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Environmental Microbiology (2014)
doi:10.1111/1462-2920.12541
Genome of the halotolerant green alga Picochlorum
sp. reveals strategies for thriving under fluctuating
environmental conditions
Fatima Foflonker,1 Dana C. Price,2 Huan Qiu,2
Brian Palenik,3 Shuyi Wang3 and
Debashish Bhattacharya2,4*
1
Departments of Biochemistry and Microbiology,
2
Ecology, Evolution and Natural Resources and
4
Institute of Marine and Coastal Science, Rutgers
University, New Brunswick, NJ 08901, USA.
3
Scripps Institution of Oceanography, University of
California, San Diego, La Jolla, CA 92093, USA.
Summary
An expected outcome of climate change is intensification of the global water cycle, which magnifies
surface water fluxes, and consequently alters salinity
patterns. It is therefore important to understand the
adaptations and limits of microalgae to survive
changing salinities. To this end, we sequenced the
13.5 Mbp genome of the halotolerant green alga
Picochlorum SENEW3 (SE3) that was isolated from a
brackish water pond subject to large seasonal salinity
fluctuations. Picochlorum SE3 encodes 7367 genes,
making it one of the smallest and most gene dense
eukaryotic genomes known. Comparison with the
pico-prasinophyte Ostreococcus tauri, a species with
a limited range of salt tolerance, reveals the enrichment of transporters putatively involved in the salt
stress response in Picochlorum SE3. Analysis of cultures and the protein complement highlight the metabolic flexibility of Picochlorum SE3 that encodes
genes involved in urea metabolism, acetate assimilation and fermentation, acetoin production and
glucose uptake, many of which form functional gene
clusters. Twenty-four cases of horizontal gene transfer from bacterial sources were found in Picochlorum
SE3 with these genes involved in stress adaptation
including osmolyte production and growth promotion. Our results identify Picochlorum SE3 as a model
for understanding microalgal adaptation to stressful,
fluctuating environments.
Received 21 March, 2014; accepted 15 June, 2014. *For correspondence. E-mail [email protected]; Tel. (+1) 848
932 6218; Fax (+1) 732 932 8746.
© 2014 Society for Applied Microbiology and John Wiley & Sons Ltd
Introduction
Climate change is expected to intensify changes in the
water cycle at the rate of a 7% increase in intensity per
degree Kelvin of warming (Held and Soden, 2006).
Increased evaporation and precipitation caused by
warmer waters and the ability of warmer air to retain more
moisture are the major driving forces in this cycle (Yu,
2011). The predicted magnification of surface water fluxes
from evaporation and precipitation closely correlate to
changing salinity patterns (Durack et al., 2000). Salt concentration in water also affects its density and thereby the
vertical mixing patterns of water (Schmitt, 2008). In addition to the challenge of adapting to salinity variation, phytoplankton communities will also face differences in
nutrient and light availability due to changes in turbulence
(Lauria et al., 1999).
Picochlorum sp. strain SENEW3 (here SE3) is potentially a highly useful model to understand the effects of
salinity stress on microalgae because of its wide range of
salt tolerance. Picochlorum SE3 is a tiny, coccoid (i.e.
non-motile) green alga (Trebouxiophyceae, Chlorophyta)
that is 2–3 μm in cell diameter. It was isolated from a small
permanent pond in the San Elijo Lagoon system in San
Diego County, California. The pond is subject to large
seasonal fluctuations in salinity (~1.7–108.3) via evaporation, precipitation and tidal influx of seawater. Laboratory studies have confirmed the wide salt tolerance range
of Picochlorum SE3 that extends from at least salinity 3.5
to 105 (Wang et al., 2014). Picochlorum SE3 tolerates
temperatures above 16°C but exhibits a reduced growth
rate above 32°C. Carotenoid production and significant
lipid body accumulation under nitrogen limitation suggests
that Picochlorum SE3 may be a promising species for
commercial algal biomass applications (Wang et al.,
2014).
Here, we report the genome sequence of the natural
isolate, Picochlorum SE3. We analyse possible mechanisms of adaptation to salt stress through comparisons
of metabolite transporters, identify genome regions of
functionally clustered genes and investigate the role of
horizontal gene transfer (HGT) in potentially enhancing
the stress tolerance capabilities of this free-living green
alga.
2
F. Foflonker et al.
Genome size
0.31
Picochlorum SE3
13.3 Mb
7367
Chlorella variabilis
46 Mb
9791
Coccomyxa subellipsoidea
49 Mb
9851
138 Mb
14566
121 Mb
15143
13 Mb
7805
12 Mb
8116
15 Mb
7847
Micromonas strain RCC299
21 Mb
10056
Micromonas pusilla CCMP1545
22 Mb
10575
0.09
0.18
0.04
0.25
0.07
0.23
Gene number
Volvox carteri
0.07
Chlamydomonas reinhardtii
Ostreococcus lucimarinus
Ostreococcus tauri
Bathycoccus prasinos
Results
Genome features and phylogeny
A total of 830 Mbp of paired-end (2 × 150 bp) Illumina
sequence data were generated from Picochlorum SE3
using the Illumina MiSeq Personal Genome Sequencer
of which 98.3% of reads matched to the assembled
contigs. The assembly comprised 1266 contigs with a
N50 = 124.5 Kbp and an average genome coverage of
62× (52× median coverage). A total of 2.07 Gbp of RNAseq data from this species were used to train the ab initio
gene predictor AUGUSTUS (Stanke and Morgenstern,
2005), resulting in high-quality gene models for downstream analysis. Our data show that the 13.5 Mbp nuclear
genome encodes 7367 protein-coding genes, with 5795
introns, a G + C content of 46.1% and a gene density
of 1.8 Kbp/gene. These values are comparable with
Ostreococcus tauri (i.e. 12.6 Mbp genome; 1.6 Kbp/
gene). Of the 458 shared core genes compiled in the
Core Eukaryotic Genes Mapping Approach (http://
korflab.ucdavis.edu/datasets/cegma/) database, 454
(99%) are present in the Picochlorum SE3 draft genome
suggesting a complete assembly. Putative annotations of
all Picochlorum SE3-predicted proteins, their contig of
origin, top database hit and other attributes are presented
in Supporting Information Table S1. A maximum likelihood
tree inferred from a concatenated alignment of 480 102
amino acids unambiguously places Picochlorum SE3 as
sister to Chlorella variabilis within Chlorophyta (100%
bootstrap support) and reveals that its average protein
evolutionary divergence rate (i.e. branch length) is
elevated since its split from C. variablilis (Fig. 1). Nested
within two other Trebouxiophyceae that have much larger
genomes (e.g. 46 Mbp, 49 Mbp), the relatively small
Fig. 1. Phylogenetic analysis of Picochlorum
SE3. Multi-gene maximum likelihood tree of
10 green algae inferred from an alignment of
480 102 amino acids. The genome size and
protein-coding gene number are shown for
each taxon.
genome of Picochlorum SE3 likely indicates genome
reduction in this taxon (Fig. 1). Streamlined genomes are
characteristics of fast-evolving species that live in specialized ecological niches or in extreme environments (e.g.
Matsuzaki et al., 2004; Palenik et al., 2007; Qiu et al.,
2013; Schönknecht et al., 2013).
Clusters of functionally related genes
Recent evidence suggests that eukaryotic gene order
may not be random, but rather some groups of functionally related genes form gene clusters (Blumenthal, 2004).
Here we identified gene clusters involved in a shared
metabolic pathway, while allowing for the presence of
intervening genes with unknown or unrelated functions. A
total of 5795 Picochlorum SE3 proteins were mapped to
482 pathways annotated in the Unipathway database.
