Exploring the association of ESR1 and ESR2 gene SNPs with polycystic ovary syndrome in human females: a comprehensive association study.

BACKGROUND: Polycystic Ovary Syndrome (PCOS) affects a significant proportion of human females worldwide and is characterized by hormonal, metabolic, and reproductive dysfunctions, including infertility, irregular menstrual cycles, acanthosis nigricans, and hirsutism. Mutations in the estrogen receptor genes ESR1 and ESR2, involved in normal follicular development and ovulation, can contribute to development of the PCOS. The present study focuses on investigating the potential correlation between single nucleotide polymorphisms (SNPs) of ESR1 and ESR2 genes and the incidence of this syndrome. METHODS: For this study, SNPs in ESR1 and ESR2 genes were retrieved from the ENSEMBL database and analyzed for their effect on mutated proteins using different bioinformatics tools including SIFT, PolyPhen, CADD, REVEL, MetaLR, I-Mutant, CELLO2GO, ProtParam, SOPMA, SWISS-MODEL and HDDOCK. RESULTS: All the SNPs documented in the present study were deleterious. All the SNPs except rs1583384537, rs1450198518, and rs78255744 decreased protein stability. Two variants rs1463893698 and rs766843910 in the ESR2 gene altered the localization of mutated proteins i.e. in addition to the nucleus, proteins were also found in mitochondria and extracellular, respectively. SNPs rs104893956 in ESR1 and rs140630557, rs140630557, rs1596423459, rs766843910, rs1596405923, rs762454979 and rs1384121511 in ESR2 gene significantly changed the secondary structure of proteins (2D). SNPs that markedly changed 3D configuration included rs1554259481, rs188957694 and rs755667747 in ESR1 gene and rs1463893698, rs140630557, rs1596423459, rs766843910, rs1596405923, rs762454979 and rs1384121511 in ESR2 gene. Variants rs1467954450 (ESR1) and rs140630557 (ESR2) were identified to reduce the binding tendency of ESRα and ß receptors with estradiol as reflected by the docking scores i.e. -164.97 and -173.23, respectively. CONCLUSION: Due to the significant impact on the encoded proteins, these variants might be proposed as biomarkers to predict the likelihood of developing PCOS in the future and for diagnostic purposes.

Protein S-nitrosylation under abiotic stress: Role and mechanism.

Abiotic stress is one of the main threats affecting crop growth and production. Nitric oxide (NO), an important signaling molecule involved in wide range of plant growth and development as well as in response to abiotic stress. NO can exert its biological functions through protein S-nitrosylation, a redox-based posttranslational modification by covalently adding NO moiety to a reactive cysteine thiol of a target protein to form an S-nitrosothiol (SNO). Protein S-nitrosylation is an evolutionarily conserved mechanism regulating multiple aspects of cellular signaling in plant. Recently, emerging evidence have elucidated protein S-nitrosylation as a modulator of plant in responses to abiotic stress, including salt stress, extreme temperature stress, light stress, heavy metal and drought stress. In addition, significant mechanism has been made in functional characterization of protein S-nitrosylated candidates, such as changing protein conformation, and the subcellular localization of proteins, regulating protein activity and influencing protein interactions. In this study, we updated the data related to protein S-nitrosylation in plants in response to adversity and gained a deeper understanding of the functional changes of target proteins after protein S-nitrosylation.

OrganelX web server for sub-peroxisomal and sub-mitochondrial protein localization and peroxisomal target signal detection.

We present the OrganelX e-Science Web Server that provides a user-friendly implementation of the In-Pero and In-Mito classifiers for sub-peroxisomal and sub-mitochondrial localization of peroxisomal and mitochondrial proteins and the Is-PTS1 algorithm for detecting and validating potential peroxisomal proteins carrying a PTS1 signal sequence. The OrganelX e-Science Web Server is available at https://organelx.hpc.rug.nl/fasta/.

Molecular cloning, expression analysis and immune-related functional identification of tumor necrosis factor alpha (TNFα) in Sepiella japonica under bacteria stress.

