Influence of Food and Nosema Ceranae Infection on the Gut

bioRxiv preprint doi: https://doi.org/10.1101/375576; this version posted July 24, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

1 Influence of food and Nosema ceranae infection on the gut microbiota of Apis 2 cerana workers 3 4 Running title: Food and infection affect the honeybee gut microbiota 5 6 Shao K. Huang1*, Kun T. Ye1, Wei F. Huang1, Bi H. Ying1, Xin Su1, Li H. Lin1, Jiang 7 H. Li1,Yan P. Chen2, Ji L. Li3, Xiu L. Bao4, Jian Z. Hu*4 8 9 1. College of Bee Science, Fujian Agriculture and Forestry University, Fujian, China 10 2. USDA-ARS Bee Research Lab, BARC-East Bldg, 476, Beltsville, MD 20705, 11 United States 12 3. Key Laboratory of Pollinating Insect Biology of the Ministry of Agriculture, 13 Institute of Apicultural Research, Chinese Academy of Agricultural Science, Beijing, 14 China 15 4.Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount 16 Sinai, New York, NY 10029, United States 17 18 Kun T. Ye, Email:[email protected]; 19 Wei F. Huang, Email: [email protected] 20 Bi H. Ying, Email:[email protected]; 21 Xin Su, Email: [email protected]; 22 Li H. Lin, Email: [email protected] 23 Jiang H. Li, Email:<[email protected]> 24 Yan P. Chen, Email: [email protected] 25 Ji L. Li , Email:[email protected] 26 Xiu L. Bao, Email:[email protected] 27 28 Co-Corresponding authors: 29 Shao K. Huang, Email:[email protected] 30 Jian Z. Hu, Email:[email protected] 1 / 24 bioRxiv preprint doi: https://doi.org/10.1101/375576; this version posted July 24, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

31 Abstract 32 Background 33 Gut microbiota plays an essential role in bee’s health. To elucidate the effect of food 34 and Nosema ceranae infection on the gut microbiota of honeybee Apis cerana, we 35 used 16S rRNA sequencing to survey the gut microbiota of honeybee workers fed 36 with sugar water or beebread and inoculated with or without N. ceranae. 37 Results 38 The gut microbiota of A. cerana is dominated by Serratia, Snodgrassella, and 39 Lactobacillus genera. The overall gut microbiota diversity was significantly 40 differential by food type. The N. ceranae infection significantly affects the gut 41 microbiota only at bees fed with sugar water. Higher abundance of Lactobacillus, 42 Gluconacetobacter and Snodgrassella and lower abundance of Serratia were found in 43 bees fed with beebread than with sugar water. N. ceranae infection led to higher 44 abundance of Snodgrassella and lower abundance of Serratia in sugar-fed bees. 45 Imputed bacterial KEGG pathways showed the significant metagenomics functional 46 differences by feeding and N. ceranae infections. Furthermore, A. cerana workers fed 47 with sugar water showed lower N. ceranae spore loads but higher mortality than those 48 fed with beebread. The cumulative mortality was strongly positive correlated 49 (rho=0.61) with the changes of overall microbiota dissimilarities by N. ceranae 50 infection. 51 Conclusions 52 Both food and N. ceranae infection significantly affect the gut microbiota in A. 53 cerana workers. Beebread feeding not only provide better nutrition but also help 54 establish a more stabled gut microbiota therefore protect bee in response to N. 55 ceranae infection. 56 57 58 59 60 2 / 24 bioRxiv preprint doi: https://doi.org/10.1101/375576; this version posted July 24, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

61 Abstract Importance 62 Gut microbiota plays an essential role in bee’s health. Scientific evidence suggests the 63 diet and infection can affect the gut microbiota and modulate the gut health, however 64 the interplay between those two factors and bee gut microbiota is not well known. In 65 this study, we used high-throughput sequencing method to monitor the changes of gut 66 microbiota by both food intake and the Nosema ceranae infection. Our result showed 67 that the gut microbiota composition and diversity of Asia Honeybee was significantly 68 associated with both food intake and the N. ceranae infection. More interestingly, 69 bees fed with beebread showed higher microbiota stability and less mortality than 70 those fed with sugar water when infected by N. ceranae . Those data suggest the 71 potential role of beebread, not only providing better nutrition but also helping 72 establish a more stabled gut microbiota to protect bee against N. ceranae infection. 73 74 75 Keywords: Apis cerana, gut, microbiota, Nosema ceranae, food 76 77 78 Background 79 European honey bees (Apis mellifera) and Asian honey bees (A. cerana) are two 80 truly domesticated bee species that play a vital role in agriculture and ecosystem by 81 providing pollination service to food crops and natural plants. However, both bee 82 species are confronted with many biotic and abiotic stressors including diseases 83 caused by pathogens and parasites, acute and sublethal toxicity of pesticides, 84 malnutrition due to loss of foraging habitat, and etc that act separately or 85 synergistically to cause the significant decline of bee health and population 86 worldwide[1-3] . As a result, the health of managed honey bees has drawn much 87 attention worldwide in recent years. There has been growing evidence that gut 88 bacteria play very important roles in animal health by maintaining homeostasis, 89 modulating immunity, regulating nutrition metabolism, and supporting host 90 development, and reproduction[4-6]. Although most insect guts harbor relatively 3 / 24

91 few microbiota species as compared to mammalian guts, insect bacteria have been 92 shown to be vital in regulating various aspects of their host biology [7-9]. Over the 93 past decade, progress has been made in understanding the composition and functional 94 capacity of microbes living in honey bee guts [10-12]. Honey bee gut microbiota is 95 established gradually through trophallaxis, food consuming, and interacting with the 96 hive environment[13]. Many factors, like genetics, age, diet, geography, and 97 medication can affect the gut microbiota composition[14,15]. Several types of 98 bacteria have been identified in the guts of A. mellifera including the genera of 99 Bacillus, Lactobacilli and Staphylococcus from Firmicutes phylum, Coliforms from 100 Enterobacteriaceae family of Proteobacteria phylum [16-18].A previous study 101 reported that species within the Apis genus share rather simple and similar gut 102 bacterial microbiota. At phylum level, among proteobacteria, Gammaproteobacteria 103 class was the most abundant, while other proteobacteria including Betaproteobacteria 104 and Alphaproteobacteria classes, Firmicutes and Actinobacteria were less frequent 105 but widespread organisms. Less than ten members formed a core species, including 106 Lactobacillus, Bifidobacterium, Neisseria, Pasteurella, Gluconobacter and newly 107 named species: Snodgrassella and Gilliamella [19-21]. However, most the studies 108 about the microbiota in Apis were conducted in European honey bees, A. 109 mellifera.The food influence on the microbiota of A. cerana has barely been 110 investigated. 111 Nosema ceranae is an intracellular parasite that disrupts a bee's digestive 112 system. It was first discovered in the A. cerana but has recently jumped host from A. 113 cerana to A. mellifera[22,23]. N. ceranae can seriously shorten the life expectancy of 114 adults, decrease the productivity of the colony, and cause severe colony lost especially 115 during wintering in the temperate area[24,25]. Furthermore stresses caused by 116 Nosema would be more severe when mixed infection happened with other parasites or 117 pathogens, such as Varroa mites, and viruses [26-30]. Now Nosema is one of the 118 major threats to the honey bee populations and has been often implemented in honey 119 bee colony losses worldwide[31,32]. The survey of microbial communities from the 120 digestive tracts of A. cerana workers showed that N. ceranae infection might have 4 / 24

