The host and their intestinal microbes

The microbiomes of our various tissues play a pivotal role in preserving our health and bolstering our resilience, yet they can also present risks. Our capacity to manipulate the microbiome and engineer it to perform advantages functions is hindered by our restricted comprehension of what influences the microbiome’s composition and what instigates its alterations.

Small animals such as the roundworm C. elegans serve as exceptional models for studying the dynamics of host-microbiome interactions. To measure these dynamics with high spatiotemporal precision, our laboratory has devised a high-resolution automated imaging platform that combines state-of-the-art microscopy, multi-modal deep learning, and multiplexed microfluidics.

Employing these tools, we subject animals to a dynamic microbial environment and to biotic and abiotic stressors, and monitor in real time how the microbiome evolves, adapts, and reacts to these environmental shifts and the advantages they confer to their hosts.

We transform images into data using deep learning tools we develop in-house and convert data into knowledge by formulating a mathematical model with predictive power, paving the way in vivo microbiome engineering capabilities.

The Gut and the Brain

Animal adaptation to environmental changes is a multifaceted dynamical phenomenon that occurs everywhere in our body. The capacity of an organism to interpret this data, adapt, and institute an appropriate response depend on their ability to integrate and coordinate information from the brain and the body.

The objective of our lab is to understand the pathways and mechanisms that organisms utilize for this purpose, with the intention to modify them, augment them, or allocate them new functions. To accomplish this, we develop novel quantitative experimental assays of diverse biological functions, including gene expression, intercellular signaling, and behavior. These are integrated with theoretical mathematical modeling and interactive machine learning techniques.
We are particularly interested in the gut-brain axis, and study ways in which information collected and processed by the nervous system affects gut functions, while information collected and processed in the gut lead to changes in behavior, memory, and learning

Using CRISPR and Deep Learning to find all the ways of long life

Can orchestrated perturbations of the activity of genes in our body change our aging trajectory to promote healthy and long life?

We are developing new generation of genetic tools and a state-of-the-art machine learning approach to guide us through the rugged landscape of aging and help us find trajectories that are long and healthful.

From independent biological drivers to complex phenotypes, synthetic biology, and drug design

What a biological system is doing is the results of many biological processes that act together. Finding ways to decompose complex biological systems into the processes that drive them can allow us to design synthetic systems and pharmaceutical interventions that are highly controllable, very precise, and have minimal side effects.

We are developing machine-learning methods to address this question across scales in biology, from a protein kinase to complex phenotypes and multi-drug interactions.