This analysis resulted in a list of 633 proteins with BLASTP
hits to Unipathway that were manually examined for evidence of functional clustering.
One interesting cluster we uncovered contains
genes involved in urea uptake and degradation
[Picochlorum_contig_54.g177.t1 – Picochlorum_contig
_54.g180.t1 (Supporting Information Table S1)]. In contrast to the major route of urea degradation to carbon
dioxide and ammonia by the nickel-containing urease
present in green algae such as Ostreococcus and
Micromonas species, as well as land plants (Qiu et al.,
2013), Picochlorum SE3 and some green algae
and fungi, including Chlamydomonas reinhardtii and
Chlorella vulgaris, use a two-step process involving an
adenosine triphosphate (ATP)-dependent urea carboxylase and allophanate hydrolase/amidase (Thompson and
Muenster, 1971; Hodson et al., 1975). In green algae,
© 2014 Society for Applied Microbiology and John Wiley & Sons Ltd, Environmental Microbiology
Genome analysis of Picochlorum SE3
3
contig 54.g180.t1
contig 54.g177.t1
contig 54.g178.t1
contig 54.g179.t1
Allophanate
hydrolase,
partial
Urea cycle
Extracellular
urea
High
affinity
urea : Na+
transporter
Urea
Urea-1-carboxylate
6.3.4.6
Urea carboxylase
3.5.1.54
Amidase/
Allophanate
hydrolase
CO2
3.5.1.5
Urease
Fig. 2. Analysis of the urea gene cluster. Urea functional gene cluster in Picochlorum SE3 includes genes encoding a high-affinity urea
transporter and two (urea carboxylase and allophanate hydrolase) enzymes involved in urea degradation instead of a single urease enzyme.
these two enzymes are encoded by genes in close proximity and are 673 bp apart in Picochlorum SE3 (Fig. 2;
Strope et al., 2011). We did not detect any genes that
encode subunits of the nickel-dependent urease complex
in the Picochlorum SE3 genome. In this alga, the twogene cluster for urea degradation is flanked by a highaffinity urea:Na+ symporter similar to DUR3 in Arabidopsis
thaliana (AtDUR3) that is involved in import of urea during
nitrogen starvation. This is the sole urea transporter identified in the Picochlorum SE3 genome. The clustering of
these genes (not the case in Ostreococcus) is not surprising because exogenous urea is an important nitrogen
source to support amino acid biosynthesis in phytoplankton (Solomon et al., 2010). Consistent with these
results, the major nitrate assimilation cluster found in
Ostreococcus (Palenik et al., 2007) is also largely conserved in Picochlorum SE3 (see Supporting Information
Table S2).
Another pathway that shows evidence of clustering is
the acetate assimilation pathway that leads to acetylcoenzyme A biosynthesis. Two genes encoding acetate
kinase and phosphate acetyltransferase are located in
close proximity (Picochlorum_contig_155.g703.t1 and
Picochlorum_contig_155.g705.t1). These genes are also
present in C. reinhardtii but not in Ostreococcus and function in acetate assimilation or in the reverse direction,
generate ATP through fermentation (Ingram-Smith et al.,
2006). This evidence suggests that Picochlorum SE3 may
be able to utilize acetate as a carbon source, enhancing
its metabolic flexibility, and may be capable of energy
generation through fermentation during anoxic conditions.
Also noteworthy is a cluster of two genes encoding alphaacetolactate decarboxylase and acetolactate synthase
(Picochlorum_contig_58.g128.t1 and Picochlorum_contig
_58.g129.t1) that are involved in the conversion of
pyruvate to acetoin as part of (R,R)-butane-2,3-diol
biosynthesis pathway. These genes have homologues in
C. variabilis and appear to have a bacterial origin, but are
absent in other Viridiplantae, including Ostreococcus. In
some bacteria, these two genes form an operon (alsSD
operon in Bacillus subtilis) and are involved in the fermentative production of acetoin, a neutral four-carbon molecule that serves to maintain cellular pH levels, regulate
nicotinamide adenine dinucleotide (NAD+/NADH) ratios,
and acts as a carbon storage molecule that can be
excreted or reutilized during stationary phase (Grundy
et al., 1993; Renna et al., 1993; Xiao and Xu, 2007).
Acetolactate synthase also catalyzes the first step in the
biosynthesis of the branched chain amino acids leucine,
isoleucine and valine (Xiao and Xu, 2007). The genome of
Picochlorum SE3 does not however encode the gene
alsR, the transcription factor essential for the transcription
of the B. subtilis alsSD operon, nor does it include (R,R)butanediol dehydrogenase, the enzyme responsible for
the reduction of acetoin to 2,3-butanediol, a common fermentation product of industrial importance in bacteria
(Nicholson, 2008; Frädrich et al., 2012). Other clusters of
functionally related gene are listed in Table 1.
We also used the program C-HUNTER (Yi et al., 2007) to
identify functional clusters based on Gene Ontology (GO)
terms. Several clusters of five to eight genes were identified that are involved in the following functions: response
to abiotic stimulus, transferase activity, hydrolase activity
and nucleotide binding. Clusters of three genes or less
included those involved in biotin synthesis, the citric acid
cycle, inorganic phosphate transport, histone proteins and
response to abscisic acid, a stress indicator (results not
shown). These results provide evidence for the clustering
of functionally related genes in Picochlorum SE3 and
suggest that some of the clusters we identified likely play
© 2014 Society for Applied Microbiology and John Wiley & Sons Ltd, Environmental Microbiology
4
F. Foflonker et al.
Table 1. Physically linked genes in shared pathways in Picochlorum SE3.
Cluster
Genes
Annotation
Contig size/gene number and pathway
1
contig_54.g177.t1
contig_54.g178.t1
contig_54.g179.t1
contig_54.g180.t1
contig_155.g703.t1
contig_155.g705.t1
contig_58.g128.t1
contig_58.g129.t1
contig_100.g576.t1
contig_100.g589.t1
contig_124.g760.t1
contig_124.g761.t1
contig_290.g866.t1
contig_290.g867.t1
contig_58.g172.t1
contig_58.g174.t1
Urea/Na+ symporter
Urea amidolyase
Allophanate hydrolase
Urea carboxylase
Phosphate acetyltransferase
Acetate kinase
Alpha-acetolactate decarboxylase
Acetolactate synthase
Aldehyde dehydrogenase YcbD
Alcohol dehydrogenase
GTP pyrophosphokinase
Penta-phosphate guanosine-3′-pyrophosphohydrolase
Bifunctional dethiobiotin synthetase
8-amino-7-oxononanoate synthase
D-3-phosphoglycerate dehydrogenase
Phosphoserine phosphatase
292 031 bp/159 genes, urea degradation
2
3
4
5
6
7
a role in environmental adaptation. Finally, we note that
due to the fragmented nature of the genome assembly
and the limited number of genes that have pathway annotations, the gene clusters we have identified likely represent an underestimate of the true number. A more
complete assembly is likely to physically connect additional genes with shared pathways functions into single
contigs.
Transporter analysis
The number and type of metabolite transporters were
compared between Picochlorum SE3 and O. tauri, a
species with limited halotolerance. We identified putative
membrane transport proteins and classified them
based on sequence similarity (BLASTP, E-value cut-off
≤ 1 × 10−10) using the Transporter Classification Database
(TCDB; http://www.tcdb.org/) (Saier et al., 2006). This
resulted in the identification of 719 putative membrane
transport proteins in Picochlorum SE3 that were categorized into 124 families, representing 9.8% of the genome.
Fewer transport proteins were identified in O. tauri, 660
proteins in 112 families, comprising 8.3% of the genome.
