After attachment of donor double stranded DNA with the surface of recipient bacterium, one strand is digested by the bacterial nuclease and the remaining one strand is then taken in by an energy-requiring transport system. This uptake of DNA takes place during late logarithmic phase of growth. During this process, Rec A type of protein plays an important role.
After reaching at proper place, the Rec A protein actively displaces one strand of chromosomal DNA of recipient cell. The process requires hydrolysis of ATP to get energy. Thus the transformation is completed.
The E. Later, it has been discovered that the transformation in E. This can be done by exposure of E. This type of transformation is called artificial. During this process, the recipient bacterial cells are able to take up double stranded DNA fragments. Physical or chemical treatment forces the recipient bacterial cell to receive exogenous DNA.
This involves nick i. The generally accepted model of the above phenomenon is given below Fig. This was discovered by Joshua Leaderberg and Nortor Zinder during their research with Salrv onella typhimurium. In this process, a small fragment of bacterial DNA is incorporated into an attacking bacteriophage i.
The phage does not cause the lysis of the host bacterium. In the bacterial cell, the phage nucleic acid codes for the synthesis of specific proteins, the repressor proteins.
The repressor proteins prevent the virus to produce the material require for its replication. The bacterial cell which carries the prophage is called lysogenic and the phenomenon where the phage DNA and bacterium exist together is called lysogeny. However, in course of time, the phage stops the synthesis of repressor proteins in the bacterial cell, and then the synthesis of phage components starts. During this separation, a number of genes of the bacterium get attached to it.
These attached genes keep on replicating along with the phage DNA Fig. When the new phage particle Fig. Thus the new bacterial cell contains its own genes and several genes from the parent bacterial cell. This type of transduction is known as specialised transduction, which is an extremely rare event.
In this process, the phage DNA starts synthesising new phages. During this process chromosome of bacterial cell gets fragmented Fig. This type of transduction is called generalised transduction.
Tests for recombination are routinely performed in MLST-based studies and it has become clear that homologous recombination rates HRR vary widely between different species for example, Maynard Smith et al.
The underlying causes of this variation, however, are rarely addressed and not well understood. Calculating a measure of recombination rate, rather than simply detecting a significant presence or absence of homologous recombination events, enables an explicit comparison between species. This allows the variation in HRR to be reviewed in the light of phylogeny and ecology.
Similar HRR among species having comparable ecologies but belonging to divergent taxonomic groups could indicate that recombination rates have evolved because of adaptive evolution. On the other hand, different HRR among species having comparable ecologies but belonging to divergent taxonomic groups could imply that recombination rates are evolutionarily constrained. Why bacteria engage in homologous recombination is the subject of intense debate Redfield, ; Narra and Ochman, ; Michod et al.
Three main hypotheses have been brought forward to explain the evolutionary benefits of homologous recombination. According to the food hypothesis, incorporation of foreign DNA in the genome is a by-product of the uptake of DNA for metabolism Redfield, , Finally, the various hypotheses for the maintenance of sex in eukaryotes, that is, the removal of deleterious mutations and the combination of beneficial mutations, could be equally applied to bacteria Narra and Ochman, Elevated HRR in certain groups thus could indicate increased need for DNA repair, increased importance of DNA for metabolism or a role for recombination to increase the efficacy of natural selection.
Many approaches are available to identify homologous recombination events and rates from sequence data. However, different methods vary in their ability to detect recombination Posada, ; Stumpf and McVean, ; Didelot and Falush, , making comparisons of datasets from the literature difficult.
Here, we reanalyzed MLST data from a wide variety of species using the coalescent-based method implemented in the computer package ClonalFrame Didelot and Falush, A wide spectrum of methods exist to estimate this ratio, using either microevolutionary techniques Falush et al. However, since it ignores length and nucleotide diversity of imported fragments, it contains no information on the actual impact recombination has on evolutionary change.
ClonalFrame attempts to reconstruct the clonal genealogy of a sample of strains, as well as the mutation and recombination events that took place on the branches of this genealogy, based on a coalescent model. The coalescent is a population genetics model that tracks the ancestry of present day individuals back in time to their last common ancestor Kingman, It approximates the expected genealogy of a sample of individuals within a large population evolving under the Wright—Fisher model Fisher, ; Wright, When a mutation happens, it affects any nucleotide in the gene fragment with uniform probability and according to the Jukes—Cantor model of substitution Jukes and Cantor, When a recombination event happens, it affects a stretch of DNA within which every nucleotide has an equal probability to be substituted Didelot and Falush, By not attempting to reconstruct the origin of each recombination event within the population, ClonalFrame provides an accurate and efficient approximation of the computationally demanding coalescent with the recombination model Hudson, As it uses Bayesian statistics, a credibility interval can be computed for each parameter, which is a direct reflection of our uncertainty to infer the parameter based on the data.
A brief description of each dataset is given in the Supplementary Information. These boundaries are arbitrary but facilitate discussion and roughly correspond to interpretations of recombination rates in the literature.
