Background. Leprosy is a chronic infectious disease caused by the intracellular acid-fast bacilli Mycobacterium leprae; it has been determined that genetic factors of the host play an important role in the disease susceptibility. Thus, in this case-control study, we evaluated the possible association between the IL-17A G-197A (rs227593) and IL-17F A7488G  gene SNPs and susceptibility to leprosy disease in Mexican population. Methods. Seventy-five leprosy patients and sixty-nine control subjects were included. Both SNPs were genotyped with the polymerase chain reaction-restriction fragment length polymorphism technique. Results. We found nonsignificant differences in genotype and allele frequencies related to IL-17A G-197A (rs227593) and IL-17F A7488G  gene SNPs in MB as well as subclinical forms of leprosy disease versus healthy individuals. Conclusions. Since the sample size is not large enough, it is difficult to sustain an association of susceptibility to leprosy with genotypes or allele frequencies of IL-17A G-197A (rs227593) and IL-17F A7488G , suggesting that IL-17 polymorphisms have no significant role in the genetic susceptibility to development of this disease in the Mexican Mestizo population. Mycobacterium leprae. It affects the skin and peripheral nerves of susceptible individuals, causing irreversible impairment of nerve function and consequent chronic disability [Leprosy is a human chronic infectious disease caused by the intracellular acid-fast bacillisability . Despitesability , 3.+ T cells and it is characterized by a Th2 T-cell immune response, with an antibody complex formation that is unable to contain the infection. By contrast, the TT skin lesions are characterized by a predominance of CD4+ T cells; they present a Th1 T-cell cytokine reaction with a vigorous T-cell response that restricts the M. leprae growth [The clinical spectrum of leprosy includes two poles, the lepromatous (LL) and tuberculoid (TT), with several intermediate (I) or dimorphic forms, including borderline tuberculoid (BT), mid-borderline (BB), and borderline lepromatous (BL); furthermore, in the WHO classification standards, the BB, BL, and LL individuals belong to multibacillary (MB) patients, whereas the BT and TT individuals go to paucibacillary (PB) patients. Immunologically, the LL skin lesions are distinguished by predominance of CD8e growth .On the other hand, this balance between the Th1 (TT) and Th2 (LL) response can be influenced by a third participant, the Th17 cells, which are known to produce a proinflammatory cytokine called interleukin-17 (IL-17) . IL-17A and IL-17F genes including the G-197A (rs227593) and A7488G , respectively, which have been identified to be associated with several diseases [ IL-17A and IL-17F genes SNPs with susceptibility or resistance to develop leprosy in Mexican patients.Based on the biological relevance of IL-17A and IL-17F cytokines, in this study we analyzed two single-nucleotide polymorphisms (SNPs) within thediseases , the aimIn this study, we recruited a total of 75 patients with leprosy  which were classified according to the International Criteria established by Ridley and Jopling , 12. The IL-17A G-197A (rs227593) and IL-17F A7488G  gene polymorphisms were analyzed by the polymerase chain reaction-restriction fragment length polymorphism system (PCR-RFLP) which was slightly modified from the two previously described methods [μL, containing 100 ng of gDNA, 1 μM of each oligonucleotide, 0.2 mM of each dNTPs, 2 mM of MgCl2, 0.5 U/μL of Taq DNA polymerase, and supplied buffer enzyme 1X . The amplification conditions were 95°C for 3 min, 35 cycles of 95°C for 30 s, 56°C for 30 s, 72°C for 30 s, and a final extension of 72°C for 3 min for IL-17A G-197A and for IL-17F A7488G they were 95°C for 3 min, 35 cycles of 95°C for 30 s, 60°C for 30 s, 72°C for 30 s, and a final extension of 72°C for 3 min. The PCR products were digested at 37°C for 2 h with 1 U of XagI and NIaIII restriction enzymes  for the identification of the IL-17A G-197A (rs227593) and IL-17F A7488G  gene polymorphisms, respectively. Finally, the digested PCR products were electrophoresed on 3% agarose gels ethidium bromide stained for the identification of the genotypes both polymorphisms.For genotyping, venous blood samples of leprosy patients and controls were collected into EDTA-containing tubes, and the genomic DNA (gDNA) was extracted from peripheral blood leukocytes according to Miller's salting-out method . The IL- methods . The PCRχ2) . Comparison data were evaluated by χ2 test or Fisher's exact test when applicable. The P values were adjusted with Bonferroni correction for multiple testing (Pc).Frequencies of genotypes and alleles, Hardy-Weinberg Equilibrium (HWE), and OR with a 95% CI were estimated using the Chi-square test ( IL-17A G-197A (rs227593) and IL-17F A7488G  gene polymorphisms. For this purpose and taking into account that the majority of cases of leprosy in Mexico are MB [ IL-17A G-197A (rs227593) and IL-17F A7488G  gene polymorphisms in patients with leprosy and healthy controls is shown in P > 0.05; data not shown). The distribution of genotypic and allelic frequencies between MB leprosy patients and control group did not show significant differences in IL-17A G-197A (rs227593) and IL-17F A7488G  gene polymorphisms (P > 0.05). This lack of association was confirmed when we performed the analysis in the clinical subtypes (LL and D) of MB leprosy, where we did not find significant differences  who were genotyped for theA rs22759 and IL-1o are MB , we only M. leprae develop leprosy, suggesting that genetic background is relevant in the development of it, since it determines the control of the immune response against this infection [ IL-17A G-197A (rs227593) and IL-17F A7488G  gene SNPs in the context of leprosy to identify if there was any association with susceptibility to leprosy in the Mexican Mestizo population. We did not find an association between both IL-17A G-197A (rs227593) and IL-17F A7488G  gene SNPs and MB leprosy or their clinical subtypes, so our study provides evidence of lack of association with susceptibility in leprosy patients; moreover, the genotype and alleles frequencies have not been reported previously in Mexican population.Despite global coverage of multidrug therapy promoted by the World Health Organization the leprosy remains as a public health problem . Nowadaynfection . In this IL-17F A7488G  gene SNP is associated with susceptibility to leprosy; likewise, they found that AG genotypes confer a decreased risk of acquiring leprosy in the North Indian Cohort and observed that this SNP also influences the clinical phenotypes in leprosy disease [ IL-17A G-197A (rs227593) and IL-17F A7488G  gene SNPs and risk of tuberculosis (TB), gastric cancer, rheumatoid arthritis (RA), intestinal bowel disease (IBD), Crohn's disease (CD), ulcerative colitis (UC), and others [ IL-17F A7488G  gene SNP were more susceptible to acquiring tuberculosis, compared to the GG genotype [ IL-17F A7488G  gene SNP was associated with risk of gastric cancer and GA genotype was associated with the clinic-pathological features and not with the risk of gastric cancer itself. However, in the case of the IL-17A G-197A (rs227593) gene SNP, this polymorphism was not associated with the risk of gastric cancer [ IL-17A G-197A (rs227593) gene SNP was significantly associated with the risk of gastric cancer, since patients who had the homozygous AA were 2.9 times more likely to develop disease; furthermore, the presence of a single A allele increases the risk of gastric cancer up to 1.7-fold. This association was only observed in early stage gastric adenocarcinomas and was not linked to H. pylori infection [ IL-17A G-197A (rs227593) gene SNP with susceptibility to the development of osteoarthritis (OA) in the Korea population has been described; however, they did not find relationship between the IL-17F A7488G  gene SNP and OA susceptibility [ IL-17F A7488G  gene SNP is not considered as a marker of susceptibility for IBD per se but is associated with increased disease activity [ IL-17F A7488G  gene SNP has no effect on susceptibility to DC but is associated with protection to UC [ IL-17A G-197A (rs227593) and IL-17F A7488G  gene SNPs could be due to the type of pathology studied but mainly to the frequency at which the polymorphic allele in each population is presented, which reflects the genetic heterogeneity of the different population, suggesting that the low frequency or absence of the polymorphic alleles may confer an advantage of decreasing risk of susceptibility. Moreover, environmental and socioeconomic factors may influence the development of different pathologies. In conclusion, we identify lack of association of IL-17A G-197A (rs227593) and IL-17F A7488G  gene SNPs with susceptibility to leprosy in Mexican population.This observation differs with a study in the North India Cohort, where thed others . In thisgenotype , whereasc cancer . Moreovetibility . With reactivity , whereasG-197A rs7593 and


These panels were reproduced from Figure 1 of Sallustio F, Serino G, Costantino V, Curci C, Cox SN, et al. (2013) miR-1915 and miR-1225-5p Regulate the Expression of CD133, PAX2 and TLR2 in Adult Renal Progenitor Cells. PLOS ONE 8(7): e68296. doi:Additionally, the cytofluorimetric images in Figure 3, panels B (CD133) and D (CD44) are the same respectively as Figure 1, panels A and C in Sallustio et al. PLOS ONE (2013). These panels represent the same cells in each article.An investigation by a Scientific Committee at the University of Bari concluded that these image duplications arose by inadvertent error, due to poor management of the image archive, and that this does not affect the results and conclusions. The authors have provided the correct image files for Figure 3, panels E, F, and G in Fig 3. Fulfillment of a bioartificial proximal tubule on-a-chip embedding ARPCs. (A) Scheme of the glomerulus and the proximal tubule structure in a human kidney nephron. Here tubular ARPCs were seeded into the device, whose cross section illustrates a confluent layer of ARPCs within the lumen microchannel and adherent to the membrane. After 4 days of culture, the lumen microchannel was perfused with the complete culture medium containing urea (UR) and creatinine (CR) and the medium without UR and CR was injected in counter-current into the lower, interstitial microchannel. (B–G) Characterization of isolated tubular ARPCs. Cytofluorimetric analysis shows the expression of CD133 (B), CD24 (C), CD44 (D). Immunofluorescence detection evidences the expression of Oct-4 (E), PAX-2 (F), BMI-1 (G). Scale bars = 50 μm. (H–I) Confluent growth of ARPCs in the device attested by immunostaining of cells with DAPI (blue) (H) and TRITC-phalloidin (red) (I). Scale bars = 100 μm.S1 FileCorrected files for Fig 3. Fulfillment of a bioartificial proximal tubule on-a-chip embedding ARPCs. Immunofluorescence detection evidences the expression of Oct-4 (E), PAX-2 (F), BMI-1 (G).(ZIP)Click here for additional data file.