The most common transporter proteins in Picochlorum
SE3 belong to the ATP-binding cassette (ABC) superfamily (60 proteins), followed by the nuclear mRNA exporter
(mRNA-E) family (39) and the peroxisomal protein
importer family (37) (see Fig. 3).
Picochlorum SE3 and O. tauri share a set of 165 distinct transporter classification (TC) numbers, making up a
core set of transporter functions. TC number distinguishes
transport proteins at the level of subfamily and substrate
range. Picochlorum SE3 encodes 533 shared proteins,
whereas O. tauri encodes 508, indicating gene expansion
in the Picochlorum SE3 genome. Putative functional
annotations of the overrepresented proteins in the
Picochlorum SE3 genome include the mitochondrial
49 683 bp /31 genes, acetyl-coenzyme A biosynthesis
304 360 bp/164 genes
(R,R)-butane-2,3-diol biosynthesis
89 890 bp/57 genes, ethanol degradation
195 646 bp/100 genes, ppGpp biosynthesis
21 912 bp/12 genes, biotin biosynthesis
biotin biosynthesis
304 360 bp/164 genes, L-serine biosynthesis
protein translocase family (3.A.8.1.1) and the sodium/
hydrogen (AtNHX8) exchanger (2.A.36.7.3). Picochlorum
SE3 had 175 transport proteins with 35 distinct TC
numbers, not present in O. tauri. The most abundant
transporters found only in Picochlorum SE3 include
general amino acid transporters (AAP3) (2.A.18.2.3)
and the multidrug resistance protein 4 involved in
efflux of drugs and signalling molecules (3.A.1.201.7).
Protein families overrepresented in O. tauri include the
resistance-nodulation-cell division (RND) superfamily
(2.A.6) that functions in drug and lipid efflux, the voltagegated ion channel superfamily (1.A.1) and the potassium
transport-related proteins. These data show generally that
both Picochlorum SE3 and Ostreococcus contain a large
number of membrane transporters, many of which are
shared and some of which are unique to each taxon. The
latter likely reflect adaptations to their different environments, although this needs to be tested using functional
analyses.
Nonetheless, it is likely that some of the transport proteins contribute to the broad range of salt tolerance in
Picochlorum SE3 (Fig. 4). For example, this alga encodes
six copies of the atNHX8/salt overly sensitive 1 (SOS1)
gene (compared with one in O. tauri), a plasma membrane Na+/H+ antiporter involved in the extrusion of
sodium from the cell that is essential for salt tolerance (Wu
et al., 1996; Qiu et al., 2002). Sodium extrusion via the
Na+/H+ antiporter is coupled to an H+ gradient formed by
an H+-ATPase. Picochlorum SE3 also contains one gene
annotated as a subunit of Na+/K+-ATPase, involved in the
ATP-dependent active extrusion of sodium from the cell,
which is particularly useful under high pH conditions when
the export of sodium via the Na+/H+ antiporter is rendered
ineffective (Taylor et al., 2012). Thought initially to
be exclusive to animals, homologues of the Na+/K+ATPase have been reported in some algae including
Dunaliella salina, Heterosigma akashiwo and Porphyra
© 2014 Society for Applied Microbiology and John Wiley & Sons Ltd, Environmental Microbiology
Genome analysis of Picochlorum SE3
5
Frequency
0
10
20
30
40
50
60
The ATP-binding Cassette (ABC) Superfamily
The Nuclear mRNA Exporter (mRNA-E) Family
The Peroxisomal Protein Importer (PPI) Family
The Gap Junction-forming Connexin (Connexin) Family
The Endoplasmic Reticular Retrotranslocon (ER-RT) Family
The Major Facilitator Superfamily (MFS)
The Mitochondrial Carrier (MC) Family
The Plant Photosystem I Supercomplex (PSI) Family
The Drug/Metabolite Transporter (DMT) Superfamily
The H+- or Na+-translocating F-type, V-type and A-type ATPase (F-ATPase)
Transporter Family
The Chloroplast Envelope Protein Translocase (CEPT or Tic-Toc)
The H+ or Na+-translocating NADH Dehydrogenase (NDH) Family
The General Secretory Pathway (Sec) Family
The P-type ATPase (P-ATPase) Superfamily
The Ankyrin (Ankyrin) Family
The Proposed Fatty Acid Group Translocation (FAT) Family
The Mitochondrial Protein Translocase (MPT) Family
The Nuclear t-RNA Exporter (t-Exporter) Family
The Amino Acid/Auxin Permease (AAAP) Family
The Autotransporter-1 (AT-1) Family
The Multidrug/Oligosaccharidyl-lipid/Polysaccharide (MOP) Flippase
The G-protein-coupled receptor (GPCR) Family
The Unknown BART Superfamily-1 (UBS1) Family
The Zinc (Zn2+)-Iron (Fe2+) Permease (ZIP) Family
The Putative Tripartite Zn2 Transporter (TZT) Family
The Monovalent Cation:Proton Antiporter-1 (CPA1) Family
Picochlorum SE3
The Transient Receptor Potential Ca2+ Channel (TRP-CC) Family
The α-Latrotoxin (Latrotoxin) Family
Ostreococcus tauri
The Voltage-gated Ion Channel (VIC) Superfamily Total
The Voltage-gated K+ Channel β-subunit (Kvβ) Family
The DedA or YdjX-Z (DedA) Family
Fig. 3. Analysis of metabolite transporters in Picochlorum SE3 showing frequency of transporters per transporter family in Picochlorum SE3
and O. tauri. Minimum frequency cut-off = 6 for Picochlorum SE3.
yezoensis (Katz and Pick, 2001; Shono et al., 2001;
Kishimoto et al., 2013). Also present is NHX1, a Na+
(K+)/H+ antiporter localized in the vacuolar membrane that
is involved in the vacuolar accumulation of K+ for osmotic
adjustment (Barragán et al., 2012). NHX1, similar to
SOS1, is also driven by a proton gradient formed by
vacuolar H+-ATPase and H+ translocating inorganic
pyrophosphatase (Blumwald, 2000).
Other proteins found in Picochlorum SE3 but not in
O. tauri include three copies of the mechanosensitive
channel 1 (MSC1), likely located in the chloroplast. MSCs
are present in most prokaryotes and sense changes in the
membrane, often involved in sensing osmotic stress
(Nakayama et al., 2007). Picochlorum SE3 also has two
inward rectifying potassium channels. Maintaining a high
intracellular potassium level is one strategy used to
reduce the toxic effects of Na+ on cells (Amtmann and
Beilby, 2010). Picochlorum SE3 contains several more
amino acid permeases than O. tauri. These are primarily
the general AAP3 involved in the transport of neutral and
acidic amino acids. Amino acids and other nitrogencontaining compounds accumulate in plant cells as
osmolytes in response to salt stress (Parida and Das,
2005).
Other environmental adaptations include genes
involved in metal uptake. Picochlorum SE3 has several
additional transporters for zinc and other heavy metals
including iron and magnesium in the zinc (Zn2+)-iron (Fe2+)
permease family (2.A.5) and the putative tripartite Zn2
transporter family (9.B.10), the CorA metal ion transporter
© 2014 Society for Applied Microbiology and John Wiley & Sons Ltd, Environmental Microbiology
6
F. Foflonker et al.
SOS1
IRK
+Na ase
ATP
Amino
H+
K+
+
Na
AAP3
Na
ATP
AD
Fig. 4. Putative distribution and functions of
metabolite transports in the Picochlorum SE3
cell, showing transporters involved in the salt
stress response.
