Comparative Proteomics Reveals That a Saxitoxin-Producing and a

Article pubs.acs.org/jpr

Comparative Proteomics Reveals That a Saxitoxin-Producing and a Nontoxic Strain of Anabaena circinalis Are Two Different Ecotypes Paul M. D’Agostino,† Xiaomin Song,‡ Brett A. Neilan,§ and Michelle C. Moffitt*,† †

School of Science and Health, University of Western Sydney, Campbelltown, NSW 2560, Australia Australian Proteomics Analysis Facility, Macquarie University, Level 1, 3 Innovation Road, Macquarie Park, NSW 2109, Australia § School of Biotechnology and Biomolecular Sciences, University of New South Wales, Kensington, NSW 2052, Australia ‡

S Supporting Information *

ABSTRACT: In Australia, saxitoxin production is restricted to the cyanobacterial species Anabaena circinalis and is strain-dependent. We aimed to characterize a saxitoxin-producing and nontoxic strain of A. circinalis at the proteomic level using iTRAQ. Seven proteins putatively involved in saxitoxin biosynthesis were identified within our iTRAQ experiment for the first time. The proteomic profile of the toxic A. circinalis was significantly different from the nontoxic strain, indicating that each is likely to inhabit a unique ecological niche. Under control growth conditions, the saxitoxin-producing A. circinalis displayed a higher abundance of photosynthetic, carbon fixation and nitrogen metabolic proteins. Differential abundance of these proteins suggests a higher intracellular C:N ratio and a higher concentration of intracellular 2-oxoglutarate in our toxic strain compared with the nontoxic strain. This may be a novel site for posttranslational regulation because saxitoxin biosynthesis putatively requires a 2-oxoglutarate-dependent dioxygenase. The nontoxic A. circinalis was more abundant in proteins, indicating cellular stress. Overall, our study has provided the first insight into fundamental differences between a toxic and nontoxic strain of A. circinalis, indicating that they are distinct ecotypes. KEYWORDS: saxitoxin, paralytic shellfish toxins, iTRAQ, photosynthesis, ecotype, cyanobacteria, comparative proteomics

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INTRODUCTION Freshwater cyanobacterial blooms are increasing in frequency and intensity due to several factors, including global warming.1 Blooms are often toxic and can have a major detrimental impact on public safety and the economy.2,3 One contributing group of toxins is the paralytic shellfish toxins (PSTs), a large group of neurotoxic alkaloids including saxitoxin (STX), which is the most researched PST to date.4 Ingestion of the PSTs is responsible for the potentially fatal illness known as paralytic shellfish poisoning (PSP). In the freshwater environment, PSTs are limited to species within the Nostocaceae and Oscillatoriaceae families of cyanobacteria; in the marine environment, they are produced by eukaryotic dinoflagellates. Structurally, the PSTs are highly nitrogenous and vary in their toxicity based on different substituent groups. The most toxic varieties are nonsulfated, followed by the monosulfated, and the least toxic are double-sulfated. Toxicity of the PSTs is mediated by the blockage of voltage gated Na+ channels.5 To date, the saxitoxin gene cluster (sxt) encoding the enzymes putatively responsible for STX biosynthesis have been identified in five cyanobacterial species.6−9 A. circinalis is the only cyanobacterium known to be capable of STX production in Australia, and several major bloom events of this cyanobacterium have been reported, particularly in the Murray−Darling basin.10,11 © 2014 American Chemical Society

Isolation of cyanobacteria from a range of habitats, such as high- or low-light environments, has revealed that natural microbial species consist of multiple ecotypes.12 An ecotype refers to a population within a species that has adapted to a specific environment. Adaptations within a species allow the ecotype population to thrive in response to specific physicochemical properties. Several ecotypes of the marine picocyanobacterium, Prochlorococcus marinus, have adapted to specific light intensities, nitrogen, and phosphorus sources, dependent on their distribution in the water strata.13−16 Recently, ecotypes of microcystin-producing and nontoxic cyanobacteria of the species Microcystis aeruginosa were investigated via a comparative proteomics approach.17,18 These studies identified strain specific proteins and differences in protein abundance between ecotypes and concluded that at the proteomic level isolates of the same species can be highly variable. Unfortunately, in terms of biomarker discovery, none of these differentially expressed proteins were directly correlated to toxicity. A morphological, physiological and genetic investigation of PST-producing (PST+) Cylindrospermopsis raciborskii identified two distinct ecotypes from the same geographic region.19 The Received: October 7, 2013 Published: January 24, 2014 1474

dx.doi.org/10.1021/pr401007k | J. Proteome Res. 2014, 13, 1474−1484

Journal of Proteome Research

Article

Growth of cyanobacterial filaments in culture was monitored via methanol extraction of chlorophyll a (chl a) adapted from Meeks and Castenholz29 using a Ultrospec 2100 Pro spectrophotometer (Biochrome, Cambridge, U.K.). Once cultures reached midlate exponential phase as defined by methanolic chl a extractions, filaments were washed with fresh control or experimental medium before resuspension in 180 mL of fresh medium. After 48 h, cultures were filtered through an 8 μm membrane (Millipore, Billerica, MA) to remove heterotrophic bacteria while retaining cyanobacterial filaments. Medium was exchanged, and protein was extracted at the same time of day for all cultures. Filaments were washed with 10 mL of sucrose buffer (100 mM EDTA [pH 8], 50 mM Tris [pH 7.4], 25% (w/v) sucrose) to remove polysaccharides and then washed with 10 mL of phosphate-buffered saline to remove all traces of sucrose buffer.

