AEM Accepts, published online ahead of print on 30 August 2013 Appl. Environ. Microbiol. doi:10.1128/AEM.01455-13 Copyright © 2013, American Society for Microbiology. All Rights Reserved.
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From green to red: horizontal gene transfer of phycoerythrin gene cluster between
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Planktothrix strains
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Running title: Transfer of phycoerythrin gene cluster
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Ave Tooming-Klunderud1#, Hanne Sogge1,2, Trine Ballestad Rounge1,3, Alexander J.
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Nederbragt1, Karin Lagesen1, Gernot Glöckner4,5, Paul Hayes6, Thomas Rohrlack7,8, Kjetill S.
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Jakobsen1,2#
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(1) University of Oslo, Centre for Ecological and Evolutionary Synthesis (CEES),
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Department of Biosciences, P.O.Box 1066, 0316 Oslo, Norway
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(2) University of Oslo, Microbial Evolution Research Group (MERG), Department of
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Biosciences, P.O.Box, 1066, 0316 Oslo, Norway
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(3) Cancer Registry of Norway, P.O. box 5313 Majorstuen, N-0304 Oslo, Norway
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(4) Institute for Biochemistry I, Medical Faculty, University of Cologne, Joseph-Stelzmann-
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Straße 52; D-50931 Köln, Germany
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(5) Leibniz-Institute of Freshwater Ecology and Inland Fisheries, IGB, Müggelseedamm 301;
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D-12587 Berlin, Germany
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(6) Faculty of Science, University of Portsmouth, St Michael’s Building, White Swan Road,
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Portsmouth, PO1 2DT, United Kingdom
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(7) NIVA, Norwegian Institute for Water Research, 0411 Oslo, Norway
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(8) Norwegian University of Life Sciences, Department of Plant and Environmental Sciences,
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P.O.Box 5003, 1432 Ås, Norway
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#
Corresponding authors:
1
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Kjetill S. Jakobsen:
[email protected]
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Ave Tooming-Klunderud:
[email protected]
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Keywords: Cyanobacteria, Planktothrix, horizontal gene transfer, phycoerythrin gene cluster,
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chemotype, recombination, phycobilisome
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Abstract:
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Horizontal gene transfer is common in cyanobacteria and transfer of large gene clusters may
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lead to acquisition of new functions and conceivably niche adaption. In the present study, we
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demonstrate that horizontal gene transfer between closely related Planktothrix strains can
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explain the production of the same oligopeptide isoforms by strains of different color.
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Comparison of the genomes of eight Planktothrix strains revealed that strains producing the
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same oligopeptide isoforms are closely related, regardless of color. We have investigated
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genes involved in the synthesis of the photosynthetic pigments phycocyanin and
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phycoerythrin, which are responsible for green and red appearance, respectively. Sequence
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comparisons suggest the transfer of a functional phycoerythrin gene cluster generating a red
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phenotype in a strain that is otherwise more closely related to green strains. Our data show
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that the insertion of a DNA fragment containing the 19.7 kb phycoerythrin gene cluster has
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been facilitated by homologous recombination, also replacing a region of the phycocyanin
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operon. These findings demonstrate that large DNA fragments spanning entire functional
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gene clusters can be effectively transferred between closely related cyanobacterial strains and
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result in a changed phenotype. Further, the results shed new light on the discussion of the role
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of horizontal gene transfer in the sporadic distribution of large gene clusters in cyanobacteria,
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as well as the appearance of red and green pigmented strains.
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Introduction
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Horizontal gene transfer (HGT), the exchange of genetic information between two
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organisms that do not share a recent ancestor–descendant relationship, is now recognized as a
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major force shaping the evolutionary history of prokaryotes (e.g. [1-4]). HGT is considered to
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be common in cyanobacteria [5]. Through the availability of bacterial genome sequences it
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has become clear that HGT can occur throughout the genome, and that a substantial fraction
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of genes have been horizontally transferred [5,6]. The quantity of genetic material that can be
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horizontally transferred may range from small gene fragments (e.g. [7-9]) to fragments
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spanning complete genes (e.g. [10-12]) and whole operons encoding complex biochemical
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pathways (e.g. [13-15]). As even the transfer of a single or a few genes can give recipient
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organisms the opportunity to implement a new function and exploit new ecological niches,
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HGT contributes to the rapid creation of biological novelty that otherwise, through mutations
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and gene duplications, might have taken millions of years to appear.
