Marine Proteomics: A Critical Assessment of an Emerging Technology

Review pubs.acs.org/jnp

Marine Proteomics: A Critical Assessment of an Emerging Technology Marc Slattery,*,†,§,∥ Sridevi Ankisetty,† Jone Corrales,‡ K. Erica Marsh-Hunkin,† Deborah J. Gochfeld,§,∥ Kristine L. Willett,‡,§,∥ and John M. Rimoldi⊥,§,∥ †

Department of Pharmacognosy, ‡Department of Pharmacology, §National Center for Natural Products Research, ⊥Department of Medicinal Chemistry, and ∥Environmental Toxicology Research Program, School of Pharmacy, The University of Mississippi, University, Mississippi 38677, United States ABSTRACT: The application of proteomics to marine sciences has increased in recent years because the proteome represents the interface between genotypic and phenotypic variability and, thus, corresponds to the broadest possible biomarker for ecophysiological responses and adaptations. Likewise, proteomics can provide important functional information regarding biosynthetic pathways, as well as insights into mechanism of action, of novel marine natural products. The goal of this review is to (1) explore the application of proteomics methodologies to marine systems, (2) assess the technical approaches that have been used, and (3) evaluate the pros and cons of this proteomic research, with the intent of providing a critical analysis of its future roles in marine sciences. To date, proteomics techniques have been utilized to investigate marine microbe, plant, invertebrate, and vertebrate physiology, developmental biology, seafood safety, susceptibility to disease, and responses to environmental change. However, marine proteomics studies often suffer from poor experimental design, sample processing/optimization difficulties, and data analysis/ interpretation issues. Moreover, a major limitation is the lack of available annotated genomes and proteomes for most marine organisms, including several “model species”. Even with these challenges in mind, there is no doubt that marine proteomics is a rapidly expanding and powerful integrative molecular research tool from which our knowledge of the marine environment, and the natural products from this resource, will be significantly expanded.

W

ith the completion of the human genome in 2000,1 the “omics” revolution ramped up to address comparative questions related to genes and their products in every field of biology, including marine sciences.2 Proteomics has emerged as perhaps the most significant technology in the “omics” era (Figure 1).3 Specifically, the proteome is what integrates changes in gene expression, mRNA stability, and protein post-translational modification (PTM) and turnover, in response to environmental change. As such, it represents the interface between genotypic and phenotypic variability and, thus, the broadest possible biomarker for eco-physiological responses and adaptations.4 Proteomics is slowly gaining support in a diversity of marine fields, including biotechnology, environmental toxicology, and aquaculture (Table 1).5−7 However, the application of proteomics within marine systems and research fields, including marine natural products chemistry, remains largely unexplored and suffers from a variety of difficulties at levels ranging from experimental design and sample processing/optimization strategies to data analysis/ interpretation. The goal of this review is to (1) explore the application of proteomic methodologies in marine systems, (2) assess the technical approaches that have been used, and (3) evaluate the pros and cons of proteomic research, with the intent of providing a critical analysis of its future roles in marine sciences. It is beyond the scope of this article to describe proteomic techniques in detail; the interested scientist is directed to several extensive methodological review articles.8−10 However, © 2012 American Chemical Society and American Society of Pharmacognosy

we will provide a brief history of the technical advancements that have structured the field of proteomics over the last two decades. We will then provide an overview of several of the more comprehensive studies that have applied proteomic techniques toward the elucidation of structure and function in marine organisms. A subset of those papers will be further utilized to demonstrate some of the problems associated with (1) experimental design, (2) sample collection/handling, (3) protein extraction and optimization, (4) protein identification and quantification, and (5) protein validation and data analysis. Finally, we will address the future ramifications of proteomics in marine sciences.

■

DISCUSSION Techniques. Protein identification and quantification is a complex issue that can be exacerbated by the many PTMs (e.g., phosphorylation, methylation, glycosylation, acetylation, oxidation, nitrosylation, and ubiquitination) that can occur in a timeor condition-specific manner. Originally, proteins were studied using immunological techniques, but these methods required knowledge of the target protein and the availability of a specific antibody. With the development of two-dimensional gel electrophoresis (2-DE), which separates complex mixtures of Received: May 24, 2012 Published: September 25, 2012 1833

dx.doi.org/10.1021/np300366a | J. Nat. Prod. 2012, 75, 1833−1877

Journal of Natural Products

Review

Figure 1. Overview of “omics” related research approaches. Proteomics is one of the most complex fields of science, as it represents the interface between genotypic and phenotypic variation, and it provides broad information regarding eco-physiological responses and adaptations, including important functional information related to biosynthesis and natural products expression.

transform ion cyclotron [FT-ICR]) and include a variety of instrument configurations. The review by Yates et al.13 provides an excellent discourse on the performance comparisons and applications of a variety of mass analyzers and instrument configurations most commonly used in proteomics. Applications. Marine Microorganisms. Marine microbes, and particularly bacteria (including cyanobacteria), are notoriously difficult to culture.22 Genomics has provided technical opportunities to explore marine microbial diversity,23 and proteomics is providing further insights into microbial taxonomy, physiology, metabolism, and ecology, as well as biofilm formation, host−pathogen interactions, antibiotic resistance mechanisms, and disease transmission factors, among others. To date, much of the research on microbial proteomics has focused on model organisms for which entire genome sequences are readily available, thereby improving access to corresponding protein information (Table 2). Several marine Vibrio species serve as model organisms for pathogenicity, including V. cholerae, V. vulnif icus, V. parahaemolyticus, and V. salmonicida. The earliest proteomics studies of marine bacteria utilized 2-DE, in combination with MS, on these Vibrio species,24−26 and the protocol is still widely used (e.g., see references in Table 1). However, recent advances in separation technologies, including affinity and strong cation exchange (SCX) chromatography, have been used instead of 2-DE separation techniques, and the MS techniques have also improved to include ESI and tandem MS approaches. Recently, the proteomes of unculturable symbiotic Vibrio spp. associated with the light organ of the squid Euprymna scolopes have been examined by overlaying 1D (sodium dodecyl sulfate polyacrylamide gel electrophoresis: SDS-PAGE) and 2-DE to assess visible differences representing protein regulation.27 In addition to Vibrio spp., the proteomes of Pseudoalteromonas spp. have been examined for their bioactive compound production.28 Unculturable symbionts of the deep-sea tube worm Riftia pachyptila have recently been examined using the aforementioned gel visualization approaches.29 The photosynthetic cyanobacterium Prochlorococcus has become an important model for heat shock stress responses, light adaptation, nutrient utilization, and secondary metabolite production.30,36−38 The Archaea is an ancient group of microorganisms, distinct from bacteria, that provides important insights into the evolution of life and specifically into extremophile strategies.30,31 The proteome of Methanococcoides burtonii has been examined extensively with respect to cold temperature adaptation.32−35 These studies have benefited from recent isobaric tags for

proteins based on small differences in their native and modified states, the broader applications of proteomic profiling were realized. Currently, much more sensitive, albeit instrumentation-intensive, techniques are available; the result has been an explosion in protein-related research similar to the genomic revolution a decade earlier. Three complementary but distinct proteomic tactics have been described and are broadly categorized as bottom-up, middle-down, and top-down. These are employed for proteinpeptide identification and characterization (Figure 2).11 In bottom-up proteomics (i.e., shotgun or discovery proteomics), complex protein mixtures are initially subjected to proteolysis, and the resulting peptide fragments are subsequently analyzed by LCMS/MS, requiring the use of high-resolution ion-trap, quadrupole time-of-flight (Q-TOF), or hybrid ion-trap/orbitrap mass spectrometers.8,12,13 Top-down approaches differ insofar as intact proteins are directly subjected to gas-phase fragmentation for MS analysis14,15 and generally have more stringent technological requirements,11 including the challenge of separating intact proteins coupled with the demand of mass-accurate instruments linear trap quadrupole (e.g., LTQ-Orbitrap).16 Middle-down proteomics, also referred to as extended range proteomic analysis, uses restricted protein cleavage protocols to generate longer peptide fragments when compared to bottom-up approaches.11,17 Both top-down and middle-down strategies carry a selective advantage of characterizing distinct protein isoforms and/or protein PTMs. Additional platform subclassification criteria have been proposed recently and are based on methods of sample preparation, separation protocols, and the type of mass spectrometer employed.18 Irrespective of the strategy adopted, mass spectrometry systems incorporate an ion source and associated optics, a mass analyzer, and data processing capabilities. Ionization techniques commonly used in proteomics include the soft-ionization methods of nanoelectrospray ionization (ESI) and matrix-assisted laser desorption ionization (MALDI). The evolution of ionization sources has advanced to include desorption/ ionization on silicon, a matrix-free MALDI technique,19 and laserspray ionization, which allows for the analysis of proteins directly from tissue using atmospheric pressure ionization mass spectrometers.20 The emergence of hard-ionization sources, such as inductively coupled plasma (ICP), provides compound-independent elemental analysis and detection and may be considered a versatile partner to ESI or MALDI in the quantification of multiple heteroatoms in metal-containing proteins.21 Mass analyzers are broadly categorized into scanning and ion-beam analyzers (quadrupole, TOF) and the trapping analyzers (ion-trap, orbitrap, Fourier 1834


marine microbial organisms

protein changes in response to temperature, pH, and salinity investigate virulence of Vibrio species, focus on metalloproteases proteomic analysis examining adherence of pathogenic bacteria to mucosal surfaces investigating virulence factors

bacterium, Vibrio anguillarum

bacterium, Vibrio corallyticus

bacterium, Vibrio salmonicida

bacterium, Vibrio splendidus

adaptation to cold

bacterium, Sphingopyxis alaskensis

tolerance to changes in salinity

proteomic responses to nutrient limitation


bacterium, Vibrio anguillarum

adaptive response to visible and ultraviolet light

research focus


organism

Table 1. Review of Marine Proteomics Studiesa

1835

2-DE, MALDITOF MS,

1-DE, 2DE, nanoLC-MS/MS (Q-TOF), ProteinLynx, Mascot, NCBI database 1-DE, 2DE, nanoLC-MS/MS (Q-TOF), ProteinLynx, NCBInr database, de novo sequencing

2-DE, MALDITOF MS/MS, Mascot, NCBI database

2-DE (radiolabeled vs silver-stained), nanoLC-MS/MS (ESI), SEQUEST, NCBInr database and Novosphingobium aromaticiviorans database, SwissProt, BLAST metabolic labeling, 1-DE, nanoLCMS/MS, SEQUEST, S. alaskensis database 2-DE, nanoLCMS/MS (QTOF), Mascot, SwissProt, NCBInr database

iTRAQ labeling; LC-MS/MS

methodology

bacterial growth in presence of skin mucus involved increase in proteins associated with motility, oxidative defense, and general stress responses toxicity of oyster pathogen correlated with metalloprotease

comparative analyses of wild-type and mutant strains revealed differential protein expression

growth, survival, and motility increased at lower salinities; possible osmoregulatory mechanism environmental stressors resulted in differential expression of proteins

quantitative differences were detected between temperature treatments

differential expression during growth phases, broad functional categories highlighted key factors in response to solar radiation use of both methods increased total number of proteins identified; crossspecies comparison helps to infer regulatory pathways

summary

217

N/A

126

NR

NR

500

6

75

19 between wildtype and mutant

40

6

102 of 752; 20 of 1023

radiolabeled 752; silver-stained 1023

30

119; 46 of these common between two growth conditions

differential expression

N/A

2DE

research findings

56

27

55

40 of 64

5

1736

12

811

validated ID

Binesse et al. 2008196

Raeder et al. 2007195

De O Santos et al. 2011194

Kim et al. 2012193

Kao et al. 2009192

Ting et al. 2010191

Ostrowski et al. 2004190

MatallanaSurget et al. 2009167

ref

identified possible biomarker for environmental stress in bacteria

notes

Journal of Natural Products Review


organism

physiology of cellular compartments in fast growing bacteria 2-DE reference map for future studies utilizing sequenced genome analyze proteome using multiple techniques for global metabolic pathways evaluating use of 2-DIGE

bacterium, Pseudoalteromonas haloplanktis

bacterium, Rhodopirellula baltica

1836

bacterium, Pirellula sp. strain 1

bacterium, Rhodopirellula baltica

bacterium, Pseudoalteromonas tunicata

investigate regulation and biosynthesis of pigments and bioactive compounds membrane proteome changes associated with adhesion

V. splendidus specific database 2-DIGE, MALDITOF MS

in oyster pathogen investigating iron acquisition system underlying pathogenesis establish complete proteome, evaluate expression under varying environmental conditions establish exoproteome (i.e., all extracellular proteins)

1-DE, 2-DE, MALDI-TOF MS, Mascot, nanoLC-MS/MS, SEQUEST, R. baltica specific database 2-DIGE, DeCyder and ImageMaster software

2-DE, MALDITOF MS

1-DE, nanoLCMS/MS, Mascot, specific R. pomeroyi database iTRAQ, SCX, nanoLC-MS/MS, ProQuant, Mascot, P. tunicata specific database blue native (BN)/ SDS 2-DE, MALDI-TOF MS, LC-MS/MS, Mascot, NCBInr database 2-DE, MALDITOF MS, Mascot, P. haloplanktis database

1-DE, nanoLCMS/MS, Mascot, specific R. pomeroyi database

methodology

research focus

bacterium, Pseudoalteromonas tunicata

bacterium, Ruegeria pomeroyi

bacterium, Ruegeria pomeroyi

bacterium, Vibrio vulnificus

Table 1. continued

2-DIGE more efficient; 5 parallel gels adequate for statistical confidence

multiple techniques yielded 709 novel proteins to published proteome

1688

1115

24

N/A

N/A

N/A

310 (cytoplasmic), 381 (periplasmic)

high capacity for protein synthesis, efficient amino acid utilzation, and substrate transport all played a role in growth ability 626 distinct protein spots, corresponding to 558 different genes 626

N/A

17

N/A

>40 protein spots observed

N/A

N/A

127


469

1963

2500

2DE

proteomic changes observed during transition from planktonic to adherent states

identified 60 proteins in exoproteome; also three highly abundant proteins for further testing identified secretome; type-II secretion pathway important in iron acquisition

expression of proteins involved occurs in early to mid logarithmic growth first complete proteome for this species; allowed incorporation of functional genomic data

summary

research findings

N/A

709

3

212

24

182 of 370 total

60

N/A

75

validated ID

Gade et al. 2003204

Hieu et al. 2008203

Gade et al. 2005202

Wilmes et al. 2011201

Hoke et al. 2011200

Evans et al. 200732

Christie-Oleza and Armengaud 2010199

Christie-Oleza et al. 2012198

Miyamoto et al. 2009197

ref

notes



nanoLC-MS/MS (ESI), MALDIMS/MS, Mascot

adaptation to stationary-phase survival in bacteria

phage resistance response to find proteins involved in conversion of light to biochemical energy study metabolism of uncultured endosymbiont

bacterium, Candidatus pelagibacter ubique

bacterium, Silicobacter pomeroyi DSS-3

bacteria; Alphaproteobacteria sp., Gammaproteobacteria sp.

