Extracellular ATP, a co-transmitter in adrenergic and cho- linergic synapses, has several functions in the central and peripheral nervous systems (17, 18). In addition, autocrine/ paracrine ATP signaling occurs in many cell types (epithelium, endothelium, fibroblasts, etc.) that release nucleotides (ATP, UTP) to the extracellular medium under resting conditions and after physiopathological events, such as hypoxia, cell swelling, shear stress, or inflammation, through nonlytic mechanisms (19, 20). Depending on the cell type, ATP release by exocytosis or through ABC transporters, stretch- and voltage-activated channels, or connexin hemichannels has been described (19 – 21). Recently, pannexin (Pnx) hemichannels have also been proposed as relevant ATP conduits (22, 23). The ATP (or UTP) released is quickly metabolized to the di- and monophosphate nucleotides through ectonucleotidases located at the cell sur- face or the extracellular matrix. Finally, they are converted into nucleosides to be recaptured by cells (24). ATP, UTP, and their metabolites have been implicated in the regulation of physio- logical processes such as epithelial secretion, vascular tone, platelet aggregation, pain sensitivity, and actions as trophic fac- tors (20, 25–29).
Sepsis is one of the oldest and most complex syndromes in medicine and a common disease with high mortality. Although the treatment of sepsis has attracted attention from people, it still has a high mortality rate. Recent research has focused on exploring the association of genes between lethal sepsis and nonfatal sepsis, while the association mechanism remains unclear. In this study, we explored different expression patterns of genes in lethal sepsis and non-fatal sepsis by analyzing geneexpression data sets for lethal sepsis and non-fatal sepsis. As a result, genes up- and down-regulated representative expression pattern in both sepsis while genes and functional levels have opposite phenomena. In non-fatal sepsis, genes down-regulated in lethal sepsis are involved in Toll-like receptor signaling pathways, biologically related processes such as negative regulation of immune responses, and signaling pathways like protein processing in the endoplasmic reticulum. In non-fatal sepsis, genes up-regulated in lethal sepsis are involved in the regulation of the actin-based process, regulation of glucose import, biological processes like protein K48 linked to ubiquitination, and signal processing such as viral myocarditis as well as antigen processing and introduction. In conclusion, our results provide a framework for a comprehensive analysis of the expression patterns of lethal sepsis and non-fatal sepsis to determine effective molecular characteristics for clinical use. Keywords: lethal sepsis, non-fatal sepsis, genes, biological processes, signaling pathways
Here we combine three high-resolution data sets - RNA sequencing, tiling expression microarray, and RNA pol ChIP sequencing - to present a characterization and analysis of the S. elongatus transcriptome. We report absolute transcript levels, operon identification, and high-resolution mapping of 5′ and 3′ transcript ends. At the 5′ end of transcripts, we characterize promoter sequence and find widespread peaks in RNA pol occupancy. At 3′ ends we observe significant Rho-independent transcription termination and occasional incomplete termination resulting in interesting transcriptional structures. In addition, we find extensive non-coding transcription, suggesting a larger role for these non-coding RNAs in bacteria, and cyanobacteria in particular, than previously anticipated. The presence of numerous non-coding RNAs and 5′ proximal pausing of RNA pol suggest that post-transcriptional regulation - regulation after binding of RNA pol at the promoter - may be more widespread in bacteria than expected. We hope this work will serve as a catalog and primer for further studies of bacterial and cyanobacterial transcription.