Tumor necrosis factor α (TNFα), a cytokine mainly secreted by active macrophages and monocytes, causes hemorrhagic necrosis of tumor tissues, kills tumor cells, regulates inflammatory responses, and plays a crucial role in innate immunity. In this study, TNFα of Sepiella japonica (named as SjTNFα) was acquired, whose full-length cDNA was 1206 bp (GenBank accession no. ON357428), containing a 5' UTR of 185 bp, a 3' UTR of 137 bp and an open reading frame (ORF) of 1002bp to encode a putative peptide of 333 amino acids for constructing the transmembrane domain and the cytoplasmic TNF domain. Its predicted pI was 8.69 and the theoretical molecular weight was 44.72 KDa. Multiple sequence alignment and phylogenetic analysis showed that SjTNFα had the highest homology to Octopus sinensis, they fell into a unified branch and further clustered with other animals. Real-time PCR indicated that SjTNFα was widely expressed in all subject tissues, including spleen, pancreas, gill, heart, brain, optic lobe, liver and intestine, and exhibited the highest in the liver and the lowest in the brain. The relative expression of SjTNFα varied at the developmental period of juvenile stage, pre-spawning and oviposition in the squid, with the highest in the liver at the juvenile stage and oviposition, and in the optic lobe of pre-spawning. After being infected with Vibrio parahaemolyticus and Aeromonas hydrophila, the expression of SjTNFα in liver and gill were both upregulated with time, and the highest expression appeared at 24 h and 8 h in liver for different infection, and at 4 h in gill consistently. Cell localization showed that SjTNFα distributed on membrane of HEK293 cells because it was a type II soluble transmembrane protein. When HEK293 cells were stimulated with LPS of different concentrations, the NF-κB pathway was activated in the nucleus and the corresponding mRNA was transferred through the intracellular signal transduction pathway, resulting in the synthesis and release of TNFα, which made the expression of SjTNFα was up-regulated obviously. These findings showed that SjTNFα might play an essential role in the defense of S. japonica against bacteria challenge, which contributed to the understanding of the intrinsic immune signaling pathway of Cephalopoda and the further study of host-pathogen interactions.

Circ-LocNet: A Computational Framework for Circular RNA Sub-Cellular Localization Prediction.

Circular ribonucleic acids (circRNAs) are novel non-coding RNAs that emanate from alternative splicing of precursor mRNA in reversed order across exons. Despite the abundant presence of circRNAs in human genes and their involvement in diverse physiological processes, the functionality of most circRNAs remains a mystery. Like other non-coding RNAs, sub-cellular localization knowledge of circRNAs has the aptitude to demystify the influence of circRNAs on protein synthesis, degradation, destination, their association with different diseases, and potential for drug development. To date, wet experimental approaches are being used to detect sub-cellular locations of circular RNAs. These approaches help to elucidate the role of circRNAs as protein scaffolds, RNA-binding protein (RBP) sponges, micro-RNA (miRNA) sponges, parental gene expression modifiers, alternative splicing regulators, and transcription regulators. To complement wet-lab experiments, considering the progress made by machine learning approaches for the determination of sub-cellular localization of other non-coding RNAs, the paper in hand develops a computational framework, Circ-LocNet, to precisely detect circRNA sub-cellular localization. Circ-LocNet performs comprehensive extrinsic evaluation of 7 residue frequency-based, residue order and frequency-based, and physio-chemical property-based sequence descriptors using the five most widely used machine learning classifiers. Further, it explores the performance impact of K-order sequence descriptor fusion where it ensembles similar as well dissimilar genres of statistical representation learning approaches to reap the combined benefits. Considering the diversity of statistical representation learning schemes, it assesses the performance of second-order, third-order, and going all the way up to seventh-order sequence descriptor fusion. A comprehensive empirical evaluation of Circ-LocNet over a newly developed benchmark dataset using different settings reveals that standalone residue frequency-based sequence descriptors and tree-based classifiers are more suitable to predict sub-cellular localization of circular RNAs. Further, K-order heterogeneous sequence descriptors fusion in combination with tree-based classifiers most accurately predict sub-cellular localization of circular RNAs. We anticipate this study will act as a rich baseline and push the development of robust computational methodologies for the accurate sub-cellular localization determination of novel circRNAs.

