No effect of Bt Cry1Ie toxin on bacterial diversity in the midgut of the Chinese honey bees, Apis cerana cerana (Hymenoptera, Apidae)

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1 No effect of Bt Cry1Ie toxin on bacterial diversity in the midgut of the Chinese honey bees, Apis cerana cerana (Hymenoptera, Apidae) Hui-Ru Jia 1, 2, Ping-Li Dai 1 *, Li-Li Geng 2, Cameron J. Jack 3, Yun-He Li 2, Yan-Yan Wu 1, Qing-Yun Diao 1, James D. Ellis 3 1. Ministry Key Laboratory of Pollinating Insect Biology, Institute of Apicultural Research, Chinese Academy of Agricultural Sciences, Beijing , China 2. State Key Laboratory for Biology of Plant Diseases and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing , China 3. Honey Bee Research and Extension Laboratory, Department of Entomology and Nematology, University of Florida, Gainesville, Florida 32611, USA *Corresponding author. Tel. (fax): address: daipingli@caas.cn. Additional information Table S1 16S rrna gene copy numbers per sample. Table S2 Statistical analysis of the copy number of 16S rrna gene of each treatment by one-way ANOVA (SPSS. 16.0). Table S3 OUT's data. Data were obtained using the Illumina Miseq2500-pyrosequencing. Table S4 The 10 most abundant bacterial genera within each sample. Table S5 Statistical analysis of the composition of the 10 most abundant midgut bacterial genera among different groups by one-way ANOVA (SPSS. 16.0). Table S6 Richness estimator of 30 samples. Table S7 Statistical analysis of richness estimator among different groups by one-way ANOVA (SPSS. 16.0). Table S8 ANOSIM statistical analysis among different groups at 2 sampling time, respectively. Fig. S1 Melting curve, amplification curve, and standard curve of qpcr.

2 Fig. S2 Rarefaction on species-abundance data. Average value of 3 replicates is shown. Fig. S3 Wooden cage and feeder.

3 Table S1 16S rrna gene copy numbers per sample. Sample name CK.15d.1 CK.15d.2 CK.15d.3 T1.15d.1 T1.15d.2 T1.15d.3 T2.15d.1 T2.15d.2 T2.15d.3 T3.15d.1 T3.15d.2 T3.15d.3 IMI.15d.1 IMI.15d.2 IMI.15d.3 CK.30d.1 CK.30d.2 CK.30d.3 T1.30d.1 T1.30d.2 T1.30d.3 T2.30d.1 T2.30d.2 T2.30d.3 T3.30d.1 T3.30d.2 T3.30d.3 IMI.30d.1 IMI.30d.2 IMI.15d.3 copy number (copies/ng) 1.46E E E E E E E E E E E E E E E E E E E E E E E E E E E E E E+01

4 Table S2 Statistical analysis of the copy number of 16S rrna gene of each treatment by one-way ANOVA (SPSS. 16.0). Group df F P CK.15d, T1.15d, T2.15d, T3.15d, IMI.15d CK.30d, T1.30d, T2.30d, T3.30d, IMI.30d

5 Table S3 OUT's data. Data was obtained using the Illumina Miseq2500-pyrosequencing. Sample Name Raw PE (#) Raw Tags (#) Clean Tags (#) Effective Tags Base (nt) Avglen (nt) CK.15d.1 62,844 57,075 48,326 47,538 19,947, CK.15d.2 65,120 58,476 50,016 49,339 20,688, CK.15d.3 69,832 62,724 53,552 52,604 22,156, CK.30d.1 63,128 57,663 49,063 48,250 20,555, CK.30d.2 75,297 68,367 57,839 56,839 24,109, CK.30d.3 65,898 59,990 50,744 49,972 21,286, IMI.15d1 60,735 55,202 48,355 47,744 19,728, IMI.15d2 65,040 59,329 51,532 50,958 21,254, IMI.15d3 73,359 66,630 57,614 56,859 23,875, IMI.30d1 68,936 61,943 52,089 51,457 21,870, IMI.30d2 74,313 67,259 59,212 58,337 24,047, IMI.30d3 73,263 66,364 58,514 57,685 23,644, T1.15d.1 76,006 69,029 59,255 58,903 24,780, T1.15d.2 76,141 69,056 61,237 60,516 24,826, T1.15d.3 77,927 70,549 59,394 58,789 25,120, T1.30d.1 65,490 59,262 49,782 48,944 20,759, T1.30d.2 78,955 71,996 62,608 61,616 25,542, T1.30d.3 68,173 62,341 53,108 51,031 21,744, T2.15d.1 65,405 58,970 49,504 49,046 20,878, T2.15d.2 37,452 34,004 29,620 29,264 12,200, T2.15d.3 69,045 62,735 55,209 54,502 22,600, T2.30d.1 69,508 63,491 54,120 53,600 22,733, T2.30d.2 67,758 62,736 56,707 55,767 22,730, T2.30d.3 68,566 62,208 52,216 51,540 22,060, T3.15d.1 61,137 55,607 48,791 48,176 19,952, T3.15d.2 76,141 69,236 59,054 58,215 24,692, T3.15d.3 69,199 63,556 55,404 54,670 22,639, T3.30d.1 78,349 71,238 61,355 60,623 25,275, T3.30d.2 78,577 71,878 64,907 64,739 26,274, T3.30d.3 70,368 64,042 54,255 53,650 22,729,