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According to Andam and co-workers [1], HGT is the norm and not the exception,
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while others call the transfer of genes between bacteria ‘both rare and promiscuous’[4].
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Successful HGT depends on transfer of genetic material to the cell (via transformation,
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conjugation, transduction or gene transfer agents), survival of the DNA in the cell, integration
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of foreign DNA via recombination and finally fixation of the integrated DNA in the
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population (involving for example selection). Since the rate of recombination decreases with
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increased sequence dissimilarity [16,17], HGT events are more common among close
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relatives, as shown by a recent analysis of 657 sequenced prokaryotic genomes [18].
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For fixation of a newly transferred gene in the population, it should provide a relevant
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function and this function must operate within the native machinery of the host cell. Since
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bacterial genomes are subject to deletional bias [19], genes that do not contribute to fitness of
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the organism will eventually be removed from the genome. Integration of new genes into
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existing cellular networks can be facilitated by acquisition of an operon containing all genes
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and regulatory regions required for function [20]. For single-gene acquisitions, the fate of new
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genes depends largely upon the existing genes in its new host. Experimental studies have
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shown that most HGT events are deleterious [21,22]. However, rare HGT events and
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mutations can be selected for under particular conditions and are thus contribute to bacterial
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adaptation and evolution [23-25].
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Horizontal gene transfer events have also been demonstrated for the filamentous
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cyanobacterium Planktothrix (e.g., [26-29]), which occurs in deep and stratified lakes in
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temperate regions of the northern hemisphere. Traditionally, Planktothrix isolated from
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different lakes have been classified into species according to morphological characteristics,
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such as cell dimension and pigmentation. Following the first description of the genus
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Planktothrix including 14 distinct species by Anagnostidis and Komárek [30], the number of
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different species has been heavily disputed. Studies based on molecular data like sequences of
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gas vesicle genes and 16S rRNA have suggested that whole Planktothrix genus is
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monospecific [31,32] while Suda and co-workers [33] described four Planktothrix species
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based on several genetic and phenotypic properties.
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Planktothrix strains isolated from Norwegian lakes and classified as distinct species at
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Algal Culture Collection of the Norwegian Institute for Water Research cannot be separated
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by 16S rRNA. Recently, Rohrlack and co-workers [34,35] reported that strains of
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Planktothrix showing >99% 16S rRNA gene sequence similarity may produce distinct
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cellular patterns of oligopeptides, bioactive secondary metabolites synthesized mostly by non-
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ribosomal peptide synthetases. Using the oligopeptide profiles produced by each strain as
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markers, they grouped strains into distinct chemotypes (Cht). Based on field studies of the 4
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Norwegian Lake Steinsfjorden, four coexisting Planktothrix chemotypes differing
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considerably in seasonal dynamics, depth distribution and participation in loss processes,
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were identified [34]. Since the production of oligopeptides is facilitated by several large and
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independently evolving operons [36,37], strains associated with a distinct chemotype are
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assumed to be more closely related. This hypothesis is also supported by data showing that
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Planktothrix strains associated with same chemotype generally have same color, either red or
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green [35]. However, in Lake Steinsfjorden, one chemotype was shown to comprise both red
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and green strains [34,35]. The red and green appearance of Planktothrix strains is associated
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with the content of accessory light harvesting pigments, the phycobiliproteins, involved in the
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photoautotrophic machinery. Phycobilisomes, the macromolecular complexes formed from
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phycobiliproteins, have an allophycocyanin core that links to the photosystems, and
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peripheral light harvesting rods that comprise either phycocyanin or phycocyanin and
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phycoerythrin (for review, see e.g. [38]). Phycocyanin, common to all cyanobacteria, imparts
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a green appearance to the cell and absorbs red light (620-630 nm). Phycoerythrin absorbs
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green light (560-570 nm) and imparts a dominant red color when present. The co-existence of
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red and green strains within the same chemotype can be explained by acquisition or loss of
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genes coding for phycoerythrin as suggested earlier for Synechococcus and other
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picocyanobacteria [39-41].
