Cumulative publication list
Predictability in Evolution
Collaborative Research Center 1310
2020
[A4] The protein translation machinery is expressed for maximal efficiency in Escherichia coli
Hu X., Dourado H., Schubert P. & Lercher M. J., Nat Commun 11, 5260, 16. October 2020, https://doi.org/10.1038/s41467-020-18948-x
[B4] Microbiota–host interactions shape ageing dynamics
Popkes M., Valenzano D.R., Phil. Trans. R. Soc. B 375, 20190596, 10. August 2020, https://doi.org/10.1098/rstb.2019.0596
[B2] Eco-evolutionary control of pathogens
Lässig M., Mustonen V., PNAS:201920263 , 31. July 2020, https://doi.org/10.1073/pnas.1920263117
[A1] Highly parallel lab evolution reveals that epistasis can curb the evolution of antibiotic resistance
Lukačišinová M., Fernando B., Bollenbach T., Nat Commun 11, 31051, 19. June 2020, https://doi.org/10.1038/s41467-020-16932-z
[B4] Extreme genomic volatility characterizes the evolution of the immunoglobulin heavy chain locus in cyprinodontiform fishes
Bradshaw W.J., Valenzano D.R., Proc. R. Soc. B.28720200489, 13. May 2020, https://doi.org/10.1098/rspb.2020.0489
[B3] Major antigenic site B of human influenza H3N2 viruses has an evolving local fitness landscape
Wu N. C., Otwinowski J., Thompson A. J., Nycholat C. M. Nourmohammad A and Wilson I. A., Nat Commun 11, 1233, 6. March 2020, https://doi.org/10.1038/s41467-020-15102-5
[A4] An analytical theory of balanced cellular growth
Dourado H., and Lercher M. J., Nat Commun 11, 1226, 6. March 2020, https://doi.org/10.1038/s41467-020-14751-w
[B3] The size of the immune repertoire of bacteria
Bradde S., Nourmohammad A., Goyal S., and Balasubramanian V., PNAS:201903666, 18. February 2020, https://doi.org/10.1073/pnas.1903666117
2019
[A3][A6] Horizontal gene transfer overrides mutation in Escherichia coli colonizing the mammalian gut
Frazão N., Sousa A., Lässig M., and Gordo I., PNAS:201906958, 20. August 2019, https://doi.org/10.1073/pnas.1906958116
[B3] Fierce Selection and Interference in B-Cell Repertoire Response to Chronic HIV-1
Nourmohammad A., Otwinowski J., Łuksza M., Mora T., M. Walczak A., Molecular Biology and Evolution, msz143, 18. June 2019, https://doi.org/10.1093/molbev/msz143
[B2] Survival of the simplest in microbial evolution
Held T., Klemmer D., Lässig M., Nature Communications 10: 2472, 6. June 2019, https://doi.org/10.1038/s41467-019-10413-8
2018
[A4] Each of 3,323 metabolic innovations in the evolution of E. coli arose through the horizontal transfer of a single DNA segment
Pang T. J., Lercher M. J., PNAS, 18. December 2018, https://doi.org/10.1073/pnas.1718997115
[A4] Machine learning applied to enzyme turnover numbers reveals protein structural correlates and improves metabolic models
Heckmann D., Lloyd C. J., Mih N., Ha Y., Zielinski D. C., Haiman Z. B., Desouki A. A., Lercher M. J., Palsson B. O., Nature Communications 9: 5252, 7. December 2018, https://doi.org/10.1038/s41467-018-07652-6
[A4] Alleles of a gene differ in pleiotropy, often mediated through currency metabolite production, in E. coli and yeast metabolic simulations
Alzoubi D., Desouki A. A., Lercher M. J., Scientific Reports 8: 17252, 22. November 2018, https://doi.org/10.1038/s41598-018-35092-1
[A3] Gene expression variability across cells and species shapes innate immunity
Hagai T., Chen X., Miragaia R. J., Rostom R., Gomes T., Kunowska N., Henriksson J., Park J.-E., Proserpio V., Donati G., Bossini-Castillo L., Vieira Braga F. A., Naamati G., Fletcher J., Stephenson E., Vegh P., Trynka G., Kondova I., Dennis M., Haniffa M., Nourmohammad A., Lässig M., Teichmann S. A., Nature 563: 197 - 202, 24. October 2018, https://doi.org/10.1038/s41586-018-0657-2
[B8] Genomic Characterization of TP53–Wild-Type Esophageal Carcinoma1
Quaas A., Heydt C., Gebauer F., Alakus H., Loeser H., Büttner R., Hillmer A., Bruns C., Merkelbach-Bruse S., Zander T., Frommolt P., Transl Oncol. 12: 154-161, 11. October 2018, https://doi.org/10.1016/j.tranon.2018.09.007
