

Abiotic stress disturbs plant cellular redox homeostasis, inhibiting seed germination and plant growth. This is a crucial limitation to crop yield. Glutathione reductase (GR) is an important component of the ascorbate-glutathione (AsA-GSH) cycle which is involved in multiple plant metabolic processes. In the present study, GRs in A. sativa (AsGRs) were selected to explore their molecular characterization, phylogenetic relationship, and RNA expression changes during seed imbibition under abiotic stress. Seven AsGR genes were identified and mapped on six chromosomes of A, C, and D subgenomes. Phylogenetic analysis and subcellular localization of AsGR proteins divided them into two sub-families, AsGR1 and AsGR2, which were predicted to be mainly located in cytoplasm, mitochondrion, and chloroplast. Cis-elements relevant to stress and hormone responses are distributed in promoter regions of AsGRs. Tissue-specific expression profiling showed that AsGR1 genes were highly expressed in roots, leaves, and seeds, while AsGR2 genes were highly expressed in leaves and seeds. Both AsGR1 and AsGR2 genes showed a decreasing-increasing expression trend during seed germination under non-stress conditions. In addition, their responses to drought, salt, cold, copper, H2O2, and ageing treatments were quite different during seed imbibition. Among the seven AsGR genes, AsGR1-A, AsGR1-C, AsGR2-A, and AsGR2-D responded more significantly, especially under drought, ageing, and H2O2 stress. This study has laid the ground for the functional characterization of GR and the improvement of oat stress tolerance and seed vigor.

ProtTrans: Toward Understanding the Language of Life Through Self-Supervised Learning

Computational biology and bioinformatics provide vast data gold-mines from protein sequences, ideal for Language Models (LMs) taken from Natural Language Processing (NLP). These LMs reach for new prediction frontiers at low inference costs. Here, we trained two auto-regressive models (Transformer-XL, XLNet) and four auto-encoder models (BERT, Albert, Electra, T5) on data from UniRef and BFD containing up to 393 billion amino acids. The protein LMs (pLMs) were trained on the Summit supercomputer using 5616 GPUs and TPU Pod up-to 1024 cores. Dimensionality reduction revealed that the raw pLM-embeddings from unlabeled data captured some biophysical features of protein sequences. We validated the advantage of using the embeddings as exclusive input for several subsequent tasks: (1) a per-residue (per-token) prediction of protein secondary structure (3-state accuracy Q3=81%-87%); (2) per-protein (pooling) predictions of protein sub-cellular location (ten-state accuracy: Q10=81%) and membrane versus water-soluble (2-state accuracy Q2=91%). For secondary structure, the most informative embeddings (ProtT5) for the first time outperformed the state-of-the-art without multiple sequence alignments (MSAs) or evolutionary information thereby bypassing expensive database searches. Taken together, the results implied that pLMs learned some of the grammar of the language of life. All our models are available through https://github.com/agemagician/ProtTrans.

Expression, Localization and Prognosis Association of MEP50 in Breast Cancer.

