Alma in Science

At her office in Department of Computational Biology – Unil 2021

“Alma pursued science with fearless passion, creativity, vision and dedication. Alma had an exceptionally sharp and creative mind, and an insatiable curiosity. She kept exploring new directions, working on everything from gene-regulatory circuits to microbial communities, to developmental processes. She was the embodiment of a true interdisciplinary scientist, combining state-of-the-art experiments with advanced computational approaches. The unifying theme of her work was to understand how interactions between individuals (be it fish, microorganisms or pancreatic cells) give rise to complex behaviour at higher levels of organization. She strived to derive simple, quantitative rules to explain the complexity that we see around us. Alma believed that science is a team effort: she was generous with her time, and always happy to discuss ideas and share resources. No matter where she went, she quickly connected with people, built formal and informal networks, and fostered collaborations and friendships.” (from: Obituary).

Alma Dal Co graduated in physics in 2011 from the University of Padua under the guidance of Professor Flavio Seno. Her thesis was dedicated to studying the spatial arrangement of proteins. In 2014, she obtained a master of science in Complexity Physics in Turin, supervised by Professors Michele Caselle and Matteo Osella. Her thesis focused on the expression of genes.

She completed her doctorate at EAWAG-ETH in Zurich in 2019, under the supervision of Professor Martin Ackermann. Her doctoral thesis centered on the spatial organization of bacterial communities. Subsequently, Alma conducted her postdoctoral research at Harvard under the guidance of Professor Michael Brenner, where she studied interactions within bacterial communities.

In 2021, Alma Dal Co secured a position as a professor at the Department of Computational Biology in Lausanne, directed by Professor Nicolas Salamin. She has been associated with the International Society for Microbial Ecology (ISME), served on the Board of the Systems Biology Section of Life Sciences Switzerland (LS2), and she was member of the Swiss National Center of Competence in Research (NCCR) Microbiomes, directed by Professor Jan Roelof van der Meer

Dalcolab

The DalcoLab proved to be a brief yet profoundly impactful journey for each of its members. At the heart of Alma’s vision for the team there was the active pursuit of dialogue and brainstorming, leading to swift collaborations with brilliant minds to tackle substantial scientific inquiries. As a mentor, Alma was both inspiring and nurturing.

The two main directions of the scientific investigations pursued in the DalcoLab, microbial ecology and morphogenesis, were two facets of the same fascination of Alma for cell collectives and their complex organization in space. In a growing assembly of cells, be them bacteria in a colony or mammalian cells forming a tissue, the interplay between spatial and functional features becomes of paramount importance in determining the fate of the collective. Discovering some of the possible rules that govern these systems, both with experimental and computational approaches, was the focus of the research at the DalcoLab.

The main lab interest was in microbial ecology, and more specifically in how, in spatially structured microbial communities, local interactions shape the properties of the community. This line of research stemmed from Alma’s own PhD work in this field. Building on her discovery that nutrient exchange occurs at the micrometer scale, part of the lab’s research was aimed at understanding how local interactions can promote the microbial diversity observed in nature. Using computational simulations and mathematical modeling, the DalcoLab was investigating how cooperation and competition shape spatial organization of communities, and how, as a result, community properties emerge across space and time. Alma previously demonstrated that microscale nutrient gradients can affect bacterial growth in a structured environment, leading to a better tolerance to antibiotics. The lab was investigating how nutrients and toxins gradients generated by bacterial activity can in turn trigger heterogeneity in the production of virulence factors. Overall, the DalcoLab’s ongoing efforts were aimed at enhancing our understanding of the dynamic relationships between individual behaviors and collective dynamics both within the clonal populations and multi-species communities that govern microbial life on our planet.

In a distinct data-centric project, the goal was to adapt concepts and tools initially designed for analyzing spatial correlations within microbial communities for application in multicellular systems. Through collaboration with medical experts, Alma embarked on an exciting endeavor: constructing a biophysical model of insulin-secreting organoids. This initiative aimed to optimize tissue architectures and contribute significantly to the pursuit of groundbreaking cures for type 1 diabetes.

  • Visit to CERN with Padua University, 2011

From the website of Dal Co lab (2022)

Welcome to the Dal Co lab at the University of Lausanne, Switzerland. We are part of the Department of Computational Biology, and of the Swiss National Centre of Competence in Research for Microbiomes. We are hiring a Postdoc. Read about how to Join us!

We study how functionality arises in biological systems. Our group is interested in a variety of systems, from microbial communities to organs. We investigate principles that drive multicellular organization and function. We do single cell experiments with microbial communities and we collaborate with groups working on other multicellular systems. We build computational models to uncover how interactions between single cells drive collective behavior and function.

Our group is interested in microbial ecology. A first central question in our research is: Can we predict the dynamics of microbial systems if we know how the individual cells interact? We address this question with single-cell experiments and modeling. We measure how single cells interact inside microbial communities, often using microscopy and microfluidics. We model these communities as systems composed of parts – the cells – that interact in space. With these models, we elucidate how properties of microbial communities (e.g. collective metabolism, response to environmental fluctuations and stresses) arise from the interactions that we observe between the single cells.

Our group is interested in collective behaviour. A second central question in our research is: How are cells programmed to produce specific multicellular behaviour? This question applies to both multicellular microbial systems and multicellular organisms. Multicellular microbial systems and multicellular organisms may share general organisational principles. We use modeling to infer which physical and biological interactions between cells are required to achieve target collective behaviours. Our group combines machine learning approaches with single-cell experimental data to understand and engineer collective behaviour. We are excited to collaborate with experimental groups working on different systems.

We are interdisciplinary. We love interdisciplinary work. If you are a microbe—or a person—it’s often not good to be surrounded by individuals just like you. This is a nice lesson from our work on interactions between bacterial cells (read what’s behind our work). We believe that connecting disciplines is crucial for understanding any system of a certain complexity. For example, the properties of a society -studied by social scientists- arise from the properties of its components, the individuals -studied by psychologists; the properties of an atom -studied by chemists- arise from the properties of its elementary components -studied by particle physicists. Connecting fields generally unlocks tremendous scientific potential. We connect disciplines to elucidate how complex biological systems function.

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