Chrysanthemum nankingense plants and subjecting them to a period of sub-zero temperature, with or without a prior low temperature acclimation.A major constraint affecting the quality and productivity of chrysanthemum is the unusual period of low temperature occurring during early spring, late autumn, and winter. Yet, there has been no systematic investigation on the genes underlying the response to low temperature in chrysanthemum. Herein, we used RNA-Seq platform to characterize the transcriptomic response to low temperature by comparing different transcriptome of C. nankingense unigenes established previously. The differentially transcribed genes (DTGs) were identified as low temperature sensing and signalling genes, transcription factors, functional proteins associated with the abiotic response, and low temperature-responsive genes involved in post-transcriptional regulation. The differential transcription of 15 DTGs was validated using quantitative RT-PCR.Six separate RNA-Seq libraries were generated from the RNA samples of leaves and stems from six different temperature treatments, including one cold acclimation (CA), two freezing treatments without prior CA, two freezing treatments with prior CA and the control. At least seven million clean reads were obtained from each library. Over 77% of the reads could be mapped to sets of The large number of DTGs identified in this study, confirmed the complexity of the regulatory machinery involved in the processes of low temperature acclimation and low temperature/freezing tolerance.The online version of this article (doi:10.1186/1471-2164-15-844) contains supplementary material, which is available to authorized users. Chrysanthemum morifolium) is a popular ornamental plant worldwide [C. nankingense has been considered as a convenient genomic model due to its simple diploid nature. In addition, it displays better tolerance to low temperature as compared to the ornamental polyploid species [Chrysanthemum , this approach has enabled the recognition of 1,770 differentially transcribed genes (DTGs) induced during low temperature acclimation [Jatropha curcas identified over 3,000 genes as being up- or down-regulated by low temperature [Anthurium sp., the method of digital gene expression enabled 39 low temperature-inducible transcription factors (TFs) to be identified [The RNA-Seq platform has become a key technology for quantifying the transcriptional response in nonmodel organisms or those with genome characteristics extremely difficult to whole-genome sequencing , 27. In limation . A similperature . While ientified .C. nankingense plants subjected to periods of sub-zero temperature with or without a prior low temperature acclimation, with a view to gaining a deeper insight into the molecular basis of this physiological adaptation. In addition, the identified candidate genes will be useful for improving adaptation to low temperature and enhancing productivity and geographical distribution.Here, the RNA-Seq platform based on Illumina NGS technology was used to characterize the transcriptomic response to low temperature by comparing the different transcriptome of http://trace.ncbi.nlm.nih.gov/Traces/sra_sub/sub.cgi). The number of clean reads per library ranged from 7.01 to 7.47 million, and the total number of nucleotides sequenced from 343,646,114 to 365,975,267 . The proportion of clean reads was over 99% in each library , and the proportion of unique matches from 57.64% (A) to 60.89% (C1). As the number of reads increased, the identification rate of new genes slowed, which indicated the saturation around seven million reads  , CKB1 (CK vs B1), CKB2 (CK vs B2), CKC1 (CK vs C1), CKC2 (CK vs C2), AC1(A vs C1), and AC2(A vs C2), the results showed that a large number of DTGs were identified . Of the 2,337 consistent DTGs, 1,410 were up- and 927 were down-regulated  showed consistency , calcium-binding proteins (CBP), calmodulin-like proteins (CML), CBL-interacting protein kinases (CIPK), calcium-dependent protein kinases (CDPK) and calmodulin-binding receptor-like kinases (CBRLK). The CK vs A comparison included three CCX, two CBP, five CML, three CIPK, and one CBRLK genes; the equivalent order for the CK vs C1 comparison was, respectively, three, one, five, five and one; for CK vs C2, three, zero, four, four and one; for CK vs B1, zero, one, three, zero and zero, along with one sodium/calcium exchanger family protein gene (SCE); for CK vs B2, zero, zero, five, two, zero, along with one SCE and one CDPK; for A vs C1, zero, one, two, one, zero; and for A vs C2, only one CBP was involved. In the comparisons, CK vs A, CK vs C1, and CK vs C2, three CCX , one CML (Unigene74966_S2_1), and one CDPK (Unigene5836_S2_1) were all found to be up-regulated; in addition, two CMLs (Unigene13572_S2_1 and 3462_S2_3), and one CDPK (CL8813.Contig2_S2_1) show-ed down-regulation. One CML (Unigene76667_S2_3) was found to be up-regulated in both comparisons, CK vs B1 and CK vs B2. These findings indicated that the genes related to Ca2+ signaling pathway played an essential role in the phenomenon of CA and freezing response without a prior CA; the complete details of DTGs involved in Ca2+ signalling pathway are presented in Table vs A comparison. In contrast, one MAPKKK and one MAPK gene were found to be differentially transcribed in CK vs C1, and one MAPKKK was represented in CK vs C2 as well as in CK vs B1. Four MAPKKK genes were observed in the CK vs B2 comparison, and one MAPKKK gene was identified in both, A vs C1 and A vs C2. The results showed that MAPK cascade, especially MAPKKK genes, participated in the plant’s response to freezing treatment, instead of CA. Therefore, all the DTGs involved in MAPK cascade were found to be up-regulated  and seven TF DTGs  were found in the A vs C1 and A vs C2 comparisons, respectively. The identified TF DTGs from the A vs C1 and A vs C2 comparisons, were involved in response to freezing treatment in plants with prior exposure to CA. The differently transcribed TFs of the CKA treatment, the A vs C1, and A vs C2 comparisons are presented in Table In the present study, members of various low tem-perature-responsive transcription factor (TF) families were identified; and 43, 44 and 46 such genes were found to be differentially transcribed in the comparisons, CK vs A, CK vs C1 and CK vs C2 comparisons. Yet, with respect to the above classes of proteins, only one LEA was found in both, A vs C1 and A vs C2, while two HSPs were identified in the A vs C1 comparison. The details of classes of protein of the CKA treatment are presented in Table Other relevant classes of protein, which featured as DTGs products, were dehydrin, LEA (late embryogenesis abundant) proteins, heat shock proteins (HSPs). The proteins involved in post-transcriptional regulation, such as ribosomal proteins and a DEAD-box ATP-dependent RNA helicase (RH), were particularly found in the CK To further verify the expression profiles of genes in our Illumina RNA-Seq results, we have performed a selection of 15 DTGs for their key roles in response to low temperature by qRT-PCR, these incorporated genes encoding serine/threonine-protein kinase, LEA protein, dehydrin, a gibberellin-regulated protein, a jasmonate ZIM-domain protein, and a DEAD-box ATP-dependent RH, along with a selection of TFs . The qPCR outcomes in each case correlated closely with the transcript abundances estimated from the RNA-Seq output Figure .Figure 3Anthurium[Camellia sinensis[The information available on the molecular basis of the response of Chrysanthemum to low temperature is still meagre. However, the development of next-generation sequencing technology provides a straightforward method for the identification of genes involved in this process, and we can try to elaborate the molecular mechanism underlying the response to low temperature. Over 77% of the reads in each of the six RNA-Seq libraries corresponded with known transcripts Table , a proponthurium. The lesnthurium. Around sinensis, the maj2+ is well recognized as a messenger in stress signalling [OsMSR2 gene is significantly up-regulated by a series of stresses including low temperature in different tissues at different developmental stages, and its heterologous expression in A. thaliana has suggested that the gene affects salinity and drought tolerance in an ABA-dependent manner [Camellia sinensis exposed to low temperature, five calmodulin genes, two CDPK genes and one CBL gene were identified to be involved in signal transduction [Low temperature stress-induced signals are directed to various pathways . Ca2+ isgnalling , and is gnalling , 36. A fgnalling , while agnalling , 38. Thegnalling . In ricet manner . In Camesduction . Here, fPeCPK10 show an enhanced level of freezing tolerance, perhaps through the transgene's enhancement of the transcript abundance of the abiotic stress-responsive genes RD29B and COR15A[CDPK homologue (CL4878.Contig1_S2_1) was identified as a DTG in the CKB2 treatment, but no other homologues featured as DTGs in any of the other treatments. However, in A vs C1 comparison, with respect to Ca2+ signalling pathway, only two CML genes (Unigene42277_S2_1 and 86214_S2_3) and one CIPK gene (CL2470.Contig1_S2_1) were identified as DTGs. Four MAPKKK genes  were differently transcribed in the CKB2 treatment. Unigene36211_S2_1 also featured in the CKB1 and CKC2 treatments, while a fifth MAPK gene (Unigene-36598_S2_1) was found to transcribe differently in the CKC1 treatment. No one gene of MAPK cascade was identified in the CKA treatment. In addition, many DTGs encoding serine/threonine-protein kinases were found in the CKA, CKC1 and CKC2 treatments; however, no gene was detected in the comparisons, A vs C1 and A vs C2. These findings provided evidence for the crucial role of Ca2+ in the low temperature acclimation process in C. nankingense, and further proved that the MAPK pathway and serine/threonine-protein kinases are more strongly involved in the response to freezing.CBL-interacting protein kinases (CIPKs), which specifically interact with CBLs, are thought to act as sensors since they lack any enzymatic activity . Three Dd COR15A. Only onA. thaliana[AtDREB1 sub-family harbors six members [DREB1A/CBF3, DREB1B/CBF1 and DREB1C/CBF2 are the ones which respond most rapidly to low temperature. A. thaliana plants constitutively expressing any one of these TFs display a heightened tolerance to freezing, drought and salinity [DREB2B TF present in the desert-adapted plant Eremosparton songoricum has been shown to enhance the tolerance of both yeast and tobacco against a variety of abiotic stresses. The constitutive expression in tobacco of EsDREB2B promotes the accumulation of proline in response to abiotic stress (including low temperature) [DREB2 homologue Unigene73473_S2_1 was up-regulated upon exposure to low temperature acclimation. It was speculated that the DREB2 may be involved in the accumulation of proline in response to low temperature. It is well known Proline accumulates in many plant species in response to environmental stress [AP2 TF has been shown to improve the tolerance of A. thaliana to low temperature, as well as to drought and high temperature [AP2-like genes  were also all up-regulated by CA. A number of other TFs, belonging to the WRKY, bHLH, TCP, MYB, MYC, Trihelix and b-ZIP families were also among the DTGs identified in treatments involving low temperature acclimation. The class of b-ZIP transcription factors, ABRE binding proteins (AREBs or ABFs), can bind to ABRE and activate ABA-dependent gene expression when plants are exposed to low temperature [vs A comparison. However, three WRKYs were all up-regulated in A vs C1, and no WRKY as DTG was found in A vs C2. These findings suggested that WRKY family played essential and different roles in CA and early freezing response. Most ERFs also showed down-regulated in CK vs A comparison, while, one ERF was detected up-regulated as DTG in A vs C1; on extending the freezing treatment, five ERFs as DTGs were all up-regulated in A vs C2. The ERFs performing under different temperature treatment showed its roles in CA and cold tolerance. Few reports to date have indicated that TCP transcription factors involve in the response to cold stress.Transcriptional regulation of stress-responsive genes is a vital component of the response to both abiotic and biotic stress . Five mathaliana; the AtD members , of