1837

endosymbiont bacterium of marine tubeworm, Rif tia pachyptila estuarine microbial communities metaproteomic study of microbial assemblages

proteomics underlying cellulolytic properties of a marine bacteria

investigating iron limitation

bacterium, Candidatus pelagibacter ubique

bacterium, Saccharophagus degradans

LC-MS/MS, SEQUEST software, C. pelagibacter ubique database, developed their own AMT library 1-DE, HPLC-MS/ MS, LC-MS/MS (Q-TOF), Mascot, SEQUEST, S. degradans database, MSDBnr database 2-DE, MALDITOF MS

physiological responses to heavy metal exposures

bacterium, Pseudomonas fluorescens

1-DE, 2-DE, MALDI-TOF MS, LC-MS/MS, MS BLAST

1-DE, 2-DE

microarray, HPLCMS/MS (ESI), accurate mass and time (AMT) library, PeptideProphet software

metaproteomics potential to link functional diversity and biological

protein modification underlies phage resistance; possibly due to 4 proteins ionization technique critical for success in proteomics applications; in this case, MALDI was ideal better understanding of symbiont’s response to oxidative stress

presents genomic, proteomic and functional analyses of the cellulase system in this species

adaptive response to stationary phase included increasing proteins for homeostasis

excluded several possible mechanisms; supported adsorption inhibition as possible mechanism cadmium and copper appeared to slow metabolism while zinc had a stimulating effect combining transcriptomic and proteomic data offered insights into cellular response to iron limitation at the translational level

2-DE, MALDITOF MS, Mascot

investigate mechanisms supporting phage resistance

bacterium, Roseobacter denitrif icans OCh114 2-DE

summary

methodology

organism

research focus

Table 1. continued

17

16, 29, 0, 0

396, 405, 362, 353 (metaproteome comparisons)

N/A

N/A

220

4

NR

52 of 616

NR

N/A

N/A

18 of 216

65 (zinc), 68 (copper), 103 (cadmium)

NR

N/A

12


NR

2DE

research findings validated ID

3

NR

167, 22

1

7

616

NR

N/A

7

ref

Kan et al. 2005212

Markert et al. 200733

Stapels et al. 2004211

Zhang et al. 2009210

Taylor et al. 2006209

Sowell et al. 2008208

Smith et al. 2010207

Poirier et al. 2008206

Huang et al. 2010205

technical applications directly applicable to marine bacteria

microarray and proteomic data point to one binding protein as potential biomarker for iron limitation

notes



review article

bacteria

1838

light adaptation

adaptation to salt stress in a halotolerant species

adaptation to salt stress in a halotolerant and mildly

cyanobacterium, Prochlorococcus marinus

cyanobacterium, Euhalothece sp. BAA001

cyanobacteria, Euhalothece sp. BAA001,

review article

review article

bacteria

microorganisms in extreme environments

review article

bacteria

review article

rapid technique to sort microorganism groups by mass spectral fingerprint; interand intragroup differentiation

bacteria from four marine sponge spp.

bacteria and Archaea

research focus

organism

Table 1. continued

iTRAQ labeling, SCX, nanoLCESI-MS/MS, ProQuant software, JGI P. marinus database stable isotope labeling, 1-DE, LC-QTOF-MS/ MS, Mascot, NCBInr database, BLAST, PCR validation stable isotope labeling, iTRAQ labeling, 1-DE, LC-QTOF-MS/

N/A

N/A

N/A

N/A

16S-rDNA sequencing, intact-cell MALDI TOF (ICM-MS), principal coordinate analysis (PCO) for phylogenetics N/A

methodology

salt adaptation strategies shared by both species; lower salinity levels

integration of genomic and proteomic approaches in marine microbial ecology metaproteomics and functional gene expression in microbial ecosystems discusses communitywide role of bacteria and Archaea in nutrient utilization and energy transduction introduction of basic principles of proteomic techniques and their application to extremophiles 11% of proteome identified; downregulation in photosystem-related proteins; upregulation of stress-related chaperone nonsaline and higher salt conditions induced stress responses

proteomics of marine bacteria, first approaches and newer technology reviewed

processes in communities ICM-MS resolved identities better at species level

summary

N/A

N/A

15 of 184

72 of 383

21 of 340

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

N/A

3 in Pseudoalteromonas spp., used as species specific biomarkers


N/A

2DE

research findings

70

72

15

N/A

N/A

N/A

N/A

N/A

N/A

validated ID

Pandhal et al. 2009217

Pandhal et al. 2008a216

Pandhal et al. 200736

Burg et al. 201135

Morris et al. 201034

Wilmes and Bond 2006215

Thomas et al. 2007214

Schweder et al. 200822

Dieckmann et al. 2005213

ref

demonstrated applicability of iTRAQ in

summary of first proteomics applications in marine bacteria

notes



organism

1839

characterize virion structural proteins of photosynthetic phage thermal regulation of growth

cyanomyovirus, S-PM2

Archaea, Methanococcoides burtonii

cyanobacteria

cyanobacteria and bacteria: Synechococcus sp., Micromonas pusilla, Halmonas variabilis

evaluation of microbial community preservation techniques for proteomic identifications review article

evaluating proteome of nitrogen-fixer under different nitrogen levels investigating iron limitation

cyanobacterium, Trichodesmium erthraeum

nitrogen-fixing diazotroph, Crocosphaera watsonii

CO2-concentrating mechanism in a marine symbiont

halotolerant species

research focus

cyanobacterium, Synechococcus WH8102

Synechocystis sp. PCC6803

Table 1. continued

1-DE, nanoLCMS/MS, ProteinLynx, SwissProt with species-specific additions 2-DE, LC/ESIMS/MS, M. burtonii genome specific database and SEQUEST, NCBInr database and Mascot

N/A

1-DE, nanoLCMS/MS (QTOF), Mascot, NCBInr database

SCX, nanoLC-MS/ MS, SEQUEST software, PeptideProphet, Scaffold 2.0,

MS, Mascot, NCBI Synechocystis database, MSQuant software 1-DE, 2-DE, MALDI-TOF MS, DataExplorer, Mascot, Synechococcus specific database 2-DE, MALDITOF MS, Mascot, NCBInr database

methodology

differential protein patterns showed upand downregulation in certain proteins; main functions methanogenesis and energy generation

mini-review of cyanobacteria and salt adaptation; also focuses on introducing proteomic technologies and advances identified 12 novel structural proteins compared to control strain

12

54

237

N/A

N/A

NR

17 of 61

160 of 1108

N/A

substantial daily variation in proteins involved in nitrogen fixation and photosynthesis utilized reduced iron requirement microwave fixation as preservation technique produced viable proteomic samples N/A

150

1106

better understanding of physiology underlying nitrogen fixation

0


NR

2DE

CO2 transport system possibly not as adaptable in cyanobacteria

stimulate stress proteins in Synechocystis

summary

research findings

43 with M. burtonii database, only 10 with NCBInr database

24 of 39 for T4, 12 of 39 for SPM2

N/A

NR

9 (targeted)

94

9 of 57

validated ID

Goodchild et al. 2004a28

Clokie et al. 2008222

Pandhal et al. 2008b221

Mary et al. 2010220

Saito et al. 2011219

Sandh et al. 2011218

Gonzales et al. 200537

ref

notes cross-species comparisons



marine plants and eukaryotic photosynthesizers

1840

diatom, Fragilariopsis cylindrus

diatoms: Thalassiosira pseudonana, Phaeodactylum tricornutum

effect of salinity increase on proteins associated with dimethylsulfoniopropionate (DMSP) metabolism in a sea-ice diatom

proteome comparison of nitrogen depleted vs repleted cultures thylakoid membrane proteome characterization

diatom, Thalassiosira pseudonana

proteome investigation of Archaea with genome analysis

Archaea, Thermococcus gammatolerans

biomarker discovery following benzo (a)pyrene (36.45 μg/L) exposure

obtain functional data for hypothetical proteins


diatom, Thalassiosira pseudonana

mechanisms underlying adaptation to cold


research focus mechanisms underlying adaptation to cold

organism


Table 1. continued

2-DE, MALDITOF, nanoLCMS/MS (LTQ), F. cylindrus v1 genome filtered and nonfiltered databases

2-DE, MALDITOF, SwissProt trEMBL database, KEGG categorization 2-DE, LC-ESI MS/ MS, NCBI species specific database

SCX, nanoLC-MS/ MS, Mascot software, SEQUEST software 1-DE, nanoLCMS/MS, Mascot, two specific databases (TGAM_ORF0 and TGAM_CDS1) iTRAQ, SCX, LCESI-MS/MS, species-specific database

LC-MS/MS, LC/ LC-MS/MS, Mascot software, SEQUEST software ICAT chromatography, LC-MS/MS

methodology

upregulation in the DMSP transaminase synthesis pathway as well as superoxide dismutase, glutathione S-transferase and vitamin B6; downregulation associated with photosynthesis, fucoxanthin-

966

NR

3310

2-DE: 80; MS: 52 out of 149 proteins identified

N/A

146

13

N/A

N/A

established genome sequence of T. gammatolerans and genome-wide proteome N/A

N/A

N/A

gene context analysis valuable tool

regulated protein functions: metabolism, photosynthesis and transport effects on photosynthesis and metabolism of proteins and carbohydrates two novel proteins identified: a diatomspecific photosystem I protein and a centric diatom speciesspecific plastidtargeted protein

14

N/A

163 proteins identified; 14 differentially expressed at experimental temperatures

differential expression N/A

2DE N/A

528 proteins identified total; 391 linked to biological processes

summary


149 (39 MALDI, 110 LC-MS)

105

65

308

250 of 1101

55 of 135

163

47 of 528

ref

Lyon et al. 2011226

Grouneva et al. 2011225

Hockin et al. 2012182

Carvalho and Lettieri 2011224

Zivanovic et al. 2009223

Saunders et al. 200531

Goodchild et al. 200530

Goodchild et al. 2004b29

description of the molecular distribution of the light harvesting complex proteins in diatoms

using ICAT, 30 proteins found not previously identified by LC-MS/MS or LC/LC-MS/ MS

notes



1841

dinoflagellates (harmful algal bloom species): Alexandrium spp. and Scrippsiella spp. dinoflagellate (harmful algal bloom species), Alexandrium spp.

1228

8

8

1

N/A 1835 (Alexandrium); 1627 (Scrippsiella) Trizol extraction produced highest resolution, number of spots, and spot intensity urea/Triton X-100 with TCA/acetone precipitation

2-DE, MALDI TOF-TOF, NCBI database

1

6

720 (toxic), 643 (nontoxic)

differential protein expression

2-DE, MALDITOF and NCBInr database by Mascot, N-terminal amino acid sequencing and Protein Data Bank or SwissProt by BLAST 2-DE, one spot MALDI-TOF, NCBI database

N/A

1

1

20

differentiation of morphospecies that contribute to toxicity

protein extraction optimization: lysis buffer vs acetone precipitation vs Trizol protein extraction optimization: urea/Triton X-100 with TCA/

validated ID

37

NR

some unique spots in each strain

N/A

N/A

N/A

N/A


no significant differences in the protein profiles of the two strains

130

species specificity in proteins characteristic of toxicity

2DE

2-DE

1

900

N/A

first report of a plasma membrane protein in a dinoflagellate

chlorophyll binding proteins, cell proliferation proteins increase in protein identifications using bioinformatics tool, BUDAPEST effect of rhythmicity on physiological states and control metabolic pathways

summary

research findings

proteome analysis of germinated cysts of two strains

2-DE, MALDI TOF, NCBI and UniProt databases

identification of biomarkers of toxicity

circadian rhythms (12 h light:12 h dark)

dinoflagellate (harmful algal bloom species), Lingulodinium polyedrum dinoflagellate (harmful algal bloom species), Lingulodinium polyedrum dinoflagellates (harmful algal bloom species), Alexandrium tamarense AT-CI01, AT-HK9301, ATPolar, and ATWHOI (all toxic), AT-HKJB (nontoxic) dinoflagellates (harmful algal bloom species): Alexandrium tamarense, A. catenella dinoflagellate (harmful algal bloom species), Alexandrium minutum 2-DE, HPLC, MS

1-DE, LC-ESI MS/ MS, UniProt algae annotated database 2-DE, LC-MS and MS/MS, SwissProt and NCBI databases

proteome characterization

microalga (coccolithophore), Emiliania huxleyi

identification of cell surface proteins

methodology

research focus

organism

Table 1. continued

Wang et al. 2009124

Lee and Lo 2008133

Chan et al. 2005228

Wang et al. 200842

Chan et al. 200641

Bertomeu et al. 200345

Akimoto et al. 200440

Jones et al. 2011227

ref

first report of raising a polyclonal antibody from a protein spot to distinguish toxic strains

discovery of a plasma membrane protein

notes



organism

1842

cross-species protein profile comparison

dinoflagellates (harmful algal bloom species): 5 Prorocentrum species, 3 Karenia species, and Scrippsiella trochoidea (nontoxic) dinoflagellate (harmful algal bloom species), Karenia digitata

1-DE, HPLC-LTQOrbitrap XL and MALDI TOF/ TOF, MS/MS, NCBI database

2-DE, LC-MS/MS, NCBI database

nitrate-deprived vs nitrate-replete (control) cultures

caffeine (60 mg/L) treatment

dinoflagellate coral symbionts: Clade A Symbiodinium microadriaticum, Clade B ITS-type B1 Symbiodinium

MALDI-TOF-TOF

2-DE, MALDITOF, NCBI database, N-terminal amino acid sequencing, SwissProt 2-DE, MALDITOF, CAFMALDI, NCBI, UniProt databases 2-DE

methodology

dinoflagellate (harmful algal bloom species), Karenia mikimotoi

HAB causing species identification

autotrophic and mixotrophic growth

acetone precipitation vs TCA/acetone precipitation vs Tris/glycerol; comparison of gel spots between groups grown under different light conditions different growth phases, light, nitrogen and phosphate growth conditions

research focus

dinoflagellate (harmful algal bloom species), Prorocentrum micans

dinoflagellate (harmful algal bloom species), Prorocentrum triestinum

Table 1. continued

differential expression related to photorespiration, reproduction, growth, protein modification, cytoskeletal stability and signal transduction differential expression of heat-shock proteins after caffeine exposure

use of C-4 and C-18 Ziptips to produce species specific peptide expression profiles

determined by differences in peptide expression profiles and not individual spots or proteins. 16 (nitratedeprived), 11 (nitrate-replete)

“A”, 14 up-, 13 downregulated; “B6”, 22 up-, 7 downregulated; “B7”, 19 up-, 6 downregulated;

N/A

NR

“A”, 279 spots; “B6”, 319 spots; “B7”, 319 spots; “C”, 431 spots

27

21


N/A

2DE

319

1200

protein expression affected by trophic mode of the dinoflagellate species specificity in 2DE protein profiles of a mixed culture

NR

differential expression in cell division and stress response proteins

produced best resolution

summary

research findings

3 per species

Pollack et al. 200974

Lei and Lü 2011230

Lee et al. 201143

N/A

27

Chan et al. 2004b132

Shim et al. 201144

Chan et al. 2004a229

ref

N/A

5

0 but 5 novel proteins added to UniProt

validated ID

peptide expression profiles for rapid identification of toxic dinoflagellate in field samples

notes



organism

1843

plant adaptation to high salinity

2-DE, MALDITOF MS, NCBInr database by Mascot

N/A

global differential expression after whole cell extractions

upregulation of oxidative damage response proteins

labeling with 12C or13C acetaldehyde, LC-MS DDA analysis, NCBI O. tauri database

green alga, Dunaliella salina

green alga, Ostreococcus tauri

review on the use or future need of ’omics’ approaches in algae; also discusses cadmium exposure (5 or 100 CdCl2) and compares microarray hybridization analysis to metabolomics glufosinate treatment, 2picoline borane labeling

freshwater microalga, Chlamydomonas reinhardtii

N/A

N/A

review article

review article: nutritional physiology in harmful algae

analysis of subproteomes greatly increased knowledge of functional pathways for temporal control of metabolism discussed best sample prep for 2-DE, MALDI-TOF, de novo sequencing and challenges due to lack of complete genome data discussion of the use of 2-DE coupled with mass spec to better understand the link between eutrophication impacts and incidence of harmful algal blooms discussion of a systemic response to a condition using ‘omics’ technology; low Cd concentrations within homeostatic levels while high toxic

summary

N/A

methodology

mini-review of proteomics utilized to identify circadian rhythm pathways

research focus

dinoflagellate (harmful algal bloom species)

sp. “B6”, Clade B ITS-type B1 Symbiodinium sp. “B7”, Clade C ITStype C1 Symbiodinium goreaui dinoflagellate, Lingulodinium polyedrum; green alga, Chlamydomonas reinhardtii dinoflagellates (harmful algal bloom species)

