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3.1: Horizontal Gene Transfer in Bacteria - Biology

3.1: Horizontal Gene Transfer in Bacteria - Biology



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Learning Objectives

After completing this section you should be able to perform the following objectives.

  1. Compare and contrast mutation and horizontal gene transfer as methods of enabling bacteria to respond to selective pressures and adapt to new environments.
  2. Define horizontal gene transfer and state the most common form of horizontal gene transfer in bacteria.
  3. Briefly describe the mechanisms for transformation in bacteria.
  4. Briefly describe the following mechanisms of horizontal gene transfer in bacteria:
    1. generalized transduction
    2. specialized transduction
  5. Briefly describe the following mechanisms of horizontal gene transfer in bacteria:
    1. Transfer of conjugative plasmids, conjugative transposons, and mobilizable plasmids in Gram-negative bacteria
    2. F+ conjugation
    3. Hfr conjugation
  6. Describe R-plasmids and the significance of R-plasmids to medical microbiology.

Bacteria are able to respond to selective pressures and adapt to new environments by acquiring new genetic traits as a result of mutation, a modification of gene function within a bacterium, and as a result of horizontal gene transfer, the acquisition of new genes from other bacteria. Mutation occurs relatively slowly. The normal mutation rate in nature is in the range of 10-6 to 10-9 per nucleotide per bacterial generation, although when bacterial populations are under stress, they can greatly increase their mutation rate. Furthermore, most mutations are harmful to the bacterium. Horizontal gene transfer, on the other hand, enables bacteria to respond and adapt to their environment much more rapidly by acquiring large DNA sequences from another bacterium in a single transfer.

Horizontal gene transfer, also known as lateral gene transfer, is a process in which an organism transfers genetic material to another organism that is not its offspring. The ability of Bacteria and Archaea to adapt to new environments as a part of bacterial evolution most frequently results from the acquisition of new genes through horizontal gene transfer rather than by the alteration of gene functions through mutations. (It is estimated that as much as 20% of the genome of Escherichia coli originated from horizontal gene transfer.)

Horizontal gene transfer is able to cause rather large-scale changes in a bacterial genome. For example, certain bacteria contain multiple virulence genes called pathogenicity islands that are located on large, unstable regions of the bacterial genome. These pathogenicity islands can be transmitted to other bacteria by horizontal gene transfer. However, if these transferred genes provide no selective advantage to the bacteria that acquire them, they are usually lost by deletion. In this way the size of the bacterium's genome can remain approximately the same size over time.

There are three mechanisms of horizontal gene transfer in bacteria: transformation, transduction, and conjugation. The most common mechanism for horizontal gene transmission among bacteria, especially from a donor bacterial species to different recipient species, is conjugation. Although bacteria can acquire new genes through transformation and transduction, this is usually a more rare transfer among bacteria of the same species or closely related species.

Transformation

Transformation is a form of genetic recombination in which a DNA fragment from a dead, degraded bacterium enters a competent recipient bacterium and is exchanged for a piece of DNA of the recipient. Transformation usually involves only homologous recombination, a recombination of homologous DNA regions having nearly the same nucleotide sequences. Typically this involves similar bacterial strains or strains of the same bacterial species.

A few bacteria, such as Neisseria gonorrhoeae, Neisseria meningitidis, Hemophilus influenzae, Legionella pneomophila, Streptococcus pneumoniae, and Helicobacter pylori tend to be naturally competent and transformable. Competent bacteria are able to bind much more DNA than noncompetent bacteria. Some of these genera also undergo autolysis that then provides DNA for homologous recombination. In addition, some competent bacteria kill noncompetent cells to release DNA for transformation.

During transformation, DNA fragments (usually about 10 genes long) are released from a dead degraded bacterium and bind to DNA binding proteins on the surface of a competent living recipient bacterium. Depending on the bacterium, either both strands of DNA penetrate the recipient, or a nuclease degrades one strand of the fragment and the remaining DNA strand enters the recipient. This DNA fragment from the donor is then exchanged for a piece of the recipient's DNA by means of RecA proteins and other molecules and involves breakage and reunion of the paired DNA segments as seen in (Figure (PageIndex{1})). Transformation is summarized in Figure (PageIndex{2}).

Figure (PageIndex{2}): Transformation: Step 1: A donor bacterium dies and is degraded.Step 2: DNA fragments, typically around 10 genes long, from the dead donor bacterium bind to transformasomes on the cell wall of a competent, living recipient bacterium.Step 3: In this example, a nuclease degrades one strand of the donor fragment and the remaining DNA strand enters the recipient. Competence-specific single-stranded DNA-binding proteins bind to the donor DNA strand to prevent it from being degraded in the cytoplasm. Step 4: RecA proteins promotes genetic exchange between a fragment of the donor's DNA and the recipient's DNA (see Figure (PageIndex{1}) for the functions of RecA proteins). This involves breakage and reunion of paired DNA segments. Step 5: Transformation is complete.

Transduction

Transduction involves the transfer of a DNA fragment from one bacterium to another by a bacteriophage. There are two forms of transduction: generalized transduction and specialized transduction.

During the replication of lytic bacteriophages and temperate bacteriophages, occasionally the phage capsid accidently assembles around a small fragment of bacterial DNA. When this bacteriophage, called a transducing particle, infects another bacterium, it injects the fragment of donor bacterial DNA it is carrying into the recipient where it can subsequently be exchanged for a piece of the recipient's DNA by homologous recombination. Generalized transduction is summarized in Figure (PageIndex{3}).

  • Step 1: A bacteriophage adsorbs to a susceptible bacterium.
  • Step 2: The bacteriophage genome enters the bacterium. The genome directs the bacterium's metabolic machinery to manufacture bacteriophage components and enzymes. Bacteriophage-coded enzymes will also breakup the bacterial chromosome.
  • Step 3: Occasionally, a bacteriophage capsid mistakenly assembles around either a fragment of the donor bacterium's chromosome or around a plasmid instead of around a phage genome.
  • Step 4: The bacteriophages are released as the bacterium is lysed. Note that one bacteriophage is carrying a fragment of the donor bacterium's DNA rather than a bacteriophage genome.
  • Step 5: The bacteriophage carrying the donor bacterium's DNA adsorbs to a recipient bacterium.
  • Step 6: The bacteriophage inserts the donor bacterium's DNA it is carrying into the recipient bacterium.
  • Step 7: Homologous recombination occurs and the donor bacterium's DNA is exchanged for some of the recipient's DNA. (Figure (PageIndex{1}) shows the functions of the RecA proteins involved in homologous recombination.)

Generalized transduction occurs in a variety of bacteria, including Staphylococcus, Escherichia, Salmonella, and Pseudomonas.

Plasmids, such as the penicillinase plasmid of Staphylococcus aureus, may also be carried from one bacterium to another by generalized transduction.

Specialized transduction: This may occur occasionally during the lysogenic life cycle of a temperate bacteriophage. During spontaneous induction, a small piece of bacterial DNA may sometimes be exchanged for a piece of the bacteriophage genome, which remains in the bacterial nucleoid. This piece of bacterial DNA replicates as a part of the bacteriophage genome and is put into each phage capsid. The bacteriophages are released, adsorb to recipient bacteria, and inject the donor bacterium DNA/phage DNA complex into the recipient bacterium where it inserts into the bacterial chromosome (Figure (PageIndex{4})).

Conjugation

Genetic recombination in which there is a transfer of DNA from a living donor bacterium to a living recipient bacterium by cell-to-cell contact. In Gram-negative bacteria it typically involves a conjugation or sex pilus.

Conjugation is encoded by plasmids or transposons. It involves a donor bacterium that contains a conjugative plasmid and a recipient cell that does not. A conjugative plasmid is self-transmissible, in that it possesses all the necessary genes for that plasmid to transmit itself to another bacterium by conjugation. Conjugation genes known as tra genes enable the bacterium to form a mating pair with another organism, while oriT (origin of transfer) sequences determine where on the plasmid DNA transfer is initiated by serving as the replication start site where DNA replication enzymes will nick the DNA to initiate DNA replication and transfer. In addition, mobilizable plasmids that lack the tra genes for self-transmissibility but possess the oriT sequences for initiation of DNA transfer may also be transferred by conjugation if the bacterium containing them also possesses a conjugative plasmid. The tra genes of the conjugative plasmid enable a mating pair to form, while the oriT of the mobilizable plasmid enable the DNA to moves through the conjugative bridge (Figure (PageIndex{5})).

Transposons ("jumping genes") are small pieces of DNA that encode enzymes that enable the transposon to move from one DNA location to another, either on the same molecule of DNA or on a different molecule. Transposons may be found as part of a bacterium's chromosome (conjugative transposons) or in plasmids and are usually between one and twelve genes long. A transposon contains a number of genes, such as those coding for antibiotic resistance or other traits, flanked at both ends by insertion sequences coding for an enzyme called transpoase. Transpoase is the enzyme that catalyzes the cutting and resealing of the DNA during transposition.

Conjugative transposons, like conjugative plasmids, carry the genes that enable mating pairs to form for conjugation. Therefore, conjugative transposons also enable mobilizable plasmids and nonconjugative transposons to be transferred to a recipient bacterium during conjugation.

Many conjugative plasmids and conjugative transposons possess rather promiscuous transfer systems that enables them to transfer DNA not only to like species, but also to unrelated species. The ability of bacteria to adapt to new environments as a part of bacterial evolution most frequently results from the acquisition of large DNA sequences from another bacterium by conjugation.

A. General mechanism of transfer of conjugative plasmids by conjugation in Gram-negative bacteria

In Gram-negative bacteria, the first step in conjugation involves a conjugation pilus (sex pilus or F pilus) on the donor bacterium binding to a recipient bacterium lacking a conjugation pilus. Typically the conjugation pilus retracts or depolymerizes pulling the two bacteria together. A series of membrane proteins coded for by the conjugative plasmid then forms a bridge and an opening between the two bacteria, now called a mating pair.

Using the rolling circle model of DNA replication, a nuclease breaks one strand of the plasmid DNA at the origin of transfer site (oriT) of the plasmid and that nicked strand enters the recipient bacterium. The other strand remains behind in the donor cell. Both the donor and the recipient plasmid strands then make a complementary copy of themselves. Both bacteria now possess the conjugative plasmid. This process is summarized in Figure (PageIndex{6})).

This is the mechanism by which resistance plasmids (R-plasmids), coding for multiple antibiotic resistance and conjugation pilus formation, are transferred from a donor bacterium to a recipient. This is a big problem in treating opportunistic Gram-negative infections such as urinary tract infections, wound infections, pneumonia, and septicemia by such organisms as E. coli, Proteus, Klebsiella, Enterobacter, Serratia, and Pseudomonas, as well as with intestinal infections by organisms like Salmonella and Shigella.

There is also evidence that the conjugation pilus may also serve as a direct channel through which single-stranded DNA may be transferred during conjugation.

B. F+ conjugation

This results in the transfer of an F+ plasmid possessing tra genes coding only for a conjugation pilus and mating pair formation from a donor bacterium to a recipient bacterium. One strand of the F+ plasmid is broken with a nuclease at the origin of transfer (oriT) sequence that determines where on the plasmid DNA transfer is initiated by serving as the replication start site where DNA replication enzymes will nick the DNA to initiate DNA replication and transfer. The nicked strand enters the recipient bacterium while the other plasmid strand remains in the donor. Each strand then makes a complementary copy. The recipient then becomes an F+ male and can make a sex pilus (see 7A through 7D).

In addition, mobilizable plasmids that lack the tra genes for self-transmissibility but possess the oriT sequences for initiation of DNA transfer, may also be transferred by conjugation. The tra genes of the F+ plasmid enable a mating pair to form and the oriT sequences of the mobilizable plasmid enable the DNA to moves through the conjugative bridge (Figure (PageIndex{5})).

C. Hfr (high frequency recombinant) conjugation

Hfr conjugation begins when an F+ plasmid with tra genes coding for mating pair formation inserts or integrates into the chromosome to form an Hfr bacterium. (A plasmid that is able to integrate into the host nucleoid is called an episome.) A nuclease then breaks one strand of the donor's DNA at the origin of transfer (oriT) location of the inserted F+ plasmid and the nicked strand of the donor DNA begins to enter the recipient bacterium. The remaining non-nicked DNA strand remains in the donor and makes a complementary copy of itself.