down-regulated, p value <0.05) are listed. Obviously, a larger number of genes was affected by the imposed nutrient limitation than by the growth rate (Table 4). Genes, belonging to pathways involved in energy produc- tion and conversion, carbohydrate transport, synthesis of amino acids, nitrogen scavenging, PHA synthesis, cellu- lar processing, and transcriptional regulation were most affected by the type of limitation (N-limiting vs. C-lim- iting conditions) (Table 4). On the other hand, several genes encoding proteins related to energy metabolism, transporters DNA and RNA repair and synthesis and also putative functions were differentially expressed, when P. putida KT2440 was challenged to different specific growth rates on glycerol. Remarkably, genes encoding signal modulators were highly overexpressed, when shift- ing from carbon to nitrogen limitation, independently of the set growth rate. A sensor hybrid histidine kinase PAS/PAC (PP_2664) and an integral membrane sensor (PP_2671) showed the highest change in geneexpression level, which was more than 30-fold. PAS domains are important elements that sense both, fluctuation of signals in the environment and the overall energy level of the cell . In addition, the LuxR (PP_2672) master gene regu- lator displayed a high expression level, as also did genes, allocated downstream of PAS/PAC (PP_2065-2069). Up- regulation of PAS and LuxR genes is likely related to the energetic state of the cell, as N-limiting cultures promote not only accumulation of PHAs, but also interactions between PAS domains and electron transport systems . High yields of PHA diminish intracellular level of ATP  and to increase the NADH/NAD+ ratio [15, 43]. Table 3 Monomer composition of medium chain length
In the present work we extend and analyze the scope of our recently proposed stochastic model for transcriptional regulation, which considers an arbitrarily complex cis-regulatory system using only elementary reactions. Previously, we determined the role of cooperativity on the intrinsic fluctuations of geneexpression for activating transcriptional switches, by means of master equation formalism and computer simulation. This model allowed us to distinguish between two cooperative binding mechanisms and, even though the mean expression levels were not affected differently by the acting mechanism, we showed that the associated fluctuations were different. In the present generalized model we include other regulatory functions in addition to those associated to an activator switch. Namely, we introduce repressive regulatory functions and two theoretical mechanisms that account for the biphasic response that some cis-regulatory systems show to the transcription factor concentration. We have also extended our previous master equation formalism in order to include protein production by stochastic translation of mRNA. Furthermore, we examine the graded/binary scenarios in the context of the interaction energy between transcription factors. In this sense, this is the first report to show that the cooperative binding of transcription factors to DNA promotes the ‘‘all-or-none’’ phenomenon observed in eukaryotic systems. In addition, we confirm that geneexpression fluctuation levels associated with one of two cooperative binding mechanism never exceed the fluctuation levels of the other.
) located on a non-coding region of chromosome 16 proximate to a lincRNA gene. Importantly, spe- cific LncRNA expression profiles have been shown to be differentially expressed in SZ. At a wider significance (P < 0.01), 258 SNPs on 104 genes were identified. A quanti- tative association analysis for methylation sites yielded a total of 5720 significant CpG sites on 3791 genes (P < 0.01). We further performed an integrative genetic analysis in order to identify overlapping genes accross both datasets. This computed a total number of 341 matching genes. Finally, an integrative analysis of these genes with with differentially expressed genes in SZ from two previous studies was carried out. From one of this studies, 16 differentially expressed genes were identified. Remarkably, 3 of them: SHANK2 ,SGK1, and TCN2 had been previously described in literature to be associated to SZ pathology. SHANK2 gene encodes for a protein with an important role during neurodevelopment. Although, SHANK2 was upregulated, our study iden- tified a highly methylated CpG site associated with this gene. Thus, probably, other epigenetic mechanisms could be involved in the regulation of SHANK2 expression. In fact this gene seems to be particular sensitive to DNA methylation pattern as it has been suggested in literature.