121 detrimental effects on the gut microbiota[1]. However, the relationship between N. 122 ceranae and microbiota in A. cerana is largely unknown. In this study, we challenged 123 A. cerana workers with N. ceranae, and then fed them with either beebread or sugar 124 water. The intent of the current study was to evaluate the effects of N. ceranae 125 infection and food types on the gut microbiota. 126 127 Methods 128 Honey bees 129 Three A. cerana colonies without identified diseases were chosen for sample 130 collection, which located at the campus of College of Bee Science, Fujian Agriculture 131 and Forestry University, Fuzhou, Fujian, China. Capped brood-combs with pupae 132 near emergence were taken out of the colonies and then kept in the incubator with 133 35±1 and 55%-65%RH. Workers emerged within 24h were collected for the study.

134 ℃ 135 Purification of Nosema ceranae spore Because the prevalence and spore loads of N. 136 ceranae in A. cerana are less than A. mellifera[33,34], we purified N. ceranae spores 137 from A. mellifera foragers. First, adult workers were captured at entrances of A. 138 mellifera colonies and immobilized in the refrigerator for few minutes, and then the 139 guts of the bees were dissected, pooled, and ground in a mortar. Afterward, the spores 140 were purified by differential centrifugation to exclude most of the debris, finally, the 141 suspension was loaded on Percoll (Sigma-Aldrich, St.Louis, USA) and centrifuged to 142 eliminate unsaturated spores [33]. The purity and maturity of spore were confirmed 143 under phase contrast microscopy. The Nosema species was confirmed by PCR method 144 [35]. 145 146 Treatments and sampling 147 The newly emerged workers (<24h) were randomly distributed into 18 laboratory 148 rearing cages. 30 bees were transferred to each cage The experimental cages were 149 divided into two groups: 1) group supplied with only 50% (W/V) sugar water in 150 modified syringe feeder [36], and 2) group supplied with both 50% (W/V) sugar water 5 / 24

151 and beebread freshly collected from the A. cerana colonies (thereafter call beebread). 152 For each group, three subgroups were set up one without spore inoculation which was 153 used as a negative control, one inoculated with N. ceranae 5000 spores per bee, and 154 one inoculated with 50000 spores per bee (Figure 1). Each subgroup consisted of 155 three cages as replicates. Cages were kept in an incubator with 30±1 and 55%-65%

156 RH. About eight workers were collected at day 5, 10, and 15 post treatment℃ (dpi) from 157 each subgroup. The gut tissue was collected from each bee at 5-day, 10-day, and 15- 158 day post infection and then stored into -80 freezer until the subsequent microbial

159 composition analysis Foods were changed ℃each other day; dead bees were counted 160 and removed every day. 161 162 DNA extraction from gut tissue samples 163 Sample bees were taken out of the refrigerator and rinsed with 7% benzalkonium 164 bromide for 2min and then rinsed four times with sterilized water to minimize the 165 bacterial contamination from the body surface. The intestine tissues were collected with 166 tweezers clamping the end of the abdomen and each gut tissue was further separated 167 and transferred into a labeled 1.5ml tube on ice. The entire procedure was conducted 168 under the aseptic condition and all tools used were sterilized. The total DNA of the gut 169 tissue samples was extracted using Insect DNA Extraction Kit II (Beijing Demeter 170 Biotech Ltd, Beijing, China) following the manufacturer’s instruction. The quality and 171 yield of DNA samples were assessed using a Quawell Q5000 UV-Vis 172 spectrophotometer (Quawell, San Jose, CA, USA). 173 174 Gut Nosema ceranae spore counting 175 After caged bees were sampled at day 5, 10, and 15 post treatment, the quantity of the 176 spores in the gut specimen was counted as previously described with slight

177 modification[33]. Briefly, the sediments of gut were resuspended in 100μl ddH2O, then 178 vortexed evenly. The suspension was loaded onto the hemocytometer for N. ceranae 179 spore inspection and counting under a microscope. We conducted three to four repeated

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180 measurements for each sample. 181 182 Bacterial 16S ribosomal RNA gene PCR amplification 183 The phylogenetically informative V3-V4 region of 16S ribosomal RNA (rRNA) gene 184 was amplified using universal primer 347F/803R [37]. The dual-barcoding approach as 185 previously described[38] was applied to label the 16S rRNA gene amplicons of each 186 sample. Briefly, the 6-mer barcodes were attached on the 5’ends of both forward and 187 reverse PCR primers so that 16S rRNA gene PCR amplicons from each sample 188 contained a unique dual barcode combination. The PCR Primers were synthesized by 189 Sangon Biotech, Shanghai, China, and the primer sequences are shown in 190 Supplementary Table 1. The 25-μL PCR reaction mixes contain 300ng of sample DNA 191 as PCR template, 1μL of 10μM forward and reverse 16S primers, and 12.5μL of 192 2×HotMaster Taq DNA mix (Tiangen Biotech, Beijing, China). The PCR reaction was 193 performed on Applied Biosystem 2720 thermal cycler (Thermo Fisher Scientific Inc., 194 Waltham, MA, USA) at 94oC for 3 minutes, then 94oC 30 seconds, 58oC 30 seconds, 195 and 72oC 20sec for 30cycles, and 72oC for 4 min. The integrity of the PCR products 196 was verified by agarose gel electrophoresis. After purified with gel purification kit 197 (Promega, Madison, WI, USA), the 16S PCR amplicons were pooled at equal molarity, 198 freeze-dried, and submitted to New York Genome Center for sequencing. 199 200 16S rRNA gene sequencing and microbiota profiling 201 The 16S rRNA gene PCR amplicons were sequenced on the Illumina HiSeq platform 202 using 2x250 paired-end fast-run mode. In total, we generated 21 million high-quality 203 16S reads obtained by NGS sequencing on pooled barcoded PCR amplicons from 86 204 samples. After splitting by barcodes, ~ 2.5x105 reads per sample were obtained. After 205 the merge, the sequencing reads with length >400 and the quality score >Q30 at more 206 than 99% of bases were further split by barcode and trimmed of primer regions using 207 CLC Genomic workbench 6 (Qiagen Bioinformatics, Redwood City, CA, USA). The 208 filtered and trimmed high-quality reads were further processed by QIIME 1.9.0[39] . 209 We used the command pick_open_reference_otus.py with the defaulted cutoff =97% 7 / 24