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The aim of this study was to investigate the genome arrangements leading to the co-
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occurrence of red and green strains within the same oligopeptide chemotype. For that
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purpose, the genomes of eight different Planktothrix strains classified as four different species
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were sequenced, four red and four green strains, including a red and two green strains from
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the same chemotype. We address the following questions: (1) how similar are the genomes of
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closely related Planktothrix strains and is there any evidence for genetic substructuring
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according to color or chemotype; (2) is the structure and chromosomal location of genes 5
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encoding phycocyanin and phycoerythrin pigments the same in all strains; (3) in the light of
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results from the two first questions, can the co-occurrence of red and green strains within the
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same chemotype be explained by altered phycoerythrin genes and is this because of a) an
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acquisition of phycoerythrin gene cluster by the red strain, or b) mutations leading to non-
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functional phycoerythrin genes in two green strains.
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Our results show that all eight Planktothrix genomes are highly similar, and that
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strains associated with the same chemotype are the most closely related, regardless of color.
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Furthermore, we reveal that a red strain from a chemotype dominated by green strains has
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acquired the 19.7 kb phycoerythrin gene cluster. Our data indicate that the DNA fragment
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containing phycoerythrin operon originated from a strain associated with a “red” chemotype.
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Materials and Methods
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Planktothrix strains and DNA isolation
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Eight Planktothrix strains isolated from lakes Steinsfjorden and Kolbotnvatnet
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(Norway) have been investigated. All strains have been kept in continuous, non-axenic
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cultures at the Algal Culture Collection of the Norwegian Institute for Water Research
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(NIVA), in Z8 medium and light at a photon flux density of 10 μmol m-2s-1, and a light-dark
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cycle of 12:12 hours. Prior to genomic DNA isolation, cells were centrifuged and re-
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suspended in TE buffer. DNA was extracted by the following procedure: cells were treated
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with lysozyme (final concentration 15 mg/ml), followed by RNaseA and Proteinase K, (5
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mg/ml, 1 % LDS) treatment. Samples were then incubated at 60°C (shaking at 300 rpm) for
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60 min. In cases where the solution did not clear after 60 minutes, the incubation time was
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prolonged with additional Proteinase K. Subsequently, 1 volume phenol: chloroform:
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isoamylalcohol [25:24:1 (v/v)]) was added. The solution was mixed by inversion at 37°C for 6
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30 min to remove pigments and proteins. After centrifugation, the upper layer was treated
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twice with 1 volume chloroform–isoamyl alcohol [24:1 (v/v)]. DNA was precipitated using
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0.1 volume 3 M sodium acetate and 2.5 volume ice-cold 96 % ethanol on ice for 1 hour. The
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DNA pellet was washed twice with ice-cold 70 % ethanol, dried at room temperature and
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dissolved in Tris-HCl buffer (pH 8.0). All DNA samples were purified using Amicon Ultra-
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0.5mL 50K Centrifugal columns to ensure high-quality DNA for paired-end library
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preparation using the 454 Life Sciences protocols. DNA was concentrated using
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manufacture’s instructions and washed twice using Tris-HCl buffer, pH 8.0.
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Sequencing
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Seven out of eight Planktothrix genomes were sequenced using 454 pyrosequencing at
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the Norwegian Sequencing Centre (http://www.sequencing.uio.no/). Strain NIVA-CYA 34
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was initially sequenced using Sanger sequencing at Max Planck Institute for Chemical
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Ecology. DNA sample of NIVA-CYA 34 was amplified using the REPLI-g® kit (Qiagen).
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The resulting DNA was randomly sheared and the fragment size range from 2500 to 3000 kb
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was selected for cloning into pUC18 standard vectors. The resulting clones were sequenced
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from both ends with the standard sequencing primers on an ABI 3700 machine generating 20
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066 sequencing reads comprising 16 Mb. An additional 454 shotgun library was prepared and
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sequenced at the Norwegian Sequencing Centre to ensure satisfactory quality of the NIVA-
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CYA 34 genome assembly. For the remaining seven strains, both shotgun and paired-end
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libraries were prepared and sequenced to 23 – 41x coverage (see Supplementary Table 1 for
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information about libraries and number of reads/bases sequenced for each strain).
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Assembly and annotation
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The newbler program (gsAssembler, Roche-454, Branford, USA) was used to
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assemble the 454 reads into scaffolds and contigs (newbler version used for assembly of each
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strain together with assembly statistics are shown in Supplementary Table 1). Since all strains
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had been cultivated non-axenically, reads from co-cultured bacteria were present in the
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dataset. To decrease the chance of co-assembling these contaminating reads with the genome
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of the strain of interest, stringent overlap settings with a minimum of 98 % overlap identity
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and a minimum of 60 bp overlap length were used. However, the assemblies of most strains
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still contained some short scaffolds with low average read depth (below 5-10 x) and/or GC
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percentages that diverged from high read depth scaffolds. These scaffolds were considered to
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be derived from co-cultured bacteria present in the sample used for DNA extraction [42]. The
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low read depth scaffolds were compared to the non-redundant NCBI protein database using
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BLASTX, and all non-cyanobacterial matching scaffolds were removed before annotation.
