Csaba Pál - Publications#


Many of Csaba Pál's works have been published in top-ranked interdisciplinary journals, such as Nature (5), Nature Genetics (3), Nature Reviews Genetics (4), Science (2), PNAS (3), Plos Biology (2), Nature Communications (1, +1 in press), Molecular Biology and Evolution (4) and Molecular Systems Biology (2). For the complete publication list, see: http://group.szbk.u-szeged.hu/sysbiol/pal-csaba-lab-index.html
For citation metrics, see: https://scholar.google.hu/citations?user=9VUsiHMAAAAJ&hl=en

Selected major publications:

1.
Highly expressed genes in yeast evolve slowly
C Pál, B Papp, LD Hurst
Genetics 158 (2), 927-931
This paper demonstrates for the first time that that evolutionary rate of a protein is predominantly influenced by its expression level rather than functional importance. Many consider this idea as a paradigmatic shift in field of protein evolution (Zhang and Yang NRG 2015). Eugene Koonin, one of the leading figures of the field argued that expression level-protein evolutionary rate is one of the four laws of genome evolution (Koonin, Plos Comp Biol 2011).

2.
Dosage sensitivity and the evolution of gene families in yeast
B Papp, C Pal, LD Hurst
Nature 424 (6945), 194-197 562 2003
Cited: 440
This paper studies the molecular mechanisms underlying dosage sensitivity. The hypothesis they described here offers a synthesis on seemingly unrelated problems such as dominance of mutations, gene duplicability and co-evolution of protein complex subunits. Predictions of the hypothesis have been confirmed in many eukaryotic organisms, and now it appears to be an important unifying model with implications on the dominance of certain human genetic diseases.

3.-9.
Adaptive evolution of bacterial metabolic networks by horizontal gene transfer
C Pál, B Papp, MJ Lercher
Nature genetics 37 (12), 1372-1375 329 2005

Metabolic network analysis of the causes and evolution of enzyme dispensability in yeast
B Papp, C Pal, LD Hurst
Nature 429 (6992), 661-664 305 2004

Chance and necessity in the evolution of minimal metabolic networks
C Pál, B Papp, MJ Lercher, P Csermely, SG Oliver, LD Hurst
Nature 440 (7084), 667-670 197 2006

Plasticity of genetic interactions in metabolic networks of yeast
R Harrison, B Papp, C Pál, SG Oliver, D Delneri
Proceedings of the National Academy of Sciences 104 (7), 2307-2312 150 2007

An integrated approach to characterize genetic interaction networks in yeast metabolism
B Szappanos, K Kovács, B Szamecz, F Honti, M Costanzo, ...
Nature genetics 43 (7), 656-662 91 2011

Systems-biology approaches for predicting genomic evolution
B Papp, RA Notebaart, C Pál
Nature Reviews Genetics 12 (9), 591-602 76 2011

Network-level architecture and the evolutionary potential of underground metabolism
RA Notebaart, B Szappanos, B Kintses, F Pál, Á Györkei, B Bogos, ...
Proceedings of the National Academy of Sciences 111 (32), 11762-11767 22 2014
Csaba Pal had a pivotal role in establishing the emerging field of evolutionary systems biology (Papp et al. 2011). His research focused on understanding the extent to which evolution is predictable at the molecular level. Csaba Pal and co-workers realized that genome-scale metabolic network modeling combined with experimental tools offers an unprecedented opportunity to study some of the most difficult problems in evolution, such as mutational robustness (Papp et al Nature 2004), horizontal gene transfer (Pal et al Nature 2005), genome reduction (Pal et al. Nature 2006), epistasis (Szappanos et al. Natute Genetics 2011), promiscuous enzyme reactions (Notebaart et al. PNAS 2014) and the problem of complex adaptations (Szappanos et al. 2016). The approach developed in these papers is now a major trend and has been followed by many other research groups.

10.
Coevolution with viruses drives the evolution of bacterial mutation rates
C Pal, MD Maciá, A Oliver, I Schachar, A Buckling
Nature 450 (7172), 1079-1081 154 2007
This paper demonstrates that antagonistic coevolution with parasites has a large impact on the evolution of bacterial mutation rate (Pal et al. Nature 2007). This is an exceptionally important finding, as it is shows how biotic interactions can shape long term changes in genomic mutation rate.

11.
Bacterial evolution of antibiotic hypersensitivity
V Lázár, GP Singh, R Spohn, I Nagy, B Horváth, M Hrtyan, R Busa‐Fekete, ...
Molecular systems biology 9 (1), 700 39 2013
By combining laboratory evolution, genome sequencing, and functional analyses, this work charted the map of evolutionary trade-offs between antibiotics. They made the striking discovery that mutations that caused multidrug resistance in bacteria simultaneously enhanced sensitivity to many other unrelated drugs (collateral sensitivity), and they also explored the underlying molecular mechanisms (Lazar et al MSB 2013). Since its publication, collateral sensitivity emerged as one of the leading concepts in antibiotic resistance research (Baym et al. Science 2016).

12.-13.
Nyerges, Á., Csörgő, B., Nagy, I., Bálint, B., Bihari, P., Lázár, V., Apjok, G., Umenhoffer, K., Bogos, B., Pósfai, G., Pál, C. (2016)
A highly precise and portable genome engineering method allows comparison of mutational effects acrossbacterial species.
Proc Natl Acad Sci U S A. 2016 Feb 16. pii: 201520040.

The dawn of evolutionary genome engineering
C Pál, B Papp, G Pósfai
Nature Reviews Genetics 15 (7), 504-512 19 2014
Csaba Pal is an advocate of the emerging field of evolutionary genome engineering (Pal et al. Nature Reviews Genetics 2014). These technologies enable 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. They recently presented a simple, all-in-one solution (Nyerges et al. PNAS 2016). The method is unique as it allows systematic comparison of mutational effects and epistasis across a wide range of bacterial species.
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