15th day with 5 mM KNO 3 or 5 mM KCl as control for 30, 60, 120 and 240 min. As shown in Figure 1, nitrate regula- tion of the NRT2.1 transporter was altered in the chl1-5 mutant (Fig. 1A) and in the T101D mutant (Fig. 1C) but not in the chl1-9 mutant (Fig. 1B), indicating that NRT2.1 induction depends on a signaling function of NRT1.1 as has been pre- viously shown. 17 Interestingly, shorter exposure to nitrate (30
promoter. This is consistent with our results, in which we did not detect any activity from promoters other than those upstream of the dksA gene (Figure 3). This unusual arrangement suggests that gluQ-rs expression is dependent on dksA-regulated conditions. Because DksA is a key member of the stringent response in bacteria and regulates a number of processes in the cell, including its own expression [25,28], the data suggest that there is coordinate regulation of tRNA modification and other DksA targets. Although we could not detect any promoter activity spe- cific for gluQ-rs in the growth conditions tested (i.e. alter- ing the pH, presence of glutamate), we cannot discount the possibility that the gene is specifically regulated under some other conditions. The regulon database (http://regu- londb.ccg.unam.mx/index.jsp) indicates that the E. coli gluQ-rs gene has a recognition site for the σ 24 subunit of RNA polymerase. From our analysis, this sequence is iden- tical to S. flexneri, but there is no experimental evidence of this recognition. Interestingly, when the gluQ-rs gene was
disease. In both conditions, protein and salt resorption are affected in kidney proximal tubular cells, ultimately leading to progressive renal failure in these patients (Bockenhauer et al., 2008; Cho et al., 2008). Lowe syndrome, also known as Oculo-cerebro-renal Lowe syndrome, is characterized by congenital cataracts, mental retardation and renal Fanconi syndrome. The latter consists of LMW proteinuria and proximal tubular acidosis. The gene responsible for the disease is OCRL, a phosphatidylinositol 4,5-bisphosphate (PIP(2))-5-phosphatase located on the X chromosome. Dent Disease is also a rare X-linked, recessively inherited proximal renal tubular disorder characterized by LMW proteinuria, hypercalciuria and nephrocalcinosis/nephrolithiasis, but only renal function is affected in these patients. Dent-1 disease is mainly caused by mutations in CLCN5, the gene encoding the chloride channel ClC-5 (Marshansky et al., 2002), and Dent-2 is caused by mutations in OCRL (Hoopes et al., 2005; Utsch et al., 2006; Sekine et al., 2007; Cho et al., 2008). Reduced excretion of megalin normally found in the urine has been reported in both Lowe syndrome and Dent disease (Norden et al., 2002; Watanabe, 2004), suggesting that megalin expression at the PT cells apical surface could be impaired in these diseases. The absence of ClC-5 in some patients is related to a signifi cant reduction in megalin expression in PT cells. Some the characteristics of these diseases are found in megalin KO mice, such as LMW proteinuria, as well as the loss of retinol binding protein (RBP), DBP and 25-hydroxy (OH) vitamin D, explaining the rickets. In addition, mouse models for Dent disease have altered expression of megalin in the PT cells (Guggino, 2007). However, it is currently unclear how mutations in the OCRL and ClC-5 genes may affect receptor expressionand/or traffi cking. It has been suggested that the lack of ClC-5 activity could be related to a failure in endosome acidifi cation and therefore impair megalin recycling to the plasma membrane (Marshansky et al., 2002; Hryciw et al., 2006). OCRL was shown to be able to bind the adaptor protein APPL1, which interacts with megalin cytoplasmic domain (Erdmann et al., 2007). Some effects of the absence of OCRL on endosome dysfunctions and megalin expression at the cell surface in Lowe syndrome have been recently proposed (see TABLE II
Contradictory articles have been published for MDR geneexpression. Previous studies showed that both vinca alkaloids and taxanes are good substrates of P-gp  and that cell lines exposed to drugs such as vincristine or Pac showed resistance associated with the expression of MDR1 . By contrast, MRP is an efficient transporter of vinca alkaloids, but not taxanes . Recently, other resistance mechanisms, such as ABCB5, an ATP-binding cassette (ABC) transporter protein, have been linked to Pac and Docetaxel resistance . In human oesophageal squamous cancer cells, up-regulation of P-gp is involved in increased Pac resistance, but not in cisplatin resistance . The connection between increased MDR1 geneexpressionand Pac has also been described in resistant human colon cancer (DLD1) and glioblastoma (U87) cell lines, while MRP1 expression decreased . Array