X-inactive specific transcript (XIST), a kind of lncRNA derived from XIST gene (Brown et al., 1991), is found up-expressed in several tumors, including ovarian cancer (Ren et al., 2015), non-small cell lung cancer (Tantai et al., 2015), glioblastoma (Yao et al., 2015), breast cancer (Salvador et al., 2013uanduHuang et al., 2016), and hepatocellular carcinoma (Zhuang et al., 2016), indicating that XIST might act as a potential diagnostic biomarker for these cancers . It has been reported that XIST is crucial for long-term survival in hematopoietic stem A 967079 (HSC) . Silencing XIST impeded cell growth, metastasis as well as facilitated cell apoptosis, and knockdown of XIST also repressed tumor growth and facilitated high survival in nude mice, which indicated that XIST exerted an essential role on the occurrence, development and progression of malignant tumors (Yao et al., 2015, Huang et al., 2016uanduZhuang et al., 2016). However, up to date, there is no related study elaborating the relevance between XIST expression and NPC progression. Hence, the role of XIST on NPC and its potential biological mechanisms still remain to be explored.
Previous studies have suggested that administration of recombinant Nrg1 improves cardiac function of injured hearts. This beneficial effect of Nrg1 can be attributed at least in part to its role in promoting CM proliferation after cardiac injury. Since ablating ErbB4 significantly diminished the proliferative effects of Nrg1 (Bersell et al., 2009, D\’Uva et al., 2015uanduGemberling et al., 2015), reduced activities or PF-01367338 levels of ErbB4/2 in the adult heart could limit a potentially greater beneficial effect of Nrg1. Indeed, we and others found that the expression of ErbB2 in the heart decreases over time until it reaches a relatively low level in the adult heart (Fig. 1B, D) (Lee et al., 1995uanduZhao et al., 1998). More interestingly, the expression profile of ErbB2 in the neonatal heart correlates nicely with the heart transitioning from being regenerative to non-regenerative. Functionally, ablating ErbB2 resulted in a significant reduction in neonatal CM proliferation (Fig. 2BaE). In contrast, overexpressing a constitutively active form of ErbB2 led to extensive proliferation of both neonatal and adult CMs, and appear to have a great effect on promoting CM proliferation than administration of recombinant NRG1 (D\’Uva et al., 2015) (Bersell et al., 2009). Overall, our study provided clear evidence that ErbB2 is one of the important regulators of CM proliferation, and the downregulation of its postnatal expression correlates with the decline of CM proliferation. Thus, identifying the factors or pathways that downregulate ErbB2 expression in the adult heart may provide novel avenues to improve the therapeutic potential of recombinant NRG1.
The data provided here suggest that the steep decline in ErbB2 expression postnatally may account for the decreased cardiac proliferative capacity soon after birth. Yet, it still remains to be determined the molecular mechanism that downregulate cardiac ErbB2 expression after birth.
Conflict of interest
AcknowledgementsWe are grateful for the expert technical assistance from the UNC Histology Core and UNC Microscopy Core. We thank members of the Liu lab and the Qian lab for helpful discussions and critical reviews of the manuscript. This study was supported by National Natural Science Foundation of China81200192 to Dr. Ma, AHA Scientist Development Grant 13SDG17060010 and the Ellison Medical Foundation (EMF) New Scholar Grant AG-NS-1064-13 to Dr. Qian, and NIH/NHLBIR00 HL109079 grant to Dr. Liu.
Isolation of intact mRNA; First sequenced mRNA; mRNA sequencing; Prolipoprotein; E. coli
The technology of sequencing of RNA was more advanced than the DNA sequencing technology in 1960s. There are a number of reasons for this; first of all, RNA in the cells is much more abundant than DNA. For example, cells contain a large amount of tRNAs so that they could be easily isolated in a pure form for structural study. In addition, as early as in 1957, a sequence-specific ribonuclease (RNase) such as RNase T1 from Aspergillus oryzae became available, which hydrolyzes specifically the 3-phosphodiester bond of guanylic acid in RNA. In addition, pancreatic RNase A, specific for the 3-cytidylic and 3-uridylic acids, was also already available then. These two enzymes substantially advanced the technology for RNA sequencing. In 1964, R. Holley and his associates for the first time determined the structure of yeast alanine tRNA ( Holley et al., 1964). Four years later in 1968, he was awarded the Nobel Prize in Physiology or Medicine for the structure determination of yeast alanine tRNA together with H. G. Khorana and M. W. Nirenberg for their contributions to the understanding of protein synthesis. Using the Holley\’s method, other scientists determined the structures of the remaining tRNAs.
The tRNA structure determination was successful because of their abundance and stability in the cells. In contrast, mRNAs exist in highly limited amounts in the cells with very short half-lives. So the major question for mRNA structure determination was then how an mRNA for a specific protein could be isolated in its intact form from cells. This was my first research theme, when I started my own laboratory at State University of New York at Stony Brook in 1971. Dr. A. Hirashima, the first postdoctoral fellow in my laboratory, discovered that the mRNA for the major outer membrane lipoprotein of Escherichia coli is highly abundant and most importantly, is extraordinarily stable with a half life of 12umin in comparison with other cellular mRNAs (less than 2umin) (Hirashima and Inouye, 1973). We then isolated the mRNA, which indeed functioned as the mRNA in a cell-free system to produce the lipoprotein (Hirashima et al., 1974). This result further encouraged us to isolate the mRNA for the lipoprotein for its structure determination. As far as I know, this mRNA is the only mRNA isolated from living cells for the determination of the entire nucleotide sequence.