The bacterial connection usually breaks before the transfer of the entire chromosome is completed so the remainder of the F+ plasmid seldom enters the recipient. As a result, there is a transfer of some chromosomal DNA, which may be exchanged for a piece of the recipient's DNA through homologous recombination, but not the ability to form a conjugation pilus and mating pairs (see Figure (PageIndex{8})A through 8E).

Exercise: Think-Pair-Share Questions

  1. A strain of living Streptococcus pneumoniae that cannot make a capsule is injected into mice and has no adverse effect. This strain is then mixed with a culture of heat-killed Streptococcus pneumoniae that when alive was able to make a capsule and kill mice. After a period of time, this mixture is injected into mice and kills them. In terms of horizontal gene transfer, describe what might account for this.
  2. A gram-negative bacterium that was susceptible to most common antibiotics suddenly becomes resistant to several of them. It also appears to be spreading this resistance to others of its kind. Describe the mechanism that most likely accounts for this.

Summary

  1. Mutation is a modification of gene function within a bacterium and while it enables bacteria to adapt to new environments, it occurs relatively slowly.
  2. Horizontal gene transfer enables bacteria to respond and adapt to their environment much more rapidly by acquiring large DNA sequences from another bacterium in a single transfer.
  3. Horizontal gene transfer is a process in which an organism transfers genetic material to another organism that is not its offspring.
  4. Mechanisms of bacterial horizontal gene transfer include transformation, transduction, and conjugation.
  5. During transformation, a DNA fragment from a dead, degraded bacterium enters a competent recipient bacterium and is exchanged for a piece of DNA of the recipient. Typically this involves similar bacterial strains or strains of the same bacterial species.
  6. Transduction involves the transfer of either a chromosomal DNA fragment or a plasmid from one bacterium to another by a bacteriophage.
  7. Conjugation is a transfer of DNA from a living donor bacterium to a living recipient bacterium by cell-to-cell contact. In Gram-negative bacteria it involves a conjugation pilus.
  8. A conjugative plasmid is self-transmissible, that is, it possesses conjugation genes known as tra genes enable the bacterium to form a mating pair with another organism, and oriT (origin of transfer) sequences that determine where on the plasmid DNA transfer is initiated.
  9. Mobilizable plasmids that lack the tra genes for self-transmissibility can be co-transfered in a bacterium possessing a conjugative plasmid.
  10. Transposons ("jumping genes") are small pieces of DNA that encode enzymes that enable the transposon to move from one DNA location to another, either on the same molecule of DNA or on a different molecule.
  11. Conjugative transposons carry the genes that enable mating pairs to form for conjugation.
  12. F+ conjugation is the transfer of an F+ plasmid possessing tra genes coding only for a conjugation pilus and mating pair formation from a donor bacterium to a recipient bacterium. Mobilizable plasmids may be co-transfered during F+ conjugation.
  13. During Hfr conjugation, an F+ plasmid with tra genes coding for mating pair formation inserts into the bacterial chromosome to form an Hfr bacterium. This results in a transfer of some chromosomal DNA from the donor to the recipient which may be exchanged for a piece of the recipient's DNA through homologous recombination.

Horizontal gene transfer

• Ten things you didn't know about Wikipedia •
Horizontal gene transfer
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“HGT” redirects here. For other uses, see HGT (disambiguation).

Horizontal gene transfer (HGT), also Lateral gene transfer (LGT), is any process in which an organism transfers genetic material to another cell that is not its offspring. By contrast, vertical transfer occurs when an organism receives genetic material from its ancestor, e.g. its parent or a species from which it evolved. Most thinking in genetics has focused on the more prevalent vertical transfer, but there is a recent awareness that horizontal gene transfer is a significant phenomenon. Artificial horizontal gene transfer is a form of genetic engineering.

As Jain, Rivera and Lake (1999) put it: "Increasingly, studies of genes and genomes are indicating that considerable horizontal transfer has occurred between prokaryotes."[1] (see also Lake and Riveral, 2007).[2] The phenomenon appears to have had some significance for unicellular eukaryotes as well. As Bapteste et al. (2005) observe, "additional evidence suggests that gene transfer might also be an important evolutionary mechanism in protist evolution."[3]

There is some evidence that even higher plants and animals have been affected. Dr. Mae-Wan Ho, a noted scientist and critic of genetic engineering, writes: "While horizontal gene transfer is well-known among bacteria, it is only within the past 10 years that its occurrence has become recognized among higher plants and animals. The scope for horizontal gene transfer is essentially the entire biosphere, with bacteria and viruses serving both as intermediaries for gene trafficking and as reservoirs for gene multiplication and recombination (the process of making new combinations of genetic material)."[4] But Richardson and Palmer (2007) are more cautious: "Horizontal gene transfer (HGT) has played a major role in bacterial evolution and is fairly common in certain unicellular eukaryotes. However, the prevalence and importance of HGT in the evolution of multicellular eukaryotes remain unclear."[5]

Due to the increasing amount of evidence suggesting the importance of these phenomena for evolution (see below), molecular biologists such as Peter Gogarten have described horizontal gene transfer as a "A New Paradigm for Biology".[6]

It should also be noted that the process is emphasised by Dr. Mae-Wan Ho as an important factor in "The Hidden Hazards of Genetic Engineering", as it may allow dangerous transgenic DNA (which is optimised for transfer) to spread from species to species.[4]
Contents
[hide]

* 1 Prokaryotes
* 2 Eukaryotes
* 3 Evolutionary theory
o 3.1 Genes
* 4 See also
* 5 Sources and notes
* 6 Further reading

Horizontal gene transfer is common among bacteria, even very distantly-related ones. This process is thought to be a significant cause of increased drug resistance when one bacterial cell acquires resistance, it can quickly transfer the resistance genes to many species. Enteric bacteria appear to exchange genetic material with each other within the gut in which they live. There are three common mechanisms for horizontal gene transfer:

* Transformation, the genetic alteration of a cell resulting from the introduction, uptake and expression of foreign genetic material (DNA or RNA). This process is relatively common in bacteria, but less common in eukaryotes. Transformation is often used to insert novel genes into bacteria for experiments, or for industrial or medical applications. See also molecular biology and biotechnology.
* Transduction, the process in which bacterial DNA is moved from one bacterium to another by a bacterial virus (a bacteriophage, commonly called a phage).
* Bacterial conjugation, a process in which a living bacterial cell transfers genetic material through cell-to-cell contact.

Analysis of DNA sequences suggests that horizontal gene transfer has also occurred within eukaryotes, from their chloroplast and mitochondrial genome to their nuclear genome. As stated in the endosymbiotic theory, chloroplasts and mitochondria probably originated as bacterial endosymbionts of a progenitor to the eukaryotic cell.[7]

Horizontal transfer of genes from bacteria to some fungi, especially the yeast Saccharomyces cerevisiae, has been well documented.[8]

There is also recent evidence that the adzuki bean beetle has somehow acquired genetic material from its (non-beneficial) endosymbiont Wolbachia however this claim is disputed and the evidence is not conclusive.[9]

"Sequence comparisons suggest recent horizontal transfer of many genes among diverse species including across the boundaries of phylogenetic "domains". Thus determining the phylogenetic history of a species can not be done conclusively by determining evolutionary trees for single genes."[10]

Horizontal gene transfer is a potential confounding factor in inferring phylogenetic trees based on the sequence of one gene. For example, given two distantly related bacteria that have exchanged a gene, a phylogenetic tree including those species will show them to be closely related because that gene is the same, even though most other genes have substantially diverged. For this reason, it is often ideal to use other information to infer robust phylogenies, such as the presence or absence of genes, or, more commonly, to include as wide a range of genes for phylogenetic analysis as possible.

For example, the most common gene to be used for constructing phylogenetic relationships in prokaryotes is the 16s rRNA gene, since its sequences tend to be conserved among members with close phylogenetic distances, but variable enough that differences can be measured. However, in recent years it has also been argued that 16s rRNA genes can also be horizontally transferred. Although this may be infrequent, validity of 16s rRNA-constructed phylogenetic trees must be reevaluated.

Biologist Gogarten suggests "the original metaphor of a tree no longer fits the data from recent genome research" therefore "biologists should use the metaphor of a mosaic to describe the different histories combined in individual genomes and use the metaphor of a net to visualize the rich exchange and cooperative effects of HGT among microbes."[6]

Using single genes as phylogenetic markers, it is difficult to trace organismal phylogeny in the presence of horizontal gene transfer. Combining the simple coalescence model of cladogenesis with rare HGT horizontal gene transfer events suggest there was no single last common ancestor that contained all of the genes ancestral to those shared among the three domains of life. Each contemporary molecule has its own history and traces back to an individual molecule cenancestor. However, these molecular ancestors were likely to be present in different organisms at different times."[11]

Uprooting the Tree of Life by W. Ford Doolittle (Scientific American, February 2000, pp 72-77)[12] contains a discussion of the Last Universal Common Ancestor, and the problems that arose with respect to that concept when one considers horizontal gene transfer. The article covers a wide area - the endosymbiont hypothesis for eukaryotes, the use of small subunit ribosomal RNA (SSU rRNA) as a measure of evolutionary distances (this was the field Carl Woese worked in when formulating the first modern "tree of life", and his research results with SSU rRNA led him to propose the Archaea as a third domain of life) and other relevant topics. Indeed, it was while examining the new three-domain view of life that horizontal gene transfer arose as a complicating issue: Archaeoglobus fulgidus is cited in the article (p.76) as being an anomaly with respect to a phylogenetic tree based upon the encoding for the enzyme HMGCoA reductase - the organism in question is a definite Archaean, with all the cell lipids and transcription machinery that are expected of an Archaean, but whose HMGCoA genes are actually of bacterial origin.[13]

Again on p.76, the article continues with:

"The weight of evidence still supports the likelihood that mitochondria in eukaryotes derived from alpha-proteobacterial cells and that chloroplasts came from ingested cyanobacteria, but it is no longer safe to assume that those were the only lateral gene transfers that occurred after the first eukaryotes arose. Only in later, multicellular eukaryotes do we know of definite restrictions on horizontal gene exchange, such as the advent of separated (and protected) germ cells."[13]

The article continues with:

"If there had never been any lateral gene transfer, all these individual gene trees would have the same topology (the same branching order), and the ancestral genes at the root of each tree would have all been present in the last universal common ancestor, a single ancient cell. But extensive transfer means that neither is the case: gene trees will differ (although many will have regions of similar topology) and there would never have been a single cell that could be called the last universal common ancestor.[13]

"As Woese has written, 'the ancestor cannot have been a particular organism, a single organismal lineage. It was communal, a loosely knit, diverse conglomeration of primitive cells that evolved as a unit, and it eventually developed to a stage where it broke into several distinct communities, which in their turn became the three primary lines of descent (bacteria, archaea and eukaryotes)' In other words, early cells, each having relatively few genes, differed in many ways. By swapping genes freely, they shared various of their talents with their contemporaries. Eventually this collection of eclectic and changeable cells coalesced into the three basic domains known today. These domains become recognisable because much (though by no means all) of the gene transfer that occurs these days goes on within domains."[13]

With regard to how horizontal gene transfer affects evolutionary theory (common descent, universal phylogenetic tree) Carl Woese says:

"What elevated common descent to doctrinal status almost certainly was the much later discovery of the universality of biochemistry, which was seemingly impossible to explain otherwise. But that was before horizontal gene transfer (HGT), which could offer an alternative explanation for the universality of biochemistry, was recognized as a major part of the evolutionary dynamic. In questioning the doctrine of common descent, one necessarily questions the universal phylogenetic tree. That compelling tree image resides deep in our representation of biology. But the tree is no more than a graphical device it is not some a priori form that nature imposes upon the evolutionary process. It is not a matter of whether your data are consistent with a tree, but whether tree topology is a useful way to represent your data. Ordinarily it is, of course, but the universal tree is no ordinary tree, and its root no ordinary root. Under conditions of extreme HGT, there is no (organismal) "tree." Evolution is basically reticulate."[14]

[edit] Genes
This list is incomplete you can help by expanding it.