210 to a cluster of nearly-identical sequencing reads as an Operational Taxonomic 211 Unit (OTU) using Uclust[40] . Representative sequences for each OTU were aligned 212 using PyNAST. Finally, the program built a biom-formatted OTU table with assigned 213 taxonomical information for each OTUs. Using Chimera Slayer[41], chimera 214 sequences arising from the PCR amplification were detected and excluded from the 215 aligned representative sequences and the OTU table. 216 217 Statistical Analysis 218 The mortality data of different groups were transformed by square root and degrees 219 and Asin, and then compared by using two-way ANOVA of the SPSS program. The 220 overall microbiota dissimilarities among all samples were accessed using the Bray- 221 Curtis distance matrices[42] generated at the genus level. The PERMANOVA 222 (Permutational Multivariate Analysis of Variance) procedure [43,44] using the 223 [Adonis] function of the R package vegan 2.0-5), with the maximum number of 224 permutations = 999, was performed to test the significance of the overall microbiota 225 differences between the gut microbiota grouped by feeding types and N. ceranae 226 infections. The diversity within each microbial community, so-called alpha-diversity 227 was calculated using the Shannon Index as metric and represented the measure of the 228 diversity at genus level [45]. Using the linear discriminant analysis (LDA) effect size 229 (LEfSe) method[46], we further selected the microbiota features significantly 230 associated with feeding types and N. ceranae infections. The program PICRUSt 231 (Phylogenetic Investigation of Communities by Reconstruction of Unobserved 232 States)[47] was used to predict the metagenome functional content based on our 16S 233 rRNA gene sequencing data. Briefly, a close reference-based OTU table was 234 generated using the QIIME pipeline and input into PICRUSt to bin individual 235 bacterial genes into Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, 236 thereby predicting their function.

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237 238 Dataset 239 16S rRNA gene sequencing information has been deposited in the European 240 Nucleotide Archive with study accession number: PRJEB21090. 241 242 Results 243 1. Simple core bacterial clusters in the gut of Apis cerana 244 As illustrated in Figure 1, the A. cerana adult workers were grouped by foods 245 and the level of N. ceranae infection. The microbial composition analysis of 246 gut tissue collected at 5-day, 10-day and 15-day post infection for each 247 subgroup following the method described previously [18,49] showed that the 248 gut microbiota of A. cerana is rather simple and mainly contain three phyla, 249 Proteobacteria, Firmicutes, and Bacteroidetes, counting for over 97% of the 250 total microbiota composition (Figure 1, Figure 2). At the genus level, less than 251 6 taxa from Proteobacteria and Firmicutes are dominant in the A. cerana gut 252 bacterial community. In details, they were the genera Snodgrassella, 253 Acetobacteraceae,Serratia, Gilliamella, Lactobacillus and unclassified genus 254 from Bacteroidetes, of which Serratia was not in the core species clusters of A. 255 mellifera[50]. 256 257 2. Foods and N. ceranae infection changed the relative abundance of 258 microbes in the gut 259 The overall microbiota dissimilarity in samples grouped by food or Nosema 260 infection was visualized in NMDS plots (Figure2). The overall gut microbiota 261 is significant different between bees fed with beebread fed and sugar (p=0.018 262 with N. ceranae infection, and p=0.001 without infection, PERMANOVA test 263 using Bray-Curtis distance). In sugar fed bees, we found N. ceranae infection 264 significantly altered the microbiota (p=0.001). However, N. ceranae infection 265 caused no significant alteration in gut microbitota in bees fed with beebread 266 (p=0.23). LEfSe method was applied to select the microbiota taxa which are 9 / 24

267 significantly associated with either food types or N. ceranae infections. In 268 subgroups without N. ceranae infection, the bees fed with beebread showed 269 more abundant Lactobacillus, Snodgrassella, Weeksellaceae, and less abundant 270 Serratia genus than bees fed with sugar. However, in the subgroups with N. 271 ceranae infection, the bees fed with beebread showed more abundant OTUs of 272 Lactobacillus and less abundant Serratia and Acetobacteraceae than bees fed 273 with sugar (Figure2). Among bees fed with sugar solution, N. ceranae infection 274 caused major changes in microbiota and was associated to increased OTUs of 275 Weeksellaceae, Snodgrassella and Gluconacetobacter and decreased 276 Proteobacteria phyla, in particular, Telluria, Serratia, and Acinetobacter. 277 Among bees fed with beebread, N. ceranae infection had a minor effect on 278 microbiota, with merely decreased the abundance of Massilia, Aggregatibacter 279 and Gluconacetobacter genera. 280 281 3. Differential metagenome features predicted by PICRUSt and their 282 association with food and N. ceranae infection status 283 We performed PICRUSt analysis to predict the full metagenomic content of 284 microbial communities using 16S gene surveys 33 and compared the predicted 285 metagenomic pathways by food and N. ceranae infection status (FigureS1). The 286 Nearest Sequenced Taxon Index (NSTI), which quantifies the uncertainty of the 287 prediction (lower values mean a better prediction), ranged from 0.027 to 0.11 288 with mean value=0.067, indicating fair reliability and accuracy in the 289 metagenome reconstruction. The heat map (FigureS1) with clustering analysis 290 showed the overall changes in predicted KEGG pathways. Among those 291 significantly differential pathways, we found the food type could affect the 292 bacterial Glycolysis/Gluconeogenesis, Fructose and mannose metabolism, 293 metabolism of several amino acids and etc. N. ceranae infection could affect 294 biosynthesis of several amino acids, the signal transduction mechanism, and the 295 lipopolysaccharide biosynthesis and phosphotransferase system (PTS). 296 10 / 24

297 4. The cumulative mortality of caged bees with different feeding type and 298 infection status. 299 When inoculated with N. ceranae spores, the average cumulative mortality of caged 300 bees increased gradually during the experimental observation, our results showed that 301 N. ceranae infection significantly shortened the longevity of workers fed with only 302 sugar water than those fed with beebread (Figure 3A). Interestingly, the spore load in 303 the gut fed with beebread were significantly higher than those with sugar water (p- 304 value=0.01and 0.007 for low N. ceranae and high N. ceranae, respectively) at 15 days 305 after inoculation (Figure 3B). This was consistent with the earlier report by Zheng et 306 al[51]. There is not interaction between food type and spore dosage on the mortality 307 (p-value=0.868, F=0.029). There was no significant difference in gut N. ceranae spore 308 counts between low and high dosage N. ceranae inoculations. This may be due to the 309 late sampling time that the spore load in the gut has reached the plateau. 310 311 5. The richness of the gut microbiota of caged bees with different feeding 312 type and infection status. 313 We used Shannon index, a commonly used metrics, for richness assessment 314 within the given community[45]. Without N. ceranae infection, the richness of 315 the microbiota in bees fed with sugar solution was significantly lower than 316 those fed with beebread (Figure 3C, p-values<0.05 at 5, 10 and 15days). 317 Furthermore, the richness of the microbiota decreased by time in bees fed with 318 sugar, but not in bees fed with beebread. In subgroups with N. ceranae 319 infection, the microbiota of bees fed with sugar showed increased richness at 320 all time points with a slightly higher mean but no significant differences to that 321 of bee fed with beebread. 322 323 6. The stability of the gut microbiota is significantly correlated with the 324 cumulative mortality 325 The stability of the microbiota in response to the N. ceranae infection in groups 326 with different of feeding conditions showed that the bee fed with beebread 11 / 24