two ecotypes were distinct in their growth rate, preference for light intensity, and toxin composition. The two Anabaena isolates chosen for this study, A. circinalis AWQC131C (hereafter 131C) and A. circinalis AWQC310F (hereafter 310F), have been shown to be PST+ and nontoxic (PST−), respectively.20 131C and 310F share extremely high sequence identity at the 16S rRNA gene level (>99%) but were isolated from different locations within the Murray−Darling Basin, Australia.21 The ability for toxin production (or lack thereof) may imply an intrinsic difference in metabolism. In addition, laboratory cultures of PST+ 131C reach stationary phase in less time than PST− 310F, and each has a unique macroscopic appearance, which suggests that the two strains may be different ecotypes. Traditionally, cyanobacterial proteomic studies have focused on the laboratory-adapted strains Synechocystis sp. PCC 6803 (hereafter Synechocystis 6803) as well as select species of Anabaena, Nostoc, and Cylindrospermopsis22−25 using twodimensional electrophoresis (2-DE) proteomics. Recently, alternatives to 2-DE proteomics have been developed, such as the isobaric tags for relative and absolute quantitation (iTRAQ) shotgun proteomic technique.26,27 Comparisons between 2-DE and iTRAQ have revealed that the latter is a suitable gel-free alternative, and this has been complimented with a rise in cyanobacterial proteomic publications. To this end, iTRAQ has allowed us to create an in-depth investigation of PST+ and PST− strains of A. circinalis, a relatively unstudied cyanobacterium. We aimed to compare protein abundance between 131C and 310F in an attempt to identify key differences in specific proteins and hence not only their secondary but also primary metabolic pathways. This study revealed major differences in the 131C and 310F proteomic profiles, particularly the abundance of photosynthetic, metabolic, and stress proteins. We propose that 131C is capable of higher rates of photosynthesis and is less prone to oxidative stress than 310F. Therefore, each is likely to inhabit a distinct ecological niche.

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Protein Extraction of Cyanobacterial Filaments

Thawed cyanobacterial filaments were washed with 2 mL of extraction buffer (500 mM triethylammonium bicarbonate (TEAB) [pH 8.5], 0.01% SDS (w/v), 0.1% Triton X-100 (v/ v)) and disrupted via the addition of 1 vol of 435−600 μm acidwashed glass beads, followed by five rounds of vortexing. The cellular protein suspension was incubated for 30 min with 2% SDS (w/v) to facilitate the collection of transmembrane proteins. Frozen samples were sent to the Australia Proteomics Analysis Facility (APAF) for sample preparation and analysis. iTRAQ Sample Preparation and Labeling

Sample preparation, chromatography, and data acquisition was adapted from a previous iTRAQ study.30 Soluble protein was acetone-precipitated, resuspended in iTRAQ buffer (250 mM TEAB and 0.05% SDS (w/v)), and submitted for protein quantitation via amino acid analysis (AAA). A total of 100 μg of protein from each sample was reduced with 5 mM tris(2carboxyethyl)phosphine (TCEP) for 1 h at 60 °C, alkylated with 10 mM s-methyl methanethiosulfonate (MMTS) at room temperature for 10 min, and finally digested with trypsin for 16 h at 37 °C. Digested samples were labeled with the iTRAQ reagents following the protocol provided by the manufacturer (Applied Biosystems, Foster City, CA).

EXPERIMENTAL PROCEDURES

Experimental Design

Strong Cation Exchange High-Performance Liquid Chromatography

Two individual 4-plex iTRAQ runs were coupled for a total of eight samples. The first iTRAQ run was designated iTRAQ-P, and the second was designated iTRAQ-N (Supporting Information 1). Samples 114 (131C) and 115 (310F) from both iTRAQ runs used cultures grown under control (unmodified) culture conditions. Also, Samples 114 and 115 from both iTRAQ runs were used as technical replicates for the experiment. Samples 116 (131C) and 117 (310F) were grown in medium designed to induce a stress response, and data will be presented separately (D’Agostino, P. M., manuscript in preparation). Biological replicates composed of protein from triplicate cultures pooled prior to iTRAQ analysis.28

The labeled iTRAQ samples were cleaned and fractionated by strong cation exchange (SCX) with an Agilent 1100 quaternary high-performance liquid chromatography (HPLC) system (Agilent, Santa Clara, CA). SCX was performed using a Polysulfoethyl A 100 mm × 2.1 mm 5 μm 200 Å column (PolyLC, Columbia, MD). Buffer A consisted of 5 mM phosphate and 25% (v/v) acetonitrile [pH 2.7], and buffer B consisted of 5 mM phosphate, 350 mM KCl, and 25% (v/v) acetonitrile [pH 2.7]. Dried labeled iTRAQ samples were resuspended in buffer A, applied to the SCX column, and further washed with buffer A. After washing, the concentration of buffer B increased from 10 to 45% over 70 min, then increased quickly to 100% for 10 min at a flow rate of 300 μL min−1. In total, 15 SCX fractions were collected for downstream data acquisition.

Cyanobacterial Culture Conditions

131C and 310F were maintained in 180 mL of Jaworski’s medium at 24 ± 1 °C and a light intensity of 11 μmol m−2 s−1 ± 1 photosynthetically active radiation (PAR) on a 12:12 h light cycle. Prior to the iTRAQ experiment, 131C and 310F cultures were subcultured and grown to early stationary phase. This process was repeated three times to train the cyanobacterial cultures to the control conditions used in the experiment.

NanoLC ESI MS/MS Data Acquisition

NanoLC ESI MS/MS was performed on a Eksigent Tempo nanoLC system (Eksigent, Dublin, CA) coupled to a Qstar Elite tandem mass spectrometer (Applied Biosystems). SCX fractions were resuspended in 100 μL of loading/desalting 1475



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Figure 1. Categorization of identified proteins according to KEGG. Categorization of all identified proteins according to KEGG. The number of identified proteins is a combination of both iTRAQ-P and iTRAQ-N runs. The figure displays the percentage of proteins in each category out of the total number of identified proteins.