There is evidence for historical horizontal transfer of the following genes:

* Lycopene cyclase for carotenoid biosynthesis, between Chlorobi and Cyanobacteria.[15]

* Endogenous retrovirus
* Germline
* HeLa
* Integron
* Provirus
* Retrotransposon
* Rhizome (philosophy)
* Genetically modified organism

1. ^ Lake, James A. and Maria C. Riveral (1999). "Horizontal gene transfer among genomes: The complexity hypothesis". PNAS (Proceedings of the National Academy of Science) 96:7: pp. 3801-3806. Retrieved on 2007-03-18.
2. ^ Lake, James A. and Maria C. Riveral (2004). "The Ring of Life Provides Evidence for a Genome Fusion Origin of Eukaryotes". Nature 431 [1]. Retrieved on 2007-03-16.
3. ^ Bapteste et al. (2005). "Do Orthologous Gene Phylogenies Really Support Tree-thinking?". BMC Evolutionary Biology 5:33. Retrieved on 2007-03-18.
4. ^ a b sfsu.edu Dr Mae-Wan Ho
5. ^ Richardson, Aaron O. and Jeffrey D. Palmer (January 2007). "Horizontal Gene Transfer in Plants". Journal of Experimental Botany 58: pp. 1-9 [2]. Retrieved on 2007-03-18.
6. ^ a b Gogarten, Peter (2000). "Horizontal Gene Transfer: A New Paradigm for Biology". Esalen Center for Theory and Research Conference. Retrieved on 2007-03-18.
7. ^ Jeffrey L. Blanchard and Michael Lynch (2000), "Organellar genes: why do they end up in the nucleus?", Trends in Genetics, 16 (7), pp. 315-320. (Discusses theories on how mitochondria and chloroplast genes are transferred into the nucleus, and also what steps a gene needs to go through in order to complete this process.) [3]
8. ^ Hall C, Brachat S, Dietrich FS. "Contribution of Horizontal Gene Transfer to the Evolution of Saccharomyces cerevisiae." Eukaryot Cell 2005 Jun 4(6):1102-15. [4] The article argues that horizontal transfer of bacterial DNA to Saccharomyces cerevisiae has occurred.
9. ^ Natsuko Kondo, Naruo Nikoh, Nobuyuki Ijichi, Masakazu Shimada and Takema Fukatsu (2002) "Genome fragment of Wolbachia endosymbiont transferred to X chromosome of host insect", Proceedings of the National Academy of Sciences of the USA, 99 (22): 14280-14285". [5] (Free full article) This article argues that Wolbachia DNA is in the azuki bean beetle genome (a species of bean weevil.
10. ^ okstate.edu
11. ^ Cladogenesis Paper
12. ^ Doolittle, Ford W. (February 2000). "Uprooting the Tree of Life". Scientific American: pp. 72-77.
13. ^ a b c d Uprooting the Tree of Life by W. Ford Doolittle (Scientific American, February 2000, pp 72-77)
14. ^ Microbiology and Molecular Biology Reviews, June 2004, p. 173-186, Vol. 68, No. 2 article A New Biology for a New Century by Carl Woese
15. ^ D.A. Bryant & N.-U. Frigaard (Nov 2006). "Prokaryotic photosynthesis and phototrophy illuminated". Trends Microbiol. 14 (11): 488. DOI:10.1016/j.tim.2006.09.001.

* http://en.citizendium.org/wiki/Horizontal_gene_transfer
* http://en.citizendium.org/wiki/Horizontal_gene_transfer_in_prokaryotes
* Steven L. Salzberg, Owen White, Jeremy Peterson, and Jonathan A. Eisen (2001) "Microbial Genes in the Human Genome: Lateral Transfer or Gene Loss?" Science 292, 1903-1906. [6] (Free full article) This article points out that one dramatic claim of horizontal gene transfer - in which a distinguished group of scientists claimed that bacteria transferred their DNA directly into the human lineage - was simply wrong.
* Woese, Carl (2002) "On the evolution of cells", PNAS, 99(13) 8742-8747. [7] (Free full article) This article seeks to shift the emphasis in early phylogenic adaptation from vertical to horizontal gene transfer.
* Snel B, Bork P, Huynen MA (1999) "Genome phylogeny based on gene content", Nature Genetics, 21(1) 66-67. [8]This article proposes using the presence or absence of a set of genes to infer phylogenies, in order to avoid confounding factors such as horizontal gene transfer.
* Webfocus in Nature with free review articles [9]
* Prabhu B. Patil and Ramesh V. Sonti (2004) "Variation Suggestive of Horizonatal Gene Transfer in Xanthomonas oryzae pv. oryzae, the leaf blight pathogen of rice" BMC Microbiology 4:40.
* Bioinformatics Vol. 22 no. 21 2006, pages 2604� for a technique to decrease the impact of HGT events on maximum likelihood cladistical analyses.
* Horizontal Gene Transfer - A New Paradigm for Biology
* Horizontal Gene Transfer (page 334 of Molecular Genetics by Ulrich Melcher)
* Report on horizontal gene transfer by Mae-Wan Ho, March 22, 1999
* Recent Evidence Confirms Risks of Horizontal Gene Transfer
* Horizontal Gene Transfer at sciences.sdsu.edu
* Horizontal gene transfer among genomes: The complexity hypothesis Vol. 96, Issue 7, 3801-3806, March 30, 1999 of The National Academy of Sciences
* PDF article on Horizontal Gene Transfer
* The New Yorker, July 12, 1999, pp. 44-61 "Smallpox knows how to make a mouse protein. How did smallpox learn that? 'The poxviruses are promiscuous at capturing genes from their hosts,' Esposito said. 'It tells you that smallpox was once inside a mouse or some other small rodent.'"
* Retrotransfer or gene capture: a feature of conjugative plasmids, with ecological and evolutionary significance
* Results of research into horizontal gene transfer Can transgenes from genetically modified plants be absorbed by micro-organisms and spread in this way?

[hide]
v • d • e
Genetics: genetic recombination

Bacterial conjugation - Chromosomal crossover - Gene conversion - Fusion gene - Horizontal gene transfer - Sister chromatid exchange - Transduction - Transfection - Transformation
Retrieved from "http://en.wikipedia.org/wiki/Horizontal_gene_transfer"

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Introduction

Polyketides comprise a large class of natural products synthesized by unrelated organisms, such as bacteria, protists, plants, fungi and animals. These compounds are often found in organisms living in mutualistic associations, such as symbiotic bacteria of fungi , insects, and sponges [1]–[4], or lichen-forming fungi [5]. Indeed, lichenized fungi, which maintain obligate associations with cyanobacterial or algal photosynthetic partners are characterized by a sophisticated vegetative morphology and a rich polyketide metabolism [6], [7]. Strikingly, only about 10% of the compounds in the lichen symbiosis occur in other fungi or in vascular plants [8]. The unique secondary metabolism of lichenized fungi exemplifies some of the prevailing problems in natural product research: How did the great diversity of compounds evolve? Which processes initiated the explosive radiation of secondary metabolites in some lineages? To address these issues we employed comparative phylogenetic methods on a set of genes involved in biosynthesis of polyketide extrolites in bacteria, as well as in lichenized and non-lichenized fungi.

Polyketide synthases (PKSs), among other enzymes, are involved in the biosynthesis of polyketides. PKSs are multifunctional enzymes, which are related to fatty acid synthases (FAS) [9], [10]. PKS and FAS condense small carbon units to form the carbon backbone of the polyketide. Structural variation is created by the usage of different starter units and chain extension substrates [11], variable reduction reactions on some or all of the keto groups [10], and post PKS tailoring of the PKS product [12]. Bacteria and fungi commonly harbor a group of PKSs that consists of a single protein complex carrying all catalytic sites (type I PKS). These PKSs are often involved in aromatic polyketide biosynthesis [13]. The domains of type I PKSs may be used reiteratively. A minimal module carries ketosynthase (KS), acyltransferase (AT), and acyl carrier protein (ACP) domains to perform one chain elongation cycle. Optional additional domains responsible for successive reduction steps are ketoreductase (KR), dehydratase (DH), and enoyl reductase (ER). The most conserved gene regions in type I PKS are the KS and AT domains, which are frequently used to infer the evolution of PKS genes [14]–[21]. The phylogenetic placement of the KS can be predictive of some of the PKS's properties, such as reducing or non-reducing functions [16], [22], [23].

The horizontal movement of genetic material between distantly related organisms, horizontal gene transfer (HGT), has played an important role in the evolution of prokaryotes [24] as well as eukaryotes [25], [26]. Interkingdom transfer of genes has also been demonstrated in fungi [27], [28]. While the majority of PKS genes in fungal genomes most likely originated from gene duplication and subsequent subfunctionalization of individual genes [16], a growing body of evidence suggests that HGT has also influenced the evolution of this gene family. Co-regulation of expression has been suggested to be among the causal factors for the clustering of biosynthetic genes in fungi [29], [30]. This clustering facilitates transfer and has been among the arguments for HGT of biosynthetic genes [31]. Further arguments include the location of biosynthetic genes in genome regions that are particularly likely to recombine, such as the telomere ends of the chromosomes [30], and the close proximity to mobile genetic elements [32], [33]. The penicillin cluster, which occurs in many bacteria and a few fungi has been cited as an example of biosynthetic gene HGT. Tentative evidence for this event was found in the codon usage in the fungal penicillin cluster, which is more like that of prokaryotes [34], and in molecular clock estimates on a penicillin cluster phylogeny, which suggest that with respect to the divergence time between bacteria and fungi, the cluster appears much closer than expected to bacterial genes [35].

In the current study we infer the evolutionary history of a clade of fungal type I PKS genes which is closely related to bacterial PKSs. Gene products of PKSs in this clade are small monocyclic or polycyclic aromatic compounds, which are precursors of fungal antibiotics, such as patulin [36], and widespread food-contaminating mycotoxins, such as ochratoxin [37]. Since 6-methylsalicylic acid synthase (6-MSAS) was the first PKS in this group to be characterized [36], we termed this clade 𠇆-MSAS-type PKS”. Gene products of closely related bacterial PKSs include aromatic moieties of potent antibiotics, such as avilamycin [38] and calicheamicin [39]. Since iteratively acting PKSs are rare in bacteria, this group is sometimes referred to as 𠇏ungal” type I PKS in bacteria [40]. HGT is typically invoked as the most likely explanation for the phylogenetic placement of the 6-MSAS clade [15], [16], [21]. However, previous studies based this conclusion on tree topology only, and the direction of the interkingdom transfer remained elusive. Kroken et al. (2003) found a clade of fungal PKS genes nested within bacterial sequences and postulated a HGT from bacteria to fungi, while Jenke-Kodama et al. (2005) interpreted the placement of bacterial genes within groups of fungal sequences as evidence for HGT in the opposite direction.

An additional reason for our interest in this clade is the occurrence of sequences from lichenized fungi [41]. While none of the PKS genes found in lichens have yet been functionally characterized, it is possible that 6-MSAS-type genes are involved in lichen compound formation. The lichen-characteristic depsides and depsidones, which result from the coupling of two or more monocyclic polyketides (e.g. orsellinic acid), could be synthesized by a 6-MSAS-type PKS (Daniele Armaleo, personal communication). This can be deduced from the structural similarity of the molecules and the architecture of the genes: 6-MSAS differs from orsellinic acid only in one reduction ( Fig. 1 ). The keto reductase (KR) and dehydratase (DH) domains responsible for this modification could be missing or dysfunctional in the mycobiont PKS, which would then result in the synthesis of orsellinic acid. Furthermore, previous phylogenetic studies have shown that a bacterial orsellinic acid PKS (aviM, <"type":"entrez-protein","attrs":<"text":"AAK83194","term_id":"15077467","term_text":"AAK83194">> AAK83194) is closely related to fungal 6-MSAS-type PKSs [16].

The aim of this study was to establish the phylogenetic origin of the enigmatic fungal 6-MSAS-type PKS biosynthetic gene in a comparative phylogenetic framework. Our results provide statistical support to the hypothesis that this PKS was transferred from an actinobacterial source into ascomycete fungi during an ancient HGT event. We report the finding of 6-MSAS-type PKS genes in a variety of lichen-forming fungi, and speculate about the possible role of lichen symbionts in the evolution of this gene.


Materials and Methods

Taxon Sampling

Genomic data of Bartonella and other bacterial organisms related to this study were downloaded from the National Center for Biotechnology Information (NCBI) GenBank (http://www.ncbi.nlm.nih.gov/, last accessed August 15, 2014) or from the website of the Bartonella Group Sequencing Project, Broad Institute of Harvard and the Massachusetts Institute of Technology (http://www.broadinstitute.org/, last accessed August 15, 2014). Bartonella species were grouped into four lineages (L1–L4) plus B. tamiae and B. australis, following the current taxonomy (Engel et al. 2011 Pulliainen and Dehio 2012 Guy et al. 2013). For the purpose of this study, we will refer to all bartonellae except B. tamiae as eubartonellae. This is based on the recognition that B. tamiae has been described as clearly distinct from all other currently known bartonellae lineages (Kosoy et al. 2008 Guy et al. 2013). A total of 28 Bartonella species were examined in this study ( table 1 ).

