Arabidopsis thaliana plants, ROS production increased with AA, but not with MFA, allowing comparison of transcript profiles under different ROS conditions during MRR. Variation in transcript accumulation over time for eight nuclear encoded mitochondrial protein genes suggested operation of both common and distinct signaling pathways between the two treatments. Consequences of mitochondrial perturbations for the whole transcriptome were examined by microarray analyses. Expression of 1316 and 606 genes was altered by AA and MFA, respectively. A subset of genes was similarly affected by both treatments, including genes encoding photosynthesis-related proteins. MFA treatment resulted in more down-regulation. Functional gene category (MapMan) and cluster analyses showed that genes with expression levels affected by perturbation from AA or MFA inhibition were most similarly affected by biotic stresses such as pathogens. Overall, the data provide further evidence for the presence of mtROS-independent MRR signaling, and support the proposed involvement of MRR and mitochondrial function in plant responses to biotic stress.Plant mitochondria signal to the nucleus leading to altered transcription of nuclear genes by a process called mitochondrial retrograde regulation (MRR). MRR is implicated in metabolic homeostasis and responses to stress conditions. Mitochondrial reactive oxygen species (mtROS) are a MRR signaling component, but whether all MRR requires ROS is not established. Inhibition of the cytochrome respiratory pathway by antimycin A (AA) or the TCA cycle by monofluoroacetate (MFA), each of which initiates MRR, can increase ROS production in some plant cells. We found that for AA and MFA applied to leaves of soil-grown  Plant mitochondria and chloroplasts communicate with the cell nucleus to modify nuclear gene expression so that organelle and cell properties can be adjusted as metabolism and the environment change. For mitochondria, this signaling is termed mitochondrial retrograde regulation (MRR) Plants with mutations in genes encoding mitochondrial electron transport chain (mtETC) components demonstrate the importance of mitochondria for many processes. Different Complex I mutations alone affect chloroplasts nuclear genes encoding mitochondrial proteins (NEMP genes), particularly genes for alternative NAD(P)H dehydrogenases (NDHs) and for alternative oxidases (AOXs). Together, NDH and AOX make a non-phosphorylating bypass pathway for the cytochrome pathway of the mtETC In one approach to the analysis of MRR, chemicals applied to leaves or suspension culture cells have been assessed for their ability to alter transcription of nuclear genes. Most work has focused on 2O2, representing increased mtROS production, and organic acids that are part of the TCA cycle, including citrate and malate. These treatments all induce AOX Nicotiana tabacumGlycine maxAOX and NDH, as well as ROS-dependent ones, operate in cells. These results with organic acids have been interpreted more specifically as indicating that mtROS-independent MRR pathways also exist. However, it is not clear that the measured responses to either of these exogenous chemical stimuli accurately represent mitochondrial signaling, whether mtROS-dependent or -independent. AOX gene expression was thought to be responsive only to mitochondrial signals, but AOX1a of Arabidopsis is now known to respond to non-mitochondrial as well as mitochondrial signaling pathways and so is not an obligate MRR marker 2O2 acts as a signal for various subcellular sites in addition to mitochondria 2O2 or organic acids difficult to interpret and leave the existence of mtROS-independent MRR pathways unresolved.Two exogenous chemical treatments that may mimic MRR signals are HAtAOX1a transcript accumulation kinetics vary A related experimental approach better ensures that mitochondrial perturbation, with consequent initiation of MRR, is the primary starting point for changes in nuclear gene transcription. This approach uses the application of known mitochondrial inhibitors. Inhibitors of all the mtETC complexes, including antimycin A (AA) which inhibits Complex III, and MFA (monofluoroacetate), a TCA cycle inhibitor that acts on aconitase, induce expression of genes encoding AOX e.g.,  and manyAOX, NDH, and other NEMP genes Chlamydomonas reinhardtii, the effects AA on the transcriptome were examined in conjunction with application of acetate Beyond To address further the relationship of MRR and nuclear gene expression, we sought to survey and compare potential MRR targets during mtETC inhibition and during TCA cycle inhibition. For this we used intact Arabidopsis plant leaves treated with AA or with MFA and found these treatments had distinct consequences for ROS production. AA did increase ROS production, as has been demonstrated in other systems. However, unlike for previous observations (see above), MFA treatment did not detectably increase ROS production. This allowed us to compare kinetics of transcript accumulation of selected NEMP genes under circumstances of unchanged and elevated ROS during known mitochondrial disruptions, providing evidence for MRR without dramatic elevation of ROS. We also compared the whole transcriptomes of treated leaves to examine the scope of the response of nuclear genes to the restriction of mitochondrial function by these two inhibitors. Analyses indicate many gene targets are affected, either directly or indirectly, by MRR from reduced mitochondrial function. For either treatment, regardless of ROS level, a strong response to oxidative stress by the transcriptome was not detected.2O2 and other peroxides 2DCFDA) alone or H2DCFDA plus AA or menadione for 6 h in the dark correlated well with imaging of leaves for DCF fluorescence and with diaminobenzidine (DAB) leaf staining, which also detects H2O2  in the external medium has been used with plant cells to assess cellular ROS production, specifically Hcts H2O2 . These rThe technique was used to determine ROS level changes in excised leaves during AA or MFA inhibition for up to 10 h in the dark. ROS production increased in leaves incubated in 10 µM AA by 4 h, continuing to 10 h . In contFor gene transcript experiments (see below), intact plants were exposed to inhibitors by sprayed application, which initiated the exposure period see ‘’. When RAtAOX1a (At3g22370), encoding the most highly expressed AOX isozyme, and NDB2 (At4g05020), encoding an NDH localized to the external surface of the inner mitochondrial membrane], two subunits of succinate dehydrogenase, an enzyme involved in both the mtETC and the TCA cycle , three proteins associated with stress , and mtPORIN (At5g15090), which is part of the permeability transition pore that may control programmed cell death through MRR in response to stresses The transcript accumulation kinetics of several NEMP genes were followed over a 12 h time course. These NEMP genes encode: two mitochondrial innermembrane proteins that help to bypass the mtETC [mtGST, GDH2, SDH2-1, HSP70-9; MtPORIN transcript levels increased at 2 h under both treatments then continued a slow increase throughout the remainder of the time course . This and the variation in kinetics of induction between the two inhibitors  although variable induction yielded q-values between 0.05 and 0.1 (SDH-FP and SDH2-1 showed highly variable results with some induction in two of the three bioreplicate experiments (data not shown). Consequently, q-values for these two genes were high  using MapMan. BINs with overall responses statistically significantly different from average (adjusted p<0.05) were identified as described in ‘Chloroplast-related categories, including those for photosynthesis  and for protein synthesis in chloroplasts (BIN 29.2.1), were among the most highly statistically significant for both AA and MFA treatments, showing pervasive decreases in transcript abundance , S4. ForFor both transcriptome data sets, metabolism-related gene categories were identified as responsive. With AA treatment, gene groups encoding enzymes for amino acid synthesis showed overall transcript level increases  and its subgroup specific to calcium signaling (BIN 30.3) as well as categories for genes encoding NAC domain transcription factors (BIN 27.3.27) and WRKY domain transcription factors (BIN 27.3.32) showed overall induction for both AA and MFA treatment . TranscrBotrytis cinerea) and oomycete (Phytophthora infestans) pathogens and the P. infestans elicitor, NPP1. Subsequent nodes join with the bacterial pathogens Pseudomonas syringae avrRpm1  and 6 h P. syringae phaseolicola, and the bacterial elicitors flagellin P. syringae phaseolicola, close to the bacterial elicitors  in 47 other experiments in which a stress was applied , includilicitors .P. syringae treatments, DC3000 6 h and HrcC- 6 h, and Erysiphe orontii 6 and 12 h treatments were in nodes distant from the AA and MFA treatment data, similar to the light treatment outgroup  have been tested for the effect of MFA on tissue ROS level, leaving open the question whether there is a typical plant tissue response to MFA with respect to ROS production. The events leading to increased ROS in tobacco cells in the presence of MFA have not been elucidated. TCA cycle inhibition by MFA presumably would serve to decrease the supply of reductant for the mtETC, creating a relatively oxidized state rather than the over-reduction that occurs with AA inhibition. However, low levels of reductant could curtail regeneration of ROS buffer systems in the mitochondria, and ultimately lead to increased mtROS. Differing activities in Arabidopsis and tobacco of the GABA shunt, a NADH-producing partial bypass pathway for the TCA cycle linked to decreased tissue ROS production To determine if accumulation of transcripts for mitochondrial proteins was affected during mitochondrial inhibition, whether or not ROS production increased, expression of eight NEMP genes was followed over a 12 h time course. Regardless of ROS level, transcripts for four of the eight NEMP genes began to accumulate within 1 h during both mtETC inhibition and TCA cycle inhibition, indicating that MRR and subsequent expression changes occurred quickly in response to the inhibitions.mtPORIN, mtGST, GDH2, and SDH2-1) consistent with mtROS-independent MRR pathway(s) operating during both mtETC inhibition and TCA cycle inhibition. Four genes showed different accumulation patterns between the treatments  and three of the first group of genes  showed a second late accumulation peak with only AA treatment. This pattern variety, evident across and within the groups of selected genes, could result from mtROS-dependent and –independent signaling. For example, the time of maximum accumulation for the transcript pair of AOX1a and NDB2 was separated by 4 h between the AA and MFA treatments. During AA inhibition, elevated mtROS could act as a signal for increased AtAOX1a expression as previously reported AtAOX1a and NDB2 induction with a pattern different from AA, a mtROS-independent MRR pathway also appears able to induce these genes. Recent indirect evidence indicates that malonate inhibition of