Simple SummaryThe arginine methyltransferase PRMT5 is an emerging therapeutic target for various cancers including breast cancer. In this study, we examine the expression and subcellular localization of its main cofactor, MEP50, in the different breast cancer subgroups. High levels of MEP50 are found in TNBC and associated with better recurrence-free survival.Breast cancer is composed of distinct subgroups, triple-negative breast cancer (TNBC), human epidermal growth factor receptor-2 (HER2), luminal A, and luminal B, which are associated with different prognosis. MEP50 is the main partner of the arginine methyltransferase PRMT5 required for its enzymatic activity. Here, we examined MEP50 expression in the different breast cancer subgroups from the transcriptomic data obtained on human breast cancer samples and on normal breast tissues in two cohorts (Curie, n = 141; The Cancer Genome Atlas—TCGA, n = 788). We observed higher levels of MEP50 mRNA in TNBC (Curie, n = 41; TCGA, n = 106) compared to the other breast cancer subgroups and normal breast tissues. Using an online KM-plotter database, which allows survival analyses in a larger number of breast cancer patients, we found that high MEP50 mRNA levels were associated with a more favorable recurrence-free survival (RFS) in TNBC (n = 953, p = 1.2 × 10−4) and luminal B (n = 1353, p = 0.013) tumors, whereas high PRMT5 mRNA levels were associated with worse RFS in these two subgroups (TNBC: n = 442, p = 1.0 × 10−4; luminal B: n = 566, p = 6.8 × 10−3). We next determined the expression and the subcellular localization of MEP50 protein by immunohistochemistry (IHC) in our Curie cohort of breast cancer (n = 94) and normal tissues (n = 7) using a validated MEP50 antibody. MEP50 was more expressed in breast tumors compared to normal breast tissues (p = 0.02). MEP50 was more localized to the cytosol in breast cancer cells compared to normal breast tissue (p = 4 × 10−4), and was more found at the plasma membrane in normal tissues compared to breast tumors (p = 0.01). We also evaluated PRMT5 activity by IHC in our Curie cohort using a validated antibody (H4R3me2s) detecting histone H4 symmetrically dimethylated on Arg3. High levels of H4R3me2s were found in normal breast tissues, whereas the lowest levels of H4R3me2s were observed in TNBC and HER2 breast cancer subgroups. Altogether, our study reports the expression of the PRMT5 cofactor (MEP50) and substrate (H4R3me2s) in breast cancer and highlights the association of PRMT5 and MEP50 mRNA with prognosis in luminal B and TNBC breast cancer subgroups and certain TNBC subtypes.

Characterization and subcellular localization of Alongshan virus proteins.

Alongshan virus (ALSV) in the Jingmenvirus group within the family Flaviviridae is a newly discovered tick-borne virus associated with human disease, whose genome includes four segments and encodes four structural proteins (VP1a, VP1b, VP2, VP3, and VP4) and two non-structural proteins (NSP1 and NSP2). Here, we characterized the subcellular distribution and potential function of ALSV proteins in host cells. We found that viral proteins exhibited diverse subcellular distribution in multiple tissue-deriving cells and induced various morphological changes in the endoplasmic reticulum (ER), and NSP2, VP1b, VP2, and VP4 were all co-localized in the ER. The nuclear transfer and co-localization of VP4 and calnexin (a marker protein of ER), which were independent of their interaction, were unique to HepG2 cells. Expression of NSP1 could significantly reduce mitochondria quantity by inducing mitophagy. These findings would contribute to better understanding of the pathogenesis of emerging segmented flaviviruses.

Identification and analysis of proline-rich proteins and hybrid proline-rich proteins super family genes from Sorghum bicolor and their expression patterns to abiotic stress and zinc stimuli.

Systematic genome-wide analysis of Sorghum bicolor revealed the identification of a total of 48 homologous genes comprising 21 proline-rich proteins (PRPs) and 27 hybrid proline-rich proteins (HyPRPs). Comprehensive scrutiny of these gene homologs was conducted for gene structure, phylogenetic investigations, chromosome mapping, and subcellular localization of proteins. Promoter analysis uncovered the regions rich with phosphorous- (BIHD), ammonium-, sulfur-responsive (SURE), and iron starvation-responsive (IRO2) along with biotic, abiotic, and development-specific cis-elements. Further, PRPs exhibit more methylation and acetylation sites in comparison with HyPRPs. miRNAs have been predicted which might play a role in cleavage and translation inhibition. Several of the SbPRP genes were stimulated in a tissue-specific manner under drought, salt, heat, and cold stresses. Additionally, exposure of plants to abscisic acid (ABA) and zinc (Zn) also triggered PRP genes in a tissue-dependent way. Among them, SbPRP17 has been found upregulated markedly in all tissues irrespective of the stress imposed. The expressions of SbHyPRPs, especially SbHyPRP2, SbHyPRP6, and SbHyPRP17 were activated under all stresses in all three tissues. On the other hand, SbHyPRP8 (root only) and SbHyPRP12 (all three tissues) were highly responsive to cold stress and ABA while SbHyPRP26 was induced by drought and Zn in the stem. Taken together, this study indicates the critical roles that SbPRPs and SbHyPRPs play during diverse abiotic stress conditions and notably the plausible roles that these genes play upon exposure to zinc, the crucial micronutrient in plants.

