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A functional analysis of random coding sequences in Escherichia coli


Bhave,  Devika
Department Evolutionary Genetics, Max Planck Institute for Evolutionary Biology, Max Planck Society;
IMPRS for Evolutionary Biology, Max Planck Institute for Evolutionary Biology, Max Planck Society;

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Bhave, D. (2020). A functional analysis of random coding sequences in Escherichia coli. PhD Thesis, Faculty of Mathematics and Natural Sciences, Kiel University, Kiel.

Cite as: https://hdl.handle.net/21.11116/0000-0007-31D9-D
Adaptation of organisms to continuously changing environments includes the
generation of genic novelty in their genomes through mechanisms such as de novo
gene evolution, duplication, fusion, lateral gene transfer, etc. De novo gene
evolution is a mechanism, wherein new gene functions can evolve from previously
non-coding sequences, which are essentially random stretches of nucleotides.
Several studies have explored the role of such random sequences as templates for
evolutionary innovation. This included a systematic study, where a library of
random coding sequences was expressed in Escherichia coli and differential growth
was measured to assess fitness effects of individual sequences. Each random
sequence from the library was categorized into negative, positive or neutral based
on its change in abundance in the population across time. In this thesis, I analyse
the effects of individual clones derived from this screen.

In order to study effects of random sequences on the fitness of the host, I cloned
representative variants from each category into E. coli strains using a multicopy
plasmid vector. In the first part of the thesis, I demonstrate that expression of
negative random peptides confers a fitness disadvantage (deleterious) in E. coli,
followed by a growth recovery. Upon further investigation, I find that these
peptides can elicit a stress response in the host instantaneously upon expression.
The highly deleterious phenotype can thus be compensated in the host. In addition,
I was able to isolate suppressor-of-phenotype clones. Re-sequencing of the
suppressors together with each of the ancestor clones helped identify interaction
partners for the deleterious peptides. In the second part, I show two mechanisms
that the host uses to adapt to deleterious peptide expression: (a) plasmid copy
number control by inactivation of the pcnB gene and (b) expression control through
inactivation of the LacI inducer binding domain. In the third part of the thesis, I
show that the positive random peptides confer competitive fitness advantage only
under stressful conditions, for example, an elevated temperature. In conclusion, I
show that random sequences indeed affect fitness of the host possibly through
targeting specific genes or proteins. This study provides experimental evidence on
how random sequences could serve as drivers of de novo gene evolution.