Table 1. continued

N/A

N/A

509

N/A

21

32

N/A

N/A

N/A

N/A

N/A

“C”, 12 up-, 37 downregulated


N/A

2DE

research findings

10 (only one validated by PCR)

420

N/A

N/A

N/A

N/A

validated ID

Cui et al. 2010235

BarriosLlerena et al. 201147

Jamers et al. 2009234

Dyhrman 2008233

Lee and Lo 2007232

Wagner et al. 2005231

ref

reductive isotopic diethylation, a novel stableisotope labeling technique

notes



1844

brown alga, Scytosiphon gracilis

copper (100 μg/L) exposure

quantification of protein turnover over 6 days

12 h daylight and 12 h darkness; low nitrogen



2-DE, LC-ESI, NCBI and EST databases, de novo sequencing

cadmium (10 μM CdCl2) treatment

green alga, Nannochloropsis oculata

N stable sitope labeling (SILAC), HPLCMS/MS, O. tauri subset database of NCBI, for cellular localization O. tauri GO annotation and Arabidopsis thaliana database, formulas for degradation and synthesis rate 2-DE, LC-MS/MS, NCBI database

15

total lysate and organelle fractions; phosphopeptide enrichment; 15 N metabolic labeling and label free quantification; HPLC-MSMS; NCBI O. tauri database

methodology

organism

research focus

Table 1. continued

overexpression of chloroplast peroxiredoxin, phosphomannomutase, glyceraldehy-3phosphate dehydrogenase, ABC transporters, chaperonin, etc.

identification of turnover, synthesis and degradation for 39 most intense proteins

upregulation of malate dehydrogenase orthologue, NADH dehydrogenase orthologue and ubiquinone oxidoreductase orthologue; downregulation of glyceraldehyde-3phosphate dehydrogenase upregulation of proteins involved in carbon storage pathways, glycolysis and phosphate transport under low nitrogen conditions; dynamin and kinesin under different light conditions

summary

1000

23

7 phosphorylated (LC-MS); 16 light vs dark (LC-MS); in low nitrogen conditions 49 up- and 66 downregulated in the nuclear fraction, 33 upand 30 downregulated in the plastid fraction, and 28 up- and 72 downregulated in the cytoplasm fraction N/A

N/A

N/A

11


389

2DE

research findings

26 out of 35

39

Contreras et al. 201050

Martin et al. 2012237

Le Bihan et al. 201146

2343 total (1794 with ≥2 peptides); 2115 (53 LCMS label-free runs), 1454 (48 -N/14N labeling runs), 573 (20 phosphopeptide-enriched runs)

ref Kim et al. 2005236

validated ID 4

first proteomic study investigating protein turnover, synthesis and degradation

notes



1845

mediterranean tapeweed, Posidonia oceanica


protein extraction optimization: Tris, lysis buffer, TCA/acetone precipitation, and phenol chloroform biomarker development in response to pollution seagrass collected from turbid areas (low-light) versus clean water areas (high-light)

copper (50, 150 μg/L) exposure

brown alga, Ectocarpus siliculosus

red alga, Gracilaria changii

protein extraction optimization (acetate buffer, phosphate buffer, Tris-HCl, cold ethanol, and four urea-containing lysis buffers) and pH stress

brown alga, Saccharina japonica

taxonomic identification

development of reliable protocols for proteomic extractions from algae

brown algae, Scytosiphon gracilis, Ectocarpus siliculosus

red alga, Bostrychia radicans, B. moritziana

research focus

organism

Table 1. continued

urea-containing buffer with PVP and Pharmalyte, best 2-DE resolution; upregulation of tryptophan synthase α chain and surface glycoprotein 7, downregulation of 6-phosphogluconate dehydrogenase genetic adaptation from copper tolerance proteins and stress related enzymes

2-DE, MALDITOF, NCBI database

32−54

423−494

3

26

NR

2600

differential expression in a reference site vs polluted one mediation of low-light acclimation by enhanced protein turnover; downregulation of RuBisCO and upregulation of proteasomes in lowlight conditions

2-DE

2-DE, nanoLCMS/MS (QTOF), SwissProt, genome databases (NCBI), and de novo

NR

phenol/chloroform, best 2-DE resolution; identified pigment proteins, metabolic enzymes and ion transporters

516

32 (female), 48 (male)

13 (after pH stress)

200

699−921

N/A


∼1100 for both species

2DE

2-DE, MALDITOF, NCBI database

2-DE

consistency between proteomic and genetic distances based on DNA sequence data and sexual compatibility studies between isolates

phenol extraction with salt removal, optimal method

2-DE, MALDITOF MS, NCBInr database by Mascot

2-DE, MALDITOF, species specific

summary

methodology


11 (database match) 1 (de novo)

N/A

15 of 42

N/A

10−14

of 46 spots selected for identification, 10 for S. gracilis; 14 for E. siliculosus 15 out of 39; 5 (after pH stress)

ref

Mazzuca et al. 200955

Bucalossi et al. 200653

Wong et al. 200648

Kim et al. 200852

Ritter et al. 201051

Kim et al. 201149

Contreras et al. 2008238

validation of RuBisCo expression with two independent techniques: immunoblotting and

proteomics validation by measurement of mRNA and enzyme activity use of proteomic degree of similarity (distances between 2-DE spots) to study genetic distances among red algae

notes



marine invertebrates

high phenol vs low phenol shoots from 20 sites protein extraction optimization and proteome characterization of juvenile, intermediate and adult blades salt stress treatment



1846

comparative proteomics of symbiotic and aposymbiotic juvenile soft Corals investigation of soluble and membrane bound proteins in soft corals proteomic characterization of coral spicules

proteomic characterization of lipid bodies in coraldinoflagellate endosymbiosis proteomic characterization

soft coral, Heteroxenia fuscescens

coral, Euphyllia glabrescens

coral, Euphyllia glabrescens

soft coral, Sinularia polydactyla

soft corals, Sarcophyton sp., Capnella gaboensis

serine proteases from marine sponges

sponges, Geodia cydonium, Suberites domuncula

oriental mangrove, Bruguiera gymnorrhiza

research focus

organism

Table 1. continued

2-DE, nanoLCESI-MS/MS,

1-DE, nanoLCESI-MS/MS, Mascot, NCBInr database

1-DE, N-terminal sequencing, Calcium autoradiography

1-DE

2-DE

1-D and 2-D PAGE and zymograms

2-DE, HPLC, NCBI database; one spot LCMS/MS

2-DE

2-DE

methodology

N-terminal sequencing provided identification of two proteins; likely important in calcification lipid body proteins identified involved in metabolism, intracellular movement, stress response, and development method for separating tissue layers that does

identification of fructose-1,6biphosphate aldolase and a novel protein in main root; osmotin and a high-molecular weight cobaltcontaining nitrile hydratase in lateral root sample preparation technique is discussed; observation of one serine protease age-related changes in protein profiles detected, but no symbiosis-related changes in host proteome total protein varied by tissue region but also by method of extraction

heterogeneity in adaptation to environmental conditions TCA, best resolution; juvenile blades not suitable for 2-DE analysis

summary

417

N/A

NR

N/A

N/A

N/A

N/A

N/A

5 groups across developmental stages

170

N/A

NR

1

6

2000−2800


22 spots (low phenols), 27 spots (high phenols) N/A

437

2DE

research findings

3

42

2

N/A

N/A

N/A

4

N/A

N/A

validated ID

Peng et al. 200870

Peng et al. 201173

Rahman et al. 200577

Tentori and Thomson 200875

Barneah et al. 200668

Wilkesman and Schroder 200779

Tada and Kashimura 200956

Spadafora et al. 2008131

Migliore et al. 200754

ref

notes

first report of proteome analysis in mangrove plants

immunogold labeling



organism

1847

nonylphenols and bisphenol A toxicity in developing abalone technique optimization for identification of mollusk shell proteins

abalone, Haliotis supertexta

abalone, Haliotis tuberculata

bisphenol A and phthalate toxicity in abalone

proteomic analysis of symbiosome membranes in Cnidariadinoflagellate symbiosis proteomic analysis of abalone shell

RP-HPLC, ESI/ QTOF-MS/MS, Mascot, H. asinina database

2-DE, MALDITOF MS/MS, Mascot, NCBInr database

1-DE, nanoLCMS/MS (ESI), Mascot, H. asinina EST library, UniProt/ KB and SwissProt databases, GenBanknr database 2-DE, MALDITOF MS, Mascot, NCBInr database

1-DE, 2-DE, MALDI-MS/MS, nanoLC-ESIMS/MS, de novo sequencing, Proteome Discoverer software, NCBInr database 2-DE, nanoLCMS/MS (ESI), Western blotting, Mascot, NCBInr database

2-DE, subtracted cDNA library, RT-PCR

Mascot, NCBInr database

of tissue layers in coral changes in larval proteome and transcriptome during onset of symbiosis identification and characterization of fluorescent proteins from marine organisms

methodology

research focus

abalone, Haliotis diversicolor supertexta

abalone, Haliotis asinina

anemone, Aiptasia pulchella

corals and soft corals, Fungia sp., Sarcophyton sp., Acropora sp.

coral, Fungia scutaria

Table 1. continued

possible mechanisms for toxicity of endocrine disrupting compounds in abalone altered proteomic profiles in abalone larvae and led to failure of metamorphosis sample preparation techniques using trifluoroacetic acid and trypsin increased protein identification within insoluble organic shell matrix

identified proteins from distinct layers, including twelve novel proteins

17 proteins identified in symbiosomes; serve as interface for interaction between host and symbiont

not degrade proteins but increases sensitivity in protein detection age-related changes in protein profiles detected, but no symbiosis-related changes proteomic techniques provides unique information for identification of fluorescent proteins; possible alternative to gene cloning

summary

N/A

156

550

N/A

N/A

66 (nonylphenols); 76 (bisphenol A)

24

N/A

N/A

N/A

28

48

3


450

2DE

research findings

5 novel

18

18

14

17

5

N/A

validated ID

Bedouet et al. 2011242

Liu et al. 2011241

Zhou et al. 2010240

Marie et al. 2010239

Peng et al. 201072

Wojdyla et al. 201176

deBoer et al. 200769

ref

multiple sample prep techniques enhance sequence coverage

notes



1848

proteomic changes after exposure to environmental pollutants

protein expression profiles from distinct environmental sites

mussel, Bathymodius azoricus

Mussel, Mytilus edulis

proteomic characterization of calcifying matrix proteins

clam, Venerupis philippinarum



clam, Scrobicularia plana

mussel, Mytilus edulis

proteomic changes after exposure to nonylphenol

clam, Ruditapes decussatus

research focus proteomic changes after exposure to environmental pollutants

organism

clam, Chamaelea gallina

Table 1. continued

2-DE, MALDITOF MS, nESIMS/MS, de novo sequencing, FASTA software, SwissProt database, NCBInr database nanoLC-MS/MS, Mascot, EST database of Venerupis sp., UniProtKB/ SwissProt database, NCBInr database 2-D DIGE, MALDI-TOF MS/MS, Mascot, SwissProt database, NCBInr database, Deep Sea Vent database for B. azoricus 2-DE, nanoLCESI-MS/MS, MassLynx, MS BLAST, FASTA software; PIR, SwissProt, NCBI databases fractionation, peroxisome enrichment, 2-D DIGE, MALDITOF MS/MS, nanoLC-ESIMS/MS, MS BLAST, FASTA software; PIR,

2-DE, MALDITOF MS, ESIQTOF-MS, Mascot, SwissProt datbase, TrEMBL database 2-DE, immunoblotting

methodology

identified protein expression signatures for each chemical used; important for biomonitoring

protein expression pattern allowed identification from polluted vs unpolluted areas

specific protein expression profiles link proteome adaptation to environmental conditions

three novel shell proteins identified

protein expression profiles were tissuedependent; potential markers of oxidative stress located protein expression profiles produced; two novel pollution biomarkers identified

screening produced several biomarker targets; especially cytoskeletal proteins

summary

130

300

4122

N/A

2000

159 (gill), 231 (digestive gland)

1000

2DE


111

13

31

N/A

N/A

54 (gill), 112 (digestive gland)

26-Sep


14

10

6

6

2

N/A

4

ref

Apraiz et al. 2006b248

Amelina et al. 2007162

Company et al. 2011247

Marie et al. 2011246

Romero-Ruiz et al. 2006245

Chora et al. 2010244

RodriguezOrtega et al. 2003243

notes



1849

proteomic changes after exposure to PCBs and PAHs proteomics underlying acute thermal stress





proteomics and genomics of variability in egg proteins


impact of toxin exposure on proteomics associated with intertidal conditions proteomics on the effects of oxidative stress biomarker discovery in shellfish toxins

biomarker profiling using proteinchip array



testing proteomics for biomonitoring after oil spill using exposure to oil


biomarker discovery after exposure to pollutants

utilizing proteomics for biomonitoring after oil spill



research focus

organism

Table 1. continued

2-DE, MALDITOF MS/MS, Mascot, EST

1-DE, nanoLCESI-MS/MS, Mascot, EMBL, MALDI-TOF/ TOF MS, Global Proteome Server Explorer, de novo sequencing, UniRef100 database, NCBInr database 1-DE, 2-DE

1-DE, 2-DE, LCMS/MS

ProteinChip arrays, SELDI-TOF MS, Biomarker Wizard software 2-DE, nanoLCMS/MS, Bioworks software, FASTAnr database ProteinChip arrays, SELDI-TOF MS, Biomarker Wizard software 2-DE, nanoLCESI-MS/MS, Mascot, NCBInr database

2-DE

SwissProt, NCBI databases 2-DE, MALDITOF MS/MS, NCBInr database, BLAST, Western blotting

methodology

PCB exposure induced physiological and proteomic changes interspecific differences were found in molecular chaperones,

identified potential biomarkers for oxidative stress identified biomarkers for shellfish toxins

stress proteins altered, as well as cytoskeletal proteins and energy transport

differential expression found by site; biomarker potential

differences between lines of mussels point to underlying genetic variation

protein expression profiles differed among stations and sampling years; effective tool for biomonitoring protein expression signatures are potentially robust method for biomonitoring exposure- and genderspecific patterns after oil exposure

summary

NR

NR

N/A

1308 (subtidal), 2581 (intertidal), 1156 (subtidal exposed), 2042 (intertidal exposed) NR

N/A

1000 but 261 selected

N/A

468

134 selected

2DE


47 (M. gallo), 61 (M. trossu)

38

N/A

NR

58 (intertidal condition), 27 (PAH exposure), 39 (both)