The results in Fig. 8 showed that the calculated molecular mass of the protein deduced from the PVGOX gene was 65.5ukDa and the protein consist of 601 amino acids (Fig. 8). The calculated molecular mass of A. niger and P. variabile glucose oxidase is about 65,000, and the number of amino WY-14643 residues of their mature proteins of the glucose oxidase from A. niger and P. variabile have 583 and 605 amino acids, respectively ( Leskovac et al., 2005uanduPulci et al., 2004). The results in Fig. 8 also indicated that the protein had the signal peptide of 17 amino acids. In contrast, the signal peptides of the glucose oxidase from A. niger and P. variabile had 22 and 16 amino acids ( Pulci et al., 2004uanduHatzinikolaou et al., 1996).
Glucose oxidases from filamentous fungi are all extremely glycosylated proteins (Kriechbaum et al., 1989), and numerous functions have been projected for the carbohydrate moiety such as temperature and pH optima as well as thermal stability, for stabilization and activity of the three-dimensional structure (Kalisz et al., 1997). Comparison of the amino acid sequence of the PVGOX gene from the F1 strain with those of P. variabile and P. amagasakiense, showed total Six possible putative N-glycosylation sites at conserved positions ( Fig. 8); however, four N-glycosylation sites had been indicated for the enzyme from P. variabile ( Pulci et al., 2004), and five were the estimated sites for the P. amagasakiense Gox ( Kiess et al., 1998), which indicates that glucose oxidase produced by F1 strain may be more stable than that produced by any other Penicillium spp. due to high possible glycosylation sites. The deduced mature protein of F1 strain also showed three cysteine residues at conserved position, which is in corresponding with that of the study conducted by Pulci et al. (2004), Kiess et al. (1998) and Frederick et al. (1990) by using P. variabile, P. amagasakiense and A. niger, respectively ( Fig. 8).
Moreover, no introns were recognized in the PVGOX gene sequence ( Fig. 9). This, however, does not represent a surprise; in fact, no introns were identified in sequences of other fungal GOX encoding genes, such as those of P. variabile P16 ( Pulci et al., 2004), A. niger, T. flavus and P. amagasakiense ( Frederick et al., 1990uanduKriechbaum et al., 1989). These authors analyzed both genomic DNA and cDNA encoding glucose oxidase and also found no evidence for introns in the gene.
The histidine residues (His-536 or His-579) were located within active site of Gox protein while acting as the potential proton acceptor (Witt et al., 2000; Fig. 10). Similarly, glucose oxidase (Gox) with active site histidine residues i.e. His-520 or His-563 from P. amagasakiense has been proposed for this catalytic role ( Wohlfahrt et al., 1999). This P. amagasakiense histidine residues (His-520 or His-563) are conserved among all the enzymes in the same glucose methanol-choline oxidoreductase family, and is situated within a similar region of their amino acids sequences, although at fluctuating positions ( Kiess et al., 1998uanduCavener, 1992). For example, histidine residues also occurs in active site of Gox isolated from A. niger (His-516 or His-559) ( Witt et al., 2000uanduHecht et al., 1993). Helix and sheet nomenclature of Gox is as in Hecht et al. (1993). Similarly, Kiess et al. (1998) also identified the secondary structure of glucose oxidase and further they also mentioned different Domain that extended FAD-binding and FAD-binding domains are composed of numerous distinct sequence regions. The other three regions each contain a single contiguous sequence. Four major consensus patterns have been identified, including the nucleotide-binding consensus sequence close to their N-termini (Kiess et al., 1998).
Furthermore, it has been reported that, the fungal strains, especially Penicillium spp. are capable of producing glucose oxidase (Gox) enzyme and the calcium carbonate presence in the medium positively affect the glucose oxidase (Gox) and catalase (Cat) activities with a instantaneous negative effect on the glucose-6-phosphate isomerase activity which might cause a metabolic shift from glycolytic pathway (EMP) to direct oxidation of glucose by gluconic acid (GA), therefore, in that way increasing GOX levels ( Sandip et al., 2009. Our results showed that addition of CaCO3 to the production medium significantly induced the glucose oxidase gene expression (Fig. 12). It was also found that, the 40ug/l of calcium carbonate was more suitable for the high expression of the GOX gene in P. viticola F1 ( Fig. 12). Furthermore, during the fermentation due to gluconic acid formation the pH of the medium drops continuously which affects fungal growth, therefore, calcium carbonate addition also helps to prevent dropping of pH which may give some sort of mechanical support to fungal mycelium for appropriate growth (Petruccioli and Federici, 1993). Our findings about the calcium carbonate as inducer of glucose oxidase were confirmatory with the findings of study of Sabir et al. (2007), Hamid et al. (2003) and Liu et al. (2001) by using different fungal species.
