EPFL BioE Talks SERIES "Revealing Evolutionary Constraints on Proteins Through Sequence Analysis"
Event details
| Date | 23.11.2020 |
| Hour | 16:30 › 17:00 |
| Speaker | Prof. Anne-Florence Bitbol, Institute of Bioengineering, EPFL, Lausanne (CH) |
| Location | Online |
| Category | Conferences - Seminars |
WEEKLY EPFL BIOE TALKS SERIES
(note that this talk is number two of a double-feature seminar - see details of the first talk here)
Abstract:
Proteins play crucial parts in all cellular processes, and their functions are encoded in their amino-acid sequences. Statistical analysis of alignments of large numbers of protein sequences has revealed “sectors” of collectively coevolving amino acids in several protein families. What is the origin of these sectors? We show that selection acting on any functional property of a protein, represented by an additive trait, can give rise to such a sector. As an illustration of a selected trait, we consider the elastic energy of an important conformational change within an elastic network model, and we show that selection acting on this energy leads to correlations among residues. For this concrete example and more generally, we demonstrate that the main signature of functional sectors lies in the small-eigenvalue modes of the covariance matrix of the selected sequences. However, secondary signatures of these functional sectors also exist in the extensively-studied large-eigenvalue modes. Our simple, general model leads us to propose a principled method to identify functional sectors, along with the magnitudes of mutational effects, from sequence data. We further demonstrate the robustness of these functional sectors to various forms of selection, and the robustness of our approach to the identification of multiple selected traits. A better understanding of protein sectors will make it possible to discern collective protein properties directly from sequences, as well as to design new functional sequences.
Bio:
Anne-Florence Bitbol studied physics at ENS Lyon. Her PhD at Université Paris-Diderot, advised by Prof. Jean-Baptiste Fournier, focused on the statistics and dynamics of complex membranes, using statistical and soft matter physics to understand how lipid bilayers are perturbed by proteins or by local chemical perturbations. She then chose to move even closer to biology, as a postdoc in the Biophysics Theory Group at Princeton University, led by Profs. Ned Wingreen, Bill Bialek and Curt Callan. There, she investigated the self-assembly of multi-protein complexes, and she also worked on evolution in rugged fitness landscapes with David Schwab. Next, she became a CNRS researcher at Laboratoire Jean Perrin, Institut de Biologie Paris-Seine, Sorbonne Université in Paris, and she recently moved to EPFL, where she is a Tenure-Track Assistant Professor in the Institute of Bioengineering and the School of Life Sciences. She is broadly interested in understanding biological phenomena in a quantitative way, through physical concepts as well as mathematical and computational tools. Her current research focuses on two main axes: the sequence-function mapping in proteins, and the evolution of microbes on complex fitness landscapes, with application to antimicrobial resistance evolution.
Zoom link (with registration) for attending remotely: https://go.epfl.ch/EPFLBioETalks
IMPORTANT NOTICE: due to restrictions resulting from the ongoing Covid-19 situation, this seminar can be followed via Zoom web-streaming only, following prior one-time registration through the link above.
(note that this talk is number two of a double-feature seminar - see details of the first talk here)
Abstract:
Proteins play crucial parts in all cellular processes, and their functions are encoded in their amino-acid sequences. Statistical analysis of alignments of large numbers of protein sequences has revealed “sectors” of collectively coevolving amino acids in several protein families. What is the origin of these sectors? We show that selection acting on any functional property of a protein, represented by an additive trait, can give rise to such a sector. As an illustration of a selected trait, we consider the elastic energy of an important conformational change within an elastic network model, and we show that selection acting on this energy leads to correlations among residues. For this concrete example and more generally, we demonstrate that the main signature of functional sectors lies in the small-eigenvalue modes of the covariance matrix of the selected sequences. However, secondary signatures of these functional sectors also exist in the extensively-studied large-eigenvalue modes. Our simple, general model leads us to propose a principled method to identify functional sectors, along with the magnitudes of mutational effects, from sequence data. We further demonstrate the robustness of these functional sectors to various forms of selection, and the robustness of our approach to the identification of multiple selected traits. A better understanding of protein sectors will make it possible to discern collective protein properties directly from sequences, as well as to design new functional sequences.
Bio:
Anne-Florence Bitbol studied physics at ENS Lyon. Her PhD at Université Paris-Diderot, advised by Prof. Jean-Baptiste Fournier, focused on the statistics and dynamics of complex membranes, using statistical and soft matter physics to understand how lipid bilayers are perturbed by proteins or by local chemical perturbations. She then chose to move even closer to biology, as a postdoc in the Biophysics Theory Group at Princeton University, led by Profs. Ned Wingreen, Bill Bialek and Curt Callan. There, she investigated the self-assembly of multi-protein complexes, and she also worked on evolution in rugged fitness landscapes with David Schwab. Next, she became a CNRS researcher at Laboratoire Jean Perrin, Institut de Biologie Paris-Seine, Sorbonne Université in Paris, and she recently moved to EPFL, where she is a Tenure-Track Assistant Professor in the Institute of Bioengineering and the School of Life Sciences. She is broadly interested in understanding biological phenomena in a quantitative way, through physical concepts as well as mathematical and computational tools. Her current research focuses on two main axes: the sequence-function mapping in proteins, and the evolution of microbes on complex fitness landscapes, with application to antimicrobial resistance evolution.
Zoom link (with registration) for attending remotely: https://go.epfl.ch/EPFLBioETalks
IMPORTANT NOTICE: due to restrictions resulting from the ongoing Covid-19 situation, this seminar can be followed via Zoom web-streaming only, following prior one-time registration through the link above.
Practical information
- Informed public
- Registration required
Organizer
Contact
- Institute of Bioengineering (IBI), Dietrich REINHARD