327 showed relatively stable microbiota. The mean dissimilarity was not 328 significantly different from either sampling time post infection or N. ceranae 329 doses. However, among bees fed with sugar solution, the microbiota 330 dissimilarities significantly increased by time, with the most dissimilarities and 331 higher consistency at 15 days with the high N. ceranae infection (Figure 3D), 332 suggesting the most diverged microbiota within this group. Further, the mean 333 microbiota dissimilarities were significantly correlated with the cumulative 334 mortality rate (r=0.61, spearman correlations, p-value=0.035). 335 336 Discussion 337 Our result demonstrated that the gut microbiota of the A. cerana adult workers 338 are composed of three major phyla, Proteobacteria, Firmicutes, and 339 Bacteriodetes. This result is consistent with the previous reports [21] except 340 that the most abundant taxa in our study was Proteobacteria, which was the 341 second in Ahn’s study [21]. At the genus level, we found that the gut 342 microbiota of Asian honey bees is dominated by a few core bacterial species, 343 including Lactobacillus, Snodgrassella and Gilliamella, among the major 344 genera found in both our study and previous studies[52]. 345 Food constituents can influence the gut microbiota composition. Our 346 results confirmed that food type significantly shapes the bees’ gut microbiota 347 composition (Figure 1 and 2). Beebread contains high protein and 348 comprehensive nutrients, which may favor those proteolytic species. In 349 addition, beebread provides additional microbiota [53,54] inoculations 350 especially lactic acid bacteria, and may benefit the gut microflora too. 351 Our study also showed that Lactobacillus and Snodgrassella genera were 352 much more abundant in those bees fed on beebread (Fig 2B). The genera, 353 Lactobacillus, Bifidobacterium and the family Pasteurelaceae, were also found 354 in beebread from colonies of A. mellifera [51]. Lactobacillus had been found in 355 flora and hive environment, including honey, royal jelly, beebread, and honey 356 sac. Lactobacillus was also found in honey bee crop and showed inhibition 12 / 24

357 effect on Paenibacillus larvae in vitro [55]. Therefore, it is plausible to 358 speculate that the Lactobacillus found in gut of adult workers fed with were 359 obtained through food trophallaxis. In contrast, bees fed with sugar only 360 showed more abundant Enterobacteraceae. Overgrowth of Enterobacteraceae 361 has been linked to gut inflammation in many studies . 362 Our data showed that higher proportion of Serratia harbored in the gut of 363 10-day old bees fed with sugar. Serratia was further confirmed as S. 364 marcescens by sequencing near full-length 16S rRNA gene(data no showed). S. 365 marcescens is commonly found in adult A. mellifera, A. cerana, and bumble 366 bee gut. It is generally harmless to honey bee, and commonly used to explore 367 the host immune reaction to microbes[56], There were two cases , that Serratia 368 had detrimental effects on A. mellifera survivorship after host microbiota was 369 erased by antibiotics . In our study, N. ceranae infection broke the balance of 370 Serratia in the microflora, and shortened host lifespan. Future investigations 371 are necessary to further explore complex interactions among N. ceranae, host, 372 and gut microbiotas. 373 Nosema resides in the gut of the bee and the infection by N. ceranae can 374 profoundly change honey bees physiology [57], and change the host-microbiota 375 relationship in the gut. Investigation conducted by Li et al. showed that four 376 common bacterial clusters, Bifidobacterium, Neisseriaceae, Pasteurellaceae, 377 and Lactobacillus in N. ceranae infected adult A. cerana workers were less 378 abundant compared to non-infected ones[58]. However, we found minor 379 changes in gut microbiota by N. ceranae infection in beebread fed bees. When 380 sugar water is the only food supplied, N. ceranae infection showed a stronger 381 effect on the overall gut microbiota with more abundant 382 Neisseriaceae/Snodgrassella, Weeksellaceae, Gluconacetobacter and less 383 abundant Serratia, Telluria and Enterobacteriaceae. Further, the lower 384 stability of gut microbiota in bee fed with sugar could lead to increased 385 susceptibility to Nosema infections in bees.

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386 Our data showed that the N. ceranae infection caused much higher cumulative 387 mortality in bees fed with sugar than bees fed with beebread . Interestingly, the 388 changes in microbiota dissimilarity were highly correlated to bee’s mortality. N. 389 ceranae infection caused significant increases in both the microbiota richness and 390 the dissimilarity in sugar fed bees, but not beebread fed bees. We speculated that N. 391 ceranae infection in sugar fed bees resulted in a more diverged microbiota, among 392 which many are not considered as probiotic in bees . The gut microbiota in bees fed 393 with beebread was stable with N. ceranae infection. This stability of gut microbiota 394 could play a protective role and result in less mortality. 395 Having a biological measure of the effect of N. ceranae infection might help us 396 further understand the controversy of honey bee health and N. ceranae infection, 397 which bees with pollen feeding resulted in higher spore load but less mortality 398 compared to those with sugar water[59]. 399 Although the 16S sequencing based taxonomy analysis is sufficient in current 400 technology development, it only identified bacterial taxa to genus level. It is difficult 401 to identify a specific species or strain that is strongly correlated to either the food 402 feeding or N. ceranae infection. 403 In summary, the gut microbiota of A. cerana workers is significantly 404 differentiated by both food types and N. ceranae infection. The higher stability 405 of the gut microbiota in the bees fed with plays a role in bees ability to defend 406 N. ceranae infection and warrants further exploration 407 408 Conflict of Interest 409 The authors declare that they have no competing interests 410 411 Authors’ contributions 412 SKH and JZH conceived an designed the study; KTY and SKH performed the 413 bee experiment, KTY, BHY, XS, and LHL counted spore loads; JZH and XLB 414 performed the microbiota analysis; WFH, JHL and YPC analyzed the phenotype 415 data; SKH, JZH and JLL contributed reagents/materials/analysis tools; SKH, 14 / 24

416 JZH wrote the paper; WFH and YPC revised the paper. All authors read and 417 approved the final manuscript. 418 419 Acknowledgement 420 We thank the genomic center of NYU to perform the NGS. This project was 421 sponsored by the Scientific Research Foundation for the Returned Overseas 422 Chinese Scholars, State Education Ministry（K4115005A）; The Ministry of 423 Agriculture 948 project (2015-Z9). 424 425 426

