“The world will not be inherited by the strongest; it will be inherited by those most able to change.”
This quote by evolutionary biologist Charles Darwin is quite appreciable in the microscopic world of bacteria and viruses.
Bacteria, in the natural world are swamped by a myriad of environmental stressors. Changes at the genetic level often beget bacterial adaptations to these challenges, helping them find a fine balance between growth and stress tolerance.
Using Escherichia coli as a model system, a group led by Dr. Aswin Sai Narain Seshasayee explored how regulatory networks evolve in natural bacterial populations. Using experimental and computational approaches, the group has discovered that over small time scales of a few months to years, bacteria adapt to their dynamic environments by predominantly modifying regulatory elements called transcription factors. Many a time, these ‘gene expression switches’ have a sweeping influence on regulatory networks and their mutations may prove costly in the long run. Pressed by such constraints, these high impact genetic alterations in transcription factors seem to get polished over several million years, eventually making them conserved across populations.
Two studies - one reporting the genetic remodelling of bacterial transcription factors over short time scales (a few weeks) and another, over longer evolutionary time (millions of years) have been published in mSphere (a journal published by the American Society for Microbiology) and in the journal, Nucleic Acids Research (published by Oxford University Press), respectively.
In bacteria, genetic customization in response to dynamic environments can be of two types – (1) modifications in the underlying genetic sequence of genes (mutations) or (2) alterations in the activity level of genes (gene expression).
“These two mechanisms converge when mutations occur in regulators of gene expression called transcription factors. Often, such regulators affect the expression of many target genes, and mutations in these genes can therefore affect multiple processes at once,” explains Aswin.
If we were to look at bacterial evolution over several billion years, a number of regulatory genes have been lost and gained. In laboratory evolutionary studies spanning shorter time scales (months or years), transcription factors were found to be the genetic hot spots for mutations. Given such a trend, would we expect transcription factors to be quite diverse among the various naturally occurring variants of bacteria? Can this understanding help us decipher how bacterial regulatory networks evolve to overcome stressors?
Using a computation method, Farhan, a graduate student in Aswin’s lab set out to test whether transcription factors were diverse across different bacterial isolates. He compared gene sequences of transcription factors and their target genes from several evolved populations of a single species of bacteria. Surprisingly, he found exactly the opposite - genes coding for transcription factors were rather conserved between these natural isolates. In fact, genetic diversity was higher among the target genes.
“We were at loss to explain these conflicting observations,” says Farhan.
“The missing link was Lenski’s long term lab evolution experiment. With 60000 generations of evolution, we could observe how the frequency of mutations in transcription factors change over time,” he continues.
Farhan went on to probe this massive dataset for answers. He identified that transcription factors displayed an initial surge for adaptive genetic changes. However, over several million generations, the frequency of mutations in transcription factors dwindled and was slowly optimized to shape the long term evolutionary trajectory. This was especially true in the case of ‘global regulators’ whose effects are more widespread and may turn out expensive if not ironed out. Thus, in well adapted environments, genetic diversity of transcription factors was quite sparse among bacterial populations.
“We now know that the high frequency of mutations in transcription factors is only limited to the early stages of adaptation. These are the driving factors for adaptation to a novel environment and therefore divergence. To understand how this happens, we first need to take on the labyrinthine task of identifying these beneficial mutations hidden within the sea of neutral mutations,” says Farhan.
This is exactly what his colleague, Pabitra and a postdoc Savita Chib began to explore.
Pabitra analysed bacterial adaptations that evolved over a short time period of 4 weeks. He used the laboratory paradigm of culturing bacteria under strong nutritional stress wherein they are poised between growth and stress management.
In particular, Pabitra looked for genetic changes during the stationary phase of the bacterial growth curve - a stage where there is no appreciable increase in the number of cells. During this stage, although quiescent in growth, these bacteria are dynamic in making purposeful changes at the molecular level. Thus mutations are rampant.
One such bacterial population isolated after 3 weeks in stationary phase showed a favourable mutation in RpoC, a gene that encodes the transcription factor called RNA polymerase. This protein is a master regulator of gene expression. Over a small time window during the stationary phase, the RpoC mutant bacteria were able to outcompete its ancestral strain – a phenomenon known as growth advantage during stationary phase.
Further experimental evidence showed that the RpoC mutant variant enhanced the activity of a master regulator of stress response – the stationary phase sigma factor. A transient upregulation of this key regulator helped attune the need for growth and tolerate stress. Thus RpoC mutant bacteria were rather slow growing and formed miniature colonies.
Slow growing bacteria are known to withstand stressors and have often been found to be pathogenic. In fact, this variant was tolerant to a mild antibiotic that it had never faced before.
“In healthcare systems, small colony variants are known to pose a challenge by causing chronic or recalcitrant diseases. Although such variants are largely found to be metabolic mutants, they may have arisen from similar regulatory changes that cause slow growth,” says Pabitra, lead author of the study.
This finding is yet another fitting example of how adaptations over short time scales are a result of genetic modifications in transcription factors and how they subsequently influence regulatory networks.
Put together, the two studies show that while bacteria wade through various challenging environments, the genetic landscape of regulatory genes and their networks paint a different picture based on the evolutionary time scales under study.
Image Credit: Preethi Ravi