Epigallocatechin-3-gallate; Fibronectin type II repeat; Green tea polyphenol; Matrix metalloproteinase-2; Molecular docking
Matrix metalloproteinases (MMPs) -2 and -9 constitute a distinct subgroup within the MMP family in terms of their substrate specificity and domain organization. They are also called gelatinases. They can digest collagen IV, a component of the basement membrane, and thus play a very important role in invasion and metastasis (Stetler-Stevenson et al., 1993uanduChabottaux and Noel, 2007). MMP-2 and MMP-9 are overexpressed in sera and malignant tissues of cancer patients (Pacheco et al., 1998, Fan et al., 2003, La Rocca et al., 2004, Pellikainen et al., 2004uanduStankovic et al., 2010), which often correlates with increased invasiveness and poor prognosis. In addition to the pro-domain, the zinc-containing catalytic domain, and the hemopexin domain that are common to most MMPs, the gelatinases have three fibronectin type II repeats inserted in their catalytic domain (Nagase and Woessner, 1999uanduVisse and Nagase, 2003). Like other MMPs, the gelatinases are secreted in the latent or inactive form. They are activated by alkylating agents or proteases via the “cysteine switch” mechanism ( Visse and Nagase, 2003). They are potential therapeutic targets, which have motivated studies on drug development.
()-Epigallocatechin-3-gallate (EGCG), the major green tea polyphenol, is popular due to its purported health benefits and biological effects. Notably, EGCG affects migration, invasiveness and metastatic potential of cancer cell lines. It also suppresses experimental metastases in mice (Yang et al., 2006, Yang and Wang, 2011uanduYang et al., 2011). Modulation in the AP 18 and activity of MMPs, as a primary cause of anti-metastatic effect of EGCG, is a subject of much scrutiny. EGCG downmodulates MMP-2 and MMP-9 expression at various levels including transcription, protein content and secretion (Annabi et al., 2002, Maeda-Yamamoto et al., 2003, Roomi et al., 2006, Roomi et al., 2009, Kato et al., 2008, Sen et al., 2009, Sen et al., 2010, Park et al., 2010uanduFarabegoli et al., 2011) and directly inhibits MMP-2 in cell free systems (Demeule et al., 2000uanduGarbisa et al., 2001). However, the mechanism of inhibition has not been adequately addressed. The present study is an attempt to obtain insights into EGCG-mediated inhibition of MMP-2 through an in silico molecular docking approach. Our results suggest that EGCG possibly inhibits MMP-2 by targeting the fibronectin type II repeats 1 and 3, and interfering with proper positioning of the substrate.
2. Materials and methods
2.1. Molecular docking
In silico molecular docking studies were carried out using AutoDock 4.2 ( Morris et al., 2009). The three-dimensional atomic coordinates for proteins and ligands were downloaded and prepared for molecular docking using tools available in AutoDock. Hydrogens were added to the polar atoms of proteins and Gasteiger charges were assigned. All the crystallographic water molecules of the protein were eliminated before molecular docking. However, in case of MMP-2, a catalytically essential crystallographic water molecule present in the active site was retained. Grid maps were assigned to each atom type in the protein and ligand. Additional electrostatic and desolvation maps were also calculated. Molecular docking simulations were performed using the Lamarckian Genetic algorithm (LGA) as the search algorithm. All molecular modeling experiments were carried out with COOT (Emsley et al., 2010) and the figures showing protein-ligand interactions were generated using PyMOL (The PyMOL Molecular Graphics System, Schrodinger, LLC).
2.2. Preparation of MMP-2 structure
The three-dimensional atomic coordinates of full length MMP-2 (PDB id: 1CK7) were downloaded from the Protein Data Bank (Berman et al., 2000). The structure had two major constraints: (1) the propeptide domain was intact rendering the protein inactive and (2) the catalytically indispensible Glu404 was mutated to alanine. Thus, to mimic a catalytically active and functional structure of MMP-2, the propeptide domain (amino acids 30a109) was removed and the alanine residue at the position 404 was replaced with glutamate using COOT. Subsequently, the structure was refined using 3Drefine server (Bhattacharya and Cheng, 2013) to overcome any anomalies that could have arisen due to the aforementioned changes. The 3Drefine refinement protocol combined iterative optimization of hydrogen bonding network with atomic level energy minimization on the optimized model using the knowledge-based force fields for efficient protein structure refinement. The hydrogen-bonding network was optimized manually using COOT. Thereafter, the refined model was validated with PROCHECK (Laskowski et al., 1993), which revealed that 90.2% of the residues were in the most favoured region, 9.2% of the residues were in the additionally allowed region, 0.7% of the residues were in the generously allowed region, and no residue was in the disallowed region (Supplementary data, Fig. S1). These results indicate that the protein model generated for active human MMP-2 was of good stereochemical quality and fit for docking studies. Furthermore, the reliability of the refined structure was confirmed by docking with the two known inhibitors, namely Batimastat and Marimastat (Rasmussen and McCann, 1997), which bind to the catalytic domain of MMP-2.
