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PROJ
Methylparaben changes the community composition, structure and assembly processes of free-living bacteria, phytoplankton and zooplankton
Description
Parabens are widely used as preservatives and bactericides in food, pharmaceuticals, and cosmetics, and are commonly found as contaminants in river and lake ecosystems. However, there are few studies on the effects of parabens on phytoplankton, zooplankton, and bacterial communities in aquatic environment.
OEP005301
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PROJ
Plasma metabolomics reveals the shared and distinct metabolic disturbance associated with cardiovascular events in patients with coronary artery disease
Description
The predictive capability of metabolic biomarkers was evaluated in the validation set. A total of 23 shared differential metabolites were associated with the composite of cardiovascular events, independent of TIMI variables, NT-proBNP and hs-cTnT. The majority were middle and long chain acylcarnitines (odds ratios ranged from 1.38 to 1.85). Distinct metabolic patterns for individual events were revealed, and glycerophospholipids alteration was specific to HF. Pathway analyses revealed tricarboxylic acid cycle played a crucial role in the development of cardiovascular events. The inclusion of metabolites into TIMI variables improved the predictive capability for the composite of cardiovascular events (AUC 0.70, 95%CI 0.64~0.75). Notably, the addition of metabolites to TIMI variables, hs-cTnT and NT-proBNP caused significant enhancement in HF risk prediction, with the AUCs of 0.91 (95%CI 0.86~0.94), 0.89 (95%CI 0.84~0.94) and 0.94 (95%CI 0.91~0.97), respectively. Acylcarnitines is the shared metabolic dysregulation in the composite of cardiovascular events, while glycerophospholipids alteration is HF specific. These findings highlight the potential utility of plasma metabolites in early and tailored risk prediction in CAD patients.
OEP005299
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PROJ
Fecal metagenomics of mice treated with Bifidobacterium infantis
Description
Infants with higher abundance of Bifidobacteria have fewer mobile genetic elements associated with more antimicrobial resistance (AMR) in the gut, and the effect of Bifidobacteria on the mechanisms of AMR and dissemination of AMR in the host gut flora is unknown. Here, we treated seven mice with Bifidobacterium infantis by gavage for 13 days, while eight mice were set up as a control group to observe the effects of B. infantis supplementation on the fecal metagenomics of mice.
OEP005300
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PROJ
The mNGS analysis of infective endocarditis
Description
We constructed a protein sequence database tailored to IE used for metaproteomic analyses, derived from matched metagenomes, which were generated from metagenomic next-generation sequencing (mNGS) of ten aliquots pooled and packaged from 158 vegetation samples that matched the ones used for metaproteomics in infective endocarditis.
OEP005268
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PROJ
ECS based on NGS in Southern Chinese couples
Description
Comprehensive expanded carrier screening using next-generation sequencing in Southern Chinese couples
OEP005278
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PROJ
Analysis of blood methylation quantitative trait loci in East Asians identifies ancestry-specific effects associated with complex trait variation
Description
This project has included individual-level genotype data (SNP chip, methy_3523_qc0.01.bed,bim,fam) and DNA methylation data (Illumina EPIC, methy_3523.rdata) of 3523 Han Chinese (NSPT), and also the individual-level genotype data (SNP chip, 200505_960Sps_passed.vcf) and DNAm data (Illumina EPIC, beta_norm.rda) of additional 798 individuals (CGZ), which are in controlled access. The individual-level genotype data is not available because of IRB restriction due to privacy concern. The individual-level DNA methylation data can be available with reasonable requests. The project also included mQTL summary statistics (cis1_10.zip, cis11_22.zip, lcis.zip, trans.zip) with threshold of 1e-10 in 3523 Han Chinese (NSPT), SNP information (effect allele equals to minor allele, and effect allele frequency) in NSPT (snp_chr1_22.info.zip), the replication for these mQTLs (CGZ_mQTL.rep2.csv) in the CGZ cohort, and blood cell-lineage (lymphoid- and myeloid-) mQTLs estimated by using CELLDMC (cts_mQTL_info.Rd). These data are available for download. Data usage shall be in full compliance with the Regulations on Management of Human Genetic Resources in China. Use of this data requires a citation of our article. For controlled access data, requests are normally processed within two weeks. A template of the data sharing and confidentiality agreement will be sent to the applicant, and the data can be used within the permitted scope after the data sharing and confidentiality agreement has been signed.
OEP002902
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PROJ
Hspa1b
Description
RNA-binding profiles of Hspa1b as an RNA-binding protein in the mouse hippocampus
OEP005267
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PROJ
KD_BAs
Description
Ketogenic diet-induced bile acids protect against obesity through reduced calorie absorption
OEP005260
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PROJ
Native microbial populations in the alkaline mines in Panxi Area, Southwest China
Description
Amplicon and metagenomic datasets of two representative iron mines in the Panxi Mining Area, Southwest China
OEP005245
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PROJ
Cross-feeding interactions among the major degrader and rare non-degraders in a bacterial consortium reveal the role of bacterial dark matter in lignin degradation
Description
Lignin is the abundant aromatic carbon polymer on earth. Its bioconversion is essential in global carbon cycle and bioenergy production. Microbial communities, which have evolved versatile enzymes and pathways, undoubtedly play a vital role in lignin biodegradation. The interactions among members in a community greatly affect the performance outcome, yet it's a significant challenge to mechanistically unravel such complex interactions. In this study, we developed the marine lignin degrading bacterial consortium (LD), through “top-down” enrichment. 16s rRNA amplicon sequencing revealed that LD is dominated by Pluralibacter gergoviae (> 98%), a lignin degrader. Further physiological analysis demonstrated that the additional unaddressed members, as the dark matter, hidden behind P. gergoviae to promote growth and lignin degradation. Genome-scale metabolic models were constructed for P. gergoviae and three non-lignin degrading species, which represent the top four members in LD consortium. The integrated in silico simulation predicted that growth/degradation is boosted by metabolic exchanges between members and enable us to construct the “bottom-up” four-species synthetic community. The performance of synthetic consortia validated the predication and revealed that the non-degraders survived on metabolic intermediates from P. gergoviae, including succinate, malate, serine and PCA derivates. In return, the non-degraders fed back glycerol, aspartate, alanine, fumarate to P. gergoviae to stimulate growth and further enhance lignin degradation. Our study uncovered the black-box of LD consortium, in which the dark matter interacts to form a syntrophy with P. gergoviae for lignin catabolism. Also, it provided a valuable step forward in manipulating microbiomes for biotechnology development.
OEP004885