N/A

50

N/A

141

NR

research findings

NR

N/A

17

15

41

N/A

43

N/A

N/A

9

validated ID

Tomanek and Zuzow 2011255

Olsson et al. 200458

McDonagh and Sheehan 2008253 Nzoughet et al. 2009254

Letendre et al. 2011252

Knigge et al. 2004251

Diz et al. 200965

Bjornstad et al. 2006250

Apraiz et al. 2009b180

Apraiz et al. 2009a249

ref

notes



1850

proteomic discovery of biomarkers of insecticide toxicity proteomic identification of stress proteins proteomic identification of larval proteins in mussel

mussel, Mytilus galloprovincialis



proteomic characterization of proteomes of two related species

proteomic characterization of species specific proteins

mussels, Mytilus edulis, M. galloprovincialis, M., trossulus

mussels, Mytilus edulis, M. galloprovincialis

proteomic expression underlying hybrid vigor

mussels, Mytilus edulis, M. galloprovincialis

research focus

protein expressions maps in hybrid crosses

organism

Mmussels, Mytilus edulis, M. galloprovincialis

Table 1. continued

1-DE, 2-DE, Proteomweaver software, Western blotting 2-DE, MALDITOF MS/MS

2-DE, MALDITOF and nanoESI MS/ MS, Mascot, MSFIT, ProteinProspector, SEQUEST, nrFASTA database 2-DE, MALDITOF and nanoESI MS/ MS, de novo sequencing, BioWorks software, SEQUEST, SwissProt database, nrFASTA database, EST database 2-DE, MALDITOF and nanoESI MS/ MS, de novo sequencing, Mascot, MS-FIT, ProteinProspector, SEQUEST 2-DE

database for Mytilus spp., SwissProt 2-DE

methodology

2-DE patterns useful for establishing reference maps and biomarker discovery identified proteins specific to this mussel species; proteomic approach allows rapid species identification

protein expression profiling detected differences in insecticide effects

comparison of global protein expression identified specific protein differences

successful application of proteomics to identify species without proteome representation in databases

proteolytic proteins, energy metabolism and oxidative stress protein expression differences might highlight reduced fitness stress proteins associated with lower viability of hybrid mussels

summary

350

450

700

1278

1250

750

250

2DE


18

N/A

12

37 of 420

NR

14 of 430

12 of 89

research findings

6

N/A

N/A

15

1

3

N/A

validated ID

Lopez et al. 2005262

Hamer et al. 2005261

Dondero et al. 2010260

Lopez et al. 2002b259

Lopez et al. 2002a258

Fuentes et al. 2002257

Diz et al. 2007256

ref

example of multiple -omics techniques utilized concurrently

notes



protein markers of algal toxin contamination technical review

mussel species

1851

proteomics underlying disease resistance

determination of sex and reproductive condition by protein profile proteomic changes in oyster exposed to elevated partial pressures of carbon dioxide

oyster, Crassostrea virginica

oyster, Crassostrea virginica

proteomic characterization of calcifying matrix proteins

oyster, Crassostrea gigas

oyster, Ostrea edulis, Crassostrea gigas

review article

mussels, Mytilus sp.

mussels, Mytilus sp.

proteomic responses to cadmium and hydrogen peroxide exposure

mussel, Perna viridis

research focus proteomics as risk assessment tool for peroxisome proliferating pollutants

organism


Table 1. continued

2-DE, MALDITOF MS/MS, Mascot, oyster specific database from NCBI

proteinChips, SELDI-TOF MS, CiphergenExpress software

nanoLC-MS/MS, Mascot, EST database of Crassostrea spp., SwissProt database, GenBank database, NCBInr database 2-DE

N/A

N/A

2-DE, nanoLCMS/MS, MassLynx software, PIR, SwissProt and NCBInr databases, immunoblotting 2-DE, MALDITOF MS/MS, Mascot, NBCInr database, invertebrate EST database 2-DE, LC-MS/MS, Mascot

methodology

identified proteins associated with reproduction; successfully classified sex and condition based on protein profiles protein expression changed significantly; cytoskeleton as major target of oxidative stress

generated reference maps for resistant and susceptible oysters; located potential biomarkers for infection

identified biomarkers for algal toxin contamination description of fractionation, 1-DE, and 2-DE techniques used in proteomic risk assessment of marine peroxisomes role of proteomics in taxonomy Identified 8 novel shell proteins

tissue-specific protein expression detected; novel stress responses for pollution monitoring

generated reference maps for peroxisomal proteins; located potential biomarkers

summary

456

N/A

∼218 (O. edulis); 287 (C. gigas)

N/A

N/A

N/A

96

800 (hepatopancreas); 400 (adductor)

200

2DE


54

20 (between species); 34 (between O. edulis stocks); 37 (between infected O. edulis stocks) 62 of 139

N/A

N/A

N/A

2

17 (hepatopancreas); 13 (adductor)

55


17

N/A

N/A

8

N/A

N/A

2

15

6

ref

Tomanek et al. 201163

Li et al. 2010269

Cao et al. 200960

Marie et al. 2011b268

Lopez 2005267

Cristobal et al. 2008266

Ronzitti et al. 2008265

Leung et al. 2011264

Mi et al. 2005263

development of useful profiling technique for oyster hatcheries but cost prohibitive

notes



organism

1852

proteomic discovery of biomarkers of metal contamination

proteomic analysis of metal contamination effects on hemolymph stress proteins from gill tissue after cadmium exposure proteomic changes in kidney tissue after cadmium exposure

oyster, Saccostrea glomerata


scallop, Chlamys farreri

scallop, Patinopecten yessoensis

proteomic analysis of immune response



scallop, Patinopecten yessoensis


proteomic analysis of shell nacre proteins proteomic discovery of biomarkers of pesticide toxicity

research focus


oyster, Saccostrea cucullata

oyster, Pinctada margaritifera

Table 1. continued

2-DE, MALDITOF MS/MS, Mascot, NCBInr database 2-DE, MALDITOF MS/MS, Mascot, NCBInr database, SwissProt database, RTPCR 2-DE, LC-MS/MS, FTICR-MS, Mascot, NCBInr database, EST database

2-DE, nanoLCMS/MS, Mascot, NCBInr database

2-DE, nanoLCMS/MS, Mascot, NCBInr database

1-DE, nanoLCMS/MS, Mascot, NCBInr database 2-DE, MALDITOF MS/MS, Mascot, NCBInr database, UniProt database, RTPCR 2-DE, nanoLCMS/MS, Mascot, GenBanknr database, SwissProt database 2-DE, nanoLCMS/MS, Mascot, NCBInr database

methodology

generated reference map for scallop; identified molecular chaperones and proteins in the antioxidant system as important targets

identified several potential biomarker proteins associated with cadmium toxicity identified several potential biomarker proteins associated with cadmium toxicity

generated reference maps for resistant and susceptible oysters; identified potential biomarkers for resistance unique protein expression profiles were determined for cadmium, copper, lead and zinc with some novel proteins not previously considered biomarker candidates unique protein expression profiles were determined for copper, lead and zinc

located potential biomarkers of infection

soluble and insoluble proteins shared constitutive material identified potential biomarkers for organophosphate pesticide toxicity

summary

65

900

800

161

305

60 (resistant), 80 (wild-type), 140 (infected)

61 (exposed), 72 (wild-type)

NR

N/A

2DE


27

13

37

25

129

6

4

12

N/A


46 (reference map); 15 (of diff expressed)

13

7

18

47

6

0

12

4

ref

Huan et al. 2011278

Huang et al. 2011a277

Fang et al. 2010276

Thompson et al. 2011275

Thompson et al. 2012274

Simonian et al. 2009b273

Simonian et al. 2009a272

Guo et al. 2012271

Bedouet et al. 2007270

notes



1853

proteomic analysis of venom bulb

proteomic analysis of venom processing

proteomic changes in optic ganglion under stress

cone snails, Conus novaehollandiae, C. victoriae

cone snail, Conus textile

octopus, Octopus vulgaris

proteomic analysis of venom gland

proteomics underlying adaptation to distinct habitats

snail, Littorina saxatilis

cone snails, Conus novaehollandiae, C. victoriae

protein changes underlying phenotypic plasticity

Snail, Littorina saxatilis

research focus proteomic changes involved in resistance to allelochemicals in diet

organism

snail, Cyphoma gibbosum

Table 1. continued

HPLC, LTGQOrbitrap MS/ MS, SEQUEST, ConoServer protein database, Conus sp. database 2-DE, MALDITOF MS, Mascot, NCBInr database

2-DE, nanoLCQTOF-MS/MS, Mascot, SwissProt database, SwissProt molluscan database, C. bullatus transcriptome-nr database 2-DE, 1-DE, nanoLC-QTOFMS/MS, Mascot, UniProtnr database

2-DE, MALDITOF MS/MS, nanoLC-MS/MS (Q-TOF), Mascot, NCBInr database

affinity chromatography, HPLC, 1-DE, nanoLC-MS/MS, BioWorks software, Mascot, NCBInr database, MSDB database, RTPCR 2-DE

methodology

venom bulb is utilized in muscular movement and burst muscle contraction; possibly for venom translocation venom duct regions have differential protein expression; possibly allow formulation for specific hunting situations differential expression mainly in mitochondrial proteins; beta-tubulin

observed differences accounted for 7% of proteome, were insensitive to environmental changes, and attributable to genetic factors differential expression between the two ecotypes; proteins involved in energy utilization were upregulated in one ecotype identified novel glandular proteins of potential importance for toxin synthesis and secretion

theta-class and molluskspecific subclass of mu Glutathione Stransferases identified

summary

600

N/A

34

161, 167

726

764

N/A

2DE


18

19

N/A

NR

22

17

N/A


18

24

16, 17

161, 167

4

N/A

4

ref

Huang et al. 2011b284

Tayo et al. 2010283

Safavi-Hemami et al. 2010282

Safavi-Hemami et al. 2011281

MartinezFernandez 2008280

MartinezFernandez 201066

Whalen et al. 2008279

notes



mini-review proteomic analysis of larval development, attachment, and metamorphosis larval proteome response to ocean acidification

proteomic changes during larval development and exposure to antifouling agent

barnacle, Balanus amphitrite



proteomic changes during larval development

polychaete worm, Pseudopolydora vexillosa


changes in phosphoproteome during larval development

polychaete worm, Pseudopolydora vexillosa

proteomic changes during larval development

alterations in host proteome in response to bacterial symbiont

squid, Euprymna scolopes; symbiont bacterium, Vibrio fischeri

polychaete worm, Capitella sp. I

research focus

organism

Table 1. continued

1854

2-DE, MALDITOF-MS/MS, Mascot, NCBInr database, invertebrate EST database 2-DE, MALDITOF-TOF MS, ESI-MS, Mascot, NCBInr database, B. amphitrite database, Western blotting

2-DE, MALDITOF-MS/MS, Mascot, NCBInr database

2-DE, MALDITOF MS/MS, Mascot, C. capitata database, NCBI nr database

2-DE, phosphoprotein enrichment kit, MALDI-TOF MS/MS, Mascot, P. vexillosa trancriptome database, NCBInr database 2-DE, MALDITOF MS/MS, Mascot, NCBI nr database

2-DE

methodology

utilization of proteomics in larval settling cues developmental stage before metamorphosis had higher protein diversity and abundance, proteins in energy metabolism, respiration, and molecular chaperones were acidification responsive during development, proteins associated with stress and energy metabolism changed; the antifouling agent seemed to suppress these changes

9

∼60

∼587

65; 111

36

566

392 (developing); 256 (attached, metamorphosed)

498 larvae, 473 juveniles

160 between competent larvae and juvenile

∼660

16

7

9

23

11 of 68

38

64

210 (precompetent larvae), 492 (competent larvae), 172 (juveniles)

polychaete worm shows fewer proteome changes during metamorphosis versus barnacle differential expression observed in stages; potential for protein markers

N/A

14 at 48 h, 80 at 96 h (age-related); 84 at 48 h, 54 at 96 h (symbiosisrelated)

NR

validated ID

and beta-actin potential biomarkers a total of 138 symbiosisrelated protein changes found at two time points; shared proteins between hatchling and symbiotic animals differential phosphoprotein expression might be due to fast morphological transitions


2DE

summary

research findings

Zhang et al. 201062

Wong et al. 201164

Thiyagarajan and Qian 2008134

Thiyagarajan 2010288

Chandramouli et al. 2011b287

Mok et al. 2009286

Chandramouli et al. 2011a285

Lemus and McFall-Ngai 200027

ref

notes



1855

proteomic changes in shrimp hepatopancreas after exposure to white spot syndrome proteomic changes in shrimp hepatopancreas after hypoxic stress

shrimp, Fenneropenaeus chinensis

crabs, Hyas araneus, Carcinus maeanas

crab, Eriocheir sinensis

shrimp, Littopenaeus vannamei

protein profiling of crab hepatopancreas tissue after exposure to pollutants

proteomic identification of immuneenhancing proteins in shrimp exposed to vitamins protein profiling of crab gill tissue after exposure to cadmium

proteome map of encysted brine shrimp embryo

brine shrimp, Artemia sinica

shrimp, Fenneropenaeus chinensis

proteomic changes in brine shrimp after exposure to copper

brine shrimp, Artemia sinica

research focus proteome changes during larval metamorphosis

organism

barnacle, Balanus amphitrite; Bryozoan, Bugula neritina

Table 1. continued

proteinChips, SELDI-TOF MS, Biomarker Wizard software

2-DE, nanoLCMS/MS (QTOF), BLAST database

2-DE, LC-ESI-MS/ MS, Mascot, NCBInr database, EST database, SEQUEST, F. chinensis peptides database, RTPCR 2-DE, MALDITOF MS, Mascot, NCBInr database

2-DE, MALDITOF MS/MS, Mascot, NCBI nr database, RTPCR

2-DE, LC-MS, SEQUEST, BioWorks software, NCBInr database 2-DE, LC-MS, BioWorks software, NCBInr database

2-DE, MALDITOF-MS/MS, Mascot, NCBInr database

methodology

cadmium appears to alter oxidative stress pathways and sulfhydryl-group binding. gender and speciesspecific differential expression; females showed greater sensitivity to pollutants

cumulative mortality lower after supplementation; identified 7 potential immunostimulant proteins

functional groups associated with energy production, metabolism and immune-related proteins

reference map is first step in developmental and physiological studies of brine shrimp protein expression drastically altered; molecular pathways may illuminate infection process

larval proteomic response in metamorphosis involved substantial changes to phosphorylation status of proteins rather than de novo protein synthesis potential biomarkers for tolerance to pollutant stress in brine shrimp identified

summary

N/A

1205

400

87, 85, 81 (shore crab); 70, 64, 54 (spider crab)

6 (acute); 31 (chronic)

29 (hemocytes), 28 (hepatopancreas)

67

68

600

640

N/A

14

7 (barnacle); 20 (bryozoan)


233

242

300 (barnacle); 325 (bryozoan)