BLAST Hit Distribution Analysis of Bartonella Genomes—Initial Discovery Screen

Initial discovery analysis of putative HGT events in metabolic pathways was assisted by an automated pipeline (available in the Dittmar Lab: https://github.com/DittmarLab/HGTector, last accessed August 15, 2014). This pipeline is based on a computational method of rapid, exhaustive, and genome-wide detection of HGT, featuring the systematic analysis of BLAST hit distribution patterns combined with a priori defined hierarchical evolutionary categories (Zhu et al. 2014). Batch BLASTP of Bartonella protein-coding genes was performed against the entire NCBI nr database (E value cutoff = 1 × 10 − 5 , other parameters remain default). Genes that have less than a statistically relevant threshold of the expected number of hits based on known close relatives of Bartonella, but meanwhile show multiple top hits from taxonomically distant organisms (non-Rhizobiales groups), were considered to be candidates of HGT-derived genes and were subject to further phylogenetic analyses (see below) (see Zhu et al. 2014 for details on pipeline). Particular attention was paid to genes involved in the core central intermediate metabolism and cell wall formation, which have been identified in previous studies on bacterial metabolism (Zientz et al. 2004).

Phylogenetic Analyses and Validation of Horizontally Transferred Genes

Phylogenetic analyses were employed to validate the putative horizontal and vertical histories of the genes identified in the initial discovery screen. Phylogenetic patterns nesting a Bartonella gene within a homologous gene clade of a candidate donor group, or as strongly supported sister group of a candidate donor group, were considered significant evidence supporting the horizontal transfer from this particular donor to Bartonella (Koonin et al. 2001 Nelson-Sathi et al. 2012 Husnik et al. 2013 Schonknecht et al. 2013). Nucleotide sequences of metabolic genes of interest (i.e., phospholipid pathway) were extracted from Bartonella genomes as well as genomes of selected organisms that represent the putative donor group and its sister groups. Sequences were aligned in MAFFT version 7 (Katoh and Standley 2013), using the L-INS-i algorithm. The MAFFT program was called from the “Translational Align” panel of Geneious 6.1 (Biomatters 2013). Alignment edges were trimmed manually, if needed. The phylogenies of single-gene families were reconstructed based on nucleotide and amino acid sequence alignments (to check for congruence) in a Bayesian Markov chain Monte Carlo (MCMC) statistical framework using MrBayes 3.2 (Ronquist et al. 2012), as well as a maximum likelihood (ML) method implemented in RAxML 7.7 (Stamatakis 2006). The Bayesian MCMC runs had a chain length of 20 million generations, with the sample frequency set as 1,000. The optimal nucleotide substitution models for all three codon positions were computed in PartitionFinder 1.1 (Lanfear et al. 2012). Three independent runs were performed for each data set to ensure consistency among runs. Trace files were analyzed in Tracer 1.5 (Drummond and Rambaut 2007) to check for convergence in order to determine a proper burn-in value for each analysis. A consensus tree was built from the retained tree-space, and posterior probabilities are reported per clade. The ML was run implementing the GTR + G model (for all codon positions) and a bootstrap analysis was performed to gauge clade support.

Survey of Genomic Environments

In order to determine the frequency, components, and boundaries of the putatively horizontally transferred genetic material, genomic environments were manually examined in Geneious 6.1 (Biomatters 2013). Our assumptions are that multiple independent transfers of a gene would likely result in different gene environments being affected. Likewise, if different Bartonella species share the same gene environment adjacent to horizontally transferred genetic material, and the transferred genes follow the previously detected vertical evolutionary pattern for bartonellae, presumably a single ancestral HGT event can be inferred for all species in that lineage. Putatively HGT-derived genes and their adjacent genomic elements were identified in recipient and donor genomes and compared across species and within lineages. Results from this analysis were mapped onto the Bartonella species tree (see below).

Molecular Evolution Analyses

Selection analyses were carried out to gage selective pressures operating on all genes in the phospholipid pathway. Selection was assessed using the ML method in the Codeml program of the Phylogenetic Analysis by Maximum Likelihood (PAML) 4.7 package (Yang 2007). As the first step, an analysis under the one-ratio model (M0) was performed to estimate a global ω value (dN/dS ratio) across the phylogenetic tree. Global selective pressures were assessed using the site models (M1a, M2a, M8, and M8a). Evolutionary rates of particular branches of interest (ω1) versus the background ratio (ω0) were computed using the branch model (model = 2). Selective pressures operating on subsets of sites of these branches were calculated using the branch-site models (model A and A1). The significance of change of ω value and evidence of positive selection was assessed using the likelihood ratio test. Positive sites were identified using the Bayes Empirical Bayes (BEB) analysis (Yang et al. 2005).

The tertiary structure of the GpsA (NAD(P)H-dependent glycerol-3-phosphate dehydrogenase) protein in Coxiella burnetii (Gammaproteobacteria: Legionellales) was used to model the position of the identified sites with positive selection in horizontally transferred gpsA genes (Seshadri et al. 2003 Minasov et al. 2009).

The possibility that the horizontally acquired gpsA genes underwent convergent evolution in Bartonella, relative to their ancestors was explored. Potential ancestral states of the gpsA genes before HGT were reconstructed under model A in Codeml of PAML (see above). The sequence was then compared with the consensus sequence of extant Bartonella species. A statistical approach recently introduced by Parker et al. (2013) was applied to identify the signatures of convergent evolution of gpsA versions after horizontal acquisition. In brief, this method is based on the significance of differences in sitewise log-likelihood supports among a commonly accepted species tree and given alternative convergent topologies under the same substitution model.

Phylogenetic Analysis of Bartonella Species

In order to parsimoniously map HGT events to the evolutionary history of bartonellae, phylogenetic relationships among Bartonella species were inferred using standard phylogenetic and phylogenomic approaches as follows:

Phylogenomic analysis: The proteomes of 23 annotated Bartonella genomes were downloaded, from which orthologous groups (OGs) were identified using OrthoMCL 2.0 (Li et al. 2003) with default parameters (BLASTP E value cutoff = 1 × 10 − 5 , percent match cutoff = 80%, MCL inflation parameter = 1.5). OGs that have exactly one member in each and every genome were isolated, resulting in 516 OGs. Members of each of these OGs were aligned in MAFFT (Katoh and Standley 2013) and refined in Gblocks 0.91b (Castresana 2000) to remove problematic regions. An optimal amino acid substitution model for each OG was computed in ProtTest 3.3 (Darriba et al. 2011) using the Bayesian information criterion. The 516 alignments were concatenated into one data set, based on which a phylogenetic tree was reconstructed using the ML method as implemented in RAxML (Stamatakis 2006) with 100 fast bootstrap replicates. Bartonella tamiae was used as an outgroup, with all other bartonellae treated as ingroup.

Standard phylogenetic analysis: Five additional species could not be included in above approach, as their proteomes are not available from GenBank. To explore and confirm the phylogenetic positions of these Bartonella species, a separate analysis following previously outlined approaches (see above) was performed using six commonly used gene markers (Inoue et al. 2010 Sato et al. 2012 Mullins et al. 2013) from 28 Bartonella genomes (B. tamiae included in ingroup) and seven outgroup genomes, which represent close sister genera of Bartonella (supplementary table S1, Supplementary Material online) (Gupta and Mok 2007 Guy et al. 2013).

Experimental Genotyping

In order to further explore the distribution of Bartonella clades with HGT-derived metabolic genes in blood-feeding insects, we screened a global sampling of 21 species of Siphonaptera and Hippoboscoidea for gpsA sequences ( table 2 ). All of these samples had been positive for Bartonella gltA gene and 16S rRNA detection by polymerase chain reaction (PCR) in previous analyses (Morse et al. 2012, 2013). Genomic DNA was extracted from each individual specimen, using the DNeasy Blood & Tissue Kit (Qiagen Sciences Inc., Germantown, MD), following the animal tissue protocol. The quality and concentrations of DNA were assessed with a NanoDrop spectrometer (Thermo Fisher Scientific, Wilmington, DE). Bacterial gpsA diversity was assessed by amplification of gpsA genes from each sample using specific primers and reaction conditions: Helicobacter-derived gpsA (He) (see Results) forward: 5′-ATG AAA ATA ACA RTT TTT GGW GGY GG-3′, reverse: 5′-TTA ATA CCT TCW GCY ACT TCG CC-3′ Enterobacteriales-derived gpsA (Ar/Se) forward: 5′-GGT TCT TAT GGY ACY GCW TTA GC-3′, reverse: 5′-TAR ATT TGY TCG GYA ATT GGC ATT TC-3′. Subsequent TA cloning (if applicable) was performed to isolate amplicons. Based on previous studies of the microbial diversity of bat flies, we expect a subset of species to harbor Arsenophonus and like organisms (ALOs) as endosymbionts (Morse et al. 2013 Duron et al. 2014). In these species, we specifically targeted Arsenophonus-type gpsA for comparative purposes. Sequence analysis and phylogenetic analysis followed the standard protocols described above.


Horizontal Gene Transfer and the Evolution of Microvirid Coliphage Genomes

FIG. 1 . The H-A intergenic region for the phages clustering with α3 and φK encodes five conserved open reading frames. Gene A* was left off of the genome map because, as for α3, there are multiple potential start sites for this gene. Consensus sequences for ribosome binding sites and the promoter are provided and based upon only the new isolates. Gene positions are based on the sequence of WA13. FIG. 2 . Maximum a posteriori probability phylogeny based upon a full genome alignment. Posterior probabilities are given above the relevant branches. At least three distinct clades are apparent and well supported, each including at least one of the previously sequenced laboratory strains. The tree is mid-point rooted for visual clarity. FIG. 3 . Gene phylogenies demonstrate complex evolutionary patterns in genome evolution. The models used for analyses are as follows: A, TIM + I + G C, K80 + G D, TrN + I + G F, TrN + I + G G, HKY + G H, GTR + G J, TrNef + I, as selected by DT-ModSel. Note that genes A and C are on different scales than the rest of the phylogenies. FIG. 4 . Gene D maximum-likelihood phylogeny places the ancestors of the α3-like group and the G4-like group within the φX174-like group. This and the slower rate of evolution of gene D suggest that the current incarnation of gene D for these other groups arose in the φX174-like group and subsequently spread to the other groups.

Abstract

Bacteria evolve rapidly not only by mutation and rapid multiplication, but also by transfer of DNA, which can result in strains with beneficial mutations from more than one parent. Transformation involves the release of naked DNA followed by uptake and recombination. Homologous recombination and DNA-repair processes normally limit this to DNA from similar bacteria. However, if a gene moves onto a broad-host-range plasmid it might be able to spread without the need for recombination. There are barriers to both these processes but they reduce, rather than prevent, gene acquisition.


MECHANISMS OF HORIZONTAL TRANSFER

Horizontal Gene Transfer and the Nature of Heredity

The first description of a horizontal gene transfer has been a major advance in molecular biology, and can even be seen as its founding experiment. By demonstrating, in 1928, that nonvirulent pneumococcus bacteria can become pathogenic simply by contact with virulent bacteria, even bacteria destroyed by heat, Griffith (1928) showed that there is a thermostable principle, capable of modifying heredity. This principle would be identified years later as DNA (Avery et al. 1944). This discovery, however, could only take place because of the remarkable ability of pneumococci to acquire DNA horizontally. We now know that in this experiment, a gene responsible for the synthesis of the polysaccharide capsule of the bacterium is transferred, and incorporated in place of its deficient counterpart in nonvirulent strains.

The cytoplasm of the bacteria, wherein the genome is located, is effectively isolated from the external medium by one or more membranes, depending on the groups of bacteria. DNA cannot passively traverse these obstacles. There are specific mechanisms that facilitate foreign DNA’s access to the genome. Three of these are well documented.

Transformation is an active mechanism by which free DNA present in the medium, typically derived from dead organisms and is taken up into the cytoplasm. This could be mainly for nutritional purposes, but some bacteria are very selective on the type of DNA that they allow into the cell, suggesting that it also serves to favor recombination with close relatives (Redfield et al. 1997 Szöllősi et al. 2006 Mell and Redfield 2014).

