Similar Datasets
Project description:Our group recently transcriptomically characterized coculture growth between Streptococcus mutans and several species of commensal streptococci (Rose et al, 2023). However, these experiments were carried out in our lab-based experimental medium, tryptone and yeast extract (TY-). To understand whether culturing these species within a medium that more closely mimics their natural environment alters the interaction, we evaluated both monoculture and coculture growth between the dental caries pathogen Streptococcus mutans and oral commensal species Streptococcus oralis in a half TY- / half human saliva mix that was optimally chosen based on our initial characterization of oral streptococci behaviors in medium mixes containing saliva. Our results surprising show that inclusion of saliva enhances the competition of Streptococcus mutans against commensal streptococci through upregulation of carbohydrate uptake and glycolytic pathways.
2023-08-22 | GSE239483 | GEO
Project description:We performed shallow whole genome sequencing (WGS) on circulating free (cf)DNA extracted from plasma or cerebrospinal fluid (CSF), and shallow WGS on the tissue DNA extracted from the biopsy in order to evaluate the correlation between the two biomaterials. After library construction and sequencing (Hiseq3000 or Ion Proton), copy number variations were called with WisecondorX.
2021-11-17 | E-MTAB-10548 | biostudies-arrayexpress
Project description:Whole genome sequencing (WGS) of tongue cancer samples and cell line was performed to identify the fusion gene translocation breakpoint. WGS raw data was aligned to human reference genome (GRCh38.p12) using BWA-MEM (v0.7.17). The BAM files generated were further analysed using SvABA (v1.1.3) tool to identify translocation breakpoints. The translocation breakpoints were annotated using custom scripts, using the reference GENCODE GTF (v30). The fusion breakpoints identified in the SvABA analysis were additionally confirmed using MANTA tool (v1.6.0).
2024-02-17 | E-MTAB-12534 | biostudies-arrayexpress
Project description:Our group recently transcriptomically characterized coculture growth between Streptococcus mutans and several species of commensal streptococci (Rose et al, 2023; Choi et al 2024). One interaction that stood out was with Streptococcus mitis ATCC 49456, which completely inhibited the growth of S. mutans during biofilm formation. This is due to abudant hydrogen peroxide production by S. mitis ATCC 49456, 3-5x higher than other oral commensal streptococci we have worked with. To understand how the transcriptome of S. mutans is modified in coculture with a high hydrogen peroxide producer, we evaluated the transcriptome during monoculture or coculture growth between the two strains. Our results show differential gene expression (DEGs) in S. mutans that follows other trends we have documented previously with other commensal Streptococcus species, as well as DEGs specific to the interaction with S. mitis.
2024-08-02 | GSE273140 | GEO
Project description:In principle, whole-genome sequencing (WGS) of the human genome even at low coverage offers higher resolution for genomic copy number variation (CNV) detection compared to array-based technologies, which is currently the first-tier approach in clinical cytogenetics. There are, however, obstacles in replacing array-based CNV detection with that of low-coverage WGS such as cost, turnaround time, and lack of systematic performance comparisons. With technological advances in WGS in terms of library preparation, instrument platforms, and data analysis algorithms, obstacles imposed by cost and turnaround time are fading. However, a systematic performance comparison between array and low-coverage WGS-based CNV detection has yet to be performed. Here, we compared the CNV detection capabilities between WGS (short-insert, 3kb-, and 5kb-mate-pair libraries) at 1X, 3X, and 5X coverages and standardly used high-resolution arrays in the genome of 1000-Genomes-Project CEU genome NA12878. CNV detection was performed using standard analysis methods, and the results were then compared to a list of Gold Standard NA12878 CNVs distilled from the 1000-Genomes Project. Overall, low-coverage WGS is able to detect drastically more (approximately 5 fold more on average) Gold Standard CNVs compared to arrays and is accompanied with fewer CNV calls without secondary validation. Furthermore, we also show that WGS (at ≥1X coverage) is able to detect all seven validated deletions larger than 100 kb in the NA12878 genome whereas only one of such deletions is detected in most arrays. Finally, we show that the much larger 15 Mbp Cri-du-chat deletion can be clearly seen at even 1X coverage from short-insert WGS.
2018-06-26 | GSE105092 | GEO