2DE


N/A

15

7

33

81

33

7

37

ref

Gomiero et al. 2006295

Silvestre et al. 2006294

Qiao et al. 2011293

Jiang et al. 2009292

Chai et al. 2010291

Zhou et al. 2008290

Zhou et al. 2010289

Thiyagarajan et al. 200961

notes



1856

transcriptome and proteome profiling of marine fouling invertebrate

characterize changes in the phosphoproteome and proteome during early metamorphosis proteome of mature sea urchin ovary

bryozoan, Bugula neritina


changes in protein expression after exposure to uv radiation

immune-response proteins in sea urchins

sea urchin, Strongylocentrotus purpuratus


sea urchin, Evechinus chloroticus

larval proteomic changes after exposure to antifouling agent


research focus proteomic analysis of larval settlement and metamorphosis

organism


Table 1. continued

1-DE, 2-DE Western blotting, ELISA, LC-MS/ MS, Global Proteome

2-DE, MALDITOF-MS/MS, Mascot, NCBInr database, B. neritina transcriptome database, qRTPCR 454 pyrosequencing, SCX fractionation, nanoLC-MS/MS (ESI-QTOF), Mascot, B. neritina transcriptome database 2-DE, nanoLCMS/MS (ESIQTOF), Mascot, B. neritina database, qRTPCR 2-DE, nanoLCQTOF-MS/MS, MudPIT, Mascot, S. purpuratus database 2-DE, MALDITOF MS, Mascot, S. purpuratus database

nanoLC-MS/MS (QTOF), Mascot, NCBInr database, B. neritina database, Western blotting, qRT-PCR

methodology

reference proteome important for diet development to enhance gonad quality and quantity UV radiation affects proteins in multiple pathways including cellular stress, protein turnover and translation, signal transduction, cytoskeletal dynamics, and metabolism proteins involved in immune response are highly variable both within and between individuals

metamorphosis was dependent on both de novo protein synthesis and post translational changes

proteins involved in energy metabolism and structural molecules were downregulated while those involved in transcription/ translation, extracellular matrix and calcification were upregulated substantial changes occurred in structural proteins, molecular chaperones, mitochondrial peptidases, and calcium-binding proteins powerful techniques increased knowledge of nonmodel organisms

summary

N/A

171 (30 min), 187 (90 min)

N/A

1306

264

60

N/A

versus control: 263 (exposed); 250 (settled)

61 of 1766


280

∼526

N/A

1080 (control); 968 (exposed); 981 (settled)

N/A

2DE


41

130

138

15

882

15

61

ref

Dheilly et al. 2009301

Campanale et al. 2011300

Sewell et al. 2008299

Wong et al. 2010298

Wang et al. 201067

Qian et al. 2010297

Zhang et al. 2011296

sample prefractionation combined with narrow range 2-DE increased proteome coverage combined 454 sequencing with gel-free shotgun proteomics

notes



proteomics underlying sea urchin spicules

proteomics underlying sea urchin test and spine proteomics underlying sea urchin tooth matrix improving protein identification in sea urchin neuropeptidome

proteomics underlying egg activation in sea urchin

review article







research focus

phosphoproteomes of urchin shell and tooth matrix

organism


Table 1. continued

1-DE, nanoLC-MS (LTQ-FT), Mascot, S. purpuratus database 1-DE, nanoLC-MS (LTQ-FT), Mascot, S. purpuratus database nanoLC-MS/MS (QTOF), MALDI-TOF MS/MS, Mascot, S. purpuratus database, de novo sequencing, Indexed Genome Database (IggyPep) 2-DE, nanoLCMS/MS (QTOF), PLGS software, S. purpuratus database, immunoblotting N/A

1-DE, nanoLC-MS (LTQ-FT), Mascot, S. purpuratus database

Machine software, S. purpuratus database, MALDI-TOF MS/MS, Mascot, S. purpuratus database 1-DE, nanoLC-MS (LTQ-FT), Mascot, S. purpuratus database

methodology

1857

baseline maternal proteome shows 94 proteins that include metabolism, cytoskeletal and gamete-associated proteins combining functional genomics and proteomics of calcium signaling and egg activation

94

N/A

N/A

N/A

600

N/A

30% increase in protein identification

N/A

N/A

N/A

N/A

N/A

N/A


N/A

2DE

N/A

identified 138 proteins in tooth matrix; model system for biomineralization

identified an acidic phosphoprotein in urchin tooth that may serve functions similar to mammalian phosphodontin Comparison of proteomes from different skeletal matrices important to understand biomineralization proteomes essential tools for further exploration of biomineralization

summary

research findings

N/A

92

N/A

138

110

231

34

validated ID

Roux et al. 2006308

Roux et al. 2008307

Menschaert et al. 2010306

Mann et al. 2008b305

Mann et al. 2008a304

Mann et al. 2010b303

Mann et al. 2010a302

ref

combination of de novo sequencing and genomewide database increased identification by 30%

notes



marine fish

1858

proteomics of echinoderm nervous system

proteomics of echinoderm immune-effector cells

sea star, Marthasterias glacialis

sea star, Marthasterias glacialis

dogfish shark, Squalas acanthias

proteomic adjustments and metabolic reorganization in epaulette shark following hypoxia or anoxia proteomes of six different tissues were evaluated for

species-specificity in proteins regulating sperm chemotaxis

sea stars, Asterias amurensis, A. forbesi, Asterina pectinifera

Epaulette shark, Hemiscyllium ocellatum

proteins involved in immune mechanisms

sea star, Asterias rubens

gill and rectal gland proteomes were examined with salinity changes

antibacterial response in sea urchin

sea urchin, Heliocidaris erythrogramma

leopard shark, Triakis semifasicata

research focus

organism

Table 1. continued

2-DE, MALDI TOF/TOF MS, Mascot, BLAST

1-DE, 2-DE, MALDI-TOF MS/MS, ProteinPilot, Mascot, UniProt, S. purpuratus database, Uniref100nr database 1-DE, 2-DE, MALDI-TOF MS/MS, ProteinPilot, Mascot, UniProt, S. purpuratus database, Uniref100nr database 2-DIGE, image analysis, MALDITOF-TOF, Mascot and PEAKS 2-DIGE, image analysis, MALDITOF-TOF, Mascot and PEAKS

1-DE, MS/MS, Mascot, MSDBnr database

1-DE, MALDITOF MS, NCBInr database

2-DE, nanoLCMS/MS, Global Proteome Machine software, S. purpuratus database

methodology

tissue-specific expression patterns of proteins complemented

observed coordinated molecular responses to low salinity which were common to rectal gland and gill sharks adjusted their physiology and proteome to sustain metabolic activity, on exposure to hypoxia

first comprehensive list of coelomocyte proteins; evidence for new pathways

bacterial challenge resulted in differential protein expression; two proteins identified that are involved in sequestration or inactivation of bacteria one protein identified with possible antiinflammatory and pro-inflammatory roles identified membranebound guanylate cyclases in all three species; receptor functions were conserved links echinoderm nervous system to mammalian; several regeneration proteins identified

summary

270

cerebellum 108, rectal gland 101


1465

rectal gland 28, gill 70

N/A

N/A

NR

N/A

24 (salineinjected), 42 (bacteriainjected)



NR

339

N/A

N/A

384

2DE


61



358

286 in radial nerve cord; 158 in synaptosomal membrane enriched

74

1

15

ref

Lee et al. 200689

Dowd et al. 2010b92

Dowd et al. 2010a91

Franco et al. 2011b313

Franco et al. 2011a312

Nakachi et al. 2008311

Coteur et al. 2007310

Dheilly et al. 2011309

notes



organism

1859

characterization of the sea bream muscle protein to assess quality of sea breams farmed in offshore cages bacterial colonization in the wild and farmed fish, specifically kidney proteome metabolic indicators of chronic stress in aquaculture species effect of dietary additive AKG (alphaketoglutarate) on the pituitary proteome alteration in liver proteome at low temperatures

gilthead sea bream, Sparus aurata





differences between sea and farmed muscle tissues of D.labrax

tissue-specific proteins to identify proteins involved in osmoregulatory and metabolic processes in response to feeding

research focus

sea bass, Dicentrarchus labrax

dogfish shark, Squalas acanthias

Table 1. continued

299 total, 164 after fold change rules applied 16 upregulated, 13 downregulated

57

200

600−700

addition of AKG increases cellular metabolism and protein synthesis and folding stress-related response and cellular defense proteins were downregulated

35


560

2-DE, MALDITOF/TOF, ESIMS/MS, Mascot, SwissProt, EMBL database, EST database 2-DE, MALDITOF/TOF, CapLC-QTOF, Mascot, SwissProt, EMBL AND EST databases, biological process by GO

2-DE, LC-MS/MS, Mascot, NCBInr database

600

11

80

ratio of structural proteins vs metabolic protein levels were similar between wild and farmed fish certain spots upregulated in Moraxella-positive tissue and underexpressed in negative tissues panel of “welfare biomarkers” identified from liver

9

28

N/A

684

2DE

differentially expressed indicate impact of aquaculture on fish muscle metabolism

biological functions and processes rectal gland proteome showed substantial changes in protein expression with feeding

summary

2-DE, MALDI-MS, nanoHPLCnanoESI-QTOFMS/MS, Mascot

2-DIGE, image analysis, MALDI TOF MS, MS/ MS, de novo sequencing, westernblotting and immunodetection, 1-DE, microfluidic SDS electrophoresis, MALDI-TOF, LC/ESI-MS MS, Protein Prospector software, TrEMBL database 1-DE, 2-DE, MALDI-MS, NanoLCnanoESI-QTOFMS/MS, Mascot

methodology

research findings

54

28

12

10

33

9

13

validated ID

Ibarz et al. 2010b316

Ibarz et al. 2010a315

Alves et al. 2010314

Addis et al. 2010b83

Addis et al. 2010a82

Monti et al. 201080

Dowd et al. 200890

ref

notes



1860

changes in liver proteome after exposure to common food additive in aquaculture post-mortem changes in muscle proteins during ice storage hepatotoxicity effects of antiparasitic drug on sea bream juveniles liver using proteomics approach molecular mechanisms underlying neurotoxicity of methylmercury (environmental contaminant) molecular mechanisms underlying neurotoxicity of PCBs (environmental contaminants) protein changes in plasma of juvenile cod induced by different levels of exposure to crude North Sea oil


Atlantic cod, Gadus morhua






protein changes in cod exposed to produced water from egg to fry stage protein expression profiles and phenotypic variation

effect of Cu exposure on the serum proteome



research focus

organism

Table 1. continued

2-DE and image analysis, de novo sequencing, LCESI-Q-TOF, cod EST database, BLAST, Mascot search 2-DE and image analysis, MALDITOF-TOF MS, cod EST NCBI databases SELDI-TOF MS

2-DE, MALDITOF MS, MS/MS

2-DE, MALDITOF MS, MS/ MS, NCBInr and cod EST database, Mascot

2-DE, MALDIMS/MS, QRTPCR

1-DE, 2DE, MALDI-TOF

2-DE, LC/MS/MS, Mascot, NCBI MSDB AND SwissProt, de novo sequencing by BLAST 2-DE, MALDITOF/TOF, NCBI nucleotide database, Mascot, Western blot

methodology

36

3993

proteomic variation correlated with individual variation in gonadosomatic index

several proteins were differentially expressed

even at low levels of exposure to crude oil, changes in protein expression were observed

out of 56 differentially expressed spots 27 were identified

biomarker candidates/ which could be used for aquatic environmental monitoring

NA

N/A

N/A

561

NA

24

137

56

71

6

800−1000

518

49 of which 29 identified

523−552

several proteins involved in metabolism were regulated by intake of maslinic acid protein changes were observed during postmortem storage on ice significant changes in the expression of proteins were observed wrt control group

12


340−370

2DE

new serum biomarkers were identified which could be used in seafood management

summary


NA

13

29

27

40

3

2

5

10

ref

Nilsen et al. 2011a135

BohneKjersem et al. 201085

BohneKjersem et al. 200984

Berg et al. 2011321

Berg et al. 2010320

Varo et al. 2010319

Schiavone et al. 200881

RufinoPalomares et al. 2011318

Isani et al. 2011317

first report on effect of diet additive on liver proteome

notes



investigation of immunecompetent molecules in skin mucus of fish protein expression patterns to elucidate cellular mechanisms of fish development protein expression patterns to elucidate immune function, growth, and development


1861

European hake, Merluccius merluccius

Atlantic herring, Clupea harengus

flatfish sp. dab, Limanda limanda




investigation of aquaculture food for mechanisms of potential growth effects proteomic analysis of marine fish larval development to study the effect of geographic location and liver tumor status on the plasma proteome insights into the origins of oocyte hydration in marine teleosts using genomic and proteomic approaches liver and brain extracts were investigated for protein variation among geographically separate populations

validity of protein expression signatures as biomonitoring tools



research focus

organism

Table 1. continued

2D protein profile of Atlantic cod larvae plasma proteome profiles of North Sea dab were more homogeneous than those of the Irish Sea dab yolk proteolysis and generation of organic osmolyte pool of free amino acids were adaptive responses to spawning in seawater more proteins were found in common between Atlantic Ocean and Cantabrain Sea populations than in Mediterranean Sea population

SELDI-TOF MS

1-DE, N-terminal micro sequencing, nanoLC-hybrid triple quad linear ion-trap 2-DIGE, MALDITOF/TOF, in house developed fish seq database from nrNCBI, BLAST, Mascot, de novo sequencing, GO

downregulation of certain proteins in larvae exposed to probiotic bacteria indicated lower levels of immunestimulation no significant differences were observed between control and treated

different isoforms may be generated by PTMs detectable by proteomics

skin mucosal proteins of Atlantic cod identified and classified

male and juvenile fish exposed to estradiol showed estrogenresponsive protein patterns

summary

2-DE, MALDITOF MS, LCMS/MS

2-DE, MALDITOF MS

2-DE, MALDITOF MS

2-DE, MALDITOF MS

2-DE, ESI QTOF, Mascot, NCBInr, dbEST

SELDI-TOF MS

methodology

NA

liver 84, brain 145

liver 2104, brain 3558

NA

N/A


NA

NA

13

23

34

NA

27

109

NR

423−435

NR

67

2DE

research findings

liver 20, brain 35

NA

N/A

77

13

10

17

61

validated ID

ref

Gonzalez et al. 201093

Kristoffersen et al. 200988

Ward et al. 200686

Sveinsdottir et al. 2011326




Rajan et al. 2011136

Nilsen et al. 2011b322

notes

first report of the effect of probiotic bacteria on fish larval protein expression profiles

testing of same samples months apart showed good levels of reproducibility first report of skin mucosal proteome in Atlantic cod



application of proteomics for identification and characterization of fish species changes in liver proteomes after toxicological exposure to cadmium and benzo(a)pyrene evaluating multiple techniques in ecological risk assessment to investigate changes in genes and proteins expressed in the testis throughout spermatogenesis in wild-type males. to identify differences in protein profiles in various muscles due to seasonal changes to understand evolution and diversity of antifreeze proteins changes in liver proteome in groupers and moray eels with ciguatoxin contamination review article

European hake species (Merluccius sp.)

flatfish, Solea senegalensis


1862

peacock hind (grouper), Cephalopholis argus, and Leopard moray eel, Gymnothorax undulates fish proteome analysis

Antarctic eelpout, Lycodichthys dearborni

big-snout croaker, Johnius macrorhynus


research focus

organism

Table 1. continued

several of the isoforms of AFP were identified using EST screen CTXs induced influx/ efflux of Na2+ or Ca2+ changes in fish liver

different proteomics technologies employed in addressing biological questions related to fish physiology

2-DE, MALDITOF/TOF, Mascot, NCBInr database N/A

sonic muscle proteins were upregulated compared to somatic muscle

two proteins upregulated and one downregulated due to Cd and benzo(a) pyrene treatment respectively genotoxicity biomarker identification in benthic fish exposed to estuarine sediments several testis proteins showed altered abundance in reared fish

commercial hake characterization using specific polypeptides

summary

EST screen, LTQ MS, DDA

2-DE, MALDI -TOF, Mascot

microarray analysis, Q-PCR, 2-DE, MALDI-TOF, ESI ITMS/MS, BLAST, NCBI database, image analysis software,

annotation using SwissProt/ TrEMBL 2-DE, MALDITOF MS, nESIITMS, SEQUEST, PepSearch, SwissProt, EST databases 2-DE, MALDITOF, capLCESI-ITMS/MS, Protein−Protein Blast software, NCBI-nr NA

methodology

27 (grouper); 18 (eel)