The values in Table 1 should be interpreted only as a general indication of HRR in a species. Results will vary when a different sample of strains is used. Loci vary in their recombination rate Mau et al. Some estimates will be imprecise because of suboptimal sampling from the natural population see below.
Finally, it has to be stressed that different populations belonging to the same species might have different HRR. The first half of the chains was discarded, and the second half was sampled every hundred iterations.
For the datasets in which we found a Gelman—Rubin statistic above 1. We then recomputed the Gelman—Rubin statistics and found all of them to be satisfactory that is, below 1.
Graphical comparisons of the traces of the likelihood and model parameters demonstrated that the runs were properly converged and mixed. All datasets analyzed here are based on multiple, selectively constrained housekeeping loci. The use of multiple loci buffers against possible variation in HRR across the genome as well as against stochastic variation.
Intergenic spacer regions, genes under diversifying selection and genes encoding ribosomal subunits were not included because of potential confounding effects of selection on the detection of HRR. Representative sampling of bacterial populations is required to estimate recombination rates that are biologically meaningful. There are two main ways in which non-representative sampling can lead to an underestimation of the actual recombination rate: 1 when multiple distinct populations are lumped together and 2 when certain genotypes are over-represented in a sample Figure 1.
Avoiding these pitfalls requires a detailed knowledge on the biology of the species in question. Sampling clones from a population. Homologous recombination events are depicted by arrows and take place primarily within separate evolutionary lineages ecotypes. Asterisks represent sampled clones. Sampling scheme 1 is biased because it does not differentiate between distinct ecotypes.
Sampling scheme 2 shows correct sampling from a distinct ecotype. Sampling scheme 3 is biased towards an epidemic clone within an ecotype visualized by the increased width of the lineage.
These clusters of closely related genotypes within a named species are often termed ecotypes Cohan, It is plausible that ecotypes could differ in their HRR because of adaptive evolution or environmental constraints. When a population sample contains different ecotypes inhabiting distinct, spatially separated micro-niches that preclude the close contact necessary for genetic exchange, HRR will be underestimated. Similarly, ecotypes inhabiting identical micro-niches in different locations are less likely to exchange DNA than clones from the same location.
Evidence for this process has been found in the soil bacterium Rhizobium leguminosarum , where clonality was less pronounced at a regional scale than it was at a global scale Souza et al.
Highly successful clones will become widespread in a population. Maynard Smith et al. Oversampling of a single clone in an epidemic population structure will therefore result in an underestimation of HRR.
Although pooling of distinct populations will generally result in an underestimation of HRR, it is possible to overestimate HRR of a given ecotype when it is lumped together with ecotypes that have higher HRR Figure 1. To avoid potential confounding effects of spatial population structure, local or regional strain collections were analyzed instead of global collections when possible.
For studies where strains were found to cluster in multiple, deep-branching clades, only one such clade was analyzed to avoid possible pooling of distinct ecotypes Cohan, , each with possibly distinct HRR. Only one representative of each Sequence Type was included in the analysis to avoid possible effects of epidemic population structure.
Bacterial species were classified according to ecology in the following broad groups: 1 extremophiles, 2 marine and aquatic bacteria, 3 terrestrial bacteria, 4 commensals, that is, species that are part of the normal flora of humans or other animals, 5 obligate pathogens and 6 endosymbionts. Depending on their environment of origin, opportunistic pathogens are classified in group 2, 3 or 4.
Great variation in HRR was detected among species Table 1. Neisseria and Helicobacter are frequently used as examples of bacteria with very high HRR, but lesser known species Flavobacterium and Pelagibacter were found to be even more recombinogenic. Extremophiles have attracted attention from microbial ecologists partly because the isolation of their habitats such as geothermal vents, seeps, springs and salt lakes results in potentially strongly structured populations, and therefore offer a special opportunity to study microbial biogeography.
The hot spring inhabiting cyanobacterium Mastigocladus laminosus has a low-to-intermediate HRR. Two archaea, the thermoacidophile Sulfolobus and the halophile Halorubrum , have similar, intermediate HRR. Homologous recombination has been detected in the bacteria Thermotoga Nesbo et al. There has been a surge in sequence-based research on marine prokaryotes in recent years for example, Rusch et al.
However, relatively few research efforts have focused at population level sequence variation. The oceanic species Pelagibacter ubique has very high HRR. HRR is also very high in the pelagic freshwater cyanobacterium Microcystis but low in the benthic marine cyanobacterium Microcoleus. Environmental isolates of marine and estuarine Vibrio parahaemolyticus and V. Disease-related lineages in both species show lowered HRR which is consistent with epidemic spread of a subset of virulent clones Chowdhury et al.
It can cause gastrointestinal disease in humans after consumption of seafood or contact with untreated water Salerno et al. A number of MLST studies have been carried out for proteobacteria that live in soil, or are associated with plants.