whicsalinity . The DREerature) . Here, tl stress . The conperature . Here, tperature . Many reperature –52. FiveA. thaliana, RH25 has been associated with enhanced freezing tolerance, probably through its function as an RNA chaperone [RCF1, a low temperature-inducible RH gene, is important for low temperature-responsive gene regulation and low temperature tolerance in plants through maintenance of normal pre-mRNA splicing instead of regulating mRNA export like a previously reported DEAD-box RH (LOS4) regulates mRNA export [Post-transcriptional regulation  has been implicated in the process of low temperature acclimation . DEAD-bohaperone . The proA export . It has A export –62. HereA export .ZmLEA3 is expressed in tobacco and yeast, it improves the plant's level of tolerance against both osmotic and oxidative stress [WCI16 expressed heterologously in A. thaliana enhances freezing tolerance [vs C1 and A vs C2. The implication was that LEA proteins probably enhance low temperature tolerance through their participation in the low temperature acclimation process. Dehydrins constitute a group of plant proteins involved in tolerance to low temperature and drought [E. globulus accumulate strongly in the stem and leaf tissue of acclimated plants, compared to non-acclimated [A. thaliana, expression of Hsp90 is developmentally regulated, but it also responds to high and low temperature, as well as salinity [C. nankinginse. A gene HSP70- encoding DTGs  featured in the CKA, CKB2, CKC1 and CKC2 treatments, which not found in the CKB1 treatment; and a number of small HSPs, belonging to the 15.7, 22.7 and 23.6 families were also among the DTGs identified in treatments involving low temperature response.Besides protein factors involved in further regulation of signal transduction and gene expression such as transcription factor and protein kinase that probably function in stress response, various functional proteins featured as products of the DTGs, in particular, LEA protein and dehydrin, LEA proteins are accumulated during the late stage of seed maturation and under moisture deficient conditions, and act to protect higher plants from damage caused by abiotic stress. When the maize gene e stress . The wheolerance . Here, s drought . The thrclimated . Here, fclimated , 68. In salinity . It is sC. nankingense. This information will prove beneficial in molecular breeding programs for excellent chrysanthemum varieties.In conclusion, it was clear that a large number of genes were induced when exposed to low temperature. The complex gene networks involved a set of interactions between cold sensing and signaling genes, genes related to post-transcription regulation responding to cold stress, transcription factors and certain functional proteins. In the present study, the DTGs identified as candidate genes in response to low temperature, require further investigation for a complete understanding of the molecular basis of cold response in C. nankingense transcriptome induced by exposure to low temperature has been provided. Many of the DTGs identified were involved in predictable classes of gene, encoding, for example, low temperature sensors and signaling molecules, TFs and certain functional proteins associated with the stress response. The large number of DTGs identified confirms the complexity of the regulatory machinery involved in low temperature acclimation and low temperature/freezing tolerance. Establishing which of these many DTGs reflect the primary response to low temperature is necessary before the molecular basis of the response can be fully elaborated; such genes would represent candidates for intervention in the breeding of chrysanthemum varieties endowed with a heightened tolerance to low temperature stress.An overview of the many changes to the C.nankingense utilized is conserved by the Chrysanthemum Germplasm Resource Preserving Centre, Nanjing Agricultural University, China. Plants raised from tissue-cultured plantlet were grown on MS medium . Four week old plants were subjected to one of the following temperature treatments: (A) 4°C for one week, (B1) -5°C for 1 h, (B2) -5°C for 2 h, (C1) 4°C for one week, followed by -5°C for 1 h, (C2) 4°C for one week, followed by -5°C for 2 h. CK plants were harvested without any additional treatment. For each treatment, the leaves and stems of three seedlings were sampled, and two samples were harvested. 30 μg of total RNA were pooled in equal amounts from the two biological replicates for subsequent RNA- Seq.The accession of Six separate libraries were prepared. The samples from the six treatments  were snap-frozen in liquid nitrogen and ground to a fine powder. Total RNA was extracted using a Total RNA Isolation System  according to the manufacturer’s instructions. When the quality of the resulting RNA was verified using a 2100 Bioanalyzer RNA Nano chip device , all six extractions delivered an RNA integrity number value of > 8.0, and a 28S:18S ratio >1.5. After checking for the absence of contamination by protein (A260/A280 nm ratios) and reagent contamination (A260/A230 nm ratios) by a Nanodrop ND-430 1000 spectrophotometer, the extractions were selected based on 28S/18S rRNA band intensity (1.5:1 ~ 2:1) and spectroscopic A260/A280 nm readings between 1.8 and 2.2, A260/A230 nm readings greater than 2.0. 10 μg RNA was pooled from each of the three sampled plants. The total RNA preparation was treated with RNase-free DNase I  to degrade any possible DNA, and mixed with oligo (dT) coated magnetic beads to concentrate the polyA mRNA.The mRNA was fragmented into short fragments ~200 nt pieces by incubation in a fragmentation buffer under elevated temperature (The Beijing Genomics Institute). The first strand of cDNA was then synthesized by priming with random hexamer, and the second strand was generated with buffer, dNTPs, RNase H and DNA polymerase I. The double strand cDNA was purified with a QiaQuick PCR extraction kit and resolved with EB buffer for end repair and addition of single nucleotide A. Finally, sequencing adaptors were ligated to the fragments. Following agarose gel electrophore, suitable fragments were selected as templates for PCR.™2000 located at the Beijing Genomics Institute . The data were deposited in the US National Center for Biotechnology Information (NCBI) Sequence Read Archive  and the Swiss-Prot protein database (http://www.expasy.ch/sprot) were used for blast search and annotation using an E-value cut off of 10-5. Functional annotation by gene ontology terms  was analyzed using the Blast2GO program [http://www.genome.jp/kegg), the major public pathway-related database [The library was sequenced using an Illumina HiSeqces/sra;  under acces/sra; . A maxim program . The Kyodatabase  was alsodatabase  was usedTo compare the differences in gene expression, the method of an algorithm developed by Audic et al.  was usedC. nankingense EF1α gene as the reference, and was based on the 2-ΔΔCT method [Total RNA was isolated from leave and stem of plants subjected to the various treatments described above. Contaminating DNA was removed by treating with RNase-free DNase I and the first cDNA strand was synthesized from 1 μg total RNA using PrimeScript® Reverse Transcriptase  and an oligo (dT) primer, according to the manufacturer’s instructions. qPCRs were performed in an Eppendorf Real Time PCR System  using a SYBR Premix Ex Taq™ Kit (Takara), according to the manufacturer’s protocol. Gene-specific primers were designed using Primer5 software  bases represented >50% of the reads. The numbers in parentheses indicate the percentage of each type of read present. (TIFF 616 KB)Additional file 2: Figure S2: Sequencing saturation analysis in the six libraries . The numbers of new genes detected rose as the read number was increased, but not beyond a threshold around 7,000,000. (TIFF 797 KB)Additional file 3: Figure S3: Distribution of gene coverage in the six libraries. (TIFF 783 KB)Additional file 4: Table S1: The transcription level of each unigene derived from the number of relevant reads recovered in the four libraries. The “GeneLength” column gives the length of exon sequence. (XLSX 7 MB)Ratio(A/CK)| ≥1. Genes listed in descending order of absolute |log2Ratio(A/CK)|. GeneIDs retrieved from the Chrysanthemum nankingense Reference Sequence Database. Annotation of unigene sequences performed using BlastX (E < 10). The “GeneLength” column gives the length of exon sequence. CK- and A- expression: frequency of unigene transcripts in libraries CK and A, respectively. CK- and A-RPKM: reads per kb per million reads for each unigene in libraries CK and A, respectively. Log2Ratio(A/CK): the ratio between the RPKM in CK and the RPKM in A. Up-Down-Regulation (A/CK), P-value and FDR of each gene are also shown. KEGG: annotation according to the KEGG database by BLAST. Blast nr: identification of homologues in GenBank. GO Component, GO Function and Go Process: ontology information of Cellular Components, Molecular Function and Biological Processes of Gene-corresponding GO terms. “-”: no hit. (XLSX 741 KB)Additional file 5: Table S2: Genes differentially transcribed in the comparison between libraries CK and A. The criteria applied for assigning significance were: P-value < 0.05, FDR ≤ 0.001, and estimated absolute |log2Ratio(B1/CK)| ≥1. Genes listed in descending order of absolute |log2Ratio(B1/CK)|. GeneIDs retrieved from Chrysanthemum nankingense Reference Sequence Database. Annotation of unigene sequences performed using BlastX (E <10). The “GeneLength” column gives the length of exon sequence. CK- and B1-expression: frequency of unigene transcripts in libraries CK and B1, respectively. CK- and B1-RPKM: reads per kb per million reads for each unigene in libraries CK and B1, respectively. Log2Ratio(B1/CK): the ratio between the RPKM in CK and the RPKM in B1. Up-Down-Regulation (B1/CK), P-value and FDR of each gene are also shown. KEGG: annotation according to the KEGG database by BLAST. Blast nr: identification of homologues in GenBank. GO Component, GO Function and Go Process: ontology information of Cellular Components, Molecular Function and Biological Processes of Gene-corresponding GO terms. “-”: no hit. (XLSX 85 KB)Additional file 6: Table S3: Genes differentially transcribed in the comparison between libraries CK and B1. The criteria applied for assigning significance were: P-value < 0.05, FDR ≤ 0.001, and estimated absolute |log2Ratio(B2/CK)| ≥1. Genes listed in descending order of absolute |log2Ratio(B2/CK)|. GeneIDs retrieved from the Chrysanthemum nankingense Reference Sequence Database. Annotation of unigene sequences performed using BlastX (E <10). The “GeneLength” column gives the length of exon sequence. CK- and B2-expression: frequency of unigene transcripts in libraries CK and B2, respectively. CK- and B2-RPKM: reads per kb per million reads for each unigene in libraries CK and B2, respectively. Log2Ratio(B2/CK): the ratio between the RPKM in CK and the RPKM in B2. Up-Down-Regulation (B2/CK), P-value and FDR of each gene are also shown. KEGG: annotation according to the KEGG database by BLAST. Blast nr: identification of homologues in GenBank. GO Component, GO Function and Go Process: ontology information of Cellular Components, Molecular Function and Biological Processes of Gene-corresponding GO terms. “-”: no hit. (XLSX 157 KB)Additional file 7: Table S4: Genes differentially transcribed in the comparison between libraries CK and B2. The criteria applied for assigning significance were: P-value < 0.05, FDR ≤ 0.001, and estimated absolute |log2Ratio(C1/CK)| ≥1. Genes listed in descending order of absolute |log2Ratio(C1/CK)|. GeneIDs retrieved from the Chrysanthemum nankingense Reference Sequence Database. Annotation of unigene sequences performed using BlastX (E <10). The “GeneLength” column gives the length of exon sequence. CK- and C1-expression: frequency of unigene transcripts in libraries CK and C1, respectively. CK- and C1-RPKM: reads per kb per million reads for each unigene in libraries CK and C1, respectively. Log2Ratio(C1/CK): the ratio between the RPKM in CK and the RPKM in C1. Up-Down-Regulation (C1/CK), P-value and FDR of each gene are also shown. KEGG: annotation according to the KEGG database by BLAST. Blast nr: identification of homologues in GenBank. GO Component, GO Function and Go Process: ontology information of Cellular Components, Molecular Function and Biological