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573 54. Su SK, Chen SL, Yu XP, Lin XZ, Hu FL (2001) Isolation and identification of 574 bacteria from pollen and bee bread. Journal of Zhejiang Agricultural 575 University 27: 627-630. 576 55. Forsgren E, Olofsson TC, Váasquez A, Fries I (2010) Novel lactic acid bacteria 577 inhibiting Paenibacillus larvae in honey bee larvae. Apidologie 41: 99-108. 578 56. Lourenço AP, Martins JR, Bitondi MMG, Simões ZLP (2009) Trade-off between 579 immune stimulation and expression of storage protein genes. Archives of 580 Insect Biochemistry & Physiology 71: 70–87. 581 57. Mayack C, Natsopoulou ME, McMahon DP (2015) Nosema ceranae alters a 582 highly conserved hormonal stress pathway in honeybees. Insect Mol Biol 24: 583 662-670. 584 58. Elzen PJ, Elzen GW, Lester GE (2004) Compatibility of an organically based 585 insect control program with honey bee (Hymenoptera: Apidae) pollination in 586 cantaloupes. J Econ Entomol 97: 1513-1516. 587 59. Zheng HQ, Lin ZG, Huang SK, Sohr A, Wu L, et al. (2014) Spore Loads May Not 588 be Used Alone as a Direct Indicator of the Severity of Nosema ceranae 589 Infection in Honey Bees Apis mellifera (Hymenoptera:Apidae). J Econ 590 Entomol 107: 2037-2044. 591 592 593

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594 Figure Legends 595 Figure 1. Experimental design and survey of the gut microbiota 596 composition. Bar plots represent the normalized relative abundance (%) of the 597 gut microbiota at genus level fed with different foods and doses of N. ceranae 598 infection at day 5, 10 and 15 (increasing order). 599 600 Figure 2.Foods and N. ceranae infection changed the relative abundance of 601 microbes in the gut. 2A. NMDS plots present the overall dissimilarity between 602 samples grouped by diet or infection status. P-values were given by 603 PERMANOVA test. 2B. The cladogram plots present the LEfSe results on the 604 gut microbiota of honey bees grouped by diet or infection status. Differences 605 are represented in the color for the most abundance class (green and red color 606 indicate increasing gin corresponded phenotype). 607 608 Figure 3. Difference in bee mortality and stabilities of the gut microbiota by 609 feeding and N. ceranae infections. 3A.Cumulative mortalities under different 610 treatment conditions; 3B. The mean and standard deviations of the N. ceranae(Nc) 611 spore load in different treatment conditions; 3C. Alpha diversity of the mid-gut 612 microbiota in different treatment conditions; 3D. The mean and variance of the 613 dissimilates (Beta diversity) of the mid-gut microbiota in different treatment 614 conditions; 3E. Illustration of the links between the decreased stability in mid-gut 615 microbiota and the increased bee mortality in sugar-fed bees. 616

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Y_ _ _

N_ _ _

_Bee_Bread_10000_15

Y_ _ _

_Bee_Bread_10000_5

N_ _ _

_Bee_Bread_1000_15 variable others Lactobacillus Hafnia _Bee_Bread_10000_15 Massilia Pseudomonas Serratia Gilliamella Acetobacteraceae_bacterium Acinetobacter Bacillus _Bee_Bread_1000_10 Bacteroidetes_bacterium Enterobacter Gluconacetobacter Rhizobiales_bacterium Salmonella _Bee_Bread_10000_10 Snodgrassella Spiroplasma Streptophyta_bacterium Telluria Others _Bee_Bread_1000_5

_Bee_Bread_10000_5 Time of Time of Microbial composition at genus level _Bee_Bread_0_15 CollectionCollection Microbial composition at genus level

_Bee_Bread_1000_15 variable others Lactobacillus Lactobacillus Saccharibacter Hafnia

_ _0_0 Massilia Neisseriaceae.Other _Bee_Bread_0_10 0 Day PseudomonasTaxa d0 Serratia Serratia

Gilliamella

_Sugar_0_5 Acetobacteraceae_bacterium _ _0_0 Weeksellaceae.OtherGammaproteobacteria.Others Acinetobacter Bacillus Taxa _Bee_Bread_1000_10 Bacteroidetes_bacterium Lactobacillus

Enterobacter _Sugar_0_10

_Sugar_0_5 Gluconacetobacter Flavobacteriaceae.Other Rhizobiales_bacterium Acetobacteraceae.Other Salmonella Snodgrassella Lactobacillus

_Sugar_0_15 Spiroplasma

_Bee_Bread_0_5 _Sugar_0_10 Neisseriaceae.Other Streptophyta_bacterium Saccharibacter

TaxaTelluria Others

_Sugar_1000_5 Enterobacteriaceae.Other _Sugar_0_15 Neisseriaceae.Other _Bee_Bread_1000_5 othersSerratia Serratia _Sugar_1000_10 Lactobacillus

_Sugar_1000_5 Pasteurellales.OthersGammaproteobacteria.Others

_Sugar_10000_15 _Sugar_1000_15 HafniaOthersSpiroplasma

TimeTime _Sugar_1000_10 ofof

Massilia Others _Sugar_10000_5 Microbial composition at genus level

_Bee_Bread_0_15 CollectionCollection Microbial composition at genus level _Sugar_1000_15 Pseudomonas

_Sugar_10000_10 Serratia

_Sugar_10000_5 _Sugar_10000_15

_Sugar_10000_10 GilliamellaOthers Lactobacillus

Taxa Pasteurellales.Others

others Serratia Saccharibacter

_Sugar_10000_10 Lactobacillus Enterobacteriaceae.Other

_ _0_0 Acetobacteraceae_bacterium _Bee_Bread_0_5 Hafnia Neisseriaceae.OtherNeisseriaceae.Other

0 Day Massilia Taxa

_Bee_Bread_0_10 Acetobacteraceae.Other

d0 Others

Pseudomonas Serratia

Lactobacillus

Serratia AcinetobacterSpiroplasma

Weeksellaceae.Other _Sugar_10000_15 Others

_Sugar_0_5

Gammaproteobacteria.Others

_ _0_0 Gilliamella Weeksellaceae.OtherGammaproteobacteria.Others _Bee_Bread_0_10

Taxa

Acetobacteraceae_bacteriumPasteurellales.Others Serratia

Acinetobacter Serratia

BacillusTaxaNeisseriaceae.Other

Bacillus Enterobacteriaceae.OtherLactobacillus Saccharibacter

_Bee_Bread_0_5 _Sugar_0_10 Bacteroidetes_bacterium

Neisseriaceae.Other

Lactobacillus _Bee_Bread_0_15

_Sugar_10000_5 _Sugar_0_5

Enterobacter

Acetobacteraceae.OtherFlavobacteriaceae.Other Bacteroidetes_bacteriumFlavobacteriaceae.Other

Gluconacetobacter Acetobacteraceae.Other

Lactobacillus

Rhizobiales_bacterium Taxa

Salmonella Weeksellaceae.OtherLactobacillus

_Sugar_0_15

_Bee_Bread_0_10 _Bee_Bread_1000_5 SnodgrassellaEnterobacterTaxa

_Bee_Bread_0_5 _Sugar_0_10 Neisseriaceae.Other Spiroplasma Saccharibacter TaxaStreptophyta_bacterium

Telluria Gluconacetobacter

_Sugar_1000_5 Enterobacteriaceae.Other

_Bee_Bread_1000_10

_Bee_Bread_0_15 _Sugar_0_15 Neisseriaceae.Other Rhizobiales_bacteriumothersSerratia