succinate dehydrogenase, a component of both the mtETC and the TCA cycle, does not increase mtROS production in Arabidopsis seedlings AOX1a and NDB2 transcript abundance in Arabidopsis culture cells For the early part of the time course, through 6–8 h, four genes showed similar transcript accumulation patterns for both treatments  where 70% of the genes induced by MFA were also induced by AA. While most of the affected genes were not NEMP genes, a number of NEMP genes did respond to the inhibitor treatments, with some being induced by both. Although the inhibitors have distinct mitochondrial sites of action, the similarities in transcriptome responses may reflect ongoing common MRR signaling, as suggested by the signaling-related functional categories  affected by both treatments. The transcriptomes may also reflect a common metabolic response to restriction of mitochondrial function caused by the inhibitors.AOX1a and NDB2 were highly induced at a later time point (12 h). Metabolic analysis showed that the TCA cycle had slowed in the rotenone-treated cells Some broad features also differed between the responses with the transcriptome resulting from cytochrome pathway inhibition consisting of mostly up-regulated genes (89%), and that resulting from TCA cycle inhibition showing relatively more down-regulation (40%), including functional gene categories for starch synthesis, photorespiration, and C1 metabolism. The transcriptome of rotenone-inhibited Arabidopsis culture cells also included down-regulation of these same functional categories A highly-significant functional gene category with overall down-regulation for all transcriptomes following mitochondrial inhibition  were statistically significant but with over-all down-regulation. In the cluster analysis, most of the abiotic stress  and oxidative stress-related  transcript subsets were weakly correlated with the AA and MFA treatment query sets. This clustering outcome suggests that the genes typically affected by abiotic and oxidative stresses were affected to a different degree, or not at all, during treatment with the two mitochondrial inhibitors.MapMan and cluster analyses provided insight into how the transcriptome as a whole responded to the mitochondrial inhibitions compared to other stresses. Glutaredoxins and glutathione 2O2 on gene expression in leaves Thus, MapMan and cluster analysis each indicated that the Arabidopsis leaf transcriptome did not strongly respond as though the leaves had been subjected to an abiotic or oxidative stress, even with increased ROS production during AA treatment. This result is consistent with observed differences between effects of AA and HRather than an association with abiotic or oxidative stress, the cluster analysis showed that the genes affected by the mitochondrial inhibitors were most similarly affected under the biotic stress conditions of pathogen challenge and bacterial elicitor exposure . Also, MapMan analysis showed “biotic stress” to be one of the most statistically significant functional gene categories for both AA and MFA treatments. This category includes genes encoding disease-resistance proteins with TIR, TIR-NBS, TIR-NBS-LRR, and CC-NBS-LRR domain signatures and genes encoding proteases and avirulence-responsive proteins.Other affected functional categories for AA and MFA showed transcript changes previously observed with biotic stress, specifically pathogen attack. Photosynthesis rates decrease Transcriptome changes suggesting increases in the amino acid pool of the leaves were also consistent with plant responses to pathogens, although the changes differed between the two inhibitor treatments. For AA-treated leaves, functional category analysis indicated that expression of genes encoding enzymes involved in aromatic amino acid synthesis, including tryptophan synthesis, increased. Similar expression changes have been observed upon bacterial infection of Arabidopsis leaves With AA treatment only, the TCA cycle and mitochondrial electron transport functional categories were significantly affected, showing overall up-regulation, consistent with the increased respiration that accompanies the resistance response P. syringae DC3000 HrcC− and DC3000 treatments did not correlate with the AA- and MFA-treatment transcriptomes or the other pathogen and pathogen-related treatments. This is because these strains, unlike P. syringae phaseolicola and avrRpm1, do not express avirulence factors recognized by Arabidopsis, and therefore do not trigger the plant's pathogen resistance response Erysiphe orontii treatment transcript subsets also were not correlated with AA and MFA. Erysiphe is an obligate biotroph, compared to the fungal necrotroph Botrytis and the oomycete facultative necrotroph PhytophthoraBotrytis and Phytophthora triggering plant transcript subset profiles that correlate closely with the AA- and MFA-treatment transcriptomes while Erysiphe does not.Further support for a link between MRR and pathogen stress response comes from the cluster analysis. The transcript subsets for Of the two abiotic stresses that clustered with AA and MFA, ozone, when applied to tobacco leaves, rapidly inhibits the mitochondrial cytochrome oxidase pathway dsr1, cannot signal for induction of a reporter gene under stress conditions because it is unable to increase mtROS production. This mutant is more susceptible to a fungal pathogen and a virulent bacterial pathogen, but shows no altered resistance to avirulant bacteria, further suggesting the possibility that some resistance pathways may operate without elevation in mtROS levels In total, with AA treatment, the transcriptome contains more elements of the transcriptome of a pathogen-challenged plant than with MFA treatment. This may be due to the elevated ROS levels from AA treatment signaling a more complete response. On the other hand, the MFA-treatment transcriptome pattern suggests that at least some of the response to pathogens can occur without elevated ROS. The Complex II mutant, Changes in the mitochondrial proteome The mtETC inhibitor AA increased ROS production by Arabidopsis leaves, but the TCA cycle inhibitor MFA had no detectable effect on ROS levels. Despite the clear difference in the observed ROS levels, both mitochondrial perturbations quickly resulted in increased NEMP gene expression, most likely to begin mitochondrial adjustments to the restrictions. Time course expression patterns of several genes were the same with both inhibitors, while patterns for others differed, including the coordinately regulated genes for enzymes of the mtETC bypass pathway. These transcript accumulation patterns show that large increases in ROS are not needed for MRR, and are consistent with the presence of mtROS-dependent and –independent MRR signaling pathways. However, no increase in ROS production by mitochondria specifically will need to be shown to verify that mtROS-independent MRR occurs. Transcriptome analysis showed that disruption of the mitochondria by either inhibitor affected transcript abundance for many nuclear genes. With AA treatment and increased ROS, the transcript profiles suggested some genomic response to oxidative stress. However, the gene expression changes observed for both mitochondrial perturbations, despite their different sites of action, corresponded most closely to expression changes of the same genes in response to biotic stresses. Thus, the possibility that restriction of mitochondrial function and MRR are involved in biotic stress responses is supported by our observations.Arabidopsis thaliana Col-0 was grown, with separate plantings for microarray and RNA blot experiments and leaf ROS measurements, in Sunshine Mix #1  soil at 21°C during 16 h of light of 100 µmol m−2 s−1 and 18°C during the 8 h dark period. Plants were fertilized as described 2O2 and other peroxides, specifically, was measured using H2DCFDA . In a set of experiments to determine ROS production under conditions used to obtain the time course RNA blot data and the microarray data, intact plants in soil at 20 days after germination were control treated or treated with inhibitors exactly as described above, including the incubation in the dark prior to inhibitor treatments. At the specified time points, leaves were excised and incubated for 30 min in H2DCFDA at a final concentration of 20 µM in 10% Murashige and Skoog basal salt mix Leaf ROS production, H2DCFDA was added to a final concentration of 20 µM, followed by a 30 min pre-incubation at about 25°C in the dark for uptake. For experiments for 2O2 following the procedure of Thordal-Christensen et al. In another set of experiments, leaves were excised and transfered to 10% Murashige and Skoog basal salt mix All plasmid and DNA fragment manipulations were done according to standard protocols AtAOX1a transcript, a labeled fragment from an AtAOX1a cDNA clone NDB2, U12861; mtPORIN, 124F4; AtHSP70-9, U15562; mtGST, U13302; GDH2, 248A23; SDH2-1, U09779; SDH-FP, U13004. Hybridization was visualized using the NightOwl cooled CCD camera system and the WinLight 32 analysis software .Total RNA was isolated from plants  using TRIzol according to the protocol of the manufacturer . RNA was separated by agarose-formaldehyde gel electrophoresis free kit, Ambion, Austin, TX, USA) according to the manufacturer's instructions. RNA concentrations were determined spectrophotometrically and integrity was checked on a 1.2% agarose-formaldehyde gel according to Sambrook et al. in vitro transcription reaction to generate amino allyl modified aRNA, 5–10 µg of which was used for coupling to either Cy3 or Cy5 dyes . After coupling at 25°C for 60 min, the reaction was quenched with hydroxylamine. The Cy3- or Cy5-labeled target was purified using an RNeasy MinElute Cleanup Kit .Total RNA was initially extracted from plants using TRIzol as described above and treated with TURBO-DNase (TURBO DNA-Microarrays used for these experiments were ATv3 x.y.z microarrays produced using the Operon-Qiagen Arabidopsis Genome Array Ready Oligo Set (AROS) version 3.0, which represents >26,000 loci . Microarrays were prepared, hybridized and washed following procedures based on the recommendations of the manufacturer . Prior to hybridizations, microarrays were rehydrated by exposure to water vapor produced by a 45°C water bath for 5–10 s and then snap dried on a 65°C heating block for 5 s. This cycle was repeated three times with cooling to about 25°C between each cycle. DNA was cross-linked to the microarrays by exposure to 180 mJ UV-radiation using a Stratalinker . Hybridization in each case was with aRNA made using RNA isolated from inhibitor-treated tissue and labeled with Cy3 or Cy5 and aRNA made using RNA isolated from control treated tissue and labeled with the complementary dye . Microarrays were then washed in 1% SDS for 5 min at about 25°C on a shaker, dipped several times into sterile diethyl pyrocarbonate-treated water, and immediately dipped in and washed with 100% ethanol with shaking at 25°C for 3 min. Finally, microarrays were dried by centrifugation at 1000 g for 3 min in slide holders in a table-top centrifuge and used for hybridization. Hybridization