Deglycosylated azithromycin targets transgelin to enhance intestinal smooth muscle function
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE156032 | GEO | 2020/08/12
REPOSITORIES: GEO
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Project description:Azithromycin (AZM) reduces pulmonary inflammation and exacerbations in chronic obstructive pulmonary disease patients with emphysema. The antimicrobial effects of AZM on the lung microbiome are not known and may contribute to its beneficial effects. Methods. Twenty smokers with emphysema were randomized to receive AZM 250 mg or placebo daily for 8 weeks. Bronchoalveolar lavage (BAL) was performed at baseline and after treatment. Measurements included: rDNA gene quantity and sequence. Results. Compared with placebo, AZM did not alter bacterial burden but reduced α-diversity, decreasing 11 low abundance taxa, none of which are classical pulmonary pathogens. Conclusions. AZM treatment the lung microbiome Randomized trial comparing azithromycin (AZM) treatment with placebo for eight weeks. Bronchoalveolar lavage (BAL) samples were obtained before and after treatment to explore the effects of AZM on microbiome, in the lower airways. 16S rRNA was quantified and sequenced (MiSeq) The amplicons from total 39 samples are barcoded and the barcode is provided in the metadata_complete.txt file.
2016-07-19 | E-GEOD-74396 | biostudies-arrayexpress
Project description:Azithromycin (AZM) reduces pulmonary inflammation and exacerbations in chronic obstructive pulmonary disease patients with emphysema. The antimicrobial effects of AZM on the lung microbiome are not known and may contribute to its beneficial effects. Methods. Twenty smokers with emphysema were randomized to receive AZM 250 mg or placebo daily for 8 weeks. Bronchoalveolar lavage (BAL) was performed at baseline and after treatment. Measurements included: rDNA gene quantity and sequence. Results. Compared with placebo, AZM did not alter bacterial burden but reduced α-diversity, decreasing 11 low abundance taxa, none of which are classical pulmonary pathogens. Conclusions. AZM treatment the lung microbiome
2016-07-19 | GSE74396 | GEO
Project description:Azm affects the integrity of the bronchial epithelial barrier. To better understand these unexpected effects of Azm on bronchial epithelium we have now investigated global changes in gene expression in VA10 cells
2019-06-27 | GSE128523 | GEO
Project description:Pseudomonas aeruginosa causes severe multi-drug resistant infections that often lead to bacteremia and sepsis. Physiologically relevant conditions can increase the susceptibility of pathogens to antibiotics, such as azithromycin (AZM). When compared to minimal inhibitory concentrations (MIC) in lab media, AZM had a 16-fold lower MIC in tissue culture medium with 5% MHB, and a 64-fold lower MIC in this tissue culture medium with 20% human serum. AZM also demonstrated increased synergy in combination with synthetic host defence peptides DJK-5 and IDR-1018 under host-like conditions and in a murine abscess model. To mechanistically study the altered effects of AZM under physiologically relevant conditions, global transcriptional analysis was performed on P. aeruginosa with and without effective concentrations of AZM. This revealed that the arn operon, mediating arabinosaminylation of lipopolysaccharides, and related regulatory systems, were downregulated in host-like media when compared to MHB. Inactivation of genes within the arn operon led to increased susceptibility of P. aeruginosa to AZM and great increases in synergy between AZM and other antimicrobial agents, indicating that dysregulation of the arn operon might explain increased AZM uptake and synergy in host-like media. Furthermore, genes involved in central and energy metabolism, and ribosome biogenesis were dysregulated more in physiologically relevant conditions treated with AZM, likely due to general changes in cell physiology as a result of the increased effectiveness of AZM in these conditions. These data suggest that, in addition to the arn operon, there are multiple factors in host-like environments that are responsible for observed changes in susceptibility.
2020-12-21 | GSE151259 | GEO
Project description:P. aeruginosa produces serious chronic infections in hospitalized patients and immunocompromised individuals, including cystic fibrosis patients. The molecular mechanisms by which P. aeruginosa responds to antibiotics and other stresses to promote persistent infections may provide new avenues for therapeutic intervention. Azithromycin (AZM), an antibiotic frequently utilized in cystic fibrosis treatment, is thought to improve clinical outcomes through a number of mechanisms including impaired biofilm growth and quorum sensing in P. aeruginosa. However, the mechanisms underlying the transcriptional response to AZM remain unclear. Here, we interrogated the P. aeruginosa transcriptional response to AZM using a fast and affordable genome-wide approach to quantitate RNA 3-prime-ends (3pMap). We identify new riboregulators and identify a prominent role of transcription termination in the response to AZM treatment.