>95% confidence for peptide identification, and the protein threshold (Unused ProtScore) was set as ≥1.3, indicating better than 95% confidence. Inbuilt algorithms of the ProteinPilot software allowed for FDR analysis using a reverse decoy database of each A. circinalis strain. For protein quantitation cut-offs, the identified protein must have a p-value (Pval) of ≤0.05 and was regarded as differentially abundant if its ratio was ≥1.2 (higher abundance in 310F) or ≤0.82 (higher abundance in 131C). ProteinPilot V4.0 requires iTRAQ tag ion signal/noise larger than nine for a peptide to merit an iTRAQ ratio. A minimum of two unique peptides for a protein iTRAQ ratio is required to obtain a Pval. A protein was only considered to be differentially abundant if identified in 131C and 310F database searches with a similar ratio and Pval ≤0.05. When a protein was quantified as differentially abundant in iTRAQ-P and iTRAQ-N, the ratio associated with the lowest Pval was used to indicate the fold change. Fold change is given in parentheses unless otherwise stated. It is important to note that only background-corrected ratios are reported in this study. These values may be exaggerated; however, the trend of differential abundance is correct for each protein. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium (http://proteomecentral. proteomexchange.org) via the PRIDE partner repository31 with the data set Accession PXD000206.

solution (0.1% (v/v) trifluoroacetic acid, 2% (v/v) acetonitrile) and 39 μL of the resuspended solution was loaded on a reversephase peptide Captrap (Michrom Bioresources, Walnut Creek, CA). Sample desalting occurred at a rate of 10 μL min−1 for 13 min. After desalting, the trap was switched online with a SGE ProteCol column (150 μm × 10 cm C18 3 μm 300 Å) with buffer A consisting of 99.9% (v/v) water and 0.1% (v/v) formic acid and buffer B consisting of 90% (v/v) acetonitrile and 0.1% (v/v) formic acid. The buffer B concentration was increased from 5 to 90% over 120 min in three linear gradient steps to elute peptides. After peptide elution, the column was cleaned with 100% buffer B for 15 min and then equilibrated with buffer A for 30 min before next sample injection. The reverse-phase nanoLC eluent was subject to positive ion nanoflow electrospray analysis in information-dependent acquisition mode (IDA). In IDA mode, a time-of-flight MS survey scan was acquired (m/z 370−1600, 0.5 s), with the three most intense multiply charged ions (counts >70) in the survey scan sequentially subjected to MS/MS analysis. MS/MS spectra were acquired in the mass range m/z 100−1600. Database Searching and Protein Data Analysis

The experimental nanoLC ESI MS/MS data were submitted to ProteinPilot V4.0 (AB Sciex) for data processing using the inbuilt Paragon Search algorithm with default settings. In brief, the ProteinPilot parameter settings were as follows: precursor ion mass tolerance, 0.2 Da; fragment ion mass tolerance, 0.2 Da; modifications, iTRAQ 4-plex, cysteine modifications as MMTS; maximum number of missed cleavages, 2; thorough search mode, selected; background subtraction, selected; false discovery rate (FDR), selected; bias correction, selected. A separate search was performed on the two databases 131C (4442 ORFs) and 310F (4443 ORFs). Each database was set up in-house and consisted of a six-frame translation of each ORF. Genomic data and ORF annotation were compiled from Illumina paired-end genome sequencing and gene annotation of 131C and 310F by BGI. Whole Genome Shotgun projects for 131C and 310F have been deposited at DDBJ/EMBL/ GenBank under the accession APIY00000000 and APIZ00000000, respectively. The versions described in this paper are the first version of each genome and will be published independently. The predicted ORFs were functionally categorized according to clusters of orthologous groups of proteins (COG), Kyoto Encyclopedia of genes and genomes (KEGG), SwissProt, Trembl, and NCBI nonredundant databases. An automated population list was generated for protein identification. Thresholds for the population list were set to

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RESULTS

Proteome Overview and Protein Properties

This study reports the first analysis of a toxin-producing cyanobacterium via the iTRAQ method and the first proteomic investigation of A. circinalis. Technical replicates resulted in a correlation of 0.81 against the 131C database and 0.824 against 310F database. FDR analysis, peptide, and protein summaries are available as Supporting Information 2 and the PRIDE database, respectively. A description of the results for iTRAQ-P and iTRAQ-N runs and the raw data from bioinformatic tools is presented in Supporting Information 3 and 4. An in-house database was devised by partial genomic sequencing of a 131C and 310F strain of A. circinalis (D’Agostino, P. M., manuscript in preparation). ORFs were predicted using Glimmer gene annotation and then converted to a six-frame translation. The six-frame translation allowed us to correct falsely annotated ORFs by confirming the identified protein sequence in an alternate frame. This resulted in an updated database containing 4447 ORFs and 4443 ORFs for 131C and 310F, respectively. The reannotated ORF list was 1476



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Table 1. Comparative Abundance of Proteins Identified in 131Ca protein ID

no. peptides (95%)

putative function (KEGG)b,c

KEGG accession

fold change

Pval

65 35 60 48 72 80 97 67 75 76 31 40 23 39

photosystem I subunit III (PsaF) photosystem II CP47 chlorophyll apoprotein (PsbB) photosystem II cytochrome b559 subunit α (PsbE) photosystem II (PsbH) photosystem II reaction center (Psb28) allophycocyanin b (ApcD) phycobilisome core component (ApcF) apocytochrome f (PetA) ferredoxin NADP+ reductase (PetH) F-type H+-transporting ATPase subunit b (AtpF) regulation of phycobilisomes (RcaD) Ycf48-like/glycosyl hydrolase - Putative PSII stability protein magnesium-protoporphyrin IX monomethyl ester cyclize geranylgeranyl reductase (ChlP)

K02694 K02704 K02707 K02709 K08903 K02095 K02097 K02634 K02641 K02109

20.9 2.8 5.6 12.6 4.5 8.9 42.1 21.5 2.9 19.1 7.2 4.5 2.5 11.4

0.0145 0.0024 0.0246 0.0403 0.0144 0.0022 0.0005 0.0046 0.0029 0.0024 0.0037 0.0032 0.0080 0.0172

94 28 36 37 73 77 60

CO2 concentrating mechanism (CcmK) ribulose 1,5-bisphosphate carboxylase small subunit (RbcS) phosphoribulokinase (PrkB) CO2 hydration protein (ChpY) beta-Ig-H3/fasciclin (NDH-1MS - CupS) NAD(P)H-quinone oxidoreductase subunit O (NdhO) ADP-glucose pyrophosphorylase (GlgC)

K08696 K01602 K00855

K00975

4.5 9.0 2.5 6.3 5.9 2.1 1.7

0.0119 0.0096 0.0073 0.0010 0.0004 0.0285 0.0027

51

thioredoxin (TrxA)

