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Loss of habitat and chemical use associated with agriculture can cause population declines of wild pollinators. Less is known about the evolutionary consequences of interactions between species used in commercial agriculture and wild pollinators. Given population declines of many wild bee species, it is crucial to understand if commercial queens become established in natural areas, if wild bees visit agricultural fields and have the potential to interact with commercial bees, and if gene flow occurs between commercial and wild bees. We drew on a long-term data set that documents commercial bumble bee (Bombus impatiens) use in New England, and we conducted genetic analyses of foraging B. impatiens from areas with varying intensities of commercial bee use. In agricultural areas with a history of commercial bee use we also sampled bees directly from commercial hives. We found significant genetic differences among foraging B. impatiens and B. impatiens sampled directly from hives (average pairwise F′ST = 0.14), but not among samples of foraging bees from natural areas (average F′ST among foraging bees = 0.002). Furthermore, Bayesian analysis of population structure revealed that foraging bees caught in areas with a history of commercial bee use grouped with samples from natural areas. These results document an agricultural setting where there was no widespread introgression of alleles from commercial bumble bees to wild bumble bees, commercial bumble bees did not become established in natural areas, and wild bees were providing pollination services to crops.

The identification of therapeutic nanoparticles formulation with preferential distribution to the tumor microenvironment remains an unsolved challenge. We have developed a high-throughput synthesis and screening platform to discover novel tumor-targeting liposomal nanoparticles. Over 1,000 unique liposomal formulations were synthesized using a combinatorial approach. The characterization of physicochemical properties (e.g., size, charge and stability) allowed the prioritization of ~500 formulations further profiled with in vitro cell-based assays (e.g., cell binding, cytotoxicity and cell barrier crossing). A subset of formulations with diverse properties was selected to create a library of 47 DNA-barcoded nanoparticles. The pharmacokinetics and biodistribution of the formulations library were measured in tumor xenografts mouse models in a highly multiplexed fashion by sequencing the DNA barcodes. The established synthesis and screening platform provides an effective approach to identify novel liposomal formulations with improved tumor and tissue distribution profile. Note: This abstract was not presented at the conference. Citation Format: Mark Audeh, Manali Dwarakanath, Michael Hopkins, Alisha Knudson, Sally Kwok, Stephen Morton, Nikki Peck, Tim Ruckh, Sarah Sanowar, Zach Scott, Peter Thana, Gary Tong, Aaron Topol, Alberto C Vitari, Eugeni Vaisberg, Jane Wang, Stanley Wong. High-throughput synthesis and screening for tumor-targeting liposomal nanoparticles [abstract]. In: Proceedings of the AACR Special Conference on Tumor Immunology and Immunotherapy; 2018 Nov 27-30; Miami Beach, FL. Philadelphia (PA): AACR; Cancer Immunol Res 2020;8(4 Suppl):Abstract nr B66.