H+
H+
ATP ase
+
P+P i
ATP
Acids
AD
P+P
i
Na+/K+
Anions
MSC1
NHX1
2Pi
H+
H+
H+
C
ATPase
h lo
r op
Va
c
l ast
uo
le
Channel Facilitated
PPi
H+pyrophosphatase
H+ATPase
ATP ADP+Pi
Transporter
Cell Membrane
Cations Anions Amino
Acids
family (1.A.35); there are 23 genes in these three categories in Picochlorum SE3 compared with 10 in O. tauri.
Picochlorum SE3 has an abundance of ABC transporters,
many of which are multidrug resistance proteins. In terms
of metabolic flexibility, Picochlorum SE3 contains seven
hexose transporters including one that is homologous to
the Hup1 glucose transporter in Chlorella kessleri (Sauer
et al., 1990), consistent with the reported mixotrophic
capabilities of Picochlorum strain S1b in the presence of
glucose (Chen et al., 2012).
A
Given the discovery of putative glucose transporters in the
Picochlorum SE3 genome, we tested the impact of
glucose on cell growth. For this experiment, we raised
Picochlorum SE3 under different levels of salt stress,
added glucose to the medium and then measured the
growth rate (Fig. 5). This analysis reveals suppressed
growth rates and longer acclimation periods between 1.4
and 1.6 M NaCl with no growth being observed at 1.8 M
B
1.00E+08
1.00E+08
0.4 M NaCl
1.4 M NaCl
1.5 M NaCl
1.6 M NaCl
1.00E+07
1.00E+07
Cells ml–1
Cells ml–1
Growth rates in the presence of organic carbon sources
1.00E+06
1.00E+05
0 g/l glucose
1 g/l glucose
5 g/l glucose
10 g/l glucose
30 g/l glucose
1.00E+06
1.00E+05
1.00E+04
1.00E+04
0
50
100
150
200
Hours
250
300
350
0
50
100
150
200
250
300
350
400
450
500
Hours
Fig. 5. Mixotrophic growth of Picochlorum SE3.
(A) Growth under salt stress and (B) growth under 1.5 M NaCl salt stress, with the addition of different amounts of glucose. The inoculation
density was 1 × 105 cells ml−1. The error bars represent standard error of (A) duplicate and (B) triplicate cultures, except for the 0.4 M NaCl
result in (A) that represents a single culture.
© 2014 Society for Applied Microbiology and John Wiley & Sons Ltd, Environmental Microbiology
Genome analysis of Picochlorum SE3
NaCl; i.e. under the conditions used in the laboratory (see
Methods). Mixotrophic growth with the addition of glucose
under 1.5 M NaCl stress showed increased maximum cell
density with increasing glucose concentrations. No evidence of heterotrophic growth was observed with the
addition of glucose in the dark. Mixotrophic growth on
glucose has also been shown to increase growth rates in
Picochlorum S1b and C. vulgaris (Liang et al., 2009;
Chen et al., 2012). Unlike Picochlorum SE3 and
C. vulgaris, C. reinhardtii lacks hexose transporters
(Doebbe et al., 2007). These results are consistent with
our comparative genomic analysis, suggesting that
glucose may be taken up and metabolized by the cell,
thereby partially mitigating the effects of high salt stress.
Preliminary culture experiments in which acetate was
added to the medium show that Picochlorum SE3, similar
to C. reinhardtii, can grow mixotrophically in the presence
of this organic carbon source (F. Foflonker and D.
Bhattacharya, unpubl. data).
HGT analysis
We investigated the extent of HGT in the Picochlorum
SE3 genome using an automated phylogenomic pipeline
(Price et al., 2012). Here we focused on inter-domain
HGT because of the greater sampling depth of prokaryote
genomes and their large phylogenetic distance from
Picochlorum SE3 that provides a clear signal of foreign
gene acquisition. We generated 5871 maximum likelihood
[randomized axelerated maximum likelihood (RAXML);
Stamatakis et al., 2008] protein trees (containing > 3
phyla) using the Picochlorum SE3-predicted proteins as
the query. These trees were sorted using the program
PHYLOSORT (Moustafa and Bhattacharya, 2008) to search
for cases of monophyly with Bacteria, Archaea or Vira.
Phylogenies of interest were then manually examined to
identify candidates for HGT with > 60% bootstrap support
for the sister-group relationship between Picochlorum
SE3 and prokaryotes or trees that included only
prokaryotes with the Picochlorum SE3 protein (Fig. 6).
Given the rampant history of HGT among prokaryotes and
the relatively rich green algal/plant database, we presumed that the absence of eukaryotic proteins in the latter
trees (except for Picochlorum SE3) was sufficient evidence to implicate HGT.
Using this approach, we found 24 instances of HGT
unique to Picochlorum SE3 (i.e. not found in any other
sequenced green alga), of prokaryotic, mainly bacterial
origin (Table 2). This can be compared with approximately
74 genes of putative prokaryotic origin in the Bathycoccus
prasinos genome (Moreau et al., 2012). Fifteen of the 24
HGT candidates in Picochlorum SE3 are expressed and
have at least 20× average expressed sequence tag (EST)
coverage (Table 2) under standard culture conditions (see
7
Materials and Methods). Interestingly, many of the 24
genes in Picochlorum SE3 have functions potentially
related to stress adaptation and the majority is related to
carbohydrate metabolism. Most are glycosyltransferases,
glycoside hydrolases and polysaccharide lyases that
function in polysaccharide synthesis and degradation into
its sugar moieties. The gain of polysaccharide-degrading
enzymes, including a cellulase, may function in cell wall
recycling, remodelling or may be excreted from the cell
and function in nutrient acquisition, thereby providing
metabolic flexibility (Gruber and Seidl-Seiboth, 2012).
Other genes may be involved in cell wall synthesis; for
example, the guanosine diphosphate (GDP)-mannose to
GDP fucose pathway; both genes in this pathway (GDPmannose-4,6,-dehydratase and GDP-L-fucose synthase)
appear to have a bacterial origin. In Arabidopsis, GDPmannose-4,6-dehydratase mutants are deficient in
L-fucose, a precursor of the cell wall constituent
rhamnose, leading to weakened cell walls resulting in
stunted growth (Reiter et al., 1993; Bonin et al., 1997).
Also noteworthy are several genes of suspected HGT
origin involved in carbohydrate modifications in the cell
wall in the green algae C. variabilis and Ostreococcus
lucimarinus (Palenik et al., 2007; Blanc et al., 2012).
Several glycosyltransferases of foreign origin involved in
cell surface protein modifications were identified in the
cyanobacterium Synechococcus and hypothesized to
function as a predation avoidance mechanism (Palenik
et al., 2003). Glycosylation was also noted as an enriched
category of genes of both prokaryotic and nonViridiplantae eukaryotic origin in B. prasinos (Moreau
et al., 2012). Taken together, these data suggests that
HGT in green algae has repeatedly conferred genes
involved in cell wall and cell surface modifications.
Several of the HGT-derived genes may contribute to the
broad salt tolerance properties of Picochlorum SE3
(Fig. 7). A gene-encoding glycerol dehydrogenase is
involved in the synthesis of glycerol, a common osmolyte
involved in osmoregulation during salt stress. Proteases,
including a glutamyl endopeptidase known to be induced
during salt stress, breaks peptide bonds thereby freeing
amino acids like glutamate, which may act as an osmolyte
(Gabdrakhmanova et al., 2005).