K03671

5.0

0.0098

81 52 47 57 72

urea transport system substrate-binding (UrtA) neutral amino acid transport system substrate-binding (NatB) DevB-like membrane ABC-transporter two-component system response regulator - LuxR family transcriptional regulator − AbrB1

K11959 K11954 K02005 K02479

18.9 8.6 87.1 5.0 3.1

0.0002 0.0003 0.0050 0.0063 0.0221

31

outer membrane efflux protein (HgdD)

K03287

7.5

0.0014

62 41

hypothetical protein hypothetical protein

27.8 23.3

0.0016 0.0026

coverage (%)

Metabolism (Photosynthesis) 131C_1733 32 131C_0723 31 131C_2189 7 131C_0666 8 131C_1447 13 131C_3677 53 131C_4251 54 131C_3164 37 131C_1347 51 131C_3547 29 131C_3757 6 131C_2188 7 131C_0733 2 131C_3290 11 Metabolism 131C_1601 13 131C_2802 5 131C_1346 12 131C_3072 13 131C_1430 11 131C_1457 11 131C_4030 12 Genetic Information Processing 131C_4086 6 Environmental Information Processing 131C_1766 47 131C_1653 19 131C_3404 3 131C_3664 29 131C_3713 16 Cellular Processes 131C_2830 7 Hypothetical or Unknown Proteins 131C_1256 7 131C_3144 6

K04035 K10960

a

Curated list of proteins that were quantitatively more abundant in 131C compared with 310F under control conditions (label 114:115). The Table displays the genome annotation ID, the number of peptides with >95% confidence, the putative function according to KEGG (gene name in parentheses if known), KEGG accession number, the fold change in abundance compared with 310F, and the Pval assigned to the protein. The proteins are organized into KEGG categories. bWhere no KEGG function could be assigned, BLASTp and pfam were utilized for putative function annotation. In specific cases, proteins were moved into a different KEGG category based on the putative function in cyanobacteria. cSome proteins annotations were altered to more specific cyanobacterial functions not taken into account by KEGG.

genetic information and processing category, followed by those involved in environmental information and processing and cellular processes, respectively. In our analysis, we identified seven proteins putatively involved in the biosynthesis of STX and its analogues. There is a common perception that proteins involved in cyanobacterial toxin biosynthesis are very low in abundance. The observation of proteins responsible for toxin production in a proteomic study is the first to our knowledge. Identification of these proteins provides confidence in the ability of the iTRAQ technique to identify low abundance proteins, which is often perceived as a major hurdle in cyanobacterial proteomics. Additionally, eight proteins identified were specific to 131C, and four proteins were specific to 310F.

used for all downstream bioinformatic tools and referred to as the theoretical proteome. Overall, 883 unique proteins were identified in 131C, and 894 were identified from 310F, corresponding to a proteome coverage of 19.9 and 20.1%, respectively (Supporting Information 5). Identified proteins were grouped into functional categories based on KEGG (Figure 1; Supporting Information 6). Proteins were identified in all six major KEGG categories with the largest category predicted to be involved in metabolic pathways, particularly energy metabolism. The second largest fraction consisted of hypothetical proteins (could not be analyzed by KEGG) and unknown proteins (classified as unknown by KEGG). This is a significant proportion of proteins with no identifiable function but is proportional to those often observed in cyanobacterial proteomics. The detection of these proteins is confirmation of their production by A. circinalis; they can now be considered as truly expressed proteins. The next largest group belonged to

Quantified Proteins with a Higher Abundance in 131C

In total, 43 proteins were identified as more abundant in 131C, with most belonging to the metabolism category of KEGG 1477



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Table 2. Comparative Abundance of Proteins Identified in 310Fa protein ID

no. peptides (95%)

Metabolism 310F_3156 46 310F_3152 38 310F_2712 7 310F_0317 5 310F_0607 19 310F_2239 41 310F_3994 4 310F_3711 24 310F_1608 13 310F_2511 11 310F_0341 6 310F_3993 1 Genetic Information Processing 310F_2224 40 310F_0779 25 310F_2454 3 310F_3633 12 310F_4265 36 310F_2914 18 310F_3302 6 Hypothetical or Unknown Proteins 310F_2942 21 310F_2943 36 310F_2944 24 310F_2967 2 310F_0392 30 310F_0139 11 310F_0140 15 310F_4008 5

coverage (%)

putative function (KEGG)b,c

75 77 65 30 58 62 18 53 46 30 52 10

phycocyanin-associated rod linker (CpcC) phycobilisome rod-core linker (CpcG) orange carotenoid protein glucose-6-phosphate 1-dehydrogenase (G6P1D) transaldolase transketolase glutathione reductase isocitrate dehydrogenase leucyl aminopeptidase phosphoketolase cysteine synthase A (CysK) 3-mercaptopyruvate sulfurtransferase

71 99 21 74 59 65 33

molecular chaperone (DnaK2) chaperonin (GroES) methionine sulphoxide reductase A (MsrA) alkyl hydroperoxide reductase/peroxiredoxin (AhpC1) chaperonin (GroEL) universal stress protein (UspA) ferritin-like protein (DpsA)

68 65 55 39 60 54 49 37

cyclic nucleotide-binding protein cyclic nucleotide-binding protein germacradienol/germacrene-D synthase (Gsy1) hypothetical protein − DUF1499 hypothetical protein − DUF1565 hypothetical protein hypothetical protein putative stress response − ferritin-like domain (DUF892)

KEGG accession

fold change

Pval

K02286 K02290

2.7 2.9 6.5 4.2 9.0 2.8 5.0 10.1 2.8 2.4 7.7 5.5

0.0000 0.0000 0.0010 0.0117 0.0094 0.0000 0.0066 0.0000 0.0123 0.0009 0.0001 0.0261