studies by  showed that the upregulation of the MDR1 gene is the dominant mechanism of Pac and vincristine resistance in the breast cancer cell line MCF-7, suggesting that resistant cells exhibit different geneexpression patterns depending on the drug treatment. In vivo studies using lung cancer xenograft models showed that drugs may induce resistance mediated by LRP, MDR1 and MRP genes , the main candidates to explain treatment failure in NSCLC patients [27,28]. However, some authors conclude that the response to chemotherapy with Pac in NSCLC patients is related to MDR1 expression, but not to LRP expression . By contrast, some authors found no relationship between expression of LRP, MDR1 or MRP1 and resistance in NSCLC [3,26]. In fact, Shimomura et al. showed similar ABCB1 mRNA levels in NSCL sensitive and resistant cell lines . Our results clearly showed that the plasma
Even though the immune system has not been implicated in adult ADHD before, there are many studies on its association with MDD although the relationship is still somewhat controversial. 34 Expression differences in cytokines have been shown to differentiate patients with MDD from ones with bipolar disorder and controls 35 and studies have shown regulation of the serotonin receptor through cytokines and neurotrophins. 36,37 Importantly, cytokines and polymorphisms in interleukin genes have been shown to predict antidepressant treatment response. 38,39 The majority of patients with MDD (70%) and a few (13%) of the participants with adult ADHD in the current study were on antidepressant medication although medication use did not correlate significantly with any geneexpression module. However, connectivity mapping revealed that the upregulation of genes in red and green modules as seen in our adult ADHD group coincides with those seen in response to application of a number of tricyclic antidepressants, indicated for the treatment of depression and ADHD with comorbid depression. Results also contained some anti-inflammatory drugs, converging with the module enrichments for immune system genes. This could support the hypothesis that anti-inflammatory drugs such as non-steroidal anti-inflammatory drugs (NSAIDs) might have a role in the treatment of MDD and, our data suggests, also ADHD. Literature on the effects of NSAIDs in patients with MDD is, however, mixed. 40,41 Our results suggest potential drug repositioning opportunities for NSAIDs for both MDD and ADHD.
Sam68 could also have a role in transcriptional regulationand may behave as a competitive inhibitor of positive regulators of transcription, as has been shown by repressing various mammalian and viral promoter constructs. Thus, binding of Sam68 to hnRNP K inhibits the function of hnRNP K in transcriptional activation of a reporter driven by the CT promoter element of the proto-oncogene c-myc . Most of these functions of Sam68 regulating transcription are mediated by protein-protein interaction, as previously shown with the inhibition of the transcriptional activity of the multifunctional adaptor CBP . In this context, there is increasing evidence for the concept of spatial and temporal coupling between splicing and transcription, especially with nuclear factors . Sam68 also directly interacts with the androgen receptor and binds to androgen responsive elements (AREs) within the promoter region of the prostate-specific antigen (PSA) gene, where Sam68 seems to have some effect on AR-regulated transcriptional activity independently of its ARN binding capacity and splicing regulatory properties in LNcaP cells . Sam68 may also be acting as a co-activator of ER-dependent transcription in mammary development and tumorigenesis . Moreover, Sam68 is required to guarantee proper expression of the gonadotropin receptor transcripts in pre-ovulatory follicles from adult ovary with a possible role upregulating both the FSH and LH receptor transcripts .
Activity was assayed in media I and III in different phases of growth and we obtained a maximum value in medium I at the end exponential phase (OD at A 660nm , ≈ 3.45). However, it was lower at the end of the stationary phase, perhaps due to cell physiological changes caused by nutrient limitation and not by osmotic influence (Fig. 3A). Similar results were obtained in medium III, but the great- est activity value was lower than in medium I (Fig. 3B). We therefore selected medium I for further study. The polymerase activity values obtained for media in non-in- duced conditions indicate an osmolarity sufficient for basal activity or an inefficient promoter regulation at transcrip- tional level (Fig. 3). E. coli DNA polymerase activity in MKH13 transformed with pOTPEX (negative control) was not detected in our polymerase activity assay.
