Journal: Folia Microbiologica

Article Title: Genotyping of Campylobacter jejuni and prediction tools of its antimicrobial resistance

doi: 10.1007/s12223-023-01093-5

Figure Lengend Snippet: Minimum spanning tree of C. jejuni based on MLST analysis. The allelic distance, recorded on the lines, was evaluated according to the sequence types (STs; listed in the circles) by Ridom SeqSphere+. Strains are colour-coded by their origin (dark grey, human; light grey, animal; white, environmental). Clusters of strains differing in maximum one allele are marked by a dashed line

Article Snippet: First, the default setting of the Ridom SeqSphere+ software (clustering based on similarity of 637 loci in maximum 13 alleles) was too strict for such a highly variable organism as C. jejuni is. cgMLST separated the 35 strains into 34 unique profiles.

Techniques: Sequencing

Journal: Folia Microbiologica

Article Title: Genotyping of Campylobacter jejuni and prediction tools of its antimicrobial resistance

doi: 10.1007/s12223-023-01093-5

Figure Lengend Snippet: Minimum spanning tree of C. jejuni s trains based on cgMLST analysis by Ridom SeqSphere+ software. The circles are colour-coded based on the origin of the strains (human, dark; environmental, white; and animal, grey). Clusters of related strains differing in max. 13 alleles are marked by dashed lines

Article Snippet: First, the default setting of the Ridom SeqSphere+ software (clustering based on similarity of 637 loci in maximum 13 alleles) was too strict for such a highly variable organism as C. jejuni is. cgMLST separated the 35 strains into 34 unique profiles.

Techniques: Software

Journal: Pathogens

Article Title: Isolation and Description of Catonella massiliensis sp. nov., a Novel Catonella Species, Isolated from a Stable Periodontitis Subject

doi: 10.3390/pathogens10030367

Figure Lengend Snippet: Maximum likelihood tree based on the comparison of 16S rRNA gene sequences showing the phylogenetic relationships of Catonella massiliensis Marseille-Q4567 T and other closely related species. Bootstrap values (expressed as percentages of 1000 replications) are displayed at the nodes. Only bootstrap values of 70% or greater are shown. Type strains are indicated with superscript T. GenBank accession numbers of 16S rRNA indicated in parentheses. Sequences were aligned using MUSCLE with default parameters, phylogenetic inference was obtained using the Maximum likelihood method and MEGA X software . Bootstrap values obtained by repeating the analysis 1000 times to generate a majority consensus tree are indicated at the nodes. There was a total of 1392 positions in the final dataset.

Article Snippet: 16S rDNA-based similarity analysis of strain Marseille-Q4567 T against GenBank yielded the highest nucleotide sequence similarities of 98.23% sequence identity with C. morbi ATCC 51271 T (GenBank accession no. NR_026248.1).

Techniques: Comparison, Software

Journal: Scientific Reports

Article Title: Transcriptional overlap links DNA hypomethylation with DNA hypermethylation at adjacent promoters in cancer

doi: 10.1038/s41598-021-96844-0

Figure Lengend Snippet: DNA hypomethylation of the MAGEA6 / CT-GABRA3 promoter correlates with DNA hypermethylation of the GABRA3 promoter in melanoma and lung adenocarcinoma. ( A ) Schematic representation of the GABRA3 locus, with broken arrows indicating transcription start sites. The exon/intron structure of CT-GABRA3 and GABRA3 transcript variants is shown above. ( B ) Clonal bisulfite sequencing of MAGEA6 / CT-GABRA3 and GABRA3 5′-regions. Vertical bars indicate location of CpG sites with positions relative to the transcription start site. Open and filled squares represent unmethylated and methylated CpG sites, respectively, and each row represents a single clone. CT-GABRA3 expression status (+) or (−) in melanoma cell lines is indicated. ( C ) Melanoma tissue samples from the TCGA were grouped according to CT-GABRA3 expression status (inferred from RNA-seq data), and the methylation level of three CpG sites embedded within the GABRA3 5′-region (position relative to TSS) were determined through the analysis of Infinium methylation data (probe intensity ratio). *** Welch’s t-test, adjusted p -value < 0.001 ( D ) Methylation level of CpG sites within the MAGEA6 / CT-GABRA3 and GABRA3 5′-regions in lung adenocarcinoma (LUAD) cell lines (CpG positions are expressed relative to the TSS). Methylation levels were calculated on the basis of Methyl-seq data from the DBTSS database. CT-GABRA3 expression status in LUAD cell lines was inferred from RNA-seq data. ( E ) The same analysis as described in D was applied to lung adenocarcinoma samples from the TCGA. ** and ***Mann–Whitney test, adjusted p -value < 0.01 and < 0.001, respectively.