Processes of Gene-corresponding GO terms. “-”: no hit. (XLSX 787 KB)Additional file 8: Table S5: Genes differentially transcribed in the comparison between libraries CK and C1. The criteria applied for assigning significance were: P-value < 0.05, FDR ≤ 0.001, and estimated absolute |log2Ratio(C2/CK)| ≥1. Genes listed in descending order of absolute |log2Ratio(C2/CK)|. GeneIDs retrieved from the Chrysanthemum nankingense Reference Sequence Database. Annotation of unigene sequences performed using BlastX (E <10). The “GeneLength” column gives the length of exon sequence. CK- and C2-expression: frequency of unigene transcripts in libraries CK and C2, respectively. CK- and C2-RPKM: reads per kb per million reads for each unigene in libraries CK and C2, respectively. Log2Ratio(C2/CK): the ratio between the RPKM in CK and the RPKM in C2. Up-Down-Regulation (C2/CK), P-value and FDR of each gene are also shown. KEGG: annotation according to the KEGG database by BLAST. Blast nr: identification of homologues in GenBank. GO Component, GO Function and Go Process: ontology information of Cellular Components, Molecular Function and Biological Processes of Gene-corresponding GO terms. “-”: no hit. (XLSX 867 KB)Additional file 9: Table S6: Genes differentially transcribed in the comparison between libraries CK and C2. The criteria applied for assigning significance were: P-value < 0.05, FDR ≤ 0.001, and estimated absolute |log2Ratio(C1/A)| ≥1. Genes listed in descending order of absolute |log2Ratio(C1/A)|. GeneIDs retrieved from the Chrysanthemum nankingense Reference Sequence Database. Annotation of unigene sequences performed using BlastX (E <10). The “GeneLength” column gives the length of exon sequence. A- and C1-expression: frequency of unigene transcripts in libraries A and C1, respectively. A- and C1-RPKM: reads per kb per million reads for each unigene in libraries A and C1, respectively. Log2Ratio(C1/A): the ratio between the RPKM in A and the RPKM in C1. Up-Down-Regulation (C1/A), P-value and FDR of each gene are also shown. KEGG: annotation according to the KEGG database by BLAST. Blast nr: identification of homologues in GenBank. GO Component, GO Function and Go Process: ontology information of Cellular Components, Molecular Function and Biological Processes of Gene-corresponding GO terms. “-”: no hit. (XLSX 53 KB)Additional file 10: Table S7: Genes differentially transcribed in the comparison between libraries A and C1. The criteria applied for assigning significance were: P-value < 0.05, FDR ≤ 0.001, and estimated absolute |log2Ratio(C2/A)| ≥1. Genes listed in descending order of absolute |log2Ratio(C2/A)|. GeneIDs retrieved from the Chrysanthemum nankingense Reference Sequence Database. Annotation of unigene sequences performed using BlastX (E <10). The “GeneLength” column gives the length of exon sequence. A- and C2-expression: frequency of unigene transcripts in libraries A and C2, respectively. A- and C2-RPKM: reads per kb per million reads for each unigene in libraries A and C2, respectively. Log2Ratio(C2/A): the ratio between the RPKM in A and the RPKM in C2. Up-Down-Regulation (C2/A), P-value and FDR of each gene are also shown. KEGG: annotation according to the KEGG database by BLAST. Blast nr: identification of homologues in GenBank. GO Component, GO Function and Go Process: ontology information of Cellular Components, Molecular Function and Biological Processes of Gene-corresponding GO terms. “-”: no hit. (XLSX 34 KB)Additional file 11: Table S8: Genes differentially transcribed in the comparison between libraries A and C2. The criteria applied for assigning significance were: P-value < 0.05, FDR ≤ 0.001, and estimated absolute |log2Ratio(A/CK): the ratio between the RPKM in CK and the RPKM in A. Log2Ratio(C1/CK): the ratio between the RPKM in CK and the RPKM in C1. Log2Ratio(C2/CK): the ratio between the RPKM in CK and the RPKM in C2. KEGG: annotation according to the KEGG database by BLAST. Blast nr: identification of homologues in GenBank. GO Component, GO Function and Go Process: ontology information of Cellular Components, Molecular Function and Biological Processes of Gene-corresponding GO terms. “-”: no hit. (XLSX 336 KB)Additional file 12: Table S9: Expression pattern analysis of DTGs following multiple comparisons: CK vs A, CK vs C1, CK vs C2. GeneIDs retrieved from the Chrysanthemum nankingense Reference Sequence Database. Log2vs B1, CK vs B2. GeneIDs retrieved from the Chrysanthemum nankingense Reference Sequence Database. Log2Ratio(B1/CK): the ratio between the RPKM in CK and the RPKM in B1. Log2Ratio(B2/CK): the ratio between the RPKM in CK and the RPKM in B2. KEGG: annotation according to the KEGG database by BLAST. Blast nr: identification of homologues in GenBank. GO Component, GO Function and Go Process: ontology information of Cellular Components, Molecular Function and Biological Processes of Gene-corresponding GO terms. “-”: no hit. (XLSX 38 KB)Additional file 13: Table S10: Expression pattern analysis of DTGs following multiple comparisons: CK Ratio(C1/A): the ratio between the RPKM in A and the RPKM in C1. Log2Ratio(C2/A): the ratio between the RPKM in A and the RPKM in C2. KEGG: annotation according to the KEGG database by BLAST. Blast nr: identification of homologues in GenBank. GO Component, GO Function and Go Process: ontology information of Cellular Components, Molecular Function and Biological Processes of Gene-corresponding GO terms. “-”: no hit. (XLSX 17 KB)Additional file 14: Table S11: Expression pattern analysis of DTGs following multiple comparisons: A vs C1, A vs C2. GeneIDs retrieved from the Chrysanthemum nankingense Reference Sequence Database. Log2Additional file 15: Table S12: GO classification of DTGs in each comparison. (XLSX 194 KB)Additional file 16: Table S13: Pathway classification of DTGs in each comparison. (XLSX 72 KB)


Bacillus subtilis class-C1 penicillin-binding protein (PBP), four clustered lysine (K) residues, K86, K114, K119, and K265, protrude from domain II. Replacement of these amino acids with glutamine (Q) residues by site-directed mutagenesis yielded Mut4KQ PBP4a. When produced in Escherichia coli without its predicted Sec-signal peptide, wild-type (WT) PBP4a was found mainly associated with the host cytoplasmic membrane, whereas Mut4KQ PBP4a remained largely unbound. After purification, the capacities of the two proteins to bind to B. subtilis membranes were compared. The results were similar to those obtained in E. coli: in vitro, a much higher percentage of WT PBP4a than of Mut4KQ PBP4a was found to interact with B. subtilis membranes. Immunodetection of PBP4a in B. subtilis membrane extracts revealed that a processed form of this PBP (as indicated by its size) associates with the B. subtilis cytoplasmic membrane. In the absence of any amphiphilic peptide in PBP4a, the crown of positive charges on the surface of domain II is likely responsible for the cellular localization of this PBP and its attachment to the cytoplasmic membrane.In PBP4a, a  E. coli PBP4) are characterized by a tertiary structure composed of three domains: a penicillin-binding (PB) domain (domain I) with a fold similar to that of the class-A β-lactamases and two domains of unknown function inserted between the conserved SxxK and SxN motifs of domain I ..E. coli,B. subtilis PBP4a was aligned with the sequences of Actinomadura R39 DD-peptidase, E. coli PBP4, and Haemophilus influenzae PBP4, the tertiary structures of which have been determined. Clostridium sp., Neisseria gonorrhoeae (PBP3), Pseudomonas aeruginosa (PBP4), and Haladaptatus paucihalophilus, an archaeabacterium. The lysine residues protruding from domain II in B. subtilis PBP4a are generally not conserved among these PBPs, and the level of amino acid conservation in domain II is low. Inspection of the available tertiary structures shows that a positively charged surface at the tip of domain II also exists in the Actinomadura R39 DD-peptidase, but not in the C1-PBPs of E. coli or H. influenzae.The primary structure of E. coli, B. subtilis PBP4a lacking the predicted Sec-signal peptide and motif that could function as a membrane anchor was expected to be found, mainly, in the cytoplasm. This was not the case, unless several lysine residues were replaced with neutral amino acids. In the DD-peptidase of the Gram-positive bacterium Actinomadura R39, a C1-PBP, some lysine residues are replaced with arginines (R). This may reflect codon usage in this GC-rich organism. Here again, a cluster of positive charges  protrudes from domain II [Streptomyces K15 DD-transpeptidase [When produced in omain II . This feeptidase  lacking eptidase .E. coli PBP4, however, the 18 C-terminal residues associate only weakly with the outer face of the cytoplasmic membrane [Neisseria gonorrhoeae PBP3 has been clearly described as associated with the outer membrane [In some low-molecular-mass PBPs, a C-terminal peptide with amphiphilic properties is involved in binding to the cytoplasmic membrane ,16. In Emembrane . A membrDictyostelium discoideum which phagocytes bacteria, a functional C1-PBP (encoded by pscA) is present [The presence of a C1-PBP in archaea is a surprising finding, given the general lack of D-amino acids as substrates in these organisms. The cell walls of archaea contain no peptidoglycan, and only some methanogenic species are known to produce a pseudomurein lacking D-amino acids and N-acetylmuramic acid. C1-PBPs are also found in halobacteria, which do not synthesize pseudomurein. It is tempting to speculate that the C1-PBP-encoding genes of these organisms have been acquired from eubacteria and that their DD-endopeptidase activity serves as a weapon against competitors or as a tool involved in recycling eubacterial cell walls. Similarly, in the eukaryotic organism  present .Escherichia coli PBP5), class-C1 PBPs generally lack an identifiable membrane anchor. This study reveals an alternative mechanism for Bacillus subtilis PBP4a binding to the cytoplasmic membrane. We suggest that the interaction between the crown of positively charged amino-acids on the surface of domain II and negatively charged components on the membrane could be valid for many Gram-positive bacteria C1-PBPs. Elucidation of new crystal structures could confirm this hypothesis.Unlike other low-molecular-weight Penicillin-Binding Proteins . Lane 5: purified PBP4a (250 ng). Lane 6–8: total protein content of induced LMG194-pBAD/mutPBP4a, clones 2–4, respectively.(TIF)Click here for additional data file.S2 FigThe production of recombinant proteins was induced with 0.05% L-arabinose and analysed after 4 h at 37°C. Lane 1: LMG194 total protein content before induction. Lane 2: total protein content in induced LMG194-pBAD/wtPBP4a. Lane 3: total protein content in induced LMG194-pBAD/mutPBP4a. Lane 4: purified PBP4a (250 ng). Lane 5: cytoplasmic protein content of induced LMG194-pBAD/wtPBP4a. Lane 6: cytoplasmic protein content of induced LMG194-pBAD/mutPBP4a. Lane 7: 1 M NaCl extract of membranes from induced LMG194- pBAD/wtPBP4a. Lane 8: 1 M NaCl extract of membranes from induced LMG194-pBAD/mut PBP4a. Lane 9: Prestained PageRuler Protein Ladder (Thermo Scientific #26616).(TIF)Click here for additional data file.S3 FigE. coli LMG194- pBAD/wtPBP4a. Lane 9: 1 M NaCl extract from membranes of induced E. coli LMG194- pBAD/mut PBP4a.The production of recombinant proteins was induced with 0.05% L-arabinose and analyzed after 4 h at 37°C. Lane 1: LMG194 total protein content before induction. Lane 2: total protein content of induced LMG194-pBAD/wtPBP4a. Lane 3: total protein content of induced LMG194-pBAD/mutPBP4a. Lane 4: Prestained PageRuler Protein Ladder (Thermo Scientific #26616). Lane 5: purified PBP4a (50 ng). Lane 6: cytoplasmic proteins of induced LMG194-pBAD/wtPBP4a. Lane 7: cytoplasmic protein content of induced LMG194-pBAD/mutPBP4a. Lane 8: 1 M NaCl extract from membranes of induced (TIF)Click here for additional data file.S4 FigLane numbering and legend are identical to those of (TIF)Click here for additional data file.S5 FigLanes 1–3: recombinant PBP4a . Lane 4: Prestained PageRuler Protein Ladder (Thermo Scientific #26616). Lanes 5–7: 4, 8, and 12 μL membrane extract, respectively.(TIF)Click here for additional data file.S1 TextEstimation by densitometry of quantities of WT or Mut4KQ PBP4a in cytoplasmic fractions and membrane extracts.(DOCX)Click here for additional data file.


