title: Integrating gut microbiota immaturity and disease-discriminatory taxa to diagnose the initiation and severity of shrimp disease.
abstract: Increasing evidence has emerged a tight link among the gut microbiota, host age and health status. This osculating interplay impedes the definition of gut microbiome features associated with host health from that in developmental stages. Consequently, gut microbiota-based prediction of health status is promising yet not well established. Here we firstly tracked shrimp gut microbiota (N = 118) over an entire cycle of culture; shrimp either stayed healthy or progressively transitioned into severe disease. The results showed that the gut microbiota were significantly distinct over shrimp developmental stages and disease progression. Null model and phylogenetic-based mean nearest taxon distance (MNTD) analyses indicated that deterministic processes that governed gut community became less important as the shrimp aged and disease progressed. The predicted gut microbiota age (using the profiles of age-discriminatory bacterial species as independent variables) fitted well (r = 0.996; P < 0.001) with the age of healthy subjects, while this defined trend was disrupted by disease. Microbiota-for-age Z-scores (MAZ, here defined as immaturity) were relative stable among healthy shrimp, but sharply decreased when disease emerged. By distinguishing between age- and disease- discriminatory taxa, we developed a model, bacterial indicators of shrimp health status, to diagnose disease from healthy subjects with 91.5% accuracy. Notably, the relative abundances of the bacterial indicators were indicative for shrimp disease severity. These findings, in aggregate, add our understanding on the gut community assembly patterns over shrimp developmental stages and disease progression. In addition, shrimp disease initiation and severity can be accurately diagnosed using gut microbiota immaturity and bacterial indicators.
authors.affiliation: School of Marine Sciences, Ningbo University, Ningbo, 315211, China.|Collaborative Innovation Center for Zhejiang Marine High-Efficiency and Healthy Aquaculture, Ningbo, 315211, China.
authors.forename: Jinbo
authors.initials: J
authors.lastname: Xiong
authors.affiliation: School of Marine Sciences, Ningbo University, Ningbo, 315211, China.
authors.forename: Jinyong
authors.initials: J
authors.lastname: Zhu
authors.affiliation: School of Marine Sciences, Ningbo University, Ningbo, 315211, China.|Collaborative Innovation Center for Zhejiang Marine High-Efficiency and Healthy Aquaculture, Ningbo, 315211, China.
authors.forename: Wenfang
authors.initials: W
authors.lastname: Dai
authors.affiliation: Key Laboratory of Marine Biogenetic Resources, Third Institute of Oceanography, State of Oceanic Administration, Xiamen, 361006, China.
authors.forename: Chunming
authors.initials: C
authors.lastname: Dong
authors.affiliation: School of Marine Sciences, Ningbo University, Ningbo, 315211, China.
authors.forename: Qiongfen
authors.initials: Q
authors.lastname: Qiu
authors.affiliation: School of Marine Sciences, Ningbo University, Ningbo, 315211, China.|Collaborative Innovation Center for Zhejiang Marine High-Efficiency and Healthy Aquaculture, Ningbo, 315211, China.
authors.forename: Chenghua
authors.initials: C
authors.lastname: Li
mesh_terms: D000818:Animals; D003445:Crustacea / Q000382:microbiology*; D017753:Ecosystem; D005260:Female; D000069196:Gastrointestinal Microbiome; D006801:Humans; D010802:Phylogeny