BR-Mediated Protein S-Nitrosylation Alleviated Low-Temperature Stress in Mini Chinese Cabbage (Brassica rapa ssp. pekinensis)

Brassinosteroids (BRs), a novel plant hormone, are widely involved in plant growth and stress response processes. Nitric oxide (NO), as an important gas signaling molecule, can regulate target protein activity, subcellular localization and function in response to various stresses through post-translational S-nitrosylation modifications. However, the relationship between BR and NO in alleviating low-temperature stress of mini Chinese cabbage remains unclear. The hydroponic experiment combined with the pharmacological and molecular biological method was conducted to study the alleviating mechanism of BR at low temperature in mini Chinese cabbage. The results showed that low temperature inhibited the growth of mini Chinese cabbage seedlings, as evidenced by dwarf plants and yellow leaves. Treatment with 0.05 mg/L BR and 50 µM NO donor S-nitrosoglutathione (GSNO) significantly increased the leaf area, stem diameter, chlorophyll content, dry and fresh weight and proline content. Meanwhile, the malondialdehyde (MDA) content in 0.05 mg/L BR- and 50 µM GSNO-treated leaves were significantly lower than those in other treated leaves under low-temperature conditions. In addition, BR and GSNO applications induced an increase in NO and S-nitrosothiol (SNO) levels in vivo under low-temperature stress. Similarly, spraying BR after the elimination of NO also increased the level of S-nitrosylation in vivo, while spraying GSNO after inhibiting BR biosynthesis decreased the level of NO and SNO in vivo. In contrast, the S-nitrosoglutathione reductase (BrGSNOR) relative expression level and GSNOR enzyme activity were downregulated and inhibited by BR treatment, GSNO treatment and spraying BR after NO clearance, while the relative expression level of BrGSNOR was upregulated and GSNOR enzyme activity was also increased when spraying GSNO after inhibiting BR synthesis. Meanwhile, the biotin switch assay showed that exogenous BR increased the level of total nitrosylated protein in vivo under low-temperature stress. These results suggested that BR might act as an upstream signal of NO, induced the increase of NO content in vivo and then induced the protein S-nitrosylation modification to alleviate the damage of mini Chinese cabbage seedlings under low-temperature stress.

Visualizing Subcellular Localization of a Protein in the Heart using Quantum Dots-Mediated Immuno-Labeling followed by Transmission Electron Microscopy.

The subcellular localization is critical to delineating proper function and determining the molecular mechanisms of a particular protein. Several qualitative and quantitative techniques are used to determine the subcellular localization of proteins. One of the emerging techniques in determining the subcellular localization of a protein is quantum dots (QD)-mediated immunolabeling of a protein followed by imaging them with transmission electron microscopy (TEM). QD is a semiconductor nanocrystal with a dual property of crystalline structure and high electron density, which makes them applicable to electron microscopy. This current method visualized the subcellular localization of Sigma 1 receptor (Sigmar1) protein using QD-TEM in the heart tissue at ultrastructural level. Small cubes of the heart tissue sections from a wild-type mouse were fixed in 3% glutaraldehyde, subsequently osmicated, stained with uranyl acetate, followed by sequential dehydration with ethanol and acetone. These dehydrated heart tissue sections were embedded in low-viscosity epoxy resins, cut into thin sections of 500 nm thickness, put on the grid, and subsequently subjected to antigen unmasking with 5% sodium metaperiodate, followed by quenching of the residual aldehydes with glycine. The tissues were blocked, followed by sequential incubation in primary antibody, biotinylated secondary antibody, and streptavidin-conjugated QD. These stained sections were blot dried and imaged at high magnification using TEM. The QD-TEM technique allowed the visualization of Sigmar1 protein'ssubcellular localization at the ultrastructural level in the heart. These techniques can be used to visualize the presence of any protein and subcellular localization in any organ system.

GraphLoc: a graph neural network model for predicting protein subcellular localization from immunohistochemistry images.