Limb-girdle muscular dystrophy type 2A (LGMD2A) is a recessive genetic disorder caused by mutations in calpain 3 (CAPN3). Calpain 3 plays different roles in muscular cells, but little is known about its functions or in vivo substrates. The aim of this study was to identify the genes showing an altered expression in LGMD2A patients and the possible pathways they are implicated in. Ten muscle samples from LGMD2A patients with in which molecular diagnosis was ascertained were investigated using array technology to analyze geneexpression profiling as compared to ten normal muscle samples. Upregulated genes were mostly those related to extracellular matrix (different collagens), cell adhesion (fibronectin), muscle development (myosins and melusin) and signal transduction. It is therefore suggested that different proteins located or participating in the costameric region are implicated in processes regulated by calpain 3 during skeletal muscle development. Genes participating in the ubiquitin proteasome degradation pathway were found to be deregulated in LGMD2A patients, suggesting that regulation of this pathway may be under the control of calpain 3 activity. As frizzled- related protein (FRZB) is upregulated in LGMD2A muscle samples, it could be hypothesized that b-catenin regulation is also altered at the Wnt signaling pathway, leading to an incorrect myogenesis. Conversely, expression of most transcription factor genes was downregulated (MYC, FOS and EGR1). Finally, the upregulation of IL-32 and immunoglobulin genes may induce the eosinophil chemoattraction explaining the inflammatory findings observed in presymptomatic stages. The obtained results try to shed some light on identification of novel therapeutic targets for limb-girdle muscular dystrophies.
reports of abnormal methylation of the GPR137 promoter in human cancer. It is therefore likely that additional events are causing the down- regulation the expression of SORBS2 and GPR137 genes. For example, methylation-inde- pendent repressor activities of DNMT3B . In the current study, we found overexpression of DNMT3B in cervical cancer and various can- cer cell lines. This event has been previously reported in various types of human cancer [8, 9, 13]. We also reported overexpression of DNMT3B and low levels of VAV3, SORBS2 and GPR137 in cervical, lung and breast cancer cell VAV3 promoter can inhibit its binding and its subsequent transcriptional activation. Th- is event could explain the expression decrease of the VAV3 gene in HaCaT cells with overexpression of DNMT3B. The overexpression of DN- MT3B in HaCaT cells, down- regulates the expression of SORBS2 and GPR137 genes, but the methylation of its promoters do not increase. SORBS2 is a scaffold protein involved in the assembly of signaling complexes in stress fibers and actin cytoskeleton [42, 43]. This gene is consid- ered as putative tumour sup- pressor and although there is evidence of the loss or decrease of its expression in cervical and pancreatic can- cer [44, 45], there is no evi- dence that this is due to pro- moter methylation. GPR137 is an integral membrane pro- tein that belongs to the GPR137 family of cell media- tors of signal transduction [46, 47]. Although the role of GPR137 in cancer is little known, several reports indi- cate that this gene is impor- tant a regulator of cell growth, apoptosis, invasion and mi- gration in different types of human cancer [48-52]. Si- milar to SORBS2 there are no Figure 5. Expression of DNMT3B,
Functional enrichment (FE) studies are procedures inspired in the systems biology criteria. The aim of these approaches is the direct examination of functionally related groups of variables, like genes or proteins, instead of studying them individually (Dopazo, 2006). In addition, it must be taken into account that the extraction of the biological information is not an easy task, to face this issue a specific vocabulary to annotate the function of the different biologic variables (proteins, genes...) has been developed in a systematic way (Zhou & Su, 2007) which allows to access them in a fast and standarized way, the Gene Ontology (GO) notation system is a perfect example. The GO notation establishes an organized system, surrounding a hierarchical structure, which defines a series of descriptive terms for the different biological entities in 3 different aspects: biological processes, molecular function and cellular components (Zhou & Su, 2007). Thus, for instance, it can be retrieved the GO terms associated to a given protein identifier, and then know in which biological processes it is involved, its biological functions or whether it is a part of a cellular component. In this way, thanks to these standarized GO terms it is possible to find, for example, two different proteins with the same functions. Taking profit of this, functional enrichment analysis can be applied, in order to detect whether there are significant differences in terms of the relative abundance of a specific function between 2 groups of variables.