Subcellular localization of fungal specialized metabolites.

Fungal specialized metabolites play an important role in the environment and have impacted human health and survival significantly. These specialized metabolites are often the end product of a series of sequential and collaborating biosynthetic enzymes that reside within different subcellular compartments. A wide variety of methods have been developed to understand fungal specialized metabolite biosynthesis in terms of the chemical conversions and the biosynthetic enzymes required, however there are far fewer studies elucidating the compartmentalization of the same enzymes. This review illustrates the biosynthesis of specialized metabolites where the localization of all, or some, of the biosynthetic enzymes have been determined and describes the methods used to identify the sub-cellular localization.

Sub-cellular localization of suppressor proteins of tomato leaf curl New Delhi virus.

Tomato leaf curl New Delhi virus (ToLCNDV), a bipartite begomovirus, is the most important among the 14 species of begomoviruses infecting tomato in Indian subcontinent. Begomovirus is known to  evade RNA silencing of host plants through suppressor proteins. However, in case of ToLCNDV, the suppressor proteins have not been studied well. The objective of the study is to know the sub-cellular localization of three suppressor proteins encoded by AV2, AC2 and AC4 ORFs of ToLCNDV in Nicotiana benthamiana. AV2, AC2 and AC4 ORFs of ToLCNDV were  cloned and sequenced (accession numbers MW423574, MW423576, MW423575, respectively) from a ToLCNDV isolate characterized earlier (accession number MW429271) and GFP tagged constructs were prepared in a plant expressing binary vector pEarleygate103. Bioinformatics analysis using Peptide 2.0 server predicted that all these proteins have more basic amino acid residues then acidic amino acid and AV2 protein has more hydrophobic amino acid residues. ScanProsite server predicted presence of different fuctional motifs in these proteins amongst which presence of kinase motif was observed in all of them. Virus mPLoc server predicted their subcellular localization. The suppressor gene constructs were agroinfiltrated on to leaves of one month old N. benthamiana plants and their subcellular localization has been studied through confocal microscopy. Results have shown that AV2 localizes in the host cell membrane and nucleus, AC2 in the nucleus and AC4 in the host cell membrane. Earlier reports with other begomoviruses also showed similar localization behaviour of these suppressor protein except AV2, where it was shown to be present in cytoplasm. Such localization study will help understand the mechanism of their suppression activity.

Journey of Poly(ethylene Glycol) in Living Cells.

As the gold standard for stealth polymer materials, poly(ethylene glycol) (PEG) has been widely used in drug delivery with excellent properties such as low toxicity, reduced immunogenicity, good water solubility, and so forth. However, lack of understanding for the fate of PEG and PEGylated delivery systems at the cellular level has limited the application of PEGylated molecules in diagnosis and therapy. Here, we chose linear PEG 5k as a representative model and focused on the internalization behavior and mechanism, intracellular trafficking, sub-cellular localization, and cellular exocytosis of PEG and PEGylated molecules in living cells. Our investigation showed that PEG could be internalized into cells in 1 h. The internalized PEG was localized to lysosome, cytosol, endoplasmic reticulum (ER) and mitochondria. Importantly, the fate of PEG in cells could be regulated by conjugating different small molecules. PEGylated rhodamine B (PEG-RB) as the positively charged macromolecule was internalized into cells by micropinocytosis and then transported in lysosomes, ER, and mitochondria via vesicles sequentially. In contrast, PEGylated pyropheophorbide-a (PEG-PPa) as the negatively charged macromolecule was internalized into cells and transported to lysosomes ultimately. PEGylation slowed down the exocytosis process of RB and PPa and significantly prolonged their residence time inside the cells. These findings improve the understanding of how PEG and PEGylated molecules interact with the biological system at cellular and sub-cellular levels, which is of significance to rational PEGylation design for drug delivery.

Advances in Computational Methodologies for Classification and Sub-Cellular Locality Prediction of Non-Coding RNAs.