Recognition of protein subcellular distribution patterns and identification of location biomarker proteins in cancer tissues are important for understanding protein functions and related diseases. Immunohistochemical (IHC) images enable visualizing the distribution of proteins at the tissue level, providing an important resource for the protein localization studies. In the past decades, several image-based protein subcellular location prediction methods have been developed, but the prediction accuracies still have much space to improve due to the complexity of protein patterns resulting from multi-label proteins and the variation of location patterns across cell types or states. Here, we propose a multi-label multi-instance model based on deep graph convolutional neural networks, GraphLoc, to recognize protein subcellular location patterns. GraphLoc builds a graph of multiple IHC images for one protein, learns protein-level representations by graph convolutions and predicts multi-label information by a dynamic threshold method. Our results show that GraphLoc is a promising model for image-based protein subcellular location prediction with model interpretability. Furthermore, we apply GraphLoc to the identification of candidate location biomarkers and potential members for protein networks. A large portion of the predicted results have supporting evidence from the existing literatures and the new candidates also provide guidance for further experimental screening. The dataset and code are available at: www.csbio.sjtu.edu.cn/bioinf/GraphLoc. Supplementary data are available at Bioinformatics online.

R17C Mutation in Photoreceptor Disc-Specific Protein, PRCD, Results in Additional Lipidation Altering Protein Stability and Subcellular Localization.

Progressive rod-cone degeneration (PRCD) is a photoreceptor outer segment (OS) disc-specific protein essential for maintaining OS structures while contributing to rhodopsin packaging densities and distribution in disc membranes. Previously, we showed PRCD undergoing palmitoylation at the sole cysteine (Cys2), where a mutation linked with retinitis pigmentosa (RP) in humans and dogs demonstrates the importance of palmitoylation for protein stability and trafficking to the OS. We demonstrate a mutation, in the polybasic region (PBR) of PRCD (Arg17Cys) linked with RP where an additional lipidation is observed through acyl-RAC. Immunolocalization of transiently expressed R17C in hRPE1 cells depicts similar characteristics to wild-type PRCD; however, a double mutant lacking endogenous palmitoylation at Cys2Tyr with Arg17Cys is comparable to the C2Y protein as both aggregate, mislocalized to the subcellular compartments within the cytoplasm. Subretinal injection of PRCD mutant constructs followed by electroporation in murine retina exhibit mislocalization in the inner segment. Despite being additionally lipidated and demonstrating strong membrane association, the mutation in the PBR affects protein stability and localization to the OS. Acylation within the PBR alone neither compensates for protein stability nor trafficking, revealing defects in the PBR likely lead to dysregulation of PRCD protein associated with blinding diseases.

Fluorescent Protein-Based Approaches for Subcellular Protein Localization in Plants.

Fluorescent proteins (FPs) remarkably advanced the study of cellular biology of plants. The most common application is their use as reporter proteins to determine the subcellular localization of a protein of interest (POI) by endogenous expression of a suitable FP-POI fusion construct in plant cells. In this chapter we describe three approaches, namely, particle bombardment, protoplast transformation, and Agrobacterium infiltration, to transiently express such fusion constructs in plant cells of different species. These approaches are versatile and can be utilized for diverse fluorescent protein-based applications.

Multiple Parallel Fusion Network for Predicting Protein Subcellular Localization from Stimulated Raman Scattering (SRS) Microscopy Images in Living Cells.

Stimulated Raman Scattering Microscopy (SRS) is a powerful tool for label-free detailed recognition and investigation of the cellular and subcellular structures of living cells. Determining subcellular protein localization from the cell level of SRS images is one of the basic goals of cell biology, which can not only provide useful clues for their functions and biological processes but also help to determine the priority and select the appropriate target for drug development. However, the bottleneck in predicting subcellular protein locations of SRS cell imaging lies in modeling complicated relationships concealed beneath the original cell imaging data owing to the spectral overlap information from different protein molecules. In this work, a multiple parallel fusion network, MPFnetwork, is proposed to study the subcellular locations from SRS images. This model used a multiple parallel fusion model to construct feature representations and combined multiple nonlinear decomposing algorithms as the automated subcellular detection method. Our experimental results showed that the MPFnetwork could achieve over 0.93 dice correlation between estimated and true fractions on SRS lung cancer cell datasets. In addition, we applied the MPFnetwork method to cell images for label-free prediction of several different subcellular components simultaneously, rather than using several fluorescent labels. These results open up a new method for the time-resolved study of subcellular components in different cells, especially cancer cells.