RA is a chronic autoimmune joint disease where persistent inflammation affects bone remodeling leading to progressive bone destruction (Harnden et al., 2016). In RA, abnormal activation of the immune system elevates pro-inflammatory cytokines and chemokines levels, which can promote synovial angiogenesis and leukocyte infiltration. The synovium forms a hyperplastic pannus with infiltrated macrophage-like and fibroblast-like synoviocytes and invades joints by secreting proteinases and inducing osteoclast differentiation (El Defrawy et al., 2015). Recent studies have shown that CXCL12, CCL5 and IL-1β could induce inflammation, and synovial pannus formation in RA (Pablos et al., 2003, Grassi et al., 2004uanduOlkkonen et al., 2015). We hypothesize that during the process of RA, up-regulation of CXCL14, CXCL12, IL-1β, and CCL5 could induce the inflammatory reaction, synovial fibroblasts, synovial pannus formation, and even malignancy of RA.
ALAD catalyzes the second step in the porphyrin and heme biosynthetic pathway; zinc is essential for enzymatic activity (Schmitt et al., 2016uanduZorana et al., 2016). ALAD mainly involves in metabolic pathways, including response to fatty acid, response to glucocorticoid, and so on. ACO1, this gene encodes a member of the aconitase/IPM isomerase protein family, which is involved in metabolic pathways and tricarboxylic TG-101348 cycle (TAC). The encoded protein has been identified as a moonlighting protein based on its ability to perform mechanistically distinct functions (Sekeli et al., 2014). Depending on iron levels in the cytosol, the encoded protein can function as either an aconitase enzyme or as an mRNA binding protein. When cellular iron levels are high, the encoded protein functions as an aconitase, an essential enzyme in the TCA cycle that catalyzes the conversion of citrate to isocitrate. When cellular iron levels are low, the encoded protein regulates iron uptake and utilization by binding to iron-responsive elements in the untranslated regions of mRNAs for genes involved in iron metabolism (Gangloff et al., 1990). ME1 catalyzes the NADPu+ dependent conversion of S-malate to pyruvate, which is involved in metabolic pathways, pyruvate metabolism, and PPAR signaling pathway. Multitudinous functions of it were regulation of NADP metabolic process, oxidation-reduction process and carbohydrate metabolic process, etc. (Skov et al., 1994). MTHFD2L terms methylenetetrahydrofolate dehydrogenase (NADPu+ dependent) 2-like, which is involved in metabolic pathways, including oxidation-reduction process, methionine biosynthetic process and purine nucleotide biosynthetic process, etc. (Bolusani et al., 2011uanduShin et al., 2014). In our previous study, we used gas chromatography time-of-flight mass spectrometry (GC-TOF/MS) technology to observe changes in the metabolic profiles of urine in rats with AA. These findings demonstrated that purine, amino acid, fat, and energy metabolism were disturbed in rats with AA. Our research has demonstrated clearly that the underlying metabonomics pathogenesis of RA may be caused by dysfunction in a range of biosynthetic and catabolic pathways, which leads to increased oxygen free radicals and inflammation (Jiang et al., 2016cuanduJiang et al., 2016b). The high expression of ALAD, ACO1, ME1 and MTHFD2L in this study suggested that RA is caused by dysfunction metabolic pathways, which is consistent with our previous study.
Although the detailed mechanisms of these genes in RA remain largely unknown, the differentially expressed LncRNAs may contribute to RA by regulating these coding-genes. Our co-expression network analysis manifested a more complex regulatory relationship between LncRNAs and mRNAs in RA compared with the controls. LncRNAs XR_008357, U75927, MRAK046251, XR_006457, DQ266363, MRAK003448, in the RA co-expression network were connected to 50 differentially expressed mRNAs, respectively. Particularly, the LncRNA MRAK003448, was connected to 192 differentially expressed mRNAs. Additionally, LncRNA MRAK046251, was connected to 103 differentially expressed mRNAs. These findings indicate that these LncRNAs may play a vital role in their corresponding networks or signaling, and therefore may contribute to the molecular regulation of RA. The dysregulation of noncoding RNAs and/or an altered noncoding RNA response have been suggested to play an important role in the etiology and pathophysiology of RA through the processes of immune response and inflammation response. LncRNAs participate in the regulation of gene expression by targeting transcription factors, initiating chromatin remodeling, regulating methylation complexes, and suppressing nearby transcription (Zhai et al., 2015). Moreover, LncRNAs have been shown to be involved in RA, osteoarthritis (OA), cognitive function and the development of synovial macrophage, synovial fibroblasts, synovial pannus formation, osteoblast differentiation, and joint destruction (Liu et al., 2014uanduWan et al., 2014). Several recent researches have manifested that LncRNA expression is altered in RA. For example, LncRNA-NR024118, which is down-regulated in the RA model group, serves as a therapeutic target inhibition of inflammatory response (Yang and Chen, 2015). Our current understanding on potential roles of LncRNA in RA is still in its infancy. Furthermore, several approaches can be employed to determine their biological functions, including LncRNA silencing, LncRNA over expression and structure disruption. This study provides new profound understanding of the molecule mechanisms of RA.