Article Snippet: Hypermethylation includes CpGs within the promoter of GABRQ . ( B ) Schematic representation of the three defined 530 kb genomic segments, corresponding to the CT-GABRA3 transcription unit (Region B ), and the two neighboring segments (Regions A and C ). ( C ) LUAD cell lines were divided in two groups, according to CT-GABRA3 expression status, and Methyl-seq datasets from DBTSS were used to determine mean methylation levels (% methylation) of all CpGs contained in each of the three genomic regions defined in ( B ). ( D ) A similar analysis, based on Infinium methylation data, was performed in melanoma (SKCM) and lung adenocarcinoma (LUAD) tissue samples from TCGA.

Techniques: Methylation Sequencing, Methylation, Expressing, RNA Sequencing, MANN-WHITNEY

Journal: Scientific Reports

Article Title: Transcriptional overlap links DNA hypomethylation with DNA hypermethylation at adjacent promoters in cancer

doi: 10.1038/s41598-021-96844-0

Figure Lengend Snippet: CT-GABRA3 expression correlates with hypermethylation of CpGs embedded within its entire transcription unit. ( A ) Using Methyl-seq data from DBTSS, CpG methylation ratios between CT-GABRA3 -positive and -negative LUAD cell lines were calculated. Values for all available CpGs within the GABRA3 locus are represented (log2). Positive or negative values indicate hypermethylation or hypomethylation, respectively, of the CpG in CT-GABRA3 -positive versus -negative LUAD cell lines. Hypermethylation includes CpGs within the promoter of GABRQ . ( B ) Schematic representation of the three defined 530 kb genomic segments, corresponding to the CT-GABRA3 transcription unit (Region B ), and the two neighboring segments (Regions A and C ). ( C ) LUAD cell lines were divided in two groups, according to CT-GABRA3 expression status, and Methyl-seq datasets from DBTSS were used to determine mean methylation levels (% methylation) of all CpGs contained in each of the three genomic regions defined in ( B ). ( D ) A similar analysis, based on Infinium methylation data, was performed in melanoma (SKCM) and lung adenocarcinoma (LUAD) tissue samples from TCGA. * and *** Welch’s t-test, p -value < 0.05 and < 0.001, respectively.

Article Snippet: Hypermethylation includes CpGs within the promoter of GABRQ . ( B ) Schematic representation of the three defined 530 kb genomic segments, corresponding to the CT-GABRA3 transcription unit (Region B ), and the two neighboring segments (Regions A and C ). ( C ) LUAD cell lines were divided in two groups, according to CT-GABRA3 expression status, and Methyl-seq datasets from DBTSS were used to determine mean methylation levels (% methylation) of all CpGs contained in each of the three genomic regions defined in ( B ). ( D ) A similar analysis, based on Infinium methylation data, was performed in melanoma (SKCM) and lung adenocarcinoma (LUAD) tissue samples from TCGA.

