Project Description

Research in humans, domesticated and lab animals has shown that early-life condition (e.g. diet, stress) plays a key role in shaping the gut microbiome throughout life and that these variations in the microbiome can have a profound impact on the health, behaviour and performance of their host. Interestingly, it is also well established that, in natural populations, the environmental conditions experienced life in life are one of the prime factors that determine how fast an individual grows, matures, reproduces, and senesces (i.e. individual life history). However, much remains to be done to unravel the role of the gut microbiome at linking early-life condition to life history trajectories in natural populations.

This PhD project will make use of a Swiss population of Alpine swifts that is very well adapted to meet this challenge. Indeed, this natural population has been monitored for more than two decades, providing outstanding information on the life history of most individuals from birth to death. In this species, the growth of nestlings varies greatly from year to year due to variations in climatic conditions from one year to the next, but also between broods in the same year, due to differences between parents in the ability to care for their brood. In addition, in this population, many individuals captured as adults have been studied at the nestling stage, thus giving detailed information on their early growth conditions. Preliminary analyses indicate that early growth conditions have important and lasting effects throughout life.

Using state-of-the-art genomic approaches on faecal samples, this PhD project will allow you to address three main objectives.

  • Objective 1: There is currently no knowledge on the microbiome in this species. Hence, your first objective will be to investigate what are the main factors (e.g. sex, age, natal vs adult social environment) that shape inter-individual variation in gut microbiome diversity measured using 16S rRNA sequencing. For instance, you will be testing whether the microbial diversity changes with age by comparing communities in samples collected from nestlings, young (1-3 years of life), mid-age (5-8 years), and old (12-18 years) adults. Moreover, Alpine swifts live in colonies, and individuals do not change colony after they start reproducing. Hence, this system also allows testing whether the microbiome of an individual is foremost influenced by the environment it is currently living (breeding colony) or the environment it was born (natal colony). Samples to address the first objective will be readily available at the start of the PhD studentship allowing the student to start the project without any delay.
  • Objective 2: Using the knowledge newly acquired from the objective 1, you will then design sampling strategies to effectively test for links between early environment, microbiome diversity, and life history traits. For instance, this could involve the sampling of slow- and fast-growing nestlings and of middle-age adults that grew slowly or fast when they were nestlings to test for associations between early growth conditions and microbiome gut diversity. This dataset can then also be used to test for the influence of early growth conditions and microbiome gut diversity on reproduction and survival rate.
  • Objective 3: Finally, using the knowledge newly acquired from the objective 2, you will explore what could be the pathways that may account for those links using shotgun sequencing to test for differences in functional characterisation of microbial communities between individuals that experienced different early-life conditions and/or expressed different life histories.

Overall, this PhD project will be exploratory. It will therefore have the potential to evolve as new discoveries are made in the project and the literature, and according to the student’s personal interests.

This inter-disciplinary PhD project across microbiology and evolutionary ecology will offer a unique opportunity for the student to gain:

  • general skills in field work using birds (handling, ringing, faecal sample collections) and population monitoring.
  • advanced skills in experimental design to implement sampling strategies allowing to collect the adequate samples for addressing the proposed research questions.
  • advanced skills in metataxonomics, metagenomics and bioinformatics such as 16S rRNA amplicon-based sequencing to investigate microbial diversity and shotgun sequencing to get insights on functional characterisation of microbial communities.
  • advanced skills in statistical modelling to test for the links between microbial diversity and/or functional characterisation of microbial communities. This will be primarily done using the statistical freeware R cran. It will allow the student to learn a variety of statistical approaches (from simple linear regressions to complex Generalised Linear Mixed Models) and selection model approaches.

The student will be based primarily at the University of Aberdeen, under the lead supervision of Dr Pierre Bize, who is evolutionary ecologists addressing the sources of variation in animal life histories. The student will be co-supervised by Prof Sharon Huws at Queen University Belfast who is an expert in Animal Science and Microbiology, Prof Chris Creevey at Queen University Belfast who is an expert in Computational Biology of microbial ecosystems, and Dr Tom Vogwill at the University of Aberdeen who is an expert in Microbiology and Evolutionary Genomics. The student will have the opportunity to participate to fieldwork in Switzerland.

For this PhD project our ideal candidate:

  • has an Honours or a Master in biology
  • is creative, highly motivated and can work alone or in teams
  • has strong interest in animal ecology and microbiology and genomics
  • has strong interest for statistical analyses and past experience with R programming
  • experience with lab work or field work is not essential; but the student should be eager to learn lab work and field work

Funding and eligibility information available here.