Delta is the largest cytosolic-GSTs subgroups in Drosophila melanogaster (11), Anopheles gambiae (17), Acyrthosiphon pisum (16), Aedes aegypti (8), Nasonia vitripennis (4), and Bombyx mori (5), while there are only 3 members in Tribolium castaneum ( Shi et al., 2012uanduSchama et al., 2016). Drosophila GSTd1 (CG10045) have DDT dehydrochloinase activity suggested that GSTd play an important role in DDT metabolism. And a number of Delta GSTs in D. melanogaster have GSH peroxidase activity against cumene hydroperoxide or catalyze the lipid peroxidation productions, which indicated that metabolism of products of lipid peroxidation is a biochemical pathway with detoxification as well as regulatory functions ( Tang and Tu, 1994uanduSawicki et al., 2003). Two another Delta GST genes, AgGST1-5 and AgGST1-6, were isolated from a DDT resistant strain of A. gambiae and their proteins expressed in Escherichia coli exhibited very high level of activity to DCNB which indicated that they were involved in insecticide resistance ( Ranson et al., 1997). While, a Delta GST has been cloned from a pyrethroid resistant strain of Nilaparvata lugens and the recombinant protein has high peroxidase activity, which proposed its critical function for preventing oxidative damage ( Vontas et al., 2002). However, not all Delta GSTs show the similar functions and there were several differences in subfamilies of Delta GSTs. In Culex pipiens, CpGSTd1 exhibited peroxidase activity and metabolize DDT, but CpGSTd2 appeared as no activity. And, both of them do not appear to play major roles in permethrin resistance in mosquitoes ( Samra et al., 2012). In addition, it is hard to detect the Ximelagatran of some Delta GSTs in the detoxification organ (fat boby), which suggested that Delta GSTs have variety functions in Bombyx mori ( Yu et al., 2008) or Tenebrio molitor ( Liu et al., 2015). Thereby, the physiological functions of Delta GSTs are varied from one insect to another, and some of these still poorly understood.
The red flour beetle, T. castaneum (Coleoptera, Tenebrionidae) is a worldwide notorious agricultural pest of stored grain and cereal products. Our previous study has identified 3 Delta GSTs of T. castaneum ( Shi et al., 2012). The purification proteins exhibited a high activity toward to CDNB and knockdown any one of them in T. castaneum caused increasing susceptibility to insecticides which suggested they play an important role in insecticide resistance. Intriguingly, loss of TcGSTd1 caused approximately 100% mortality which has never been reported in any insects before (data not shown). And it is still unknown how TcGSTd1 performs its functions in the red flour beetle. Therefore, in order to clarify the specific function and especial information in regulatory system of TcGSTd1 gene. RNA-sequencing technology and RNAi were merged to investigate the potential functions of TcGSTd1, and our study can shed new lights in signaling modulated systems of relative genes in insect species.
2. Material and methods
In this study, T. castaneum Georgia-1 (GA-1) strain was used as experimental animal. Insects were reared in whole wheat flour containing 5% brewer\’s yeast at constant temperature (30uC) and relative humidity (55%) under standard conditions (Reidy et al., 1990).
2.2. Double-strand RNA synthesis and injection
For double-strand RNA (dsRNA) synthesis, primers containing TcGSTd1-specific sequences (sense primer: 5-TATTAAGATCAACCCGCAAC-3, antisense primer: 5- TCGACCATCTGCTTAAAGAT-3) and the T7 polymerase promoter (TAATACGACTCACTATAGGG) at the 5-end of both the sense primer and anti-sense primer were designed to amplify dsDNA of TcGSTd1. And TcGSTd1 dsRNA synthesis and RNAi were performed as described previously ( Li et al., 2014b). Larvae injected with TcGSTd1 dsRNA were denoted as ds-TcGSTd1 group, and larvae injected with an equal volume of buffer were denoted as control group.
2.3. RNA preparation and Illumina sequencing
Control and RNAi of TcGSTd1 beetle samples were collected and used for RNA-sequencing. Total RNA was isolated separately from of control and ds-TcGSTd1 insects at the fifth day after injection by using the RNAiso™Plus Trizol reagent (TaKaRa), which according to the manufacturer\’s protocol. The quality and quantity of total RNA samples were assessed by using a NanoDrop 2000 spectrophotometer (Thermo Scientific, Wilmington, DE, USA), and experimental samples were normalized to the same concentration. The integrity of RNA was detected by using a 1% agarose gel and Agilent 2100 Bioanalyzer. Poly (A) mRNA was isolated by using oligo(dT) beads and was disrupted into short fragments (approximately 200ubp). The fragments were purified with a QIAquick PCR Extraction Kit (Qiagen, Germany), followed by end repairing and adaptor ligation. Experimental cDNA syntheses were performed by using Illumina Tru-Seq™ RNA sample preparation kit according to the manufacturer\’s protocol. Single-end RNA-sequencing libraries of control and ds-TcGSTd1 samples were prepared and then sequenced on the Illumina HiSeq™ 2000 platform. And the raw data of RNA-sequencing were deposited to the NCBI Sequence Read Archive (SRA) database (http://trace.ncbi.nlm.nih.gov.ezproxy.lib.ncyu.edu.tw/Traces/sra_sub/sub.cgi?login=pda), and the accession numbers were SRR3087513 (control) and SRR2087948 (ds-TcGSTd1).
