Csaba Pal (Hungarian: Pál [ˈpaːl] Csaba [ˈt͡ʃɒbɒ]; born March 27, 1975)[6][7] is a Hungarian biologist at the Biological Research Centre (BRC)[8] in Szeged Hungary. His laboratory is part of the Synthetic and Systems Biology Unit at BRC.[9][10] His research is at the interface of evolution, antibiotic resistance and genome engineering[11][5] and has published over 80 scientific publications in these areas.[12][13]

Csaba Pal
Pal in 2009
Born (1975-03-27) March 27, 1975 (age 49)
Budapest, Hungary
EducationEötvös Loránd Tudományegyetem (PhD)
Alma materHungarian Academy of Sciences (D.Sc.)
OccupationBiologist
EmployerBiological Research Centre
Awards
Websitehttp://group.szbk.u-szeged.hu/sysbiol/pal-csaba-lab-index.html

Education

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Csaba Pal completed his master's in biology at Eötvös Loránd University, Budapest, in 1998.[7][14] Four years later he was awarded a Doctor of Philosophy degree from the Eötvös Loránd University, Budapest in 2002.[7][14] In 2018 he received a Doctor of Science degree from the Hungarian Academy of Sciences.[7] Csaba Pal spent several years abroad with scholarships. He had the opportunity to research in Bath,[15] Oxford, Heidelberg and Italy.[7][14] Prior to his return to Hungary in 2008, he worked as a visiting scientist at the University of Trento.[7][14] In 2023 Csaba Pál become a Corresponding member of the Hungarian Academy of Sciences.

Career and research

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Csaba Pal works on fundamental and applied problems in the evolution of genome networks and antibiotic resistance.[11] To achieve these goals, he develops methods in systems biology, computational metabolic modelling and genome engineering.

Genome evolution

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In 2001, Csaba Pal and colleagues demonstrated that highly expressed genes in yeast evolve slowly.[16] Later, they argued that evolutionary rate of a protein is predominantly influenced by its expression level rather than functional importance. This research has contributed to a paradigmatic shift in the field of protein evolution.[17][18] Balazs Papp, Csaba Pal, and Laurence Hurst studied molecular mechanisms underlying dosage sensitivity.[19] They specifically tested what is now known as the dosage balance hypothesis.[20] The hypothesis offers a synthesis on seemingly unrelated problems such as the evolution of dominance, gene duplicability and co-evolution of protein complexsubunits. In 2007, Pal and colleagues demonstrated that antagonistic co-evolution with parasites has a large impact on the evolution of bacterial mutation rate.[21] This paper showed how biotic interactions shape mutation rate evolution.

More recently, the Pal lab explored the consequences of compensatory adaptation on gene content evolution.[22] It is well known that while core cellular processes are generally conserved during evolution, the underlying genes differ somewhat between related species. They demonstrated that gene loss initiates adaptive genomic changes that rapidly restores fitness, but this process has substantial pleiotropic effects on cellular physiology and evolvability upon environmental change.[22]

Network evolution

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The Pal lab has also contributed to the nascent field of evolutionary systems biology.[23] Their research focused on understanding the extent to which evolution is predictable at the molecular level. Using genome-scale metabolic network modelling combined with experimental tools they studied key issues in evolution, such as mutational robustness,[24] horizontal gene transfer,[25] genome reduction,[26] epistasis,[27][28] promiscuous enzyme reactions,[29] and complex adaptations.[30]

Antibiotic resistance

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Csaba Pal's laboratory currently studies the problem of antibiotic resistance. By combining laboratory evolution, genome sequencing, and functional analysis, they charted the map of evolutionary trade-offs between antibiotics. They found that multidrug resistance mutations in bacteria simultaneously enhance sensitivity to many other unrelated drugs (collateral sensitivity), and explored the underlying molecular mechanisms.[31]

Genome engineering

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Finally, the Pal lab is an advocate of the emerging field of evolutionary genome engineering.[32][33] Genome engineering enables the modification of specific genomic locations in a directed and combinatorial manner, and allow studying central evolutionary issues in which natural genetic variation is limited or biased. However, current tools have been optimized for a few laboratory model strains, lead to the accumulation of numerous undesired, off-target modifications, and demand extensive modification of the host genome prior to large-scale editing. The Pal laboratory presented a simple, all-in-one solution.[34][35] The method is unique as it allows systematic comparison of mutational effects and epistasis across a wide range of bacterial species.

