Dataset Information

New Genetic Markers Differentiating IPEC and ExPEC Pathotypes-A New Approach to Genome-Wide Analysis Using a New Bioinformatics Tool.

ABSTRACT: The increasingly expanding genomic databases generate the need for new tools for their processing and further use. In the paper, a bioinformatics tool, which is a search engine of microsatellite elements-trinucleotide repeat sequences (TRS) in files of FASTA type-is presented. An innovative approach was applied in the tool, which consists of connecting-within one search engine-both mapping of TRS motifs and extracting sequences that are found between the mapped TRS motifs. Accordingly, we present hereby the tool called TRS-omix, which comprises a new engine for searching information on genomes and enables generation of sets of sequences and their number, providing the basis for making comparisons between genomes. In our paper, we showed one of the possibilities of using the software. Using TRS-omix and other IT tools, we showed that we were able to extract sets of DNA sequences that can be assigned only to the genomes of the extraintestinal pathogenic Escherichia coli strains or to the genomes of the intestinal pathogenic Escherichia coli strains, as well as providing the basis for differentiation of the genomes/strains belonging to each of these clinically essential pathotypes.

SUBMITTER: Majchrzak M

PROVIDER: S-EPMC10002601 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

New Genetic Markers Differentiating IPEC and ExPEC Pathotypes-A New Approach to Genome-Wide Analysis Using a New Bioinformatics Tool.

Majchrzak Marta M Sakowski Sebastian S Waldmajer Jacek J Parniewski Pawel P

International journal of molecular sciences 20230228 5

The increasingly expanding genomic databases generate the need for new tools for their processing and further use. In the paper, a bioinformatics tool, which is a search engine of microsatellite elements-trinucleotide repeat sequences (TRS) in files of FASTA type-is presented. An innovative approach was applied in the tool, which consists of connecting-within one search engine-both mapping of TRS motifs and extracting sequences that are found between the mapped TRS motifs. Accordingly, we presen ...[more]

PMID: 36902111

Similar Datasets

Project description:BackgroundEpithelial ovarian cancer (EOC), as a lethal malignancy in women, is often diagnosed as advanced stages. In contrast, intermediating between benign and malignant tumors, ovarian low malignant potential (LMP) tumors show a good prognosis. However, the differential diagnosis of the two diseases is not ideal, resulting in delays or unnecessary therapies. Therefore, unveiling the molecular differences between LMP and EOC may contribute to differential diagnosis and novel therapeutic and preventive policies development for EOC.MethodsIn this study, three microarray data (GSE9899, GSE57477 and GSE27651) were used to explore the differentially expressed genes (DEGs) between LMP and EOC samples. Then, 5 genes were screened by protein-protein interaction (PPI) network, receiver operating characteristic (ROC), survival and Pearson correlation analysis. Meanwhile, chemical-core gene network construction was performed to identify the potential drugs or risk factors for EOC based on 5 core genes. Finally, we also identified the potential function of the 5 genes for EOC through pathway analysis.ResultsTwo hundred thirty-four DEGs were successfully screened, including 81 up-regulated genes and 153 down-regulated genes. Then, 5 core genes (CCNB1, KIF20A, ASPM, AURKA, and KIF23) were identified through PPI network analysis, ROC analysis, survival and Pearson correlation analysis, which show better diagnostic efficiency and higher prognostic value for EOC. Furthermore, NetworkAnalyst was used to identify top 15 chemicals that link with the 5 core genes. Among them, 11 chemicals were potential drugs and 4 chemicals were risk factors for EOC. Finally, we found that all 5 core genes mainly regulate EOC development via the cell cycle pathway by the bioinformatic analysis.ConclusionBased on an integrated bioinformatic analysis, we identified potential biomarkers, risk factors and drugs for EOC, which may help to provide new ideas for EOC diagnosis, condition appraisal, prevention and treatment in future.

Project description:BackgroundGermline pathogenic variants in the breast cancer type 1 susceptibility gene BRCA1 are associated with a 60% lifetime risk for breast and ovarian cancer. This overall risk estimate is for all BRCA1 variants; obviously, not all variants confer the same risk of developing a disease. In cancer patients, loss of BRCA1 function in tumor tissue has been associated with an increased sensitivity to platinum agents and to poly-(ADP-ribose) polymerase (PARP) inhibitors. For clinical management of both at-risk individuals and cancer patients, it would be important that each identified genetic variant be associated with clinical significance. Unfortunately for the vast majority of variants, the clinical impact is unknown. The availability of results from studies assessing the impact of variants on protein function may provide insight of crucial importance.Results and conclusionWe have collected, curated, and structured the molecular and cellular phenotypic impact of 3654 distinct BRCA1 variants. The data was modeled in triple format, using the variant as a subject, the studied function as the object, and a predicate describing the relation between the two. Each annotation is supported by a fully traceable evidence. The data was captured using standard ontologies to ensure consistency, and enhance searchability and interoperability. We have assessed the extent to which functional defects at the molecular and cellular levels correlate with the clinical interpretation of variants by ClinVar submitters. Approximately 30% of the ClinVar BRCA1 missense variants have some molecular or cellular assay available in the literature. Pathogenic variants (as assigned by ClinVar) have at least some significant functional defect in 94% of testable cases. For benign variants, 77% of ClinVar benign variants, for which neXtProt Cancer variant portal has data, shows either no or mild experimental functional defects. While this does not provide evidence for clinical interpretation of variants, it may provide some guidance for variants of unknown significance, in the absence of more reliable data. The neXtProt Cancer variant portal ( https://www.nextprot.org/portals/breast-cancer ) contains over 6300 observations at the molecular and/or cellular level for BRCA1 variants.