2021-06-08 | GSE173073 | GEO
Project description:Experimental Design Type of experiment: In order to evaluate the influence of subinhibitory concentrations of the macrolide antibiotic Azithromycin (AZM) on the global Pseudomonas aeruginosa gene expression, we performed a comparative gene expression analysis of AZM-treated versus untreated P. aeruginosa PAO1 cultures. Experimental factors: P. aeruginosa PAO1 cultures with and without addition of 2 µg/ ml AZM were grown until early stationary phase. Total RNA was extracted when the cultures reached an OD600 of 2.8. The transcriptomes of the untreated cultures were taken as reference values. Both of the AFFYMETRIX Chips of AZM-treated PAO1 (GSM45590, GSM45591) were compared with each of the two chips of the untreated PAO1 (GSM45588, GSM45589). Hybridization procedures and parameters: Hybridization of the probes was carried out according to the manufacturer’s “Expression Analysis Protocol (p. 25: Modified Fluidic Protocol for P. aeruginosa cDNA Assay)”, see http://www.affymetrix.com: Hybridization for 16 h at 50°C and 60 rpm. - Post Hyb Wash 1: 10 cycles of 2 mixes/cycle with Wash Buffer A at 25°C - Post Hyb Wash 2: 4 cycles of 15 mixes/cycle with Wash Buffer B at 50°C - Stain: Stain the probe array for 10 minutes in Streptavidin Solution Mix at 25°C - Post Stain Wash: 10 cycles of 4 mixes/cycle with Wash Buffer A at 30°C - 2nd Stain Wash: Stain the probe array for 10 minutes in antibody solution at 25°C - 3rd Stain Wash: Stain the probe array for 10 minutes in SAPE solution at 25°C - Final Wash: 15 cycles of 4 mixes/cycle with Wash Buffer A at 30°C. The holding temperature is 25°C. Measurement of data and specifications: Data transformation and selection procedures: · The entire signals were scaled to 150 (4% capped median); scaling factors of the arrays were within 3.4 fold of each other, as the % genes called present were in the range of 23.7% and 38.1% for three arrays (GSM455889, GSM45589, GSM45591) and 74,4% for one array (GSM45590). The background levels (Average Background) were similar for all arrays (in a range of 47.20 and 55.64). The Q scores were comparable (in a range of 2.38 and 2.81). The Average Signals of the four arrays were similar (between 187.8 and 228.7). · Scanning hardware: AFFYMETRIX Scanner; software: AFFYMETRIX MAS 5 (Statistical Algorithms Reference Guide, http://www.affymetrix.com/support/technical/technotes/statistical_reference_guide.pdf), MICRO DB 3 and DMT 3 · Image analysis software: AFFYMETRIX MAS 5 Data selection: · Threshold of Signal Log ratio: -1/1; change is I (increased), MI (marginally increased), D (decreased), MD (marginally decreased); change p-value >0.999 or <0.001; only genes that are present (Detection=P) in at least one of the compared chipsets. · Only following genes were considered: Minimal threshold of regulation ±2 fold; minimal change p-values of 0.999 and 0.001, respectively; minimal difference of signal intensities of 200. · The final gene expression data table used by the authors to make their conclusions after data selection and transformation will be published as supplementary data. Keywords: other
2006-05-10 | GSE2430 | GEO
Project description:Experimental Design; Type of experiment:; In order to evaluate the influence of subinhibitory concentrations of the macrolide antibiotic Azithromycin (AZM) on the global Pseudomonas aeruginosa gene expression, we performed a comparative gene expression analysis of AZM-treated versus untreated P. aeruginosa PAO1 cultures. Experimental factors:; P. aeruginosa PAO1 cultures with and without addition of 2 µg/ ml AZM were grown until early stationary phase. Total RNA was extracted when the cultures reached an OD600 of 2.8. The transcriptomes of the untreated cultures were taken as reference values. Both of the AFFYMETRIX Chips of AZM-treated PAO1 (GSM45590, GSM45591) were compared with each of the two chips of the untreated PAO1 (GSM45588, GSM45589). Hybridization procedures and parameters:; Hybridization of the probes was carried out according to the manufacturerâs âExpression Analysis Protocol (p. 25: Modified Fluidic Protocol for P. aeruginosa cDNA Assay)â, see http://www.affymetrix.com:; Hybridization for 16 h at 50°C and 60 rpm. - Post Hyb Wash 1: 10 cycles of 2 mixes/cycle with Wash Buffer A at 25°C; - Post Hyb Wash 2: 4 cycles of 15 mixes/cycle with Wash Buffer B at 50°C; - Stain: Stain the probe array for 10 minutes in Streptavidin Solution