Subject: Life Sciences, Biochemistry Keywords: 16S rRNA gene; bacterial diversity; catabolic activity; cultivation; Pannonian steppe; pyrosequencing
Online: 22 June 2021 (14:26:55 CEST)
In this study, we examined the effect of salinity and alkalinity on the metabolic potential and taxonomic composition of microbiota inhabiting the sodic soils at different plant communities. The soil samples were collected in the Pannonian steppe (Hungary, Central Europe) under extreme dry and wet weather conditions. The metabolic profiles of microorganisms were analysed by MicroResp method, the bacterial diversity was assessed by cultivation and next generation amplicon sequencing based on the 16S rRNA gene. Catabolic profiles of microbial communities varied primarily according to the alkali vegetation types. Most members of the strain collection were identified as plant associated and halophilic/alkaliphilic species of Micrococcus, Nesterenkonia, Nocardiopsis, Streptomyces (Actinobacteria) and Bacillus, Paenibacillus (Firmicutes) genera. Based on the pyrosequencing data, the relative abundance of phyla Proteobacteria, Actinobacteria, Acidobacteria, Gemmatimonadetes and Bacteroidetes changed also mainly with the sample types, indicating distinctions within the compositions of bacterial communities according to the sodic soil alkalinity-salinity gradient. The effect of weather extremes was the most pronounced in the relative abundance of phyla Actinobacteria and Acidobacteria. The type of alkali vegetation caused greater shifts in both the diversity and activity of sodic soil microbial communities than the extreme aridity and moisture.
ARTICLE | doi:10.20944/preprints202211.0513.v1
Subject: Medicine & Pharmacology, Oncology & Oncogenics Keywords: breast cancer; small tumors; DNA methylation; CCDC181; ZNF177; fibroadenoma; biomarker; MS-HRM; pyrosequencing
Online: 28 November 2022 (10:51:17 CET)
The DNA methylation profile of breast cancer differs from that in healthy tissue and can be used as a diagnostic and prognostic biomarker. Aim of the study: to compare gene methylation in small malignant breast tumors less than 2 cm and in healthy tissue and fibroadenoma. Methylation of the following 15 genes was studied: MAST1, PRDM14, ZNF177, DNM2, SSH1, AP2M1, CACNA1E, CPEB4, DLGAP2, CCDC181, GCM2, ITPRIPL1, POM121L2, KCNQ1, TIMP3. Methods: analysis was made by our modified MS-HRM method followed confirmation of the results by pyrosequencing. The genes were selected from publications that studied DNA methylation in breast cancer with high genome coverage. The study group included 48 samples of breast cancer, the control group included 24 samples of fibroadenoma and 24 samples of healthy tissue. Results: significant differences were found in methylation of 8 genes: CCDC181, GSM2, ITPRIPL1, ZNF177, CACNA1E, DLGAP2, TIMP3 (all р<0.001), and PRDM14 (р=0.002). The most accurate diagnostic value, based on logistic regression, was shown with the compound of two genes – CCDC181 and ZNF177 (AUC=0.99) in pyrosequencing analysis. Conclusion: small breast cancer tumors have a specific DNA methylation profile that distinguishes them from healthy tissue and benign proliferative lesions.
ARTICLE | doi:10.20944/preprints201809.0428.v1
Subject: Biology, Other Keywords: inter- and intra-host nucleotide variations; Hepatitis A virus; next-generation sequencing; pyrosequencing
Online: 21 September 2018 (04:59:34 CEST)
The accurate virus detection, strain discrimination, and source attribution of contaminated food items remains a persistent challenge because of the high mutation rates anticipated to occur in foodborne RNA viruses, such as Hepatitis A virus (HAV). This has led to predictions of the existence of more than one sequence variant between the hosts (inter-host) or within an individual host (intra-host). However, there have been no reports of intra-host variants from an infected single individual, and little is known about the accuracy of the single nucleotide variations (SNVs) calling with various methods. In this study, the presence and identity of viral SNVs, either between HAV clinical specimens or among a series of samples derived from HAV clone1-infected FRhK4 cells, were determined following analyses of nucleotide sequences generated using next-generation sequencing (NGS) and pyrosequencing methods. The results demonstrate the co-existence of inter- and intra-host variants both in the clinical specimens and the cultured samples. The discovery and confirmation of multi-viral RNAs in an infected individual is dependent on the strain discrimination at the SNV level, and critical for successful outbreak traceback and source attribution investigations. The detection of SNVs in a time series of HAV infected FRhK4 cells improved our understanding on the mutation dynamics determined probably by different selective pressures. Additionally, it demonstrated that NGS could potentially provide a valuable investigative approach toward SNV detection and identification for other RNA viruses.