The gardeners buying products sourced from conventional agriculture often justify their choice by indicating that “organic products are much too expensive, and not for everybody”, or by the fact that they do not believe that products labeled organic are really organic. Sometimes it appears they simply do not maintain any relationship between the way they cultivate and what they buy.
We assembled three theoretical profiles of gardeners from the analysis of explored variables: the Sunday gardener, the hedonist gardener and the militant gardener. They correspond to three types of commitment in gardening activity, which differ in motivations, agronomic practices, the source of produce purchased, and the links which can be established between them (Table 3). All of the gardeners are found on the continuum created with these categories.
Characteristics of gardeners; theoretical profiles.Theoretical profile (socio-professional group)MotivationsAgronomical practicesPerception of agriculturePurchase of produceSunday gardener (retirees, working class, intermediate classes)PastimeContact with the natureMeetingsDiggingPossible use of pesticidesCriticism of industrial agriculture but consumption of produce from industrial sourcesBuys supermarket produce from industrial agriculture sourcesHedonist gardener (retirees, intermediate classes)Pleasure to produceContact with the natureSource of energyDigging/take care of the LY300164 (minimal turning of soil)Diseases: no treatment or treatment with natural products/plants associationCriticism of industrial agriculture with efforts to purchase locally grown produce or organic produceBuys supermarket produce from industrial agriculture sources and organic or locally grown produceMilitant gardener (upper and intermediate classes)Passion/pleasureContact with the naturePolitical motivations: reappropriation of the food supply, environmental protection, social changeTake care of the soil (minimal turning of soil)Diseases: no treatment or treatment with natural products/plants associationStrong criticism of industrial agriculture and rejection of produce from industrial sourcesBuys organic produce from identified local farmersFull-size tableTable optionsView in workspaceDownload as CSV
The Sunday gardener
The Sunday gardener is found primarily in the family gardens. A working class, middle-class, or retired male, he gardens for the pleasure of being outside while cultivating his vegetables. He sees gardening as a pastime, and associates the garden with a little slice of countryside where he can breathe fresh air, sit in a chair, and discuss gardening with his neighbors or spend time as a family. His garden might be more organized for leisure activities with a small building, a paved terrace (although generally forbidden in the regulations), a barbecue, etc. He has an aperitif there, he may picnic in his garden, and he organizes festivities there. His garden is an extension of his domestic sphere. This gardener works his garden much the same way as he remembers his parents in theirs. He waters and maintains a piece of lawn on his plot, treats his tomatoes with the Bordeaux mixture, and might use other chemical products to maintain his garden. To complement his own harvest (which he considers as produced naturally), he buys produce from the supermarket, without paying particular attention to origin or production techniques.Portrait of a Sunday gardenerLouis, a 65 year-old former truck driver, had some gardening experience when he was younger but didn;t start gardening in a community plot until his retirement. He considers his plot as a place for recreation as well as a source of produce from his “kitchen” gardening activities. He planted magnolia and olive trees, and landscaped with decorative flowers, two small ponds and a pergola to create space for outdoor family meals. For Louis, his garden represents primarily the opportunity to enjoy an outdoor activity and interact with other gardeners rather than concentrating on production. Nevertheless he takes pleasure in consuming the tomatoes, zucchini, eggplant, radishes and peppers grown in his own plot. Most of the seeds used come from his own vegetables. He turns the soil by hand (spade) at the end of each winter, and adds manure collected from fields around nearby villages. He occasionally resorts to chemical pesticides to maintain plant quality. The garden does not provide all the produce he needs for consumption. He also relies on vegetables from super markets, and remains unimpressed with organic labels, having little confidence in their compliance with certification requirements. “It\’s impossible to know where that comes from; that\’s a load of garbage.” Louis thinks that industrial farming produces inferior vegetables, but believes it is a “necessary evil” in order to insure enough food for everyone.
The complete set of raw sequencing files is available from the National Center for Biotechnology Information (NCBI) database under accession number SRP053237 (http://www-ncbi-nlm-nih-gov.ezproxy.lib.ncyu.edu.tw/projects/geo/). All other supporting data are included in the Supplementary files.
2.4. RNAseq data processing
The RNAseq data went through multiple stages of thorough quality control as recommended by Guo et al. (2013c). Raw data and alignment quality control were performed using QC3 (Guo et al., 2014a), and gene quantification quality control was conducted using MultiRankSeq (Guo et al., 2014b). Raw data were aligned with TopHat2 (Kim et al., 2013) against the mm10 mouse reference genome, and read counts per gene were obtained using HTSeq (Anders et al., 2014). Normalized read counts (used in all plots) were obtained by normalizing each gene\’s read count against the sample\’s total read count, then multiplied by a constant (1 × 106). pcRNA and lncRNA were annotated using references file MM10 v38.82 downloaded from Ensembl. Hierarchical clustering analysis and heatmaps were produced using the Heatmap3 (Zhao et al., 2014) package from R. For all samples, quality control data are contained in Table S2.