mixture (60 µL) consisted of 48 or 96 pmol of dye (which corresponded to about 0.3–0.6 µg of labeled aRNA), 3.6 µL of liquid block , 2× SSC, and 0.08% SDS (w/v). The hybridization mixture was incubated in a boiling water bath for 2 min and transferred to ice. A raised cover slip  was placed over each microarray and hybridization mixture was applied to one end of this open-ended chamber. The microarray was immediately placed in a hybridization chamber and incubated overnight (8–12 h) at 55°C. After hybridization, microarrays were washed successively for 5 min in 2× SSC and 0.5% (w/v) SDS at 55°C, followed by 0.5× SSC and then 0.05× SSC, both at about 25°C. The microarray was dried by centrifugation at 1000 g for 3 min and scanned using a G2565BA Microarray Scanner System . Quantitative data were extracted from image files of microarrays and further analyzed using GenePix Pro 6.0 software  and the appropriate GenePix Array List file from the Oligonucleotide Microarray Facility.2-transformed. In the first ANOVA step of the mixed model, these values were scaled and normalized. In the second ANOVA step, these data were used to determine statistically significant differences in gene transcript levels between treated and control samples. The ANOVA steps were performed in SAS version 9 . A false discovery rate parameter, the q-value, was calculated using the q-value package provided by Bioconductor to correct for the multi-testing problem and was used to identify significantly differentially expressed genes Three biological replicate experiments (each including treatment and control) with dye-swapping (6 microarrays) and a duplicate slide of one dye condition for each of two of the biological replicates  were performed and used in the analyses for AA-treated versus control samples. Three biological replicate experiments (each including treatment and control) with dye-swapping (6 microarrays) were performed and used in analyses for MFA-treated versus control samples. For analyses of the AA-treated or MFA-treated versus control samples, differences in transcript levels were determined by a two-step mixed model analysis of variance (ANOVA) procedure http://mapman.gabipd.org). The Wilcoxon-Mann-Whitney rank sum test using the Benjamini-Hochberg correction for false discovery, part of the ImageAnnotator analysis, was used to assign probabilities to BINs showing whether the average BIN response  was significantly different from the average responses of all the other BINs in a data set Analysis of the microarray data using MapMan was essentially as previously described 2-transformed expression ratios were derived for all available replicates then averaged. From these data sets, the AA- or MFA-responsive genes that are represented in all array types were used in the respective cluster analyses. When AA-responsive genes were the query set, MFA treatment data were included in the analysis, and vice versa. The finalized data sets from these experiments were compared using Cluster http://sourceforge.net/projects/jtreeview/). The Pearson correlation coefficients derived by Cluster between experiments are listed in Expression of 1316 genes was statistically significantly (q≤0.05) either up-regulated or down-regulated following AA treatment. By the same criteria, 606 genes were deemed MFA-responsive. These genes were used in a cluster analysis of transcript levels of the same genes during biotic and abiotic stress treatments. From public databases , 46 expeResource S1Genes oppositely regulated during AA and MFA treatments.(XLS)Click here for additional data file.Resource S2MapMan BINs with rank sum adjusted probabilities of p<0.05 identified for the MFA- and AA-treatment q-value data sets.(XLS)Click here for additional data file.Resource S3Diagramatic representation of selected statistically significant functional gene categories (BINs) with cytochrome pathway inhibition by AA (left) or TCA cycle inhibition by MFA (right). The BINs have been excerpted from MapMan diagrams. The logged q-value is shown for each gene  with the direction of transcript level change indicated by color, blue indicating an increase, and red indicating a decrease. All the BINs were standardized to the same range of the color scale. On the scale, values less than −1.3 or greater than 1.3 correspond to q-values of 0.05 or less.(TIF)Click here for additional data file.Resource S4Fold-change and q-value data for genes in BINs that appear in  and  and/or are discussed in the text.(XLS)Click here for additional data file.Resource S5List of experiments used for cluster analyses.(XLS)Click here for additional data file.Resource S6Pearson correlation coefficients for cluster analyses using genes with significantly altered expression (q≤0.05) by cytochrome pathway inhibition with AA or TCA cycle inhibition with MFA.(XLS)Click here for additional data file.Resource S7Heat map of gene expression data from all experiments used in the cluster analyses arranged by their associations as determined by the Cluster program using genes whose expression was altered in expression (q≤0.05) by AA.(TIF)Click here for additional data file.Resource S8Heat map of gene expression data from all experiments used in the cluster analyses arranged by their associations as determined by the Cluster program using genes whose expression was altered in expression (q≤0.05) by AA.(TIF)Click here for additional data file.Resource S9Heat map of gene expression data from all experiments used in the cluster analyses arranged by their associations as determined by the Cluster program using genes whose expression was altered in expression (q≤0.05) by AA.(TIF)Click here for additional data file.Resource S10Heat map of gene expression data from all experiments used in the cluster analyses arranged by their associations as determined by the Cluster program using genes whose expression was altered in expression (q≤0.05) by AA.(TIF)Click here for additional data file.Resource S11Heat map of gene expression data from all experiments used in the cluster analyses arranged by their associations as determined by the Cluster program using genes whose expression was altered in expression (q≤0.05) by AA.(TIF)Click here for additional data file.Resource S12Heat map of gene expression data from all experiments used in the cluster analyses arranged by their associations as determined by the Cluster program using genes whose expression was altered in expression (q≤0.05) by AA.(TIF)Click here for additional data file.Resource S13Heat maps of gene expression data from all experiments used in the cluster analyses arranged by their associations as determined by the Cluster program using genes whose expression was altered in expression (q≤0.05) by MFA.(TIF)Click here for additional data file.Resource S14Heat maps of gene expression data from all experiments used in the cluster analyses arranged by their associations as determined by the Cluster program using genes whose expression was altered in expression (q≤0.05) by MFA.(TIF)Click here for additional data file.Resource S15Heat maps of gene expression data from all experiments used in the cluster analyses arranged by their associations as determined by the Cluster program using genes whose expression was altered in expression (q≤0.05) by MFA.(TIF)Click here for additional data file.


Both gastric and colorectal cancers (CRC) are the most frequently occurring malignancies worldwide with the overall survival of these patients remains unsatisfied. Identification of tumor suppressor genes (TSG) silenced by promoter CpG methylation uncovers mechanisms of tumorigenesis and identifies new epigenetic biomarkers for early cancer detection and prognosis assessment. Cystathionine-beta-synthase (CBS) functions in the folate metabolism pathway, which is intricately linked to methylation of genomic DNA. Dysregulation of DNA methylation contributes substantially to cancer development.CBS gene in CRC samples, compared to adjacent tissues. Methylation and decreased mRNA expression of CBS were detected in most CRC cell lines by methylation-specific PCR and semiquantitative RT-PCR, as well as in gastric cancer. Treatment with 5-aza-2'-deoxycytidine and/or trichostatin A reversed methylation and restored CBS mRNA expression indicating a direct effect. Aberrant methylation was further detected in 31% of primary CRCs (29 of 96) and 55% of gastric tumors (11 of 20). In contrast, methylation was seldom found in normal tissues adjacent to the tumor. CBS methylation was associated with KRAS mutations in primary CRCs . However, no association was found between CBS methylation or KRAS mutations with cancer relapse/metastasis in Stage II CRC patients.To identify potential TSGs silenced by aberrant promoter methylation in CRC, we analyzed tumor and adjacent tissues from CRC cases using the Illumina Human Methylation45 BeadChip. We identified hypermethylation of the CBS mRNA levels are frequently downregulated through CpG methylation of the CBS gene in gastric cancer and CRC, suggesting that CBS functions as a tumor suppressor gene. These findings warrant further study of CBS as an epigenetic biomarker for molecular diagnosis of gastrointestinal cancers.A novel finding from this study is that the folate metabolism enzyme  Both gastric and colorectal cancers are the most frequently occurring malignancies worldwide whose incidence has increased in recent years APC, MGMT, MLH1, INK4Ap16, VHL, RASSF1A, HIC1, CHFR, ADAMTS18, PCDH10 and DLEC1Inactivation of multiple tumor suppressor genes (TSG) is a key molecular event in the multi-step genetic pathogenesis of CRC cystathionine-beta-synthase (CBS) gene which encodes for a key enzyme in folate metabolism CBS was a new potential TSG and to test if CBS mRNA expression was downregulated by promoter hypermethylation in CRC, as well as in gastric cancer. We also investigated the potential role of CBS gene hypermethylation as a biomarker to predict tumor relapse or metastasis in stage II (T3N0M0) CRC patients.In the present study, we screened for TSGs silenced by aberrant promoter methylation in CRC and found hypermethylation of the This study was conducted in accordance with the Helsinki guidelines for human subjects studies and was approved by the Institutional Review Board of the Cancer Hospital, Chinese Academy of Medical Sciences (CAMS), Beijing, China. Signed informed consent was obtained from all study participants for sample collection and analysis.DNMT1 and DNMT3B  was a gift from Dr. Bert Vogelstein, Johns Hopkins University Four CRC  and 16 gastric cancer  cell lines were used 2 and subsequently stored at −80°C until processed. The diagnosis was confirmed through hematoxylin and eosin (HE)-staining and histopathological analysis was performed to define representative tumor regions. Clinical information was available for all CRC patients, including gender, age, differentiation, and follow-up data. The median age of CRC patients was 68 years (range 37–93), and male to female ratio was 1.4∶1 (56∶40). The number of well, moderate and poor-differentiation cases was 14, 56 and 26, respectively. Cancer staging (pTNM) was defined