Distinct overlapping functions for Prickle1 and Prickle2 in the polarization of the airway epithelium.

Planar cell polarity (PCP) signaling polarizes cells within the plane of an epithelium. In the airways, planar cell polarity signaling orients the directional beating of motile cilia required for effective mucociliary clearance. The planar cell polarity signaling mechanism is best understood from work in Drosophila, where it has been shown to both coordinate the axis of polarity between cells and to direct the morphological manifestations of polarization within cells. The ‘core’ planar cell polarity signaling mechanism comprises two protein complexes that segregate to opposite sides of each cell and interact with the opposite complex in neighboring cells. Proper subcellular localization of core planar cell polarity proteins correlates with, and is almost certainly responsible for, their ability to direct polarization. This mechanism is highly conserved from Drosophila to vertebrates, though for most of the core genes, mammals have multiple paralogs whereas Drosophila has only one. In the mouse airway epithelium, the core protein Prickle2 segregates asymmetrically, as is characteristic for core proteins, but is only present in multiciliated cells and is absent from other cell types. Furthermore, Prickle2 mutant mice show only modest ciliary polarity defects. These observations suggest that other Prickle paralogs might contribute to polarization. Here, we show that Prickle1 segregates asymmetrically in multiciliated and nonciliated airway epithelial cell types, that compared to Prickle2, Prickle1 has different spatial and temporal expression dynamics and a stronger ciliary polarity phenotype, and that Prickle1 and Prickle2 mutants genetically interact. We propose distinct and partially overlapping functions for the Prickle paralogs in polarization of the airway epithelium.

Subcellular Localization Prediction of Human Proteins Using Multifeature Selection Methods.

Subcellular localization attempts to assign proteins to one of the cell compartments that performs specific biological functions. Finding the link between proteins, biological functions, and subcellular localization is an effective way to investigate the general organization of living cells in a systematic manner. However, determining the subcellular localization of proteins by traditional experimental approaches is difficult. Here, protein–protein interaction networks, functional enrichment on gene ontology and pathway, and a set of proteins having confirmed subcellular localization were applied to build prediction models for human protein subcellular localizations. To build an effective predictive model, we employed a variety of robust machine learning algorithms, including Boruta feature selection, minimum redundancy maximum relevance, Monte Carlo feature selection, and LightGBM. Then, the incremental feature selection method with random forest and support vector machine was used to discover the essential features. Furthermore, 38 key features were determined by integrating results of different feature selection methods, which may provide critical insights into the subcellular location of proteins. Their biological functions of subcellular localizations were discussed according to recent publications. In summary, our computational framework can help advance the understanding of subcellular localization prediction techniques and provide a new perspective to investigate the patterns of protein subcellular localization and their biological importance.

Ustilaginoidea virens Nuclear Effector SCRE4 Suppresses Rice Immunity via Inhibiting Expression of a Positive Immune Regulator OsARF17.

Rice false smut caused by the biotrophic fungal pathogen Ustilaginoidea virens has become one of the most important diseases in rice. The large effector repertory in U. virens plays a crucial role in virulence. However, current knowledge of molecular mechanisms how U. virens effectors target rice immune signaling to promote infection is very limited. In this study, we identified and characterized an essential virulence effector, SCRE4 (Secreted Cysteine-Rich Effector 4), in U. virens. SCRE4 was confirmed as a secreted nuclear effector through yeast secretion, translocation assays and protein subcellular localization, as well as up-regulation during infection. The SCRE4 gene deletion attenuated the virulence of U. virens to rice. Consistently, ectopic expression of SCRE4 in rice inhibited chitin-triggered immunity and enhanced susceptibility to false smut, substantiating that SCRE4 is an essential virulence factor. Furthermore, SCRE4 transcriptionally suppressed the expression of OsARF17, an auxin response factor in rice, which positively regulates rice immune responses and resistance against U. virens. Additionally, the immunosuppressive capacity of SCRE4 depended on its nuclear localization. Therefore, we uncovered a virulence strategy in U. virens that transcriptionally suppresses the expression of the immune positive modulator OsARF17 through nucleus-localized effector SCRE4 to facilitate infection.