Awards and honours

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Csaba Pal received several domestic and international awards, including the Ignaz Lieben Award (2009),[36][circular reference][37] Szent-Györgyi Talents Award (2014),[1] and the Bolyai Prize (2015).[38][39][40][41] In 2016, Csaba Pal became member of Academia Europaea.[2] In 2017 he was selected as EMBO (European Molecular Biology Organization) member.[3][4] and in 2018, became a member of the FEMS. (Federation of European Microbiological Societies)[5] In 2021 Csaba received and Academic Award[42] and in 2023 he was elected as Corresponding member of the Hungarian Academy of Sciences[43][44]

References

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  1. ^ a b "Szent-Györgyi Talents Award". www.nobel-szeged.hu. Archived from the original on 29 January 2020. Retrieved 29 January 2020.
  2. ^ a b "Academy of Europe: P%C 3%A 1 l Csaba". www.ae-info.org. Retrieved 28 January 2020.
  3. ^ a b Jukic, Igor. "EMBO welcomes 65 new members". EMBO. Archived from the original on 19 June 2017. Retrieved 16 June 2017.
  4. ^ a b "Find people in the EMBO Communities". people.embo.org. Retrieved 28 January 2020.
  5. ^ a b c "FEMS Expert: Dr Csaba Pal". FEMS. Retrieved 29 January 2020.
  6. ^ "BRC Csaba PÁL D.Sc". www.brc.hu. Retrieved 29 January 2020.[permanent dead link]
  7. ^ a b c d e f "BRC Csaba PÁL CV" (PDF). Archived from the original (PDF) on 29 January 2020. Retrieved 29 January 2020.
  8. ^ "BRC". www.brc.hu. Retrieved 28 January 2020.
  9. ^ "BRC Synthetic and Systems Biology Unit". www.brc.hu. Archived from the original on 28 January 2020. Retrieved 29 January 2020.
  10. ^ "Csaba Pál Laboratory". group.szbk.u-szeged.hu. Retrieved 28 January 2020.
  11. ^ a b "New members greeted in Heidelberg". EMBO. 19 December 2018. Retrieved 19 December 2018.
  12. ^ "Magyar Tudományos Művek Tára". m2.mtmt.hu. Retrieved 31 January 2020.
  13. ^ "Csaba Pal - Google Scholar Citations". scholar.google.hu. Retrieved 31 January 2020.
  14. ^ a b c d "Academy of Europe: CV". www.ae-info.org. Retrieved 29 January 2020.
  15. ^ "Students and post-docs past and present". people.bath.ac.uk. Retrieved 28 January 2020.
  16. ^ Hurst, Laurence D.; Papp, Balázs; Pál, Csaba (June 2001). "Highly Expressed Genes in Yeast Evolve Slowly". Genetics. 158 (2): 927–931. doi:10.1093/genetics/158.2.927. PMC 1461684. PMID 11430355.
  17. ^ Zhang, Jianzhi; Yang, Jian-Rong (2015). "Determinants of the rate of protein sequence evolution". Nature Reviews Genetics. 16 (7): 409–420. doi:10.1038/nrg3950. PMC 4523088. PMID 26055156.
  18. ^ Koonin, E. V. (2011). "Are there laws of genome evolution?". PLOS Computational Biology. 7 (8): e1002173. arXiv:1108.3589. Bibcode:2011PLSCB...7E2173K. doi:10.1371/journal.pcbi.1002173. PMC 3161903. PMID 21901087.
  19. ^ Papp, Balázs; Pál, Csaba; Hurst, Laurence D. (July 2003). "Dosage sensitivity and the evolution of gene families in yeast". Nature. 424 (6945): 194–197. Bibcode:2003Natur.424..194P. doi:10.1038/nature01771. ISSN 1476-4687. PMID 12853957. S2CID 4382441. Retrieved 10 July 2003.