Techniques: Expressing, CpG Methylation Assay, Methylation

Journal: Scientific Reports

Article Title: Transcriptional overlap links DNA hypomethylation with DNA hypermethylation at adjacent promoters in cancer

doi: 10.1038/s41598-021-96844-0

Figure Lengend Snippet: Experimental hypomethylation/activation of CT-GABRA3 induces de novo methylation of CpGs within its transcription unit. ( A ) Diagram depicting O’Neill’s experiment. Clones were derived from hTERT-immortalized human male fibroblasts transfected with an anti-DNMT1 shRNA producing vector (pSh- DNMT1 ). ( B ) cDNA microarray data were analyzed to determine relative mRNA levels of DMNT1 , MAGEA6 and ( CT- ) GABRA3 (the two transcript variants cannot be distinguished by microarray), in the control hTERT fibroblast cell line (Ctrl) and in the three DNMT1-depleted clones (D8, D10 and D18). ( C ) Infinium methylation data were used to determine mean methylation levels of all CpGs (mean probe intensity ratios) in the control cell line and the DNMT1-depleted clones. Analyses are provided for the CT-GABRA3 transcription unit (Region B ), and the two neighboring segments (Regions A and C, see Fig. B). ***One-way paired ANOVA test with Dunnett’s correction, p -value < 0.001.

Article Snippet: Hypermethylation includes CpGs within the promoter of GABRQ . ( B ) Schematic representation of the three defined 530 kb genomic segments, corresponding to the CT-GABRA3 transcription unit (Region B ), and the two neighboring segments (Regions A and C ). ( C ) LUAD cell lines were divided in two groups, according to CT-GABRA3 expression status, and Methyl-seq datasets from DBTSS were used to determine mean methylation levels (% methylation) of all CpGs contained in each of the three genomic regions defined in ( B ). ( D ) A similar analysis, based on Infinium methylation data, was performed in melanoma (SKCM) and lung adenocarcinoma (LUAD) tissue samples from TCGA.

Techniques: Activation Assay, Methylation, Clone Assay, Derivative Assay, Transfection, shRNA, Plasmid Preparation, Microarray, Control

Journal: Scientific Reports

Article Title: Transcriptional overlap links DNA hypomethylation with DNA hypermethylation at adjacent promoters in cancer

doi: 10.1038/s41598-021-96844-0

Figure Lengend Snippet: Identification of other genomic loci displaying correlation between DNA hypermethylation of an overlapped promoter (OPr) and activation of an overlapping transcript (OTr) in LUAD cell lines. ( A ) Flowchart of the bioinformatics selection procedure. Broken arrows indicate positions of transcription start sites, wavy lines correspond to overlapping transcription, and empty or filled circles represent unmethylated or methylated CpGs, respectively. ( B ) Features of selected genomic loci. For OPrs, the table provides: distance from TSS of OTr; gene symbol (with transcript variant according to NCBI RefSeq descriptions, or indicated as vX when the variant was undescribed); Pearson coefficient of correlation between OTr activation and promoter CpG methylation; Pearson coefficient of correlation between OTr activation and promoter H3K36me3 (coefficient in bold if adjusted p- value < 0.05). For OTrs: name of transcript or transcript variant, or “unnamed” if not described in NCBI RefSeq; CpG methylation level of 5′-region in normal lung; Pearson coefficient of correlation between transcriptional activation and 5′-region CpG methylation level (“/” when methylation data were unavailable, coefficient in bold if adjusted p- value < 0.05); cancer-germline (“CG”) features, i.e. OTr is specifically expressed and its 5′-region demethylated in testis. OTrs were categorized according to their predicted dependency ( me CpG-dependent) or independency ( me CpG-independent) on DNA demethylation for transcriptional activation in LUAD cells (see text for criteria); several OTrs were categorized “Undetermined” because methylation data in LUAD cell lines were lacking. ( C ) The number of CpGs were calculated in the genomic segments located − 400 to + 400 relative to the TSS of OPrs and OTrs. Results are expressed as number of CpGs per 100 bp, and are plotted on a log2 scale. Sequences were categorized according to CpG density: (> 4 CpG/100 bp: High, 2–4 CpG/100 bp: Medium, < 2 CpG/100 bp: Low).