Serratia

_Sugar_1000_15 _Sugar_1000_10

_Bee_Bread_1000_15 _Bee_Bread_1000_5 Lactobacillus

_Sugar_1000_5 SalmonellaPasteurellales.OthersGammaproteobacteria.Others _Sugar_1000_15

_Sugar_10000_15 _Bee_Bread_10000_5 SnodgrassellaHafniaOthersSpiroplasma _Bee_Bread_1000_10 _Sugar_1000_10

Massilia Others

_Sugar_10000_5 Spiroplasma _Bee_Bread_10000_10

_Bee_Bread_1000_15 _Sugar_1000_15 Pseudomonas

_Sugar_1000_10 Streptophyta_bacterium _Sugar_10000_10

_Bee_Bread_10000_15 Serratia

_Bee_Bread_10000_5 Telluria _Sugar_10000_5

_Sugar_10000_15 Others

_Sugar_10000_10 N_ _ _ Gilliamella

Taxa Pasteurellales.Others

others Serratia

_Bee_Bread_10000_10 _Sugar_10000_10 Lactobacillus

bee bread Acetobacteraceae_bacteriumEnterobacteriaceae.Other _Bee_Bread_0_5 Hafnia

Neisseriaceae.Other

Y_ _ _ Massilia

Acetobacteraceae.Other

Pseudomonas Others

Lactobacillus

Spiroplasma

_Bee_Bread_10000_15 Serratia Acinetobacter

Weeksellaceae.Other _Sugar_10000_15 _Sugar_1000_5 Others

Gilliamella Gammaproteobacteria.Others _Bee_Bread_0_10

Taxa

Acetobacteraceae_bacteriumPasteurellales.Others Serratia

Acinetobacter Serratia

BacillusNeisseriaceae.Other

Bacillus Enterobacteriaceae.Other

Saccharibacter N_ _ _

_Bee_Bread_0_5 Bacteroidetes_bacterium

Neisseriaceae.Other

Lactobacillus

_Sugar_10000_5 _Bee_Bread_0_15

Enterobacter

Acetobacteraceae.Other

Bacteroidetes_bacteriumFlavobacteriaceae.Other

Gluconacetobacter

Lactobacillus

Rhizobiales_bacterium Taxa

Weeksellaceae.Other

Y_ _ _ Salmonella

_Bee_Bread_0_10 _Bee_Bread_1000_5 SnodgrassellaEnterobacterTaxa Spiroplasma _Sugar_0_15 Streptophyta_bacterium