We are investigating a novel vaccination series using E39 and E39' (EIWTFSTKV), an attenuated version of E39, in a Phase Ib, randomized, single-center trial (NCT020196524) evaluating IR and monitoring long-term immunity. We present the initial IR analysis to the primary vaccination series (PVS).Folate Binding Protein (FBP) is overexpressed in breast, endometrial, and ovarian cancers. E39  is an HLA-A2 restricted FBP peptide vaccine already shown to generate significant in vivo IR, local reaction(LR) was measured 48hours after each inoculation (R1-6), and delayed type hypersensitivity (DTH) was measured pre-vaccine(R0), 1 and 6-months after the PVS . Ex vivo IR was measured via dextramer assay for E39-specific CD8+ T-cells at R0, RC1, and RC6. Statistical analyses included descriptive statistics, t-test, Chi-squared, Fisher's exact test and ANOVA as appropriate.HLA-A2+ breast or ovarian cancer patients were enrolled after completion of standard of care therapy and randomized into three arms: EE-6 inoculations of E39; EE'-3 inoculations of E39 then 3 of E39'; or E'E-3 inoculations of E39' then 3 of E39. PVS includes 6 inoculations total, one every 3-4 weeks containing 250mcg GM-CSF + 500mcg peptide in the first 5 patients per arm and 1000mcg of peptide in second 5 patients. To assess the In vivo LR showed a significant difference within EE and EE' arms. LR peaked in EE at R4, while EE' continued to increase in size throughout the PVS. An increase in in vivo DTH was observed within arm EE' from R0-RC1-RC6 . Ex vivo analysis of IR revealed no significant difference between groups (p=0.39), nor within groups .Thirty-two patients were enrolled , with no clinicopathologic differences between groups, or significant toxicities appreciated. in vivo response is enhanced with the use of the attenuated E39' after E39. This was observed in the EE' arm, this vaccination sequence producing the most prominent LR and DTH responses. Continued analysis of immunologic responses as more data is obtained will further elucidate the optimal vaccination series for the prevention of recurrence in breast and ovarian cancer.In this Phase Ib trial comparing three vaccination strategies in ovarian and breast cancer patients, preliminary analysis revealed E39, given sequentially with or without E39', is immunogenic. The ClinicalTrials.gov identifier NCT020196524.


Some show PA-Nter activity exclusively with Mn2+, whereas others report Mg2+ as a natural cofactor. To clarify it, we performed a series of experiments with varied ion concentrations and substrate type. We observed cleavage in the presence of both ions, with a slight preference for manganese, however PA-Nter activity highly depended on the amount of residual, co-purified ions. Furthermore, to quantify cleavage reaction rate, we applied fluorescence cross-correlation spectroscopy (FCCS), providing highly sensitive and real-time monitoring of single molecules. Using nanomolar ssDNA in the regime of enzyme excess, we estimated the maximum reaction rate at 0.81± 0.38 and 1.38± 0.34 nM/min for Mg2+ and Mn2+, respectively. However, our calculations of PA-Nter ion occupancy, based on thermodynamic data, suggest Mg2+ to be a canonical metal in PA-Nter processing of RNA in vivo. Presented studies constitute a step toward better understanding of PA-Nter ion-dependent activity, which will possibly contribute to new successful inhibitor design in the future.PA subunit of influenza RNA-dependent RNA polymerase deserves constantly increasing attention due to its essential role in influenza life cycle. N-terminal domain of PA (PA-Nter) harbors endonuclease activity, which is indispensable in viral transcription and replication. Interestingly, existing literature reports on  Influenza has caused outbreaks every 1–3 years repeatedly throughout past 400 years –4. Accor2+  on the total protein concentration Ptot and total ion concentration Itot bound to protein with an equilibrium constant Kd. It is obtained as a root of a quadratic equation describing the equilibrium of free ion If and protein Pf and P•I complex formed (Pf +If ⇔ P•I).For the discussion regarding metal ion occupancy of PA-Nter in living cells, we used a dependence of protein-ion complex << KM), allow for a determination of kcat/KM value. This is because:The reported here I class)  or ~0.6•RNase H1 . These e0-nt RNA  and 0.230-nt RNA , indicatkcat/KM at the level of ~2•103 M-1s-1, similar for both metall ions. Indeed this value is smaller than the mentioned above values for other nucleic acid-cleaving enzymes. Probably the relatively low processivity of PA-Nter is increased when the enzyme works together with PB2 unit binding effectively the 5’ mRNA cap of the cleaved mRNA chain.From the linear regime of PA-Nter kinetics measured here, we can estimate 2+ reported by some authors, basing on the thermodynamic data on ion binding by PA-Nter /Ptot  for a range of PA-Nter concentrations Click here for additional data file.S2 Fig(TIF)Click here for additional data file.S3 Fig(TIF)Click here for additional data file.S4 Fig(TIF)Click here for additional data file.S5 Fig(TIF)Click here for additional data file.S6 Fig(TIF)Click here for additional data file.S7 Fig(TIF)Click here for additional data file.S1 Table(DOC)Click here for additional data file.


Kip1, phospho-Rb and E2F1) through immunohistochemistry and cell death through TUNEL in autopsy hippocampal tissue samples arrayed in a tissue microarray (TMA) composed of three groups: I) “clinical-pathological AD” (CP-AD) - subjects with neuropathological AD (Braak≥IV and CERAD = B or C) and clinical dementia ; II) “pathological AD” (P-AD) - subjects with neuropathological AD (Braak≥IV and CERAD = B or C) and without cognitive impairment ; and III) “normal aging” (N) - subjects without neuropathological AD (Braak≤II and CERAD 0 or A) and with normal cognitive function . Our results show that high levels of oxidative DNA damage are present in all groups. However, significant reductions in DNA repair and cell-cycle inhibition markers and increases in cell-cycle progression and cell death markers in subjects with CP-AD were detected when compared to both P-AD and N groups, whereas there were no significant differences in the studied markers between P-AD individuals and N subjects. This study indicates that, even in the setting of pathological AD, healthy cognition may be associated with a preserved repair to DNA damage, cell-cycle regulation, and cell death in post-mitotic neurons.Alzheimer’s disease (AD) is characterized by progressive cognitive decline associated with a featured neuropathology (neuritic plaques and neurofibrillary tangles). Several studies have implicated oxidative damage to DNA, DNA repair, and altered cell-cycle regulation in addition to cell death in AD post-mitotic neurons. However, there is a lack of studies that systematically assess those biological processes in patients with AD neuropathology but with no evidence of cognitive impairment. We evaluated markers of oxidative DNA damage , DNA repair , and cell-cycle (Cdk1, Cdk4, Cdk5, Cyclin B1, Cyclin D1, p27 Alzheimer’s disease (AD) is the most frequent cause of dementia in the elderly, accounting for approximately 70% of dementia cases Although there is evidence showing that the majority of persons identified as having clinical AD meet the neuropathological criteria for AD Although the neurobiological basis of such discordance between pathology and clinical outcome is not yet understood, there may be compensatory mechanisms that protect such individuals against the clinical emergence of AD because they carry a high burden of histopathological lesions but can support them without cognitive decline, remaining resilient DNA injury due to oxidative stress has been confirmed in various studies to have a role in the pathogenesis of AD It is important to note that although oxidative damage to DNA (ODD), DNA repair (DR), cell-cycle (CC) and cell death (CD) have been widely explored in individuals with AD , there has been little postmortem investigation of neurobiological processes in individuals with normal cognition despite AD pathology (P-AD). Therefore, our aim in this study was to verify whether there are differences among CP-AD, P-AD, and normal individuals  related to ODD, DR, CC, and CD. We observed reduced levels of DNA repair and cell-cycle inhibition markers, as well as elevated levels of cell-cycle progression markers in association with increased levels of cell death in post-mitotic neurons of clinical and pathological AD individuals; in contrast, individuals with AD neuropathology but no evidence of cognitive impairment (P-AD) present a similar expression profile to individuals with normal aging.Hippocampal tissue samples were obtained post-mortem from the Brain Bank of the Brazilian Aging Brain Study Group Human autopsy brain tissue was fixed in 4% paraformaldehyde and used for neuropathological evaluation. Neuropathological examinations were performed using immunohistochemistry, according to internationally accepted criteria clinical-pathological AD” (CP-AD); II) 12 subjects with neuropathological AD (Braak≥IV and CERAD = B or C) and without cognitive impairment , termed “pathological AD” (P-AD); and III) 31 subjects without neuropathological AD (Braak≤II and CERAD 0 or A) and with normal cognitive function , termed “normal aging individuals” (N). The neuropathological and clinical data and post-mortem interval of each case can be visualized in Based on pathological and clinical criteria, subjects were categorized into three groups: I) 19 subjects with neuropathological AD (Braak≥IV and CERAD = B or C) and clinical dementia , termed “This study was approved by the Ethical Board for Research Project Analysis (CAPPesq) of the University of São Paulo Medical School (research protocol 285/04) and by the Ethical Committee for Research (CEP) of the A. C. Camargo Cancer Center (research protocol 1232/09) and was conducted in accordance with the Helsinki Declaration.Using the tissue microarray (TMA) technology, hippocampal samples (CA1 region) from 62 subjects  were arrayed in one recipient paraffin block using a manual arraying instrument . This instrument was utilized for creating holes in the recipient array block and for acquiring tissue cores from the donor block. The donor block was manually positioned for sampling based on a visual alignment with the corresponding HE-stained section on a slide by a pathologist. The needle was used to retrieve a cylindrical sample from a selected region in the donor block and to extrude the sample core directly into the recipient block with defined array coordinates. After the block construction was completed, 4-µm sections of the resulting tissue microarray block were cut with a microtome. An adhesive tape system  was used for sectioning the array block. The microtome knife cuts underneath a piece of tape that is placed over the block surface. The thin tissue section adheres to the tape, which is then rolled on an adhesive-coated microscope slide to