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1.
Regulation of carbohydrate degradation pathways in Pseudomonas involves a versatile set of transcriptional regulators.
Udaondo, Z, Ramos, JL, Segura, A, Krell, T, Daddaoua, A
Microbial biotechnology. 2018;(3):442-454
Abstract
Bacteria of the genus Pseudomonas are widespread in nature. In the last decades, members of this genus, especially Pseudomonas aeruginosa and Pseudomonas putida, have acquired great interest because of their interactions with higher organisms. Pseudomonas aeruginosa is an opportunistic pathogen that colonizes the lung of cystic fibrosis patients, while P. putida is a soil bacterium able to establish a positive interaction with the plant rhizosphere. Members of Pseudomonas genus have a robust metabolism for amino acids and organic acids as well as aromatic compounds; however, these microbes metabolize a very limited number of sugars. Interestingly, they have three-pronged metabolic system to generate 6-phosphogluconate from glucose suggesting an adaptation to efficiently consume this sugar. This review focuses on the description of the regulatory network of glucose utilization in Pseudomonas, highlighting the differences between P. putida and P. aeruginosa. Most interestingly, It is highlighted a functional link between glucose assimilation and exotoxin A production in P. aeruginosa. The physiological relevance of this connection remains unclear, and it needs to be established whether a similar relationship is also found in other bacteria.
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2.
Assessment of the association between ZBTB20 rs9841504 polymorphism and gastric and esophageal cancer susceptibility: a meta-analysis.
Shi, J, Li, W, Ding, X
The International journal of biological markers. 2017;(1):e96-e101
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Abstract
BACKGROUND The protein encoded by ZBTB20 is a member of the POK family, whose members function as transcriptional repressors through interactions mediated by their conserved C2H2 Krüppel-type zinc finger and BTB/POZ domains. Polymorphisms in ZBTB20 appeared to be associated with gastric and esophageal cancer susceptibility in biological models, but the results of these studies were inconclusive. Therefore, we conducted a meta-analysis by pooling all available data to assess the exact association between the ZBTB20 rs9841504 polymorphism and gastric and esophageal cancer susceptibility. METHOD The meta-analysis was performed for homozygote comparison, heterozygote comparison, and dominant and recessive models by applying a fixed- or random-effects model. The pooled odds ratios (ORs) with the corresponding confidence intervals (CIs) were calculated. Moreover, the data were analyzed using the Stata 12.0 software(StataCorp). RESULT A total of 8 independent case-control studies comprising 9,994 cases and 10,258 controls were included. We found a significant association between the rs9841504 polymorphism and decreased gastric cancer susceptibility in the allelic, homozygous, dominant and recessive models (B vs. A:OR = 0.797, 95% CI 0.644-0.986, p = 0.036; BB vs. AA:OR = 0.601, 95% CI 0.366-0.988, p = 0.045; BA + BB vs. AA:OR = 0.789, 95% CI 0.627-0.992, p = 0.043; BB vs. BA + AA:OR = 0.635, 95% CI 0.405-0.997, p = 0.049). Conversely, no association between the rs9841504 polymorphism and esophageal cancer susceptibility was found. In subgroup analysis by ethnicity, we observed a significantly decreased susceptibility to gastric cancer in Asian populations in the allele contrast, homozygous and recessive models (B vs. A:OR = 0.791, 95% CI 0.628-0.996, p = 0.046; BB vs. AA:OR = 0.559, 95% CI 0.323-0.966, p = 0.037; BB vs. BA + AA:OR = 0.593, 95% CI 0.361-0.972, p = 0.038). CONCLUSIONS In summary, our work suggests that the ZBTB20 rs9841504 polymorphism is a protective factor for gastric cancer rather than esophageal cancer.
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Inferring causal metabolic signals that regulate the dynamic TORC1-dependent transcriptome.
