Der diesjährige Ulrich-Hadding-Forschungspreis wurde am 24. September 2019 an Dr. Tin Yau Pang (research group for Computational Cell Biology,Prof. Lercher) vergeben.
Education and professional experience
- Dr. Tin Yau Pang obtained his PhD in Physics at the State University of New York at Stony Brook and the Brookhaven National Laboratory (BNL), from 2007 to 2014. He worked in the Sergei Maslov Lab in BNL, studying (1) scaling laws of transcription factors in bacterial genomes, and (2) the neutral evolution of single nucleotide polymorphisms (SNPs) in bacterial genomes.
- He did his bachelor and master in Physics at the Hong Kong University of Science and Technology. For his Master project, he worked in the lab of Kowk Yip Szeto on the Ising model of interacting spins, studying how the initial spin configuration affects the equilibrium spin configuration.
- Since 2014, Dr. Pang has worked on diverse projects in the lab of Prof. Martin Lercher at HHU as a postdoctoral researcher.
The research focus of Dr. Pang lies on systems biology. In his recent work, he studied phenotypic innovations in strains of E. coli that arose through horizontal gene transfer (HGT). Comparison of genotype and metabolic phenotype between ancestral and descendant strains along the same lineage revealed that all new phenotypes arose through a single HGT event. This indicates that each successful HGT event must be adaptive; otherwise, the newly acquired genes would immediately be lost again. Currently, he works on mathematical models for diverse topics, including the optimal density of biochemical molecules in cells and the evolution of the menopause.
Previously, in one of his PhD projects, Dr. Pang has worked on a simple model that describes the growth of a bacterial genome. This model points out that, as the number of all genes in a bacterial genome increases, the number of additionally required genes per new phenotype decreases, because the bacterium can reuse more and more of the genes that already exist in the genome. The transcription factor genes per new phenotype, however, stay constant. Therefore, the number of transcription factors scales faster-than-linear with the number of all genes in bacterial genomes. This non-linear growth model applies not only to bacterial genomes, but also to man-made complex systems: the package repository of the Linux operating system shows scaling laws that can be explained by the same model [3-5].
In another PhD project, which is still on-going, Dr. Pang studied the distribution of SNPs (single nucleotide differences) between different E. coli strains. If we divide the pairwise alignment of two genomes into segments with equal length and count the SNPs on each segment, we will obtain a distribution of local SNP density. The shape of this SNP distribution is that of a Poisson distribution, with an added exponential tail. Dr Pang constructed a model to explain how this SNP distribution evolves through mutations and recombination events as the two genomes diverge from each other. Dr. Pang further applied this model for the reconstruction of the strain family tree; compared with other family tree reconstruction algorithms, it has the advantage of inherently accounting for the frequent recombination and HGT between bacterial strains, which distorts tree reconstructions [6-8].
1. Pang, T. Y. Y. & Lercher, M. J. Each of 3,323 metabolic innovations in the evolution of E. coli arose through the horizontal transfer of a single DNA segment. Proceedings of the National Academy of Sciences of the United States of America, 2019 , 116 , 187-192
2. Pang, T. Y. & Lercher, M. J. Supra-operonic clusters of functionally related genes (SOCs) are a source of horizontal gene co-transfers. Scientific reports, 2017 , 7
3. Maslov, S.; Krishna, S.; Pang, T. Y. & Sneppen, K. Toolbox model of evolution of prokaryotic metabolic networks and their regulation, Proceedings of the National Academy of Sciences, 2009 , 106 , 9743-9748
4. Pang, T. Y. & Maslov, S. A Toolbox Model of Evolution of Metabolic Pathways on Networks of Arbitrary Topology, PLoS Comput Biol, 2011 , 7 , e1001137+
5. Pang, T. Y. & Maslov, S. Universal distribution of component frequencies in biological and technological systems, Proceedings of the National Academy of Sciences, 2013 , 110 , 6235-6239
6. Dixit, P. D.; Pang, T. Y.; Studier, F. W. & Maslov, S. Recombinant transfer in the basic genome of Escherichia coli, Proceedings of the National Academy of Sciences, 2015 , 112 , 9070-9075
7. Dixit, P. D.; Pang, T. Y. & Maslov, S. Recombination-Driven Genome Evolution and Stability of Bacterial Species Genetics, Genetics, 2017 , 207 , 281-295
8. Pang, T. Y. A coarse-graining, ultrametric approach to resolve the phylogeny of prokaryotic strains with frequent recombination, bioRxiv, 2016 , 094599+
The excellence of Dr. Pang’s research – both during his PhD and especially at the HHU – is evidenced by the fact that many of his findings were published in the top-quality journal PNAS (2009; 2013, 2015; 2019).
This prize is endowed with 5.000,- €.