according to the 7th edition of American Joint Committee of Cancer 3N0M0).All primary samples including four paired fresh CRC and normal tissues, 96 primary formalin fixed paraffin embedded (FFPE) CRC tissues and 20 FFPE gastric cancer of tissues, were obtained from the Department of Pathology, Cancer Hospital, CAMS, Beijing, China. In addition, for methylation study, corresponding tumor-free margins from 20 gastric cancer and 17 CRC patients were analyzed. All patients did not undergo previous chemo- or radiotherapy since they presented with resectable tumors. Fresh specimens were snap-frozen in liquid NTotal RNA and DNA were extracted from cell lines using the TRI Reagent (Molecular Research Centre). For fresh tumor tissues, frozen sections were obtained and reviewed to make sure that tumor content was more than 80% of section area. DNA was extracted from fresh tissues and FFPE samples using the QIAamp® DNA Mini kit (Qiagen) following the manufacturer’s instructions.CBS were treated with 5 uM of 5-aza-2′-deoxycytidine (Aza) (Sigma) for three days and followed with 100 nM trichostatin A  for one day as described previously Two gastric cancer cell lines (YCC10 and SNU719) and one CRC (HCT116) cell line with silenced www.illumina.com. The results of the DNA methylation assay were compiled for each locus using the Illumina Bead Studio software (Illumina) and are reported as beta (β) values which are DNA methylation scores ranging from 0 to 1,reflecting the fractional DNA methylation level of a single CpG site All DNA specimens were subjected to bisulfite modification using the EZ DNA Methylation Kit (Zymo Research) according to the manufacturer instructions. One µg of genomic DNA from each sample was bisulfite converted and eluted in 18 µl elution buffer, and 5 µl of each sample was analyzed with the Illumina Infinium DNA methylation assay using the Human Methylation45 BeadChip , which is an allele-specific assay with 480,000 CpG loci covering the whole genome GAPDH as control. The primers for CBS are listed in RT–PCR was performed as described previously KRAS gene were examined using the Human KRAS Mutation Qualitative Detection Kit (ACCB Biotech Ltd.). Fluorescent probes were designed to specifically detect 7 different point mutations (G12V/S/R/D/A/C and G13D). The assay was carried out according to the manufacturer’s protocol using the MX3000P real-time PCR system (Stratagene). Presence or absence of mutations was assessed qualitatively from the fluorescence amplification curve.The seven hotspot mutations within codon 12 and 13 of Bisulphite modification of DNA was carried out as described earlier using 2.4M sodium metabisulphite 2 tests were used to analyze possible correlations between clinical parameters, KRAS mutation and CBS methylation status of tumor samples. All analyses were performed using SPSS for Windows. P<0.05 was considered statistically significant.χloci covering the whole genome. Among all CpG sites that were hypermethylated in tumor samples (data not shown), four CpG sites located were in the CBS gene  whereas low expression was in bone marrow tissue  of gastric cancer and 75.0% (3/4) of CRC cell lines  and two methylated gastric cancer (YCC10 and SNU719) cell lines were treated with Aza, a DNA methyltransferase inhibitor, and TSA. After treatment, CBS expression was restored in methylated cell lines along with a marked increase of unmethylated promoter alleles  and 55% of gastric tumors (11 of 20), but was infrequently found in normal gastric  or colon tissue  samples . These results suggest that hypermethylation of the CBS promoter is a common event in CRC and gastric cancers.We further investigated the presence of  samples . There wKRAS gene were examined in 96 primary CRC, where CBS methylation status was previously analyzed (KRAS mutation was detected in 45% (13/29) of CBS-methylated and 24% (16/67) of CBS-unmethylated primary CRCs indicating a positive correlation between CBS methylation and KRAS mutations (P<0.05). Further analysis showed no correlation of CBS methylation and KRAS mutation with cancer relapse/metastasis in stage II CRC patients  in CRC CBS 844ins68 polymorphism is associated with decreased survival in head and neck squamous cell cancer The gene CBS expression could lead to the accumulation of homocysteine, which will be recycled to methionine by methionine systhase via the remethylation pathway CBS expression may dysregulate DNA methylation. Our results revealed frequent methylation of CBS in gastrointestinal cancer cell lines and primary tumors. Thus, the suppression of CBS by promoter methylation, instead of genetic alterations, would also result in a disturbance of methyl-group metabolism and contribute to cancer development with increased DNA damage by oxidative stress, impairing antioxidant capacity, and dysregulating DNA methylation. However, CBS methylation was not associated with recurrence in our cohort of patients with stage II CRC. We suggest that larger cohorts of patients are necessary to study this potential association with sufficient statistical power.Furthermore, the loss of KRAS mutations in patients with CRC remains controversial. A study by Roth et al. suggested that the prognostic value for KRAS mutation status for PFS and OS was lacking in patients with stage II and III resected colon cancer KRAS mutations displayed significantly worse disease-free survival compared with those having wild-type KRASKRAS mutations at codon 12 from those at codon 13 with respect to clinicopathological features and survival KRAS mutation status as a prognostic factor for relapse or metastasis in patients with stage II resected CRC. Instead, we found that CBS methylation was significantly associated with KRAS mutations. This feature is in line with a previous report showing that CpG island methylator phenotype (CIMP) is associated with KRAS mutations The prognostic value of CBS is suppressed by promoter methylation in colorectal and gastric cancers. We found that the methylation-mediated silencing of CBS could be reversed by genetic or pharmacologic demethylation, suggesting that CBS functions as a tumor suppressor in these cancer types. The deregulation of CBS and its association with a malignant tumor phenotype is potentially associated to the crucial role of CBS in methionine metabolism and the maintenance of intracellular redox homeostasis. Our study warrants further analysis of CBS as an epigenetic biomarker for the molecular diagnosis of CRC and gastric cancer.In summary, the salient finding from this study is that


The relaxation response (RR) is the counterpart of the stress response. Millennia-old practices evoking the RR include meditation, yoga and repetitive prayer. Although RR elicitation is an effective therapeutic intervention that counteracts the adverse clinical effects of stress in disorders including hypertension, anxiety, insomnia and aging, the underlying molecular mechanisms that explain these clinical benefits remain undetermined. To assess rapid time-dependent  genomic changes during one session of RR practice among healthy practitioners with years of RR practice and also in novices before and after 8 weeks of RR training, we measured the transcriptome in peripheral blood prior to, immediately after, and 15 minutes after listening to an RR-eliciting or a health education CD. Both short-term and long-term practitioners evoked significant temporal gene expression changes with greater significance in the latter as compared to novices. RR practice enhanced expression of genes associated with energy metabolism, mitochondrial function, insulin secretion and telomere maintenance, and reduced expression of genes linked to inflammatory response and stress-related pathways. Interactive network analyses of RR-affected pathways identified mitochondrial ATP synthase and insulin (INS) as top upregulated critical molecules (focus hubs) and NF-κB pathway genes as top downregulated focus hubs. Our results for the first time indicate that RR elicitation, particularly after long-term practice, may evoke its downstream health benefits by improving mitochondrial energy production and utilization and thus promoting mitochondrial resiliency through upregulation of ATPase and insulin function. Mitochondrial resiliency might also be promoted by RR-induced downregulation of NF-κB-associated upstream and downstream targets that mitigates stress. The relaxation response (RR) is a physiological and psychological state opposite to the stress or fight-or-flight response The RR is elicited when an individual focuses on a word, sound, phrase, repetitive prayer, or movement, and disregards everyday thoughts Our previous study provided the first evidence that RR practice in healthy subjects at rest results in genomic expression alterations when comparing long-term RR practitioners to novices before and after their short-term RR training Regular daily practice of techniques that can be used to elicit the RR are often recommended for sustaining its beneficial effects. The immediate psychological and physiological effects from one session of RR-eliciting practice have been reported Our study design is composed of both prospective and cross-sectional features . The proThe long-term practitioners reported regularly practicing various RR-eliciting techniques including several types of meditation, Yoga, and repetitive prayer. They did not receive any intervention as part of this study. The novices received trainings in techniques to elicit the RR, which included 8 weekly individual training sessions from an experienced clinician in our research center. During the weekly session, subjects were guided through an RR sequence, including diaphragmatic breathing, body scan, mantra repetition, and mindfulness meditation, while passively ignoring intrusive thoughts. A 20-minute audio CD that guided listeners through this same sequence was given to the subjects to listen at home once a day We collected blood samples and biological measures when study subjects attended morning laboratory sessions, during which M and N2 listened to a 20-minute RR-eliciting CD and N1 listened to a 20-minute health education CD (control). Blood samples for gene expression profiling were collected immediately prior to (T0), immediately after (T1) and 15 minutes after (T2) listening to the respective 20-minute CD . FractioTotal RNA was isolated from the peripheral blood mononuclear cells (PBMCs) in the blood samples as described previously For transcriptional profiling, the Affymetrix human genome high throughput arrays plates with 96 arrays (HT U133A), containing more than 22,000 transcripts, were used. Scanned array images were analyzed by dChip Data analysis for identifying RR affected genes and gene sets was conducted first based on individual genes then on biologically related gene sets using a hierarchy of bioinformatics techniques described below and outlined in The individual gene analysis was implemented to identify differentially expressed genes based on intergroup  and intragroup  comparisons using a random-variance t-test. The random-variance t-test is an improvement over the standard separate