Biography
Dr. Yifan (Yi-Fan) Yang, born in 1984 in Wuhan, Hubei. He completed his undergraduate studies at Yuanpei College of Peking University, where he studied both mathematics and life sciences, earning a bachelor's degree in life sciences in 2008. In 2011 and 2016, he obtained his master's and doctoral degrees from the University of Paris (Paris V) in France. In 2019, he began his postdoctoral research at the Weizmann Institute of Science in Israel under the mentorship of Uri Alon. He is expected to join Westlake University in January 2025 as a principal investigator, with research interests focused on nonlinear dynamics in biological aging, statistical physics, and quantitative physiology.
Research
This research group will integrate wet lab experiments, theoretical modelling, and computational approaches to study biological aging from a systems perspective. The research is divided into three parts: first principles of biological aging, the system architecture of cellular stress responses and cell cycle regulation, and mammalian aging and tissue homeostasis.
(1) First Principles of Biological Aging
In current research on biological aging, traditional bottom-up approaches, such as molecular genetics and molecular cell biology, face challenges due to complexity, randomness, and emergent properties. While many biological processes associated with aging have been identified as hallmarks of aging, it remains unclear how their interactions lead to individual aging and determine lifespan.
All complex systems, whether living or non-living, including engineered systems like cars, airplanes, and even materials, experience functional decline over time, becoming more susceptible to damage and eventual failure. The fundamental principle is that the "components" of these systems have interdependent relationships, where small unobserved component failures make failure cascades more likely. Thus, quantitative studies on how these systems fail can reflect the internal interdependencies and organizational structure of these systems. This approach provides a novel perspective for understanding the robustness of living systems and may reveal the fundamental cause of aging for specific biological systems.
Dr. Yifan Yang's existing work demonstrates that:
1. The aging processes of organisms, such as E. coli and humans, and engineered systems, such as cars and airplanes, can be described by two different quantitative laws, highlighting qualitative differences between biological and engineered systems.
2. Aging processes across various model organisms, from E. coli to mice, can be described by a universal low-dimensional stochastic differential equation.
These findings raise deeper questions: Why do entirely different organisms exhibit the same dynamic aging processes? What are the fundamental differences in system architecture between living and engineered systems? Our research group will address these questions from a first-principal basis.
(2) Quantitative Laws in Stress Responses and Cell Cycle Regulation
The theoretical research above requires empirical validation in simpler biological systems. Microbial systems, such as fission yeast and E. coli, with their short reproduction cycles and rapid evolutionary capabilities, provide experimental platforms for testing these theories.
Fission yeast and some bacterial species have made significant contributions over the past few decades to understanding the cellular principles of aging. Dr. Yifan Yang's work successfully demonstrated that aging dynamics observed in mammals also apply to E. coli, a unicellular prokaryote.
Like how mammals have multiple tissues, unicellular organisms have multiple organelles. Different organelles accumulate damage at varying rates due to their distinct functional activities, macromolecular composition and structure. However, at the system level, these living organisms exhibit relatively simple dynamics: the damage dynamics in E. coli can be described by a one-dimensional stochastic differential equation, indicating that interactions among different types of damage lead to the system being describable by a single aggregate variable (mean-field approximation).
This research group will use fission yeast and other microorganisms as a model system to further investigate the dynamic processes of damage in different organelles in vivo and the structural characteristics of their interaction networks. This direction will primarily employ time-lapse microscopy and automated experimental platforms such as liquid-handling robots to explore quantitative laws in cellular damage, stress responses, and cell cycle regulation.
(3) Mammalian Aging and Tissue Homeostasis
Additionally, the group plans to use existing theoretical tools to develop the next generation of biomarkers and clocks for measuring physiological and biological age. One major goal in the field of aging biology is to develop biomarkers that measure physiological states rather than absolute chronological age. These biomarkers have various applications, such as screening for anti-aging drugs and designing personalized precision medicine and healthcare strategies.
Using machine learning methods and multi-omics data, such as epigenomics, researchers have already developed various aging clocks. Clocks calibrated to chronological age are referred to as "chronological age clocks," while those calibrated to physiological damage and biological age are called "biological age clocks." These clocks are often constructed from thousands of epigenetic sites selected from tens of thousands of candidates using algorithms like Lasso regression. However, the physiological processes involving these sites and their mechanistic connections to aging remain unclear.
The damage dynamics model Dr. Yifan Yang help develop can be used to develop the next generation of physiological clocks and establish mechanistic links between clocks and physiological processes. The group will develop custom machine learning methods and utilize existing biobanks and human cohort studies to create mechanistically meaningful physiological clocks that predict organ physiological states and tissue damage. This research goal aims to uncover the biological mechanisms of mammalian tissue aging and tissue homeostasis.
Representative Publications (*Corresponding authors)
1.Yang Y, Mayo A, Levy T, Jarosz D, Alon U*.Compression of sickspan by interventions that steepen the survival curve. BioRxiv (2023 in revision forNat. Commun) doi:10.1101/2023.10.04.560871.
2.Yang Y*, Karin O, Mayo A, Song X, Chen P, Santos A, Lindner AB, Alon U*. Damage dynamics and the role of chance in the timing ofE. colicell death.Nat. Commun.14.1 (2023): 2209.
3.Yang Y*, Santos AL, Xu L, Lotton C, Taddei F, Lindner AB*. Temporal scaling of aging as an adaptive strategy of Escherichia coli.Science Advances(2019) May 29;5:eaaw2069S.
4.Yang Y, Song X, Lindner AB*.Time-lapse microscopy and image analysis of Escherichia coli cells in mother machines.Methods in Microbiology, (2016) Dec 1;43:49-68.
5.Izard J, Gomez Balderas CD, Ropers D, Lacour S, Song X, Yang Y, Lindner AB, Geiselmann J, de Jong H. A synthetic growth switch based on controlled expression of RNA polymerase.Mol. Syst. Biol.(2015) Nov 23;11(11):840.
Contact Us
We welcome young scholars interested in studying the principles of biological aging to join us. Applicants should send a cover letter, C.V. (mandatory), and a portfolio (optional, including publications, code, scientific illustrations, etc.) to the following email: yangyifan@westlake.edu.cn.