Oliveira, AP, Dimopoulos, S, Busetto, AG, Christen, S, Dechant, R, Falter, L, Haghir Chehreghani, M, Jozefczuk, S, Ludwig, C, Rudroff, F, et al
Molecular systems biology. 2015;(4):802
Abstract
Cells react to nutritional cues in changing environments via the integrated action of signaling, transcriptional, and metabolic networks. Mechanistic insight into signaling processes is often complicated because ubiquitous feedback loops obscure causal relationships. Consequently, the endogenous inputs of many nutrient signaling pathways remain unknown. Recent advances for system-wide experimental data generation have facilitated the quantification of signaling systems, but the integration of multi-level dynamic data remains challenging. Here, we co-designed dynamic experiments and a probabilistic, model-based method to infer causal relationships between metabolism, signaling, and gene regulation. We analyzed the dynamic regulation of nitrogen metabolism by the target of rapamycin complex 1 (TORC1) pathway in budding yeast. Dynamic transcriptomic, proteomic, and metabolomic measurements along shifts in nitrogen quality yielded a consistent dataset that demonstrated extensive re-wiring of cellular networks during adaptation. Our inference method identified putative downstream targets of TORC1 and putative metabolic inputs of TORC1, including the hypothesized glutamine signal. The work provides a basis for further mechanistic studies of nitrogen metabolism and a general computational framework to study cellular processes.
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4.
Exercise with low glycogen increases PGC-1α gene expression in human skeletal muscle.
Psilander, N, Frank, P, Flockhart, M, Sahlin, K
European journal of applied physiology. 2013;(4):951-63
Abstract
Recent studies suggest that carbohydrate restriction can improve the training-induced adaptation of muscle oxidative capacity. However, the importance of low muscle glycogen on the molecular signaling of mitochondrial biogenesis remains unclear. Here, we compare the effects of exercise with low (LG) and normal (NG) glycogen on different molecular factors involved in the regulation of mitochondrial biogenesis. Ten highly trained cyclists (VO(2max) 65 ± 1 ml/kg/min, W max 387 ± 8 W) exercised for 60 min at approximately 64 % VO(2max) with either low [166 ± 21 mmol/kg dry weight (dw)] or normal (478 ± 33 mmol/kg dw) muscle glycogen levels achieved by prior exercise/diet intervention. Muscle biopsies were taken before, and 3 h after, exercise. The mRNA of peroxisome proliferator-activated receptor-γ coactivator-1 was enhanced to a greater extent when exercise was performed with low compared with normal glycogen levels (8.1-fold vs. 2.5-fold increase). Cytochrome c oxidase subunit I and pyruvate dehydrogenase kinase isozyme 4 mRNA were increased after LG (1.3- and 114-fold increase, respectively), but not after NG. Phosphorylation of AMP-activated protein kinase, p38 mitogen-activated protein kinases and acetyl-CoA carboxylase was not changed 3 h post-exercise. Mitochondrial reactive oxygen species production and glutathione oxidative status tended to be reduced 3 h post-exercise. We conclude that exercise with low glycogen levels amplifies the expression of the major genetic marker for mitochondrial biogenesis in highly trained cyclists. The results suggest that low glycogen exercise may be beneficial for improving muscle oxidative capacity.
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Glioma-associated oncogene family zinc finger 1 expression and metastasis in patients with head and neck squamous cell carcinoma treated with radiation therapy (RTOG 9003).
Chung, CH, Dignam, JJ, Hammond, ME, Klimowicz, AC, Petrillo, SK, Magliocco, A, Jordan, R, Trotti, A, Spencer, S, Cooper, JS, et al
Journal of clinical oncology : official journal of the American Society of Clinical Oncology. 2011;(10):1326-34
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Abstract
PURPOSE Glioma-associated oncogene family zinc finger 1 (GLI1) expression was assessed to determine a potential role of hedgehog (Hh) signaling in head and neck squamous cell carcinoma (HNSCC). Additional proteins known to be modulated by Hh signaling, including beta-catenin (CTNNB1) and epidermal growth factor receptor (EGFR), were also assessed to determine the correlation among these distinct signaling pathways. PATIENTS AND METHODS Nuclear GLI1 and CTNNB1 expression levels were determined in tumors from patients enrolled on Radiation Therapy Oncology Group (RTOG) 9003, a radiation fractionation trial. The results were also correlated with previously determined EGFR expression. The expression levels were evaluated in relation to three end points: time to metastasis (TTM), time to disease progression (TDP), and overall survival (OS). RESULTS Among 1,068 eligible patients, data on GLI1, CTNNB1, and EGFR were available in 339, 164, and 300 patients, respectively. Although CTNNB1 expression did not differentiate prognosis, GLI1 was associated with poorer outcomes, adjusted for age, TNM stages, and Karnofsky performance score, and the significant influence persisted in a multivariable analysis (quartile 4 [Q4] v Q1 to Q3: TTM hazard ratio [HR], 2.7; 95% CI, 1.5 to 4.9; TDP HR, 1.6; 95% CI, 1.1 to 2.5; OS HR, 1.9; 95% CI, 1.4 to 2.7). The significance of GLI1 persisted in a multivariable analysis that included EGFR expression levels. CONCLUSION These data suggest that Hh signaling may play an important role in metastasis and that GLI1 could serve as a marker in HNSCC, but the regulatory mechanisms and oncogenic significance need further investigation. Risk classification based on this analysis needs a validation in independent cohorts.