Other HGT-derived genes potentially involved in stress
adaptation include those involved in sulfate scavenging,
growth-promoting hormone synthesis, cell cycle control and DNA methylation. An arylsulfatase gene in
Picochlorum SE3 is potentially involved in sulfur
mineralization by the hydrolysis of sulfate esters to sulfate
(de Hostos et al., 1988). Whereas most plants and algae
increase inorganic sulfur uptake in response to sulfur
limitation stress typical of freshwater environments,
periplasmic arylsulfatases provide the means to utilize
organic sulfur as an alternative, and are induced in
© 2014 Society for Applied Microbiology and John Wiley & Sons Ltd, Environmental Microbiology
100
86
53
Firmicutes
Rhodophyta-Boldia sp. contig 22757 1
Fungi
FibrobacteresAcidobacteria-Terriglobus saanensis SP1PR4 gi320108709
Firmicutes-Staphylococcus hominis SK119 gi228475763
Tenericutes-Mycoplasma penetrans HF 2 gi26554143
100
Tenericutes-Mycoplasma iowae 695 gi350546566
Firmicutes-Paenibacillus mucilaginosus KNP414 gi337748795
Cyanobacteria-Nostoc punctiforme PCC 73102 gi186682481
Viridiplantae-Chlorella NC64A jgi35601
Viridiplantae-Oryza sativa Japonica Group gi115464407
Viridiplantae-Arabidopsis lyrata subsp. lyrata gi297806095
78
Viridiplantae-Arabidopsis lyrata jgi486945
99 Viridiplantae-Arabidopsis thaliana gi15240950
100
Viridiplantae-Arabidopsis thaliana gi15234062
Viridiplantae-Glycine max gi356506590
61 100 88 Viridiplantae-Populus trichocarpa gi224079117
99 Viridiplantae-Ricinus communis gi255563082
75
Viridiplantae-Physcomitrella patens subsp patens gi168008475
Viridiplantae-Physcomitrella patens subsp. patens gi168021407
85
Viridiplantae-Chlamydomonas reinhardtii gi159491138
Rhodophyta-Porphyridium purureum 2012 contig 479.1
100
Chloroflexi-Ktedonobacter racemifer DSM 44963 gi298251494
Fibrobacteres/Acidobacteria-Granulicella tundricola gi322433283
Planctomycetes-Planctomyces maris DSM 8797 gi149178136
76
Alveolata-Cryptosporidium muris RN66 gi209876424
100 Alveolata-Cryptosporidium hominis TU502 gi67623969
Alveolata-Cryptosporidium parvum Iowa II gi66363022
Amoebozoa-Acanthamoeba castellanii tbACL00000790 3
Amoebozoa-Hartmannella vermiformis tbHVL00001944 3
72
89
Actinobacteria
Metazoa-Nasonia vitripennis gi156538983
97 Excavata-Leishmania infantum JPCM5 gi146099506
Excavata-Leishmania major strain Friedlin gi157876137
Excavata-Leishmania braziliensis MHOM BR 75 M2904 gi154336655
Actinobacteria
100
Cyanobacteria
100
91
100
Planctomycetes
Bacteroidetes/Chlorobi-Chitinophaga pinensis DSM 2588 gi256420798
Bacteroidetes/Chlorobi-Flavobacterium johnsoniae UW101 gi146301575
Chlamydiae/Verrucomicrobia-Methylacidiphilum infernorum V4 gi189220208
Chlamydiae/Verrucomicrobia-Chthoniobacter flavus Ellin428 gi196234738
Chlamydiae/Verrucomicrobia-Pedosphaera parvula Ellin514 gi223936081
Cyanobacteria-Gloeobacter violaceus PCC 7421 gi37521626
Nitrospirae-Candidatus Nitrospira defluvii gi302037007
100 Cyanobacteria-Cylindrospermopsis raciborskii CS 505 gi282900698
100
Cyanobacteria-Raphidiopsis brookii D9 gi282897903
Cyanobacteria-Anabaena variabilis ATCC 29413 gi75910313
51
100
70
60
100
Proteobacteria
Francisella spp.
Picochlorum-contig-43-g357-t1
0.5 substitutions/site
Other Bacteria/
Archaea
ChlamydiaeVerrucomicrobia-Parachlamydia acanthamoebae UV7 gi338174716
ChlamydiaeVerrucomicrobia-Parachlamydia acanthamoebae str. Hall’s coccus gi282892060
ChlamydiaeVerrucomicrobia-Waddlia chondrophila WSU 86 1044 gi297621853
100
100
97
80
100
8057
57
86
62
65
81
74
100
Cyanobacteria-Synechococcus sp CC9311 gi113954751
Cyanobacteria-Synechococcus sp. WH 7805 gi88809700
Chloroflexi-Ktedonobacter racemifer DSM 44963 gi298248939
Actinobacteria-Frankia sp. EuI1c gi312197329
Archaea-Methanosarcina acetivorans C2A gi20089483
100
Archaea-Methanosarcina barkeri str Fusaro gi73668953
65
rettgeri DSM 1131 gi291327076
99 100 Proteobacteria-Providencia
Proteobacteria-Providencia stuartii ATCC 25827 gi183598941
100
Proteobacteria-Dickeya dadantii Ech586 gi271501529
84
Proteobacteria-Edwardsiella tarda ATCC 23685 gi294634417
Proteobacteria-Desulfovibrio magneticus RS 1 gi239907262
100
100
94
97
100
95
60
51
100
99
100
100
0.2 substitutions/site
78
Picochlorum-contig-15-g22-t1
Proteobacteria-Pseudoalteromonas atlantica T6c gi109896461
Proteobacteria-Shewanella amazonensis SB2B gi119773445
Proteobacteria-Pseudoalteromonas atlantica T6c gi109896448
Bacteroidetes/Chlorobi-Bacteroides sp. D2 gi315921059
Proteobacteria-Pseudoalteromonas tunicata D2 gi88857326
75 Proteobacteria-Stenotrophomonas maltophilia JV3 gi344207627
Proteobacteria-Stenotrophomonas maltophilia K279a gi190574625
99
100 Proteobacteria-Stenotrophomonas sp. SKA14 gi254522131
100
100 Proteobacteria-Xanthomonas fuscans subsp. aurantifolii str ICPB 11122 gi294625907
Proteobacteria-Xanthomonas fuscans subsp. aurantifolii str ICPB 10535 gi294664809
100
100 Proteobacteria-Xanthomonas campestris pv campestris str 8004 gi66769470
65
100 Proteobacteria-Stigmatella aurantiaca DW4 3 1 gi310822571
Proteobacteria-Stigmatella aurantiaca DW4 3 1 gi115373389
69
Fibrobacteres/Acidobacteria-Granulicella tundricola gi322433051
Fibrobacteres/Acidobacteria-Acidobacterium capsulatum ATCC 51196 gi225871709
Fibrobacteres/Acidobacteria-Terriglobus
saanensis SP1PR4 gi320106524
81 100
Fibrobacteres/Acidobacteria-Granulicella tundricola gi322435793
Fibrobacteres/Acidobacteria-Candidatus Koribacter versatilis Ellin345 gi94967545
63
Bacteroidetes/Chlorobi-Bacteroides sp. 1 1 6 gi253571344
Thermotogae-Kosmotoga olearia TBF 19 5 1 gi239616888
72
Actinobacteria-Streptomyces flavogriseus ATCC 33331 gi357409612
Actinobacteria-Streptomyces sp. SPB78 gi302519724
Stramenopiles-Phytophthora capsici jgi82743
Actinobacteria-Streptomyces violaceusniger Tu 4113 gi345011319
100 Actinobacteria-Streptomyces griseoflavus Tu4000 gi302562622
92
Actinobacteria-Streptomyces zinciresistens K42 gi345852298
90 99
Actinobacteria-Streptomyces pristinaespiralis ATCC 25486 gi297191008
Actinobacteria-Stackebrandtia nassauensis DSM 44728 gi291300803
91
Actinobacteria-Amycolatopsis mediterranei U32 gi300790149
54
100
Actinobacteria-Streptomyces
sp. AA4 gi302526472
100
99
Actinobacteria-Actinosynnema mirum DSM 43827 gi256376007
Actinobacteria-Janibacter sp. HTCC2649 gi84496412
Actinobacteria-Rubrobacter xylanophilus DSM 9941 gi108805388
Chloroflexi-Ktedonobacter racemifer DSM 44963 gi298247695
100
Chloroflexi-Ktedonobacter racemifer DSM 44963 gi298241261
Firmicutes-Clostridium spiroforme DSM 1552 gi169349600
67
Fibrobacteres/Acidobacteria-Candidatus Solibacter usitatus Ellin6076 gi116624232
89
FibrobacteresAcidobacteria-Terriglobus saanensis SP1PR4 gi320105657
Firmicutes-Mahella australiensis 50 1 BON gi332981218
Bacteroidetes/Chlorobi-Odoribacter splanchnicus DSM 20712 gi325282145
Bacteroidetes/Chlorobi-Maribacter sp. HTCC2170 gi305664924
Bacteroidetes/Chlorobi-Leeuwenhoekiella blandensis MED217 gi86142021
100 91
Bacteroidetes/Chlorobi-Zunongwangia profunda SM A87 gi295136007
Bacteroidetes/Chlorobi-Flavobacterium johnsoniae UW101 gi146299791
Bacteroidetes/Chlorobi-Capnocytophaga canimorsus Cc5 gi340620830
74
77 Bacteroidetes/Chlorobi-Capnocytophaga sputigena ATCC 33612 gi213961665
Bacteroidetes/Chlorobi-Capnocytophaga ochracea DSM 7271 gi256819062
100
65
93Bacteroidetes/Chlorobi-Capnocytophaga ochracea F0287 gi315224469
100
Bacteroidetes/Chlorobi-Capnocytophaga sp. oral taxon 329 str F0087 gi332876949
B
Fig. 6. Examples of two types of RAXML trees that show evidence of HGT in Picochlorum SE3. The results of 100 bootstrap replicates are shown on the branches when ≥ 50%.