Conjugation is a one-way transmission mechanism of DNA from one cell to another via a “sexual pilus” by which DNA is transported. This mechanism has spuriously been compared with eukaryotic sex. The donor bacterium is described as male, whereas the recipient bacterium is called female. In fact, the genes responsible for conjugation are carried by plasmids or bacteriophages known as “conjugative,” that use conjugation to insure their transmission (and thus transform the female into male). Sometimes, however, these conjugative elements accidentally carry with them the DNA of the host, in which case they can promote transfer of genes other than their own.

Transduction is a type of transfer that occurs via a bacteriophage that transmits the DNA from one cell to another. At the end of its replication cycle, the host cell undergoes lysis, and fragmented DNA of the host genome is occasionally packaged inside infectious particles. This DNA can then be injected into another individual, in place of virus DNA. Some species of bacteria have hijacked this mechanism to their advantage and have recruited bacteriophage genes to facilitate genetic exchange. Such defective phage capsids, present, in particular, in many α-proteobacteria, are called “gene transfer agents” (GTAs) (Lang and Beatty 2007).

Once inside the cytoplasm, DNA has several possible fates. It can be destroyed by DNA degradation systems that are present in the cytoplasm of the host (restriction enzymes, DNAses, etc.) or persist as autonomous replicative entities, such as plasmids. Finally, all or part of the DNA may be integrated into the host chromosome. This integration depends on several factors such as the degree of similarity with genomic DNA of the host, in the case of homologous recombination, or physical association with other sequences capable of integration such as transposable elements or bacteriophage genes. When homologous recombination occurs, the foreign DNA sequence replaces existing homologous sequences in the host genome—this is what happens in the pneumococcus example. On the contrary, when DNA is integrated into the genome by other means, it is often simply inserted as an entirely new gene.

Evolutionary Consequences of Horizontal Transfer

The true evolutionary role and impact that horizontal gene transfer has had on the evolution of life were only realized recently with the advent of genome sequencing. The above mechanisms have relatively low specificity, and thus allow movement of genetic information even between distant species, with correspondingly profound consequences on the modes of adaptation and the concept of bacterial species (Ochman et al. 2005).

In comparison to descent with modification, horizontal gene transfer offers the possibility for quite drastic adaptation. However, far from questioning the principle of Darwinian evolution, as has been suggested, this mode of evolution underscores the importance of taking into account different levels of selection (e.g., genes vs. genomes) for understanding the evolution of genomes. Many genes present in bacterial genomes come from prophages and hence have evolved under different constraints than the rest of the genome. Nonetheless, bacterial genomes have repeatedly co-opted functions from their genomic parasites (Canchaya et al. 2004 Bobay et al. 2014). Also, it has been suggested that the organization in operons of bacterial genomes (i.e., in groups of functionally related genes and cotranscribed) could be the result of a need for coregulation as well as a selection pressure for genes that interact to perform a function to remain together during horizontal transfers. This model is known as the “selfish operon” (Lawrence and Roth 1996 Price et al. 2006). Horizontal gene transfer has also been seen as a barrier to defining species in prokaryotes (and, as we shall see later, also for the concept of prokaryotic phylogeny). Defined in animals on a criterion of interfertility, or on a more molecular level, by the limits of recombination, the biological species is a concept that is difficult to apply to bacteria.


Results & discussion

Analysis of donor lineages in HGT events

To investigate donor organisms of HGTs of 64 chlamydia strains, we inferred transfer events by reconciling each gene tree of 1,030 homologous gene sets to 2,472 completely sequenced prokaryotic species phylogenies. Following initial identification and evaluation procedure, we detected 1,030 highly reliable HGT events occurred between different species including Chlamydia for every gene family. It appeared that HGT has favorably occurred between species in the Chlamydiae phylum, but there was also a number of genes derived from organisms outside of the phylum. These organisms belong to 59 different genera, covering 12 bacterial and archaeal phyla which include a wide spectrum of life style (Fig 1). Numerous HGT events were subjected to occur between Chlamydia and Proteobacteria, Spirochaetes, whereas Chlamydia barely received genes from organisms in Actinobacteria phylum. Various species-specific trends of HGT were also observed in each chlamydial species. For example, several species in phylum Firmicutes such as Bacillus anthracis CDC 684, Enterococcus faecium Aus 0085, and Staphylococcus aureus subsp. aureus TCH60 transferred genes only to C. psittaci, and absence of HGT to C. muridarum from several donor organisms in Bacteroidetes were observed (Fig 1).

(A) This figure illustrates a global pattern of HGT in 8 Chlamydia species analyzed. The phylogenetic tree of 2,472 prokaryotic species was constructed with FastTree (ver. 2.9) based on multiple sequence alignment of 16S rRNA. Tree was visualized using Interactive Tree of Life Version 3.4.3 (http://itol.embl.de/) [28]. Each colored strip of the outer circle represents different phylum of bacteria and archaea. The actual donor phylums are highlighted with asterisk. From inside out, circled bar charts represent C. abortus, C. caviae, C. felis, C. muridarum, C. pecorum, C. pneumoniae, C. psittaci, and C. trachomatis, respectively. Each bar chart shows the gene transfers from corresponding organism in the tree, and the vertical bars represent the number of HGT events between corresponding donors and recipient organisms. (B) Heatmap showing the number of HGTs between Chlamydia and non-chlamydial donor species. Rows represent all identified donor species (SV ≥ 0.9) Columns represent recipient Chlamydia species. Only HGT events have SV ≥ 0.9 are shown here.

Although many of donor organisms such as Neisseria meningitidis and Treponema pedis are known to be pathogenic to vertebrates or host associated, there exist other donor species which are typically considered as free-living bacteria including Isophaera pallida ATCC 43644, Methylacidiphilum infernorum V4, and Salinispira pacifica L21-RPU1-D2. First, for the donor species that occupy very similar niches as Chlamydia, many organisms residing and causing infections in respiratory system or urogenital organs in human or other animals were identified, in which most of the Chlamydia species are associated. Additionally, our result shows an occurrence of several HGTs with commensal organisms isolated from gastrointestinal (GI) tract of mammals. For example, ribose-phosphate pyrophosphokinase gene was transferred from Ureaplasma parvum which inhabit genital areas (SV: 1.0), and Enterococcus faecium transferred gene encoding ABC transporter family protein to C. psittaci (SV: 1.0). In previous study, it was discovered that not only Chlamydia can efficiently infect the GI tract of all hosts, including humans, but GI tract can also act as reservoir sites for chlamydial persistent infection [29, 30]. It has been reported that the GI tract is also considered to be a hot spot for HGT among bacteria [31].

In addition to bacteria residing in human or animal body sites, we observed a big proportion of environmental donor species which inhabit aquatic or terrestrial habitats (Fig 1). For instance, Lysyl-tRNA synthetase gene was transferred from aquatic bacteria, Caldilinea aerophile (SV: 0.97), and gene encoding MiaB-like tRNA modifying enzyme was transferred from Thermanaerovibrio acidaminovorans DSM 6589 residing terrestrial environments (SV: 1.0). The mechanisms by which gene transfer of Chlamydia occurring is still unclear. A number of phages required for transduction were discovered and DNA transfers were observed after host co-infection of multiple strains in many studies [9–11]. Chlamydiae phylum is considered as a group of successful parasites that have an extremely broad host range and distributed ubiquitous in nature. There have been only four families (Parachlamydiaceae, Simkaniaceae, Waddliaceae, and Criblamydiaceae) discovered within the phylum which can grow in natural hosts like amoebae [2]. However, it has been reported in many studies that a large number of rRNA sequence of chlamydia-like organisms are detected in various environmental samples such as soil, water, hot spring, and activated sludge samples [4, 32, 33]. Our results suggest that Chlamydia may have even more various host range than we have thought and potentially exchange genes in as yet unknown natural host. It also suggests the hypothesis that there may exist a novel gene transfer mechanism enabling Chlamydia to exchange genes with free-living organisms.

Variation in the effect of HGT between species

Analysis of 64 chlamydial genomes using the HGTree database identified that 701 gene families were inferred to have undergone one or more HGT, with 97 gene families transferred from outside of Chlamydiae. Further examination of the 701 HGT-acquired genes with RAxML and RANGER-DTL 2.0 resulted in 548 putative genes including 42 non-Chlamydia originated genes with high reliability. The percentage of received genes was markedly variable across the species, being more than threefold greater in C. felis lineage (30.1% of total genes), C. abortus lineage (27.4% of total genes), and C. caviae lineage (27.1% of total genes) than in C. trachomatis (8.15

9.66%) (Fig 2). The great amount of variability in the number of transferred genes between species is derived mainly from intra-phylum transfer events, on the other hands, the ratio of the inter-phylum transferred genes is shown consistently low across all strains. We also looked at the distribution of all detected gene families across COG functional categories [26]. We found that genes from all functional categories (Metabolism, Information storage and processing, and Cellular processes and signaling) are subject to transfer (Fig 3). In contrast, in inter-phylum transfers, genes related to metabolism, and information storage and processing are assigned relatively high (31% and 49%, respectively), while only 16% of cellular processes and signaling genes are assigned (Fig 3). These results indicate that there may exist genetic barriers of inter-phylum HGT in chlamydial genomes. Gene transfer between distantly related organisms is known to occur less frequently than between closely related organisms since genetic mechanisms and different genome organization can act as constraints for inter-phylum HGT [34, 35].

Boxplots show the distribution of the ratio of transferred genes for organisms in each Chlamydia species. Each plot shows the distribution of ratios of transferred genes from organisms outside of Chlamydiae phylum (Top) and ratios of transferred genes from Chlamydia (Bottom). The x-axis indicates of 8 Chlamydia species used in this study, and the y-axis indicates ratio of the number of transferred genes in the number of total gene in each strain. The great amount of variability in the number of transferred genes between species is derived mainly from intra-phylum transfer events, on the other hands, the ratio of the inter-phylum transferred genes is shown consistently low across all strains.

The functional categories are according to the COG database [26]. (A) It shows the distribution of genes received from Chlamydia. (B) It shows the distribution of received genes from organisms other than Chlamydiae phylum. Genes from all functional categories (Cellular processes and signaling, Information storage and processing, and Metabolism) are subject to transfer. In contrast, in inter-phylum transfers, genes related to metabolism, and information storage and processing are assigned relatively high (31% and 49%, respectively), while only 16% of cellular processes and signaling genes are assigned.

As mentioned above, the C. felis and C. abortus genome displayed the highest ratio of HGT genes in all the species, with 30.1% and 27.4% of total genes, respectively. C. abortus is the most recently diverged species which mainly responsible for enzootic abortion in sheep and cattle [36]. There is a strong correlation between adaptation and HGT. It is known that bacteria can respond to SOS triggered by environmental stress and promote horizontal distribution of essential genes for survival [37]. In a recent study, 190 recombination events were observed in 12 C. trachomatis recombinants under antibiotic pressure [38]. It is also reported that mismatch repair gene deficient bacteria have significantly increased the rate of HGT and subsequent recombination of those genes[39]. In this way, HGT can be used to speed up the rates of adaptation in new environments [40], on the other hand, it is kept at a minimal level [41]. Therefore, high ratio of HGT genes of C. abortus can be explained as the result of ongoing adaptation to a new pathogenic lifestyle in placenta. In contrast, all of the C. trachomatis lineages show relatively low ratios, with an average of 9.08% of genes transferred. Possible explanation for this phenomenon is that C. trachomatis has very long evolutionary history since its divergence from the other Chlamydia approximately 6 million years ago [42], and unlike other Chlamydia that infect across multiple host species with histories of frequent host species jumps [14, 43], C. trachomatis has human beings as its exclusive natural host. Nevertheless, they are successfully adapted intracellular pathogens, which infections are among the most common of all human bacterial infections as it is a leading cause of sexually transmitted infection and blindness worldwide [44, 45]. In this point of view, it may be hypothesized that their stability as well-adapted pathogens in static environments for a long period have made them to keep gene transfers at a minimal level. In addition, the absence of C. trachomatis infecting phages detected may have impacts on the low ratio of HGT [11].

