| Literature DB >> 27118586 |
Philipp Engel1, Waldan K Kwong2, Quinn McFrederick3, Kirk E Anderson4, Seth Michael Barribeau5, James Angus Chandler6, R Scott Cornman7, Jacques Dainat8, Joachim R de Miranda9, Vincent Doublet10, Olivier Emery11, Jay D Evans12, Laurent Farinelli13, Michelle L Flenniken14, Fredrik Granberg15, Juris A Grasis16, Laurent Gauthier17, Juliette Hayer18, Hauke Koch19, Sarah Kocher20, Vincent G Martinson21, Nancy Moran22, Monica Munoz-Torres23, Irene Newton24, Robert J Paxton10, Eli Powell22, Ben M Sadd25, Paul Schmid-Hempel26, Regula Schmid-Hempel26, Se Jin Song27, Ryan S Schwarz12, Dennis vanEngelsdorp28, Benjamin Dainat29.
Abstract
As pollinators, bees are cornerstones for terrestrial ecosystem stability and key components in agricultural productivity. All animals, including bees, are associated with a diverse community of microbes, commonly referred to as the microbiome. The bee microbiome is likely to be a crucial factor affecting host health. However, with the exception of a few pathogens, the impacts of most members of the bee microbiome on host health are poorly understood. Further, the evolutionary and ecological forces that shape and change the microbiome are unclear. Here, we discuss recent progress in our understanding of the bee microbiome, and we present challenges associated with its investigation. We conclude that global coordination of research efforts is needed to fully understand the complex and highly dynamic nature of the interplay between the bee microbiome, its host, and the environment. High-throughput sequencing technologies are ideal for exploring complex biological systems, including host-microbe interactions. To maximize their value and to improve assessment of the factors affecting bee health, sequence data should be archived, curated, and analyzed in ways that promote the synthesis of different studies. To this end, the BeeBiome consortium aims to develop an online database which would provide reference sequences, archive metadata, and host analytical resources. The goal would be to support applied and fundamental research on bees and their associated microbes and to provide a collaborative framework for sharing primary data from different research programs, thus furthering our understanding of the bee microbiome and its impact on pollinator health.Entities:
Mesh:
Year: 2016 PMID: 27118586 PMCID: PMC4850275 DOI: 10.1128/mBio.02164-15
Source DB: PubMed Journal: MBio Impact factor: 7.867
Outstanding questions in bee microbiome research
| Field of knowledge | Research question |
|---|---|
| Bee health | |
| 1. | How do different microbes impact bee health? |
| a. | Nutritional versus defensive symbioses? |
| b. | Host range and fitness effects of pathogens? |
| 2. | Which combinations of microbes are most detrimental or beneficial? |
| 3. | Do microbes in wild and managed bee populations influence health in similar ways? |
| 4. | How do environmental factors influence host-microbiome interactions? |
| 5. | How do the interactions among microbiome members modulate the impact of individual members, to the benefit or cost to the host? |
| Evolution and ecology | |
| 1. | What are the functions of the different microbes in the bee gut? |
| 2. | Which factors drive the composition and evolution of the bee microbiome? |
| 3. | How does the social/solitary lifestyle of bees influence microbiome evolution? |
| 4. | How has domestication changed the bee microbiome? |
Major challenges for bee microbiome studies
| Area of study | Questions and considerations |
|---|---|
| 1. Defining bee health | What are the best measures of fitness at the individual and colony levels? In social insects, fitness experiments with individual bees may not reflect the fitness of a colony. |
| 2. Microbiome composition | How do distinct microbes interact to affect hosts? Microbes likely influence one another’s effect on the host. Coinfections pose a challenge for disentangling individual roles, and certain experiments may need to be conducted in microbiome-free hosts. |
| 3. Host genetics | Bees are genetically diverse, which may affect microbiome-host interactions. Can the influence of genetic differences among hosts be controlled for? |
| 4. Environmental factors | These are likely to contribute to microbiome composition and function. How can such environmental factors be reliably measured and tested? |
| 5. Physiological variables | The physiology and development of bees can differ substantially according to season, age, housing, and nutrition. Do these differences influence microbiome relationships? |
| 6. Microbiome quantification | Different diagnostic tools (quantitative and qualitative) exist to study microbiome compositions. How comparable are these tools? |
| 7. Wild pollinators | For the majority of the ~20,000 wild bee species, the microbiome composition and functions are unknown. Systematic and standardized sampling approaches are needed. |
| 8. Data accessibility | Systematic archiving of large sequencing datasets with accompanying metadata information is crucial so that cross-study analyses can be conducted. |
FIG 1 A resource and analysis platform for bee microbiome studies. Large amounts of sequence data, metadata, and methods are being generated by different research groups around the globe. A centralized platform is needed to systematically archive such information, to make it available to other researchers in the field, to allow cross-study analyses, and to standardize approaches. The bee microbiome platform will enable more detailed analyses of available data to formulate novel hypotheses about bee health and microbiome evolution.
Practical steps for advancements
| Challenge and step |
|---|
| 1. Many microbes are important to bee biology, but often an experiment focuses on only one type. Simultaneous screening for 16S rRNA genes, 18S rRNA genes, and viruses is needed to yield a more comprehensive picture of the microbiome. |
| 2. If simultaneous screening as proposed in step 1 is not feasible, archiving aliquots of DNA/RNA/whole samples will facilitate future identification of the other microbes. |
| 3. Quantitative PCR of total individual (i.e., per bee) microbial loads will help with the interpretation of relative compositional data, as typically acquired by amplicon sequencing. |
| 4. Proper metadata are needed for interpretation and comparison of results. As much information as possible should be recorded and made accessible for an experiment. |
| 5. Standardized experimental bee lines should be established to control for host genetic differences between laboratories. |
| 6. Standardization of protocols, such as the methods of isolation of host, bacterial, and viral DNA/RNA, is necessary for cross-study analysis. |
| 7. Sampling and sequencing environmental sources, such as flowers and nest components, will help to understand the spread and transmission of bee microbes. |
| 8. Bee microbiome researchers should be engaged to actively participate in the bee microbiome project and to help establish this necessary and important community service. |