A. Tree inferred from an indolepyruvate decarboxylase enzyme that shows Picochlorum SE3 to be monophyletic with bacteria, not Viridiplantae, which are elsewhere in this tree.
B. Tree inferred from an alpha-1,2-mannosidase enzyme that provides an example of a tree containing only Picochlorum SE3 and a wide diversity of bacteria.
100
A
8
F. Foflonker et al.
© 2014 Society for Applied Microbiology and John Wiley & Sons Ltd, Environmental Microbiology
Gene
22
272
85
685
306
759
490
758
707
667
902
589
397
527
914
357
382
462
62
61
86
379
451
526
Contig
15
28
29
85
87
101
114
124
166
201
205
231
82
107
196
43
89
91
29
30
41
96
96
126
Alpha-1,2-mannosidase
Sheath polysaccharide-degrading enzyme
Cellulase (glycosyl hydrolase family 5)
Glycosyltransferase family 1 (PEP-CTERM exsortase domain)
GDP-mannose-4,6 -dehydratase
Glycosyltransferase o-methyltransferase
O-methyltransferase
GDP-L-fucose synthase
Rmt2 protein, putative arginine methyltransferase
Sheath polysaccharide-degrading enzyme
Carbohydrate-binding family v xii
Glycosyl transferase, group 2 family protein
Glutamylendopeptidase
Trypsin-like serine protease
Peptidase M13 (PepO)
Indolepyruvate decarboxylase
5-methyltetrahydropteroyltriglutamate/ homocysteine S-methyltransferase
Glycerol dehydrogenase
Regulator of chromosome condensation (RCC1) related protein
Hypothetical protein
Unknown
Arylsulfatase
Fusaric acid resistance protein
DNA methylase n-4 n-6 domain protein
Annotation
7.3E-178
8.1E-41
6.3E-48
2.4E-67
0.0E+00
2.8E-11
3.0E-27
3.7E-134
8.7E-09
1.4E-34
2.4E-24
8.2E-30
3.9E-20
1.1E-15
1.0E-151
4.7E-117
1.0E-27
8.0E-118
2.4E-17
–
–
1.0E-61
1.2E-06
8.7E-76
E-value
Carbohydrate metabolism
Carbohydrate metabolism
Carbohydrate metabolism
Carbohydrate metabolism
Carbohydrate metabolism
Carbohydrate metabolism
Carbohydrate metabolism
Carbohydrate metabolism
Carbohydrate metabolism
Carbohydrate metabolism
Carbohydrate metabolism
Carbohydrate metabolism
Proteinase
Proteinase
Proteinase
Amino acid metabolism
Amino acid metabolism
Lipid metabolism
Cell cycle control
Unknown
Unknown
Sulfur limitation stress
Defense
DNA methylation
Putative function
Bacteroidetes/Chlorobi
Ambiguous
Ambiguous
Verrucomicrobia
Ambiguous
Ambiguous
Ambiguous
Ambiguous
Ambiguous
Ambiguous
Ambiguous
Ambiguous
Ambiguous
Ambiguous
Ambiguous
Ambiguous
Actinobacteria
Ambiguous
Ambiguous
Ambiguous
Ambiguous
Ambiguous
Proteobacteria
Archaea
Putative prokaryotic donor
802
4
429
0
3273
646
2551
914
1799
723
408
318
15
86
1910
195
250
978
289
0
12
14
327
2936
EST reads
mapped to gene
47.72
0.56
37.88
0
448.87
181.81
425.83
141.35
276.87
108.34
61.51
34.49
2.2
13.22
138.78
15.02
26.42
123.66
43.32
0
1.2
1.28
14.25
302.88
Average EST
coverage
Table 2. Instances of HGT that were identified in the Picochlorum SE3 genome and their putative gene functions. Putative gene annotations, results of the BLAST analysis, phylogenetic domain
of gene origin, putative gene function, putative prokaryotic donor, and the number of EST reads that mapped to the gene, and their average coverage are shown.
Genome analysis of Picochlorum SE3
© 2014 Society for Applied Microbiology and John Wiley & Sons Ltd, Environmental Microbiology
9
10
F. Foflonker et al.
Cell wall
synthesis
Sulfate
ester
Cell wall
degradation
Proteins
B
Protein
degradation
on
A
S
Sulfat
Sulfate
Amino
Acids
ds
no Ac
S
Sugars
Growth hormone
synthesis
y
F
E
-2
Na + SO4
D
Glycer
Glycerol
Sulfur
Osmolytes
mol
molytes
DMSP
C
Grow
Growth
G
Nucleus
Cell cycle control
C
G
C. reinhardtii and Volvox carteri under sulfur limitation
(Lien and Schreiner, 1975; Yildiz et al., 1994; Takahashi
et al., 2011). Excess sulfur can be incorporated in sulfur
containing amino acids such as cysteine and methionine
or shunted to the synthesis of dimethylsulfoniopropionate,
an osmoprotectant that is favoured under nitrogen-limiting
conditions (Ratti and Giordano, 2008). Another bacterial
gene found in Picochlorum SE3, regulation of chromosome condensation (RCC1) is a protein that binds the
nucleosome and is involved in chromosome segregation
during cell division (England et al., 2010). RCC1 may be
involved in cell cycle control, important in unpredictable
environments. It is also among the expanded gene families in the diatoms Phaeodactylum tricornutum and
Thalassiosira pseudonana (Bowler et al., 2008). Also of
foreign origin is an enzyme involved in the synthesis of a
plant growth promotion hormone, indole-3-acetic acid,
typically produced by plants and plant-associated soil
bacteria (Sergeeva et al., 2002). This growth hormone
promotes growth in co-cultures of C. vulgaris with the
plant growth-promoting rhizobacterium Azospirillium
brasilens (De-Bashan et al., 2008).