t-test as it permits sharing information among genes about within-class variation without assuming that all genes have the same variance. For the comparison of N1 vs. M or N2 vs. M at any time point the unpaired univariate t-test was used. The paired t-test was used for the time dependence within each group or comparison of N1 group with N2 group. Genes were considered statistically significant if their p value was less than 0.01. P-values for significance were computed based on 1,000 random permutations, at a nominal significance level of each univariate test of 0.01. To extract temporal expression patterns of individual genes that showed significant time and group differences, we then adopted the Self Organizing Map (SOM) clustering technique p-value<0.05 were considered significant  The individual gene based analysis and SOM analyses are able to identify genes that depict large expression changes. However, subtle  gene expression differences in biologically- and functionally-linked genes in response to RR might be missed using these two approaches. To overcome this analysis shortage we adopted the popular Gene Set Enrichment Analysis (GSEA) which was originally developed by Mootha et al for the purpose of identifying genes involved in oxidative phosphorylation that are coordinately downregulated in human diabetes The genes from enriched pathways were merged into functional modules on the basis of overlap of significantly enriched genes using enrichment map plugin http://www.ingenuity.com/). It calculates the P value using Fisher Exact test for each network and pathway according to the fit of user's data to the IPA database To gain an insight about pathways of the differentially expressed genes and gene sets we analyzed interactive networks and pathways for different patterns identified from GSEA analysis of differentially expressed genes using the commercial system biology oriented package Ingenuity Pathways Analysis (IPA 4.0)  genes of pathways from various patterns and generated an integrated network using known Protein-Protein, Protein-DNA and Protein-RNA interactions were selected. The interaction information was obtained using literature search, information from knowledge base databases such as MIPS, DIPS, HPRD and ingenuity systems We performed transcriptional profiling analysis on all samples using the Affymetrix HT Human Genome U133A Array Plate. After stringent quality control analysis We next determined which differentially expressed genes were common to individual pairwise comparisons between groups . These common genes are shown as the intersecting areas of the Venn diagrams in Similarly, the within-group comparison identified a number of genes that were differentially expressed across the three time points within each group . The lonTo identify temporal gene expression patterns, we performed SOM analysis on all of the differentially expressed genes identified by the individual gene analysis above In contrast, a distinct set of genes exhibited Progressive Downregulation patterns that had highest gene expression values in N1, lower in N2 and the lowest in M at all three time points. Furthermore, only the M group showed a decreasing time trend in gene expression from T0 to T1 .We defined Long-term Upregulation patterns as those for which gene expression levels were elevated in M compared to both N1 and N2, for which there were few gene expression differences between the two at all three time points. Only the M group showed higher expression across the three time points as compared to N1 and N2 .Similarly, we identified Long-term Downregulation patterns that contain genes with expression lower in M than both N1 and N2. In addition, only the M group exhibited a decreasing time trend across the 3 time points in gene expression. These genes are significantly associated with regulation of apoptosis, nuclear transport, metabolic processes, JAK-STAT cascade, T- and B-cell activation, regulation of cell cycle, insulin sensitivity, glucose transport, DNA replication, chemokine signaling, EGF signaling, and stress response .While identification of gene expression differences and gene expression patterns based on individual-gene analysis described above is able to reveal a subset of statistically significant changes in gene expression, subtle  gene expression differences in biologically- and functionally-linked genes in response to RR might be missed in this analysis. Gene Set Enrichment Analysis (GSEA) is a statistical approach that identifies enrichment of sets of differentially expressed genes that share a common biological function or regulation We performed GSEA to identify enrichment of the statistically significantly affected gene sets that are associated with various pathways by comparing two groups at each time point as well as comparing changes across time points within each group. A False Discovery Rate (FDR) <25% was used to indicate significant group difference and a p value of <0.05 was used to indicate significant time difference. As previously, we categorized enriched pathways into 4 patterns based on the number of time points with group differences in gene set expressions: Progressive Upregulation, Progressive Downregulation, Long-term Upregulation and Long-term Downregulation. The progressive patterns were further categorized into Progressive I and Progressive II patterns on the basis of the similarity between M and N2 groups on genomic expression changes in comparison to N1.The Progressive I Upregulated pattern consisted of gene sets that were significantly enriched in both N2 and M subjects as compared to N1 subjects and with greater enrichments in M subjects at each time point   and insulin secretion pathways were also upregulated in M compared to N1 and N2, as indicated by the significant group differences at T0 and T1 and the relatively higher gene expression values shown in the heatmap  and T cell signaling pathways . The heaGSEA also identified pathways that had similar enrichments for M and N2 as compared to N1 where there was no significant difference between M and N2 at T0 and T1  as the top focus genes. These genes play a critical role in telomere stability and maintenance .Interactive network analysis on the 23 downregulated pathways with Progressive I pattern generated a complex network that consists of genes from pathways related to inflammation, immune response, T cell signaling and mRNA processing. Within this interactive network we identified many of the top 20 focus hubs of these pathways to be related to NF-κB activity including MAPK14, MYC, PTPKB2, TP53, and TRAF6 .The interactive network analysis on the 15 downregulated pathways with Progressive II pattern revealed a similar enrichment of NF-κB activity related focus molecules  . The intFinally, in an attempt to better understand the molecular mechanism of RR and to identify the most critical focus genes, we merged the Long-term and Progressive systems biology networks and investigated the focus hubs in this integrated network. The network of the top 20 focus hubs of this analysis clearly showed enrichment for NF-κB upstream and downstream target molecules   and idenTo evaluate whether changes of physiological or biological parameters acquired in the subjects before and after RR elicitation correlate with gene expression changes, we conducted correlation analysis on 10 selected pathways that were significantly affected by RR in Long-term or Progressive manner , S6 usinWe observed significant increases in FeNO level from T0 to T1 for M (p<0.01) and N2 (p<0.001), but non-significant increases in N1 . The FeNThese negative correlations indicate that RR mediated downregulation of IL7, immune response and NF-κB/stress activation related pathways (RELA Pathways) are linked to increases in FeNO levels. FeNO is known for its role in lowering blood pressure through vascular dilation Substantial research on mind-body interventions has established their ability to reduce chronic stress and enhance wellness through induction of the RR Analysis of the transcriptome data revealed that temporal modulation of gene expression occurred in both short- (N2) and long-term (M) practitioners as compared to novices (N1). Long-term RR practitioners exhibited more pronounced and consistent immediate gene expression changes as compared to short-term practitioners. Some genes were modified only in long-term practitioners (Long-term patterns), whereas others were modified in both short- and long-term practitioners with a greater intensity in the latter (Progressive patterns).Importantly, this study demonstrates that during one session of RR practice rapid changes in gene expression (on the order of minutes) are induced that are linked to a select set of biological pathways among both long-term and short-term practitioners that might explain the health benefits of RR practices. These genes have been linked to pathways responsible for energy metabolism, electron transport chain, biological oxidation and insulin secretion. These pathways play central roles in mitochondrial energy mechanics, oxidative phosphorylation and cell aging The GSEA findings are further supported by the results from our systems biology analysis, which identified insulin (INS) and ATP synthase subunit gamma (ATP5C1) as top focus hubs. The mitochondrial ATP synthase is critical in regulating the production of adenosine triphosphate (ATP), which in turn is a key determinant for secretion of insulin from β-cells in response to glucose. Mutations in ATP synthase leading to its impaired signaling have been shown to induce oxidative stress and impaired insulin secretion in β-cells Gene sets identified by GSEA as progressively downregulated by RR practices are linked to pathways that play critical roles in the inflammatory response, including those connected with the pro-inflammatory transcription factors NF-κB and RELA, and TNFR2, IL7 and TCR signaling. Systems biology analysis identified NF-κB associated molecules  as top focus hub genes. Downregulation of NF-κB inflammatory response gene sets may lead to reductions in oxidative stress, insulin resistance and apoptosis Finally, NF-κB activation in PBMCs has been shown to correlate with peripheral levels of oxidative stress and can be reduced by therapeutic interventions that decrease oxidative stress Long-term RR practice, moreover, upregulated pathways associated with genomic stability such as telomere packing, telomere maintenance and tight junction interaction. Telomere dysfunction can cause disruption of mitochondrial regulators and cause mitochondrial compromise that ends in apoptosis Systems biology analysis identified histone (HIST1H2BC), calcium channel (CACNA1C) and cytochrome C (CYC1) among top focus hubs of the Long-term Upregulated pathways. HIST1H2BC is a core component of the nucleosome and is thereby essential to transcriptional regulation, DNA repair, DNA replication and chromosomal stability. Cytochrome C is an important member of the mitochondrial respiratory and energy production complex that again may provide an insight into the role of RR in mitochondrial energy efficiency. CACNA1C, a calcium