Prokaryotic Evolution

Introduction

The biological processes that occur in an organism have been viewed to be a symbolic wonder and many scientists are studying the starting point, the evolution and the process of survivorship of species for the past years. Both Archaea and bacteria under the domain of Prokaryotes are considered as the main divergence that lead to the appearance of the domain of Eukarya (Gribaldo, S,2006). This great evolutionary process happened because of natural Archaea and bacteria have been known to use recombination in the exchanging of genes while reproducing in a vertical descent (Shapiro, 2016). The horizontal transfer of the genes gives the organisms an opportunity to spread any genes or mutations in a rapid manner between the species thereby reducing any burden caused by deleterious mutations (Shapiro, 2016). By definition, vertical descent or clonality is viewed as the existing balance between both horizontal and vertical inheritance (Shapiro, 2016). Clonality is however not static in some cases like, for example, most clonal expansions occur as a result of non-clonal populations with high recombining like pathogens (Shapiro, 2016). The analysis of the past clonality of a bacterial population which is measured by its diversified genomes can act as a good predictor of its future clonality (Shapiro, 2016).

The recombination processes have over time been invoked in offering explanations of the noted discrepancies between nucleotide sequences and dendrograms thereby showing that some bacteria like the E.coli can be clonal by nature (Lackner, 2011). Keynotes have to be made however that the clonality of bacteria duly depends on the paradigm status for every existing bacterial populace (Dixit, 2017). Data collected on the clonality of different species relies heavily on the demonstrative capacity of the high coefficients of linkage disequilibrium addendum to the frequency recovery of any stray genotypes that have multiple loci (Dixit, 2017). The linkage disequilibrium in bacterial populations can, however, arise in several ways whereby the analyzed samples may be inclusive of a mixture of various populations which may be ecologically or geographically isolated thereby creating barriers to the gene exchange process; the occurrence of temporary disequilibrium due to an epidemic population structure; maintenance of a disequilibrium owing to the epistatic fitness interactions existing between the loci; and finally the occurrence of the disequilibrium owing to a genetic drift (Dixit, 2017). Various deductions have been made on the global distribution of genotypes that are single multilocus with a developing issue being noted on the need for explanations to be raised on the random association that exists in most alleles found in every locus through the recombination process (TB, 2015).

Literature Review

Dixit (2017) presented a paper titled as “Recombination-driven genome evolution and stability” and the studies showed that the factors that determine the evolution and stability of bacterial species through the use of a computational model and a statistical test that aimed at detecting any relationship that existed between different loci and genes. Owing to the fact that the bacteria divide in a clonal manner, the gene transfer in a horizontal manner can be followed by homologous recombination (Dixit, 2017). By use of the Multi Locus Sequence Typing, the results derived from the paper showed that there were two main regimes involved in the evolution of bacteria with double composite parameters dictating the evolutionary state of the bacteria (Dixit, 2017). The framework generalizations included the selection and classification of genomes into divergent or Meta stable regimes (Dixit, 2017). In the case of the divergent regime, there was an occurrence of cohesion owing to the insufficient recombination needed to overcome the mutational drift (Sela, 2016; Dixit, 2017). This was duly characterized by strict recombination barriers and low-frequency recombination. An increase in the divergence between the genome pairs was also recorded through the evolutionary course with species which lacked any genetic consistency with any secluded clonal sub-populace dissolved and developed in a continuous manner (Sela, 2016). The genomes were however noted to incessantly recombine with the populace owing to the high-frequency recombination and low recombination barriers in the meta-stable regime (Dixit, 2017). The regime remained stable temporarily with the genes being cohesive with the transitions noted between the two regimes being affected by changes made in the parameters needed for the evolution process (Dixit, 2017).

For the purpose of exploring any evolutionary trends contained in Archaea and bacteria, Novichkov (2009) systematically presented a paper which used a data set and analysis of at least forty one ATGCs nucleobases, which they contain biological information that can leads us to track down functional characters and base substitutions within a given specie. These molecular information can be used to compare between original ATGCs nucleobases and the new evolved nucleobases maintained throughout years. In fact, The Novichkov showed that the median ratio of any synonymous substitution and non-synonymous rates used in measuring the selection pressure of protein sequences act as stable factors for the alienable tight genome clusters (Novichkov, 2009). The paper was based on a previous musing by Koonin (2008) whereby the findings noted that parasitic bacteria are subjected to weak purifying selection owing to the dramatic changes in terms of shrinkage of genomes (Koonin E., 2008). This can be overly attributed to the frequent bottlenecks and the small effective population sizes. These bottlenecks are considered as a major event that happen in various level where the size of the population is dramatically reduced within that certain species population. Actually, it can be characterized on a molecular level and environmental level such as disasters and the genetic variation.

Takeuchi (2014) indicates that there is no existing evidence on the streamlining of genomes that are brought about by the genome size correlation, gene size or even selective pressure even though a good number of free-living prokaryotes with close pressure are found in the entire genome range (Takeuchi, 2014). Addendum to this, Novichkov (2009) examined any relationships between the existent genomic features and the sequence of evolution rates. Moreover, the key results from the paper show that even though the gene order changes at a faster rate compared to other sequential proteins during prokaryotes evolution (Novichkov, 2009), there is an inherent relationship between the amino acid distance and the rearrangement expanse signifying that there is a subjective condition meted on the events that lead to genome rearrangement and the progression of amino acid chains during genomic evaluation (Novichkov, 2009).