Differential expression analyses between all postnatal ages and AC480 regions were performed using MultiRankSeq (Guo et al., 2014b) with three methods for RNAseq analysis: DESeq (Anders and Huber, 2010); edgeR (Robinson et al., 2010); baySeq (Hardcastle and Kelly, 2010). These three methods were chosen based on results of several previous studies in which multiple RNAseq differential analysis methods were compared for accuracy and sensitivity of read count-based data (Dillies et al., 2013, Guo et al., 2013a, Kvam et al., 2012, Robles et al., 2012 and Soneson and Delorenzi, 2013). In analyses of the same dataset, the methods typically differ in numbers of differentially expressed genes identified in a comparison of any two samples and also in the direction of expression (up- or down-regulation). False discovery rate (FDR < 0.05) was used to correct multiple testing. The differential expression datasets associated with each pairwise comparison (4 ages × 2 brain areas) are contained in Supplementary Tables S5–S10. Trend analysis of lncRNA expression across the four age points (P7 → P14 → P21 → Adult) was conducted using the Mann-Kendall trend test (Hirsch et al., 1982).
Potential interactions between lncRNAs and pcRNAs were identified using Spearman correlation analysis. To evaluate lncRNA coding potential, we employed the Coding-Potential Assessment Tool (CPAT) (Wang et al., 2013b) (Table S11). BEDTools (Quinlan and Hall, 2010) was used to extract the genomic sequences of lncRNA as input for CPAT. We also performed network analysis using Cytoscape (Saito et al., 2012) and function analysis using WebGestalt (Wang et al., 2013a) based on the correlation results (Table S12). To ensure high correlations were not due to static low expression values across all samples, we filtered out the lowest 25% of all RNAs based on standard deviation. For a subset of genes, lncPro (Lu et al., 2013) was applied to obtain interaction scores between lncRNAs and selected protein targets.
2.5. Database and Look-Up tool for generating lncRNA maturational profiles
Table S4 contains the raw read counts, differential analyses, and pcRNA correlations for all lncRNAs. Tables S5–10 contain the differential expression analyses for comparisons of postnatal age and brain region. To facilitate screening and extraction of maturational profiles from the database, a Look-Up tool was developed (Table S13). The tool automatically plots the maturational profiles and correlation matrices for any single lncRNA gene or list of genes (up to 25 at a time) by brain region. It also generates a listing of the normalized counts for all samples by age and brain region for custom applications.
To the best of our knowledge, there are limited data about the mechanism of induction or inhibition in insect Vg by Cd. Cervera et al. (2005) have suggested that Cd effect on vitellogenesis was not mediated by a disturbance in JH production, but probably by an alteration in the JH hormone receptor activity, as happens in fish (Le Guevel et al., 2000). Hence, to understand the modulatory mechanisms of Cadmium on Vg expression in S. exigua, more detailed studies will be necessary.
In summary, this is the first report of Vg gene sequence and its detailed analysis in S. exigua which showed a developmental stage-, tissue- and sex-specific expression. Cd down-regulation of Vg gene expression suggests Cd stress elicits an important Vg response in S. exigua. However, more detailed studies on the mechanism of induction or inhibition in insect Vg by Cd might be a next step to allow us to further understand the influence of heavy metals on regulation of vitellogenesis.
Hotspots of recombination have provided a valuable tool in elucidating the mechanism of homologous recombination, for example, the ARG4 and HIS4 hotspots of Saccharomyces cerevisiae ( Sun et al., 1989, White et al., 1993 and Fan et al., 1995), and the M26 and mbs1 hotspots of S. pombe ( Steiner et al., 2002 and Cromie et al., 2006). M26 was originally discovered among a large number of mutations in the ade6 gene that uniquely showed a 10–20 fold higher frequency of recombination compared to other mutations, including the closely linked M375 mutation ( Gutz, 1971). Characterization of M26 showed that it was active in meiosis, but not mitosis ( Ponticelli et al., 1988). It is also context-dependent – it is active in some, but not all, sites in the genome and is inactive when located on a plasmid ( Ponticelli and Smith, 1992 and Virgin et al., 1995). The reason for inactivity on a plasmid is not known, but it was assumed that the hotspot requires some aspect of BMS-536924 structural context not found on plasmids. The M26 hotspot results from a single G?T mutation in the ade6 open reading frame ( Szankasi et al., 1988), which creates a seven bp sequence, ATGACGT (Schuchert et al., 1991) that is a binding site for the Atf1-Pcr1 transcription factor, which is also required for activity of the hotspot ( Wahls and Smith, 1994 and Kon et al., 1997).
Like hotspots in S. cerevisiae ( Ohta et al., 1994 and Wu and Lichten, 1994), the M26 hotspot is a site of meiosis-induced chromatin remodeling resulting in a micrococcal nuclease (MNase) hypersensitive site ( Mizuno et al., 1997). Also like hotspots in S. cerevisiae, M26 is the site of meiosis-induced double-strand breaks (DSBs) that require both general recombination factors, like Rec12 (Spo11 homolog), as well as Atf1 and Pcr1, which are required specifically for the M26 hotspot ( Steiner et al., 2002).