channel gene, mediates the entry of calcium ions into excitable cells and is also involved in a variety of calcium-dependent processes, including muscle contraction, hormone and neurotransmitter release, gene expression, cell motility, cell division and cell death.Similarly, pathway enrichment and systems biology analysis on long-term RR downregulated genes revealed associations with pathways involved in immune response , apoptosis  and stress response . Psychological effects on PBMC gene expression associated with DNA repair mechanisms and immune response have been observed in women with postpartum depression, thus linking psychological stress to deregulated immune function and DNA repair that could be impacted by RR In summary, we conducted the first study to employ advanced genomic analysis methodology and systems biology analysis to examine temporal transcriptional changes during one session of RR practice and found that RR practice induced upregulation of ATPase and insulin function. This suggests that RR elicitation may enhance mitochondrial energy production and utilization. At the same time RR induced downregulation of NF-κB-dependent pathways, with effects on upstream and downstream targets that may mitigate oxidative stress. These findings, while preliminary, suggest that RR practice, by promoting what might be called mitochondrial resiliency, may be important at the cellular level for the downstream health benefits associated with reducing psychosocial stress. Mitochondria have evolved the capacity to modulate specific anabolic and catabolic circuitries that control programmed cell death and autophagocytosis. They also confer an ability to sense the intracellular environment and help the cell adapt to a variety of stressors mitochondrial resiliency or mitochondrial reserve capacity. The gene expression data indicate the RR specifically upregulates energy production of ATP through the ATP synthase electron transport complex. This might result in an enhanced mitochondrial reserve providing the capacity to meet the metabolic energy demands required to buffer against oxidative stress that emerges in many stress related diseases. Depending on variables such as genetic endowment and epigenetic interactions with micro- and macro-environmental circumstances, different mitochondria will have variable capacities to dampen the pathogenic effects of oxidative stress, and this has sometimes been referred to as differential mitochondrial reserve capacityThe RR significantly affects multiple pathways through mitochondrial signaling that may promote cellular and systemic adaptive plasticity responses. In essence these adaptive responses become markers of what might be called Our findings provide a framework for further deciphering the in-depth molecular pathways associated with the clinical benefits of the RR. To confirm this molecular mechanism of RR, validation of the results using secondary biochemical testing will be necessary.Figure S1Schematic view of temporal relaxation response study design and analysis plans. The transcriptome profiling was performed on peripheral blood mononuclear cells (PBMCs) collected immediately prior to (T0), immediately after (T1) and 15 minutes after (T2) listening to a 20-minute Education CD by the Novices (N1) or a 20-minute RR CD by the Short term practitioners (N2) and the Long term practitioners (M). The global transcriptome of PBMCs was profiled using HT_U133A arrays containing >22,000 transcripts. The transcriptome data were analyzed using high-level bioinformatics algorithms to identify differentially expressed transcripts, significantly affected pathways and systems biology networks that are related to RR elicitation. The expression patterns were generated from differentially expressed genes using Self- Organizing Maps (SOM) analysis. The results of the GSEA from all comparisons were classified to temporal patterns  by developing a Rlanguage script.(PDF)Click here for additional data file.Figure S2Temporal genomic expression patterns during one session of RR elicitation. Genes that were differentially expressed either across or within groups comparisons at different time point were used as seed sets of genes for Self-Organizing Map (SOM) analysis. These differentially expressed genes were partitioned to 18 separate maps according to Pearson correlation coefficient based distance metrics. Each pattern represents a set of genes that depict a similar expression pattern suggesting that they are biologically linked to a specific function. The figure displays the box plot of the gene expression with X-axis representing time points and groups, and Y-axis representing scaled gene expression data from −1 to +1. The patterns are merged into 10 expression categories on the basis of similarities in expression patterns.(PDF)Click here for additional data file.Figure S3Interactive Network of progressively (Progressive II) upregulated genes. The network was generated from genes of 27 progressively upregulated pathways (Progressive I) related to energy production, metabolism, growth factors and glucose regulation. The interaction information about the genes was obtained from public interaction databases or the commercial Ingenuity package. In a network each node represents a gene and an edge represents an interaction . The nodes with high degree of connectivity (Top 20) are highlighted in yellow color.(PDF)Click here for additional data file.Figure S4Interactive network and focus hubs of genes depicting Longterm Upregulation patterns. A) Interactive network, B) Top 20 focus genes. The interactive network and focus hub identification analysis was performed on genes from 14 Long-term Upregulated pathways linked to DNA stability, recombination and repair. In the network each node represents a gene and an edge represents an interaction. The focus gene hubs were identified using the bottleneck algorithm for identification of the most interactive molecules with a tree like topological structure. The bottleneck algorithm ranks genes on the basis of significance level with smaller rank indicating increasing confidence. The pseudocolor scale from red to green represents the bottleneck ranks from 1 to 20 .(PDF)Click here for additional data file.Figure S5Interactive network and focus hubs of genes depicting acute Progressive (Progressive II) Downregulation patterns. The interactive network and focus hub identification analysis was performed on genes from 15 Progressively Downregulated (Progressive I) pathways linked to mRNA processing and immune response. The focus gene hubs were identified using the bottleneck algorithm for identification of the most interactive molecules with a tree like topological structure. The bottleneck algorithm ranks genes on the basis of significance level with smaller rank indicating increasing confidence. The pseudocolor scale from red to green represent bottleneck ranks from 1 to 20.(PDF)Click here for additional data file.Figure S6Top focus gene hubs identified from Interactive networks of significantly affected Long-term Downregulated pathways. The figure represents the top 20 focus genes identified from complex interactive networks generated from pathways with Long-term Downregulated patterns. The focus gene hubs were identified and ranked using the bottleneck algorithm for identification of the most interactive molecules with a tree like topological structure. The pseudocolor scale from red to green represent bottleneck ranks from 1 to 20 .(PDF)Click here for additional data file.Table S1Gene—ontology enrichment analysis of progressive and long—term expression patterns.(PDF)Click here for additional data file.Table S2FeNO levels during one session of RR elicitation.(PDF)Click here for additional data file.Table S3Correlation analysis of NO levels and Selected 10 pathways affected progressively or only in long term manner by RR (Bold). The correlation analysis was performed both by comparing FeNO and gene expression levels at particular time point  as well as changes in gene expression and FeNO levels within a group. The significance of the correlation was determined on the basis of P value (P<0.05) and FDR (<25%). The positive and negative correlations between FeNO and gene expression levels are indicated by red and green color respectively.(PDF)Click here for additional data file.Text S1Supporting Information(PDF)Click here for additional data file.


Single voxel proton magnetic resonance spectroscopy (MRS) can be used to monitor changes in brain inflammation and neuronal integrity associated with HIV infection and its treatments. We used MRS to measure brain changes during the first weeks following HIV infection and in response to antiretroviral therapy (ART).Brain metabolite levels of N-acetyl aspartate (NAA), choline (tCHO), creatine (CR), myoinositol (MI), and glutamate and glutamine (GLX) were measured in acute HIV subjects (n = 31) and compared to chronic HIV+individuals (n = 26) and HIV negative control subjects (n = 10) from Bangkok, Thailand. Metabolites were measured in frontal gray matter (FGM), frontal white matter (FWM), occipital gray matter (OGM), and basal ganglia (BG). Repeat measures were obtained in 17 acute subjects 1, 3 and 6 months following initiation of ART.p = 0.0014), as well as chronic subjects (p = 0.0023). A similar tCHO/CR elevation was noted in OGM; no other metabolite abnormalities were seen between acute and control subjects. Mixed longitudinal models revealed resolution of BG tCHO/CR elevation after ART (p = 0.022) with tCHO/CR similar to control subjects at 6 months.After adjustment for age we identified elevated BG tCHO/CR in acute HIV cases at baseline (median 14 days after HIV infection) compared to control (We detected cellular inflammation in the absence of measurable neuronal injury within the first month of HIV infection, and normalization of this inflammation following acutely administered ART. Our findings suggest that early ART may be neuroprotective in HIV infection by mitigating processes leading to CNS injury. Infection with human immunodeficiency virus-1 (HIV) remains a major health issue affecting 34 million people worldwide, with 2.7 million new infections reported in 2010 Infection and inflammation of the CNS is linked to neurological and cognitive findings in chronic HIV. Cerebrospinal fluid (CSF) HIV RNA levels are more valuable in predicting neuropsychological testing impairment 6 months following initiation of ART than are plasma HIV RNA levels, CD4+lymphocyte counts, or Centers for Disease Control and Prevention disease stage classification 1H-proton magnetic resonance spectroscopy (MRS) measures signals from hydrogen atoms specific to the molecular structure of the metabolite in which they are contained. Brain MRS studies can document the extent of inflammation underlying HIV, disease progression and treatment response. Neurons can be distinguished by the relative level of N-acetyl-aspartate (NAA), because it is synthesized within the brain almost exclusively by neurons from aspartate and acetyl coenzyme A Non-invasive The primary goal for this study was to examine brain MRS metabolites