transfer the section to the slide.2O2) three times for 10 min. The sections were blocked with serum-free protein block  at room temperature for 20 min to prevent non-specific binding and then incubated with the primary antibodies  and boiled in a pressure-cooker for 4 min. Endogenous peroxidase activity was removed with 3% hydrogen peroxide (Htibodies  at room In Situ Apoptosis Detection Kit (TREVIGEN®) according to the manufacturer’s instructions. This technique, based on TUNEL, detects DNA fragmentation resulting from apoptotic signaling cascades. This assay is based on the presence of DNA fragments, which can be identified with terminal deoxynucleotidyltransferase, an enzyme that catalyzes the addition of labeled dUTPs with a secondary antibody conjugated to horseradish peroxidase, generating a brown coloration when reacted with DAB.Detection of cell death was performed using the TACS 2 TdT®-DAB Events’ tool of ZEN lite software (ZEISS). Identification of neurons was based on their typical morphological parameters After performing immunohistochemical reactions, slides were digitalized on a ScanScope XT device (Aperio Technologies), and then the full-slide image was segmented by Spectrum™ software (Aperio Technologies) to generate an image of each core (sample). Subsequently, these images were used to manually count neurons using the ‘0 – no stainingp≤Percentile 33% 1 – 0, 33<p≤P0, 662 – Pp>P0 663 – I)Intensity of staining  of each marker for each sample was defined by the following equation:p = positivity;i = number of intensity categories;nI = intensity of staining.Thus, we exclude the possibility of assigning the same expression values for samples with low positivity but high intensity as for samples with high positivity and low intensity.P-value of ≤0.05 was used as the criterion for statistical significance. Hierarchical clustering analysis was based on Pearson’ correlations and average linkage from expression values of assessed markers. Reliability of the clustering was assessed by the Bootstrap technique using MEV software Group differences in demographic variables were analyzed using analysis of variance (ANOVA) and χ-square tests as appropriate. Differences among medians of studied markers were assessed by Kruskal-Wallis tests, which were followed by Dunn’s test, using GraphPad Prism software version 6.0. A In this study, markers were examined in the hippocampus, which is affected early in AD and which has been extensively studied. Our sample groups did not statistically differ in average age or in gender distribution, although the female frequency was higher in the CP-AD and P-AD groups. Significant differences in postmortem intervals (PMI) were also not detected among the groups .Oxidative damage to DNA can be caused by reactive oxygen species (ROS), which are produced by radiation or by products of aerobic metabolism. The oxidized base, 8-Hydroxyguanine (8-OHdG), the most commonly analyzed biomarker of DNA damage, showed high levels of nuclear staining in all groups. However, a statistically significant difference was only found between CP-AD and N, with greater expression in demented subjects . A similAnother biomarker for DNA damage is H2AX, a histone that is phosphorylated in response to double-strand breaks of DNA, giving rise to λ-H2AX. In our samples, nuclear λ-H2AX expression was higher in CP-AD individuals than in normal aging group (N), whereas no significant difference in cytoplasmic expression was detected among the groups .High levels of oxidative damage can be caused by relatively inefficient DNA repair. Thus, we assayed some proteins involved in the DNA-damage repair system, whose roles are essential for detecting damage and triggering a repair response.p53 is a protein activated in response to a wide variety of stresses that can damage the cell genome; once it is bound to sites of DNA damage, p53 promotes DNA repair and simultaneously stimulates the transcription of direct effectors of cell-cycle arrest. Our results show that nuclear p53 expression was significantly greater in the P-AD and N groups than in the CP-AD group ; howeverBRCA1 is known to regulate transcription and cell-cycle progression; thus, the presence of BRCA1 is indicative of cell-cycle changes and DNA damage, both of which are pathogenic changes in AD. Significantly higher levels of nuclear BRCA1 were detected in P-AD individuals compared with CP-AD subjects, but differences were not significant either between P-AD and N or between CP-AD and N . For cytIn the cytoplasm, PTEN antagonizes the phosphatidylinositol 3-kinase (PI3K/AKT) signaling pathway. PTEN also accumulates in the nucleus, where it has been shown to control DNA repair. In the nucleus, PTEN showed higher levels of expression in P-AD and N groups than in the CP-AD group . Unlike To systematically evaluate the cell-cycle events in our groups, cell-cycle markers of early stages  and later stages  were used in addition to the inhibitor of cyclin-dependent kinases (p27).Regarding nuclear staining, pyramidal neurons from the hippocampus of CP-AD individuals demonstrated higher expression levels of Cdk4, cyclin D, phospho-Rb, E2F1, Cdk1, and cyclin B than did those from either P-AD or N subjects –S14. ForFor the cytoplasmic staining –S14, sigin situ. Apoptotic neurons were found at higher rates in hippocampus from individuals with CP-AD than in samples from P-AD and N subjects, as can be seen in To evaluate the neuronal cell death, terminal deoxynucleotidyltransferase-mediated biotinylated UTP nick end labeling (TUNEL) was performed An overview of the studied biomarkers is presented in Markers of oxidative damage to DNA (8-OHdG and H2AX) were elevated in the CP-AD group compared to the N group, regarding both nuclear and cytoplasmic expression.Markers of DNA repair (p53 and PTEN) were decreased in the CP-AD group compared to both the P-AD and N groups, regarding nuclear expression. BRCA1 was significantly decreased only in CP-AD compared to P-AD, although there is a trend of normal individuals showing similarity to preclinical subjects.Markers of cell-cycle progression  were elevated in the CP-AD group compared to both the P-AD and N groups, regarding nuclear expression; some markers, such as Cdk4, phospho-Rb, and Cdk1, were found elevated in the CP-AD group compared to the N group for cytoplasmic expression.Markers of cell-cycle inhibition  were decreased in the CP-AD group compared to both the P-AD and N groups, regarding nuclear expression.Neuronal cell death was elevated in the CP-AD group compared to both the P-AD and N groups.Searching for an expression pattern based on markers that achieved statistical significance between the CP-AD group and the other two groups (P-AD and N), a hierarchical clustering was conducted with all individuals in this study. The dendrogram in This clustering displays an expression pattern composed of high levels of cell-cycle progression markers  and apoptosis markers, along with low levels of cell-cycle inhibitors and DNA repair markers  in CP-AD individuals; P-AD and N individuals show the opposite pattern, with low levels of cell-cycle progression markers and apoptosis markers and high levels of cell-cycle inhibitors and DNA repair markers.Individuals who have evidence of abundant AD pathology but do not meet clinical criteria for mild cognitive impairment (MCI) or dementia, thus preserving their cognitive functioning, have been described by a range of allied concepts such as “pathological aging”, “preclinical AD”, “asymptomatic AD”, and “resilient AD” The etiology and pathogenesis of AD is not fully understood, but several factors have been implicated in the progression of AD Elevated levels of oxidative stress markers and mitochondrial dysfunction have been found in AD. Recent studies have reported alterations in DNA repair proteins (cell-cycle checkpoint proteins and tumor suppressors) of pathways involved in the repair of oxidative stress-induced lesions in patients with AD p53 is a tumor-suppressor protein that is activated in response to a variety of stressors that can damage the integrity of the cellular genome In the cytoplasm, PTEN acts as a specific phosphatase for 3′-phosphatidylinositol and is the major negative regulator of the activity of the phosphatidylinositol-3-kinase (PI3K) signaling pathway There is also growing evidence for the association between DNA damage and increased expression of cell-cycle markers in AD To emphasize a potential role of cell-cycle regulation and DNA repair in the symptomatic progression of AD, Yang et al. Cell-cycle studies have shown that ectopic expression of cell-cycle markers is associated with neuronal cell death In general, we observed reduced levels of DNA repair and cell-cycle inhibition markers and elevated levels of cell-cycle progression markers in association with increased levels of cell death in post-mitotic neurons of clinical and pathological AD subjects. In contrast, individuals who have AD neuropathology but no evidence of cognitive impairment (P-AD) present an expression profile similar to that of individuals with normal aging - with opposite levels of those markers, suggesting that healthy cognition may be associated with preserved DNA damage repair and cell-cycle regulation. Therefore, this indicates that these individuals (P-AD) had reserve, repair or resilience factors that protected them against the deleterious effects of brain pathology, and we speculate that DNA repair, cell-cycle regulation and neuronal cell death are molecular factors that may contribute to the clinical expression of AD.Although additional studies are required to better understand the pathogenic mechanisms, especially the early stages of AD, and to uncover and validate biomarkers of resilience, we believe that our findings are an important step in better understanding the molecular neurobiology of healthy brain aging even in the face of brain pathology (resilient brain aging) and may serve to generate possibilities for new treatment strategies.Figure S1Schematic model to estimate the numbers of hippocampal neurons. Pyramidal neurons from five randomly selected hippocampal cores  of three different slides were counted, and then the average number of counted neurons was used to estimate the total number of hippocampal neurons for further analysis.(TIF)Click here for additional data file.Figure S2Counting of positively stained neurons. Using the tool ‘Events’ of ZEN software, neurons were manually selected, considering the nuclear (blue markers) and cytoplasmic (green markers) staining separately. The software then gives the number of selected events (blue and green arrows).(TIF)Click here for additional data file.Figure S3Hippocampus stained for 8-OHdG. Immunohistochemical immunoreactivity of 8-OHdG in the nuclei (top) of hippocampal neurons from CP-AD (A), P-AD (B), and N (C) individuals. Immunohistochemical immunoreactivity of 8-OHdG in the cytoplasm (bottom) of hippocampal neurons from CP-AD (D), P-AD (E), and N (F) individuals. Larger dashed boxes show magnifications of the smaller boxes. CP-AD, clinical-pathological Alzheimer’s disease; P-AD, pathological Alzheimer’s disease; N, normal aging. Scale bars = 50 pixels.