Project Report: Fight fire with fire: Microbes and parasites of Alfalfa Leafcutting Quinn McFrederick, Kaleigh Russell, and Hoang Vuong, UC Riverside Department of Entomology; Theresa Pitts-Singer & Ellen Klinger, Logan Lab Introduction Microbiome: Recent research suggests that the microbiome (= microbial community associated with a host) is important for honey and bumble bee health (1-3). The McFrederick lab studies the microbiome of solitary and wild bees, including the alfalfa leafcutting bee (ALCB). In 2015, we conducted an experiment to investigate the function of the microbiome in ALCB nutrition. We tested the hypothesis that a dominant member of the ALCB microbiome aids pollen digestion. Our data, however, did not support this hypothesis (Fig. 1). Instead we found that the natural microbiome lowered the overall protein content of larvae (Fig. 1). These bees did not have chalkbrood symptoms, suggesting that lower protein is not due to this disease. Protein content of larval food affects adult body size (4), which determines foraging range (5). Members of the natural microbiome may negatively affect ALCB foraging and seed production. In summer 2016, one of our main goals was to study the natural microbiome and ALCB health. We are in the process of identifying microbes associated with lower host protein and lipid levels. To increase ALCB productivity, we aim to identify microbes that may negatively affect ALCB health, which is the first step in their control.

Parasitoids: In recent years, parasitic , such as pumila, have become increasingly problematic for ALCB production. While some control measures for Sapyga exist (e.g. 6), there is the unexplored possibility that microbial pathogens can be used for biological control. We have therefore been studying the microbiome of Sapyga and chalcid parasites. The goal of this project is to identify bacteria or fungi that are found associated with the wasp parasite but not ALCBs. If these microbes are closely related to known pathogens, we can then design future experiments to test their host specificity and possible use as biocontrol agents.

Objectives 1. Identify deleterious microbes in the ALCB larval gut. 2. Identify fungal or bacterial pathogens of parasitic wasps that may be leveraged to control parasitic wasps and not harm ALCBs.

Methods: Objective 1: To identify microbes that compete with ALCB larvae for nutrients, we characterized lipid content, protein content, and the microbiomes of 5th instar ALCB larvae. In July of 2016 Theresa Pitts-Singer and Ellen Klinger of the Logan Bee Lab sent us freshly collected provisions from two sites in Cache County, Utah. We selected brood cells with eggs and weighed each brood cell. We reared larvae in the lab to the last instar. As soon as the larvae molted into the final instar, we pulled them from their brood cell, weighed the remaining pollen, and performed sterile dissection. We saved the gut for microbial sequencing and the rest of the larvae for nutritional analysis. To characterize microbial communities, we are conducting Illumina sequencing of bacterial and fungal communities found in the larval guts, using our standard protocols (7-10). Briefly, we use bacterial (799F, 115R) and fungal (ITS1, ITS2) primers that do not amplify plant plastids (11, 12). The primers include 8 base pair indices, which we use to give each sample a unique label. We clean up the PCR reactions, perform a second reaction that incorporates the Illumina sequencing adapters and primers into the amplicons, normalize the amount of PCR product per reaction, and sequence the resulting DNA on the Illumina MiSeq using V3 reagents for 2 X 300 base pairs. As of January 13, 2017, we received the data from our first sequencing run. We are therefore still in the middle of this research. To measure nutrition, we quantified protein and lipid content of each larvae. First, we weighed the remaining fat bodies after dissecting out the larval guts. We homogenized each separately in 300ul of sterile nanopure water, with two steel 3mm beads in a Qiagen Tissue Lyser II for 6 minutes at 30Hz. We assayed samples and standards in triplicate, using tissue culture U-bottom plates. We incubated the plates with samples and BCA Protein Assay kit at 37 °C for 30 minutes, cooled them to room temperature, then took absorbance measurements at 562nm with the Thermo Scientific Varioskan Lux using the SkanIt software. For lipids, we followed the methods of Judd et al. (13). We thawed the remaining homogenized larvae samples, added 1 ml of 2:1 chloroform to methanol, and vortexed each sample for 30 seconds to dissolve lipid in chloroform. We then centrifuged each sample to at 14,000 x g for 2 minutes. To prepare standards, we dissolved 40mg of Cholesterol in 500 ul of sterile water, then added 3.5 ml of 2:1 chloroform:methanol solution to make 10ug/ul standards. We then assayed the standards and samples in microplate format. To perform the assays, we placed standards and samples in microplates, allowed the chloroform to evaporate, dissolved the remaining lipids in 200 ul of concentrated sulfuric acid, incubated for 20 min at 90 C, cooled the plates to room temperature, and added 50 ul of phosphor-vanillin reagent, which induces color development. We allowed the color to develop for 10 minutes then measured absorbance at 540nm using the SkanIt software on the Thermo Scientific Varioskan Lux.