2.3 7.4 6.9 5.6 2.3 7.5 8.5

0.0029 0.0302 0.0383 0.0013 0.0000 0.0004 0.0498

2.1 2.8 1.9 27.2 27.2 24.7 34.0 8.8

0.0001 0.0012 0.0026 0.0016 0.0000 0.0000 0.0000 0.0014

K00036 K00616 K00615 K00383 K00031 K01255 K01632 K01738 K01011 K04043 K04078 K07304 K03386 K04077

K10187

a

Curated list of proteins that were quantitatively more abundant in 310F compared with 310F under control conditions (label 114:115). The table displays the genome annotation ID, the number of peptides with >95% confidence, the putative function according to KEGG (gene name in parentheses if known), KEGG accession number, the fold change in abundance compared with 131C, and the Pval assigned to the protein. The proteins are organized into KEGG categories. bWhere no KEGG function could be assigned, BLASTp and pfam were utilized for putative function annotation. In specific cases, proteins were moved into a different KEGG category based on the putative function in cyanobacteria. cSome protein annotations were altered to more specific cyanobacterial functions not taken into account by KEGG.

oxygen species (ROS). Increases of two chlorophyll biosynthesis enzymes, magnesium-protoporphyrin IX monomethyl ester cyclase (2.5) and ChlP (11.4), were observed. The Ycf28like/glycosyl hydrolase (4.5) is thought to be involved in PSII maintenance, while RcaD (7.2) regulates phycobilisome production, as determined by Komenda et al.35 and Noubir et al.,36 respectively. Additionally, the thioredoxin, TrxA (5.0), is involved in redox metabolism increased in abundance.37 The carbon concentrating mechanism (CCM) is a cooperative group of adaptations that increases CO2 fixation efficiency.38 Structurally, the carboxysome shell protein CcmK (4.5) forms the majority of the assemblage. Also, two enzymes that catalyze CO2 fixation reactions within the carboxysome were more abundant. Phosphoribulokinase (2.5), which provides substrate for Rubisco (ribulose 1,5-bisphosphate carboxylase/oxygenase), and RbcS (9.0), the small subunit of Rubisco, were quantified using iTRAQ. Rubisco is one of the most important enzymes in nature because it functions to catalyze the first step of CO2 fixation in photosynthetic organisms.39 Photosynthetic CO2 fixation is coupled to glycogen synthesis during photosynthesis in periods of excess carbon. Our study also revealed a higher abundance of GlgC (1.7), a protein involved in glycogen synthesis.

(Table 1). The fold difference is expressed in parentheses, and a complete list of quantified proteins and statistics can be found in Supporting Information 7. Metabolic Proteins

131C displayed higher abundance of photosystem II (PSII), photosystem I (PSI), cytochrome b6/f (Cyt b6/f), and ATPase complexes. The 4 PSII proteins PsbB, PsbE, PsbH, and Psb28 were observed to have an increased fold abundance ranging from 2.6 to 12.6. The allophycocyanin proteins are the lowest energy phycobiliproteins with both ApcD (8.9) and ApcF (42.1) needed for energy transfer from phycobilisome to photosystem. The Cyt b6/f complex protein, PetA (21.5), and the Ferredoxin:NADP+ oxidoreductase (FNR), PetH (2.9), were increased within 131C. These proteins perform essential functions in electron transport and generation of NADPH.32,33 In addition, the PSI complex protein, PsaF (20.9), was also more abundant. In cyanobacteria, PsaF is involved in electron transport.34 The F-type ATPase subunit b (19.1) forms the stalk of the ATPase complex and is important for stability. In addition to the higher abundance of photosynthetic proteins, we observed an increased proportion of proteins involved in the biosynthesis of chlorophyll, PSII maintenance, phycobilisome regulation, and response to intracellular reactive 1478



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Hypothetical Proteins

Cyanobacteria usually encode two specific CO2 uptake systems as part of the CCM.38,40 A low-affinity CO2 uptake system (NDH-1MS’) is cytoplasmic membrane-bound and constitutively expressed. Conversely, expression of the alternative uptake system (NDH-1MS) is inducible, anchored in the thylakoid membrane and has a high affinity for CO2. It is thought that the conversion of CO2 to HCO3− is performed by the NDH-1MS specific CO2 hydration protein, ChpY,41 which was 6.3 times more abundant in 131C. 131C_1430 (5.9) is annotated as a Beta-Ig-H3/fasciclin by KEGG but shows high similarity to CupS of Synechocystis 6803. CupS is a small subunit of the NDH-1MS complex, but its physiological function remains unknown.42 Lastly, NdhO (2.1) forms part of all NDH-1 complexes in cyanobacteria, but to date, the function of NdhO has not been ascertained.43

Quantified proteins with no KEGG category were investigated for putative functions via BLASTp and pfam bioinformatic databases. The two proteins 131C_1256 and 131C_3144 were 27.8 and 23.3 times more abundant in 131C. Unfortunately, these two proteins did not contain any conserved domains according to BLASTp or pfam, and a putative function could not be assigned. Quantified Proteins with a Higher Abundance in 310F

The PST− 310F strain displayed higher abundances of 52 proteins, mainly belonging to the phycobilisome apparatus, the oxidative pentose phosphate pathway (oxPPP), glutathione metabolism, cysteine metabolism, repair, and geosmin biosynthesis (Table 2). Also, 310F had a higher number of hypothetical proteins for which no putative function could be assigned.