KEGG analysis of transferred gene families was performed to investigate pathways that might play important roles in Chlamydia and test whether transferred gene sets of each lineage are varied across functional pathways. In our analysis, variation in the number of transferred gene sets between lineages was quite similar across pathways, in most lineages, carbohydrate, nucleotide, and cofactor metabolism exchanged most abundantly (Fig 4). In previous study, frequent exchange of genes in carbohydrate transport and metabolism among animal associated organisms was observed [46]. However, we found that the effect of intra-phylum transfer and inter-phylum transfer on each pathway were different (Fig 5). For instance, genes associated in aminoacyl-tRNA biosynthesis pathway were horizontally acquired mainly from non-chlamydial species, and interestingly, HGT of the genes related to type III secretion system (T3SS) almost exclusively occurred at intra-phylum level (Fig 5). The varying effect on the functional categories and species suggest some pathways may accept the introducing of new genes from different phylum better than other pathways. Not all genes are permissive to interspecific gene transfer. Genes which encode proteins making up large complexes or genes whose products interact with other particles a lot display less preference towards HGT [47]. In addition, deleterious interaction between native and acquired proteins may be also important barriers [47, 48]. Barriers between certain species have been recognized as well for many bacterial and archaeal species [49].

The figure displays variation in the number of transferred gene sets across KEGG Pathways. The Boxplots represent the number of genes associated in corresponding KEGG Pathway transferred to each Chlamydia species. Each row denote 8 different Chlamydia species used in this study. The y-axis indicates the number of genes transferred counted.

The figure displays variation in the number of transferred gene sets between inter-phylum HGT and intra-phylum HGT. The Boxplots show the number of genes transferred to each Chlamydia species distributed across KEGG Pathways. Each row denotes inter- and intra-phylum HGT genes. The y-axis indicates the number of received genes to Chlamydia species counted.

HGT of virulence-related genes of Chlamydia

Bacterial evolution is largely dependent on the ability to adapt and colonize specific niches. Gene transfers of virulence-related genes may affect the pathogenesis of specific Chlamydia strains. Therefore, it is important to identify these events to expand our understanding of speciation event and strain emergence. Although Chlamydia have very conserved genomes as a result of genome reduction imposed by their intracellular lifestyle [42], there is a region of hotspot for genome variation which is termed as “Plasticity zone,” and the region encodes virulence factors including membrane attack complex/perforin protein (MACPF), cytotoxin, and genes related to important biosynthesis and salvage pathways [50]. Presence or absence of these genes in the region are known to confer different niche-specificity to the organisms. Based on our work, there appeared to be several events of HGT in the plasticity zone occurring within Chlamydia genus. Since Chlamydia interact frequently with membranes during their infection, the role of MACPF is important [51]. We found the gene transfer of MACPF from C. abortus S26/3 to C. felis Fe/C-56 (SV: 1.0) and to C.psittaci M56 (SV: 1.0) separately. The tryptophan biosynthesis pathway is necessary for survival of Chlamydia since host restricts chlamydial growth by degrading tryptophan as a defense mechanism [52]. Each Chlamydia species possesses different level of functional gene sets of tryptophan biosynthesis pathway [53]. Among the genes associated in this pathway, only TyrP gene encoding tyrosine/tryptophan transport protein was transferred within Chlamydia genus (from C. felis Fe/C-56 to C. caviae GPIC SV: 1.0). However, phylogenetic incongruence suggested that TrpC of C. pecorum E58, C. felis Fe/C-56, and C. caviae GPIC were might have been transferred from Coxiella burnetti dugway 5J108-111 strain, another obligate intracellular pathogen of humans and animals (SV: 1.0). TrpC encodes indole-3-glycerol phosphate synthase which is necessary in the fourth step of tryptophan biosynthesis pathway. It was previously proposed that Coxiella burnetti acquired trp operon from simkania negevensis, a bacterium belonging to the Chlamydiae phylum [54]. Putative multiple intra-genus gene transfers were also observed in adenosine deaminase (Add) associated in purine ribonucleotide biosynthesis pathway (S1 Fig), although no signs of HGT were detected in GuaAB. Presence of tox/adhesion may affect Chlamydia pathogenesis and host-range. These loci present only in C. trachomatis, C. muridarum, C. pecorum, C. psittaci, C. caviae, and C. felis species. To determine whether strains possessing the locus have gained the gene recently or whether these genes are lost by strains that do not is important [14]. According to our analysis, HGT of tox/adhesion had occurred from Escherichia coli and Citrobacter rodentinum to C. caviae GPIC (SV: 1.0).

Chlamydia displays a unique biphasic developmental cycle. At all stages of infection, interactions between the Chlamydia and its host are essential, and they translocate different types of virulence effector proteins into host cytoplasm which are used for manipulation of host cellular functions [55]. Like virulence genes in the plasticity zone, T3SS genes seemed to be mostly transferred within Chlamydia. Among the genes encoding structural components of the T3SS apparatus, there were evidences for intra-genus HGT in 5 genes (SctW, SctS, SctR, SctF, and SctP). Among the effector proteins that are used for manipulation of host cell immune response, EEA1, Cap1, CPAF, Tsp, and pGP6-D appear to have histories of HGT only with other Chlamydia.

HGT among Chlamydiaceae has been featured in many comparative genomics studies in recent few years [13, 14, 56]. We have discovered, using a tree reconciliation method, exchanges of virulence related genes are mainly occurred within Chlamydia genus. It suggests that intra-genus HGT may have been a major mechanism for the acquisition of determining factors of infection in Chlamydia. This discovery reflect that virulence related genes circulate among Chlamydia which may facilitate speciation event and new strain emergence. In microbial pathogens, virulence genes are particularly important determinants of host and tissue range [57], and transfer of those genes may provide a fitness benefit to the recipient. Gene acquisition from closely related species which have already adapted to meet the particular requirements of similar niche would confer even more advantages for adaptation. It will be informative to see if intra-genus HGT is a general mechanism for the acquisition of such factors also in other obligate intracellular pathogenesis. In this study, we uncovered several features of HGT acting on Chlamydia genome evolution and proposed an expansion of current understanding of Chlamydia ecology. More insights into HGT mechanism of Chlamydia will come from future laboratory experiments.


ORIGINAL RESEARCH article

  • 1 Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT, USA
  • 2 GenØk-Centre for Biosafety, The Science Park, Tromsø, Norway
  • 3 Department of Pharmacy, Faculty of Health Sciences, University of Tromsø, Tromsø, Norway

Experimental approaches to identify horizontal gene transfer (HGT) events of non-mobile DNA in bacteria have typically relied on detection of the initial transformants or their immediate offspring. However, rare HGT events occurring in large and structured populations are unlikely to be detected in a short time frame. Population genetic modeling of the growth dynamics of bacterial genotypes is therefore necessary to account for natural selection and genetic drift during the time lag and to predict realistic time frames for detection with a given sampling design. Here we draw on statistical approaches to population genetic theory to construct a cohesive probabilistic framework for investigation of HGT of exogenous DNA into bacteria. In particular, the stochastic timing of rare HGT events is accounted for. Integrating over all possible event timings, we provide an equation for the probability of detection, given that HGT actually occurred. Furthermore, we identify the key variables determining the probability of detecting HGT events in four different case scenarios that are representative of bacterial populations in various environments. Our theoretical analysis provides insight into the temporal aspects of dissemination of genetic material, such as antibiotic resistance genes or transgenes present in genetically modified organisms. Due to the long time scales involved and the exponential growth of bacteria with differing fitness, quantitative analyses incorporating bacterial generation time, and levels of selection, such as the one presented here, will be a necessary component of any future experimental design and analysis of HGT as it occurs in natural settings.


Horizontal Gene Transfers from Bacteria to Entamoeba Complex: A Strategy for Dating Events along Species Divergence

Horizontal gene transfer has proved to be relevant in eukaryotic evolution, as it has been found more often than expected and related to adaptation to certain niches. A relatively large list of laterally transferred genes has been proposed and evaluated for the parasite Entamoeba histolytica. The goals of this work were to elucidate the importance of lateral gene transfer along the evolutionary history of some members of the genus Entamoeba, through identifying donor groups and estimating the divergence time of some of these events. In order to estimate the divergence time of some of the horizontal gene transfer events, the dating of some Entamoeba species was necessary, following an indirect dating strategy based on the fossil record of plausible hosts. The divergence between E. histolytica and E. nuttallii probably occurred 5.93 million years ago (Mya) this lineage diverged from E. dispar 9.97 Mya, while the ancestor of the latter separated from E. invadens 68.18 Mya. We estimated times for 22 transferences the most recent occurred 31.45 Mya and the oldest 253.59 Mya. Indeed, the acquisition of genes through lateral transfer may have triggered a period of adaptive radiation, thus playing a major role in the evolution of the Entamoeba genus.

1. Introduction

Entamoeba genus is formed by morphologically similar amoebas most of them are intestinal parasites that can infect several hosts [1]. Entamoeba histolytica is one of the most important intestinal protozoan parasites in humans causing amoebic colitis they can also invade the liver causing amoebic liver abscess. It is estimated that this parasite causes 70,000 deaths worldwide each year [2]. Furthermore, the E. dispar species is morphologically almost identical to E. histolytica. However, until today, this has been considered as a commensal organism of the human gut. Nevertheless, E. dispar has been detected in patients with symptomatic amoebic colitis and also in the material of amoebic liver abscesses [3]. Very recently, a novel lineage of the Entamoeba genus has been detected in the intestine of rhesus macaques Macaca mulatta. Moreover, it has been proposed as a candidate to revive the name E. nuttallii for this lineage, particularly due to its genetic characteristics.

E. nuttallii infects captive and wild macaques and is capable of causing abscesses in hamster’s livers [4]. The species of Entamoeba invadens infects reptiles and causes colitis, liver abscesses, and, sometimes, acute death. It has been used as the main encystation model for Entamoeba species, since the in vitro culture of E. dispar can excyst producing the trophozoites and, thereafter, these trophozoites can undergo encystation in vitro. Phylogenetic reconstructions performed by Stensvold et al., in 2011, based on sequences of the gene for the small subunit of rRNA, clustered together E. histolytica and E. nuttallii and, basal to the latter node, branched those from E. dispar. SSURNA sequences from E. invadens branched together with those of E. ranarum. Both sequences formed the sister group of a node consisting of more than two-thirds of the Entamoeba species included in the analysis [1].

It is well known that horizontal gene transfer (HGT, or lateral gene transfer, LGT), of genetic material between unrelated individuals, has played a significant role in prokaryotic gene acquisition and genome evolution [5, 6]. Over the past few years, its importance in eukaryotic evolution has been reevaluated as it has been found in a higher frequency than expected and related with adaptation to certain niches [7]. Despite its presence in multicellular organisms such as Bdelloid rotifers [8], it is more likely to occur in unicellular eukaryotes [9]. Alsmark et al., in 2013, analyzing several genomes of protozoa found that Leishmania mayor, Entamoeba histolytica, and Trypanosoma brucei have the major percentage of genes acquired by lateral transfer with 0.96, 0.68, and 0.47, respectively [10]. Although the phylogenetic discrepancy has been the most reliable method to identify horizontally transferred genes, this latter procedure has been criticized, due to the following arguments: it is known that it might be modified due to methodological artifacts such as substitution saturation or long-branch attraction. Because there are only four bases that constitute nucleic acids, there is a relatively high probability that two nucleotide sequences might share the same bases in a random site by mere chance. This phenomenon is caused regularly by the high molecular substitution rate present in the locus, and its particular unwanted results are the loss of phylogenetic information and the possible high similarity between unrelated sequences. As a whole, this phenomenon is known as substitution saturation and is one of the main problems when analyzing molecular data [11]. HGT may be inferred amiss due to substitution saturation and it must be taken into account on every phylogenetic analysis.

The divergence time estimation for protozoan species is commonly a challenging endeavor, especially at the node calibration step. Even though some protozoan taxa might have fossil record, the most common strategy to calibrate date estimates is the indirect calibration based on animal or plant fossils with a specific underlying biological hypothesis [12]. In fact, the calibration of time estimates performed with protozoan fossil record has proven to be unpractical for extant taxa [13]. Although it has been suggested from gene comparisons that the divergence time between E. histolytica and E. dispar may have occurred some tenths of millions of years ago [14–16], until now no exhaustive research has been performed on the subject.

