Ningning Liu, Shanghai Jiao Tong University,2020.12.02

Description

Despite recent progress in our understanding of the association between the gut microbiome and colorectal cancer (CRC), multi-kingdom gut microbiome dysbiosis in CRC across cohorts is unexplored. We investigated four-kingdom microbiota alterations using CRC metagenomic datasets of 1,368 samples from 8 distinct geographical cohorts. Integrated analysis identified 20 archaeal, 27 bacterial, 20 fungal and 21 viral species for each single-kingdom diagnostic model. However, our data revealed superior diagnostic accuracy for models constructed with multi-kingdom markers, in particular the addition of fungal species. Specifically, 16 multi-kingdom markers including 11 bacterial, 4 fungal and 1 archaeal feature, achieved good performance in diagnosing patients with CRC (area under the receiver operating characteristic curve (AUROC) = 0.83) and maintained accuracy across 3 independent cohorts. Coabundance analysis of the ecological network revealed associations between bacterial and fungal species, such as Talaromyces islandicus and Clostridium saccharobutylicum. Using metagenome shotgun sequencing data, the predictive power of the microbial functional potential was explored and elevated D-amino acid metabolism and butanoate metabolism were observed in CRC. Interestingly, the diagnostic model based on functional EggNOG genes achieved high accuracy (AUROC = 0.86). Collectively, our findings uncovered CRC-associated microbiota common across cohorts and demonstrate the applicability of multi-kingdom and functional markers as CRC diagnostic tools and, potentially, as therapeutic targets for the treatment of CRC.

OEP001340

Chenfen Zhou, PICB,2021.01.22

Description

OEP001718

Lu Fan, South University of Science and Technology of China,2023.06.15

Description

metagenome data of sponge C. concentrica

OEP004196

Xin Li, Shanghai Institute of Nutrition and Health,CAS,2024.04.30

Description

OEP005254

Jun Yang, Institute of Urban Environment, Chinese Academy of Sciences,2021.03.31

Description

Here we uesed amplicon sequencing in order to explore the habitat preference of prokaryotic community from Xiamen urban parks

OEP001968

Jun Yang, Institute of Urban Environment, Chinese Academy of Sciences,2021.05.26

Description

Here we uesed amplicon sequencing in order to explore the habitat preference of microeukaryotic community from Xiamen urban parks

OEP002253

Wenqian Song, Shanghai Institutes for Biological Sciences,2024.05.15

Description

OEP005302

Ruolin Cheng, Third Institute of Oceanography, Ministry of Natural Resources, China,2024.05.16

Description

Sulfurimonas-associated proviruses and uncultured viral genomes (UViGs)

OEP005305

丽君 周, 中国科学院南京地理与湖泊研究所,2024.05.13

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

Zheng-Jiang Zhu, Chinese Academy Of Sciences,2024.05.13

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