N/A

N/A

NA

80

40

NA

2 and 1 on treatment with Cd and benzo(a) pyrene

NA


not mentioned

NA

130

N/A

NA

NR

NA

2DE

research findings

N/A

13 (grouper); 15 (eel)

NA

30

26

NA

11

NA

validated ID

Forne et al. 201094

Jiang et al. 201187

Kelley et al. 2010332

Lin et al. 2011331

Forne et al. 2011330

Costa et al. 2012329

Costa et al. 2010328

Pineiro et al. 2001327

ref

notes



1863

a

review article

various marine organisms

harbor seal, Phoca vitulina

harbor seal, Phoca vitulina

evaluation of epidermal cell lines for in vitro testing of environmental stressors use of new bioanalytical techniques to identify biomarkers of contamination in marine mammals investigation of possible biomarker for health status of marine mammals

review article

various marine organisms

bottlenose dolphin, Tursiops truncatus

review article

seafood and marine products

HPLC-ICP-MS, nanoLC-ESIQTRAP-MS, MALDI-TOFMS, Mascot, SwissProt

2-DIGE, nanoLC− ESI−MS/MS

2-DE

N/A

N/A

N/A

N/A

N/A

methodology

transferrin, the iron transport protein identified

utilization of proteomics in marine commercial industries role of proteomics to study effects of climate change on marine commercial industries proteomics as a tool in environmental assessment and toxicology studies molecular profiling of marine fauna; environmental assessment. establishment of epidermal cell cultures and cell lines as tools for identifying environmental stressors significant changes were induced at proteome level by exposure to dioxins

functional genomics and proteomics of osmoregulation in “nonmodel” organisms

summary

NA

422 (control); 206 (treated)

NA

100

NA

N/A

N/A

NA

N/A

N/A

N/A

N/A

N/A

N/A


N/A

N/A

2DE

research findings

Data are subdivided by organism, research focal questions, methods used, and specific results. Note: N/A = not applicable; NR = not reported.

marine mammals

review article

seafood and marine products

research focus review article

organism

tilapia, Oreochromis sp.; Dogfish shark, Squalus acanthias; intertidal sponge Tetilla mutabilis

Table 1. continued

validated ID

NA

20

NA

N/A

N/A

N/A

N/A

N/A

ref

Grebe et al. 2010337

Brenez et al. 2004336

Yu et al. 2005335

Veldhoen et al. 2012185

Tomanek 201010



Kultz et al. 2007333

notes

first investigation and characterization of Tf protein

focused by areas of study

comparison of database search parameters that greatly affect protein identification in nonmodel organisms.




Review

dinoflagellates during bloom conditions and to better understand growth patterns under various environmental parameters.40−44 Bertomeu et al.45 used 2-DE followed by MALDI-TOF-MS and LC-MS/MS to identify a plasma membrane protein that can be used as a biomarker for toxic HABs. However, techniques such as isotope labeling have been used in the study of other microalgae such as Ostreococcus tauri.46,47 Proteomics research on foliose marine macroalgae has been largely limited to protein extraction optimization techniques in species such as the red seaweed Gracilaria changii and the brown algae Saccharina japonica,48,49 as well as an investigation of the effects of copper contamination in the brown algae Scytosiphon gracilis and Ectocarpus siliculosus.50,51 In addition, Kim et al.52 applied proteomic techniques to the taxonomic identification of the red algae Bostrychia radicans. The authors used the distance between 2D gel spots as a unique method to predict genetic distances between species. In contrast to terrestrial plants, in which proteomes are well established (e.g., complete annotated genomes in species such as thale cress, Arabidopsis thaliana; soybean, Glycine max; rice, Oryza sativa; corn, Zea mays), proteomes of marine plants have received little attention. Because seagrass abundance has declined due to coastal development and pollution,53 proteomic stress biomarkers have been a focus of seagrass health studies using 2-DE alone or in combination with LC-MS/MS.54,55 In addition, Tada and Kashimura56 assessed the effects of salt treatment on the proteome of the oriental mangrove, Bruguiera gymnorrhiza, in order to develop salt-tolerance options for agricultural crop productivity. Marine Invertebrates. In studies involving coastal invertebrates such as mussels, oysters, and barnacles, proteomic techniques have been used to detect exposure to environmental pollutants and diseases.57−64 Many of these studies have utilized 2-DE with surface-enhanced laser desorption/ionization (SELDI) MS, or nano-UPLC with MS/MS, to identify protein expression signatures. Additionally, larval biology and development, fouling, and phenotypic plasticity have been examined in the mussel Mytilus edulis, the marine snail Littorina saxatilis, and the bryozoan Bugula neritina, respectively,65−67 using either 2-DE or SCX fractionation, followed by nanoUPLC and QTOF MS, or HPLC-MS/MS. Despite their ecological importance, reef-building and soft corals have been assessed using proteomic techniques only a few times; these studies have focused on the relationship between corals and their photosymbiotic algae Symbiodinium spp.68−73 One study74 examined the effects of caffeine on the proteomes of four species of coral dinoflagellate endosymbionts

Figure 2. Proteomic workflow diagram related to “bottom-up” and “top-down” processes. Specifically, “bottom-up”, or shot-gun, proteomics analyzes peptide fragments of complex protein mixtures, while “top-down” approaches characterize intact proteins.

relative and absolute quantification (iTRAQ) and 3D-LC/MS/ MS shotgun peptide sequencing proteomic approaches. Marine Algae and Plants. Primary producers in the marine environment include planktonic and benthic algae, as well as flowering plants (i.e., seagrasses and mangroves), and their ecological importance has provided an impetus for proteomics applications. To date, most of the proteomic research related to primary producers has focused on dinoflagellates that cause harmful algal blooms (HABs), because they have environmental, economic, and public health consequences.39 The main goal of these studies has been to rapidly identify toxic Table 2. List of Marine Species with Complete Proteomesa microorganisms algae other unicellular eukaryotes and metazoans parasites invertebrates vertebrates

Methanococcoides burtonii,b Rhodopirellula baltica,b Sphingopyxis alaskensis,b Synechococcus sp. strains,b Vibrio cholera,b V. f ischeri,b V. f urnissii,b V. harveyi,b V. parahaemolyticus,b V. splendidus,b and V. vulnificusb Aureococcus anophagef feren (harmful microalga),b Ectocarpus siliculosus (brown alga),d,b Micromonas pusilla (green alga),b Ostreococcus tauri (green alga),b O. lucimarinus (green alga),b Phaeodactylum tricornutum (diatom),b Thalassiosira pseudonana (diatom),b Volvox carteri (green alga)b Monosiga brevicollis (choanoflagellate),b Trichoplax adhaerens (placozoan)b Perkinsus marinus (oyster protozoan parasite)b Branchiostoma f loridae (Florida lancelet),b Ciona intestinalis (transparent tunicate),b Nematostella vectensis (starlet sea anemone),b Oikopleura dioica (tunicate)b Gasterosteus aculeatus (three-spined stickleback),b,c,d Gadus morhua (cod),c Latimeria chalumnae (coelacanth),c Oryzias latipes (medaka),c,d Takif ugu rubripes (pufferfish),c Tetraodon nigroviridis (spotted green pufferfish),b,c,d and Tursiops truncatus (common bottlenose dolphin)c

a

These complete proteome sets are based on the translation of a completely sequenced genome. bAnnotated and available to download in Uni-Prot (www.uniprot.org). cProteome available to download and resulting from the automatic pipeline of a completely sequenced genome in Ensembl (www.ensembl.org). dOrganisms found in marine and freshwater environments. 1864



Review

gather transcriptional and proteomic profiles of spermatogenesis.94 This comprehensive study utilized qPCR, 2-DE, MALDI-TOF-MS, and ESI-IT-MS/MS, followed by a microarray analysis. Marine Natural Products Research. Natural products have played an important role in the discovery and development of new pharmaceuticals, and the structural novelty of marine natural products suggests that the marine environment will be a significant source of future biomedical compounds.95 In recent years, genomic approaches have supplanted traditional bioassay-guided isolation techniques for the identification of marine natural products (e.g., bryostatin96 and barbamide97). Despite the critical role of proteins in biosynthesis, proteomics has seen limited use as an indicator of expressed marine natural products. For example, nonribosomal peptides (NRP) and polyketides (PK), whose biosynthesis is facilitated by NRP synthetase (NRPS) and PK synthase (PKS) enzymes, represent important classes of compounds that often exist as “silent gene clusters”.98 Proteomic profiling has the potential to identify these expressed enzymes and, thus, the pathways of the novel marine natural products they produce. A good example of this research potential was demonstrated in two strains of the model bacterium Bacillus subtilis. Meier et al.99 used an orthogonal active site identification system (OASIS) to identify the biosynthetic pathways of NRP and hybrid PK-NRP antibiotics from the complex bacterial proteome. Specifically, a gel-free LC-MS/MS platform was used to identify and compare NRPS/PKS activity in the two bacterial strains and to identify new gene clusters associated with secondary metabolite production. Likewise, Bumpus et al.100 used an FT-ICRbased approach (PrISM: proteomic interrogation of secondary metabolism) to profile NRPS enzymes involved in the production of the antibiotic gramicidin in Bacillus brevis and to identify the biosynthetic gene clusters involved in the production of the herbicide phosphinothricin tripeptide in Streptomyces viridochromogenes. However, there have been no attempts to utilize proteomic profiling of silent gene clusters in marine species, although the approaches have been used to identify micromolar concentrations of marine natural products.101 Thus, OASIS and PrISM proteomic approaches represent a near-future opportunity to discover new bioactive marine natural products. Small molecule interactions with active site proteins can provide important insights into new drug targets and candidates,102 and several marine natural product leads have been identified using two proteomic approaches. Chemical proteomics uses small molecules as active-site-directed probes, which target specific categories of biological activity.103 Once an adduct is formed between probe and protein, the sample can be purified using affinity chromatography and separated using SDS-PAGE, and the bound protein or family of proteins can be identified by mass spectrometry, thus providing new targets for small-molecule screening.102,104,105 This technique was used to identify the macromolecular target of an anti-inflammatory sesterterpene, petrosaspongiolide M, from the marine sponge Petrosaspongia nigra, as a proteosome inhibitor.106 Similarly, heat shock protein 90 and glucose-regulated protein 94 were identified as the key biological targets of an anti-inflammatory peptide, perthamide C, isolated from the marine sponge Theonella swinhoei.107 Radeke et al.108 also used chemical proteomics to show that ilimaquinone isolated from the marine sponge Hippospongia metachromia inhibits cellular methylations by specifically interacting with the enzyme S-adenosylhomocysteinase.

belonging to three widely distributed clades: clade A, Symbiodinium microadriaticum from the anemone Zoanthus sociatus; clade B, from the anemone Aiptasia pallida and from the octocoral Pseudopterogorgia bipinnata; and clade C, from the anemone Discosoma sancti-thomae. The symbionts were obtained from laboratory cultures, and caffeine effects were assessed using 2-DE separation followed by LC-MS/MS.74 Intracolonial differences in spatial expression patterns of proteins within the octocorals Sarcophyton sp. and Capnella gaboensis were examined using 2-DE.75 Four coral species, Fungia concinna, Acropora eurystoma, and two Sarcophyton species, were utilized by Wojdyla et al.76 to identify novel fluorescent proteins. Sclerite calcification processes and biomineralization within the soft coral Sinularia polydactyla were assessed in two studies.77,78 Two sponges, Geodia cydonium and Suberites domuncula, have been utilized to investigate proteolytic enzymes.79 Marine Fish. Proteomics has emerged as a powerful tool for monitoring seafood safety in cultured and/or wild populations of fish.6 For example, differences between protein expression levels of wild and farmed sea bass, Dicentrarchus labrax, were identified using SDS PAGE followed by MALDI-TOF-MS and LC/ESI-MS/MS.80 The seabream, Sparus aurata, has been the subject of several proteomic studies aimed at enhancing production in mariculture conditions. Specifically, Schiavone et al.81 used gel-based MALDI-TOF-MS to examine muscle protein patterns that changed during storage on ice as markers for seafood freshness, and 33 proteins were ultimately identified using 2-DE coupled with nanoHPLC-ESI-QTOF analysis.82 Another study focused on the kidney proteome of seabream to better understand Moraxella sp. pathogenesis during an outbreak in an aquaculture facility.83 Differential proteomics indicated that seven proteins were significantly upregulated in the kidney tissue of infected fish.83 Another area of concern for fisheries biologists is anthropogenic contaminants, such as oil spills, and their potential threat to seafood populations. Juvenile cod, Gadus morhua, exposed to varying levels of North Sea crude oil exhibited differential expression of 137 plasma proteins, of which 29 were positively identified using MS/MS.84,85 Likewise, plasma samples of the flatfish Limanda limanda have been examined using SELDI proteomic techniques, for biomarkers of liver tumors, which are a common indicator of exposure to anthropogenic toxins.86 However, diet-derived ciguatoxins produced by dinoflagellates can also cause stress responses in fish, and Jiang et al.87 used proteomic techniques to assess resistance mechanisms to these toxins in grouper, Cephalopholis argus, and moray eel, Gymnothorax undulatus, liver tissues. Proteomics are also providing important insights into basic metabolic function in a number of marine fish. For example, in the Atlantic herring, Clupea harengus, precursor−product relationships between parent vitellogenin genes and derivative yolk proteins, which are involved in oocyte hydration and survival during early development in the saline oceanic environment, have been addressed using a comprehensive approach that encompassed polymerase chain reaction (PCR), Western immunoblotting, SDS-PAGE, and nanoLC coupled with hybrid triple quadrupole linear ion-trap.88 Likewise, osmotic stress and salt secretion in several shark species have been examined using 2-DE followed by MALDI-TOF-MS.89−92 In the European hake, Merluccius merluccius, proteomics has been utilized to investigate protein variation within natural populations from three sampling sites.93 Finally, an economically important flatfish, the Senegalese sole, Solea senegalensis, was examined to 1865



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Figure 3. Practical steps for obtaining reproducible and robust proteomic data. Considerations include (1) sample collection and handling, (2) extraction and optimization, (3) LC MS/MS analysis, (4) protein ID and quantification, and (5) functional analysis and validation. Brief descriptions of the issues are included in this figure; for a thorough discussion see the text.