In the first annotation of the genome of E. histolytica HM1:IMSS reported by Loftus et al., a list of 96 HGT candidates was included, many from bacterial donors [17]. Later, in 2007, Clark et al. updated the analyses and sorted these 96 candidates into different categories according to their consistency in Bayesian and maximum likelihood distance bootstrap trees [18]. From the 96 original candidates, 41 remained strongly supported 27 turned to be more weakly supported than before the lateral gene transfer hypothesis of 14 candidates was weakened by increased taxonomic sampling 9 candidates were found in other microbial eukaryotes and, in the remaining 5 cases, vertical gene transfer is now the simplest explanation for the observed topology. Horizontal gene transfer remains the strongest hypothesis to explain 68 of the 96 original topologies [18]. But the number of LGT candidates can change according to phylogenetic methodology. For example, recently, in a study by Grant and Katz, in 2014, it is concluded that there are 116 genes of Entamoeba having a bacterial or archaeal origin [19]. In laboratory, Field et al. showed that the acetyl-CoA synthetase and the adh1 genes of E. histolytica share a common evolutionary history, more related to prokaryotes than other eukaryotes, and suggested that these genes were transferred early [20]. Hand in hand, Nixon et al. tried to demonstrate that genes for the anaerobic metabolism in Giardia and Entamoeba genera were obtained laterally while there was no enough data available to achieve that goal, the authors did reject the amitochondriate fossil and the hydrogen hypotheses to explain the resemblance of these genes to prokaryotic sequences [21].

The objective of this study is, primarily, to estimate the divergence time between E. histolytica, E. dispar, and E. invadens and then date HGT events of a representative genes, thereof, through the evolution of these species of Entamoeba. Representative gene was taken from the list of 68 candidates mentioned above and an additional analysis carried out to distinguish different levels of saturation rates in the DNA sequence, hypothesizing convergence or ancient HGT.

2. Methods

2.1. Gene Selection and Sequence Alignments

Accession numbers of the 68 well supported candidates were obtained from the list in Clark et al., 2007, and then searched in the Amoeba DB database, http://amoebadb.org/amoeba/ [22], in order to get the amino acid and coding sequences.

The following genes were selected to carry out the Entamoeba divergence time estimations: DNA-directed RNA polymerase I subunit RPA2 (EHI_186020), elongation factor 2 (EHI_189490), actin (EHI_131230), tubulin gamma chain (EHI_008240), and clathrin heavy chain (EHI_201510) since they are single-copy, housekeeping genes that were not obtained by HGT.

Each one of the HGT candidate amino acid sequences was used as a query against the NCBI Protein Reference Sequence Database (RefSeq) [23] with the BLASTp algorithm [24], using default parameters. The top 50 blast hits were collected for further analyses.

The homologous amino acid sequence from E. nuttallii was included in the analyses to calibrate the HGT divergence time estimates. Each E. histolytica HGT candidate was used as a query against the E. nuttallii P19 open reading frame translation database with the BLASTp algorithm. Only the top hit was collected and discarded, if the query coverage and/or identity were less than 60%.

In order to estimate the divergence time of housekeeping genes, sequences from E. dispar were downloaded and then corresponding orthologs were searched against the open reading frame translation database of E. histolytica, E. nuttallii, and E. invadens (available at http://amoebadb.org/common/downloads/) using the BLASTp algorithm, with default parameters. In addition, homologs of the former were looked for in the amino acid sequence database from Dictyostelium discoideum (available at http://dictybase.org/) [25] also using a BLASTp search. Only the top hit was collected and discarded if the query coverage or identity was less than 60%.

Each amoeba sequence was aligned with its amoebic ortholog (when a report existed in the Amoeba DB database) and with the prokaryotic sequences found by the BLAST search. In every study, amino acid sequences were aligned using the program Clustal W [26] and then their codon sequences according to the amino acid alignment with Biopython scripting [27]. Sequence alignments were inspected manually and edited to remove synapomorphies and codons with sequencing errors.

2.2. Substitution Saturation Test

Distance matrices were built for the nucleotide alignments. The nucleotide substitution model used was the Maximum Composite Likelihood, with a gamma distribution for the rate variation among sites. All codon positions were included and ambiguous positions were removed for each sequence pair. This analysis was conducted in MEGA software [28].

For each evolutionary distance matrix, sequences with low distance values (equal to or less than 0.1 standard deviations) according to the E. histolytica sequences were selected to make a shorter sequence alignment, including only closely related sequences, according to the distance matrices.

Substitution saturation indexes Iss. and Iss.c [12, 29] were calculated for each alignment, considering the three positions of each codon. Whenever a sequence alignment showed substantial saturation after the first analysis, the indexes were calculated again, though we remove the third position of each codon to avoid the possible substitution saturation due to the degeneracy of the genetic code. In these assays, statistical significance value was set at

. These tests were executed using the package DAMBE [30].

Tree topology examination was necessary to decide whether the alignment was phylogenetically informative for those alignments that showed substantial saturation when excluding the third position of each codon.

2.3. Phylogenetic Analyses

In order to evaluate the phylogenetic relevance of the shorter alignments that presented substantial saturation when removing the third position of each codon, the substitution saturation tests were introduced to the program MrBayes 3.2 [31]. The number of run MCMC generations was 500,000, excluding the third position of each codon every 125 generations a tree was sampled. Whenever a tree from the latter resulted in asymmetrical topology, the HGT candidate was discarded from the analysis.

In all cases the GTR+I+G nucleotide substitution model was employed, and 25% of tree samples were discarded as burn-in. A consensus tree was constructed from the remaining samples, and then it was inspected manually and edited using Dendroscope [32].

Constructions of consensus trees for donor group designation were made using two different approaches: maximum likelihood and Bayesian phylogenetics. 61 sequence alignments were introduced to the program jModeltest2 [33], in order to find the sequence substitution model that best fitted the observed alignment. Eleven substitution schemes were used, along with relative frequencies per base, proportion of invariable sites, and the variation of substitution rates along the alignment. The base tree to perform each analysis was built with the BioNJ algorithm and the NNI search algorithm. Finally the AICc criterion was used to select the best model for each alignment.

Maximum likelihood trees were built for each alignment by the program PhyML 3 [34]. In each case, the base tree was built with BioNJ and the best tree whether from NNI or SPR search algorithms was selected. One hundred bootstrap tests were executed per alignment. The same strategy was included in the input for the PhyML software for the candidates that passed the saturation tests, when ignoring the third position of each codon.

Similarly, the alignments that presented no substitution saturation in the first saturation analysis were used as input to construct trees by the program MrBayes [31]. 1,000,000 MCMC generations were run sampling a tree every 200 generations. Also, 1,000,000 MCMC generations were run excluding the third position of each codon for candidates that presented no substitution saturation in the second saturation analysis a tree was sampled every 200 generations. In both cases, the GTR+I+G substitution model was used, and a consensus tree was built after discarding 25% of the resulting topologies as burn-in. For each of the 61 candidates, the bootstrap values of the coincident nodes in the maximum likelihood trees were added manually to the resulting topology of the Bayesian phylogenetic analyses using the program Dendroscope (Supplementary Information, in Supplementary Material available online at http://dx.doi.org/10.1155/2016/3241027).

2.4. Bayesian Divergence Time Estimates

Two sets of estimations were performed: first, Entamoeba divergence time was calculated using a set of five housekeeping genes: DNA-directed RNA polymerase I subunit RPA2, elongation factor 2, actin, tubulin gamma chain, and clathrin heavy chain. Orthologs from E. histolytica, E. nuttallii, E. dispar, E. invadens, and D. discoideum were included in the dataset. The input tree used for the analysis was the following: ((((E. nuttallii, E. histolytica), E. dispar), E. invadens), D. discoideum).

Then, the HGT event dates were evaluated only with selected candidates, after considering three criteria: well supported branching in the Bayesian phylogenies, assigned donor group at least at the phylum level, and the presence of an ortholog in E. nuttallii. The dataset for each estimation included sequences contained in the alignments and used for the phylogenetic reconstructions from (i) E. histolytica, (ii) E. dispar and/or E. invadens, (iii) up to four randomly chosen sequences from the resulting sister group of Entamoeba cluster in the Bayesian phylogenies referred to as “a,” “b,” “c,” and “d,” (iv) up to three randomly chosen sequences from the resulting out-group in the Bayesian phylogenies referred to as “x,” “y,” and “z.” Moreover, the homologous sequence from E. nuttallii was aligned by-eye with the rest of the dataset. A common user-input tree would look like this: (((((E. nuttallii, E. histolytica), E. dispar), E. invadens), ((a, b),(c, d))), ((x, y), z)), even though the relationships within the sister group (a, b, c, and d) might vary.

The estimations were carried out using the programs Estbranches and Multidivtime [35, 36], following the step by step manual by Rutschmann [37]. The node between E. nuttallii and E. histolytica was used to calibrate the divergence estimations. Since E. nuttallii has only been isolated in rhesus macaques and E. histolytica has been found in feces from wild baboons (Papio sp.) [38, 39], we assumed that the E. nuttallii lineage diverged from E. histolytica at the same time that the primate lineages Macaca and Papio did. Paleontological evidence suggests that this divergence occurred after 8 Mya, but before 4 Mya [40, 41]. Consequently the node was calibrated between 5.5 and 6.5 Mya. For each alignment, the program Baseml [42] with the F84+G model was used to estimate nucleotide frequencies, transition/transversion rate ratio (parameter κ), and rate heterogeneity among sites (shape parameter α). Then, the maximum likelihood of the branch lengths of the tree and the variance-covariance matrix were estimated by the Estbranches program. Finally, a Bayes MCMC analysis was performed with the program Multidivtime, to approximate the posterior distributions of substitution rates and divergence times. A total of 5,100,000 generations were run, 100,000 were discarded as burn-in, and then a sample was taken every 100 generations.

For the Entamoeba divergence time, the five housekeeping genes were analyzed simultaneously, 5,100,000 generations were run, 100,000 were discarded as burn-in, and then a sample was taken every 100 generations. Time units were set to million years and referred to as “million years ago” (Mya). For the prior parameters, we selected 100 time units between the tip and the root of the tree, with a standard deviation of 50 time units, and an oldest time value of 300. For each candidate, the mean and standard deviation of prior distribution for the rate of molecular evolution at the in-group root node were set as the median of the evolution rates provided by Estbranches. The divergence time estimates were carried out in triplicate to confirm similar results of the analysis between repetitions. Results are showed as Mya ± the standard deviation provided by Multidivtime.

3. Results

3.1. Substitution Saturation Tests

Substitution saturation indexes Iss. and Iss.c [12, 28] were calculated for each alignment considering the first two or the three positions of each codon. The index Iss. is a measure of entropy of a given nucleotide sequence alignment. The index Iss.c is the measure of entropy of a simulated sequence alignment that shares the number of sequences and number of sites with the former but has a random distribution of nucleotide bases. Hence, if the Iss. value approaches that of Iss.c, it is a signal that the sequence alignment holds high substitution saturation. Both indexes were calculated for each shorter alignment. When using the three sites of each codon, 38 alignments displayed lower Iss. values than their respective Iss.c values these differences were statistically significant ( ), implying little saturation. In 14 cases, the differences between Iss. and Iss.c were not statistically significant. Other 10 candidates display the same behavior, and in the remaining 6 cases the value of Iss. index was higher than Iss.c and, also, differences were statistically significant. In the second essay, in which the first 38 sequences were not included, every third position of each codon was ignored, in order to avoid the possible substitution saturation observed due to the degeneracy of the genetic code. Altogether, 15 alignments resulted in a significantly lower Iss. index, and other 4 alignments had a significantly higher Iss. than their respective Iss.c. The remaining 11 alignments showed nonsignificant differences therefore tree topology was needed to evaluate their phylogenetic usefulness. To this end, 11 trees were built: 3 of them showed asymmetrical topology and 8 presented symmetrical topology. The respective HGT candidates from the 3 asymmetric trees, alongside those candidates from the 4 alignments whose Iss.c values were significantly higher in the second test, were permanently discarded from the research, since our results strongly denote that these alignments lack phylogenetic information.

3.2. Bayesian Phylogenetics and Putative Donor Groups

The assays were carried out with the lingering 61 candidates, using the complete coding sequence alignments. Phylogenetic analyses were made with the program MrBayes [31], 1,000,000 MCMC generations were run sampling a tree every 200 generations, using the first two or the three positions of each codon. When evaluating donor groups in the 38 trees constructed with complete codons, it was possible to locate a donor group at least at phylum level (Figure 1), as well as in 15 trees built, excluding the third position.