Selenoproteins
Selenoproteins are selenocysteine-containing proteins,
often oxidoreductases that are widely distributed in all
domains of life. Green algae such as O. tauri and
C. reinhardtii contain 26 and 10 selenoproteins, respectively, whereas some higher plants lack selenoproteins
(Novoselov et al., 2002; Lobanov et al., 2007; Palenik
et al., 2007). Selenocysteine is encoded by a UGA codon
Fig. 7. Putative functions in Picochlorum SE3
conferred by HGT. Many genes have roles in
cell growth, response to nutrient limitation or
production of osmolytes for osmoregulation.
A. Glycosyltransferases, glycoside hydrolases
and polysaccharide lyases may function in
cell wall degradation. Some may be excreted
from the cell.
B. GDP-mannose-4,6,-dehydratase and
GDP-L-fucose synthase involved in fucose
synthesis, important for cell wall integrity.
C. Indolepyruvate decarboxylase that
catalyzes the conversion of indolepyruvate to
indole-3-acetic acid, a plant auxin.
D. Glycerol dehydrogenase that catalyzes the
conversion of glycerone to glycerol, a
common osmoprotectant.
E. Three peptidases that are involved in
protein cleavage to amino acids.
F. A periplasmic arylsulfatase that converts
sulfate esters to sulfate for uptake into the
cell.
G. Regulation of chromosome condensation
(RCC1) protein that is involved in cell cycle
control.
(typically read as a stop codon) in the mRNA sequence,
and its translation as selenocysteine is dependent on the
presence of a SECIS element (selenocysteine insertion
sequence) located in the 3′ untranslated region in
eukaryotes (Liu and Jiang, 2012). We used TBLASTN to
search for similarity between Picochlorum SE3 proteins
and known selenoproteins in O. tauri (Palenik et al.,
2007). Top hits were tested for the occurrence of the
conserved stem-loop structure of the SECIS element
using SECISEARCH (Mariotti et al., 2013), which were then
manually verified. Using this approach, suprisingly,
no clear evidence was found for the presence of
selenoproteins in Picochlorum SE3, although our data do
not preclude their potential occurrence in the genome.
Hydrogenase activity and other genes of interest
The Picochlorum SE3 genome contains two hydA-like
genes encoding (FE)-hydrogenase involved in maintaining pH homeostasis while releasing H2 gas in response to
anoxic stress. Hydrogen evolution is present in green
algae such as C. reinhardtii but is absent from others (e.g.
D. salina) and provides a target alternative energy source
(Cao et al., 2001). Our finding suggests that Picochlorum
SE3 may have H2-evolution capabilities, adding to its repertoire of stress adaptations. This species may also
provide an attractive alternative to C. reinhardtii for H2
production, particularly because a high salt, selective
medium could be utilized for cultivation. Finally, similar
to C. variabilis NC64A, the genome of Picochlorum
SE3 contains genes involved in chitin and chitosan
biosynthesis (Blanc et al., 2010). A homologue of chitin
© 2014 Society for Applied Microbiology and John Wiley & Sons Ltd, Environmental Microbiology
Genome analysis of Picochlorum SE3
synthase, four copies of chitin deacetylase, three
chitinase genes and a chitosanase gene were found (see
Supporting Information Table S1), suggesting that chitin
and chitosan may contribute to the resilience of the
Picochlorum SE3 cell wall.
Discussion
Microalgae are increasingly being looked upon as indicators of climate change and as their genomes are being
determined and metabolic pathways described, as potential models for biotechnology (e.g. Huesemann et al.,
2009; Hannon et al., 2010; Wang et al., 2014). Two traits
of particular interest for the biofuel industry are salt tolerance as a means of achieving crop protection in open
pond systems and high-lipid production (Hannon et al.,
2010). Picochorum SE3 has both of these properties and
is therefore a potential algal biofuel candidate (Wang
et al., 2014). Understanding how this alga is able to
survive in a stressful and fluctuating environment offers
the promise to advance both applied and fundamental
research.
Given this interest, it was serendipitous that
Picochlorum SE3 has a highly reduced and compact
genome of size 13.5 Mbp (i.e. with a gene present every
approximately 2 Kbp) that is highly amenable to comparative analysis. Our work identifies a suite of characters that
differentiate Picochlorum SE3 from its non-halotolerant
sisters that represent major innovations in this lineage.
One of these is the clustering of functionally related genes
such as for urea metabolism and acetate assimilation that
likely allow a rapid response to nutrient stress. Another
adaptation to salt and nutrient stress in Picochlorum SE3
is the expansion of metabolite transporter gene families
with 719 members representing nearly 10% of the gene
inventory. We found seven transporters putatively capable
of glucose uptake with culture work showing that glucose
in the medium improved algal growth rate under high salt
stress (Fig. 5). A third major input into overcoming environmental stress in Picochlorum SE3 is HGT of bacterial
genes.
The notion that microalgae can, like bacteria, gather
genes from the environment to adapt to changing conditions has still not been widely tested with free-living taxa.
A recent study of the extremophilic (i.e. found in hot
acidic waters near fumaroles) Cyanidiophytina red alga
Galdieria sulphuraria showed that its remarkable metabolic flexibility (e.g. glycerol metabolism, ability to detoxify
mercury and arsenic) is explained by HGT from
prokaryotic sources. Its sister lineage, the rock-dwelling
Galdieria phlegrea has, since its split from G. sulphuraria,
regained all of the genes required for urea hydrolysis
through (likely independent) HGTs from bacteria, allowing
it to survive in the nitrogen-limited cryptoendolithic envi-
11
ronment (Qiu et al., 2013). Our results with Picochlorum
SE3 significantly extend these findings and show that an
alga that lives in a variety of environmental conditions
ranging from mesophilic to halophilic is also able to
acquire genes from the environment to extend its metabolic flexibility. This trait is evident in the enhanced repertoire of proteins involved in carbohydrate metabolism,
osmolyte regulation, sulfate scavenging and cell cycle
control. The 24 clear cases of HGT we identified in
Picochlorum SE3 stand in stark contrast to the obvious
strong selection in this lineage for shedding genes and
reducing genome size and complexity. This observation
suggests that the prokaryote-derived genes in
Picochlorum SE3 must confer an ecological, adaptive
advantage.
In summary, although little known in the general scientific literature, our results identify Picochlorum SE3 as a
potentially valuable model for investigating the origin of
metabolic flexibility in eukaryotic microbes. The next step
is to develop genetic tools in Picochlorum SE3 to test the
hypotheses presented here with the goal of using this
knowledge to improve other microbial strains of interest to
serve basic and applied research goals.
Experimental procedures
Strains and culture conditions
Picochlorum strain SENEW3 (SE3) was isolated by B.P. and
S.W. from the San Elijo Lagoon system, in San Diego County,
California and is described further in Wang et al. (2014). The
alga was cultivated in artificial seawater (Goldman and
McCarthy, 1978) based Guillard’s F/2 medium without silica
at 25°C under continuous light (∼ 100 uE m−2 s) on a rotary
shaker at 100 r.p.m. (Innova 43, New Brunswick Eppendorf).
The high salt stress experiments were done in duplicate
cultures by varying the concentration of NaCl in the artificial
seawater based F/2 medium. Mixotrophic growth rate experiments under 1.5 M NaCl stress were performed in triplicate
cultures with the addition of 1–30 g l−1 of glucose that was
filter sterilized using 0.2 μm cellulose acetate filters.
Heterotrophic growth was tested with the addition of 5 g l−1
glucose in the dark. Picochlorum SE3 stock solution was
used to inoculate 100 ml flasks to the inoculation density of
1 × 105 cells ml−1. Algal growth was determined by cell counts
using a hemacytometer (Neubauer improved, Hausser
Scientific) and IMAGEJ software.
