1. Bioinformatics and AD microbiome modelling
This project “AI for Net Zero” aims to rapidly transform the anaerobic digestion (AD) industry into a data-driven, digitalised sector, to accelerate and enhance its contributions to a Net-Zero UK. Due to the complexities of predicting how different waste feedstocks and different microbial communities will interact under varying operating conditions, current AD production systems use conservative approaches to avoid process upset, which limits the full potential of AD. This project has a multi-disciplinary team from across the UK to develop novel AI approaches, combined with process systems engineering, systems biology, and life-cycle assessment to develop whole-systems decision-making tools informed by detailed sub-system modelling.The AD microbiome team will investigate AD microbiome dynamic responses to feedstock variation, operational conditions and biogas production at industrial- and lab-scale AD bioreactors, and reveal underlying metabolic pathways and key features. Molecular biological methods (qPCR, RT-qPCR, amplicon sequencing, metagenomics and metatranscriptomics) will be used to characterise microbial community composition and functional pathways and data will be used to build AD microbiome models.The PDRA will:
Coordinate sample collection from university labs and industrial collaborator’s sites.Analyse collected samples, DNA/RNA extraction and sequencing.Bioinformatics data analysisSupport project team and other group membersSupervise PhD students on bioinformaticsDuration: one year contract with possibility to renew.
2. Environmental AMR in UK-Canada dairy farms
This project is a collaboration between University of Surrey, UK, and McGill University, Canada, to investigate, in complex microbiomes in dairy cattle and associated environments, how AMR can be affected/controlled by microbial ecological interactions. Field samples from organic and conventional dairy farms in UK and Canada will be analysed and compared on microbiome and AMR. Collective results using shotgun metagenomics tools and high-throughput multiplexed amplicon sequencing and ddPCR methods will generate an overview and detailed information on AMR burden in dairy farms. The project aims to construct isolation libraries and synthetic microbial community (which improves reproducibility and replications) to create model microbiome for mechanistic investigations of ecological interactions and AMR. This project will contribute to the long-term goal of AMR transmission mitigation.The PDRA will:
Coordinate and conduct filed sampling campaign from UK dairy farms.Analyse collected samples, DNA extraction and sequencing, chemical analysis.Data analysis (with help from bioinformatician)Test and design synthetic microbiomeTravel to Canadian collaborator lab and get training.Side project: Supervise PhD students for qPCR analysis of N-cycling genes in wastewater treatment systems.Duration: one year contract with possibility to renew.
Website:
https://www.surrey.ac.uk/people/bing-guo
Email:
b.guo@surrey.ac.uk
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