  20. ^ Birchler, J. A.; Veitia, R. A. (20 August 2012). "Gene balance hypothesis: Connecting issues of dosage sensitivity across biological disciplines". Proceedings of the National Academy of Sciences. 109 (37): 14746–14753. doi:10.1073/pnas.1207726109. ISSN 0027-8424. PMC 3443177. PMID 22908297.
  21. ^ Pal, Csaba; Maciá, María D.; Oliver, Antonio; Schachar, Ira; Buckling, Angus (December 2007). "Coevolution with viruses drives the evolution of bacterial mutation rates". Nature. 450 (7172): 1079–1081. Bibcode:2007Natur.450.1079P. doi:10.1038/nature06350. ISSN 1476-4687. PMID 18059461. S2CID 4373536. Retrieved 2 December 2007.
  22. ^ a b Szamecz, Béla; Boross, Gábor; Kalapis, Dorottya; Kovács, Károly; Fekete, Gergely; Farkas, Zoltán; Lázár, Viktória; Hrtyan, Mónika; Kemmeren, Patrick; Groot Koerkamp, Marian J. A.; Rutkai, Edit; Holstege, Frank C. P.; Papp, Balázs; Pál, Csaba (2014). "The Genomic Landscape of Compensatory Evolution". PLOS Biology. 12 (8): e1001935. doi:10.1371/journal.pbio.1001935. PMC 4144845. PMID 25157590.
  23. ^ Papp, Balázs; Notebaart, Richard A.; Pál, Csaba (September 2011). "Systems-biology approaches for predicting genomic evolution". Nature Reviews Genetics. 12 (9): 591–602. doi:10.1038/nrg3033. ISSN 1471-0064. PMID 21808261. S2CID 13965868. Retrieved 2 August 2011.
  24. ^ Papp, Balázs; Pál, Csaba; Hurst, Laurence D. (June 2004). "Metabolic network analysis of the causes and evolution of enzyme dispensability in yeast". Nature. 429 (6992): 661–664. Bibcode:2004Natur.429..661P. doi:10.1038/nature02636. ISSN 1476-4687. PMID 15190353. S2CID 492849. Retrieved 10 June 2004.
  25. ^ Pál, Csaba; Papp, Balázs; Lercher, Martin J. (December 2005). "Adaptive evolution of bacterial metabolic networks by horizontal gene transfer". Nature Genetics. 37 (12): 1372–1375. doi:10.1038/ng1686. ISSN 1546-1718. PMID 16311593. S2CID 14611750. Retrieved 20 November 2005.
  26. ^ Pál, Csaba; Papp, Balázs; Lercher, Martin J.; Csermely, Péter; Oliver, Stephen G.; Hurst, Laurence D. (March 2006). "Chance and necessity in the evolution of minimal metabolic networks". Nature. 440 (7084): 667–670. Bibcode:2006Natur.440..667P. doi:10.1038/nature04568. ISSN 1476-4687. PMID 16572170. S2CID 4424895. Retrieved 30 March 2006.
  27. ^ Harrison, Richard; Papp, Balázs; Pál, Csaba; Oliver, Stephen G.; Delneri, Daniela (13 February 2007). "Plasticity of genetic interactions in metabolic networks of yeast". Proceedings of the National Academy of Sciences. 104 (7): 2307–2312. Bibcode:2007PNAS..104.2307H. doi:10.1073/pnas.0607153104. ISSN 0027-8424. PMC 1892960. PMID 17284612.
  28. ^ Szappanos, Balázs; Kovács, Károly; Szamecz, Béla; Honti, Frantisek; Costanzo, Michael; Baryshnikova, Anastasia; Gelius-Dietrich, Gabriel; Lercher, Martin J.; Jelasity, Márk; Myers, Chad L.; Andrews, Brenda J.; Boone, Charles; Oliver, Stephen G.; Pál, Csaba; Papp, Balázs (July 2011). "An integrated approach to characterize genetic interaction networks in yeast metabolism". Nature Genetics. 43 (7): 656–662. doi:10.1038/ng.846. ISSN 1546-1718. PMC 3125439. PMID 21623372.