Project description:BackgroundGWAS discoveries on the X-chromosome are underrepresented in the literature primarily because the analytical tools that have been applied were originally designed for autosomal markers. Our objective here is to employ a new robust and flexible tool for chromosome-wide analysis of X-linked markers in complex traits. Orofacial clefts are good candidates for such analysis because of the consistently observed excess of females with cleft palate only (CPO) and excess of males with cleft lip with or without cleft palate (CL/P).MethodsGenotypes for 14,486 X-chromosome SNPs in 1,291 Asian and 1,118 European isolated cleft triads were available from a previously published GWAS. The R-package HAPLIN enables genome-wide-level analyses as well as statistical power simulations for a range of biologic scenarios. We analyzed isolated CL/P and isolated CPO for each ethnicity in HAPLIN, using a sliding-window approach to haplotype analysis and two different statistical models, with and without X-inactivation in females.ResultsThere was a larger number of associations in the Asian versus the European sample, and similar to previous reports that have analyzed the same GWAS dataset using different methods, we identified associations with EFNB1/PJA1 and DMD. In addition, new associations were detected with several other genes, among which KLHL4, TBX22, CPXCR1 and BCOR were noteworthy because of their roles in clefting syndromes. A few of the associations were only detected by one particular X-inactivation model, whereas a few others were only detected in one sex.Discussion/conclusionWe found new support for the involvement of X-linked variants in isolated clefts. The associations were specific for ethnicity, sex and model parameterization, highlighting the need for flexible tools that are capable of detecting and estimating such effects. Further efforts are needed to verify and elucidate the potential roles of EFNB1/PJA1, KLHL4, TBX22, CPXCR1 and BCOR in isolated clefts.

Project description:Companion animals and humans are known to share extraintestinal pathogenic Escherichia coli (ExPEC), but the extent of E. coli sequence types (STs) that cause extraintestinal diseases in dogs is not well understood. Here, we generated whole-genome sequences of 377 ExPEC collected by the University of Melbourne Veterinary Hospital from dogs over an 11-year period from 2007 to 2017. Isolates were predominantly from urogenital tract infections (219, 58.1%), but isolates from gastrointestinal specimens (51, 13.5%), general infections (72, 19.1%), and soft tissue infections (34, 9%) were also represented. A diverse collection of 53 STs were identified, with 18 of these including at least five sequences. The five most prevalent STs were ST372 (69, 18.3%), ST73 (31, 8.2%), ST127 (22, 5.8%), ST80 (19, 5.0%), and ST58 (14, 3.7%). Apart from ST372, all of these are prominent human ExPEC STs. Other common ExPEC STs identified included ST12, ST131, ST95, ST141, ST963, ST1193, ST88, and ST38. Virulence gene profiles, antimicrobial resistance carriage, and trends in plasmid carriage for specific STs were generally reflective of those seen in humans. Many of the prominent STs were observed repetitively over an 11-year time span, indicating their persistence in the dogs in the community, which is most likely driven by household sharing of E. coli between humans and their pets. The case of ST372 as a dominant canine lineage observed sporadically in humans is flagged for further investigation. IMPORTANCE Pathogenic E. coli that causes extraintestinal infections (ExPEC) in humans and canines represents a significant burden in hospital and veterinary settings. Despite the obvious interrelationship between dogs and humans favoring both zoonotic and anthropozoonotic infections, whole-genome sequencing projects examining large numbers of canine-origin ExPEC are lacking. In support of anthropozoonosis, we found that most STs from canine infections are dominant human ExPEC STs (e.g., ST73, ST127, ST131) with similar genomic traits, such as plasmid carriage and virulence gene burden. In contrast, we identified ST372 as the dominant canine ST and a sporadic cause of infection in humans, supporting zoonotic transfer. Furthermore, we highlight that, as is the case in humans, STs in canine disease are consistent over time, implicating the gastrointestinal tract as the major community reservoir, which is likely augmented by exposure to human E. coli via shared diet and proximity.

Dataset Information

New Genetic Markers Differentiating IPEC and ExPEC Pathotypes-A New Approach to Genome-Wide Analysis Using a New Bioinformatics Tool.

Publications

New Genetic Markers Differentiating IPEC and ExPEC Pathotypes-A New Approach to Genome-Wide Analysis Using a New Bioinformatics Tool.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets