Computational protocol: Pine Defensive Monoterpene α-Pinene Influences the Feeding Behavior of Dendroctonus valens and Its Gut Bacterial Community Structure

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[…] The beetles from 0 mg/g α-pinene phloem media and 9 mg/g α-pinene phloem media after 6 h (0 mg/g α-pinene 6 h feeding group and 9 mg/g α-pinene 6 h feeding group) and 48 h (0 mg/g α-pinene 48 h feeding group and 9 mg/g α-pinene 48 h feeding group) were dissected, and then the bacteria genomic DNA of each insect gut sample was extracted by using a TIANamp Bacteria DNA kit (TianGen, Beijing, China) according to the manufacturer’s instructions, respectively. The PCR reactions were carried out in a 20 μL of solution containing 10 ng of DNA, 1 μL of 10 μM of each primer, 2 μL of 2.5 mM dNTPs, 0.3 μL Fastpfu polymerase (Transgene, Beijing, China), and 4 μL 5× Fastpfu buffer. The amplifications were performed in an ABI GeneAmp® 9700 thermal cycler (Applied Biosystems, Foster City, CA, USA) with an initial denaturation step at 95 °C for 10 min followed by 30 cycles of annealing and extending (each cycle occurred at 95 °C for 30 s followed by 55 °C for 30 s and an extension step at 72 °C for 45 s) and the final extension at 72 °C for 10 min using 16S rRNA primers 341F (5′-CCTAYGGGRBGCASCAG-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′) []. The final PCR products were analyzed by electrophoresis in 1.5% agarose gel followed by staining with ethidium bromide and visualization under ultraviolet light. The purified amplicons were pyrosequenced on an Illumina platform (Illumina MiSeq PE250, Illumina, CA, USA).Paired-end reads were assembled with FLASH (V1.2.7, Available online: www.ccb.jhu.edu) and low-quality reads were filtered using the QIIME (Quantitative Insights Into Microbial Ecology) software packages (V1.9.0, Available online: www.qiime.org) with default parameters []. Chimeras were checked and removed with UCHIME [] and qualified sequences were clustered into Operational Taxonomic Units (OTUs) at 97% sequence similarity with a UPARSE algorithm []. The representative OTU was selected based on the most abundant sequence in each OTU, and then taxonomic identification was performed using the RDP classifier [] algorithm implemented in QIIME and using the Greengene database under a confidence threshold of 80% (Available online: http://greengenes.secondgenome.com) []. [...] In comparisons of the boring length of beetles between 0 and 9 mg/g α-pinene feeding groups, means of cases were tested using independent t-test or Mann–Whitney U-test, depending on the results of the test of normality and homogeneity of variance. Data were analyzed using SPSS 12.0 (SPSS Inc., Chicago, IL, USA) for Windows, and figures were drawn using Origin 8.5 (Origin Lab Corporation, Northampton, MA, USA).For MiSeq data analysis, rarefaction curves were estimated using the “alpha_rarefaction.py” script in QIIME to test whether the sequencing efforts adequately represented the bacterial diversity within each sample. Two richness estimators (the abundance-based coverage estimator (ACE) and a nonparametric richness estimator based on distribution of singletons and doubletons (Chao1)) and two diversity indices (Shannon and Simpson index) were calculated for the samples using the “alpha_diversity.py” script in QIIME. The diversity indices of four groups and the relative abundances of different genera were compared using One-way ANOVA test followed by Bonferroni test (equal variances) or One-way Brown-Forsythe’s ANOVA test followed by Dunnett’s T3 test (unequal variances). Non-metric multidimensional scaling (NMDS) was used to visualize the phylogenetic distance (Jaccard similarity) between the bacterial communities from different samples. Composition differences were tested using ANOSIM with 10,000 permutations using PAST software [,]. The representative sequences of all OTUs were used to construct neighbor-joining trees. The phylogenetic tree together with sample sequence abundance data were used for weighted Unifrac PCoA (principal coordinate analysis) which considers both relative abundance and different branch lengths in a tree, through the online Fast Unifrac program []. A Permutational Multivariate Analysis of Variance based on the weighted UniFrac distance (PERMANOVA, “PermanovaG” function in the “GUniFrac” package of R) was used to test for differences in community composition between four sample groups []. […]

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