Reverse chemical proteomics is a second technique to probe small natural product interactions with target site proteins.109 This approach involves cloning a cDNA library of interest into a cell-based expression system, with the resulting recombinant proteins used to target bioactive natural products immobilized on an affinity support.108 To date, this relatively new technique has been applied to the marine natural products kahalalide F isolated from the green alga Bryopsis sp. via the herbivorous saccoglossan mollusk Elysia rufescens and palau’amine from the sponge Stylotella aurantium.109 However, a cellular receptor was identified only for the former compound; the protein binding partner for this compound was identified using T7 phage displayed human disease cDNA libraries as human RPS25 in a dose-dependent manner.110 Thus, in contrast to the potential of proteomics in biosynthetic studies, chemical and reverse chemical proteomics are already providing important information relative to marine natural product drug targets/mechanism of action. Approach. Experimental Design. As in any scientific venture, experimental design in the field of proteomics requires a sound hypothesis, selection of an appropriate study population, and adequate replication to assess differences among treatment groups beyond the level of natural variation. Proteomics research is suited to assessing impacts of a diversity of treatment effects, both in natural systems and in manipulative experiments, provided that appropriate controls are employed. It is also necessary that the study organisms have a valid taxonomic identity. In experiments utilizing proteomic techniques, condition of the sample is one of the most vital considerations to retrieving quality, reproducible, proteome data. In addition, protein composition varies within and between biological cells, fluids, and tissues. Protein composition can further vary in time and space as a function of some environmental stimuli, related to either natural gradients and disturbances or experimental treatments. Thus, replication and the use of controls need to be robust enough to account for this variability. Unfortunately, to date, many proteomics studies suffer from numerous experimental design flaws, and some of these pitfalls are described in the Critical Evaluation section below. Sample Collection and Handling. Appropriate collection and storage of proteomic samples are critical aspects of preprocessing prior to protein extraction (Figure 3). Thus, an appropriate model system for any given experimental design

must be carefully considered, and the sampling strategy has to be foremost in the mind of a researcher to ensure that a proteomic study yields accurate and reproducible data. Here we provide a general overview of sample collection and preparation strategies relative to marine organisms; additional details of broader scope can be found in Bodzon-Kulakowska et al.111 The primary difference between samples collected from the marine environment and those generated, for example, in a biomedical research laboratory, is the presence of salt, which can impact proteins.112 When collecting marine samples, whether in the field or from wet lab aquaria, the organisms should be rinsed with distilled water to ensure that salt concentration is reduced. In addition, the samples should be cleaned of encrusting organisms, environmental debris, and/or other potential sources of contamination to guarantee native protein source and quality. Sample handling has serious repercussions for protein degradation and, ultimately, the loss of quantification power.9 There are two common ways to store and transport collected samples from an experimental site. The first, and generally preferred method, is to freeze the sample in liquid N2 immediately. If this is not an option, for example when transferring samples from the field to a shore-based laboratory, the specimens can be transported alive or in a dry ice/MeOH slurry prior to freezing. Alternatively, the samples can be transported in a lysis buffer prior to freezing with liquid N2. A benefit of this latter approach is that the buffer will provide some protection against enzymatic degradation of proteins due to freeze/thaw cycles, which are often inherent with airline travel from the field to home laboratories. It is important to note that some methods of anesthesia used on live organisms in accordance with IACUC (Institutional Animal Care and Use Committee) requirements might result in changes to the proteome profile due to either degradation and/or interference. Most laboratory freezers also undergo freeze/thaw cycles that can damage samples during storage. Thus, a “best practice” protocol to control for quality and reproducibility is to aliquot samples between multiple −80 °C freezers and to institute this level of caution at each stage of sample preparation (i.e., multiple aliquots of unmanipulated source samples, aliquots of extracted samples, aliquots of digested samples, and aliquots of cleaned or “ready-to-run” samples). Protein Extraction and Optimization. Sample preparation strategies can be broken down into four main steps: (1) 1866



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digestion protocol to ensure complete digestion of the sample, and multiple digestion enzymes are often used together in a stepwise fashion.127 Clean-up of contaminants in the protein mixture can be done during extraction, as well as after digestion, and this step prepares the sample for instrumental analysis. The most common contaminants are salts and detergents, and there are a number of methodologies for their removal.111 Salts can be removed by spin and microdialysis, ultrafiltration, gel filtration, and precipitation. The authors have had particularly good results with a proprietary solid-phase extraction technique that utilizes C18 resin beds (Millipore ZipTip). Detergents are commonly removed by dialysis, gel filtration, adsorption chromatography, and precipitation. It is important to note that incomplete removal of detergents can lead to buildup in nano-LC columns, ultimately resulting in column failure. Optimization. It should be increasingly clear from the preceding discussion on sample collection and processing (which fall under the simplified heading of “extraction and optimization” on our proteomics workflow; see Figure 3) that there is not a single “cookbook” approach to protein discovery and identification. Thus, the most time-consuming aspect of proteomics research is the optimization of strategies for protein solubilization, precipitation, fractionation, and reduction/alkylation/ digestion. These must be conducted for each species, tissue type, or cell line, as the steps may result in the introduction of significant variability in protein detection. Likewise, optimization includes the identification of the most advantageous instrumentation parameters; these are highly specific and will vary even if the same species or tissue is run side-by-side on different systems. While most proteomics studies have undoubtedly performed some level of sample optimization, many peerreviewed publications on marine organisms make no mention of this step, instead citing reviews119,128−139 on the benefits of optimizing sample preparation methods. However, some papers do include this information, and we present a few selected examples here. Mazzuca et al.55 optimized the protein extraction protocol for the seagrass Posidonia oceanica before characterizing protein expression in blades relative to the effect of reduced light.131 Up to eight extraction solutions were tested to optimize protein recovery from the brown alga S. japonica.49 Protein extraction procedures were compared for cultures of the harmful algal bloom species Prorocentrum triestinum and Alexandrium spp. In the former species, a 10 mM Tris buffer containing 0.02% azide produced the best results, while in the latter species, Trizol was the preferred method.132,133 However, in the case of the harmful alga Alexandrium tamarense, 40 mM Tris buffer produced poor results, while extraction in a urea/Triton X-100 buffer with TCA/acetone precipitation produced the best results.124 Thiyagarajan and Qian134 discuss the importance of optimization in regards to marine invertebrates. Their study examined protein expression patterns in larval barnacles, Balanus amphitrite, as well as several other marine invertebrates not specifically discussed. They noted that the addition of thiourea in the lysis buffer enhanced solubilization of membrane proteins, while a TCA/acetone precipitation step improved the quality and reproducibility of the 2-DE maps.134 In two species of soft corals, Sarcophyton sp. and Capnella gaboensis, Tentori and Thomson75 demonstrated that differences in the protein profiles obtained depended on the extraction buffer used. Specifically, the authors found that a Tris-based extraction buffer with the detergent Nonidet P-40 increased detection of

homogenization, (2) protein extraction, (3) digestion, and (4) cleanup for instrumental analysis. The challenges inherent within each of these steps relate to the complexity of the proteome and its broad dynamic range.113 Homogenization consists of disrupting the cells and creating a homogeneous mixture of the sample. This can be accomplished through mechanical, ultrasonic, pressure, freeze−thaw, or lytic (osmotic or detergent) techniques.111 When a sample is homogenized, the proteins in the mixture must be solubilized. Each mixture requires specific handling to avoid modification, aggregation, and precipitation of the proteins, all of which can result in protein loss. Solubilizing agents within the homogenization buffer include chaotropes, which disrupt hydrogen bonds and enable protein unfolding (most frequently used are urea and thiourea); detergents, which disrupt hydrophobic interactions and enable protein extraction (most frequently used are SDS, Triton X-100, and 3-(3-cholamidopropyl)dimethylammonio-2-hydroxy-1-propanesulfonate [CHAPS], depending on detergent ionic character needed); reducing agents, which disrupt disulfide bonds (most frequently used are dithiothreitol, dithioerythritol, triscarboxyethylphosphine, and tributylphosphine); and a protease/phosphatase inhibitor, which prevents degradation during cell disruption by endogenous enzymes (customized to the buffer, such as phenylmethylsulfonyl fluoride, ethylene diamine tetraacetic acid, aminoethyl benzylsulfonyl fluoride, sodium orthovanadate, and Sodium fluoride to name a few, as well as newer commercial mixtures). There are a number of other publications that reference specific comparisons of protein isolation and solubilization methods, including commercially available kits, and we have referenced a selection of these.9,112,114−120 Protein extraction encompasses the concentration or enrichment methods used to isolate sample protein, typically using centrifugation or precipitation, as well as the actual separation techniques. Protein precipitation can be accomplished with a variety of solvents (e.g., acetone, EtOH, phenol, or trichloroacetic acid [TCA]), in addition to commercial kits that typically pair these solvents with polymers or antibodies.121−125 The extraction procedure and the enrichment strategy are dictated by the targeted protein, and choices include separation using electrophoresis, prefractionation using antibodies or carrier ampholytes, and depletion of high-abundance proteins using solid-phase or affinity chromatography. Finally, the concentration of the extracted protein must be measured, most commonly by some variation of the Bradford assay.126 The assay parameters will vary depending on the chemical composition of the buffer in which the sample is reconstituted, so it is critical to know the molarity of salts, detergents, and reducing agents present in the homogenization or solubilization buffer. Digestion of the protein is typically preceded by a reduction step to disrupt disulfide bonds and promote protein unfolding, and an alkylation step to modify cysteine residues.111 It is important to note that temperatures higher than 55 °C must be avoided if urea is present to prevent urea-based carbamylation of lysines. The most commonly used enzyme for protein digestion is modified trypsin, which has high specificity for cleavage at the carboxylic side of arginine and lysine and generates peptides in the useful mass range for mass spectrometry.112 Other proteases are also used, most notably the endoproteinases Lys-C (cleaves at the carboxylic side of lysine), Glu-C (cleaves at the carboxylic side of glutamic acid), Asp-N (cleaves at the amino side of aspartic acid and cysteine), and Arg-C (cleaves at the carboxylic side of arginine). Modified trypsin can also be used in a double 1867



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reasons for and against the use of “related-species” databases for protein identifications. Fröhlich et al.148 showed that a SwissProt subset database, the Metazoa subset, generated more protein identifications in Daphnia pulex than did a database of a species from the same subphylum, Drosophila melanogaster, with a completely annotated genome sequence. However, using a related species-specific database (D. pulex) or a genus-specific database (Daphnia longicephala) generated more identifications than either the SwissProt subset or subphylum-specific databases.148 Likewise, comparing expressed sequence tag (EST) sequences of poorly annotated crustaceans such as shrimp, lobster, and crab with whole-genome proteomes of model organisms (the insect D. melanogaster and the nematode Caenorhabditis elegans) generated more protein identifications for phylogenetically similar species.149 To decide which database (i.e., “generic” or “related-species”) generates the best results, the total number of peptides identified in the sample relative to the number of peptides detected but not matched to a database should be considered. Peptide coverage of a protein and a high number of sequential b- and y-ions in each peptide are also important. Therefore, in addition to numbers of proteins identified, robust data assessment cannot be overlooked. Protein Quantification. Quantitative 2-DE followed by MS analysis has been widely used in marine proteomics to identify disease states, exposure to toxins, stress, and seafood quality.150,151 Owing to the well-established limitations of 2-DE, such as gel-togel variation and limited dynamic range, difference gel electrophoresis (DIGE), in which equal amounts of samples from different treatment groups are labeled with spectrometrically resolvable dyes, is an alternative method for gel-based protein quantification152 An internal standard allows for normalization of the ratios between the dyes to determine protein expression changes by fluorescence. Alternatively, stable isotope labeling incorporates different tags that are detected by MS.147,152 There are various approaches to this, including stable isotope labeling with amino acids in cell culture (SILAC), isotope coded affinity tags (ICAT), and iTRAQ, but the concept remains the same: tagging results in quantifiable mass shifts of the labeled amino acids. In label-free proteomics, absolute quantification can be accomplished using internal standards normalized to the data with commercially available software (e.g., PLGS). For example, PLGS measures differential expression in protein abundance based on peptide ion peak intensities observed in low collision energy mode. Identical peptides from triplicates of each sample are clustered based on mass precision and a retention time tolerance using the PLGS clustering algorithm. In Mascot, quantitative changes in proteins are also based on ion intensities calculated by summation of all spectra identified from each sample group,144 while Serac PASC calculates ratios of ion intensities for peptides matched between different experiments and averages the peptide ratios as a measure of protein change in stable labeling studies. Protein Validation and Data Analysis. While optimization strategies ensure that sample proteins are identified and quantified reproducibly, validation ensures the quality of those data. Specifically, validation assesses accuracy and precision of the protein data set typically using either MS techniques or independent molecular techniques. Mass Spectrometry Validation. Tandem MS (MS/MS) analysis of the peptides obtained by proteolysis of a complex mixture of proteins is a widely employed recent technique in proteomics. However, bioinformatic tools rely on in silico databases using different scoring methods, statistics, and probability models. Proteins matched to databases have to be validated as

membrane-bound proteins in these cnidarians over the buffer alone. These examples highlight the need for optimization of extraction procedures for each species, as well as structural aspects of proteins present in soluble and insoluble fractions of specific tissue groups. Nilsen et al.135 mentioned that optimization tests were performed on plasma samples of the commercially important cod G. morhua exposed to alkylphenol, but do not present any information on what procedures were used. However, Rajan et al.,136 in an investigation of the cod skin mucosal proteome, noted an increase in the quality of protein coverage on 1D and 2D gels when they utilized a commercially available protein cleanup kit (BioRad), as well as a nonstandard detergent, aminosulfobetaine-14, in their sample buffer, compared to the more classically used detergent CHAPS. Protein Identification and Quantification. Protein identification occurs after the raw data from the mass spectrometer are acquired and compared to an existing database.137 Due to the large amount of raw data generated in a single analysis, identification is possible only with the implementation of complex in silico clustering algorithms using heuristic, probabilistic, and Bayesian models.138 Mascot, which uses a probabilistic clustering algorithm to determine the odds that a fragmented peptide will result in an observed spectrum, is the most widely used program for protein identification.139 SEQUEST is another commonly used program that uses empirical and correlation measurement models to score the alignment between observed and predicted spectra140,141 As the field of proteomics has advanced, Bayesian and heuristic algorithms have been developed, including OMSSA,142 X!Tandem,143 Xcalibur,144 ProteinLynx Global Server (PLGS),145 Phenyx,146 and ProteinPilot.147 Although the mathematical principles of these algorithms differ, the search parameters to obtain protein identifications are consistent. Peptide and fragment mass tolerance, type of digestion enzyme, allowed missed cleavages, fixed modifications, variable modifications, number of peptide matches per protein, and a false positive rate are parameters that determine the accuracy of the identification. The number of peptides identified can increase or decrease as these parameters are changed, and increasing the peptide and fragment mass tolerance will increase the number of proteins identified. By increasing the minimum number of peptide matches per protein, the certainty of the match increases at the expense of missing small proteins or polypeptides. Therefore, it might be necessary to run multiple searches with different parameters. The false positive rate (FPR) is important because an identification search ceases when the FPR is reached. The faster the FPR is reached during a search, the faster the search will stop. However, this does not guarantee that all the proteins in a sample will be identified; searches against inadequate or nonspecific databases can fall into this category. Databases. Currently there are 22 complete proteomes of marine organisms out of 243 annotated in the UniProt database and five more resulting from the automatic pipeline of the complete genomes in Ensembl (Table 2). A complete proteome is the entire set of proteins expressed by a specific organism, that is to say, the set of protein sequences that can be derived by translation of all protein coding genes of a completely sequenced genome (www.uniprot.org). The lack of species-specific databases for protein identification in marine species is by far the most significant limiting factor in proteomics research. As a result, protein searches are conducted against generic databases (i.e., UniProt, SwissProt, and NCBInr) or against “relatedspecies” databases for cross-species comparisons. There are 1868