On the other hand, in three different cases, it was only possible to assign a donor group at the level of domain because the sister group of the Entamoeba cluster was formed by sequences that belonged to different phyla but from the same domain. A total of 61 consensus trees were built (Supplementary Information). Donor taxa could not be identified in the remaining five topologies, due to the different domains included and no apparent association with the amoebic genes. The domain Archaea was assigned to only four out of the 61 analyzed candidates, 3 of which belonged to the Euryarchaeota phylum and only one branched exclusively with sequences from Methanococcales. The bulk of the genes branched with bacterial sequences, from which 12 had no clear association with any phylum. Bacteroidetes was the most prevalent donor group with sixteen donated genes moreover, ten of them were probably transferred from the order Bacteroidales. In 6 trees the Entamoeba genes branched inside a larger cluster with high posterior probability values. Alternatively, in 9 other cases amoebic genes were separated from their basal group by a large evolutionary distance, but being branched with their sister group always showed high supporting values. The second most abundant donor group was the phylum Firmicutes, even though only in 4—out of the eleven candidates—a donor order could be designated. One gene branched strongly with sequences from Bacillales and the other 3 branched with Clostridiales. In most cases, the posterior probability of every node between the Entamoeba genes and their sister group was close to 1.0, with the exception of the type A flavoprotein (EHI_09671), which grouped with several bacterial clusters through a polytomy. The phylum Proteobacteria was designated as the donor group for a total of seven genes this was the phylum which presented the highest diversity of orders: Campylobacterales, Pseudomonadales, Burkholderiales, and Enterobacteriales. Despite the fact that just one gene belonged to each donor order, each one of them grouped with high posterior probability, with the exception of Fe-S cluster assembly protein (EHI_049620) whose posterior probability was 0.7 in the node between the amoebic cluster and sequences from Campylobacterales. Although one candidate branched poorly (posterior probability: 0.64) with sequences from Fusobacteria, it was not possible to determine a donor order. In up to 5 trees, the sequence of E. invadens did not branch with its Entamoeba ortholog but with prokaryotic sequences or as basal group instead.

3.3. Divergence Time Estimates

Entamoeba divergence time was calculated with the following set of five housekeeping genes: DNA-directed RNA polymerase I subunit RPA2, elongation factor 2, actin, tubulin gamma chain, and clathrin heavy chain. Orthologs from E. histolytica, E. nuttallii, E. dispar, E. invadens, and D. discoideum made up the dataset.

The median rate of molecular evolution among the five amoebic genes provided by Estbranches was 0.02364 substitutions per site per million years, which was then used as the mean and standard deviation of prior distribution for the rate of molecular evolution at the in-group root node for the Multidivtime program. Finally, the estimates for the split ages between these lineages were the following: split date between E. nuttallii and E. histolytica, 5.93 ± 0.28 Mya, between E. histolytica and E. dispar, 9.97 ± 1.37 Mya, and between E. histolytica and E. invadens, 68.18 ± 16.04 Mya (Figure 3).

Twenty-two Entamoeba candidates were selected after considering three criteria: well supported branching in the Bayesian phylogenies, assigned donor group at least at the phylum level, and the presence of an ortholog in E. nuttallii. The most recent transference was that of gene endo-1,4-beta-xylanase (EHI_096280) from Bacteroidetes dated 31.45 ± 15.69 Mya. The oldest transferences occurred 253.59 ± 28.91 Mya when the gene tartrate dehydrogenase (EHI_143560) was donated by Proteobacteria (Figure 2). The median of molecular evolution for this gene was 0.00089 substitutions per site per million years interestingly, this rate is smaller than the final rate of substitutions for the five amoebic housekeeping genes, which was 0.0014 substitutions per site per million years. This slow rate explains why such an old HGT event is still detectable and also why a donor group could still be determined for this gene. This is interesting because it is possible that some other HGT events may have been masked because of higher nucleotide substitution rates and the homogenization of the xenolog gene to the recipient genome.

without counterparts in the genome of E. invadens.

homologous genes in the genome of E. dispar.

Several overlapping transference dates were found, some of them from the same donor group: alpha-1,2-mannosidase (EHI_009520), mannose-1-phosphate guanylyltransferase (EHI_052810), and fructokinase (EHI_054510) from Bacteroidetes ranging from 55.53 Mya to 77.8715 Mya, nicotinate-phosphoribosyltransferase (EHI_023260) and hypothetical protein (EHI_072640) from Bacteroidales ranging from 94.98 Mya to 164.16 Mya, and Fe-S cluster assembly protein NifU (EHI_049620) and metallo-beta-lactamase family protein (EHI_068560) from Proteobacteria ranging from 119.89 Mya to 176.9304 Mya. Gene synteny in the genome of E. histolytica and functional group information were still necessary to define simultaneous horizontal gene transfer events.

4. Discussion

In this study the substitution saturation of the well supported HGT gene candidates from the genome of E. histolytica was verified and assigned a putative donor group for each candidate through phylogenetic reconstruction. In addition, a first approach into the divergence time estimation of some species of Entamoeba through indirect node calibration was presented, using the fossil record of their feasible hosts. Finally the gene transfer events of some HGT candidates were dated, revealing gene losses, postdivergence transfers, and a simultaneous transfer of two genes. The BLAST search results were able to provide a glimpse of the analysis outcome, since the top hits that resulted in the highest

-values ( -13 and -16 for EHI_085050 and EHI_156240, resp.) belonged to candidates discarded because of substitution saturation. Moreover, for the 3 candidates whose top hits were sequences from Archaea, the latter domain was the putative donor group after inspecting the Bayesian phylogenies. It is interesting that most of the Entamoeba HGT candidate genes have no or few paralogs in the genome of the different species of Entamoeba included in the analyses, while some others had at least 3 paralogs in each genome. The former diversification may be result of neutral evolution in the case of the gene that encodes the metallo-beta-lactamase superfamily protein (EHI_115720), considering that beta-lactam antibiotics induce bacterial cell wall degradation and therefore are innocuous to Entamoeba species [43]. On the other hand, two of the candidates with the largest gene families, hypothetical protein and aldehyde-alcohol dehydrogenase 2 (EHI_104900 and EHI_160940, resp.), were discarded after the substitution saturation tests. It is likely that these gene families are result of an ancient HGT and have lost phylogenetic information, due to mutational saturation or they have been acquired through vertical descent and they are similar to bacterial sequences, as a result of the same mechanism.

The procedures here presented managed to find donor groups at the order level, including the following: Bacteroidales, Clostridiales, Spirochaetales, Campylobacterales, Burkholderiales, Bacillales, Flavobacteriales, Methanococcales, and Enterobacteriales. Most of the donor taxa can be found in the gut of vertebrates, it is well known that the three bacterial phyla are major part of the gut microbiota, but other less abundant groups have donated genetic material to Entamoeba species such as anaerobic Archaea. Although most members of the Entamoeba genus are parasitic or commensal organisms, lineages of free living Entamoeba like E. ecuadoriensis have been found [1], and some of these xenolog genes have been acquired from free living donor groups.

The Bacteroidetes phylum monopolizes lateral gene donations to the Entamoeba species included in this analysis, and the second most abundant group is the phylum Firmicutes and then Proteobacteria (Figure 1). These results are in contrast with those reported previously [44], in which they found 16 candidates closely related to Proteobacteria nevertheless we found only 8. Likewise, we found no traces of HGT from Actinobacteria. These differences may result of the increased sampling due to the growth of biological databases and the substitution saturation tests. Consistent results are the frequency of LGT from Bacteroidetes, Spirochaetes, and Fusobacteria. In fact, the phylum Bacteroidetes has been found as potential donor to other horizontally transferred genes in different organisms, such as Ciliates [45] and Dinoflagellates [46], thus confirming the promiscuity of this taxon.

Several studies have highlighted the ecological relationship between E. histolytica and bacteria, specifically during pathogenesis [47, 48]. This study supports the importance of these associations as they can provide evolutionary innovations to the genus, and although no virulence factors have been transferred, antibiotic resistance genes are among the 61 candidates. In fact, the gene 5-nitroimidazole antibiotic resistance protein (EHI_068430) has been transferred from Bacteroidales. As most HGT events were millions of years ago, it is unlikely that these genes have functioned as acquired adaptations against antibiotics. These genes might have had other functions such as secondary metabolite degradation or no function at all, before the antibiotics were a selective pressure in the human gut.

Although the alignment for protein serine acetyltransferase (EHI_202040) resulted in little saturation while excluding the third position of each codon and its phylogeny showed a symmetric topology, it is very unlikely that an ancestor of the Entamoeba genus had obtained this from halophilic archaea and probably other bacteria group can be the donor.

Since estimating the age of the gene transfer events was one of the main objectives of this study, it was necessary to approximate the divergence times of the species of Entamoeba. To accomplish this aim, the identification of E. nuttallii as a separate lineage provided crucial information. The fact that E. nuttallii has only been isolated from rhesus macaques and E. histolytica has been found in feces from wild baboons [38, 39] led to the assumption that the E. nuttallii and E. histolytica lineages were separated simultaneously with their hosts at some time between 4 and 8 Mya according to the fossil record, although it has been assumed that this interval is narrower [49]. The results from the amoebic species split date calculations might be underestimated by the fact that only one node was calibrated, as there is no direct fossil record of species of Entamoeba. Although other authors have made studies regarding the age of the Amoebozoa phylum as a whole using animal and plant fossils, it was not possible to use their results because of differences in time scale and classification [13]. Some divergence time estimates of HGT candidates have overlapping standard deviations this is particularly interesting when the donor groups coincide, because these genes could have been transferred at the same time. To determine if these genes were transferred simultaneously, some characteristics were taken into account: gene transfer age, donor group, metabolic context, and location in the genome. It has been suggested that functionally related genes might be located closely especially in prokaryotic genomes [50], and it should be expected that a simultaneous horizontal gene transfer would result in one or more xenologs positioned near one to another and functionally related. Two genes shared most of these attributes: the genes for the mannose-1-phosphate guanylyltransferase (EHI_052810) and the fructokinase (EHI_054510) were donated by Bacteroidales, probably between 60 and 70 million years in the past. Both genes are involved in fructose, mannose, amino sugar, and nucleotide sugar metabolism.

The dating of some transfers explained why certain genes are absent in some of the genomes of the amoebic species, included in this analysis (Figure 3). The transfer of the endo-1,4-beta-xylanase (EHI_096280) occurring 31.45 ± 15.69 Mya is in fact more recent than the divergence between the lineage of E. invadens and the ancestor of the other species of Entamoeba (68.18 ± 16.04 Mya) thus this gene was never present in the genome of the immediate ancestor of E. invadens. Conversely, the coding sequence for the 5-nitroimidazole-resistance protein (EHI_068430), which was transferred earlier (99.82 ± 29.94 Mya), was lost afterwards by E. invadens. The same conclusion could be applied to the gene coding for the hypothetic protein (EHI_198610), which was obtained 162.08 ± 27.07 Mya from Proteobacteria, which is now absent in the genome of E. dispar.

E. histolytica remains as one of the protists with the highest number of laterally transferred genes from bacterial origin in their genomes along with Trichomonas vaginalis and Giardia lamblia [9] or along with Leishmania mayor and Trypanosoma brucei [19]. This large uptake of bacterial genes, which in general took place relatively early in the evolutionary history of the Entamoeba genus, may have functioned as a trigger for adaptive evolution. The latter assertion may be palpable in the case of the genes coding for the acetyl-CoA synthetase and the adh1 but other genes gained through HGT, whose functions are unknown or obscured by biased annotations, may have been also important in the evolution of these organisms. The ancestor of the genus Entamoeba, which in our point of view, might as well be the ancestor of Endolimax, equipped with this newly acquired genes, might have tried exploring new ecosystems and forms of life and eventually settled in the gut of vertebrates.

Competing Interests

The authors declare that they have no competing interests.

Acknowledgments

The authors thank the partial support by Grant no. 79220 from the National Council of Science and Technology (CONACyT). Thanks are due to Valeria Zermeño, Lilia González-Ceron, and Rocío Incera for proofreading and translation review.

Supplementary Materials

The supplementary information consists of image files showing the consensus trees built for this research. Files are named with the AmoebaDB accession number of the horizontal gene transfer can-didate being tested. Files with the “_tre_ed.png” suffix are the trees built to evaluate the phylogenetic relevance of shorter alignments, these trees were built with the MrBayes 3.2 software. The posterior probability is shown for each node and the bar shows the expected number of substitutions. The re-maining files show the consensus trees generated for the designations of donor groups. These are the consensus topologies returned by the program MrBayes 3.2, showing in each node, its posterior prob-ability. Whenever a tree built with Phyml showed the same node, the bootstrap value was added man-ually. The bar shows the number of expected substitutions. Image files were generated and edited using the program Dendroscope.

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Copyright

Copyright © 2016 Miguel Romero et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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