during the first month of HIV infection. We sought to define the extent of brain parenchymal inflammation and neuronal injury and to examine changes in these metabolites after initiation of ART during acute HIV.This study investigated the first 40 enrollees of the RV 254/SEARCH 010 protocol, an ongoing study characterizing acute HIV infection in Bangkok, Thailand . All cases were enrolled during Fiebig stages I-IV, the earliest stage of HIV infection before appreciable antibody response can be detected and typically less than one month after exposure. Details are provided elsewhere Immediately after enrollment and baseline MRI/MRS, 29/31 participants started ART composed of efavirenz (EFV), tenofovir (TNF), and emtricitabine (FTC) (standard ART). Eighteen of these subjects also started raltegravir (RAL) and maraviroc (MRC) (“mega-ART”). Efavirenz was discontinued in 9 cases due to intolerance (n = 7) or primary drug resistance (n = 2). Among these, only two cases were on standard ART, and the efavirenz was replaced with raltegravir. Seventeen subjects who completed all follow-up MRS  were evaluated to investigate treatment response.The studies were approved by institutional review boards in Thailand  and in the U.S. . All participants signed written consent.Twenty-six ART-naïve chronically infected HIV+Thai subjects  and 10 HIV-negative Thai controls  were analyzed for comparison. All controls and chronically infected subjects were deemed to have normal cognition after neuropsychological testing and multi-disciplinary consensus conferences, which included a neurologist and a neuropsychologist, met the same exclusion criteria as the acute subjects, and were free of opportunistic infection. All subjects underwent one-time (baseline) MRS using the same protocol on the same scanner with no interim software or hardware upgrades and captured by the same technician (MP).Lymphocyte subsets were measured at a local clinical laboratory and plasma HIV RNA levels were measured in fresh specimens by Roche Amplicor HIV-1 Monitor Test v1.5 with dilution for HIV RNA>750,000 copies/ml.o, with 1 mm voxel resolution) MRI scan on a GE Signa HDx 1.5T clinical scanner  using an 8-channel head coil for data reception and a standard body coil for transmission. Single voxel MRS was acquired using a double spin echo data acquisition (PROBE-P) with TE = 35 ms, TR = 1.5s at four voxel locations: left frontal white matter , midline frontal grey matter , occipital grey matter  and basal ganglia . Briefly, time domain MRS data from each coil of the 8-channel phased array head coil were combined using unsuppressed water FIDs from each coil as scaling factor in vivo. The reference solutions were 50 mM NAA, 50 mM CHO, 100 mM GLU, 100 mM GLN, 100 mM CR, and 150 mM MI. All reference solutions were adjusted to pH 7.2 with 0.1 M NaOH. Metabolite quantification for NAA, CR, tCHO, MI, and GLX were included only if the signal to noise ratio was>4 and their percent standard deviations were<20% Data were transferred by secured protocol to the central processing location at Huntington Medical Research Institutes in Pasadena, CA where two authors (NS and WR) processed all data using the time domain linear combination fitting software, LCModel  and Tukey procedure for pairwise comparisons. We analyzed the main effect of acute and chronic HIV on metabolites using general linear model multivariate analyses of variance (MANOVA). We completed multivariate analyses using Pillai’s Trace tests for each voxel including the three groups as predictors and the four metabolites of interest  as responses. For voxels where we rejected the joint null hypothesis of no effect of acute, chronic and control groups on the responses at p = 0.05, we then examined the individual metabolite levels within those models. Voxels for which we did not reject the null hypothesis were not investigated further. For voxels for which the null hypotheses were rejected, further analyses compared the metabolites among the different groups using ANOVA. In all models, CR and age were included as covariates. Although mean educational attainment and gender differed among groups, they were not included in the primary models since our main analyses compared acute cases to controls and since age and CR were more important to covary than was education and gender, each was felt less likely to appreciably impact MRS. Secondary analyses included education.For the acute HIV+group, we used Spearman’s correlation to evaluate the relationship between MRS data and clinical variables. We evaluated MRS changes over time using mixed models with a complete case analysis approach. The 6-month metabolite ratios were compared to the cross-sectional HIV-negative control ratios to assess for normalization of values associated with treatment.+lymphocyte count and plasma HIV RNA level were lower for the chronic HIV group . The HIV subtypes were identified to be CRF01_AE (n = 25) and B (n = 1) with 5 cases that could not be typed.The 31 acute HIV+subjects were at Fiebig stages I (10); II (3); III (15); and IV (3) at the time of MRS with a median (range) estimated duration since exposure of 14 (1–32) days Table 1.A total of 133 MRI/MRS examinations were performed on 67 subjects over a period of 32 months (from December 2008 to May 2011). We observed low percent coefficient of variation of phantom metabolite concentrations  reflecting hardware stability and an ability to reliably detect changes in metabolite ratios of 2–4%.p = 0.002) and OGM (p = 0.037) for further investigation (p = 0.001) and compared to chronic groups . NAA/CR did not differ compared to controls although it was higher than that measured in the chronic group . In OGM, we similarly noted elevated tCHO/CR in acute compared to control groups . We also identified higher GLX/CR in the acute compared to chronic groups , but no significant differences between GLX/CR in control subjects and either HIV group. We did not include education in our primary models due to the small sample size; however, repeated analyses that included education did not appreciably alter these findings. Voxels at FWM and FGM were not evaluated as they did not meet scrutiny of our statistical approach. Secondary explorations in these voxels did not suggest missed findings.Our statistical approach identified voxels at BG . We did not identify associations with estimated duration of infection. Patients with Fiebig III/IV had significantly increased BG NAA/CR after adjusting for age, as compared to patients with Fiebig I/II . No other correlations were identified in relation to Fiebig stage.Multivariate models within the acute group identified a relationship between CSF HIV RNA and metabolites in FWM only. Examining individual metabolites at this voxel, we identified a direct association between logβ = −0.002/month, p = 0.022) and MI/CR at OGM . Increased NAA/CR was noted in FGM , FWM  and OGM  longitudinally. Most of these changes were temporally related to initiation of treatment with large changes at month 1 and lesser changes thereafter  of HIV infection. Our findings extend existing knowledge of brain involvement through CSF analyses by demonstrating abnormalities within brain tissue itself. In our work, the MRS inflammatory signature normalized after ART that included medications with high  CNS penetration-effectiveness, based on cerebrospinal fluid studies. We noted no detectable differences seen in comparison to control subjects. The metabolite primarily altered was CHO, thought to reflect reactive cell turnover as it is closely correlated to membrane lipids Unexpectedly, we noted a rise in NAA/CR in several brain regions associated with treatment. Despite this finding, neither the baseline nor the six-month NAA/CR ratios differed in the acute compared to control groups. Recognizing the risk that the trend could be an artifact of using CR as a standardizing metabolite, we subsequently evaluated NAA concentrations (uncorrected for T1 and T2 relaxation times) at these voxels, confirming a rise of NAA at BG but not at other locations. Since neither NAA nor NAA/CR differed from that of control subjects at any time point, the clinical significance of this finding may be less important and speculation regarding etiology premature. Our study design was limited by having control subjects imaged only once (baseline) with our comparison to acute cases who were imaged longitudinally.We did not identify a decrease in markers of neuronal injury in early HIV. Our study subjects were imaged substantially earlier than those included in a prior report demonstrating reduced NAA/CR ratios in early infection in which subjects were enrolled up to 90 days after Western blot evidence of infection The differences observed in NAA/CR and GLX/CR between acute and chronic groups is likely related to smaller bidirectional alterations in both acute and chronic groups relative to the control group, although, this is speculative since no statistically significant differences to controls was identified in either group. In contrast, a reduction of glutamate has been observed in cognitively normal chronic HIV+subjects and in other studies of early HIV, but with similar caveats that the timing was later than that accomplished in our study, and effects of variable ART use cannot be excluded Similar to our longitudinal CHO data, a small decrease in MI/CR was noted in OGM after treatment. Here, however, neither baseline nor follow-up values differed statistically from that of our control group. Elevated MI has been observed in cognitively impaired HIV+subjects during the chronic stage of infection Our observations support the hypothesis that immune cellular infiltration and turnover characterizes the brain during the earliest stage of HIV infection, providing an early conduit for brain parenchymal viral seeding In this work, the duration of HIV and Fiebig stage did not appreciably predict levels of MRS metabolites. In FWM, CSF HIV RNA level correlated to higher GLX/CR, but we did not identify associations for any other voxel/metabolite pair. Together, these findings suggest that the inflammation noted during acute HIV is likely not dependent on the level of systemic antibody response, and that CSF HIV RNA may correlate with release of neurotoxins in the brain but otherwise is independent of brain inflammation in this early period.We had anticipated that the largest metabolic changes would be seen in BG and FWM based on the known higher frequency of detection of HIV antigen in these regions at autopsy in chronic HIV without treatment In conclusion, this study identified indirect evidence for brain parenchymal cellular infiltration in the absence of neuronal dysfunction or gliosis during the first month following HIV infection. We further found that this process is not present following 6 months of ART initiated immediately after diagnosis. Our findings highlight a potential pathway for early seeding of HIV and initial steps toward establishment of latent viral reservoirs in CNS, and suggest that early ART may be neuroprotective as a means to prevent neuronal injury and ameliorate brain inflammation.