A multi-scale multi-model deep neural network via ensemble strategy on high-throughput microscopy image for protein subcellular localization

Protein subcellular locations are closely related to the function of proteins. By detecting the abnormalities in subcellular locations, we can infer the occurrence of some diseases and mine new drug targets. A large number of single-cell high-throughput microscopy images provide us with relevant resources for studying protein distribution patterns. However, in the existing image-based protein subcellular localization methods, the traditional techniques are lack of efficiency and accuracy, and the potential of deep learning methods has not been fully tapped. So in this study, we propose a multi-scale multi-model deep neural network via ensemble strategy for protein subcellular localization on single-cell high-throughput images. First of all, we employ a deep convolutional neural network as multi-scale feature extractor and use global average pooling to map extracted features at different stages into feature vectors, then concatenate these multi-scale features to form a multi-model structure for image classification. In addition, we add Squeeze-and-Excitation Blocks to the network to emphasize more informative features. What is more, we use an ensemble method to fuse the classification results from the multi-model structure to obtain the final subcellular location of each single-cell image. Experiments show the validity and effectiveness of our method on yeast cell images, it can significantly improve the accuracy of high-throughput microscopy image-based protein subcellular localization, and we achieve the classification accuracy of 0.9098 on the high-throughput microscopy images of yeast cells. In the work of protein subcellular localization, our method provides a framework for processing and classifying microscope images, and further lays the foundation for the study of protein and gene functions.

Oleanolic acid stimulation of cell migration involves a biphasic signaling mechanism

Cell migration is a critical process for wound healing, a physiological phenomenon needed for proper skin restoration after injury. Wound healing can be compromised under pathological conditions. Natural bioactive terpenoids have shown promising therapeutic properties in wound healing. Oleanolic acid (OA), a triterpenoid, enhances in vitro and in vivo cell migration. However, the underlying signaling mechanisms and pathways triggered by OA are poorly understood. We have previously shown that OA activates epidermal growth factor receptor (EGFR) and downstream effectors such as mitogen-activated protein (MAP) kinase cascade and c-Jun N-terminal kinase (JNK), leading to c-Jun transcription factor phosphorylation, all of which are involved in migration. We performed protein expression or migration front protein subcellular localization assays, which showed that OA induces c-Jun activation and its nuclear translocation, which precisely overlaps at wound-edge cells. Furthermore, c-Jun phosphorylation was independent of EGFR activation. Additionally, OA promoted actin cytoskeleton and focal adhesion (FA) dynamization. In fact, OA induced the recruitment of regulator proteins to FAs to dynamize these structures during migration. Moreover, OA changed paxillin distribution and activated focal adhesion kinase (FAK) at focal adhesions (FAs). The molecular implications of these observations are discussed.

Ph5GT silencing alters flower color and flavonoids metabolome profile in petunia.

Anthocyanins are important pigments in plants and glycosylation plays an important role in the stability of anthocyanins. Anthocyanin 5-O-glucosyltransferase (5GT) can glycosylate anthocyanin at the 5-O-position. Till now, the enzymatic activity characteristics of 5GT had been studied in vitro in a variety of plants. However, the subcellular localization of 5GT protein still remained unclear, and little genetic evidence on the roles of 5GT in plants has been reported. The full-length Ph5GT gene from petunia (Petunia hybrida) was isolated in this study. Green fluorescent fusion protein assays revealed that Ph5GT protein was localized to the cytoplasm. Ph5GT was found to be highly expressed in flowers, with highest levels of expression occurring during the coloring stage of flower development. Furthermore, Ph5GT silencing led to the change in flower color from purple to light purple and a significant reduction in total anthocyanin content. The metabolome analysis revealed that the content of malvidins and petunidins modified by glycosylation at the 5-O-position was significantly reduced, while the content of their precursor without glycosylation was significantly increased, implying that Ph5GT could glycosylate malvidin and petunidin derivatives and that the substrate types of Ph5GT were expanded in comparison to previous studies.