Supervisors

Pierre Bize

Primary Supervisor:

Profile: Pierre Bize
Email: pierre.bize@abdn.ac.uk
Institution: University of Aberdeen
Department/School: School of Biological Sciences

Sharon Huws

Secondary Supervisor:

Profile: Sharon Huws
Email: s.huws@qub.ac.uk
Institution: Queen's University, Belfast
Department/School: School of Biological Sciences

Thomas Vogwill

Additional Supervisor:

Profile: Thomas Vogwill
Email: thomas.vogwill@abdn.ac.uk
Institution: University of Aberdeen
Department/School: School of Biological Sciences

Chris Creevey

Additional Supervisor:

Profile: Chris Creevey
Email: chris.creevey@qub.ac.uk
Institution: Queen's University, Belfast
Department/School: School of Biological Sciences

References

Wilkinson TJ, & Huws SA. 2017. Characterization of the Microbiome along the Gastrointestinal Tract of Growing Turkeys. Front Microbiol, 8, 1089. https://doi.org/10.3389/fmicb.2017.01089

Huws SA, Creevey CJ et al. Addressing global ruminant agricultural challenge through understanding the rumen microbiome: past, present, and future. Front Microbiol, 9, 2161. https://doi.org/10.3389/fmicb.2018.02161

Hird SM. 2017. Evolutionary biology needs wild microbiomes. Front Microbiol, 8, 725. https://doi.org/10.3389/fmicb.2017.00725

Research Methods

This project will allow the student to gain

  1. General skills in field work using birds (handling, ringing, faecal sample collections) and population monitoring.
  2. Advanced skills in experimental design to implement sampling strategies allowing to collect the adequate samples for addressing the proposed research questions.
  3. Advanced skills in metataxonomics, metagenomics and bioinformatics such as 16S rRNA amplicon-based sequencing to investigate microbial diversity and shotgun sequencing to get insights on functional characterisation of microbial communities.
  4. Advanced skills in statistical modelling to test for the links between microbial diversity and/or functional characterisation of microbial communities. This will be primarily done using the statistical freeware R cran. It will allow the student to learn a variety of statistical approaches (from simple linear regressions to complex Generalised Linear Mixed Models) and selection model approaches.

Expected Training Provision

Aberdeen University offers an array of courses through the graduate school https://www.abdn.ac.uk/pgrs/ and bespoke training and courses through the QUADRAT DTP https://www.quadrat.ac.uk/training/. In Aberdeen the student will be trained in field ecology and monitoring/sample collection, and in statistical analyses. Queen’s University Belfast also offers an array of courses available through the graduate school https://www.qub.ac.uk/graduate-school/. These courses will be open to the student irrespective of being based most of the time in Aberdeen. More specifically the student will spend time with the supervisors in QUB to gain training in metataxonomic and metagenomic wet lab processing and subsequently computational approaches to analyse sequence data. The timings of these visits will depend upon sample collection and availability. The student will also be encouraged to attend relevant courses outside both universities, attend and present at least two national conferences.

Impact

There is growing recognition from research in medicine and agronomy that the microbiome plays a key role at shaping the health and phenotype of its host, and that part of the variation in the host microbiome diversity in rooted in host early-life conditions. Remarkably, it is well established that, in natural populations, environmental conditions experienced during early-life is one the prime factor shaping the phenotype and life history of individuals. Yet, everything remains to be done to unravel the role of the gut microbiome at linking early-life condition to life history trajectories in natural populations. The proposed project aims to generate new knowledge in a well characterised natural bird population on (i) the sources of individual variation in gut microbiome diversity, including the importance of early growth conditions, and (ii) on the links between microbiome diversity and function and their host life history trajectory. All potential outcomes are likely to provide an important foundation of knowledge and a basis for future studies on the roles of the microbiome in natural populations.

Proposed Supervision

Dr Pierre Bize (UoA) will be the lead supervisor and take in charge the overall management of the PhD project. He will provide samples for the start of the project so that the student can start without any delay, will train the student in the field and provide training and guidance for statistical modelling used for objectives 1 to 3. He will provide the student with unlimited access to the long-term database for the species used in the proposed project and to field sites.

The student will spend time with the co-supervisors in QUB (Prof Sharon Huws and Chris Creevey) to process samples collected in Aberdeen and samples for metataxonomic and metagenomic analysis and subsequent computational approaches to analyse sequence data. The timings of these visits will depend upon sample collection and availability. In UoA, the student will be further supported by Dr Vogwill on topics relating to sample preparation and analysis as well as computational approaches.

The student will sequence samples using the genomics core technology unit in UoA and/or QUB, and with the choice between the 2 platforms will be made depending on the research questions and access to the best cost-effective technology to address it. Whatever the platform that is used, the student will be able to watch the processing and gain insight into the whole procedure. The student will gain access to the UoA and QUB Tier 2 high computing cluster.

All the supervisors will provide advice and guidance on samples required and sampling procedures. All the supervisors will help with the interpretation of the results and comments on the different research chapters and publications which evolve from the studentship.

Proposed Timetable

Year 1

Samples to address the first objective will be readily available at the start of the PhD studentship allowing the student to start the project without any delay.

Training in genomics and bioinformatics: 16S rRNA sequencing.

Analyses of the faecal samples already available to address the objective 1 and interpretation of the results (chapter 1).

Design of a sampling strategy to address the objective 2.

Implementation in the field of the sampling strategy for the objective 2.

 

Year 2

Analyses of the faecal samples to address the objective 2 and interpretation of the results (chapter 2).

Design of a sampling strategy to address the objective 3.

Implementation in the field of the sampling strategy for the objective 3.

Training in genomics and bioinformatics: shotgun sequencing analysis.

 

Year 3+

Analyses of the faecal samples to address the objective 3 and interpretation of the results (chapter 3).

Revision of chapters 1 and 2, if needed, and writing of the general introduction and conclusion.

QUADRAT Themes

  • biodiversity

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