Periodic Reporting for period 3 - DEUSBIO (Deciphering and Engineering the overlooked but Universal phenomenon of Subpopulations in BIOtechnology)
Berichtszeitraum: 2024-03-01 bis 2025-08-31
The project was designed to address the phenomenon of microbial subpopulation in the context of bioproduction. Defined subpopulations emerging from genetically identical cells have been found across all forms of life, including microorganisms. Understanding microbial subpopulations has great importance in a variety of fields for example biomedicine in antimicrobial resistance research or environmental microbiome. Here we are focusing on bioproduction, where the appearance of low-producing and slow-growing cells limit overall yields and productivities. Addressing this issue would enable the creation of more profitable bioprocess, which is key to develop a bio-based economy. Despite their biological and biotechnological relevance, this universal phenomenon has not been largely overlooked in part due to technical limitations arising from using single cell methodologies and analysis tools. Only recently, latest developments of robust single cell sequencing techniques have been developed, which can be now employed to study microbial subpopulations. Such advances, together with the blooming of synthetic biology tools that we and others have developed to facilitate strain engineering, make this project timely.
This ambitions project will have a high impact in both fundamental and industrial research and could challenge our current conception of clonal populations. The global economy faces many societal challenges, including dealing with climate change, a growing population to be fed and kept healthy and an unsustainable dependence on non-renewable resources. The current manufacturing of most chemicals, energy, materials, and consumer products relies on the exploitation of fossil fuels, which are non-renewable and limited. It is therefore urgent to find new production technologies, utilising renewable sources, such as those provided by Industrial Biotechnology. Microbial-based bioproduction can convert low-cost substrates into chemicals, materials, or fuels in an eco-friendly manner. Despite the advantages offered by microbial biotechnology, few bioprocesses have reached the market due to high production costs and low yields.
The overall objectives of the DEUSBIO project are:
1. Identify the main types of subpopulations that emerge in yeast under different growth and production conditions.
2. Develop tools to monitor and characterize heterogeneity at the single-cell level.
3. Uncover the genetic determinants—specific genomic regions and regulators—responsible for the formation of these subpopulations.
4. Engineer more homogeneous yeast populations with enhanced and consistent bioproduction capacities
5. Explore community-based strategies (e.g. division of labour) to reduce cell stress that can lead to heterogeneity.
This ambitions project will have a high impact in both fundamental and industrial research and could challenge our current conception of clonal populations. The global economy faces many societal challenges, including dealing with climate change, a growing population to be fed and kept healthy and an unsustainable dependence on non-renewable resources. The current manufacturing of most chemicals, energy, materials, and consumer products relies on the exploitation of fossil fuels, which are non-renewable and limited. It is therefore urgent to find new production technologies, utilising renewable sources, such as those provided by Industrial Biotechnology. Microbial-based bioproduction can convert low-cost substrates into chemicals, materials, or fuels in an eco-friendly manner. Despite the advantages offered by microbial biotechnology, few bioprocesses have reached the market due to high production costs and low yields.
The overall objectives of the DEUSBIO project are:
1. Identify the main types of subpopulations that emerge in yeast under different growth and production conditions.
2. Develop tools to monitor and characterize heterogeneity at the single-cell level.
3. Uncover the genetic determinants—specific genomic regions and regulators—responsible for the formation of these subpopulations.
4. Engineer more homogeneous yeast populations with enhanced and consistent bioproduction capacities
5. Explore community-based strategies (e.g. division of labour) to reduce cell stress that can lead to heterogeneity.
UP to now, we have conducted the work according to the project plan and timeline.
We have successfully identified and characterised phenotypic subpopulations using FACS-based transcriptomics, fluorescent metabolic sensors, and a GFP-tagged protein library. We generated a catalogue of transcriptional subpopulation in yeast and a library of strains with different subpopulations marked with fluorescence reporters. We also used knockout libraries to uncover key regulators of heterogeneity. With these methods, we identified the mechanisms involved in the emergence of subpopulations. While single-cell RNA sequencing has not yet been fully implemented due to technical challenges, we are actively developing protocols and exploring SPLiT-seq as a scalable alternative.
The project has now shifted toward translational applications, including strain engineering and community-based strategies to mitigate heterogeneity and enhance bioproduction yields and we are working on engineering yeasts to produce homogeneous cells to increase yield in bioproduction.
Each of our finding and achievements are now in preparation for publications in leading scientific journals (some of them already published).
We have successfully identified and characterised phenotypic subpopulations using FACS-based transcriptomics, fluorescent metabolic sensors, and a GFP-tagged protein library. We generated a catalogue of transcriptional subpopulation in yeast and a library of strains with different subpopulations marked with fluorescence reporters. We also used knockout libraries to uncover key regulators of heterogeneity. With these methods, we identified the mechanisms involved in the emergence of subpopulations. While single-cell RNA sequencing has not yet been fully implemented due to technical challenges, we are actively developing protocols and exploring SPLiT-seq as a scalable alternative.
The project has now shifted toward translational applications, including strain engineering and community-based strategies to mitigate heterogeneity and enhance bioproduction yields and we are working on engineering yeasts to produce homogeneous cells to increase yield in bioproduction.
Each of our finding and achievements are now in preparation for publications in leading scientific journals (some of them already published).
This project has advanced the state of the art by providing a comprehensive, multi-layered understanding of phenotypic heterogeneity in yeast and its impact on bioproduction. We have developed and applied innovative tools, including a GFP-tagged protein library, fluorescent metabolic sensors, and subpopulation transcriptomics via FACS, to dynamically track and characterise subpopulations in live cells. These approaches have enabled us to uncover regulatory mechanisms, including key genetic determinants of heterogeneity identified through systematic knockout screening. By the end of the project, we will have a homogenised best-in-class yeast population created at the lab for the first time.
We currently explore the effects of natural community behaviours on molecular expression pathways, identifying features that support division of labour and reduce cellular burden, which will lead to the best production yield strain.
Once we create a homogenised yeast population, we will engineer the strains in order to produce high-value molecules.
The project outcomes are or will be published either in journals with an interest in bioproduction, microbial communities and synthetic biology, such as Nature Communications, Nature Biotechnology, Metabolic Engineering, and Nature Microbiology. These results will be presented at the Gordon Conference in Synthetic Biology, the major conference in the field, which takes place every two years in the USA.
We currently explore the effects of natural community behaviours on molecular expression pathways, identifying features that support division of labour and reduce cellular burden, which will lead to the best production yield strain.
Once we create a homogenised yeast population, we will engineer the strains in order to produce high-value molecules.
The project outcomes are or will be published either in journals with an interest in bioproduction, microbial communities and synthetic biology, such as Nature Communications, Nature Biotechnology, Metabolic Engineering, and Nature Microbiology. These results will be presented at the Gordon Conference in Synthetic Biology, the major conference in the field, which takes place every two years in the USA.