Prediction of Protein Subcellular Localization Based on Microscopic Images via Multi‐Task Multi‐Instance Learning

Protein localization information is essential for understanding protein functions and their roles in various biological processes. The image-based prediction methods of protein subcellular localization have emerged in recent years because of the advantages of microscopic images in revealing spatial expression and distribution of proteins in cells. However, the image-based prediction is a very challenging task, due to the multi-instance nature of the task and low quality of images. In this paper, we propose a multi-task learning strategy and mask generation to enhance the prediction performance. Furthermore, we also investigate effective multi-instance learning schemes. We collect a large-scale dataset from the Human Protein Atlas database, and the experimental results show that the proposed multi-task multi-instance learning model outperforms both single-instance learning and common multi-instance learning methods by large margins.

Cloning and functional characterization of a lysophosphatidic acid acyltransferase gene from Perilla frutescens

Perilla (Perilla frutescens L.) is an important edible-medicinal oil crop, with its seed containing 46%-58% oil. Of perilla seed oil, α-linolenic acid (C18:3) accounts for more than 60%. Lysophosphatidic acid acyltransferase (LPAT) is one of the key enzymes responsible for triacylglycerol assembly in plant seeds, controlling the metabolic flow from lysophosphatidic acid to phosphatidic acid. In this study, the LPAT2 gene from the developing seeds of perilla was cloned and designated as PfLPAT2. The expression profile of PfLPAT2 gene was examined in various tissues and different seed development stages of perilla (10, 20, 30, and 40 days after flowering, DAF) by quantitative real-time PCR (qRT-PCR). In order to detect the subcellular localization of PfLPAT2 protein, a fusion expression vector containing PfLPAT2 and GFP was constructed and transformed into Nicotiana benthamiana leaves by Agrobacterium-mediated infiltration. In order to explore the enzymatic activity and biological function of PfLPAT2 protein, an E. coli expression vector, a yeast expression vector and a constitutive plant overexpression vector were constructed and transformed into an E. coli mutant SM2-1, a wild-type Saccharomyces cerevisiae strain INVSc1, and a common tobacco (Nicotiana tabacum, variety: Sumsun NN, SNN), respectively. The results showed that the PfLPAT2 open reading frame (ORF) sequence was 1 155 bp in length, encoding 384 amino acid residues. Functional structure domain prediction showed that PfLPAT2 protein has a typical conserved domain of lysophosphatidic acid acyltransferase. qRT-PCR analysis indicated that PfLPAT2 gene was expressed in all tissues tested, with the peak level in seed of 20 DAF of perilla. Subcellular localization prediction showed that PfLPAT2 protein is localized in cytoplasm. Functional complementation assay of PfLPAT2 in E. coli LPAAT mutant (SM2-1) showed that PfLPAT2 could restore the lipid biosynthesis of SM2-1 cell membrane and possess LPAT enzyme activity. The total oil content in the PfLPAT2 transgenic yeast was significantly increased, and the content of each fatty acid component changed compared with that of the non-transgenic control strain. Particularly, oleic acid (C18:1) in the transgenic yeast significantly increased, indicating that PfLPAT2 has a higher substrate preference for C18:1. Importantly, total fatty acid content in the transgenic tobacco leaves increased by about 0.42 times compared to that of the controls, with the C18:1 content doubled. The increased total oil content and the altered fatty acid composition in transgenic tobacco lines demonstrated that the heterologous expression of PfLPAT2 could promote host oil biosynthesis and the accumulation of health-promoting fatty acids (C18:1 and C18:3). This study will provide a theoretical basis and genetic elements for in-depth analysis of the molecular regulation mechanism of perilla oil, especially the synthesis of unsaturated fatty acids, which is beneficial to the genetic improvement of oil quality of oil crops.