Environmental Information and Processing and Cellular Processes

Metabolic Proteins

Several proteins involved in transcriptional regulation, substrate binding, and transport were found to be more abundant in 131C. 131C_3664 (5.0) displayed similarity to the LuxR-family of transcriptional regulators. A homologue of 131C_3664 (All3660) was identified in Anabaena sp. PCC 7120 (hereafter Anabaena 7120), but no function has been assigned. Bacteria have been reported to use LuxR family response regulators for regulating quorum sensing genes.44 However, in cyanobacteria, the LuxR family has been proposed to regulate genes in response to the redox status of the cell.45 We identified the AbrB-like transcription factor, AbrB1 (3.1). AbrB-like transcription factors are unique to cyanobacteria, and all genomes analyzed to date encode at least two copies. In Synechocystis 6803, the two AbrB homologues correspond to Sll0359 (AbrB1/CalA/cyAbrB) and Sll0882 (AbrB2).46,47 AbrB1 has been implicated in the regulation of a wide range of cellular metabolic processes, such as regulation of the bidirectional hydrogenase (hox) genes,48 cell division,49 iron superoxide dismutase,50 and cylindrospermopsin.51 Interaction between AbrB1 and AbrB2 may be involved in modulating the C:N ratio via the codependent activation of nitrogen metabolism genes such as urtA, amt1, and glnB.52,53 Several putative nitrogen and nutrient-affiliated proteins were identified as more abundant in 131C than 310F. Part of the high-affinity urea permease complex consists of the substrate binding subunit, UrtA (18.9). In cyanobacteria, UrtA is the upregulated in response to a low nitrogen environment.54 131C_1256 (27.8) shows some similarity to Sll1704, a hypothetical protein found within Synechocystis 6803, but a function for this protein could not be postulated. A DevB-like protein (87.1) and HgdD (7.5) were identified within 131C. In Anabaena 7120, DevB and HgdD (together with DevAC) form a complex (DevBCA/HgdD) for the export of heterocyst specific glycolipids.55,56 Also, another DevBCA/ HgdD-like complex (All0809/8/7-TolC) has been identified within Anabaena 7120, and both exporters are vital for diazotrophic growth, but it is unknown if a related function is performed by the third homologue identified in 131C.57 The periplasmic binding protein of the N−I neutral amino acid transport system, NatB (8.6), was identified. NatB forms a high-affinity neutral amino acid transport system in conjunction with NatA and is most likely increased in abundance in an attempt to keep up with metabolic demand.58,59

Phycobilisome linker proteins and an orange carotenoid protein were more abundant in 310F. The phycobilisome linker proteins have two functions: (1) to provide structural integrity to the phycobilisome antennae subunits and (2) to mediate energy transfer from the phycobilisome subunits toward the reaction center. We identified the two phycobilisome linker proteins CpcC (2.7) and CpcG (2.9) to be more abundant in 310F. The orange carotenoid protein (6.5) acts as a defensive mechanism against light-induced stress via heat dissipation, as determined by Kerfeld and Kirilovsky.60 The proteins G6P1D (4.2), transaldolase (9.0), transketolase (2.8), and phosphoketolase (2.4) are involved in the oxPPP and CO2 fixation. Additionally, G6P1D is involved in glutathione metabolism along with isocitrate dehydrogenase (10.2), glutathione reductase (5.0), and leucyl aminopeptidase (2.8). Cysteine and sulfur metabolism have been closely coupled to glutathione, and the two proteins, CysK (7.7) and 3mercaptopyruvate sulfurtransferase (5.5), were more abundant in 310F. Of the two enzymes, CysK catalyzes essential reactions in the formation of cysteine, while 3-mercaptopyruvate sulfurtransferase catalyzes reactions generating thiosufate and pyruvate. Genetic Information and Processing

310F was found to be higher in abundance of proteins that are involved in cellular stress response and maintenance. The chaperones GroEL (2.3), GroES (7.4), DnaK2 (2.3), DspA (8.5), and UspA (7.5) consisted of the most characterized proteins in the genetic information processing category. The GroEL and GroES chaperones are found in the majority of bacteria and respond to a wide range of cellular stresses. GroEL and GroES form a complex to interact and ensure the correct folding of a wide range of proteins.61 Of the three homologues, DnaK2 is believed to be the sole protein involved in response to a broad range of stress conditions.62 Three DnaK homologues have been identified in Synechocystis 6803.63 Elevated levels of dnaK2 transcripts were seen in response to temperature, high-light intensities, and oxidative stress.62 DpsA is similar to the Alr3808 homologue of Anabaena 7120. Expression of Alr3808 is directed by FurA, a transcription factor responsible for activation of genes in response to iron and oxidative stress. A similar functional role of DspA in Synechococcus sp. PCC 7942 was presented by Peña and Bullerjahn.64 There are limited data regarding cyanobacterial UspA proteins, and most knowledge has been elucidated from 1479



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experiments with E. coli. Therefore, it must be noted that UspA may not perform a similar function in cyanobacteria. In E. coli, UspA seems to have a functional role in resistance to DNA damage. Mutational studies of UspA resulted in early death of cells, while overexpression blocked cells in a growth-arrested state.65 Other stress proteins identified are involved in cellular repair caused by oxidative stress. MsrA (6.9) is involved with methionine oxidation stress and catalyzes the specific reduction of methionine S-sulfoxide. A general antistress function is performed by the alkyl hydroperoxide reductase/peroxiredoxin, AhpC1 (5.5), via reduction of reactive species.

growth phase, leading to possible consequences for STX production within 131C. Saxitoxin Biosynthesis

The iTRAQ method has gained popularity in recent years for several advantages over 2-DE gels. We were able to confidently identify a total of seven proteins encoded within the putative sxt pathway for the first time. This is a surprising discovery considering secondary metabolite biosynthetic proteins are thought to be low in abundance. Identification of these proteins provides confidence in the sensitivity of the iTRAQ method for analysis of cyanobacterial proteomics and allows for future experiments to determine environmental conditions that may alter abundance of cyanobacterial toxin proteins. The putative constitutive expression of all Sxt proteins as well as the high amount of energy and substrates required for STX biosynthesis equates to a large total net energy expenditure.7 From the higher abundance of photosynthetic CO2 fixation proteins and increased growth rate of 131C, it is proposed that this strain has a higher net energy pool available for cellular metabolism. If this is true, it raises three possibilities in regards to the higher energy 131C ecotype and PST production. (i) By some unknown mechanism, the PSTs allow 131C to achieve a higher net energy pool via increased photosynthesis and CO2 fixation. A major divergence between 131C and 310F seems to be the abundance of photosynthetic proteins and anti-ROS. Two independent comparative proteomic studies of microcystin-producing and nontoxic M. aeruginosa showed a higher abundance of photosynthetic and metabolic proteins in the toxic strain.17,18 A consequence of a high rate of photosynthesis is the accumulation of ROS. Again, the fitness of toxic M. aeruginosa increased via binding of microcystin to proteins in vivo in response to high light and oxidative stress conditions.69 In 131C, the PSTs may also help increase fitness by allowing a higher rate of photosynthesis or by reducing damage caused by ROS compared with the nontoxic 310F. (ii) The higher net energy production achieved by 131C may allow for the energyintensive production of the PSTs. This may have implications for the genetic evolution of lower energy strains, such as 310F. It has been hypothesized that the sxt gene cluster was excised from strains that are no longer toxic.6,70,71 We have identified sxt gene fragments within 310F that support the loss of toxicity theory (D’Agostino P. M., unpublished). When 310F evolved into a lower energy producing ecotype, its survival may have depended on the excision of the sxt cluster from the 310F genome, as it could no longer support STX biosynthesis. (iii) The PSTs may be unlinked to the higher energy production of 131C compared with 310F. Only a single strain of toxic and nontoxic A. circinalis was analyzed in this study, thus, it is difficult to correlate STX production with cellular energy production and growth. Future studies need to include more strains to gain a greater understanding between PST+ and STX− A. circinalis at a proteomic level to determine if the observations seen in this study are simply due to strain-specific differences or if these results correlate with toxicity. A higher C:N ratio may also have an impact on the level of toxicity in 131C. According to the STX pathway proposed by Kellmann et al.,7 each molecule of STX uses two arginine residues and one 2OG (α-ketoglutarate) as substrate. Arginine increased STX and sxt transcripts in the PST+ cyanobacterium C. raciborskii T3.72 However, the effect of 2OG on transcription and STX biosynthesis has not been investigated. The C:N status is sensed by the presence (binding) of 2OG to the