Ficus awkeotsang Makino) is an edible component of a popular drink consumed in Asia. Hepatitis B virus (HBV) infection is prevalent in Asia, and current treatments for HBV infection need improvement. This study aimed to evaluate the effect of PEI on the surface antigen expression by HBV (HBsAg). Human hepatoma cell lines Hep3B and Huh7 served as in vitro models for assessing the cytotoxicity and HBsAg expression. A culture of primary hepatocytes cultured from mice served as the normal counterpart. Cell viability was measured by 3--2,5-diphenyltetrazolium bromide (MTT) colorimetric assay. HBsAg expression was evaluated by measuring HBsAg secretion into the culture medium using an enzyme-linked immunosorbent assay. The results showed that PEI did not affect the viability of the human hepatoma cell lines or primary mouse hepatocytes. PEI inhibited the expression of HBsAg in hepatoma cell lines harboring endogenous (Hep3B) and integrated (Huh7) HBV genomes in a concentration- and time-dependent manner, thus implicating a universal activity against HBV gene expression. In conclusion, it suggests that PEI from jelly fig inhibits the expression of human HBsAg in host cells without toxic effects on normal primary hepatocytes.Pectinesterase inhibitor (PEI) isolated from jelly fig ( The HBsAg secreted in the culture medium was measured using a commercial enzyme-linked immunosorbent assay (ELISA) kit . The optical density values determined using ELISA were normalized with the cell viability. The detection of HBsAg in the sera of patients indicates an existing HBV infection and the risk of developing cirrhosis and hepatocellular carcinoma. Thus, HBsAg is a useful index for evaluating viral activity . The relt-test or ANOVA test. Statistical analyses were performed using the Statistical Package for the Social Sciences software package, v18.0 , and a P value of <0.05 was considered significant. Results are presented as mean ± SEM. Differences among the treatment groups were assessed by Student's μg/mL) for 48 h and then subjected to MTT assay. As shown in Figures μg/mL did not significantly affect the cell viability of Hep3B and Huh7 cells, respectively. Therefore, the biological activity of PEI in these cells was probably not due to cellular toxicity.  To determine the cytotoxicity of PEI on the human hepatoma cells, Hep3B and Huh7 cells were treated with various concentrations of PEI  for 48 h in serum-free medium after serum starvation. The culture medium was then harvested and the amount of HBsAg was measured by ELISA. As shown in Figures μg/mL of PEI in Hep3B and Huh7 cells, respectively  was also demonstrated in Hep3B and Huh7 cells, as shown in Figures To examine the relative expression levels of HBsAg in human hepatoma cells exposed to PEI. Hep3B and Huh7 cells were treated with different concentrations of PEI  for 48 h and then subjected to MTT assay. As shown in  Primary cultured hepatocytes isolated from BALB/c mice served as a normal counterpart for assessment of PEI toxicity in normal tissue. Normal hepatocytes were treated with various concentrations of PEI  with 57% basic amino acids, which inhibited the intrinsic carambola PE activity required for methanol reduction in wines . It is u The experimental models tested in this study comprised Hep3B cells that harbored endogenous HBsAg and a stable clone of HBV DNA-integrated Huh7 cells. PEI inhibited HBsAg expression in both cell lines, indicating its universal activity against HBsAg expression. However, this experimental model only provides a screening platform for anti-HBV agents . Further Normal liver toxicity assessment based on the in vitro hepatocyte viability showed no evidence of PEI hepatotoxicity. Currently used anti-HBV agents have various levels of toxicity , which f In clinical practice, chemotherapy-related HBV reactivation and subsequent fulminant failure is not rare in HBV-infected patients , 16. TheIn conclusion, PEI isolated from jelly fig may inhibit human HBsAg expression in host cells without any toxic effects on normal hepatocytes.


Plasmodium falciparum is responsible for the most severe form of malaria in humans. Antigenic variation of P. falciparum erythrocyte membrane protein 1 leads to immune evasion and occurs through switches in mutually exclusive var gene transcription. The recent progress in Plasmodium epigenetics notwithstanding, the mechanisms by which singularity of var activation is achieved are unknown. Here, we employed a functional approach to dissect the role of var gene upstream regions in mutually exclusive activation. Besides identifying sequence elements involved in activation and initiation of transcription, we mapped a region downstream of the transcriptional start site that is required to maintain singular var gene choice. Activation of promoters lacking this sequence occurs no longer in competition with endogenous var genes. Within this region we pinpointed a sequence-specific DNA–protein interaction involving a cis-acting sequence motif that is conserved in the majority of var loci. These results suggest an important role for this interaction in mutually exclusive locus recognition. Our findings are furthermore consistent with a novel mechanism for the control of singular gene choice in eukaryotes. In addition to their importance in P. falciparum antigenic variation, our results may also help to explain similar processes in other systems. Borrelia spp., Neisseria spp., Giardia lamblia, Plasmodium falciparum and Trypanosoma brucei, this paradigm of clonal phenotypic variation reaches a remarkable yet poorly understood level of sophistication  on the RBC surface  in ring-stage parasites during the first half of the IDC   and demonstrated its exclusive localization to the active var locus suggesting a role for this enzyme in the transmission of epigenetic memory  that is essential for var promoter activation. Notably, we also identified a region downstream of the transcriptional start site (TSS) and demonstrate an important role for this element in mutually exclusive promoter recognition. In absence of this sequence var promoters are fully active but, unlike wild-type promoters, do not compete with endogenous var gene transcription. Within this region we identified a 47 bp motif that interacts in a sequence-specific manner with an unknown nuclear protein. Together, our results show for the first time that the complex regulation of mutually exclusive var gene transcription involves functional cis-acting modules with intrinsic and position-dependent activities. They are furthermore consistent with a novel mechanism in sustaining singular gene choice in eukaryotes.We postulated that transcriptional control of var promoter elements we employed a system suitable to analyse promoter activity in stably transfected parasites. All reporter constructs are based on the parental plasmid pBC (bsd) resistance cassette selects for stable episomes. A 2.5 kb var upsC upstream sequence (PFL1960w) controls transcription of the dual reporter encoding human dihydrofolate reductase fused to green fluorescent protein (hdhfr-gfp). A var gene intron element is located downstream of the hdhfr-gfp cassette to account for its role in var gene regulation. A telomere-associated repeat element 6 sequence (TARE6/rep20) is included for improved plasmid segregation . As shown in var promoter activity. The promoter in pBC5, lacking 491 bp of the 5′ UTR, was also fully active. In contrast, the truncation encompassing bps −1057 to −1 in pBC4 caused a significant reduction in steady-state transcript levels. Hence, this approach identified two regulatory regions, located upstream and downstream of the putative TSS, respectively, which fulfil important roles in var promoter function.To identify elements involved in promoter activation and mutual exclusion we sequentially truncated the upsC upstream sequence from either the 5′ or 3′ end B. We chokahrp) gene promoter for three reasons. First, the TSS of this gene has been mapped to 849 bp upstream of the ATG  (min). qRT-PCR analysis revealed that upsC fragments C1 (−1679 to −1200) and C2 (−1401 to −727) consistently activated Kmin to a similar extent in both the episomal and chromosomal context whereas fragment C3 had no effect. Furthermore, neither the var intron nor the rep20 element altered Kmin activity. Together, these findings corroborate the results obtained with the upsC deletion constructs and are consistent with the presence of a var UAS located between bps −1401 and −1217. The fact that this element activates transcription from a heterologous minimal promoter suggests an autonomous, context-independent function in activating RNA polII-mediated transcription.We cloned two overlapping fragments containing the putative upsC UAS upstream of KBC2Kmin) D and S1.BC2Kmin) B, was usHere, we investigated the functional region downstream of the putative TSS that is defined by plasmids pBC4 and pBC5 (−1057 to −491). Deletion of this region caused a substantial reduction in steady-state transcripts B, suggesvar promoters do not transcribe endogenous var genes and fail to express PfEMP1  in electromobility shift assays (EMSA) using parasite nuclear extracts. Whereas MEE1 and MEE3 showed no sign of specific binding (data not shown), the central 47 bp MEE2 fragment formed a DNA–protein complex that was specifically competed in a dose-dependent manner by an excess of homologous competitor only A. To chavar genes. We inspected all var upstream sequences (−600 to −1 relative to the start ATG) and identified a perfect or slightly deviated MEE2 core motif with the consensus sequence (A/T)(A/T)(A/T)GA(T/A)TA in 44 (73%) out of all 60 var genes. Strikingly, in all but four cases this motif (i) is conserved in terms of orientation and position relative to the ATG start codon, (ii) is embedded in an overall highly similar sequence context including a characteristic poly-dT stretch, and (iii) occurs in upsB-, upsC-, upsB/C- and upsB/A-type var genes (var gene (PF07_0048), in which six nucleotide positions are changed compared with MEE2 including one substitution in the core motif, competed as efficiently as the wild-type MEE2 motif (var gene (PFL0005w), in which 19 positions are altered including two in the core motif, competed albeit with lower efficiency (var upsA (PFD1235w) and a var-unrelated rif (PFB0035c) upstream region, in which an AT(A/T)GATTA core motif is present at the same relative position as in MEE2, failed to inhibit formation of the MEE2–protein complex  also binds to related motifs found in a large proportion of T. brucei, the causing agent of African sleeping sickness, mutually exclusive transcription of variant surface glycoprotein genes is carried out by an extranucleolar RNA polI-containing body  to a cis-acting sequence motif present in this region (MEE2) corroborates this hypothesis and suggests an important role for this DNA–protein interaction in mutually exclusive promoter activation. The presence of MEE2-related motifs in a large subset of var genes provides circumstantial evidence for a conserved mechanism of singular var gene choice. Although the exact function of this interaction remains to be discovered, binding of MIF to the mutual exclusion element may earmark var loci for mutually exclusive activation. Additional experiments tailored towards identifying MIF and dissecting the exact function of this interaction in var regulation are now required to test this hypothesis. In this context it is worth mentioning that the 47 bp MEE2 sequence does not contain any obvious ApiAP2 transcription factor-binding motifs  . RNA was glyoxylated for 1 h at 55°C in five volumes glyoxal reaction mixture and electrophoresis was performed using 1× BPTE-buffered 1.5% agarose gels  was performed on whole-cell lysates. Primary antibody dilutions were: mouse anti-GFP , 1:500; mouse anti-GAPDH 1-10B (kind gift of Claudia Daubenberger), 1:20 000. PfEMP1 was extracted from trophozoite-infected RBC pellets (Triton X-100-insoluble/SDS soluble fraction) as described (van Schravendijk et al., High-salt nuclear extracts and EMSAs were prepared and carried out as described (Voss