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. 2024 Jan 19;19(1):e0289215.
doi: 10.1371/journal.pone.0289215. eCollection 2024.

Bacterial microbiome associated with cigarette beetle Lasioderma serricorne (F.) and its microbial plasticity in relation to diet sources

Affiliations

Bacterial microbiome associated with cigarette beetle Lasioderma serricorne (F.) and its microbial plasticity in relation to diet sources

Thanga Suja Srinivasan et al. PLoS One. .

Abstract

Insect-microbial symbiosis contributes positively to the physiology of the insect and diet is considered as one important factor determining microbial symbiosis. In this study, we have characterized the microbiota of cigarette beetle, Lasioderma serricorne (Fabricius) on different diets and phases. The beetles were reared on different diet sources (exposed phase) for six generations and were reverted to their natal source (reverted phase) and further maintained for six more generations. The bacterial diversity and richness were higher in the exposed phase and once reverted to the natal source, the microbial abundance has re-assembled according to the natal diet source. There was re-assemblage of microbial composition in accordance to the diet and the bacterial cells are able to establish and proliferate on reverting to their natal source. The bacterial composition of the beetle was mainly dynamic and not transient where the bacterial cells were maintained at low abundance and were re-established according to the diet source. Overall, we found that the microbiota of cigarette beetle to be dynamic and bacterial composition to re-assemble in a diet-specific manner. The study provides insights on diet associated microbial plasticity of cigarette beetle and a further comprehensive understanding on mechanisms involved in microbial plasticity will help develop novel pest management strategies for this invasive insect pest.

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Conflict of interest statement

The authors have declared that no competing interests exist

Figures

Fig 1
Fig 1. Details of the experiments with cigarette beetle and microbiome sampling.
Cigarette beetle were initially cultured on wheat as natal (N) source (called as natal phase) for 6 generations (G) and sampled for microbiome analysis at N- 6G. Then natal phase colonies were cultured for another 6G on each of exposed (E) diets called as exposed phase colonies and beetles sampled for microbiome at E-6G. The colonies were continued for a further 6G on wheat diet called as reverted (R) phase with microbiome sampling at R-6G. Six biological replicates were maintained for each treatment and three technical replicates for 16s DNA sequencing.
Fig 2
Fig 2. Bacterial structure of cigarette beetle microbiome at phylum and genus level.
Bar-plots show the abundance and distribution of the A) 20 most abundant phylum and B) 30 most abundant genera across diets.
Fig 3
Fig 3. Alpha diversity indices of cigarette beetle microbiome across phases.
Statistically significant values * = P ≤ 0.05, ** = P ≤ 0.01, *** = P ≤ 0.005; df = 2.
Fig 4
Fig 4. Heat map of the top 35 abundant families showing the relative abundance of the bacteria taxa across diet sources.
Fig 5
Fig 5. The relative abundance of genus Wolbachia associated with cigarette beetle across diets.
Error bars are indicated, lowercase letters indicate homogenous groups (Tukey, p ≤ .05; df = 8).
Fig 6
Fig 6. Principal coordinate analysis (PCoA) of community structure of cigarette beetle across diet sources (df = 8) and phases (df = 2).
Each symbol represents phase and corresponding color represents diet. Colored triangle represents natal phase; colored inverted triangle, diamond, circle, square represents exposed phase; colorless inverted triangle, diamond, circle and square represents reverted phase.
Fig 7
Fig 7. Venn diagram representing the shared genus of cigarette beetle microbiome across diet source.
Fig 8
Fig 8. Comparison on the relative abundance of key genera associated with the microbiomes of cigarette beetle from natal phase and reverted phase after six generations.
Statistically significant values * = P ≤ 0.05, ** = P ≤ 0.01, *** = P ≤ 0.005; df = 4.

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