Further characterization of M26 showed that hotspot activity could be enhanced by extending the 7 bp sequence to make a 10 bp palindromic sequence, ATGACGTCAT. This longer sequence has about 3-fold higher activity than the seven bp sequence (Steiner and Smith, 2005b) and is associated with meiosis specific double-strand breaks (DSBs) at multiple naturally-occurring sites in the S. pombe genome ( Steiner and Smith, 2005a, Wahls and Davidson, 2010, Steiner et al., 2011 and Fowler et al., 2014). The 10 bp M26 motif also creates a hotspot when placed in the ADE2 promoter region of S. cerevisiae but not in the ADE2 open reading frame ( Steiner and Steiner, 2012), which is consistent with most DSBs in S. cerevisiae occurring in gene promoters ( Pan et al., 2011). This also suggests that some factor inhibits the activity of potential hotspots in protein coding regions. However, this inhibition is not absolute as three tandem copies of M26 generated a hotspot in the ADE2 open reading frame ( Steiner and Steiner, 2012). Given the higher activity of the 10 bp M26 sequence, we investigated the properties of this motif in one, two, or three copies both on a chromosome and on a plasmid.
Up to now, the GenBank database search revealed 14 Vg sequences from Lepidoptera. In this study, we have identified the fifteenth sequence of lepidopteran insect Vg, that of S. exigua, which provided the basic information for its functional analysis. The deduced amino-acid sequence of Vg from S. exigua was aligned with the corresponding sequences of other lepidopteran insects by Vector NTI 9.0 software. S. exigua Vg was most similar to Vg from Spodoptera litura (87.5% identity), followed by Helicoverpa armigera (70.16%), Actias selene (54.93%), Saturnia japonica (54.22%), Samia cynthia (54.19%), Antheraea pernyi (54.08%), Antheraea yamamai (53.55%). It had only 47% identity to Lymantria dispar. Alignment of the C-terminal region revealed that the GL/ICG motif, cysteine residues and a DGXR motif (upstream of the GL/ICG motif) were highly conserved among lepidopteran insect Vgs ( Fig. 2). However, other characteristics of insect Vg were not observed in S. exigua Vg, such as polyserine tracts which contain tandem serine repeats. In common, polyserine domains are located on both sides of a consensus RXXR of Insect Vgs. The polyserine regions might serve as good phosphorylation sites and a lack of polyserine domains may indicate the involvement of different mechanisms for Vg receptor binding during endocytosis in insects ( Xie et al., 2009, Wahli, 1988 and Tufail and Takeda, 2008).
Fig. 2. Partial amino PQ 401 alignment of SEVg with other Vg sequences. Alignment is showing the DGXR and GLCG conserved region in months Vgs. Identical residues are shown in black background while conservative residues are in grey background. BMVg: the Vg from Bombyx mandarina, CSVg: the Vg from Chilo suppressalis, CCVg: the Vg from Cadra cautella, ASVg:the Vg from Actias selene, APVg: the Vg from Antheraea pernyi, AYVg: the Vg from Antheraea yamamai, BOVg: the Vg from Bombyx mori, CMVg: the Vg from Cnaphalocrocis meinalis, CEVg: the Vg from Corcyra cephalonica, HAVg: the Vg from Helicoverpa armigera, LDVg: the Vg from Lymantria dispar, SCVg: the Vg from Samia cynthia, SJVg: the Vg from Saturnia japonica, SLVg: the Vg from Spodoptera litura, SEVg: the Vg from Spodoptera exigua.Figure optionsDownload full-size imageDownload high-quality image (767 K)Download as PowerPoint slide
3.3. Phylogenetic relationship
The evolutionary relationship of 15 Vgs derived from lepidopteran insects was evaluated after aligning the complete amino acid sequences and conducting a phylogenetic analysis using neighbor joining methods (NJ) with MEGA version 5.1 and representative species of the orders Diptera and Hymenoptera (Anopheles minimus, Anopheles subpictus, Encarsia formosa and Pteromalus puparum, respectively) as outgroups. Within lepidopteran insects, the monophyly of six families has been well supported by NJ tree with high values. S. exigua clustered with S. litura and H. armigera with high support which all belong to Noctuidae. The familial relationships within Lepidoptera clearly recovered the phylogenetic relationships. Lymantria dispar, occurs here in a basal position of the Lepidoptera with high bootstrap support (100%) which is consistent with previous study based on Vg sequence . To more fully elucidate phylogenetic relationships within Lepidoptera based on comparative analysis of Vg gene sequence, further study is needed based on increased taxon sampling within major groups of Lepidoptera.
NJ tree of lepidopteran insects Vgs. Numbers on the branches represent the percentage of 1000 bootstrap samples supporting the branch.Figure optionsDownload full-size imageDownload high-quality image (528 K)Download as PowerPoint slide
3.4. Vg gene expression
S. exigua Vg was expressed specifically in the female fat body ( Fig. 4A), but not in other tissues including the ovary, cuticle, gut, muscle and Malpighian tubules (Fig. 4B). Data showed that no transcripts were detected at entire nymph and early pupa stages of S. exigua ( Fig. 5A). The developmental expression patterns of Vg showed that the Vg expression in the fat body was first transcribed in 5th day female pupae and showed a low expression level (relative expression level = 0.00043). Its expression was significantly increased from late stage of female pupa to 24-h-old female adults, peaked in 48-h-old female adults before started to decrease quickly (Fig. 5B).