SFB 1310: Predictability in Evolution

进化生物学传统上关注的是在很长一段时间内重建过去的过程和祖先关系。但我们能预测未来进化过程的路径和结果吗，至少在短期内？这是《儿童权利公约》1310的核心问题。我们在快速进化的系统中解决这个问题，包括实验室中的微生物种群、病毒和免疫系统以及癌细胞种群。这些系统中的预测分析包括耐药性和抗原性的进化，免疫系统中抗体的进化，以及癌细胞在其有机体环境中的进化。为了预测进化，我们必须将遗传、表型和环境变化与对器官功能和适应性的因果和可重复的影响联系起来。为了描绘这种影响，我们在实验和理论上分析了大规模并行和时间分辨的进化过程。对可预测性的力量和局限性进行量化，为长期存在的进化中的偶然性和必然性问题提供了新的线索。与此同时，我们提出了一个新的问题：我们能否获得控制进化的预测？回答这个问题是我们工作的生物医学应用的关键。我们的研究计划建立在对基因组序列、分子相互作用、细胞新陈代谢和生长的高通量分析的基础上。我们正在将这些工具推进到一种连贯的进化技术中。CRC联合了分子遗传学、生物物理学、医学和理论建模方面的强大和跨学科的能力范围。我们共同努力提高进化的可预测性。

Evolutionary biology has traditionally been concerned with reconstructing past processes and ancestral relationships over long time scales. But can we predict pathways and outcomes of future evolutionary processes, at least over short periods? This is the central question of CRC 1310. We address this question in fast-evolving systems, including microbial populations in the laboratory, viruses and immune repertoires, and cancer cell populations. Predictive analysis in these systems includes the evolution of drug resistance and antigenicity, the evolution of antibodies in immune systems, and the evolution of cancer cells in their organismic environment.To predict evolution, we must link genetic, phenotypic, and environmental changes to causal and reproducible effects on organismic functions and fitness. To map such effects, we analyze massively parallel and time-resolved evolutionary processes in experiment and theory. Quantifying power and limitations of predictability sheds new light on long-standing questions of chance and necessity in evolution. At the same time, we ask a new question: can we harvest predictions for control of evolution? Answering this question is key to the bio-medical applications of our work. These include the design of antibiotics, of vaccines for influenza and SARS-CoV-2, and of therapies for cancer.Our research programme builds on high-throughput analysis of genomic sequences, molecular interactions, cell metabolism and growth. We are advancing these tools to a coherent technology for evolution. The CRC unites a strong and interdisciplinary spectrum of competence in molecular genetics, biophysics, medicine, and theoretical modelling. Together, we endeavor to increase the predictability of evolution.