[B8] Impact of TP53 mutation status on systemic treatment outcome in ALK-rearranged non-small-cell lung cancer
Kron A., Alidousty C., Scheffler M., Merkelbach-Bruse S., Seidel D., Riedel R., Ihle M. A., Michels S., Nogova L., Fassunke J., Heydt C., Kron F., Ueckeroth F., Serke M., Krüger S., Grohe C., Koschel D., Benedikter J., Kaminsky B., Schaaf B., Braess J., Sebastian M., Kambartel K. O., Thomas R., Zander T., Schultheis A. M., Büttner R., Wolf J., Ann Oncol. 29: 2068-2075, 1. October 2018, https://doi.org/10.1093/annonc/mdy333
[A2] Rare beneficial mutations cannot halt Muller's ratchet in spatial populations
Park S.-C., Klatt P., Krug J., EPL 123: 48001, 3. September 2018, http://stacks.iop.org/0295-5075/123/i=4/a=48001
[A2] The utility of fitness landscapes and big data for predicting evolution
de Visser, J. A. G. M., Santiago F. E., Fragata I., Matuszewski S., Heredity 121: 401–405, 20. August 2018, https://doi.org/10.1038/s41437-018-0128-4
[A2] Ecology dictates evolution? About the importance of genetic and ecological constraints in adaptation
de Vos M. G. J., Schoustra S. E., de Visser J. A. G. M., EPL 122: 58002, 17. July 2018, http://stacks.iop.org/0295-5075/122/i=5/a=58002
[A2] Unraveling the causes of adaptive benefits of synonymous mutations in TEM-1 β-lactamase
Zwart M. P., Schenk M. F., Hwang S., Koopmanschap B., de Lange N., van de Pol L., Nga T. T. T., Szendro I. G., Krug J., de Visser J. A. G. M., Heredity 121: 406–421, 2. July 2018, https://doi.org/10.1038/s41437-018-0104-z
[B8] Genetic instability and recurrent MYC amplification in ALK‐translocated NSCLC: a central role of TP53 mutations
Alidousty C., Baar T., Martelotto L. G., Heydt C., Wagener S., Fassunke J., Duerbaum N., Scheel A. H., Frank S., Holz B., Binot E., Kron A., Merkelbach-Bruse S., Ihle M. A., Wolf J., Büttner R., Schultheis A.M., J Pathol. 246: 67-76, 9. June 2018, https://doi.org/10.1002/path.5110
[B7] Multi-region proteome analysis quantifies spatial heterogeneity of prostate tissue biomarkers
Guo T., Li L., Zhong Q., Rupp N.J., Charmpi K., Wong C.E., Wagner U., Rueschoff J.H., Jochum W., Fankhauser C.D., Saba K., Poyet C., Wild P.J., Aebersold R., Beyer A., Life Science Alliance, 29. May 2018, https://doi.org/10.26508/lsa.201800042
[B5] Method for identification of condition-associated public antigen receptor sequences
Pogorelyy M.V., Minervina A.A., Chudakov D.M., Mamedov I.Z., Lebedev Y.B., Mora T., Walczak A.M., eLife 2018;7:e33050, 13. May 2018, https://doi.org/10.7554/eLife.33050
[B4] The short-lived African turquoise killifish (Nothobranchius furzeri): a new model system for research on ageing.
In Conn's Handbook of Models of Human Aging
Muck J., Kean S., Valenzano D.R.,Academic Press, 2. May 2018, ISBN: 9780128113530
[B4] A Protocol for Laboratory Housing of Turquoise Killifish (Nothobranchius furzeri)
Dodzian J., Kean S., Seidel J., Valenzano D.R., J. Vis. Exp. (134) e57073, 11. April 2018, https://doi.org/10.3791/57073
[A2] Universality Classes of Interaction Structures for NK Fitness Landscapes
Hwang S., Schmiegelt B., Ferretti L., Krug J., J Stat Phys 172: 226, 13. February 2018, https://doi.org/10.1007/s10955-018-1979-z
[B5] High-throughput immune repertoire analysis with IGoR
Marcou Q., Mora T., Walczak A.M., Nature Communications Volume 9:561, 8. February 2018, https://doi.org/10.1038/s41467-018-02832-w
[B7] regNet: an R package for network-based propagation of gene expression alterations
Seifert M., Beyer A., Bioinformatics Volume 34 Issue 2:308–311, 15. January 2018, https://doi.org/10.1093/bioinformatics/btx544
[A2] Local Fitness Landscapes Predict Yeast Evolutionary Dynamics in Directionally Changing Environments
Gorter F. A., Aarts M. G. M, Zwaan B. J., de Visser J. A. G. M., Genetics 208: 307-322, 1. January 2018, https://doi.org/10.1534/genetics.117.300519