Nutrigenomics and the resilience of bees in a changing climate

Ecosystem stability and global food security depend upon healthy populations of bees, our foremost pollinators. Bees provide pollination services worth hundreds of billions of pounds annually. Honeybees and bumblebees are our most important managed pollinators, but the UK is home to ~245 species of wild solitary bees which collectively perform most pollination.

Unfortunately, bee populations are declining, with multiple causes. Key to bee survival and fitness is nutrition; all bees feed offspring with pollen gathered from the landscape. But human influences such as agricultural intensification are altering nutritional landscapes for bees [3,4], and fundamentally affecting gene expression, growth and reproduction. Most of what we know about bee nutrition comes from studies in social bees like honeybees or bumblebees [5,6], where nutrition influences caste determination, development, pathogen resistance and others. However, the nutritional ecology of other bees, particularly solitary bees, is largely unstudied. Unless these bees can detect and respond to changes in nutritional landscapes, their fitness will be reduced – a scenario we term a “nutritional trap”.

Human activity is also changing climates and raising average temperatures. Temperature affects animals’ metabolic rate, physiology, digestion, and nutrient assimilation, as well as gene expression. Dr Gilbert’s recent work [7] has identified the need to store enough carbohydrate and fat to survive the winter as potentially critical for solitary bees’ nutritional ecology. But we know little about how this is regulated, how climate change will affect bees, and how bees will deal with changing nutritional landscapes in a future filled with uncertainty.

Graph showing cocoon weight of Osmia bicornis bee larvae (colour-coded from blue to red) according to protein and carbohydrate eaten before pupation.
Figure 1. Cocoon weight of Osmia bicornis bee larvae (colour-coded from blue to red) according to protein and carbohydrate eaten before pupation. Larvae with highest weights (red) ate low protein but high carbohydrate. Larvae were kept on fixed diets with different ratios of protein and carbohydrate, and different overall nutrient concentrations. Taken from [7] (click image to view).
We are now, for the first time, in a position to understand not just whether but also how different nutritional landscapes and climates affect bees. This exciting cross-institutional project combines field ecology with cutting edge molecular approaches to address a crucial knowledge gap about how bees are being affected by human-altered nutritional landscapes. This project addresses issues relevant for pure ecological science, conservation biology, agriculture and crop science.

At Hull, Dr Gilbert’s lab has pioneered rearing protocols for the economically and ecologically important solitary bee, Osmia bicornis. This work is providing an unprecedented window onto bee nutritional ecology (Figure 1). At Leeds, Dr Duncan’s lab uses a variety of cutting-edge molecular tools to understand how bees are influenced by their environment. Dr Duncan has conducted groundbreaking work on how nutrition affects gene expression in developing bees (Figure 2), as well as recent work on the environmental and molecular control of reproduction in O. bicornis. The student will capitalise on this timely opportunity to synthesize the research interests of these two research groups and create collaborative links between institutions. The candidate will be integrated into both lab groups and will benefit from the infrastructure and connections at both universities.

 

Differences in larval nutrition in the honeybee results in gene expression changes and ultimately adult bees with different reproductive potential and lifespan.
Figure 2. Differences in larval nutrition in the honeybee results in gene expression changes and ultimately adult bees with different reproductive potential and lifespan (queens are reproductive and long-lived, workers are sterile and short-lived) (Click image to view paper). Honeybee worker and queen images used with permission of Alexander Wild and royal Jelly image used under creative commons licence (Waugsberg [CC BY-SA 3.0 (https://creativecommons.org/licenses/by-sa/3.0)]
Using careful manipulations within controlled laboratory environments, the student will first establish how dietary macronutrients affect the fitness of solitary bee larvae in response to changes in rearing temperature. Then, they will use high-throughput sequencing technology to examine genome-wide expression profiles of larvae receiving different diet and temperature treatments, to understand the molecular and physiological mechanisms underlying bees’ responses to landscape and climate change. Nutritional cues are known to alter gene expression [8], but to date studies have focussed largely on a few genes, and only in honeybees. The student will compare larvae receiving different treatments in (1) choices larvae make about which nutrients to consume, (2) correlates of fitness such as body size and overwinter survival, and (3) expression of growth- versus diapause-related genes.

Outcomes: The findings will, firstly, shed light on the optimal nutrition for bees – both currently, and in a warmer future. They will help inform active measures such as wildflower strips to conserve and promote these vital pollinators as the climate changes. Secondly, results will also show the physiological effects of different nutritional landscapes upon bees, now and in the future, allowing us a detailed understanding of the resilience of solitary bees to landscape change in a changing climate. Finally, the results will provide comparisons and contrasts with existing knowledge of social bee gene expression, physiology and nutrigenomics, providing unparalleled insights into bee nutritional ecology.

For details please contact Dr James Gilbert (james.gilbert@hull.ac.uk).

References: 1. Coley P, et al. Oecologia. 2002;133: 62–69. 2. Rothman JM, et al. Ecology. 2015;96: 873–878. 3. Naug D. Biol Conserv. 2009;142: 2369–2372. 4. Donkersley P, et al. Ecol Evol. 2014;4: 4195–4206. 5. Paoli PP, et al. Amino Acids. 2014;46: 1449–1458. 6. Helm BR, et al. Biol Open. 2017;6: 872–880. 7. Austin AJ, Gilbert JDJ. bioRxiv. 2018; https://www.biorxiv.org/content/10.1101/397802v1.abstract 8. Di Pasquale G, et al. PLoS One. 2013;8: e72016.