Article Snippet: Hypermethylation includes CpGs within the promoter of GABRQ . ( B ) Schematic representation of the three defined 530 kb genomic segments, corresponding to the CT-GABRA3 transcription unit (Region B ), and the two neighboring segments (Regions A and C ). ( C ) LUAD cell lines were divided in two groups, according to CT-GABRA3 expression status, and Methyl-seq datasets from DBTSS were used to determine mean methylation levels (% methylation) of all CpGs contained in each of the three genomic regions defined in ( B ). ( D ) A similar analysis, based on Infinium methylation data, was performed in melanoma (SKCM) and lung adenocarcinoma (LUAD) tissue samples from TCGA.

Techniques: Activation Assay, Selection, Methylation, Variant Assay, CpG Methylation Assay

Journal: Scientific Reports

Article Title: Transcriptional overlap links DNA hypomethylation with DNA hypermethylation at adjacent promoters in cancer

doi: 10.1038/s41598-021-96844-0

Figure Lengend Snippet: DNA hypomethylation-induced transcriptional overlap is associated with DNA hypermethylation of PTPRO and RERG tumor suppressor genes. ( A ) RNA-seq data from indicated samples were analyzed with IGV. Exon–intron structures are depicted on the top. ( B ) RT-PCR analyses in various normal tissues were performed with primers specific for either RERG or CT-RERG transcripts. ( C ) Bisulfite-seq data (NIH Roadmap epigenomics) revealing the methylation level (histograms) of CpG sites (vertical bars) surrounding the CT-RERG transcription start (broken arrow) in normal tissues. ( D ) CT-RERG -negative lung tumor cell lines were cultured with (−) or without (+) the DNA methylation inhibitor 5-azadC, and RT-PCR experiments were performed to test induction of CT-RERG mRNA. NCI-H661 lung tumor cell line was used as a positive control of CT-RERG expression. ACTB served as an internal control, and MAGEA1 as a control of 5-azadC induction. ( E ) Three 240 kb genomic regions were defined for subsequent analyses: CT-RERG transcription unit ( B ) and the two neighboring segments ( A and C ). ( F ) Mean amounts of ChIP-seq reads for H3K36me3 or control input in genomic regions A, B and C were compared in LUAD cell lines that do or do not express CT-RERG . *Mann–Whitney test, p -value < 0.05. ( G ) Mean methylation levels (%, Methyl-seq data) of all CpGs contained in each of the three genomic regions were compared in CT-RERG -positive and -negative LUAD cell lines. ****Mann–Whitney test, p -value ≤ 0.0001. ( H ) Mean methylation levels of all CpG sites embedded within the 5′region of either the PTPRO (n = 8, − 215 to + 359 relative to TSS) or RERG (n = 9, − 258 to + 364) were compared in CT-RERG - and CT-RERG + LUAD tumor samples (TCGA). *Mann–Whitney test, p -value < 0.05. ( I ) The proportion of samples with PTPRO hypermethylation was determined in TCGA samples of hepatocellular carcinoma (LIHC, n = 369) grouped according to the CT-RERG expression status. Considering that the mean CpG methylation values within the PTPRO 5′-region was 0.08 (SD ± 0.014) in normal liver tissues (n = 41), the region was considered hypermethylated in tumor samples where the mean CpG methylation value was > 0.2. ***Fisher’s exact test, p -value < 0.001.

Article Snippet: Hypermethylation includes CpGs within the promoter of GABRQ . ( B ) Schematic representation of the three defined 530 kb genomic segments, corresponding to the CT-GABRA3 transcription unit (Region B ), and the two neighboring segments (Regions A and C ). ( C ) LUAD cell lines were divided in two groups, according to CT-GABRA3 expression status, and Methyl-seq datasets from DBTSS were used to determine mean methylation levels (% methylation) of all CpGs contained in each of the three genomic regions defined in ( B ). ( D ) A similar analysis, based on Infinium methylation data, was performed in melanoma (SKCM) and lung adenocarcinoma (LUAD) tissue samples from TCGA.

Techniques: RNA Sequencing, Reverse Transcription Polymerase Chain Reaction, Bisulfite Sequencing, Methylation, Cell Culture, DNA Methylation Assay, Positive Control, Expressing, Control, ChIP-sequencing, MANN-WHITNEY, CpG Methylation Assay