Gene Fusion Analysis of Positive Charge-Induced Segment Re-orientation in the Tetracycline Resistance Protein

1993 ◽  
Author(s):  
Farrell D. McAfee
Keyword(s):  
Gene Fusion ◽  
Positive Charge ◽  
Tetracycline Resistance ◽  
Resistance Protein ◽  
Fusion Analysis

scholarly journals A New Type of Fusion Analysis Applicable to Many Organisms: Protein Fusions to the URA3 Gene of Yeast

Genetics ◽  
1987 ◽  
Vol 117 (1) ◽  
pp. 5-12
Author(s):  
Eric Alani ◽  
Nancy Kleckner
Keyword(s):  
Gene Fusion ◽  
Enzyme Assay ◽  
Decarboxylase Activity ◽  
Lacz Gene ◽  
Coding Region ◽  
Ura3 Gene ◽  
Promoter Sequences ◽  
E Coli ◽  
New Type ◽  
Fusion Analysis

ABSTRACT We have made constructs that join the promoter sequences and a portion of the coding region of the Saccharomyces cerevisiae HIS4 and GAL1 genes and the E. coli lacZ gene to the sixth codon of the S. cerevisiae URA3 gene (encodes orotidine-5′-phosphate (OMP) decarboxylase) to form three in frame protein fusions. In each case the fusion protein has OMP decarboxylase activity as assayed by complementation tests and this activity is properly regulated. A convenient cassette consisting of the URA3 segment plus some immediately proximal amino acids of HIS4C is available for making URA3 fusions to other proteins of interest. URA3 fusions offer several advantages over other systems for gene fusion analysis: the URA3 specified protein is small and cytosolic; genetic selections exist to identify mutants with either increased or decreased URA3 function in both yeast (S. cerevisiae and Schizosaccharomyces pombe) and bacteria (Escherichia coli and Salmonella typhimurium); and a sensitive OMP decarboxylase enzyme assay is available. Also, OMP decarboxylase activity is present in mammals, Drosophila and plants, so URA3 fusions may eventually be applicable in these other organisms as well.

scholarly journals Protein functional links in Trypanosoma brucei, identified by gene fusion analysis

2011 ◽  
Vol 11 (1) ◽  
Author(s):  
Dimitris Dimitriadis ◽  
V Lila Koumandou ◽  
Philip Trimpalis ◽  
Sophia Kossida
Keyword(s):  
Trypanosoma Brucei ◽  
Gene Fusion ◽  
Fusion Analysis

scholarly journals Next Generation Sequencing for Gene Fusion Analysis in Lung Cancer: A Literature Review

Diagnostics ◽  
2020 ◽  
Vol 10 (8) ◽  
pp. 521
Author(s):  
Rossella Bruno ◽  
Gabriella Fontanini
Keyword(s):  
Lung Cancer ◽  
Next Generation Sequencing ◽  
Gene Fusion ◽  
Repetitive Sequences ◽  
Clinical Samples ◽  
Gene Fusions ◽  
Next Generation ◽  
Hybrid Capture ◽  
Fusion Analysis ◽  
Generation Sequencing

Gene fusions have a pivotal role in non-small cell lung cancer (NSCLC) precision medicine. Several techniques can be used, from fluorescence in situ hybridization and immunohistochemistry to next generation sequencing (NGS). Although several NGS panels are available, gene fusion testing presents more technical challenges than other variants. This is a PubMed-based narrative review aiming to summarize NGS approaches for gene fusion analysis and their performance on NSCLC clinical samples. The analysis can be performed at DNA or RNA levels, using different target enrichment (hybrid-capture or amplicon-based) and sequencing chemistries, with both custom and commercially available panels. DNA sequencing evaluates different alteration types simultaneously, but large introns and repetitive sequences can impact on the performance and it does not discriminate between expressed and unexpressed gene fusions. RNA-based targeted approach analyses and quantifies directly fusion transcripts and is more accurate than DNA panels on tumor tissue, but it can be limited by RNA quality and quantity. On liquid biopsy, satisfying data have been published on circulating tumor DNA hybrid-capture panels. There is not a perfect method for gene fusion analysis, but NGS approaches, though still needing a complete standardization and optimization, present several advantages for the clinical practice.

A case of cutaneous syncytial myoepithelioma with extensive adipocytic metaplasia: Usefulness of EWSR1‐PBX3 gene fusion analysis

2021 ◽  
Author(s):  
Kanade Shimada ◽  
Osamu Ansai ◽  
Tatsuya Katsumi ◽  
Tokiko Deguchi ◽  
Ryota Hayashi ◽  
...  
Keyword(s):  
Gene Fusion ◽  
Fusion Analysis

scholarly journals SAFE Software and FED Database to Uncover Protein-Protein Interactions using Gene Fusion Analysis

2011 ◽  
Vol 8 ◽  
pp. EBO.S8018 ◽  
Author(s):  
Dimosthenis Tsagrasoulis ◽  
Vasilis Danos ◽  
Maria Kissa ◽  
Philip Trimpalis ◽  
V. Lila Koumandou ◽  
...  
Keyword(s):  
Protein Interactions ◽  
Gene Fusion ◽  
Protein Protein Interactions ◽  
Fusion Analysis

scholarly journals Exploration of the Neisseria resistome reveals resistance mechanisms in commensals that may be acquired by N. gonorrhoeae through horizontal gene transfer

2020 ◽  
Author(s):  
Michael A Fiore ◽  
Jordan C Raisman ◽  
Narayan H Wong ◽  
André O Hudson ◽  
Crista B Wadsworth
Keyword(s):  
Antibiotic Resistance ◽  
Antibiotic Resistance Genes ◽  
Tetracycline Resistance ◽  
Dna Gyrase ◽  
Resistance Mechanisms ◽  
Gene Identifier ◽  
Prospective Surveillance ◽  
Beta Lactamases ◽  
Cephalosporin Resistance ◽  
Resistance Protein

Non-pathogenic Neisseria have repeatedly been demonstrated to transfer antibiotic resistance genes to their pathogenic relative, Neisseria gonorrhoeae. However, the resistance genotypes and subsequent phenotypes of non-pathogens within the genus have been studied and described less frequently. Here, we use Etests to characterize the minimum inhibitory concentrations (MICs) of a panel of Neisseria (n=26) - including several commensal species - acquired from the CDC & FDA's Antibiotic Resistance (AR) Isolate Bank to a suite of diverse antibiotics. We furthermore use whole genome sequencing and the Comprehensive Antibiotic Resistance Database (CARD) Resistance Gene Identifier (RGI) platform to predict possible causal resistance-encoding mutations. Within this panel, resistant isolates to all tested antimicrobials including penicillin (n=5/26), ceftriaxone (n=2/26), cefixime (n=3/26), tetracycline (n=10/26), azithromycin (n=11/26), and ciprofloxacin (n=4/26) were found. In total we identify 63 distinct mutations predicted by RGI to be involved in resistance. The presence of several of these mutations had clear associations with increases in MIC such as: DNA gyrase subunit A (gyrA) (S91F) and ciprofloxacin, tetracycline resistance protein (tetM) and 30S ribosomal protein S10 (rpsJ) (V57M) and tetracycline, and TEM-type beta-lactamases and penicillin. However, mutations with strong associations to macrolide and cephalosporin resistance were not conclusive. This work serves as an initial exploration into the resistance-encoding mutations harbored by non-pathogenic Neisseria, which will ultimately aid in prospective surveillance for novel resistance mechanisms that may be rapidly acquired by N. gonorrhoeae.

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