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DISCUSSION In this study, we investigated two strains of A. circinalis that share very high sequence similarity at the 16S rRNA gene level (>99%) but vary in their capability to biosynthesize the PSTs. These results have identified previously unknown differences between a toxic and nontoxic strain of A. circinalis at the protein level. Under identical culture conditions, the two strains exhibited differential proteomic profiles, particularly among homologous proteins. This observation indicates that the proteomic profiles between these two strains have been hardwired, potentially as a consequence of their previous ecological context. Evaluation of the PST+ A. circinalis 131C Proteome

Comparative proteomics using iTRAQ revealed PST+ 131C to be more abundant in proteins belonging to photosynthesis and electron transport when compared with 310F. Photosynthesis and electron transport work to increase the pmf and reducing equivalents, thus increasing the energy available for cellular work and metabolic functions. Multiple proteins of the PSII complex, phycobilisomes, PSII repair, and Cyt b6/f were more abundant in 131C compared with 310F. A possible indication of the higher amount of energy may be observed by the increased growth rate of 131C compared with 310F (Supporting Information 3). Photosynthesis is tightly coupled to CO2 fixation and the CCM. The higher abundance of CCM within 131C is likely due to the increase in photosynthetically derived energy. The carboxysomes allow CO2 fixation via the Calvin cycle, which provides carbon skeletons for cellular growth. This is supported by the higher abundance of GlgC, which indicates that the cells are actively synthesizing glycogen, a process that occurs during times of excess carbon within the cell.66 The global nitrogen regulator NtcA is known to regulate the high-affinity urea substrate binding protein encoded by urtA as well as the devBCA operon.54,67 NtcA is activated by 2oxoglutarate (2OG), a sensor for the C:N ratio within cyanobacteria.68 Likewise, AbrB1 is thought to form a complex with AbrB2 and alter transcription of nitrogen-related genes as a response to the C:N ratio.52 The A. circinalis cultures used in this study were grown in NO3− replete media, and hence the cells were not starved of nitrogen. It is possible that the increased abundance of UrtA and the DevB/HgdD-like complex in 131C is not the result of nitrogen starvation but instead due to increased baseline levels of NtcA and AbrB1 activation. Knowledge of carbon and nitrogen, metabolic pathways in cyanobacteria and the observed protein abundances in this study may indicate that 131C is a higher C:N ecotype than 310F. Consequently, 131C may also have a higher intracellular concentration of 2OG than 310F during this 1480



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Figure 2. Model illustrating the putative metabolic pathways of 131C. The high abundance of photosynthesis and Calvin cycle proteins are likely to lead to the production of high-energy molecules (NADPH and ATP) and a high C:N ratio. NADPH and ATP enter the carboxysome to power carbon fixation via the Calvin cycle. Excess carbon is stored in the form of glycogen and results in increased C:N ratio in the form of 2OG. The accumulation of 2OG then activates the transcriptional regulator NtcA. The high C:N ratio can be observed by increases in the urea transport and DevBCA/HgdD complexes, which are induced by NtcA when the intracellular C:N ratio is high, in addition to proteins involved in glycogen biosynthesis. The transcriptional regulator AbrB1 is thought to be involved in regulation of the C:N ratio; however, whether this occurs as a response to 2OG levels is currently unknown. Also, the high C:N ratio may affect STX biosynthesis via the 2OG-dependent dioxygenase SxtS. PSII, photosystem II; Cyt b6/f, cytochrome b6/f; PSI, photosystem I; pmf, proton motive force; FNR, ferredoxin:NADP+ oxidoreductase; 2OG, 2oxoglutarate; STX, saxitoxin.

signaling protein NtcA.73,74 The observed protein abundances in this study have led to the hypothesis that 131C is capable of a higher basal C:N ratio when compared with 310F. It is possible the putative higher basal C:N in 131C compared with 310F may result in a higher baseline intracellular concentration of 2OG compared with the PST− 310F. SxtS is a 2OGdependent dioxygenase putatively involved in oxygenation and ring formation of STX.6,7,75 Therefore, we hypothesize that SxtS is posttranslationaly regulated by 2OG and acts as a regulation checkpoint in regards to STX biosynthesis (Figure 2). Thus, the high intracellular concentration of 2OG (via a high C:N ratio) is used as a substrate by SxtS with succinate and CO2 forming the byproducts of the reaction.7 Lastly, photosynthesis would provide the reducing equivalents needed during several steps of STX biosynthesis. While our experiment does not provide direct evidence to support this theory, we believe that the scenario warrants further investigation via the direct measurement of 2OG, photosynthesis, and PST production within 131C and 310F.