Objective 2: We obtained samples of sapygid and chalcid parasites from one grower and the Logan Bee Lab. To avoid freeze-thaw cycles of the samples, which affect microbial community analyses (15), we promptly extracted DNA following standard protocols that we helped develop (16). We then conducted two rounds of microbial community analysis as in (10). In one round, we characterized bacterial communities using our standard methods (16). In the second round, we will characterize fungi using our ITS primers as described above. As expected, we received a large number of Sapyga pumila. We also obtained the chalcid wasps Baryscapus megachilidis, Melittobia chalybii, and Pteromalus apum. Roger Burks, a chalcid systematist that works in the UC Riverside Department of Entomology, identified the chalcid wasps. Results Objective 1. To capture variation in nutrition and microbiome composition, we sequenced the microbiome and analyzed lipid and protein content of 95 larvae. We have completed the protein and lipid analyses (Figures 2 and 3). We found variation in both protein and lipid levels at both sites, which we will correlate with specific bacterial taxa. We are currently analyzing our sequencing data, as we had planned in our timeline for this year’s project. We will relate variation in microbial communities to variation in larval nutrition. To determine which microbes co-occur with lower or higher nutritional values, we will use SparCC, a program that identifies co-occurrence between values (14). Objective 2. In total, we analyzed 95 parasitic wasp samples. We have received the 16S bacterial data, and are in the process of analyzing these data. To determine if there are putative biocontrol agents associated with wasps but not bees, we will compare microbiomes from our previous work (10) and objective 1 to wasp microbes. We will especially pay attention to microbes from known pathogens, such as Spiroplasma, Serratia, Wolbachia (reproductive parasite), and fungal pathogens such as Beauvaria. ALCB 5th instar protein contents 4.5 4 3.5 3 2.5 2 1.5 1

mg Protein mg Protein per wet gm mass 0.5 0 Site A Site B

Fig. 2. Average mg protein per gram ALCB larvae. Error bars are standard deviations.

120 ALCB 5th instar lipid contents

100

80

60

40

mg lipids per mg lipidsper gm wet mass 20

0 Site A Site B Fig. 3. Average mg lipid per gm ALCB larvae. Error bars are standard deviations.

Discussion The proposed research will contribute to management and production of healthy ALCB by identifying microbes that negatively affect ALCB nutrition. These microbes can then be targeted for control in future work. We will also identify possible biocontrol agents of wasp parasites. This is the first step towards using microbes as an additional method for control of parasitic wasps, which have the ability to decimate entire operations when not kept in check (6).

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2. Koch H, Schmid-Hempel P. 2011. Socially transmitted gut microbiota protect bumble bees against an intestinal parasite. Proceedings of the National Academy of Sciences 108:19288– 19292.

3. Corby-Harris V, Snyder LA, Schwan MR, Maes P, McFrederick QS, Anderson KE. 2014. Origin and effect of Alpha 2.2 Acetobacteraceae in larvae and description of Parasaccharibacter apium gen. nov., sp. nov. Appl Environ Microbiol 80:7460–7472.

4. Roulston TH, Cane JH. 2002. The effect of pollen protein concentration on body size in the sweat bee Lasioglossum zephyrum (: Apiformes). Evol Ecol 16:49–65.

5. Greenleaf SS, Williams NM, Winfree R, Kremen C. 2007. Bee foraging ranges and their relationship to body size. Oecologia 153:589–596.

6. Torchio PF. 1979. An eight-year field study involving control of Sapyga pumila Cresson (Hymenoptera: Sapygidae), a wasp parasite of the alfalfa leafcutter bee, pacifica Panzer. Journal of the Kansas Entomologocal Society 52:412–419. 7. McFrederick QS, Rehan SM. 2016. A novel approach for simultaneous investigation of pollen and bacterial communities in brood provisions of a small . Mol Ecol 25:2302-2311.

8. McFrederick QS, Wcislo WT, Taylor DR, Ishak HD, Dowd SE, Mueller UG. 2012. Environment or kin: whence do bees obtain acidophilic bacteria? Mol Ecol 21:1754–1768.

9. McFrederick QS, Wcislo WT, Hout MC, Mueller UG. 2014. Host species and developmental stage, but not host social structure, affects bacterial community structure in socially polymorphic bees. FEMS Microbiol Ecol 88:398–406.

10. McFrederick QS, Mueller UG, James RR. 2014. Interactions between fungi and bacteria influence microbial community structure in the Megachile rotundata larval gut. Proceedings of the Royal Society B-Biological Sciences 281:20132653.

11. Hanshew AS, Mason CJ, Raffa KF, Currie CR. 2013. Minimization of chloroplast contamination in 16S rRNA gene pyrosequencing of insect herbivore bacterial communities. J Microbiol Methods 95:149–155.

12. Smith DP, Peay KG. 2014. Sequence depth, not PCR replication, improves ecological inference from next generation DNA sequencing. PLoS One 9:e90234.

13. Judd TM, Magnus RM, Fasnacht MP. 2010. A nutritional profile of the social wasp metricus: differences in nutrient levels between castes and changes within castes during the annual life cycle. J Insect Physiol 56:42–56.

14. Friedman J, Alm EJ. 2012. Inferring correlation networks from genomic survey data. PLoS Comput Biol 8:e1002687.

15. Sergeant MJ, Constantinidou C, Cogan T, Penn CW, Pallen MJ. 2012. High-throughput sequencing of 16S rRNA gene amplicons: Effects of extraction procedure, primer length and annealing temperature. PLoS One 7:e38094.

16. Engel P, James RR, Koga R, Kwong WK, McFrederick QS, Moran NA. 2013. Standard methods for research on Apis mellifera gut symbionts. Journal of Apicultural Research 52:1–24.