Apart from protein-coding Ribonucleic acids (RNAs), there exists a variety of non-coding RNAs (ncRNAs) which regulate complex cellular and molecular processes. High-throughput sequencing technologies and bioinformatics approaches have largely promoted the exploration of ncRNAs which revealed their crucial roles in gene regulation, miRNA binding, protein interactions, and splicing. Furthermore, ncRNAs are involved in the development of complicated diseases like cancer. Categorization of ncRNAs is essential to understand the mechanisms of diseases and to develop effective treatments. Sub-cellular localization information of ncRNAs demystifies diverse functionalities of ncRNAs. To date, several computational methodologies have been proposed to precisely identify the class as well as sub-cellular localization patterns of RNAs). This paper discusses different types of ncRNAs, reviews computational approaches proposed in the last 10 years to distinguish coding-RNA from ncRNA, to identify sub-types of ncRNAs such as piwi-associated RNA, micro RNA, long ncRNA, and circular RNA, and to determine sub-cellular localization of distinct ncRNAs and RNAs. Furthermore, it summarizes diverse ncRNA classification and sub-cellular localization determination datasets along with benchmark performance to aid the development and evaluation of novel computational methodologies. It identifies research gaps, heterogeneity, and challenges in the development of computational approaches for RNA sequence analysis. We consider that our expert analysis will assist Artificial Intelligence researchers with knowing state-of-the-art performance, model selection for various tasks on one platform, dominantly used sequence descriptors, neural architectures, and interpreting inter-species and intra-species performance deviation.

Comparison of mass spectrometry data and bioinformatics predictions to assess the bona fide localization of proteins identified in cell wall proteomics studies.

Plant cell walls have complex architectures made of polysaccharides among which cellulose, hemicelluloses, pectins and cell wall proteins (CWPs). Some CWPs are anchored in the plasma membrane through a glycosylphosphatidylinositol (GPI)-anchor. The secretion pathway is the classical route to reach the extracellular space. Based on experimental data, a canonical signal peptide (SP) has been defined, and bioinformatics tools allowing the prediction of the sub-cellular localization of proteins have been designed. In the same way, the presence of GPI-anchor attachment sites can be predicted using bioinformatics programs. This article aims at comparing the bioinformatics predictions of the sub-cellular localization of proteins assumed to be CWPs to mass spectrometry (MS) data. The sub-cellular localization of a few CWPs exhibiting particular features has been checked by cell biology approaches. Although the prediction of SP length is confirmed in most cases, it is less conclusive for GPI-anchors. Three main observations were done: (i) the variability observed at the N-terminus of a few mature CWPs could play a role in the regulation of their biological activity; (ii) one protein was shown to have a double sub-cellular localization in the cell wall and the chloroplasts; and (iii) peptides were found to be located at the C-terminus of several CWPs previously identified in GPI-anchored proteomes, thus raising the issue of their actual anchoring to the plasma membrane.

mLoc-mRNA: predicting multiple sub-cellular localization of mRNAs using random forest algorithm coupled with feature selection via elastic net.

BACKGROUND: Localization of messenger RNAs (mRNAs) plays a crucial role in the growth and development of cells. Particularly, it plays a major role in regulating spatio-temporal gene expression. The in situ hybridization is a promising experimental technique used to determine the localization of mRNAs but it is costly and laborious. It is also a known fact that a single mRNA can be present in more than one location, whereas the existing computational tools are capable of predicting only a single location for such mRNAs. Thus, the development of high-end computational tool is required for reliable and timely prediction of multiple subcellular locations of mRNAs. Hence, we develop the present computational model to predict the multiple localizations of mRNAs. RESULTS: The mRNA sequences from 9 different localizations were considered. Each sequence was first transformed to a numeric feature vector of size 5460, based on the k-mer features of sizes 1-6. Out of 5460 k-mer features, 1812 important features were selected by the Elastic Net statistical model. The Random Forest supervised learning algorithm was then employed for predicting the localizations with the selected features. Five-fold cross-validation accuracies of 70.87, 68.32, 68.36, 68.79, 96.46, 73.44, 70.94, 97.42 and 71.77% were obtained for the cytoplasm, cytosol, endoplasmic reticulum, exosome, mitochondrion, nucleus, pseudopodium, posterior and ribosome respectively. With an independent test set, accuracies of 65.33, 73.37, 75.86, 72.99, 94.26, 70.91, 65.53, 93.60 and 73.45% were obtained for the respective localizations. The developed approach also achieved higher accuracies than the existing localization prediction tools. CONCLUSIONS: This study presents a novel computational tool for predicting the multiple localization of mRNAs. Based on the proposed approach, an online prediction server "mLoc-mRNA" is accessible at http://cabgrid.res.in:8080/mlocmrna/ . The developed approach is believed to supplement the existing tools and techniques for the localization prediction of mRNAs.