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Comparative analysis of regulatory motif discovery tools for transcription factor binding sites.
Wei, W, Yu, XD
Genomics, proteomics & bioinformatics. 2007;(2):131-42
Abstract
In the post-genomic era, identification of specific regulatory motifs or transcription factor binding sites (TFBSs) in non-coding DNA sequences, which is essential to elucidate transcriptional regulatory networks, has emerged as an obstacle that frustrates many researchers. Consequently, numerous motif discovery tools and correlated databases have been applied to solving this problem. However, these existing methods, based on different computational algorithms, show diverse motif prediction efficiency in non-coding DNA sequences. Therefore, understanding the similarities and differences of computational algorithms and enriching the motif discovery literatures are important for users to choose the most appropriate one among the online available tools. Moreover, there still lacks credible criterion to assess motif discovery tools and instructions for researchers to choose the best according to their own projects. Thus integration of the related resources might be a good approach to improve accuracy of the application. Recent studies integrate regulatory motif discovery tools with experimental methods to offer a complementary approach for researchers, and also provide a much-needed model for current researches on transcriptional regulatory networks. Here we present a comparative analysis of regulatory motif discovery tools for TFBSs.
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Finding motifs with insufficient number of strong binding sites.
Leung, HC, Chin, FY, Yiu, SM, Rosenfeld, R, Tsang, WW
Journal of computational biology : a journal of computational molecular cell biology. 2005;(6):686-701
Abstract
A molecule called transcription factor usually binds to a set of promoter sequences of coexpressed genes. As a result, these promoter sequences contain some short substrings, or binding sites, with similar patterns. The motif discovering problem is to find these similar patterns and motifs in a set of sequences. Most existing algorithms find the motifs based on strong-signal sequences only (i.e., those containing binding sites very similar to the motif). In this paper, we use a probability matrix to represent a motif to calculate the minimum total number of binding sites required to be in the input dataset in order to confirm that the discovered motifs are not artifacts. Next, we introduce a more general and realistic energy-based model, which considers all sequences with varying degrees of binding strength to the transcription factors (as measured experimentally). By treating sequences with varying degrees of binding strength, we develop a heuristic algorithm called EBMF (Energy-Based Motif Finding Algorithm) to find the motif, which can handle sequences ranging from those that contain more than one binding site to those that contain none. EBMF can find motifs for datasets that do not even have the required minimum number of binding sites as previously derived. EBMF compares favorably with common motif-finding programs AlignACE and MEME. In particular, for some simulated and real datasets, EBMF finds the motif when both AlignACE and MEME fail to do so.
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BioOptimizer: a Bayesian scoring function approach to motif discovery.
Jensen, ST, Liu, JS
Bioinformatics (Oxford, England). 2004;(10):1557-64
Abstract
MOTIVATION Transcription factors (TFs) bind directly to short segments on the genome, often within hundreds to thousands of base pairs upstream of gene transcription start sites, to regulate gene expression. The experimental determination of TFs binding sites is expensive and time-consuming. Many motif-finding programs have been developed, but no program is clearly superior in all situations. Practitioners often find it difficult to judge which of the motifs predicted by these algorithms are more likely to be biologically relevant. RESULTS We derive a comprehensive scoring function based on a full Bayesian model that can handle unknown site abundance, unknown motif width and two-block motifs with variable-length gaps. An algorithm called BioOptimizer is proposed to optimize this scoring function so as to reduce noise in the motif signal found by any motif-finding program. The accuracy of BioOptimizer, which can be used in conjunction with several existing programs, is shown to be superior to using any of these motif-finding programs alone when evaluated by both simulation studies and application to sets of co-regulated genes in bacteria. In addition, this scoring function formulation enables us to compare objectively different predicted motifs and select the optimal ones, effectively combining the strengths of existing programs. AVAILABILITY BioOptimizer is available for download at www.fas.harvard.edu/~junliu/BioOptimizer/
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Comparative genomics of the KdgR regulon in Erwinia chrysanthemi 3937 and other gamma-proteobacteria.