Mix at 25°C; - Post Stain Wash: 10 cycles of 4 mixes/cycle with Wash Buffer A at 30°C; - 2nd Stain Wash: Stain the probe array for 10 minutes in antibody solution at; 25°C; - 3rd Stain Wash: Stain the probe array for 10 minutes in SAPE solution at 25°C; - Final Wash: 15 cycles of 4 mixes/cycle with Wash Buffer A at 30°C. The; holding temperature is 25°C. Measurement of data and specifications:; Data transformation and selection procedures:; · The entire signals were scaled to 150 (4% capped median); scaling factors of the arrays were within 3.4 fold of each other, as the % genes called present were in the range of 23.7% and 38.1% for three arrays (GSM455889, GSM45589, GSM45591) and 74,4% for one array (GSM45590). The background levels (Average Background) were similar for all arrays (in a range of 47.20 and 55.64). The Q scores were comparable (in a range of 2.38 and 2.81). The Average Signals of the four arrays were similar (between 187.8 and 228.7). · Scanning hardware: AFFYMETRIX Scanner; software: AFFYMETRIX MAS 5 (Statistical Algorithms Reference Guide, http://www.affymetrix.com/support/technical/technotes/statistical_reference_guide.pdf), MICRO DB 3 and DMT 3; · Image analysis software: AFFYMETRIX MAS 5; Data selection:; · Threshold of Signal Log ratio: -1/1; change is I (increased), MI (marginally increased), D (decreased), MD (marginally decreased); change p-value >0.999 or <0.001; only genes that are present (Detection=P) in at least one of the compared chipsets. · Only following genes were considered: Minimal threshold of regulation ±2 fold; minimal change p-values of 0.999 and 0.001, respectively; minimal difference of signal intensities of 200. · The final gene expression data table used by the authors to make their conclusions after data selection and transformation will be published as supplementary data.
2008-06-12 | E-GEOD-2430 | biostudies-arrayexpress
Project description:Low-dose macrolides are effective therapy in patients with chronic lung infections, but the mechanisms of action are unclear. We compared global gene expression profiles between P.aeruginosa with and without low-dose Azithromycin (AZM) to study why the low-dose macrolide therapy is effective for cystic fibrosis and diffuse panbronchiolitis. Keywords: dose-response
2009-05-01 | GSE12738 | GEO
Project description:We performed RNA-Seq analysis and compared three groups 1) WT+IL-23 v. WT+GFP (control), 2) Mdl1-/-+IL-23 v. WT+GFP (control), and 3) WT+IL-23 v. Mdl1-/-+IL-23. Sets of differentially expressed genes (DEG) were defined on the basis of standard thresholds i.e. a |log2FC|≥2 combined with an adjusted p-value≤0.01 against the control group. Differential expression analysis revealed 1171 (619 up-regulated and 552 down-regulated) DEGs in WT+IL-23 v. WT+GFP, 414 (303 up-regulated and 111 down-regulated) DEGs in Mdl1-/-+IL-23 v. WT+GFP, and 260 (122 up-regulated and 138 down-regulated) DEGs in WT+IL-23 v. Mdl1-/-+IL-23
2022-07-02 | GSE133830 | GEO
Project description:The objective of this study was therefore to evaluate the impact of simultaneous vitrification of large numbers of embryos with the OC (20 embryos per device) system on gene expression patterns of in vivo-derived blastocysts when compared to the Superfine Open Pulled Straw (SOPS) system (5-7 embryos per device) through a microarray approach. In vivo-developed embryos were surgically retrieved from 16 sows in 4 replicates. Embryos at the blastocyst stage (n=180) were selected for the experiment and divided into three experimental groups: blastocysts vitrified with the OC system (n=60), blastocysts vitrified with the SOPS system (n=60), and a control group consisting of fresh, nonvitrified blastocysts (n=60). After in vitro culture for 24 h, six pools of 8 viable embryos (n=48 embryos per group) were prepared for transcriptome analysis. Embryos were placed in sterile tubes with 5 µL of PBS, immediately immersed in LN2 and stored at -80 °C until microarray analysis. After microarray analysis, a list of DEGs was generated for comparison of each vitrification system (OC and SOPS) with the control. Then, the two DEG lists were compared to determine the specific genes altered in each vitrification system and the DEGs shared by both systems. In addition, a list of DEGs was obtained by direct comparison of both vitrification systems. Pathway enrichment analysis was performed for each obtained list of DEGs.
2023-03-06 | E-MTAB-12772 | biostudies-arrayexpress