(TIF)Click here for additional data file.Figure S4Hippocampus stained for λ-H2AX. Immunohistochemical immunoreactivity of λ-H2AX in the nuclei (top) of hippocampal neurons from CP-AD (A), P-AD (B), and N (C) individuals. Immunohistochemical immunoreactivity of λ-H2AX in the cytoplasm (bottom) of hippocampal neurons from CP-AD (D), P-AD (E), and N (F) individuals. Larger dashed boxes show magnifications of the smaller boxes. CP-AD, clinical-pathological Alzheimer’s disease; P-AD, pathological Alzheimer’s disease; N, normal aging. Scale bars = 50 pixels.(TIF)Click here for additional data file.Figure S5Hippocampus stained for p53. Immunohistochemical immunoreactivity of p53 in the nucleus (top) of hippocampal neurons from CP-AD (A), P-AD (B), and N (C) individuals. Immunohistochemical immunoreactivity of p53 in the cytoplasm (bottom) of hippocampal neurons from CP-AD (D), P-AD (E), and N (F) individuals. Larger dashed boxes show magnifications of the smaller boxes. CP-AD, clinical-pathological Alzheimer’s disease; P-AD, pathological Alzheimer’s disease; N, normal aging. Scale bars = 50 pixels.(TIF)Click here for additional data file.Figure S6Hippocampus stained for BRCA1. Immunohistochemical immunoreactivity of BRCA1 in the nuclei (top) of hippocampal neurons from CP-AD (A), P-AD (B), and N (C) individuals. Immunohistochemical immunoreactivity of BRCA1 in the cytoplasm (bottom) of hippocampal neurons from CP-AD (D), P-AD (E), and N (F) individuals. Larger dashed boxes show magnifications of the smaller boxes. CP-AD, clinical-pathological Alzheimer’s disease; P-AD, pathological Alzheimer’s disease; N, normal aging. Scale bars = 50 pixels.(TIF)Click here for additional data file.Figure S7Hippocampus stained for PTEN. Immunohistochemical immunoreactivity of PTEN in the nuclei (top) of hippocampal neurons from CP-AD (A), P-AD (B), and N (C) individuals. Immunohistochemical immunoreactivity of PTEN in the cytoplasm (bottom) of hippocampal neurons from CP-AD (D), P-AD (E), and N (F) individuals. Larger dashed boxes show magnifications of the smaller boxes. CP-AD, clinical-pathological Alzheimer’s disease; P-AD, pathological Alzheimer’s disease; N, normal aging. Scale bars = 50 pixels.(TIF)Click here for additional data file.Figure S8Hippocampus stained for phospho-AKT. Immunohistochemical immunoreactivity of phospho-AKT in the nuclei (top) of hippocampal neurons from CP-AD (A), P-AD (B), and N (C) individuals. Immunohistochemical immunoreactivity of phospho-AKT in the cytoplasm (bottom) of hippocampal neurons from CP-AD (D), P-AD (E), and N (F) individuals. Larger dashed boxes show magnifications of the smaller boxes. CP-AD, clinical-pathological Alzheimer’s disease; P-AD, pathological Alzheimer’s disease; N, normal aging. Scale bars = 50 pixels.(TIF)Click here for additional data file.Figure S9Hippocampus stained for Cdk4. Immunohistochemical immunoreactivity of Cdk4 in the nuclei (top) of hippocampal neurons from CP-AD (A), P-AD (B), and N (C) individuals. Immunohistochemical immunoreactivity of Cdk4 in the cytoplasm (bottom) of hippocampal neurons from CP-AD (D), P-AD (E), and N (F) individuals. Larger dashed boxes show magnifications of the smaller boxes. CP-AD, clinical-pathological Alzheimer’s disease; P-AD, pathological Alzheimer’s disease; N, normal aging. Scale bars = 50 pixels.(TIF)Click here for additional data file.Figure S10Hippocampus stained for Cyclin D. Immunohistochemical immunoreactivity of cyclin D in the nuclei (top) of hippocampal neurons from CP-AD (A), P-AD (B), and N (C) individuals. Immunohistochemical immunoreactivity of cyclin D in the cytoplasm (bottom) of hippocampal neurons from CP-AD (D), P-AD (E), and N (F) individuals. Larger dashed boxes show magnifications of the smaller boxes. CP-AD, clinical-pathological Alzheimer’s disease; P-AD, pathological Alzheimer’s disease; N, normal aging. Scale bars = 50 pixels.(TIF)Click here for additional data file.Figure S11Hippocampus stained for phospho-Rb. Immunoreactivity of phospho-Rb in the nuclei (top) of hippocampal neurons from CP-AD (A), P-AD (B), and N (C) individuals. Immunoreactivity of phospho-Rb in the cytoplasm (bottom) of hippocampal neurons from CP-AD (D), P-AD (E), and N (F) individuals. Larger dashed boxes show magnifications of the smaller boxes. CP-AD, clinical-pathological Alzheimer’s disease; P-AD, pathological Alzheimer’s disease; N, normal aging. Scale bars = 50 pixels.(TIF)Click here for additional data file.Figure S12Hippocampus stained for E2F1. Immunoreactivity of E2F1 in the nuclei (top) of hippocampal neurons from CP-AD (A), P-AD (B), and N (C) individuals. Immunoreactivity of E2F1 in the cytoplasm (bottom) of hippocampal neurons from CP-AD (D), P-AD (E), and N (F) individuals. Larger dashed boxes show magnifications of the smaller boxes. CP-AD, clinical-pathological Alzheimer’s disease; P-AD, pathological Alzheimer’s disease; N, normal aging. Scale bars = 50 pixels.(TIF)Click here for additional data file.Figure S13Hippocampus stained for Cdk1. Immunoreactivity of Cdk1 in the nuclei (top) of hippocampal neurons from CP-AD (A), P-AD (B), and N (C) individuals. Immunoreactivity of Cdk1 in the cytoplasm (bottom) of hippocampal neurons from CP-AD (D), P-AD (E), and N (F) individuals. Larger dashed boxes show magnifications of the smaller boxes. CP-AD, clinical-pathological Alzheimer’s disease; P-AD, pathological Alzheimer’s disease; N, normal aging. Scale bars = 50 pixels.(TIF)Click here for additional data file.Figure S14Hippocampus stained for cyclin B. Immunoreactivity of cyclin B in the nuclei (top) of hippocampal neurons from CP-AD (A), P-AD (B), and N (C) individuals. Immunoreactivity of cyclin B in the cytoplasm (bottom) of hippocampal neurons from CP-AD (D), P-AD (E), and N (F) individuals. Larger dashed boxes show magnifications of the smaller boxes. CP-AD, clinical-pathological Alzheimer’s disease; P-AD, pathological Alzheimer’s disease; N, normal aging. Scale bars = 50 pixels.(TIF)Click here for additional data file.Figure S15Hippocampus stained for p27. Immunoreactivity of p27 in the nuclei (top) of hippocampal neurons from CP-AD (A), P-AD (B), and N (C) individuals. Immunoreactivity of p27 in the cytoplasm (bottom) of hippocampal neurons from CP-AD (D), P-AD (E), and N (F) individuals. Larger dashed boxes show magnifications of the smaller boxes. CP-AD, clinical-pathological Alzheimer’s disease; P-AD, pathological Alzheimer’s disease; N, normal aging. Scale bars = 50 pixels.(TIF)Click here for additional data file.Figure S16Hippocampus stained for Cdk5. Immunoreactivity of Cdk5 in the nuclei (top) of hippocampal neurons from CP-AD (A), P-AD (B), and N (C) individuals. Immunoreactivity of Cdk5 in the cytoplasm (bottom) of hippocampal neurons from CP-AD (D), P-AD (E), and N (F) individuals. Larger dashed boxes show magnifications of the smaller boxes. CP-AD, clinical-pathological Alzheimer’s disease; P-AD, pathological Alzheimer’s disease; N, normal aging. Scale bars = 50 pixels.(TIF)Click here for additional data file.


Indian cassava mosaic virus (ICMV) and Sri Lankan cassava mosaic virus (SLCMV). The Agrobacterium Ti plasmid virulence gene virE2, encoding a nuclear-localized, single-stranded DNA binding protein, was introduced into Nicotiana benthamiana to develop tolerance against SLCMV. Leaf discs of transgenic N. benthamiana plants, harboring the virE2 gene, complemented a virE2 mutation in A. tumefaciens and produced tumours. Three tested virE2 transgenic plants displayed reduction in disease symptoms upon agroinoculation with SLCMV DNA A and DNA B partial dimers. A pronounced reduction in viral DNA accumulation was observed in all three virE2 transgenic plants. Thus, virE2 is an effective candidate gene to develop tolerance against the cassava mosaic disease and possibly other DNA virus diseases.Cassava mosaic disease is a major constraint to cassava cultivation worldwide. In India, the disease is caused by  Geminiviridae is classified into seven genera, Begomovirus, Mastrevirus, Curtovirus, Becurtovirus, Eragrovirus, Topocuvirus and Turncurtovirus  DNA A (NCBI Accession No. KP455484) and DNA B (NCBI Accession No. 455485) were cloned following rolling circle amplification  from field-infected cassava leaf samples.PstI fragment in pBSIIKS+. An 1.7-kb PstI/HindIII fragment of DNA A from pBS-SLCMV-At-A was cloned into pBSIIKS+ to yield pBS-SLCMV-At0.6A. The full length DNA A, as a PstI fragment from pBS-SLCMV-At-A, was cloned into the PstI site of pBS-SLCMV-At0.6A to yield the partial dimer clone of SLCMV-[Attur2] DNA A in pBSIIKS+ (pBS-SLCMV-At1.6A). A SacI/SalI fragment from pBS-SLCMV-At1.6A comprising the partial dimer was cloned into the corresponding sites of the binary vector pPZP201 [The plasmid pBS-SLCMV-At-A harbors the full length SLCMV-[Attur2] DNA A (2758 bp) as a  pPZP201  to yield+ as a BamHI fragment. A 2.3-kb BamHI/KpnI fragment from pBS-SLCMV-At-B was inserted into the corresponding sites of the binary vector pPZP201 to yield pPZP-SLCMV-At0.8B. The full length SLCMV-[Attur2] DNA B, as a BamHI fragment from pBS-SLCMV-At-B, was cloned in the BamHI site of pPZP-SLCMV-At0.8B to yield pPZP-SLCMV-At1.8B with the partial dimer of SLCMV-[Attur2] DNA B.The plasmid pBS-SLCMV-At-B harbors the full-length SLCMV-[Attur2] DNA B (2738 bp) in pBSIIKSA. tumefaciens strain Ach5 by triparental mating dCTP using the Megaprime DNA labeling system  to prepare probes. Hybridizations were carried out at 65°C and high stringency post hybridization washes were performed [Total plant DNA was extracted  and estierformed .N. benthamiana leaf discs were infected with wild type A. tumefaciens strain A348 (with the wild type Ti plasmid pTiA6) and the mutant A. tumefaciens strain A348mx358 which harbors pTi358 with Tn3 HoHo1 insertion in the virE2 gene [virE2 transgenic N. benthamiana plants were preincubated for two days on MS shoot induction medium and infected with A. tumefaciens strains grown to A600 = 1 in AB minimal medium [Control rE2 gene . For Virl medium . The leaN. benthamiana plants was used for RNA extraction. Total RNA was extracted using the Trizol method as per instructions provided by the manufacturer . RNA was estimated in a spectrophotometer. Total RNA (10 µg) was electrophoresed in a 1.2% (w/v) agarose gel containing 1% formaldehyde (v/v) in 1 × MOPS (3-(N-morpholino)propane sulphonic acid) buffer. Northern blot analysis was performed as described by Pawlowski et al. [Young leaf tissue (0.5 g) of i et al. .N. benthamiana plants was performed with the A. tumefaciens strain Ach5 harboring the partial dimers of SLCMV-[Attur2] DNA A and DNA B (two strain method). The A. tumefaciens (pPZP-SLCMV-At1.6A) and A. tumefaciens (pPZP-SLCMV-At1.8B) cultures were grown in AB minimal medium to A600 = 1 and cells were centrifuged at 28 °C at 1100× g. The pellets were resuspended in AB minimal medium (pH 5.6) containing 100 µM acetosyringone. The