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Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing
Published on: October 15, 2019
Identifying Potential Polymicrobial Pathogens: Moving Beyond Differential Abundance to Driver Taxa
Jiaqi Lu1,2, Xuechen Zhang1,2, Qiongfen Qiu2
1State Key Laboratory for Managing Biotic and Chemical Threats to the Quality and Safety of Agro-products, Ningbo University, Ningbo, 315211, China.
Abstract:
It is now recognized that some diseases of aquatic animals are attributed to polymicrobial pathogens infection. Thus, the traditional view of "one pathogen, one disease" might mislead the identification of multiple pathogens, which in turn impedes the design of probiotics. To address this gap, we explored polymicrobial pathogens based on the origin and timing of increased abundance over shrimp white feces syndrome (WFS) progression. OTU70848 Vibrio fluvialis, OTU35090 V. coralliilyticus, and OTU28721 V. tubiashii were identified as the primary colonizers, whose abundances increased only in individuals that eventually showed disease signs but were stable in healthy subjects over the same timeframe. Notably, the random Forest model revealed that the profiles of the three primary colonizers contributed an overall 91.4% of diagnosing accuracy of shrimp health status. Additionally, NetShift analysis quantified that the three primary colonizers were important "drivers" in the gut microbiotas from healthy to WFS shrimp. For these reasons, the primary colonizers were potential pathogens that contributed to the exacerbation of WFS. By this logic, we further identified a few "drivers" commensals in healthy individuals, such as OUT50531 Demequina sediminicola and OTU_74495 Ruegeria lacuscaerulensis, which directly antagonized the three primary colonizers. The predicted functional pathways involved in energy metabolism, genetic information processing, terpenoids and polyketides metabolism, lipid and amino acid metabolism significantly decreased in diseased shrimp compared with those in healthy cohorts, in concordant with the knowledge that the attenuations of these functional pathways increase shrimp sensitivity to pathogen infection. Collectively, we provide an ecological framework for inferring polymicrobial pathogens and designing antagonized probiotics by quantifying their changed "driver" feature that intimately links shrimp WFS progression. This approach might generalize to the exploring disease etiology for other aquatic animals.
Insights
This study identifies key Vibrio species as primary colonizers in shrimp white feces syndrome (WFS), revealing their role in disease progression and enabling the design of targeted probiotics for aquatic animal health.
Area of Science:
- Aquatic animal pathology
- Microbial ecology
- Disease diagnostics
Background:
- Aquatic animal diseases are often caused by polymicrobial infections, challenging the "one pathogen, one disease" model.
- Accurate identification of multiple pathogens is crucial for developing effective probiotic treatments.
Purpose of the Study:
- To investigate polymicrobial pathogens associated with shrimp white feces syndrome (WFS) based on their abundance changes during disease progression.
- To identify key microbial "drivers" and potential probiotic targets in WFS.
Main Methods:
- Analysis of microbial community composition and abundance changes over WFS progression.
- Application of Random Forest and NetShift models to identify disease-associated pathogens and their ecological roles.
- Prediction of functional pathways affected in diseased shrimp.
Main Results:
- Three Vibrio species (V. fluvialis, V. coralliilyticus, V. tubiashii) were identified as primary colonizers driving WFS.
- These primary colonizers accurately diagnosed shrimp health status (91.4% accuracy) and acted as "drivers" in microbiota shifts.
- Commensal bacteria antagonizing these Vibrio species were identified, and key metabolic pathways were found to be downregulated in diseased shrimp.
Conclusions:
- An ecological framework was established to infer polymicrobial pathogens and design targeted probiotics by quantifying microbial "driver" features.
- This approach offers a method for understanding disease etiology in aquatic animals and developing novel therapeutic strategies.
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