@article{570,
  abstract     = {Most phenotypes are determined by molecular systems composed of specifically interacting molecules. However, unlike for individual components, little is known about the distributions of mutational effects of molecular systems as a whole. We ask how the distribution of mutational effects of a transcriptional regulatory system differs from the distributions of its components, by first independently, and then simultaneously, mutating a transcription factor and the associated promoter it represses. We find that the system distribution exhibits increased phenotypic variation compared to individual component distributions - an effect arising from intermolecular epistasis between the transcription factor and its DNA-binding site. In large part, this epistasis can be qualitatively attributed to the structure of the transcriptional regulatory system and could therefore be a common feature in prokaryotes. Counter-intuitively, intermolecular epistasis can alleviate the constraints of individual components, thereby increasing phenotypic variation that selection could act on and facilitating adaptive evolution. },
  author       = {Lagator, Mato and Sarikas, Srdjan and Acar, Hande and Bollback, Jonathan P and Guet, Calin C},
  issn         = {2050-084X},
  journal      = {eLife},
  publisher    = {eLife Sciences Publications},
  title        = {{Regulatory network structure determines patterns of intermolecular epistasis}},
  doi          = {10.7554/eLife.28921},
  volume       = {6},
  year         = {2017},
}

@phdthesis{1121,
  abstract     = {Horizontal gene transfer (HGT), the lateral acquisition of genes across existing species
boundaries, is a major evolutionary force shaping microbial genomes that facilitates
adaptation to new environments as well as resistance to antimicrobial drugs. As such,
understanding the mechanisms and constraints that determine the outcomes of HGT
events is crucial to understand the dynamics of HGT and to design better strategies to
overcome the challenges that originate from it.
Following the insertion and expression of a newly transferred gene, the success of an
HGT event will depend on the fitness effect it has on the recipient (host) cell. Therefore,
predicting the impact of HGT on the genetic composition of a population critically
depends on the distribution of fitness effects (DFE) of horizontally transferred genes.
However, to date, we have little knowledge of the DFE of newly transferred genes, and
hence little is known about the shape and scale of this distribution.
It is particularly important to better understand the selective barriers that determine
the fitness effects of newly transferred genes. In spite of substantial bioinformatics
efforts to identify horizontally transferred genes and selective barriers, a systematic
experimental approach to elucidate the roles of different selective barriers in defining
the fate of a transfer event has largely been absent. Similarly, although the fact that
environment might alter the fitness effect of a horizontally transferred gene may seem
obvious, little attention has been given to it in a systematic experimental manner.
In this study, we developed a systematic experimental approach that consists of
transferring 44 arbitrarily selected Salmonella typhimurium orthologous genes into an
Escherichia coli host, and estimating the fitness effects of these transferred genes at a
constant expression level by performing competition assays against the wild type.
In chapter 2, we performed one-to-one competition assays between a mutant strain
carrying a transferred gene and the wild type strain. By using flow cytometry we
estimated selection coefficients for the transferred genes with a precision level of 10-3,and obtained the DFE of horizontally transferred genes. We then investigated if these
fitness effects could be predicted by any of the intrinsic properties of the genes, namely,
functional category, degree of complexity (protein-protein interactions), GC content,
codon usage and length. Our analyses revealed that the functional category and length
of the genes act as potential selective barriers. Finally, using the same procedure with
the endogenous E. coli orthologs of these 44 genes, we demonstrated that gene dosage is
the most prominent selective barrier to HGT.
In chapter 3, using the same set of genes we investigated the role of environment on the
success of HGT events. Under six different environments with different levels of stress
we performed more complex competition assays, where we mixed all 44 mutant strains
carrying transferred genes with the wild type strain. To estimate the fitness effects of
genes relative to wild type we used next generation sequencing. We found that the DFEs
of horizontally transferred genes are highly dependent on the environment, with
abundant gene–by-environment interactions. Furthermore, we demonstrated a
relationship between average fitness effect of a gene across all environments and its
environmental variance, and thus its predictability. Finally, in spite of the fitness effects
of genes being highly environment-dependent, we still observed a common shape of
DFEs across all tested environments.},
  author       = {Acar, Hande},
  issn         = {2663-337X},
  pages        = {75},
  publisher    = {Institute of Science and Technology Austria},
  title        = {{Selective barriers to horizontal gene transfer}},
  year         = {2016},
}

@article{1902,
  abstract     = {In the 1960s-1980s, determination of bacterial growth rates was an important tool in microbial genetics, biochemistry, molecular biology, and microbial physiology. The exciting technical developments of the 1990s and the 2000s eclipsed that tool; as a result, many investigators today lack experience with growth rate measurements. Recently, investigators in a number of areas have started to use measurements of bacterial growth rates for a variety of purposes. Those measurements have been greatly facilitated by the availability of microwell plate readers that permit the simultaneous measurements on up to 384 different cultures. Only the exponential (logarithmic) portions of the resulting growth curves are useful for determining growth rates, and manual determination of that portion and calculation of growth rates can be tedious for high-throughput purposes. Here, we introduce the program GrowthRates that uses plate reader output files to automatically determine the exponential portion of the curve and to automatically calculate the growth rate, the maximum culture density, and the duration of the growth lag phase. GrowthRates is freely available for Macintosh, Windows, and Linux.We discuss the effects of culture volume, the classical bacterial growth curve, and the differences between determinations in rich media and minimal (mineral salts) media. This protocol covers calibration of the plate reader, growth of culture inocula for both rich and minimal media, and experimental setup. As a guide to reliability, we report typical day-to-day variation in growth rates and variation within experiments with respect to position of wells within the plates.},
  author       = {Hall, Barry and Acar, Hande and Nandipati, Anna and Barlow, Miriam},
  issn         = {1537-1719},
  journal      = {Molecular Biology and Evolution},
  number       = {1},
  pages        = {232 -- 238},
  publisher    = {Oxford University Press},
  title        = {{Growth rates made easy}},
  doi          = {10.1093/molbev/mst187},
  volume       = {31},
  year         = {2014},
}