Quantitative real-time PCR. Total RNA was extracted using the Trizol reagent (Invitrogen), and employed for measurement of Lin28a and Lin28b mRNAs. For assays of miRNA levels, total RNA was extracted with the Ambion ® mirVana ™ miRNA Isolation Kit (Ambion, Inc; CA, USA). Quality and concentration of RNAs were determined by agarose gel and spectrophotometer ND-1000 NANODROP 385 (Thermo-scientific). Real-time PCR was performed on a BioRad CFX96 Real Time PCR Detection System. For Lin28a and Lin28b mRNAs, 2 μ g of total RNA per tissue sample were treated with RQ1 RNAse-free DNAse-I (Promega) and retro-transcription was carried out in a 30-μ l reaction, using AMV reverse transcriptase and random primers (Promega). For PCR, we used SYBR Green qPCR Master Mix (Promega). The primer pairs used were: Lin28a-forward: 5′-cccggtggacgtcttt gtg-3′, Lin28a-reverse: 5 ′ -cactgcctcaccctccttga-3 ′ ; Lin28b-forward: 5 ′ -ggatcagatgtggactgtgagaga-3 ′ and Lin28b-reverse: 5 ′ -ggaggta gaccgcattctttagc-3′. For data analysis, relative standard curves were constructed from serial dilutions of one reference sample cDNA and the input value of the target gene was standardized to Hprt levels in each sample. Hprt-forward: 5′-agccgaccggttctgtcat-3′, Hprt-reverse: 3′-ggtcataacctggttcatcatcac-5′. PCR was initiated by one cycle of 95 °C for 10 min, followed by 40 cycles of 15 s at 95 °C, 35 s at 60 °C, and 10 s at 72 °C, followed by one hold of 72 °C for 10 min.
ulated) of the 77 mutant vs wt comparisons involved only genes whose mutations have well documented develop- mental phenotypes. These genes were AP2-6, ARR21, GLABROUS1 and LFY-12 mutations . They regulated 1475, 1420, 1379 and 1362 genes, respec- tively – a much more than the category average (471 genes). These results indicate that global geneexpression patterns are established during plant development. The results also suggest that the Arabidopsis transcriptome is robust to most perturbations, with only an estimated 1.5% of the genome on average responding in a single experiment to experimental factors such as chemical or hormone treatments, pathogen challenges or environ- mental stress. A detail of the categories in which each of the Arabidopsis genes responds is presented in Additional File 2. Additional Files 3 to 10 contain the genes that respond in exclusively one category, including organ type. Given its impact on global geneexpression levels, we next wished to evaluate the importance of organ type in the context of typical experimental factors that are tested in the laboratory. We compared the number of genes responding in shoots or roots for each of the nine treat- ments in the AtGenExpress abiotic stress series. On aver- age, only 13% of the total genes that responded to a treatment responded in both organs. By contrast, a much higher proportion of genes (88%) were regulated by the treatment in an organ-specific manner (Additional File 11). This data indicate that plant responses to external stimuli are strongly organ-dependent and underscore the need for a more thorough survey of organ-specific and, by extension, cell-specific responses in Arabidopsis and other plants .
Adaptation through clonally variant geneexpression is fundamentally different from adaptation through directed transcriptional responses (Supplemental Fig. S10). We propose that spontaneous, stochastic switches between the active and repressed states for a large number of genes generates transcriptional diversity within clonal parasite populations before any challenge is applied, thus representing a bet-hedging (risk- spreading) strategy (Veening et al. 2008). Upon a change in the environment, transcriptional heterogeneity provides the grounds for natural selection of pre-existing parasites with transcriptional patterns that confer maximum fitness under the new conditions. Diversity confers fitness to a population in changing environments, and mathematical models predict that diversity generated by stochastic variation is favored over sensing followed by transcriptional responses when the environment changes infrequently (Kussell and Leibler 2005), as in the case of the environment where P. falciparum blood stages reside. Adaptation through a stochastic phenotype-switching mechanism, controlled at the epigenetic level, occurs at a much faster time-scale than genetic adaptation, and is both heritable and reversible. Our results showing extensive transcriptional variation for genes involved in the interaction of the parasite with its environment provide strong support to the idea that bet-hedging strategies play a predominant role in P. falciparum adaptation. While adaptation via spontaneous clonally variant expression/selection and adaptation via directed transcriptional responses are not mutually exclusive, the former strategy may compensate for the reported limited ability of P. falciparum to mount immediate directed responses. This is a testable hypothesis that has important implications not only to understand how this devastating parasite adapts to natural fluctuating environmental conditions, but also to predict how it may evolve in front of renewed efforts to control or eradicate the disease