Prof. Dr. Filipe Cabreiro

Research Area: Ageing and the Microbiome

Website: Cabreiro Lab

 

1. Research Background:

Dysregulation of host metabolism and immunity underlies a vast proportion of human diseases but also ageing. Recent evidence shows that disease arises from the complex interactions between the genetic make-up of the host and the environment. The microbiota, a key environmental factor, regulates most aspects of human physiology and consequently the propensity for ill-health but the dynamics and factors that govern the interactions between host and microbe in the context of disease are poorly understood. We aim at unraveling the mechanisms underlying metabolic disease, through the study of the physiology of the entire holobiont (the host and its associated commensal microbes) and how it is influenced by environmental factors (e.g. diet, drugs). Such approach is essential to develop new predictive tools for drug action and discover novel and efficient pharmacological approaches to treat disease. Recent findings from our lab highlight the therapeutic power of genetically or pharmacologically manipulating intestinal microbiota to ensure host metabolic health, treat disease (e.g. type-2 diabetes and cancer) and improve healthy ageing. Ultimately, our goal is to identify precise and robust drugable mechanisms in both host cells and gut bacteria that will be harnessed for the treatment of metabolic disease and create avenues for translational applications for treating human disease.

Lab Aims:

  1. Develop experimental and computational tools to study the causal relationship between host genetics, microbial genetics and nutrient interactions in the context of ageing;
  2. Discover combinatorial (drug-drug) pharmacological and/or pharmacomicrobiomic (drug-microbe) approaches to treat metabolic disease and improve ageing;
  3. Testing evolutionary conservation of findings in mouse models and humans.

2. Research questions addresses by the group:

How do microbes communicate with host cells? What molecules or mechanisms are implicated? What organelles and cellular mechanisms sense microbial cues? How do cells mount adequate responses to such cues to maintain cellular homeostasis during ageing? How do microbes hijack host cellular metabolism for their own benefit.

3. Possible projects:

  1. Microbe-IAge: We aim to investigate the thousands of new genes that exist in the human and earth microbiome and discover biosynthetic clusters producing novel molecules that activate pro-longevity programs in C. elegans (focus on microbe-mitochondrial communication) and increase health and lifespan in both worms and mice.
    Areas: Ageing, Organismal biology, systems biology, chemistry, genomics, evolution, synthetic biology, microbiology.
  2. Awakening longevity drugs with gut microbes. We will utilize the 3 billion gene pool catalogue of the human gut microbiota to act as microbial factories and chemically modify FDA approved drugs. These will be tested in a high-throughput manner in C. elegans for improving ageing and hits will be further validated in other models such as cell systems and mouse models.
    Areas: Ageing, Organismal biology, systems biology, pharmacology, genomics, metabolomics, microbiology.
  3. Improving Ageing through a Machine Learning Drug-Drug-Microbe Approach. We will utilize the combinatorial space of drug interactions to improve lifespan. The conceptual novelty in this project results from targeting the host cells in addition to the microbial cells to obtain a full synergistic effect on healthspan and lifespan of the host. Screening will be performed in C. elegans and validation will occur in mouse models.
    Areas: Ageing, Organismal biology, machine learning-AI, pharmacology, microbiology.

4. Applied Methods and model organisms:

Model Organisms: We utilize a combination of tractable genetic models such as the nematode C. elegans, widely used for studying host-microbe interactions, human-cell derived gut organoids and cell cultures, and mouse models (including germ-free) to identify mechanisms driving ageing in an environment-dependent manner.

Applied Methods: We combine high-throughput genomic/chemical screening approaches. These include the screening of thousands of bacterial strain collections and or drug and nutrient compounds. We utilise CRISPr/cas technology and synthetic biology approaches to modify bacteria.
We perform multi-omics experiments (e.g. transcriptomics, proteomics, metabolomics) at the holobiont level. And utilize a systems biology computational approach for data integration.

This holistic approach will provide phenotypic, genomic and biochemical molecular datasets that will enrich our understanding of the fundamental processes underlying host-microbial cross-talk at the systemic, cellular and molecular levels. 

5. Desirable skills and qualifications:

Professional qualifications:

  • Completed Masters degree in life sciences, microbiology, computational or related fields. A background in physiology, metabolism or aging is a plus.

Personal skills:

  • Proficiency in written and spoken English is mandatory.
  • Evidence of great communication and team work skills, curiosity-driven science and excellent problem-solving skills.

Technical skills:

  • Experience in animal tissue handling, organoid or cell culture is desirable.
  • Experience in microbiology or systems/computational biology is desirable.
  • Experience in C. elegans husbandryis desirable.
  • Experience in microbiology or systems biology is desirable.
  • Experience with mass spectrometry (e.g metabolomics) is desirable
  • Proficiency in R studio (and/or other) programming language is desirable.

6. References:

Selected publications from our lab.

  • Klunemann M et al. (2021) Bioaccumulation of therapeutic drugs by human gut bacteria. Nature (accepted)
  • Martinez-Miguel, VE et al, Cabreiro F and Bjedov I, (2021) Increased fidelity of protein synthesis extends lifespan. Cell Metabolism
  • Essmann C et al. Cabreiro F. (2020) Mechanical properties measured by Atomic Force Microscopy define new health biomarkers in ageing C. elegans. Nature Comms.
  • Bana B. and Cabreiro F. (2019). The Microbiome and Aging. Annu Rev Genet.
  • Pryor R et al. Cabreiro F. (2019) Host-Microbe-Drug-Nutrient Screen Identifies Bacterial Effectors of Metformin Therapy. Cell
  • Scott TA et al., Cabreiro F. (2017) Host-Microbe Co-metabolism Dictates Cancer Drug Efficacy in C. elegans. Cell
  • Cabreiro F. et al. (2013) Metformin retards aging in C. elegans by altering microbial folate and methionine metabolism. Cell
  • Cabreiro F. et al. (2011) Absence of effects of Sir2 overexpression on lifespan in C. elegans and Drosophila. Nature.