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Assembly of the NIVA-CYA 34 genome was done using both the Sanger and 454-
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reads. Newbler was given a trimming file (-vt option) to remove pUC18 plasmid vector
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sequences from the Sanger reads. The ‘-stopjoin’ and ‘-repfill’ options were used for
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assembly. One low-coverage non-cyanobacterial scaffold was removed from the newbler
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assembly. Four of the unscaffolded contigs were identified as containing cyanobacterial
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sequences; these were added to the scaffolds before annotation.
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According to classification of Genomes Sequence Standards [43], we consider the
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assemblies as improved high-quality drafts. Annotation of all genome sequences was
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performed using the U.S. Department of Energy (DOE) Joint Genome Institute (JGI)
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integrated microbial genomes database and comparative analysis system (IMG) [44].
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Comparison of genomes
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The IMG system was used for pair wise comparison of genomes and calculation of
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Pearson correlation coefficients of COG (Cluster of Orthologous Groups) profiles.
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Homologous genes were defined as genes having a minimum of 80% sequence identity and
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identified using BLASTP.
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Hierarchical clustering by COG profiles was performed by IMG system using the tool
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Cluster (http://www.falw.vu/~huik/cluster.htm). For construction of the pairwise hierarchical
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tree, a function profile vector (gene counts per COG) was generated for each genome. The
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distance metrics between these profile vectors was calculated by means of un-centered
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correlation. Pairwise single-linkage clustering was performed, grouping the two closest
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profile vectors first to form a group, then grouping the next pair of closest groups or vectors
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until all genomes were incorporated into the hierarchical tree.
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Phylogenetic analyses of genomes were performed using a set of core genes. Core
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genes were defined as genes present in all genomes and having a minimum of 90% sequence
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identity, resulting in data set of 3 690 genes. The final data set (after removing 100% identical
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genes in all genomes together with transposases, oligopeptide synthetases, retron type reverse
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transcriptases, phage-associated proteins and proteins shorter than 50 aa) contained 2 914
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genes. Ten sub-sets of genes for generating phylogenies were created by random sampling of
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20 genes from the core gene set (2914 genes) repeated 10 times using R (R development core
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team 2012. R: A language and environment for statistical computing, reference index version
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2.10.1. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3-900051-07-0, URL
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http://www.R-project.org). Sequences were aligned using Mega 5 software [45] and
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concatenated for each of the ten data sets. List of genes for each data set is shown in
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Supplementary Table 2. Maximum likelihood (ML) analyses were carried out using RAxML
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[46] with 1000 bootstrapped resamplings with GTRCAT model. The resulting individual
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phylogenetic trees are shown in Fig. S1. Finally, the aligned sequences of all 200 genes were
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concatenated
resulting
in
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546
bp
long
alignment
(available
through
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http://dx.doi.org/10.6084/m9.figshare.719100) and Maximum likelihood (ML) analyses were
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carried out using RAxML [46] with 1000 bootstrapped resamplings with GTRCAT model.
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Analyses of phycobilisome genes
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All gene sequences analysed (phycoerythrin, phycocyanin and flanking genes) were
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downloaded from IMG. Sequences were aligned using Mega 5 software [45]. Nucleotide
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diversity was analyzed using the computer program DNA Sequence Polymorphism (DnaSP)
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[47]. Maximum likelihood (ML) analyses of cpc genes were carried out using RAxML [46]
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with 1000 bootstrapped resamplings. GTRCAT was determined to be the best evolutionary
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model using ModelTest [48].
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Detection of recombination events
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Recombination events were detected by visual analyses of informative sites (variable
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sites where each variant occurs in at least two sequences) as described by Rudi and co-
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workers [7]. In order to detect the recombination breakpoints, concatenated sequences of
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cpcBA (reverse-complement) and CHAP domain genes were analyzed using the RDP 4
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software [49]. Sequences from strains NIVA-CYA 406 and NIVA-CYA 15 were discarded as
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these are identical with sequences from strains NIVA-CYA 98 and NIVA-CYA 34,
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respectively. Recombination signals were accepted if at least three different methods detected
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statistically significant (P