DNA and RNA extraction and library construction
Approximately 100 mg of cells was harvested by centrifugation at 4000 r.p.m. for 2 min and then immediately frozen with
liquid nitrogen. DNA extraction was performed using the
DNeasy Plant Mini Kit (Qiagen, Valencia, CA) and total RNA
was extracted using the RNeasy Mini Kit (Qiagen). DNA and
cDNA libraries were constructed using the Nextera DNA
Sample Preparation Kit V2 and TruSeq RNA Sample
© 2014 Society for Applied Microbiology and John Wiley & Sons Ltd, Environmental Microbiology
12
F. Foflonker et al.
Preparation Kit, respectively (Illumina, San Diego, CA), following manufacturer’s protocols.
Genome and transcriptome sequencing
A total of 830 Mbp of paired-end (2 × 150 bp) Illumina
genome sequence data and 2.07 Gbp (13.8 million reads) of
paired-end 2 × 150 bp mRNAseq data were generated from
Picochlorum SE3 using the Illumina MiSeq Personal Genome
Sequencer (Illumina, San Diego, CA). The genome assembly
was generated using the CLC GENOMICS WORKBENCH de novo
assembler (CLC Bio, Aarhus, Denmark) and consisted of
1266 contigs totalling 13.45 Mbp with an N50 of 124 539 bp.
The RNA-seq data were aligned to the genome using GSNAP
(Wu and Nacu, 2010) and the output used to train the ab initio
gene predictor AUGUSTUS (Stanke and Morgenstern, 2005),
resulting in 7367 high-quality gene models for downstream
analysis. The sequence data used to assemble the draft
Picochlorum SE3 draft genome and the assembled contigs
can be accessed via National Center for Biotechnology
Information (NCBI) BioProject PRJNA245752. The genome
assembly, gene models and phylogenomic output (see
below) are also available at: http://cyanophora.rutgers.edu/
picochlorum/.
Phylogenomic analysis
Automated phylogenomic analysis of individual proteins was
done as previously described in Price and colleagues (2012).
Briefly, BLASTP was used to retrieve a set of taxonomically
diverse sequences from our in-house protein database.
Sequence alignments were constructed using MAFFT V6.864B
(Katoh et al., 2002), and RAXML 7.2.8 (PROTGAMMAWAG
model; 100 bootstrap replicates) was used to generate 5871
trees containing greater than or equal to three phyla. Trees
were sorted for monophyly with Bacteria, Archaea and Vira
using PHYLOSORT (Moustafa and Bhattacharya, 2008).
Instances of HGT were then manually confirmed with ≥ 60%
bootstrap support for the sister relationship between
Picochlorum SE3 and prokaryotes or trees containing only
prokaryotes.
Transporter analysis
Putative membrane transport proteins and their classifications were identified based on sequence similarity
searches (BLASTP, E-value cut-off ≤ 1 × 10−10) against the
TCDB. TC numbers were used to identify a set of core or
shared proteins and those unique to Picochlorum SE3 or
O. tauri.
Construction of multi-protein tree
We collected complete proteome data from 10 green algae:
Picochlorum SE3, C. reinhardtii (Merchant et al., 2007),
V. carteri (Prochnik et al., 2010), C. variabilis (Blanc et al.,
2010), Coccomyxa subellipsoidea (Blanc et al., 2012),
Micromonas isolate RCC299 (Worden et al., 2009),
Micromonas pusilla CCMP1545 (Worden et al., 2009),
O. lucimarinus, O. tauri (Palenik et al., 2007) and B. prasinos
(Moreau et al., 2012), from the glaucophyte Cyanophora
paradoxa (Price et al., 2012) and from the red alga
Porphyridium purpureum (Bhattacharya et al., 2013). These
combined data were subjected to an all-versus-all self-BLASTP
search (E-value cut-off ≤ 1e-05). Orthologue groups across
the 12 taxa were constructed using ORTHOMCL (Li et al., 2003)
with default settings. Sequence alignments were constructed
for orthologous groups containing only one sequence in each
green algal taxon (allowing missing data in a maximum of two
taxa). The alignment was built using MAFFT (--auto) (Katoh
et al., 2002) with the poorly aligned regions being removed
using GBLOCKS (−b4 = 5; −b5 = h) (Talavera and Castresana,
2007). Because GBLOCKS is unable to remove badly aligned
individual sequence within well-conserved blocks, we applied
T-COFFEE (Notredame et al., 2000) to remove poorly aligned
residuals (i.e. conservation score ≤ 5). Sequences less than
one half of the alignment length and columns with less than
eight residues were also removed from alignments. The
resulting alignments (≥ 100 amino acids) were used for
single-gene tree construction using PHYML3 (Guindon et al.,
2010) under the LG+Γ + F + I model. Trees (and the alignments) with 20% longest total branch length were removed.
The remaining 1656 alignments were concatenated into a
super-alignment (480 102 amino acids). The multi-protein
tree was built using RAXML (Stamatakis et al., 2008) under the
PROGAMMALGF model. The bootstrap values were generated using 100 replicates.
Functionally clustered pathways
We downloaded pathway annotations from the Unipathway
database (Morgat et al., 2012). The sequences of the
underlying genes were retrieved from UniProt/Swiss-Prot
that comprises a collection of high-quality manually annotated and non-redundant protein sequences (http://www
.ebi.ac.uk/uniprot). The resulting database comprises proteins for 907 reactions (gene families) that build 207
pathways (478 subpathways). Picochlorum SE3 protein
sequences were used as query to search against the
database using BLASTP (E-value cut-off ≤ 1 × 10−10). This
resulted in a list of 633 Picochlorum SE3 proteins with significant hits. Physically linked genes involved in the same
pathway were then manually identified. C-HUNTER (Yi et al.,
2007) was also used to identify functional clusters based on
GO terms (Ashburner et al., 2000; minimum number of
genes per cluster 2; maximum cluster size 3; E-value cut-off
≤ 1 × 10−3; threshold of cluster overlap 10%) and (minimum
number of genes per cluster 2; maximum cluster size 50;
E-value cut-off ≤ 1 × 10−4; threshold of cluster overlap 50%).
GO terms were identified using the BLAST2GO program
(default settings) (Conesa et al., 2005). The top two levels
of GO scheme were not considered; e.g. molecular function
and biological process, which are too general to provide
insights in this analysis.
Acknowledgements
This work was supported by a grant from the Department of
Energy (DE-EE0003373/001). F.F. acknowledges graduate
training support from the National Science Foundation Fuels
IGERT program at Rutgers University (0903675). The
authors have no conflict of interest with respect to this work.
© 2014 Society for Applied Microbiology and John Wiley & Sons Ltd, Environmental Microbiology
Genome analysis of Picochlorum SE3
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Supporting information
Additional Supporting Information may be found in the online
version of this article at the publisher’s web-site:
Fig. S1. Mixotrophic growth of Picochlorum SE3. Growth of
Picochlorum SE3 cultures in the absence of high salt stress
(0.4 M NaCl) with the addition of different amounts of
glucose. The inoculation density was 1 × 10 E + 5 cells ml−1.
The error bars represent standard error from triplicate
cultures.
Table S1. List of predicted proteins in Picochlorum SE3
showing their putative annotations and results of a BLASTP
search against a comprehensive in-house database.
Table S2. Ostreococcus tauri nitrate assimilation gene clusters and the corresponding Picochlorum SE3 genes and their
contig locations. Genes located on the same contig are
shown in boldface.
© 2014 Society for Applied Microbiology and John Wiley & Sons Ltd, Environmental Microbiology