Rodionov, DA, Gelfand, MS, Hugouvieux-Cotte-Pattat, N
Microbiology (Reading, England). 2004;(Pt 11):3571-3590
Abstract
In the plant-pathogenic enterobacterium Erwinia chrysanthemi, almost all known genes involved in pectin catabolism are controlled by the transcriptional regulator KdgR. In this study, the comparative genomics approach was used to analyse the KdgR regulon in completely sequenced genomes of eight enterobacteria, including Erw. chrysanthemi, and two Vibrio species. Application of a signal recognition procedure complemented by operon structure and protein sequence analysis allowed identification of new candidate genes of the KdgR regulon. Most of these genes were found to be controlled by the cAMP-receptor protein, a global regulator of catabolic genes. At the next step, regulation of these genes in Erw. chrysanthemi was experimentally verified using in vivo transcriptional fusions and an attempt was made to clarify the functional role of the predicted genes in pectin catabolism. Interestingly, it was found that the KdgR protein, previously known as a repressor, positively regulates expression of two new members of the regulon, phosphoenolpyruvate synthase gene ppsA and an adjacent gene, ydiA, of unknown function. Other predicted regulon members, namely chmX, dhfX, gntB, pykF, spiX, sotA, tpfX, yeeO and yjgK, were found to be subject to classical negative regulation by KdgR. Possible roles of newly identified members of the Erw. chrysanthemi KdgR regulon, chmX, dhfX, gntDBMNAC, spiX, tpfX, ydiA, yeeO, ygjV and yjgK, in pectin catabolism are discussed. Finally, complete reconstruction of the KdgR regulons in various gamma-proteobacteria yielded a metabolic map reflecting a globally conserved pathway for the catabolism of pectin and its derivatives with variability in transport and enzymic capabilities among species. In particular, possible non-orthologous substitutes of isomerase KduI and a new oligogalacturonide transporter in the Vibrio species were detected.
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Hypermethylation of the GATA genes in lung cancer.
Guo, M, Akiyama, Y, House, MG, Hooker, CM, Heath, E, Gabrielson, E, Yang, SC, Han, Y, Baylin, SB, Herman, JG, et al
Clinical cancer research : an official journal of the American Association for Cancer Research. 2004;(23):7917-24
Abstract
PURPOSE In lung cancer, DNA hypermethylation is known to be a common event. EXPERIMENTAL DESIGN Gene expression and methylation status of GATA-4, GATA-5, and GATA-6 were analyzed with cell lines and primary human lung cancers. Methylation profiles of primary lung cancers were analyzed and correlated with clinical as well as histopathological data. RESULTS Complete methylation was detected by methylation-specific PCR for both GATA-4 and GATA-5 in four cell lines (H358, DMS-53, A549, and H1299), all of which had no expression by reverse transcription-PCR analysis. Demethylation with 5-aza-2'deoxycytidine restored expression in each case. GATA-6 was ubiquitously expressed in all of the six cell lines. GATA-4 bisulfite sequencing revealed complete methylation of the GATA-4 promoter in H358 cells, correlating well with its lack of expression at the mRNA level. Only a few CpG sites showed methylation by bisulfite sequencing within the GATA-4 promoter in a cell line that expressed the gene. In 63 cases of primary lung cancers, GATA-4 and GATA-5 promoter methylation was detected in (42 of 63) 67% and (26 of 63) 41%, respectively. GATA-6 remained unmethylated both in cell lines and primary tumors. Six autopsy specimens of normal lung tissue showed no aberrant promoter hypermethylation for the GATA genes. Correlation of concomitant GATA-4 and GATA-5 methylation with clinicopathological parameters only found a statistically significant increase in methylation frequency with increasing patient age (P < 0.001). CONCLUSIONS These epigenetic changes in the GATA genes in lung cancer are tumor-specific, relate to the loss of GATA gene expression, and occur increasingly in the elderly.