cultures were mixed (1:1) and agroinfection was performed by inoculating 10 µL of the bacterial mixture above the node of the first fully expanded leaf from the top. The stem was immediately pricked with a 30 G needle  DNA A and DNA B. Two weeks post-infection, control plants infected with partial dimers of SLCMV showed severe stunting and downward leaf curling. These symptoms were noticeably reduced in the E3, E6 and E7 transgenic plants -214,785-100%). All three transgenic plants exhibited reduction in viral DNA in comparison to the control plant  genome modified to express the M13 phage ssDNA binding protein g5p [N. benthamiana plants. Binding of g5p with the ssDNA of ToLCV may have competed with the NSP binding to ssDNA and thereby reduced the spread of the viral DNA. As in the case of g5p, the ssDNA binding protein VirE2 also might cooperatively bind to SLCMV ssDNA in the nucleus, thus preventing NSP binding and shuttling to the cytoplasm for cell to cell and systemic movement. It would very useful to study whether VirE2 can out-compete NSP in an in vitro ssDNA binding assay. Our reports show that A. tumefaciens VirE2, with the unique features of ssDNA binding and nuclear localization, is very effective in both MYMV [Local and systemic spread of geminiviral DNA is essential to establish infection in different parts of a plant. In bipartite begomoviruses, nuclear shuttle protein (NSP) and movement protein (MP) play important roles in viral movement. NSP helps in the transport of geminivirus DNA from the nucleus to the cytoplasm, whereas MP facilitates the viral movement between the cells ,42,43,44tein g5p  developeoth MYMV  and SLCM


WT-GTP/GDP) catalytic domain, the K-Ras4BWT-GTP–GAP complex, and the mutants  and their complexes with GAP. In addition, we simulated ‘exchanged’ nucleotide states. These comprehensive simulations reveal that in solution K-Ras4BWT-GTP exists in two, active and inactive, conformations. Oncogenic mutations differentially elicit an inactive-to-active conformational transition in K-Ras4B-GTP; in K-Ras4BG12C/G12D-GDP they expose the bound nucleotide which facilitates the GDP-to-GTP exchange. These mechanisms may help elucidate the differential mutational statistics in K-Ras4B-driven cancers. Exchanged nucleotide simulations reveal that the conformational transition is more accessible in the GTP-to-GDP than in the GDP-to-GTP exchange. Importantly, GAP not only donates its R789 arginine finger, but stabilizes the catalytically-competent conformation and pre-organizes catalytic residue Q61; mutations disturb the R789/Q61 organization, impairing GAP-mediated GTP hydrolysis. Together, our simulations help provide a mechanistic explanation of key mutational events in one of the most oncogenic proteins in cancer.Ras mediates cell proliferation, survival and differentiation. Mutations in K-Ras4B are predominant at residues G12, G13 and Q61. Even though all impair GAP-assisted GTP → GDP hydrolysis, the mutation frequencies of K-Ras4B in human cancers vary. Here we aim to figure out their mechanisms and differential oncogenicity. In total, we performed 6.4 μs molecular dynamics simulations on the wild-type K-Ras4B (K-Ras4B Ras proteins are quintessential members of small GTPases that function as molecular switches by alternating between inactive GDP-bound and active GTP-bound states136789111213The three human Ras genes encode four proteins: H-Ras, N-Ras and the splice variants K-Ras4A and K-Ras4B. All share approximately 90% sequence identity in their catalytic domain (residues 1–166) but show significant differences in their C-terminal hypervariable region (HVR)15et al.Despite intense interest in Ras over the years192021Over the years molecular dynamics (MD) simulations have been carried out to understand the structure and function of wild-type (WT) and mutated proteins25262829303132343537384042434412WT–GTP exists in two states: active and inactive. Oncogenic mutations elicit an inactive-to-active conformational transition in K-Ras4B-GTP. During our K-Ras4BWT-GDP simulations we did not capture conformations visiting the active state. However, the G12C and G12D mutations dramatically affect the distribution of the K-Ras4B inactive state and increase the exposure of the nucleotide-binding site. The exchanged nucleotide simulations indicate that GTP-to–GDP exchange in K-Ras4BWT can sample the GDP-like open conformation, whereas in our timescales the GDP-to-GTP exchange simulation is incapable of capturing the GTP-like closed conformation. Finally, simulations of the K-Ras4BWT-GTP–GAP complex reveal that in addition to providing the arginine finger R789, GAP plays a key role in stabilizing the active, catalytically competent conformation of K-Ras4B. However, the oncogenic mutations markedly disturb the alignment of catalytic residue Q61 of K-Ras4B and GAP’s R789, impairing the GAP-mediated GTP hydrolysis. Collectively, our data provide detailed mechanisms of how oncogenic mutations affect the structural and dynamic behavior of K-Ras4B and resolve its mutational biases in human cancers.Here, we address these questions by performing μs explicit solvent MD simulations of K-Ras4B catalytic domain in its GTP/GDP-bound states as well as the GTP-bound K-Ras4B–GAP complex of the WT and oncogenic states . The simulations show that in solution, K-Ras4BQ61H (PDB ID: 3GFT) and K-Ras4BG12D (PDB ID: 4DSN)WT-GTP and in 4DSN, residue S1 was mutated back to native M1 and the C-terminal HVR (residues 167–180) were deleted to model the K-Ras4B catalytic domain. The G13D mutant as well as the G12C and G12V mutants were constructed based on the 3GFT and 4DSN, respectively, by replacing targeted residues with desirable residues. The simulation of Q61H mutant was directly used the PDB 3GFT.In the simulation of K-Ras4B–GTP in aqueous solution, the structures of K-Ras4BWT (PDB ID: 4LPK)G12D (PDB ID: 4EPR)In the simulation of K-Ras4B–GDP, the structures of K-Ras4BWT was extracted from the respective MD trajectory. Based on this simulated structure, GTP (GDP) in the nucleotide-binding site was replaced by GDP (GTP) and subsequently MD simulations were conducted on the resulting systems.In the nucleotide exchange simulations, the last 400 ns snapshot of GTP/GDP-bound K-Ras4BWT in complex with GDP and AlF3 was extracted (PDB ID: 1WQ1)3 were substituted by GTP to model the K-Ras4BWT-GTP–GAP complex. The sulfide bond between C771 and C876 in the GAP was defined. The respective mutants were then constructed by replacing targeted residues with desirable residues.In the simulations of the K-Ras4B–GAP complex, the structure of H-Raswww.pharmacy.manchester.ac.uk/bryce/amber). Energy minimization of the initial model was performed following the introduction of mutations in K-Ras4B. Next, the proteins were solvated in a truncated octahedral box with TIP3PIn the respective complexes, GppNHp, a nonhydrolyzable GTP analogue, was modified to physiological GTP. The parameters for GTP and GDP were taken from AMBER parameter database , for the displacement of all Cα atoms pairs, i and j, was calculated (E.g. 1),To identify protein domains with correlated residue motions the cross-correlation coefficient, C is from −1 and 1. Positively correlated residues move in the same direction, whereas (negatively) anti-correlated residues in the opposite direction.The value of WT-GTP. The covariance matrix C of the atomic coordinates was constructed (E.g. 2):PCAxi is a Cartesian coordinate of the ith Cα atom, 〈xi〉 represents the time average over all the configurations selected in the simulation, and N is the number of the Cα atoms. Prior to analysis, translation and rotational motions were excluded by overlaying the Cα atom of K-RasWT-GTP to the reference crystal structure.where C yields the eigenvalues λi and the corresponding eigenvectors Vi, namely, the principal component (PC). Vi represent the directions in the multidimensional space that correspond to independent modes of atomic motion, while λi represent their corresponding amplitudes. The first few PCs describe collective global motions in the protein. The projection Proj of any structure (snapshot) M onto the ith PC was calculated (E.g. 3):The diagonalization of Mα is the Cα atoms of proteins after overlaying M with the reference crystal structure.where a atoms to remove overall rotation and transition. Then, pairwise Cα atoms RMSD comparisons were performed between any snapshot and the average coordinate after rigid-body alignment using a threshold of 1.5 Å.The clustering was performed with the average-linkage algorithm that has been described previouslyK-Ras4B structure consists of two components, the catalytic domain (residues 1–166) and the membrane targeting HVR (residues 167–188)58WT-GTP and its oncogenic mutants was carried out to explore the effect of oncogenic mutations. Second, each 400 ns simulation of K-Ras4BWT-GDP and the oncogenic mutants was deployed to probe how oncogenic mutations affect the dynamics of the nucleotide-binding site. Third, each 200 ns nucleotide exchange simulation of K-Ras4BWT was conducted to investigate the conformational transitions and the accessibility of the two states during the nucleotide exchange process. Finally, each 200 ns simulation of K-Ras4BWT-GTP–GAP and the oncogenic mutants was performed to elucidate the role of GAP in catalysis and the disruption of GAP-mediated GTP hydrolysis in oncogenic mutants.For the twenty systems of K-Ras4B in the different states we performed a total of 6.4 μs MD simulations . Althoug31P NMR spectra and crystal structures of guanosine 5′-triphosphate (GppNHp)-bound forms of H-Ras mutants suggested that in their GTP-bound forms they exist in two interconverting conformations, ‘inactive’ and ‘active’60WT-GTP. Principal component analysis (PCA) and cluster analysis show the existence of two, active and inactive, states in K-Ras4BWT-GTP (α atom of switch II residue G60 to the Pβ atom of GTP (d1) and the other from the Cα atom of switch I residue T35 to the Pβ atom of GTP (d2), were calculated. As shown in d2 exhibit small differences between WT and mutated GTP-bound K-Ras4B, suggesting subtle conformational changes in the switch I domain triggered by oncogenic mutations compared to K-Ras4BWT-GTP. However, comparisons of the probability distributions of d1 between WT and mutated GTP-bound K-Ras4B reveal notable changes, indicating that oncogenic mutations have an effect on the conformational dynamics of switch II domain. For K-Ras4BWT-GTP, we observed two intervals of probability distributions of d1  of GDP was measured to predict the magnitude of mutations-induced conformational changes of the nucleotide-binding site in K-Ras4BWT and its oncogenic mutants. As shown in To reveal the conformational preference of K-Ras4Blculated . Compari  in the nucleotide-binding site with GDP (GTP), respectively . As shown in 2 during the 550–600 ns compared to that of 60.4 ± 9.1Å2 during the 400–550 ns  of K-Ras4B in the free and complexed with GAP states were analyzed. As shown in WT-GTP-GAP complex .