Ortho_Sim_Loc: Essential protein prediction using orthology and priority-based similarity approach.

Proteins are the essential macro-molecules of living organism. But all proteins cannot be considered as essential in different relevant studies. Essentiality of a protein is thus computed by computation methods rather than biological experiments which in turn save both time and effort. Different computational approaches are already predicted to select essential proteins successfully with different biological significances by researchers. Most of the experimental approaches return higher false negative outcomes with respect to others. In order to retain the prediction accuracy level, a novel methodology "Ortho_Sim_Loc"has been proposed which is a combined approach of Orthology, Similarity (using clustering and priority based GO-Annotation) and Subcellular localization. Ortho_Sim_Loc can predict enriched functional set essential proteins. The predicted results are validated with other existing methods like different centrality measures, LIDC. The validation results exhibits better performance of Ortho_Sim_Loc in compare to other existing computational approaches.

LncRBase V.2: an updated resource for multispecies lncRNAs and ClinicLSNP hosting genetic variants in lncRNAs for cancer patients.

The recent discovery of long non-coding RNA as a regulatory molecule in the cellular system has altered the concept of the functional aptitude of the genome. Since our publication of the first version of LncRBase in 2014, there has been an enormous increase in the number of annotated lncRNAs of multiple species other than Human and Mouse. LncRBase V.2 hosts information of 549,648 lncRNAs corresponding to six additional species besides Human and Mouse, viz. Rat, Fruitfly, Zebrafish, Chicken, Cow and C.elegans. It provides additional distinct features such as (i) Transcription Factor Binding Site (TFBS) in the lncRNA promoter region, (ii) sub-cellular localization pattern of lncRNAs (iii) lnc-pri-miRNAs (iv) Possible small open reading frames (sORFs) within lncRNA. (v) Manually curated information of interacting target molecules and disease association of lncRNA genes (vi) Distribution of lncRNAs across multiple tissues of all species. Moreover, we have hosted ClinicLSNP within LncRBase V.2. ClinicLSNP has a comprehensive catalogue of lncRNA variants present within breast, ovarian, and cervical cancer inferred from 561 RNA-Seq data corresponding to these cancers. Further, we have checked whether these lncRNA variants overlap with (i)Repeat elements,(ii)CGI, (iii)TFBS within lncRNA loci (iv)SNP localization in trait-associated Linkage Disequilibrium(LD) region, (v)predicted the potentially pathogenic variants and (vi)effect of SNP on lncRNA secondary structure. Overall, LncRBaseV.2 is a user-friendly database to survey, search and retrieve information about multi-species lncRNAs. Further, ClinicLSNP will serve as a useful resource for cancer specific lncRNA variants and their related information. The database is freely accessible and available at http://dibresources.jcbose.ac.in/zhumur/lncrbase2/.

A Genetic Toolbox for the New Model Cyanobacterium Cyanothece PCC 7425: A Case Study for the Photosynthetic Production of Limonene.

