CAMI2 plasmids
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB50299 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR8755780_1.fastq.gz | Fastqsanger.gz | |||
| ERR8755780_2.fastq.gz | Fastqsanger.gz | |||
| ERR8755781_1.fastq.gz | Fastqsanger.gz | |||
| ERR8755781_2.fastq.gz | Fastqsanger.gz | |||
| ERR8755782_1.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 16 |
Similar Datasets
Project description:Critical Assessment of Metagenome Interpretation marine raw sequencing data
| PRJEB50297 | ENA
Project description:Critical Assessment of Metagenome Interpretation plant-associated raw sequencing data
| PRJEB50298 | ENA
Project description:Critical Assessment of Metagenome Interpretation strain madness raw sequencing data
| PRJEB50270 | ENA
Project description:Gut plasmids show heightened sensitivity to gut microenvironmental changes compared to their bacterial hosts. To explore their significance in colorectal cancer (CRC), we analyzed metagenomic data from 863 participants (312 CRC, 387 high-risk, 164 low-risk). Plasmid and bacterial profiles were characterized, along with trace elements and metabolites. Differential analysis, functional gene assessment (ARG, MGE, MRG, VFGB), random forest modeling, and structural equation modeling (SEM) were applied. In terms of overall abundance, plasmids in both the high-risk and CRC groups exhibited a decreasing trend. Gut plasmids significantly influenced the functional genes (ARG, MGE, MRG, VFGB) of their bacterial hosts. Six key bacterial hosts (Enterobacterales, Burkholderiales, Hyphomicrobiales, Lactobacillales, Bacteroidales, Campylobacterales) and 12 plasmid markers were identified. The plasmid-based model effectively predicted CRC risk. SEM revealed that trace elements (e.g., Ni), metabolites (e.g., 5-Hydroxytryptophol), and host bacteria (e.g., Campylobacterales, Enterobacterales) predominantly exerted negative effects on most plasmids, whereas Ni exhibited a positive influence on plasmids NZ_CP013564.1, NZ_CP024312.1, and NZ_CP48284.1. We characterized the composition of gut plasmids and their bacterial hosts, explored the impacts of gut plasmids on bacterial functionality, and mapped multi-omics interaction networks linking plasmids, hosts, and metabolic features.
2026-04-24 | MTBLS14358 | MetaboLights
Project description:Gut plasmids show heightened sensitivity to gut microenvironmental changes compared to their bacterial hosts. To explore their significance in colorectal cancer (CRC), we analyzed metagenomic data from 863 participants (312 CRC, 387 high-risk, 164 low-risk). Plasmid and bacterial profiles were characterized, along with trace elements and metabolites. Differential analysis, functional gene assessment (ARG, MGE, MRG, VFGB), random forest modeling, and structural equation modeling (SEM) were applied. In terms of overall abundance, plasmids in both the high-risk and CRC groups exhibited a decreasing trend. Gut plasmids significantly influenced the functional genes (ARG, MGE, MRG, VFGB) of their bacterial hosts. Six key bacterial hosts (Enterobacterales, Burkholderiales, Hyphomicrobiales, Lactobacillales, Bacteroidales, Campylobacterales) and 12 plasmid markers were identified. The plasmid-based model effectively predicted CRC risk. SEM revealed that trace elements (e.g., Ni), metabolites (e.g., 5-Hydroxytryptophol), and host bacteria (e.g., Campylobacterales, Enterobacterales) predominantly exerted negative effects on most plasmids, whereas Ni exhibited a positive influence on plasmids NZ_CP013564.1, NZ_CP024312.1, and NZ_CP48284.1. We characterized the composition of gut plasmids and their bacterial hosts, explored the impacts of gut plasmids on bacterial functionality, and mapped multi-omics interaction networks linking plasmids, hosts, and metabolic features.
2026-04-26 | MTBLS14376 | MetaboLights
Project description:Metagenome sequencing All specimens were collected and immediately stored in a -80 freezer. All BALF samples were subjected to MS. DNA was extracted from BALF using the TIANamp Micro DNA kit (DP316, Tiangen Biotech). DNA libraries were constructed with the end-repair method and then sequenced on the BGI Sequencer platform (BGI Genomics, Shenzhen, China). Bioinformatic pipeline analysis Low-quality and short (<35 bp) reads were removed from raw data using fastp [10]. Remaining reads were mapped to the human reference genome (hg19) using the Burrows-Wheeler method to remove sequences of human origin. Filtered reads were classified with RefSeq, downloaded from NCBI (ftp://ftp.ncbi.nlm.nih.gov/genomes/).
2026-06-30 | E-MTAB-15179 | biostudies-arrayexpress
Project description:Rat gut extrachromosomal elements for the Critical Assessment of Metagenomic Interpretation (CAMI)
| PRJEB20380 | ENA
Project description:These experiments use a barcoded pool of reporter transcripts, each of which encode the same mScarlet-PPIG_LCD fusion protein, but using different degrees of GA-multivalency via codon bias, and containing a different number of constitutive introns. In order to be able to perform experiments using this pool, it was necessary to perform long-read sequencing of the plasmid pool to relate the barcodes in the 3' ends of the reporter to their gene structure. Therefore, we performed long-read sequencing of the plasmid pool (both the original pool used for transfection and the ePB plasmid used for PiggyBac integration). Furthermore, to determine the splicing patterns of the reporter genes, we transfected the plasmid pool into HeLa cells for 16 hours, then performed targeted long-read sequencing of the reporter plasmids via RT-PCR. Note: the Nanopore adapter ligation strategy means that reads can come in either orientation. To determine the gene architectures and barcodes, we used fuzzy string matching. First we matched to various fixed sequences throughout the reporter transcripts to determine the orientation of the read and that the read spanned the full length of the transcript. Then we used the same string matching strategy to detect the presence of the different intronic or exonic sequences - the gene architecture. Then we extracted the associated unique plasmid barcode associated with that gene architecture. Example reporter sequences can be found here: https://benchling.com/faraway/f_/kXCfddtQ-public-reporter-plasmid-maps/ or alternatively, in Supplemental Table 2 of the bioRxiv submission here: https://www.biorxiv.org/content/10.1101/2023.08.21.554177v1.supplementary-material
2025-07-29 | E-MTAB-13330 | biostudies-arrayexpress
Project description:The siRNA transfection includes JAK3 and EZH2 siRNAs. The plasmid transfection includes EZH2 WT and its mutants. We used gene expression data from JAK3 siRNA to test whether it affected epigenetic regulation, and used EZH2 mutants to study how it affected EZH2 canonical function.
2016-07-26 | GSE75680 | GEO
Project description:Plasmid sequencing of marine Enterobacteriales carrying a carbapenemase gene (blaKPC)
| PRJEB91552 | ENA