Genome and proteome evolution

Dr. Enrique M. Muro is a principal investigator (tenured).
Computational Biologist and Bioinformatician with background in Neural Computation/Artificial Neural Networks and Computational Physics.


Enrique M. Muro

Contact information:
Dr. Enrique M. Muro
Institute of Organismic and Molecular Evolution (iomE)
Faculty of Biology
Johannes Gutenberg University of Mainz
Biozentrum I
Hans-Dieter-Huesch-Weg 15
55128 Mainz. Germany

E-mail: ed.zniam-inu@orum (not a palindrome, please read it backwards)

Research

We have made progress to quantitatively understand how the genetic architecture of life was transformed during eukaryogenesis. We have brought to light how the distributions of protein coding gene and protein lengths evolved across the whole tree of life. Our findings show, quantitatively, that eukaryotes emerged as a second-order transition phase, arising from the tension of increasing gene length and the constraints on producing longer proteins on average. Evolutionary biologists have tried to unveil the mechanism leading to eukaryotes after the symbiosis between a Bacteria and an Archaea, referred as the "black hole at the heart of biology". We have demostrated that it occurred abruptly but yet continuously, at a critical point. The increase in cellular complexity induced by this evolutionary event unlocked the path towards subsequent biological transitions such as multicellularity, sexuality, sociability, and so on.
In recent years, research on pseudogene evolution, retrotransposons, 3D architecture of chromatin and transcription has been also carried out. Always a passionate of interdisciplinary teams.

The following work, which proposes novel perspectives on how to observe evolutionary processes, is the main foundation of my current research on genome and proteome evolution:
- The emergence of eukaryotes as an evolutionary algorithmic phase transition.
Muro, E.M., Ballesteros, F.J., Luque, B., Bascompte, J.
PNAS Online since 27 March 2025. https://www.pnas.org/doi/10.1073/pnas.2422968122

See also some reflections in the two articles below that emphasize why the current research line is well grounded:
- PNAS commentary article (see https://www.pnas.org/doi/10.1073/pnas.2505484122)
- Mark Buchanan's Nature Physics column (see https://www.nature.com/articles/s41567-025-02905-w)

Statement

Science is full of rules that simplify the way nature works. Simplifications that, many times, stand on our incomplete knowledge of the domain and can mislead posterior research. It is not always the most efficient way to learn but, for practical reasons, is a good strategy. This has been previously approached in the concept of Falsifiability by Karl Popper. Biology, in particular, is specially prone to this problem due to its intrinsic complexity.
The state of the art is the best we have. Nevertheless, exceptions can be relevant, causal of functionality and even have implications in human diseases. Therefore, scientists supported by evidence and swimming against the tide, have big chances to make a difference if they are strong enough. In summary, there is no such unique way to develop science, but creativity, critical thinking and new perspectives lead straight to the conquest of new results, and if for any reason it is a must to ferret out where the mainstream is, trying alternative solutions that follow the parsimony principle will be my way to go.

Keywords

Computational Biology, proteome and genome evolution, genomics.

Still interested on: non-coding genes, pseudogenes, transcription, mobile DNA, systems biology, three-dimensional chromatin structure, stem cells, astrobiology, artificial intelligence, neural networks, models for the development of the central visual system.

Innovative Approaches to Teaching at the Faculty:

Advantages of working on computational biology © Biocomicals by Alper Uzun, PhD.

Even though I was already teaching subjects related to computational biology and bioinformatics -such as genomics, homology, MSA, phylogenetics, protein structure databases- I set up the first complete programming course designed for biologist at our Faculty. Given the rapid technological advances in biology, it had become essential to provide our graduates with these skills and knowledge. So I simply made it happen!
The result of that effort is the following electronic book, which I use in my classes and other learning programs "Fundamentals of programming in biology with Python". Enjoy it!

Science outreach:

Bioinformatics, el Pais



Book on Bioinformatics: Bioinformática. Entre la carne y la máquina
Enrique M. Muro
After publication was translated to some languages. Available in spanish, italian, rumanian, ... 		@ El Pais

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