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Livestock Metabolomics: Investigating Metabolic Signatures of Methane Mitigation in Beef Cattle

Funding
Funded
Study mode
Full-time
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Subject area
Biological and Biomedical Sciences
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Overview

Enteric methane from cattle is a major contributor to agricultural greenhouse gas emissions and a significant loss of dietary energy. This fully funded PhD will use untargeted metabolomics to investigate the long-term metabolic impacts of methane-suppressing feed additives in the rumen microbiota of beef cattle, identifying biomarkers linked to methane reduction, animal performance, health, and sustainability.

About this opportunity

Research Background

Agriculture contributes approximately 27% of greenhouse gas (GHG) emissions in Northern Ireland, with ruminant livestock representing the largest source. Enteric methane (CH₄) emissions from cattle account for more than half of farm-gate emissions and remain a major challenge in achieving the UK’s Net Zero targets by 2050. While improvements in genetics, nutrition, and productivity have reduced methane intensity per unit of meat produced, further reductions are required to offset increasing global demand for animal protein.

Methane production in the rumen represents not only an environmental concern but also a loss of 2–12% of dietary energy consumed by the animal. Recent advances in methane-suppressing feed additives, including TRADILIN 130 and Asparagopsis spp., have demonstrated considerable potential to reduce methane emissions. However, significant knowledge gaps remain regarding their long-term effects on animal performance, metabolism, health, rumen microbial ecology, welfare, and beef quality. In particular, little is known about the systemic metabolic adaptations of the rumen microbiota associated with sustained methane mitigation strategies and whether specific metabolic signatures can predict methane emissions, feed efficiency, or animal resilience.

This fully funded PhD project will address these knowledge gaps by applying state-of-the-art untargeted metabolomics to investigate the metabolic responses of dairy-origin beef cattle exposed to methane-suppressing feed additives throughout their entire production cycle. The project will generate novel insights into the biological mechanisms underpinning methane reduction and identify biomarkers associated with improved productivity and sustainability.

Aims and Objectives

  • Evaluate the long-term effects of methane-suppressing feed additives on animal growth, feed efficiency, health, and welfare.
  • Conduct comprehensive untargeted metabolomic profiling of serum, plasma and rumen fluid samples collected across key developmental stages.
  • Identify metabolic pathways and biomarkers associated with methane reduction, feed efficiency, animal health, and productive performance.
  • Integrate metabolomics data with methane emissions, rumen microbiome composition, and animal phenotypes to improve understanding of host–microbiome interactions.

 

Training and collaboration

This PhD project is supported by the Department of Biochemistry, Cell and Systems Biology (BCSB) at the University of Liverpool, the Department of Chemistry and the Sustainable Livestock Systems Branch at the Agri-Food and Biosciences Institute (AFBI), Northern Ireland. The PhD student will be based at the University of Liverpool’s  centre for metabolomics research (CMR), which is equipped with the state of the art mass spectrometry, nuclear magnetic resonance (NMR) spectroscopy, as well as Raman and infrared microspectroscopy instrumentations, and is a world leader in this area.

The student will also be associated with AFBI, which is providing full funding for the student and the research project. At AFBI, the student will undertake field and lab work to investigate the long-term metabolic impacts of methane-suppressing feed additives in beef cattle. The student will be trained and responsible for professional conduct of animal handling and field work across the production cycle, including monitoring cattle performance, data recording, health and welfare, and collecting biological samples (i.e., serum, plasma, rumen fluid, etc.) at multiple timepoints of the animal’s developmental stages. The student will also be supporting the collection of methane emissions data, rumen microbiome, phenotypic data/samples and any other task required for the project. By engaging in the sample collection and data analysis, the student will have the opportunity to develop expertise under the guidance of AFBI technicians and research scientists while developing hands-on experience using AFBI’s cutting-edge, high-tech animal facilities and equipment.

Scientific skills:

The student will have the opportunity to receive training in mass spectrometry, metabolomics, biochemistry, data processing, and animal husbandry, enabling the development of a broad and interdisciplinary scientific skill set. By the end of the PhD programme, the student will have developed a distinctive competitive advantage in the emerging field of livestock metabolomics, through the integration of field experience, laboratory expertise, and a strong publication record.