Cyanobacteria, the largest phylum of prokaryotes, perform oxygenic photosynthesis and are regarded as the ancestors of the plant chloroplast and the purveyors of the oxygen and biomass that shaped the biosphere. Nowadays, cyanobacteria are attracting a growing interest in being able to use solar energy, H2O, CO2 and minerals to produce biotechnologically interesting chemicals. This often requires the introduction and expression of heterologous genes encoding the enzymes that are not present in natural cyanobacteria. However, only a handful of model strains with a well-established genetic system are being studied so far, leaving the vast biodiversity of cyanobacteria poorly understood and exploited. In this study, we focused on the robust unicellular cyanobacterium Cyanothece PCC 7425 that has many interesting attributes, such as large cell size; capacity to fix atmospheric nitrogen (under anaerobiosis) and to grow not only on nitrate but also on urea (a frequent pollutant) as the sole nitrogen source; capacity to form CO2-sequestrating intracellular calcium carbonate granules and to produce various biotechnologically interesting products. We demonstrate for the first time that RSF1010-derived plasmid vectors can be used for promoter analysis, as well as constitutive or temperature-controlled overproduction of proteins and analysis of their sub-cellular localization in Cyanothece PCC 7425. These findings are important because no gene manipulation system had been developed for Cyanothece PCC 7425, yet, handicapping its potential to serve as a model host. Furthermore, using this toolbox, we engineered Cyanothece PCC 7425 to produce the high-value terpene, limonene which has applications in biofuels, bioplastics, cosmetics, food and pharmaceutical industries. This is the first report of the engineering of a Cyanothece strain for the production of a chemical and the first demonstration that terpene can be produced by an engineered cyanobacterium growing on urea as the sole nitrogen source.

The role of the cytoskeleton in germ plasm aggregation and compaction in the zebrafish embryo.

The transmission of genetic information from one generation to another is crucial for survival of animal species. This is accomplished by the induction of primordial germ cells (PGCs) that will eventually establish the germline. In some animals the germline is induced by signals in gastrula, whereas in others it is specified by inheritance of maternal determinants, known as germ plasm. In zebrafish, aggregation and compaction of maternally derived germ plasm during the first several embryonic cell cycles is essential for generation of PGCs. These processes are controlled by cellular functions associated with the cellular division apparatus. Ribonucleoparticles containing germ plasm components are bound to both the ends of astral microtubules and a dynamic F-actin network through a mechanism integrated with that which drives the cell division program. In this chapter we discuss the role that modifications of the cell division apparatus, including the cytoskeleton and cytoskeleton-associated proteins, play in the regulation of zebrafish germ plasm assembly.

Study of subcellular localization of Glycine max γ-tocopherol methyl transferase isoforms in N. benthamiana.

Gamma-tocopherol methyltransferase (γ-TMT) converts γ-toc to α-toc-the rate limiting step in toc biosynthesis. Sequencing results revealed that the coding regions of γ-TMT1 and γ-TMT3 were strongly similar to each other (93% at amino acid level). Based on the differences in the N-terminal amino acids, Glycine max-γ-TMT proteins are categorized into three isoforms: γ-TMT1, 2 and 3. In silico structural analysis revealed the presence of chloroplast transit peptide (cTP) in γ-TMT1 and γ-TMT3 protein. However, other properties of transit peptide like presence of hydrophobic amino acids at the first three positions of N-terminal end and lower level of acidic amino acids were revealed only in γ-TMT3 protein. Subcellular localization of GFP fused γ-TMT1 and γ-TMT3 under 35S promoter was studied in Nicotiana benthamiana using confocal microscopy. Results showed that γ-TMT1 was found in the cytosol and γ-TMT3 was found to be localized both in cytosol and chloroplast. Further the presence γ-TMT3 in chloroplast was validated by quantifying α-tocopherol through UPLC. Thus the present study of cytosolic localization of the both γ-TMT1 and γ-TMT3 proteins and chloroplastic localization of γ-TMT3 will help to reveal the importance of γ-TMT encoded α-toc in protecting both chloroplastic and cell membrane from plant oxidative stress.

Distinct Hepatic PKA and CDK Signaling Pathways Control Activity-Independent Pyruvate Kinase Phosphorylation and Hepatic Glucose Production.

Pyruvate kinase is an important enzyme in glycolysis and a key metabolic control point. We recently observed a pyruvate kinase liver isoform (PKL) phosphorylation site at S113 that correlates with insulin resistance in rats on a 3 day high-fat diet (HFD) and suggests additional control points for PKL activity. However, in contrast to the classical model of PKL regulation, neither authentically phosphorylated PKL at S12 nor S113 alone is sufficient to alter enzyme kinetics or structure. Instead, we show that cyclin-dependent kinases (CDKs) are activated by the HFD and responsible for PKL phosphorylation at position S113 in addition to other targets. These CDKs control PKL nuclear retention, alter cytosolic PKL activity, and ultimately influence glucose production. These results change our view of PKL regulation and highlight a previously unrecognized pathway of hepatic CDK activity and metabolic control points that may be important in insulin resistance and type 2 diabetes.