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sequences. This makes RNA-Seq attractive for nonmodel organisms, such as marine organisms. Critical Evaluation. Experimental Design Considerations. Experimental design in the field of proteomics, as in other fields of science, encompasses the formulation of a hypothesis, the selection of a study population(s), and the allocation of experimental resources to achieve an unbiased, in-depth view of the protein complement of the experimental unit, whether that represents cellular, organismal, or population levels of organization.154 Hunt et al.155 identified several key issues in proteomic studies that might result in experimental error, including large numbers of measurements per sample; analytical variation inherent to protein extraction, separation, and data acquisition; and biological variation of environmental or genetic origin. While it may not be possible to control for all these sources of variation, many of the issues can be avoided with standard experimental procedures of randomization and blocked designs.154−156 Avoiding systematic errors associated with different sample collection protocols, incomplete extraction/digestion techniques, suboptimal sample storage conditions, instrument calibration issues over the duration of sample runs, erroneous group comparisons, and even the use of outdated algorithms for data analysis are crucial to a valid proteomic study.157 Inherent to the reduction of these experimental errors is sufficient replication at both the biological and technical levels and also sufficient sampling of the proteins (i.e., “instrumental replication”). An a priori power analysis can help optimize the experimental design by providing an estimate of the minimal number of replicates.158 However, few proteomics studies consider appropriate experimental design and replication, if any, rarely exceeds three biological replicates.159 It is also common to see “pseudoreplication”,160 either by design (e.g., by ̈ . For pooling of small samples) or due to statistical naiveté example, in a study of the proteome of a sea urchin tooth, 100 individuals were collected but then pooled into one sample, from which two fractions were obtained during protein extraction;161 this effectively results in a single biological replicate for protein identification. In contrast, a study of pollution effects on mussels provided some biological replication (i.e., 3 or 4 individuals per treatment site), but no technical replication was reported.162 Evans et al.32 compromised biological replication (= duplicate marine bacterium cultures) of wild-type (D2Wt) and wmpD mutant (D2W3) Pseudoalteromonas tunicata with technical replicates (n = 2), likely at the expense of statistical power and increased false positives.163−165 Nonetheless, at least two marine proteomic studies have incorporated high numbers of both biological and technical replicates. Monti et al.80 utilized nine biological replicates of both farmed and wild-caught sea bass, D. labrax, with five technical replicates of these samples on each of two different types of protein chips. Addis et al.82 utilized 540 individual gilthead sea bream, S. aurata, representing caged and wild populations, to map the muscle proteome. This study concurrently assessed the question of individual versus pooled samples and found significant differences in the visible protein expression profiles. A more comprehensive study that discussed sample pooling focused on the mussel M. edulis and addressed three major concerns: biological averaging of protein expression, reduction of biological variance, and the effects of pooling on possible dilution of proteins.164 While they were able to resolve the former two issues, the authors found that a percentage of proteins visible within individuals were not visible in the pooled samples. As they pointed out, these lost proteins might be

specific proteins using various methods. Manual validation is an option, but it is practically very difficult when large numbers of protein hits are returned in a search. Randomized or reversed database searches, also known as target decoy database searches,153 have gained importance in recent years as a validation tool that filters false positive rates. These approaches can apply more stringent search parameters, including peptide and fragment ion mass tolerance, number of peptide matches per protein, checks for series of consecutive b- and y-ions in MS/MS data, and incorporation of possible modifications that can occur during the process of protein extraction and digestion. Proteins can also be validated using third party software such as Scaffold (Proteome Software, Inc.), which combines results from various search engines. Independent Molecular Validation. Although it can be much more time-consuming and costly, results obtained with additional independent molecular techniques reinforce studies on protein expression and often provide additional biological insights into their function. These techniques include immunoblotting (e.g., Western blotting), ELISA (enzyme-linked immunosorbent assay), protein microarrays, and immunohistochemistry. Immunoblotting is a commonly used semiquantitative technique that allows the detection of specific proteins, following gel electrophoresis and membrane blotting, using antibodies. In contrast, ELISA represents several quantitative techniques (direct, sandwich, and competitive) that work by the same principle as immunoblotting. While these techniques are limited to the detection of a single protein at a time, protein microarrays (analytical, functional, and reversed phase) allow many proteins to be tracked in a single experiment. However, protein microarrays are cost-prohibitive and limited by the lack of antibody libraries for many species, particularly marine organisms. Immunohistochemistry represents another validation strategy that has the unique advantage of identifying differentially expressed proteins within specific cell types and tissue. An alternative approach to “immuno”-driven techniques is to validate protein expression results using enzymatic assays. In these assays a target enzyme is selected, and thus the reaction it catalyzes is known. There are many different types of commercially available enzymatic assays (e.g., oxidative stress assays) that can be of interest when studying the effect of stressors or contaminants in the marine environment. Finally, changes in genomic and proteomic expression together provide a fuller understanding of biological function from transcription to translation. Because changes in the expression of a gene do not always correlate with changes in expression of the protein it encodes, genomic techniques are not a complete validation of results obtained in proteomics. However, if running genomic expression experiments is logistically possible, one would consider the scenario of proteogenomic studies optimal. Realtime (RT) PCR is a common technique to investigate changes in mRNA expression, and it is well established in many molecular biology laboratories. A high-throughput genomics technique that allows the study of changes in the expression of many genes in one experiment is DNA microarrays. However, because gene sequences of many marine organisms are not annotated, the availability of this approach is currently limited. A newer technique is RNA-Seq, also called whole transcriptome shotgun sequencing. Next-generation sequencing instruments allow deepsequencing coverage of the transcriptome without limitation in detecting transcripts that correspond to known genomic 1869



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biologically important to the treatment differences.164 A corollary consideration to the issues of pooling is the need for instrumental replicates to ensure “uniformity of representation” and “accuracy and level of detail of the experiment description”.166 While there have been efforts to identify minimal standards for proteomic studies,167−173 information regarding the performance criteria for instrumental replication (i.e., multiple internal runs, frequency of instrument calibration, choice and utilization of internal standards, etc.) remains unclear within the literature. There are many other important considerations pertaining to experimental design in proteomics studies, whether the study is one of discovery (i.e., global) proteomics or one of biomarker (i.e., targeted) proteomics. The location and size of proteins are other parameters that must be incorporated into the experimental design, since resource allocation will differ with extraction method, fractionation, and depletion, as well as molecular weight ranges.174 Between-run variation can be minimized through training on available instruments, and regular calibrations and maintenance tasks must be factored into the overall experimental design to reduce any “run date effect” and limits of dynamic range.175 Within-run variation can be reduced by only accepting proteins that occur in more than one replicate.176 In many cases, a pilot study can be beneficial to researchers to identify experimental design flaws.177 The biomedical field has been particularly cognizant of these issues, and there are numerous reports that cross-check and investigate the validity of proteomics data, including the scrutiny of experimental design.113,166,174,177,178 Data Analysis Considerations. Data acquisition specifics, detailed descriptions of raw data processing parameters, differential expression analysis criteria, and database information are essential for scientific reproducibility in proteomics research. 2-DE followed by MALDI-TOF-MS and data processing performed using Mascot is the most common method for protein identification and quantification in marine organisms (see references in Table 1). Furthermore, protein differential expression in 2-DE is determined by differences in spot density detected by commercially available software programs based on two approaches: warping and creation of a fusion gel before spot detection, and spot detection on every single gel before spot matching.179 In addition to differential expression, when differences in spot density are correlated with an additional end point, statistical analyses such as principal component analysis (PCA) have been used.93,180 For example, population frequency distributions and protein features of the liver and brain in European hake, M. merluccius, were investigated using differences in 2-DE spots.93 To observe patterns of protein expression, the authors used two multivariate clustering analyses, PCA and hierarchical clustering. They further determined which spots were population-specific by using multivariate linear discriminant analysis. As a result, they found clustering within populations and identified spots that distinguished 100% of the individuals within a population. More recently, approaches other than 2-DE, such as LC-MS/ MS, have been used,47,181 but there is a lack of consensus on how high-throughput proteomic data analysis should be described and reported. For example, to determine differential protein expression in the alga, S. gracilis, relative to copper exposures, Contreras et al.50 searched an NCBI database of related organisms using BLASTP for 19 overexpressed proteins potentially involved in copper tolerance. However, the authors did not report which related-species databases were used or how the results might have differed when the raw data were compared against multiple databases. The authors also failed to

describe the criteria for protein alignment to BLASTP and criteria for differential expression analysis. In contrast, the proteomes of the thylakoid membranes of two diatom species, Thalassiosira pseudonana and Phaeodactylum tricornutum, were compared by LC-MS/MS analysis.181 A data-dependent acquisition method was used, peak lists were created by Analyst QS, and database searches were performed by Mascot. In this case, the authors reported details of the data-dependent acquisition scan and that of two product ion scans, as well as the criteria for selection of fragmentation ions. After raw data acquisition peak list files were created, the first database used contained species-related protein sequences from NCBI, while a second database included the original diatom genome project JGI database. For Mascot, database search settings included precursor-ion mass tolerance, fragment-ion mass tolerance, missed trypsin cleavages, and modifications of carbamidomethylation of cysteine and methionine oxidation. Tissue-specific protein expression of the spiny dogfish shark, Squalus acanthias, was performed using 10 internal standard spots for quantification purposes.89 The MALDI-TOF-MS data were searched using Mascot; MSBLASTP2 and the de novo explorer module from Applied Biosystems were used to perform sequencing of each MS/MS ion. In this study, the authors provided the search criteria that were used for successful identification of proteins and their closest orthologs. In addition, they reported that more proteins were identified by MSBLASTP2 than Mascot,89 which emphasizes the value of using multiple search engines. It should be standard practice to report raw data processing parameters of this nature. Another important parameter that requires methodological discussion is the number of peptide matches accepted for positive protein identification. To characterize the proteome of the red alga Gracilaria changii, Wong et al.48 ran a peptide mass fingerprinting analysis. Protein identifications were performed using Mascot probability-based MOWSE scoring and ProFound Bayesian rank Z scoring against the NCBI database. In their results, the authors reported not only the score of the significant matches but also the number of peptide matches per protein identified and the percent coverage of the peptides to the theoretical protein. However, this level of detail is rarely provided, and it is likely that identified “proteins”, based on single peptide alignments, represent anomalous data rather than experimentally robust results. Gene ontology and pathway analyses are standard practice in genomics, and it is common to find these types of analyses in proteomics of organisms with a sequenced genome. In one study, after performing searches against an in-house fish protein database, the functional categories of identified proteins were determined using the Web-based QuickGO tool (www.ebi.ac. uk/QuickGO/) and MIPS Functional Catalogue (http://www. helmholtz-muenchen.de/en/mips/projects/funcat/index. html).93 The use of two different approaches for protein function identification can reiterate a concomitantly identified function, as well as identify a novel function. Recently, Hockin et al.182 investigated proteomic responses to nitrogen stress in the diatom Thalassiosira pseudonana and demonstrated the functional categories of the differentially expressed proteins using the Kyoto Encyclopedia of Genes and Genomes (KEGG). The authors discussed each of the functional categories and depicted pathways demonstrating nitrogen starvation effects on multiple biological processes including amino acid metabolism, photosynthesis, and carbon metabolism. Interestingly, Hockin et al.182 also discussed relationships between proteomic and 1870



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For example, protein expression data can supplement the current weight-of-evidence risk assessment paradigms to better understand anthropogenic insult in the marine environment.185 Likewise, proteomics can provide important functional information regarding biosynthetic pathways of novel marine natural products, as well as insights into mechanism of action and molecular targets.187 While these specific research angles have rarely been addressed in the marine environment, there is ample evidence from terrestrial and aquatic ecosystems that the potential rewards are significant.188,189 There remain key studies that must be designed to guide the appropriate implementation of proteomics research. Fundamentally, there is a need to understand the concept of biological noise in protein response, including how protein expression is constitutively altered over time, organism sex or age, or natural environmental fluctuations (salinity, seasonal temperature, etc.).186 Even though field studies are more technically challenging, these are clearly needed to address the natural variability in responses at the protein level. In addition, it will be critical to phenotypically anchor proteomics results with meaningful physiological effects at both the organismal and population levels of biological organization. Without an understanding of how the protein response is related to biological impact, the implications of the results to marine environmental change, stressor exposure, or biomarker development are limited. As such, proteomic studies must include appropriate taxonomic validation of samples to ensure results represent experimental variation and not species-specific differences in protein expression. Even with these challenges in mind, there is no doubt that marine proteomics is a rapidly expanding and powerful integrative molecular research tool from which our knowledge of the marine environment will be significantly expanded.

transcriptomic changes; this work is a good representation of the bigger picture of biological function. While transcriptomics or proteomics alone can provide much information on the cellular/molecular conditions relative to the environment, a systems biology approach will ultimately provide a better understanding of biological function. Validation Considerations. As noted, validation is an incredibly important, and often overlooked, component of proteomics, and there are examples of studies that have applied due diligence to this regard. For example, a quantitative proteomic study of the effects of solar radiation on the marine bacterium Sphingopyxis alaskensis employed iTRAQ labeling for both relative and absolute quantification.183 Reporter ion peaks were further used to estimate the relative abundances of proteins by searching the S. alaskensis database using ProQuant software, and a data-dependent acquisition mode for MS and tandem MS spectra was used to search the S. alaskensis tryptic digest database with Mascot. Identified proteins were manually validated to ensure the presence of consecutive b- and y-ions, and Scaffold was used to further validate the identified proteins and to identify proteins that were unique to particular treatment groups. While some studies have utilized either MS-based validation or independent molecular validation, the best approach combines both strategies. For example, RT-qPCR in combination with 2-DE was used to validate the identity of distinct strains of the brown alga E. siliculosus that were adapted to copper stress.51 Likewise, a comprehensive proteomic and transcriptomic profile of an economically important flatfish, S. senegalensis, assessed gene expression changes during spermatogenesis.94 Differential protein expression during various stages of spermatogenesis was identified using 2-DE, and the resulting spots were subjected to MALDITOF-MS and nano-ESI IT MS/MS; these were compared to the NCBI database using BLAST. The proteins identified were validated by comparing theoretical and experimental molecular mass (Mr) and isoelectric point (pI) values, number of peptides assigned, quality of de novo sequences, and q-PCR.

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AUTHOR INFORMATION

Corresponding Author

*Tel: +1-662-915-1053. Fax: +1-662-915-6975. E-mail: [email protected].

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Notes

CONCLUSIONS Proteomics techniques represent a widely underutilized research tool in the field of marine sciences. Protein measurements include PTMs and relate directly to functional mechanisms. The knowledge gained from proteomics studies significantly enhances the understanding of genomic and transcriptomic data,10 as well as providing detail on the overall metabolomic profile.184 Only by combining these levels of information will scientists be able to fully understand complex biological processes and their roles in ecological interactions in the marine world. To date, proteomics techniques have been utilized to investigate marine vertebrate and invertebrate physiology, development, biology, taxonomy, toxicology, seafood safety, genetic variability, susceptibility to disease, and responses to diverse environmental changes.6,10,185,186 Currently, the major limitation holding back the field of proteomics is the lack of available annotated genomes for a broad diversity of marine organisms. It is surprising that certain species (e.g., the oyster Crassostrea virginica and the sea urchin Strongylocentrotus purpuratus) lack this level of detail despite their importance as model organisms in physiological and ecological contexts (see Table 2). As genomic information continually becomes available with the speed and ever-decreasing costs of whole genome sequencing and enhanced bioinformatics, proteomics will provide answers to many fundamental biological questions.

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS D. Ferreira provided a critical evaluation of this manuscript; for his time and insights we are grateful. Much of the research related to our work on marine proteomics and the technical issues discussed within this review were funded by NOAA NIUST grants to M.S., D.G., J.R., and K.W.

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REFERENCES

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Marine Proteomics: A Critical Assessment of an Emerging Technology

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