 

Transferable skills:

The student will participate in fortnightly meetings with the wider research team and will prepare and submit monthly progress reports to the supervisory team. This process will strengthen the student’s written communication skills, analytical thinking, data interpretation, statistical analysis, project management, and understanding of results within the multidisciplinary context of the project. Career development opportunities will be discussed from an early stage to support the student in pursuing activities aligned with their chosen career pathway. Attendance at national and international conferences will further enhance transferable skills, encourage collaboration, and provide opportunities to present research findings to the wider scientific community. The student will also have access to a great resource of professional development options through AFBI Learning and Development. The supervisory committee will strongly advise and support the student to strengthen their transferable skills simultaneous to developing scientific skills.

 

Managerial skills:

Training and support will also be provided in the design and execution of laboratory experiments, alongside the organisational and administrative skills required to successfully manage and complete a complex multidisciplinary research project.

Further reading

  • Goldansaz, S. A., Guo, A. C., Sajed, T., Steele, M. A., Plastow, G. S., & Wishart, D. S. (2017). Livestock metabolomics and the livestock metabolome: A systematic review. PloS one, 12(5), e0177675.
  • Razban, V., Carballo, O. C., Morrison, S., & Shirali, M. (2026). RNA-Seq Analysis of Ruminal Methane Emissions in Beef-on-Dairy Cattle: Evidence for Immune, Nervous, and Endocrine Pathway Involvement. Animals, 16(4), 589.
  • Thompson, J. P., Cristobal-Carballo, O., Yan, T., Lawther, K., Dimonaco, N. J., Zeller, W. E., … & Theodoridou, K. (2025). Unlocking the potential of willow condensed tannins: effects on rumen fermentation, microbiome, and metabolome for sustainable ruminant nutrition. Animal Microbiome, 7(1), 81.

Cristobal-Carballo, O., McCoard, S. A., Cookson, A. L., Ganesh, S., Lowe, K., Laven, R. A., & Muetzel, S. (2021). Effect of methane inhibitors on ruminal microbiota during early life and its relationship with ruminal metabolism and growth in calves. Frontiers in microbiology, 12, 710914.

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Who is this for?

Eligibility: UK students with the equivalent of at least a 2.1 Honours degree in Animal Science, Chemistry, or a biological discipline including: Biology or Biochemistry.

An interview will be undertaken with suitable candidates before an offer is made.

Fees and a stipend for 4 years will be paid, provided eligibility is met.

This studentship is fully supported by AFBI and is particularly relevant to candidates with an interest in sustainable livestock systems, methane mitigation and agricultural greenhouse gas emissions in Northern Ireland (NI). Applicants from NI and the island of Ireland are encouraged to apply. All applications will be assessed on merit, subject to the relevant eligibility requirements.

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How to apply

  1. 1. Contact supervisors

    Applicants should apply by e-mailing Dr Howbeer Muhamadali (Howbeer.Muhamad-ali@liverpool.ac.uk) and Dr Seyed Ali Goldansaz (SeyedAli.Goldansaz@afbini.gov.uk).

    Supervisors Email address Staff profile URL
    Dr Howbeer Muhamadali Howbeer.Muhamad-ali@liverpool.ac.uk https://www.liverpool.ac.uk/people/howbeer-muhamad-ali
    Dr Seyed Ali Goldansaz SeyedAli.Goldansaz@afbini.gov.uk n/a
    Dr Omar Cristobal Carballo OmarCristobal.Carballo@afbini.gov.uk n/a
  2. 2. Prepare your application documents

    Applicants should submit:

    • CV, including details of academic qualifications, research experience, publications (if applicable), and relevant skills.
    • A cover letter outlining their motivation for undertaking the PhD and their suitability for the project.
    • A research proposal (maximum 2 pages) relevant to the theme of the PhD programme, demonstrating the applicant’s understanding of the research area, ability to formulate research questions, and potential approach to addressing them.
    • Two reference letters, submitted directly by referees or included with the application:

    One reference should comment primarily on the applicant’s academic merit, research potential, and ability to undertake doctoral-level study.

    The second reference should comment primarily on the applicant’s character, professionalism, interpersonal skills, and suitability for a research environment.

  3. 3. Apply

    Finally, register and apply online. You'll receive an email acknowledgment once you've submitted your application. We'll be in touch with further details about what happens next.

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Funding your PhD

Tuition fees and a stipend for 4 years will be paid, provided eligibility is met.

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Contact us

Have a question about this research opportunity or studying a PhD with us? Please get in touch with us, using the contact details below, and we’ll be happy to assist you.

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