Intensive case study has established dysbiosis in the gut microbiota-shrimp disease relationship; however, variability in experimental design and the diversity of diseases arise the question of whether some gut indicators are robust and universal in response to shrimp health status, irrespective of causal agents. Through an unbiased subject-level meta-analysis framework, we re-analysed 10 studies, including 261 samples, four lifestages and six different diseases (the causal agents are virus, bacterial, eukaryotic pathogens, or unknown). Results showed that shrimp diseases reproducibly altered the structure of gut bacterial community, but not diversity. After ruling out the lifestage-and disease specific-discriminatory taxa (different diseases dependent indicators), we identify 18 common disease-discriminatory taxa (indicative of health status, irrespective of causal agents) that accurately diagnosed (90.0% accuracy) shrimp health status, regardless of different diseases. These optimizations substantially improved the performance (62.6% vs. 90.0%) diagnosing model. The robustness and universality of model were validated for effectiveness via leave-onedataset-out validation and independent cohorts. Interspecies interaction and stability of the gut microbiotas were consistently compromised in diseased shrimp compared with corresponding healthy cohorts, while stochasticity and beta-dispersion exhibited the opposite trend. Collectively, our findings exemplify the utility of microbiome metaanalyses in identifying robust and reproducible features for quantitatively diagnosing disease incidence, and the downstream consequences for shrimp pathogenesis from an ecological prospective.
Increasing evidence has supported dysbiosis in the faecal microbiome along control-adenoma-carcinoma sequence. In contrast, the data is lacking for in situ tumor bacterial community over colorectal cancer (CRC) progression, resulting in the uncertainties of identifying CRC-associated taxa and diagnosing the sequential CRC stages. Through comprehensive collection of benign polyps (BP, N = 45) and the tumors (N = 50) over the four CRC stages, we explored the dynamics of bacterial communities over CRC progression using amplicons sequencing. Canceration was the primarily factor governing the bacterial community, followed by the CRC stages. Besides confirming known CRC-associated taxa using differential abundance, we identified new CRC driver species based on their keystone features in NetShift, including Porphyromonas endodontalis, Ruminococcus torques and Odoribacter splanchnicus. Tumor environments were less selective for stable core community, resulting in heterogeneity in bacterial communities over CRC progression, as supported by higher average variation degree, lower occupancy and specificity compared with BP. Intriguingly, tumors could recruit beneficial taxa antagonizing CRC-associated pathogens at CRC initiation, a pattern known as “cry-for-help”. By distinguishing age- from CRC stage-associated taxa, the top 15 CRC stage-discriminatory taxa contributed an overall 87.4% accuracy in diagnosing BP and each CRC stage, in which no CRC patients were falsely diagnosed as BP. The accuracy of diagnosis model was unbiased by human age and gender. Collectively, our findings provide new CRC-associated taxa and updated interpretations for CRC carcinogenesis from an ecological perspective. Moving beyond stratifying case-control, the CRC-stage discriminatory taxa could add the diagnosis of BP and the four CRC stages, especially the patients with poor pathological feature and un-reproducibility between two observers.
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