HRR was found to be intermediate in both Pseudomonas syringae and P. Data on P. The nitrogen fixing soil bacterium Klebsiella pneumophila is an important opportunistic pathogen for which we found a low HRR.
In agreement with the original study, the first two species were found to have low HRR with B. HRR was found to be higher in another local B. Firmicutes species for which less well-defined populations were sampled are Listeria monocytogenes and Oenococcus oeni. This group is largely composed of species that inhabit the gastrointestinal tract, the respiratory tract and skin. The gastrointestinal lifestyle of some commensals means that they can also be common in the environment.
The related, but never pathogenic commensal N. We classified Helicobacter pylori as an opportunistic pathogens as it inhabits the stomachs of over half the global human population but only occasionally causes disease Falush et al. It is one of the best-known examples of bacteria with very high HRR Suerbaum et al. It is a ubiquitous commensal in the intestine of mammals and birds, but certain types are also known to persist in the environment Walk et al.
Figure 2: Structure of the Holliday junction. A Electron-microscope image of a recombination intermediate. In this image, the Holliday junction was partially denatured to assist its visualization. B Two possible configurations for the Holliday junction, with the DNA shown in the parallel left or antiparallel configuration right. Potter, H. DNA recombination: in vivo and in vitro studies.
Cold Spring Harb. All rights reserved. Liu, Y. Happy Hollidays: 40th anniversary of the Holliday junction. Nature Reviews Molecular Cell Biology 5 , Figure Detail. Although common, genetic recombination is a highly complex process.
It involves the alignment of two homologous DNA strands the requirement for homology suggests that this occurs through complementary base-pairing , but this has not been definitively shown , precise breakage of each strand, exchange between the strands, and sealing of the resulting recombined molecules.
This process occurs with a high degree of accuracy at high frequency in both eukaryotic and prokaryotic cells. The basic steps of recombination can occur in two pathways, according to whether the initial break is single or double stranded. In the single-stranded model , following the alignment of homologous chromosomes, a break is introduced into one DNA strand on each chromosome, leaving two free ends.
Each end then crosses over and invades the other chromosome, forming a structure called a Holliday junction Figure 2. The next step, called branch migration , takes place as the junction travels down the DNA. The junction is then resolved either horizontally, which produces no recombination, or vertically, which results in an exchange of DNA. In the alternate pathway initiated by double-stranded breaks, the ends at the breakpoints are converted into single strands by the addition of 3' tails.
These ends can then perform strand invasion, producing two Holliday junctions. From that point forward, resolution proceeds as in the single-stranded model Figure 3.
Note that a third model of recombination, synthesis-dependent strand annealing [SDSA], has also been proposed to account for the lack of crossover typical of recombination in mitotic cells and observed in some meiotic cells to a lesser degree.
No matter which pathway is used, a number of enzymes are required to complete the steps of recombination. The genes that code for these enzymes were first identified in E. This research revealed that the recA gene encodes a protein necessary for strand invasion. Meanwhile, the recB , recC , and recD genes code for three polypeptides that join together to form a protein complex known as RecBCD; this complex has the capacity to unwind double-stranded DNA and cleave strands.
Two other genes, ruvA and ruvB , encode enzymes that catalyze branch migration , while Holliday structures are resolved by the protein resolvase , which is product of the ruvC gene.
In eukaryotes, recombination has been perhaps most thoroughly studied in the budding yeast Saccharomyces cerevisiae. Many of the enzymes identified in this yeast have also been found in other organisms, including mammalian cells. Such studies reveal that the Rad genes named for the fact that their activity was found to be sensitive to radiation play a key role in eukaryotic recombination. In particular, the Rad51 gene, which is homologous to recA , encodes a protein called Rad51 that has recombinase activity.
This gene is highly conserved, but the accessory proteins that assist Rad51 appear to vary among organisms. For example, the Rad52 protein is found in both yeast and humans, but it is missing in Drosophila melanogaster and C. RPA has a higher affinity for ssDNA than Rad51, and it therefore can inhibit recombination by blocking Rad51's access to the single strand needed for invasion. Once access has been gained, Rad51 polymerizes on the DNA strand to form what is called a presynaptic filament, which is a right-handed helical filament containing six Rad51 molecules and 18 nucleotides per helical repeat.
The search for DNA homology and formation of the junction between homologous regions is then carried out within the catalytic center of the filament.
In addition to proteins that assist Rad51 activity, there are also some proteins that inhibit it. It is thought that these proteins play a role in preventing recombination during DNA replication when it is not needed. Donor cells must contain a small DNA segment called the F-plasmid, which the recipient must lack. The donor cell provides a single strand of DNA from the F-plasmid and transfers it to the recipient.
In some cases, the donor also contributes chromosomal DNA beyond that of the F-plasmid. The recipient combines the donor DNA with its own genome. He holds an M. You can see samples of his work at ericbank. How Do Bacteria Reproduce? What Is the Diploid Number?
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