Telluria Gluconacetobacter

_Bee_Bread_1000_10 _Bee_Bread_0_15 Rhizobiales_bacterium

_Sugar_1000_15 _Bee_Bread_1000_15

_Bee_Bread_1000_5 Salmonella

_Bee_Bread_10000_5 Snodgrassella _Sugar_0_10 _Bee_Bread_1000_10

Spiroplasma _Bee_Bread_10000_10 _Bee_Bread_1000_15

_Sugar_1000_10 Streptophyta_bacterium

_Bee_Bread_10000_15

_Bee_Bread_10000_5 Telluria

N_ _ _

_Sugar_0_5 _Bee_Bread_10000_10 Y_ _ _

_Sugar_1000_5 _Bee_Bread_10000_15 N_ _ _

_ _0_0 Y_ _ _

_Sugar_0_15

_Sugar_0_10

_Sugar_0_5

_ _0_0 Feeding type Feeding type Feeding type NonNon-infected-infected NonNon-infected-infected Non-infected Infected Non-infected NonNon-infected-infectedInfected Non-infected NonNonIInfectedNon-infected-INoninfectednfected-infectedI-nfectedinfectedInfected IInfectedNonINonnfected-infectedInfected-infected IInfectedInfectedInfected 0.50 0.50 NonNonNon-infected-infected--infectedinfected 0.50 NonNonIInfectedNon-Iinfected-nfectedinfected-infected NonNonIInfectedNon-Iinfected-nfectedinfected--infectedinfected IInfectedInfected Non-infected Infected BeeBee bread bread Non-infectedBeeBee bread breadBeeBee bread bread NonInfected-infectedInfected BeeBee bread bread Infected BeeBee bread bread Infected ● ● Non-infected● Bee bread ●Infected ●Bee breadBee bread ● BeeBee bread breadBee breadBee bread Bee bread 0.50 0.50 SugarSugar Non-infected 0.50 SugarSugarSugarSugar NonInfected-infected SugarSugar NonInfected-infected SugarSugar Infected BeeBee bread breadBeeSugar bread BeeBee bread breadBeeBeeSugarBee breadbread breadBeeSugar bread SugarSugarBeeSugarBee bread breadBeeSugar bread BeeBee bread breadBeeSugar bread ● ● ● Bee bread ● ●Bee breadBee bread ● BeeBee bread breadBeeBee bread breadBee bread Bee bread ● ● SugarSugarSugarSugar ● ● SugarSugarSugarSugarSugarSugar ● ● SugarSugarSugarSugarSugarSugar SugarSugarSugar Bee bread BeeSugar breadBeeSugar bread BeeSugar breadBee bread BeeSugar bread ● ● ● Sugar● ● ● Sugar Sugar● ● ● Sugar Sugar Sugar ● ● p−value=0.001 ● p−value=0.018 p−value=0.001 ● ● p−value=0.018 p−value=0.001 ● p−value=0.018 ● ● ● ● 0.25 ● ● 0.25 0.25 ● 0.25 p−value=0.018 ● 0.25 p−value=0.001 p−value=0.018 0.25 p−value=0.001 p−value=0.018 ● p−value=0.001 ●● ●● ●● 0.25 0.25 0.25 0.25 ● 0.25 0.25 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● Food ● ● Food ● Food Food ● Food ● ● Food ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● Bee_bread ● ● ● Bee_bread ● ●● Bee_bread ● ● ●● Bee_bread ● Bee_bread ● ● Bee_bread ● Food ● ● Food ● Food Food ● Food ● ● Food ● ● MDS2 ● ● MDS2 MDS2 MDS2 ● ● ● ● MDS2 MDS2 ● Sugar ● . ● Sugar ● ● Sugar ● ● Sugar ● ● ● ● Sugar ● Sugar ● ● ● Bee_bread Bee_bread ● ● ● Bee_bread Bee_bread ● ● ● Bee_bread Bee_bread ● ● ● ● ● ● ● ● ● ● ● ● MDS2 ● ● MDS2 MDS2 MDS2 ● ● ● ● MDS2 ●● ● Sugar MDS2 ●● ● Sugar ●● ● Sugar ● Sugar 0.00 ● ● ● Sugar 0.00 ● ● ● Sugar ● ● ● 0.00 0.00 ● 0.00 ● ● ● ● ● ● ● 0.00 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●●● ● ● ●● ● ● ● ● ● ●●● ● ● ● 0.00 ● 0.00 ● 0.00 ●● ● ● ● 0.00 ● ● ● 0.00 ● ● ● ● ● 0.00 ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● The copyright holder for this preprint (which was preprint (which for this holder The copyright ● ● ● ● ●● ● ● ● ●● ● ●● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●● ● ● ● ● ●● ● ● ● ● ●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● −0.25 ● −0.25 ● ● ● −0.25 ● ● ● ● −0.25 ● ● ● −0.25 ● ● ● ● ● −0.25 ● ● ● ● −0.25 −0.25 ● ● −0.25 ● −0.25 ● ● −0.25 ● ● −0.25 ● −0.4 −0.2 0.0 0.2● 0.4 −0.25● 0.00 0.25 −0.4 0.50 −0.2 0.0 0.2● 0.4 −0.25● 0.00 0.25 −0.4 0.50 −0.2 0.0 0.2● 0.4 −0.25● 0.00 0.25 0.50 MDS1 MDS1 MDS1 MDS1 MDS1 MDS1 −0.4 −0.2 0.0 0.2 0.4 −0.25 0.00 0.25 −0.4 0.50 −0.2 0.0 0.2 0.4 −0.25 0.00 0.25 −0.4 0.50 −0.2 0.0 0.2 0.4 −0.25 0.00 0.25 0.50 MDS1 MDS1 MDS1 MDS1 MDS1 MDS1 BeeBeeBee bread bread bread NosemaBeeBee infectionSugarBee bread breadSugar bread BeeBeeSugarBee bread breadSugar bread SugarSugar Bee bread Sugar Bee bread Nc infectionBeeBeeBee bread bread bread Sugar Bee bread Nc infectionBeeBeeSugarBee bread breadSugar bread Sugar Nc infectionBeeBeeSugarBee bread breadSugar bread SugarSugar Bee bread Sugar Bee bread Bee bread Sugar Bee bread BeeSugar bread Sugar BeeSugar bread Sugar ● ● NonNon-infected-infected Bee bread ● NonNonNon-infected--infected-infectedinfected BeeSugar bread NonNon-infected-infected BeeSugar bread NonNon--infectedinfected Sugar p−value=0.001 Non-infected Bee breadp−value=0.001 Non-infectedinfected BeeSugar breadp−value=0.001 NonNon--infectedinfectedNon--infectedinfected BeeSugar bread Non-infected Sugar ● ● InfectedInfected ● InfectedInfected ● ● ● NonNon-infected-infectedNon-infected ● ● NonNonNon-infected--infected-infectedinfectedNonNonInfected--infectedinfectedNon-infected ● NonInfectedINonnfected-infected-infectedNonInfected-infectedNon-infected NonNon--infectedinfectedNonInfected-infectedNon-infected p−value=0.001 Non-infectedNon-infected p−value=0.001 Non-infectedinfectedNon-infected p−value=0.001 NonNon--infectedinfectedNonNon-infected--infectedinfectedNon-infected Non-infected 0.2 ● 0.2 0.2 ● ● Infected ● InfectedInfectedInfectedInfected ● InfectedInfectedInfectedInfected InfectedInfectedInfected ● Non-infected ● NonNonInfected--infectedinfected ● NonNonInfected-infected-infected NonInfected-infected ● ● ● 0.2 ● license International 4.0 CC-BY-NC-ND ● 0.2 ● 0.4 ● 0.4 0.2 ● ● 0.4 Infected ● Infected ● ● ● ● ● Infected ● ●● ● ● ● ● ●● 0.4 ● ● ● 0.4 ● ● ● 0.4 ● ● ● ● 2018. July 24, posted this version ● ● ● ● ● ● ● ● ● ● ● ● ; ● ● ● ● ● ● ● p−value=0.23 ● ● p−value=0.23 ● ● ● p−value=0.23 ● ● 0.0 ● ●●● 0.0 ● ●●● 0.0 ● ●●● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● p−value=0.23 ● p−value=0.23 ● ● p−value=0.23 ● 0.0 ● ●● 0.0 ● ● 0.0 ● ●● 0.2 ●● ● ● 0.2 ● ●● ● 0.2 ● ● ● ● ● ● ● ● ● ● ● ● ● Treatment ● Treatment ● Treatment ● ● Treatment ● Treatment Treatment ● ● ● 0.2 ● ● ● 0.2 ● ● ● ● ● ● non−infected ● 0.2 ● ● non−●infected ● ●● non−infected ● ● ●● non−●infected ● ● non−infected ● ● ● non−infected ● ● Treatment ● Treatment ● Treatment ● ● Treatment ● Treatment Treatment ● ● MDS2 ● ● MDS2 MDS2 MDS2

● ● MDS2 ● infected−0.2 MDS2 ● infected ● infected−0.2 ● infected ● ● ● infected−0.2 ● infected ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● non−infected non−infected ● ● non−infected ● ● non−infected ● ● non−infected ● ● ● non−infected ● ●

● ● MDS2 ● ● MDS2 MDS2 MDS2

● ● MDS2 MDS2 ● ● infected−0.2 a under available ● infected infected−0.2 ● infected ● infected−0.2 ● infected ● ● ● ● ● ●● ● ● ● ● ● ● ●● ● ● 0.0 ● 0.0 ● 0.0 ● ● ● ● ● ● ● ● ● ●● ● ●● ● ● ● ● ● ●● ● ●● ● ●● ● 0.0 ● ● 0.0 ● ● 0.0 ● ● ●● ● ● ● ● ● ● ● ●● ● ● ● ● ● −0.4 ● ● ● ● −0.4 ●● ● ● ●● ● ●● ● ● ● ●● ● −0.4 ●● ● ● ●● ● ●●● ● ● ● ●●● ●● ● ●● ● ● ●● ● ●● ● ● ● ● −0.4 ● ●● ● ● ● −0.4 ● ●● ● ● ● ● −0.4 ● ● ●● ● ● ● ● ●● ● ● ●● ● ● ● −0.2 ● ● ● −0.2 ● ● ● −0.2 ● ● ● ●● ● ●● ● ● ● ● ● ● −0.2 −0.2 ● −0.2 −0.6 −0.6 −0.6 ● ● ● ● ● ● −0.6 −0.6 −0.6 −0.25 0.00 0.25 ●0.50 −0.50 https://doi.org/10.1101/375576 −0.25 ● 0.00 0.25 −0.25 0.00 0.25 ●0.50 −0.50 −0.25 ● 0.00 0.25 −0.25 0.00 0.25 ●0.50 −0.50 −0.25 ● 0.00 0.25 MDS1 MDS1 MDS1 MDS1 MDS1 MDS1 −0.25 0.00 0.25 0.50 −0.50 −0.25 0.00 0.25 −0.25 0.00 0.25 0.50 −0.50 −0.25 0.00 0.25 −0.25 0.00 0.25 0.50 −0.50 −0.25 0.00 0.25

MDS1 doi: MDS1 MDS1 MDS1 MDS1 MDS1 not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made made It is perpetuity. in preprint the display to a license bioRxiv granted has who the author/funder, is review) peer by certified not bioRxiv preprint bioRxiv bioRxiv preprint doi: https://doi.org/10.1101/375576; this version posted July 24, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