that the corresponding protein has multiple routes for nonphotosynthetic carbon metabolism.76 Increased abundance of chaperone and anti-ROS proteins was observed within 310F when compared with 131C. The chaperone proteins DnaK, GroEL, and GroES that are known to respond to a range of stress responses in bacteria were identified in our study. We also identified the less studied chaperones DspA and UspA in addition to a bacterial stress protein containing a ferritin-like domain. Finally, the identification of orange carotenoid proteins indicates a response to light stress.60 310F has an elevated level of anti-ROS proteins AhpC1 and MsrA compared with 131C. Glutathione was also was abundant in 310F and been shown to have an anti-ROS stress capacity in bacteria and may account for the elevated levels of proteins involved in glutathione and cysteine metabolism.77 A scan of four A. circinalis genomes 131C, 310F, A. circinalis ACBU02, and A. circinalis ACFR02 could not identify a gene-encoding catalase when the Anabaena 7120 Mn-catalase (alr0998) was used as bait for this search. Therefore, it is possible that AhpC1-, MsrA-, and glutathione/cysteine-related proteins are elevated in an attempt to counter redox stress within 310F. The presence of numerous orange carotenoid, chaperone, and anti-ROS proteins indicates that the cell is under stress. These results corroborate the low abundance of PSII, the increased levels of phycobilisome linker proteins, and the increase in energy production via the oxPPP. On the basis of the observed protein abundances, it is possible that 310F is an ecotype adapted to lower light environments. We believe 310F, when compared with 131C, is unable to cope with the light intensities used in the study, and as a result, 310F displays a cellular stress phenotype under standard laboratory conditions.

PST− A. circinalis 310F Is an Ecotype under Continual Cellular Stress under Laboratory Culture Conditions

The 310F proteome contained a higher abundance of phycobilisome linker proteins and those present in the oxPPP. An increase in linker proteins has been observed in stressed cells and is thought to increase electron transfer efficiency from the phycobilisomes to the photosystem reaction center in an effort to generate energy more efficiently.16 The proteins G6P1D, transaldolase, and transketolase are involved in oxPPP and were found to be more abundant in 310F. G6P1D is encoded by zwf, and knockouts of this gene indicate 1481



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CONCLUSIONS Overall, the distinct proteome profiles of 131C and 310F under identical growth conditions indicate that these strains are likely to occupy different ecological niches and are two different ecotypes. We have identified several key avenues for future investigation involving possible posttranslational regulation of STX biosynthesis and evolution leading to different A. circinalis ecotypes. In the future, more studies are needed to ascertain whether a correlation exists between ecotypes identified in this study and STX production by increasing the number of PST+ and PST− A. circinalis species analyzed. Knockout of the sxt cluster in 131C in conjunction with proteomics will directly identify metabolic pathways affected by STX production with the ultimate aim of identifying the cellular function of the PSTs.

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Cubeddu, Elise Wright, and Daniel Kirk for carefully reading and editing the manuscript.

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ABBREVIATIONS PSTs, paralytic shellfish toxins; STX, saxitoxin; sxt, saxitoxin biosynthetic gene cluster; 131C, Anabaena circinalis AWQC131C; 310F, Anabaena circinalis AWQC310F; PST+, a paralytic shellfish toxin-producing organism; PST−, a nonparalytic shellfish toxin-producing organism; 2-DE, two-dimensional SDS-PAGE; Synechocystis 6803, Synechocystis sp. PCC 6803; iTRAQ, isobaric tags for relative and absolute quantitation; chl a, chlorophyll a; SDS, sodium dodecyl sulfate; TCEP, tris(2-carboxyethyl)phosphine; MMTS, s-methyl methanethiosulfonate; SCX, strong cation exchange; HPLC, highperformance liquid chromatography; IDA, information-dependent acquisition mode; m/z, mass-to-charge ratio; FDR, false discovery rate; ORF, open reading frame; COG, clusters of orthologous groups of proteins; KEGG, Kyoto Encyclopedia of Genes and Genomes; PSI, photosystem I; PSII, photosystem II; Cyt b 6 /f, cytochrome b 6 /f ; FNR, ferredoxin: NADP + oxidoreductase; ROS, reactive oxygen species; CCM, carbon concentrating mechanism; Anabaena 7120, Anabaena sp. PCC 7120; hox, bidirectional hydrogenase gene cluster; oxPPP, oxidative pentose phosphate pathway; G6P1D, glucose-6phosphate 1-dehydrogenase; 2OG, 2-oxoglutarate

ASSOCIATED CONTENT

S Supporting Information *

Supporting Information 1: Figure displaying the two 4-plex iTRAQ runs. Samples 114 and 115 from each run were combined, and their data were used for analysis in this study. Samples 116 and 117 were used for a separate publication. Supporting Information 2: iTRAQ-P and iTRAQ-N FDR data for 131C and 310F databases. Data were generated by ProteinPilot performed by APAF. Supporting Information 3: The proteome characteristics presented in a results and discussion format. This includes data obtained from bioinformatic tools and a comparison of our identified proteome with the theoretical proteome. These data are then compared with other cyanobacterial proteomes as outlined in other cyanobacterial proteomic studies. Supporting Information 4: Raw data obtained from bioinformatic tools. Supporting Information 5: List of proteins identified via iTRAQ and their putative function. Supporting Information 6: Presentation of identified proteins categorized into functional groups according to KEGG. Supporting Information 7: List of raw background-corrected ratios generated from the ProteinPilot output. These include unused protscore, total protscore, % coverage, %coverage(50), %coverage(95), peptides(95%), ratio, ratio Pval, ratio error factor, ratio lower Cl, and ratio upper Cl. This material is available free of charge via the Internet at http://pubs.acs.org.

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REFERENCES

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AUTHOR INFORMATION

Corresponding Author

*Phone: +(612) 4620 3521. Fax: +(612) 4620 3025. E-mail: m. moffi[email protected]. Author Contributions

The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS This research was funded by the Australian Research Council, grant number DP0880264. Proteomic work was undertaken at APAF. The infrastructure was provided by the Australian Government through the National Collaborative Research Infrastructure Strategy (NCRIS). P.M.D. was supported by an Australian Postgraduate Award. We thank Rali Alexova, Liza 1482



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