Robust bacterial co-occurence community structures are independent of r- and K-selection history

Pettersen, Jakob Peder; Gundersen, Madeleine S.; Almaas, Eivind

doi:10.1038/s41598-021-03018-z

Cited by 3 publications

(1 citation statement)

References 50 publications

(62 reference statements)

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“…Analyzing the dynamic network of the microbiome offers the potential to predict changes like the microbial network. Pettersen et al ( 93 ) explored the significant difference between K-selection (via continuous feeding) and R-selection (via pulsed feeding) utilizing dynamic data network modularity analysis and proposed that clustering may be a similar ecological niche preference among the involved bacteria. The impact of different intervention strategies on the pattern and the role of the microbiome can be assessed using micro-ecological dynamic network analysis.…”

Section: Network Modeling Bridges the Gap Between Mechanistic Modelin...mentioning

confidence: 99%

Progress on network modeling and analysis of gut microecology: a review

Luo,

Zhu,

Jia

et al. 2024

Appl Environ Microbiol

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The gut microecological network is a complex microbial community within the human body that plays a key role in linking dietary nutrition and host physiology. To understand the complex relationships among microbes and their functions within this community, network analysis has emerged as a powerful tool. By representing the interactions between microbes and their associated omics data as a network, we can gain a comprehensive understanding of the ecological mechanisms that drive the human gut microbiota. In addition, the network-based approach provides a more intuitive analysis of the gut microbiota, simplifying the study of its complex dynamics and interdependencies. This review provides a comprehensive overview of the methods used to construct and analyze networks in the context of gut microecological background. We discuss various types of network modeling approaches, including co-occurrence networks, causal networks, dynamic networks, and multi-omics networks, and describe the analytical techniques used to identify important network properties. We also highlight the challenges and limitations of network modeling in this area, such as data scarcity and heterogeneity, and provide future research directions to overcome these limitations. By exploring these network-based methods, researchers can gain valuable insights into the intricate relationships and functional roles of microbial communities within the gut, ultimately advancing our understanding of the gut microbiota’s impact on human health.

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Section: Network Modeling Bridges the Gap Between Mechanistic Modelin...mentioning

confidence: 99%

Progress on network modeling and analysis of gut microecology: a review

Luo,

Zhu,

Jia

et al. 2024

Appl Environ Microbiol

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Influence of ammonia nitrogen management strategies on microbial communities in biofloc-based aquaculture systems

Chen,

Sun,

Tian

et al. 2023

Science of The Total Environment

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Bacterial community structures and dynamics associated with rotated positioning syndrome in gilthead sea bream (Sparus aurata) larviculture

Bel Mokhtar,

Apostolopoulou,

Koumoundouros

et al. 2024

Front. Aquac.

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IntroductionThe availability of high-quality gilthead seabream (Sparus aurata) larvae in larviculture represents a major bottleneck to the aquaculture. This challenge can be compounded by losses resulting from the emergence of a clinical disorder’s symptomatology. In this study, the observed syndrome included a rotated positioning of the larval sagittal plane and in most cases leading eventually to death. MethodsHerein, we examined using amplicon sequencing of the 16S rDNA the bacterial communities associated with S. aurata larvae at different conditions (including both fish with no evidence of the syndrome and fish with syndrome) during the early developmental stages along with the contribution of rearing water, organic matter and provided feed in the microbiota during an experiment of 18 days. ResultsOver the development of larvae, differences were observed in the bacterial composition between healthy and symptomatic larvae as well as between components of the system. A remarkable presence of members of the Psychrobacter genus was observed in symptomatic larvae with a significant increase at 18dph. The healthy larvae harbor different bacterial profile with a dominance of Vibrio and Bacillus genera during 3-8dph, various members of Alphaproteobacteria during 11-14dph and Marinifilum at 18dph. The rearing water showed a different bacterial profile compared to the other components, with a slight effect of healthy larvae at 3-8dph. The bacteriome of feeds provided during the rearing of larvae was found to be diverse. Chlorella was mainly dominated by members of Firmicutes, while Rotifer and Artemia were mainly dominated by members of Proteobacteria including different species of Psychrobacter. At 18dph, Artemia feed seems to affect the symptomatic larvae bacteriome, where it enhanced the presence of Psychrobacter spp.DiscussionInterestingly, the comparative network analysis at 18dph indicated that the bacterial associations in symptomatic larvae were primarily driven by members of the Psychrobacter genus. While various phyla contributed to bacterial associations in healthy larvae with different frequencies including mainly members of Proteobacteria, Bacteroidota and Firmicutes phyla. Finally, the Gammaproteobacteria/Alphaproteobacteria ratio was found to be related to the health condition of larvae. This study provides valuable information which can be used as indicators for monitoring the health status of S. aurata larvae.

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Robust bacterial co-occurence community structures are independent of r- and K-selection history

Cited by 3 publications

References 50 publications

Progress on network modeling and analysis of gut microecology: a review

Progress on network modeling and analysis of gut microecology: a review

Influence of ammonia nitrogen management strategies on microbial communities in biofloc-based aquaculture systems

Bacterial community structures and dynamics associated with rotated positioning syndrome in gilthead sea bream (Sparus aurata) larviculture

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