3A4A 3A4A3A 3C4C 3C4C 3E4E 3E4E3E non-infected non-infectedinfected infected

0.6 0.6 1.2 1.2 1.2 1.2 Treatment Treatment Food Food Food Food Sugarsugar Sugarsugar ● B ● B BbeeBee Bread bread BbeeBee Bread bread Sugar.1000Ncsugar+low Nc Sugar.1000Ncsugar+low Nc 0.8 0.8 0.8 0.8 sugar sugar 0.4 0.4 Sugar.10000Ncsugar+high Nc Sugar.10000Ncsugar+high Nc S S S Sugar S Sugar Shannon Index Shannon Index Breadbread Breadbread Shannon Index Shannon Index Bread.1000Ncbread+low Nc Bread.1000Ncbread+low Nc 0.4 0.4 0.4 0.4● ● Cumulative MortalityCumulative Cumulative MortalityCumulative Bread.10000Ncbread+high Nc Bread.10000Ncbread+high Nc 0.2 0.2 ● ●

5 10 155 105 1015 155 10 15 Days Days Days Days 0.0 0.0

0 50 105 1510 15 Days Days

3D4D 3D4D 3B4B 3B4B 3D bee bread bee bread sugar sugar Treatment TreatmentSpore load SporeSD load SD low Nc lowhigh Nc Nc highlow Nc lowhigh Nc Nc high Nc (x108) (x108) 1.00

sugar+lowSugar.1000Nc Nc sugar+lowSugar.1000Nc1.40 Nc 1.400.61 0.61 0.75 ●

●

● sugar+Sugar.10000Nchigh Ncsugar+Sugar.10000Nc1.12high Nc 1.120.15 0.15 0.50

● Mortality

● rho=0.61 breadBread.1000Nc+low Nc breadBread.1000Nc3.59+low Nc 3.590.78 0.78 0.25 ● ● p−value=0.035

● ● ● ● breadBread.10000Nc+high NcbreadBread.10000Nc3.21+high Nc 3.210.65 0.65 ● 0.00

0.5 0.6 0.7 0.8 0.9 Dissimilarity bioRxiv preprint doi: https://doi.org/10.1101/375576; this version posted July 24, 2018. The copyright holder for this preprint (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under aCC-BY-NC-ND 4.0 International license.

617 Supplementary Table 1. PCR primers for bacterial 16S sequencing

Primer Name Sequence

16SF1 AGTCGACAGGAGGCAGCAGTRRGGAAT

16SF2 AGGAACTCGGAGGCAGCAGTRRGGAAT

16SF3 AGCTGTAGGGAGGCAGCAGTRRGGAAT

16SF4 AGGACACGGGAGGCAGCAGTRRGGAAT

16SF5 AGAGCGAGGGAGGCAGCAGTRRGGAAT

16SF6 AGTCTCTAGGAGGCAGCAGTRRGGAAT

16SF7 AGCGTGTCGGAGGCAGCAGTRRGGAAT

16SF8 AGATGCGTGGAGGCAGCAGTRRGGAAT

16SF9 AGAACGCAGGAGGCAGCAGTRRGGAAT

16SF10 AGATTACCGGAGGCAGCAGTRRGGAAT

16SF11 AGTGGTCAGGAGGCAGCAGTRRGGAAT

16SF12 AGCCGTTTGGAGGCAGCAGTRRGGAAT

16SR1 AGTCGACACTACCRGGGTATCTAATCC

16SR2 AGGAACTCCTACCRGGGTATCTAATCC

16SR3 AGCTGTAGCTACCRGGGTATCTAATCC

16SR4 AGGACACGCTACCRGGGTATCTAATCC

16SR5 AGAGCGAGCTACCRGGGTATCTAATCC

16SR6 AGTCTCTACTACCRGGGTATCTAATCC

16SR7 AGCGTGTCCTACCRGGGTATCTAATCC

16SR8 AGATGCGTCTACCRGGGTATCTAATCC

16SR9 AGAACGCACTACCRGGGTATCTAATCC

16SR10 AGATTACCCTACCRGGGTATCTAATCC

16SR11 AGTGGTCACTACCRGGGTATCTAATCC

16SR12 AGCCGTTTCTACCRGGGTATCTAATCC

618 619

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620 Supplementary Figures 621 Figure S1. Heatmap of metagenome features predicted by PICRUSt and 622 their association with food and N. ceranae infection. Heatmap was drawn 623 by R package ComplexHeatmap. Each column corresponds to a specific 624 sample, each row to a KEGG pathway predicted by PICRUSt. The proportions 625 that each lineage contributed to the full population within each sample are 626 indicated with the color scale to the right of the figure (values from -2 to 2). 627 Metadata is color-coded at the top, including food, and N. ceranae infection. 628 The KEGG pathways were clustered using average linkage hierarchical 629 clustering as default and split by kmeans=5. The mean abundance of each 630 pathway ranged from 0% to 6% was shown with gradual color changes. A non- 631 parametric Wilcox test with FDA adjusted p-values was listed for 632 food(pvalue1) or infection(pvalue2). The labeled KEGG Pathways are 633 with >0.5% mean abundance and only shown significance(p<0.05) at either 634 food (green color) or infection (red color). 635 636

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Food Infection Food Infection Bee_Bread non−infected Bee_Bread non−infected Sugar lowNc Sugar lowNc highNc highNc Samples FoodSamples infection Pores ion channels Protein folding and associated processing cluster1 cluster1 Fatty acid biosynthesis cluster2 cluster2 Valine, leucine and isoleucine biosynthesis Lipopolysaccharide biosynthesis Phenylalanine, tyrosine and tryptophan biosynthesis Pantothenate and CoA biosynthesis cluster3 Starch and sucrose metabolism General function prediction only

cluster3 Signal transduction mechanisms Phosphotransferase system (PTS)

cluster4 Fructose and mannose metabolism

Arginine and proline metabolism Porphyrin and chlorophyll metabolism Membrane and intracellular structural molecules cluster4 Cysteine and methionine metabolism Methane metabolism Glycolysis / Gluconeogenesis cluster5 cluster5 Replication, recombination and repair proteins mean KEGG mean KEGG log10(pvalue1) log10(pvalue2) − − log10(pvalue1) log10(pvalue2)

KEGG mean− − −log10(pvalue1) −log10(pvalue2) KEGG mean −log10(pvalue1)2 Cellular Processes−log10(pvalue2) 6% 1e−10 1e−10 2 Cellular Processes 6% 11e−10 Environmental1e− Information10 Processing 4% 1e−8 1e−8 1 Environmental Information Processing 4% 01e−8 Genetic Information1e−8 Processing 2% 1e−6 1e−6 0 Genetic Information Processing 2% −1e1−6 Metabolism1e−6 1% 1e−4 1e−4 −1 Metabolism 1% −1e2−4 Unclassified1e−4 0.5% 0.01 0.01 −2 Unclassified 0.5% 0.01 0.01 0% 1 1 0% 1 1