As Dan Graur presented in his textbook “ Molecular and Genome Evolution” prokaryotic genomes tend to be smaller than the eukaryotic gnomes size (Graur, 2016). Additionally, Bacterial genomes diverge into two orders which are the bacterial genomes and the archean genomes in term of variations (Graur, 2016). The bacterial genomes are tend to be approximately larger than archean genomic content as shown on (Table 1). The prokaryotic genomes contain productive functional genomics and the composition of the functional content tend to be around 90% (Graur, 2016).

A theory set explains the genetic strength controls of genome complexity and size which was also presented by Martinez-Kano (2015) with a key focus being made on prokaryotes. Additionally, prokaryotic genome tend to experience a high intraspecifice rate of variation during evolving within the genomic content (Graur, 2016). As a matter of fact, prokaryotes tend to have large efficient sizes of the population which imply strong selection traits that enable them to maintain any compact genomes (Martínez-Cano, 2015). Through the use of such selection traits, any short sequences that are non-functional tend to incur costs during the selection process through the combining of any increasing expenditure on the energy rate and the subsequent reduction of the rate of replication (Martínez-Cano, 2015). Comparisons were also drawn between the multicellular forms of eukaryotes and prokaryotes with results showing that the effective population size in eukaryotes is smaller thereby meaning that the selection process is not enough to ensure the elimination of any genetic material that may be superfluous (Dixit, 2017). Surprisingly this elimination actually helps in the minimization of any bloated genomes whilst providing the required materials needed for the evolution of any complex features (Martínez-Cano, 2015). The author presents assumptions on the fact that any extra genetic material that arises from acquisition or duplication can be viewed to be deleterious to the bacteria because the new DNA will not be able to work immediately (Martínez-Cano, 2015). The elucidated theory can be said to be a slight deviation from the well-established population genetic principles as it provides a unified framework that helps in the understanding of the genome evolution complexity status without raising any issues on widespread adaptation. It can also be assumed to be a null hypothesis used in explaining the genome evolution with predictions being made on the inverse correlation existing between the selective strength and genome sizes (Martínez-Cano, 2015). Even though the selection of the protein sequence level was done through the conducting of measurements of strictly related microbes through the use of synonymous substitution rates to non-synonymous ratios, there were indicative results that the large prokaryotic genes evolve under strong selection than small ones (Martínez-Cano, 2015).

Drivers of Evolution among Free-Living Prokaryotes

A) Increased Rate Of Mutation Hypothesis

Mutations are the causing key to maintain variability and evolution among species, which led to the development of new features that are needed for survival (Fisher 1992). Mutations affecting the protein coding sequences regions can be used as an estimation indicator for long or short eclountionray distance (AL Halpern – ‎1998). The variety in the rate of mutations in prokaryotic genomes helped to increase the probability to drifted into new allelic selection which led to the continuous evolution in prokaryotic cells (Marais et al., 2008). In fact, the high mutation rate was a positive advantage for bacteria colonies to evolve towards new desired habitat (Marais et al., 2008).

A vital aspect in the evolution of prokaryotes has been deemed to be the accelerated protein evolution rates in bacteria (McCandlish DM, 2015). By looking at bacterial protein rate and the evaluation of their functional process, the prediction of the evolutionary tree can be be possible. In fact, this accelerated protein evolution occurs as a byproduct when there is an increase in the rate of mutations which becomes beneficial like in most novel niche colonization cases (McCandlish DM, 2015). Classical genetic models that aim at explaining the population of bacteria have stated that product selection of the effective population size (Ne) determines the fate of allele only if the selection coefficient is greater than one (Nes>1). The fate of the allele can also be caused by the genetic waft especially if its values are less than one Ne s<1 (McCandlish DM, 2015). The model, however, applies when there is the negligible rate in mutation but if the equilibrium frequency of the allele is at zero then there is a chance of the allele being lost in the population (McCandlish DM, 2015).

B) Migration and Paring of Replication Forks.

Figure 1.

Replication Fork. The leading strand in the direction 5’ to 3’ tend to be the main continuous synthesis process and also the lagging strand occur in the same direction which is 5’ to 3’. But it is in a discontinuous pattern. The green labeling shows the RNA/DNA primer that activate the leading-strand synthesis and Okazaki fragment on the lagging strand.

 

The DNA replication process in prokaryotes acquired the replication fork formation is structured as shown on (figure 1) because of the helicase separation of the DNA strands at the origin of replication. The replication fork process is tend to be one of the most effective factors that can cause genomes to be unstable overtime, and that helped to make evolution process in prokaryotic genomes (Setlow et al.1963). In fact blocking the replication fork blockage would be a critical step to make the bacterial genomes stable and turn off gene duplication process (J Atkinson – ‎2009). The activation of the replication fork would help to increase the evolutionary trait in bacterial genome. Actually, the replication fork in bacterial cells migrates along the DNA molecules in a manner that causes a complementary base pairing between the new and the parental DNA strands (Doroghazi, 2011). The existence of these replication forks duly depends on the structural composition of the nucleotides and how the electrons are distributed in the DNA. It is of common knowledge that the nucleotides take structural forms that are tautomeric with their adenine compounds undergoing base pairing with both thymine and cytosine (Doroghazi, 2011). Any mispairing that may occur from the base pairing may lead to the replication of DNA and may be attributed to the presence of tautomeric forms that are short living. For years, this phenomenon has been difficult to explain with Meinke (2012) stating that any mispairing resulting from the replication of the DNA can be corrected through the use of repair processes guided by enzymes. The author, however, posits that in the case that any sequence alterations remain unpaired, there might be an occurrence of substitution mutations (Meincke, 2012).