  29. ^ Notebaart, Richard A.; Szappanos, Balázs; Kintses, Bálint; Pál, Ferenc; Györkei, Ádám; Bogos, Balázs; Lázár, Viktória; Spohn, Réka; Csörgő, Bálint; Wagner, Allon; Ruppin, Eytan; Pál, Csaba; Papp, Balázs (12 August 2014). "Network-level architecture and the evolutionary potential of underground metabolism". Proceedings of the National Academy of Sciences. 111 (32): 11762–11767. Bibcode:2014PNAS..11111762N. doi:10.1073/pnas.1406102111. ISSN 0027-8424. PMC 4136603. PMID 25071190.
  30. ^ Szappanos, Balázs; Fritzemeier, Jonathan; Csörgő, Bálint; Lázár, Viktória; Lu, Xiaowen; Fekete, Gergely; Bálint, Balázs; Herczeg, Róbert; Nagy, István; Notebaart, Richard A.; Lercher, Martin J.; Pál, Csaba; Papp, Balázs (20 May 2016). "Adaptive evolution of complex innovations through stepwise metabolic niche expansion". Nature Communications. 7 (1): 11607. Bibcode:2016NatCo...711607S. doi:10.1038/ncomms11607. ISSN 2041-1723. PMC 5411730. PMID 27197754.
  31. ^ Lázár, Viktória; Pal Singh, Gajinder; Spohn, Réka; Nagy, István; Horváth, Balázs; Hrtyan, Mónika; Busa-Fekete, Róbert; Bogos, Balázs; Méhi, Orsolya; Csörgő, Bálint; Pósfai, György; Fekete, Gergely; Szappanos, Balázs; Kégl, Balázs; Papp, Balázs; Pál, Csaba (2013). "Bacterial evolution of antibiotic hypersensitivity". Molecular Systems Biology. 9: 700. doi:10.1038/msb.2013.57. PMC 3817406. PMID 24169403.
  32. ^ Bokor, Dóra (11 June 2018). "Directed evolution of multiple genomic loci allows the prediction of antibiotic resistance". MTA.hu (in Hungarian). Retrieved 11 June 2018.
  33. ^ Pál, Csaba; Papp, Balázs; Pósfai, György (28 May 2014). "The dawn of evolutionary genome engineering". Nature Reviews Genetics. 15 (7): 504–512. doi:10.1038/nrg3746. ISSN 1471-0056. PMID 24866756. S2CID 6854503. Retrieved 28 May 2014.
  34. ^ Nyerges, Ákos; Csörgő, Bálint; Nagy, István; Latinovics, Dóra; Szamecz, Béla; Pósfai, György; Pál, Csaba (1 April 2014). "Conditional DNA repair mutants enable highly precise genome engineering". Nucleic Acids Research. 42 (8): e62. doi:10.1093/nar/gku105. ISSN 0305-1048. PMC 4005651. PMID 24500200.
  35. ^ Nyerges, Ákos; Csörgő, Bálint; Nagy, István; Bálint, Balázs; Bihari, Péter; Lázár, Viktória; Apjok, Gábor; Umenhoffer, Kinga; Bogos, Balázs; Pósfai, György; Pál, Csaba (11 February 2016). "A highly precise and portable genome engineering method allows comparison of mutational effects across bacterial species". Proceedings of the National Academy of Sciences. 113 (9): 2502–2507. Bibcode:2016PNAS..113.2502N. doi:10.1073/pnas.1520040113. ISSN 0027-8424. PMC 4780621. PMID 26884157.
  36. ^ "Lieben Prize". Wikipedia. 17 January 2020. Retrieved 29 January 2020.
  37. ^ "Csaba Pal". stipendien.oeaw.ac.at. Archived from the original on 10 April 2019. Retrieved 17 November 2008.
  38. ^ "Pál Csaba biológus a Bolyai-díjas 2015-ben". Hivatalos weboldalra költözött a Bolyai-díj. Retrieved 17 May 2015.
  39. ^ "Bolyai-díj – 2015". National Geographic (in Hungarian). 18 May 2015. Retrieved 18 May 2015.
  40. ^ "Biologist Csaba Pál is awarded this year's Bolyai Prize". www.t-systems.hu. Retrieved 18 May 2015.
  41. ^ "Pál Csaba biológus kapta az idei Bolyai-díjat". hirado.hu (in Hungarian). Retrieved 17 May 2015.
  42. ^ "Akadémiai elismerések a közgyűlésen". 3 May 2021.
  43. ^ "Eseménynaptár".
  44. ^ "Antibiotikumok és ellenálló baktériumok – Pál Csaba székfoglaló előadása (2023.03.14.)". YouTube. 3 April 2023.