[Sub-cellular localization and overexpressing analysis of hydroxylase gene TcCYP725A22 of Taxus chinensis].

The discovery of hydroxylases in the anticancer drug taxol biosynthesis pathway is a hotspot and difficulty in current research. In this study, a new hydroxylase gene TcCYP725A22 (GenBank accession number: MF448646.1) was used to construct a sub-cellular localization vector pCAMIBA1303-TcCYP725A22-EGFP to get the transient expression in onion epidermal cells. Laser confocal microscopy revealed that the protein encoded by this gene was localized in the cell membrane. Furthermore, the recombinant plant expression plasmid pBI121-TcCYP725A22 was constructed. After transient transformation to the Taxus chinensis mediated by Agrobacterium tumefaciens LBA4404, qRT-PCR and LC-MS were utilized to analyze the effects of TcCYP725A22 overexpression on the synthesis of taxol. The results showed that, in the TcCYP725A22 overexpressed cell line, expression levels of most defined hydroxylase genes for taxol biosynthesis were increased, and the yield of taxanes were also increased. It was concluded that the hydroxylase gene TcCYP725A22 is likely involved in the biosynthetic pathway of taxol.

Distinct Distribution Patterns of Potassium Channel Sub-Units in Somato-Dendritic Compartments of Neurons of the Medial Superior Olive.

Coincidence detector neurons of the medial superior olive (MSO) are sensitive to interaural time differences in the range of a few tens of microseconds. The biophysical basis for this remarkable acuity is a short integration time constant of the membrane, which is achieved by large low voltage-activated potassium and hyperpolarization-activated inward cation conductances. Additional temporal precision is thought to be achieved through a sub-cellular distribution of low voltage-activated potassium channel expression biased to the soma. To evaluate the contribution of potassium channels, we investigated the presence and sub-cellular distribution profile of seven potassium channel sub-units in adult MSO neurons of gerbils. We find that low- and high voltage-activated potassium channels are present with distinct sub-cellular distributions. Overall, low voltage-activated potassium channels appear to be biased to the soma while high voltage-activated potassium channels are more evenly distributed and show a clear expression at distal dendrites. Additionally, low voltage-activated potassium channel sub-units co-localize with glycinergic inputs while HCN1 channels co-localize more with high voltage-activated potassium channels. Functionally, high voltage-activated potassium currents are already active at low voltages near the resting potential. We describe a possible role of high voltage-activated potassium channels in modulating EPSPs in a computational model and contributing to setting the integration time window of coincidental inputs. Our data shows that MSO neurons express a large set of different potassium channels with distinct functional relevance.

Replication stress-induced Exo1 phosphorylation is mediated by Rad53/Pph3 and Exo1 nuclear localization is controlled by 14-3-3 proteins.

BACKGROUND: Mechanisms controlling DNA resection at sites of damage and affecting genome stability have been the subject of deep investigation, though their complexity is not yet fully understood. Specifically, the regulatory role of post-translational modifications in the localization, stability and function of DNA repair proteins is an important aspect of such complexity. RESULTS: Here, we took advantage of the superior resolution of phosphorylated proteins provided by Phos-Tag technology to study pathways controlling the reversible phosphorylation of yeast Exo1, an exonuclease involved in a number of DNA repair pathways. We report that Rad53, a checkpoint kinase downstream of Mec1, is responsible for Exo1 phosphorylation in response to DNA replication stress and we demonstrate a role for the type-2A protein phosphatase Pph3 in the dephosphorylation of both Rad53 and Exo1 during checkpoint recovery. Fluorescence microscopy studies showed that Rad53-dependent phosphorylation is not required for the recruitment or the release of Exo1 from the nucleus, whereas 14-3-3 proteins are necessary for Exo1 nuclear translocation. CONCLUSIONS: By shedding light on the mechanism of Exo1 control, these data underscore the importance of post-translational modifications and protein interactions in the regulation of DNA end resection.