6 Table S4 The abundances of top10 classified bacterial genera within each sample. Commen salibacter Snodgra ssella Lactoba cillus Gilliame lla Sacchar ibacter Frischel la Bartone lla Citroba cter Bifidoba cterium other CK.15d CK.15d CK.15d CK.30d CK.30d CK.30d T1.15d T1.15d T1.15d E T1.30d T1.30d T1.30d T2.15d T2.15d T2.15d T2.30d T2.30d T2.30d T3.15d T3.15d T3.15d T3.30d T3.30d E T3.30d IMI.15d IMI.15d IMI.15d IMI.30d IMI.30d IMI.30d

7 Table S5 Statistical analysis of the composition of TOP10 dominant midgut bacterial genera among different groups by one-way ANOVA (SPSS. 16.0). Taxonomy Group F df P Commensalibacter Snodgrassella Lactobacillus Gilliamella Saccharibacter Frischella Bartonella Citrobacter Bifidobacterium other CK.15d, T1.15d, T2.15d, T3.15d, IMI.15d CK.30d, T1.30d, T2.30d, T3.30d, IMI.30d CK.15d, T1.15d, T2.15d, T3.15d, IMI.15d CK.30d, T1.30d, T2.30d, T3.30d, IMI.30d CK.15d, T1.15d, T2.15d, T3.15d, IMI.15d CK.30d, T1.30d, T2.30d, T3.30d, IMI.30d CK.15d, T1.15d, T2.15d, T3.15d, IMI.15d CK.30d, T1.30d, T2.30d, T3.30d, IMI.30d CK.15d, T1.15d, T2.15d, T3.15d, IMI.15d CK.30d, T1.30d, T2.30d, T3.30d, IMI.30d CK.15d, T1.15d, T2.15d, T3.15d, IMI.15d CK.30d, T1.30d, T2.30d, T3.30d, IMI.30d CK.15d, T1.15d, T2.15d, T3.15d, IMI.15d CK.30d, T1.30d, T2.30d, T3.30d, IMI.30d CK.15d, T1.15d, T2.15d, T3.15d, IMI.15d CK.30d, T1.30d, T2.30d, T3.30d, IMI.30d CK.15d, T1.15d, T2.15d, T3.15d, IMI.15d CK.30d, T1.30d, T2.30d, T3.30d, IMI.30d CK.15d, T1.15d, T2.15d, T3.15d, IMI.15d CK.30d, T1.30d, T2.30d, T3.30d, IMI.30d

8 Table S6 Richness estimator of 30 samples. Sample Observed_ species Shannon Simpson Chao1 ACE Goods_ coverage CK.15d CK.15d CK.15d CK.30d CK.30d CK.30d T1.15d T1.15d T1.15d T1.30d T1.30d T1.30d T2.15d T2.15d T2.15d T2.30d T2.30d T2.30d T3.15d T3.15d T3.15d T3.30d T3.30d T3.30d IMI.15d IMI.15d IMI.15d IMI.30d IMI.30d IMI.30d

9 Table S7 Statistical analysis of richness estimator among different groups by one-way ANOVA (SPSS. 16.0). Richness estimator Group F df P Obseverd_species Shannon CK.15d, T1.15d, T2.15d, T3.15d, IMI.15d CK.30d, T1.30d, T2.30d, T3.30d, IMI.30d CK.15d, T1.15d, T2.15d, T3.15d, IMI.15d CK.30d, T1.30d, T2.30d, T3.30d, IMI.30d

10 Table S8 ANOSIM statistical analysis among different groups at 2 sampling time, respectively. Group R-value P-value IMI.15d - T3.15d T2.15d - T3.15d T2.15d - IMI.15d Ck.15d - T3.15d Ck.15d - IMI.15d Ck.15d - T2.15d T1.15d - T3.15d T1.15d - IMI.15d T1.15d - T2.15d T1.15d - Ck.15d T2.30d - T1.30d IMI.30d - T1.30d IMI.30d - T2.30d T3.30d - T1.30d T3.30d - T2.30d T3.30d - IMI.30d Ck.30d - T1.30d Ck.30d - T2.30d Ck.30d - IMI.30d Ck.30d - T3.30d

11 Fig. S1 Melting curve, amplification curve, and standard curve of qpcr.

12 Fig. S2 Rarefaction on species-abundance data. Average value of 3 replicates were showed.

13 Fig. S3 Wooden cage and feeder.