Translational plant proteomics: A perspective

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Review

Translational plant proteomics: A perspective☆

Ganesh Kumar Agrawala,⁎, Romina Pedreschib, Bronwyn J. Barklac,Laurence Veronique Bindschedlerd, Rainer Cramerd, Abhijit Sarkare, Jenny Renaut f,Dominique Jobg, Randeep Rakwala, h, i,⁎⁎aResearch Laboratory for Biotechnology and Biochemistry (RLABB), GPO Box 13265, Kathmandu, NepalbFood and Biobased Research, Wageningen University and Research Centre, P.O. Box 17, 6700 AA Wageningen, The NetherlandscInstituto de Biotecnología, Universidad Nacional Autónoma de Mexico, A.P. 510-3 Col. Miraval Cuernavaca, Morelos 62250, MexicodDepartment of Chemistry, University of Reading, Reading RG6 6AD, United KingdomeCSIR-SRF, Laboratory of Air Pollution and Global Climate Change, Department of Botany, Banaras Hindu University, Varanasi 221005, UP, IndiafCentre de Recherche Public-Gabriel Lippmann, Department of Environment and Agrobiotechnologies (EVA), Belvaux, GD, LuxembourggCNRS/UCBL/INSA/Bayer CropScience Joint Laboratory, UMR 5240, Bayer CropScience, 14-20 rue Pierre BAIZET, F-69263, Lyon Cedex, FrancehGraduate School of Life and Environmental Sciences, University of Tsukuba, 1-1-1 Tennoudai, Tsukuba 305-8572, Ibaraki, JapaniDepartment of Anatomy I, School of Medicine, Showa University, 1-5-8 Hatanodai, Shinagawa, Tokyo 142-8555, Japan

A R T I C L E I N F O A B S T R A C T

Translational proteomics is anemerging sub-discipline of the proteomics field in the biologicalsciences. Translational plant proteomics aims to integrate knowledge from basic sciences totranslate it into field applications to solve issues related but not limited to the recreational andeconomic values of plants, food security and safety, and energy sustainability. In this review,we highlight the substantial progress reached in plant proteomics during the past decadewhichhas paved theway for translational plant proteomics. Increasingproteomics knowledgein plants is not limited to model and non-model plants, proteogenomics, crop improvement,and food analysis, safety, and nutrition but to many more potential applications. Given thewealth of information generated and to some extent applied, there is the need formore efficientand broader channels to freely disseminate the information to the scientific community.This article is part of a Special Issue entitled: Translational Proteomics.

© 2012 Elsevier B.V. All rights reserved.

Available online 9 April 2012

Keywords:BiomarkerBiodiversityEducation awarenessFoodNutritionStress

Contents

1. Introduction: From plant proteomics to translational plant proteomics . . . . . . . . . . . . . . . . . . . . . . . . . 45892. Translational plant proteomics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45893. Information transfer between model and non-model plants to advance knowledge in plant biology . . . . . . . . . 4590

J O U R N A L O F P R O T E O M I C S 7 5 ( 2 0 1 2 ) 4 5 8 8 – 4 6 0 1

☆ This article is part of a Special Issue entitled: Translational Proteomics.⁎ Correspondence to: G.K. Agrawal, Research Laboratory for Biotechnology and Biochemistry (RLABB), GPO Box 13265, Kathmandu, Nepal.

Tel.: +81 29 853 4653; fax: +81 29 853 6614.⁎⁎ Correspondence to: R. Rakwal, Graduate School of Life and Environmental Sciences, University of Tsukuba, 1-1-1 Tennoudai, Tsukuba305-8572, Ibaraki, Japan.

E-mail addresses: [email protected] (G.K. Agrawal), [email protected] (R. Rakwal).

1874-3919/$ – see front matter © 2012 Elsevier B.V. All rights reserved.doi:10.1016/j.jprot.2012.03.055

Ava i l ab l e on l i ne a t www.sc i enced i r ec t . com

www.e l sev i e r . com/ loca te / j p ro t


4. Proteogenomics to annotate genomes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45904.1. The past and present of plant genomes and their annotation . . . . . . . . . . . . . . . . . . . . . . . . . . 45904.2. Structural and functional gene annotation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45904.3. The proteogenomics workflow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45914.4. The future of plant genomes and their annotation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4592

5. Biodiversity screening . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45926. Tolerance to biotic and abiotic factors for crop improvement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45937. Food analysis, safety, and nutrition (human health) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4594

7.1. Food composition and quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45947.2. Food safety . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45957.3. Food authenticity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45957.4. Nutrition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45957.5. The perspective of food science and technology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4596

8. Energy sustainability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45969. Global action plan on plant proteomics (GA3P) in facilitating the transfer of knowledge and discoveries . . . . . . . 4596

10. Concluding remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4597Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4597References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4597

1. Introduction: From plant proteomics totranslational plant proteomics

Tremendous progress in plant proteomics has beenmade since2000 when few proteomics reports were published and plantproteomics was in its infancy. Today's progress is unquestion-able and can be evidenced by the availability of several bookssolely devoted to plant proteomics [1–5] and several specialissues on plant proteomics published by the journals Proteomics(http://onlinelibrary.wiley.com/doi/10.1002/pmic.v11.9/issuetoc),Phytochemistry (http://www.sciencedirect.com/science/journal/00319422/72/10), and Journal of Proteomics (http://www.sciencedirect.com/science/journal/18743919/74/8). Moreover, there areseveral review series in plant proteomics [6, and referencestherein], rice proteomics [7,8, and references therein], and plantphosphoproteomics [9, and references therein] available to date.These book reviews and special issues describe the progressmade in plant proteomics but also highlight the need for opendiscussion to generate visionary ideas in plant proteomics.Progress includes but it is not limited to: (i) the provision ofqualitative and quantitative plant proteomics techniques (e.g.,sample preparation and fractionation to gel-based and gel-freeapproaches, peptide analysis and confident protein assignment,database development and bioinformatics tools, and the processof analyzing andmining the data to address the biological ques-tions of interest), establishing a targeted and global proteome, ormapping the post-translationalmodifications (PTMs); and (ii) theexpansion of proteomics sub-disciplines [1] from expressionproteomics to functional, structural, and to translationalproteomics.

Progress in plant proteomics is the input for “translationalplant proteomics”, which is the topic of discussion of thisreview. The main aims of this review are: (i) to definetranslational plant proteomics and (ii) to show the progressmade in some plant biology related research areas. We alsoenvisage global engagement of the plant proteomics scientificcommunity in support of translational plant proteomics.

2. Translational plant proteomics

“Translation” is derived from the Latin word translatio, whichmeans to bring across. Before the term translational proteomicswas coined, “translational research”had already been a familiarterm, particularly in connection with medical research. Thus,the Translational ResearchWorking Group (TRWG) has definedit as: “translational research transforms scientific discoveriesarising from laboratory, clinical, or population studies intoclinical applications to reduce cancer incidence, morbidity, andmortality” (see http://www.cancer.gov/researchandfunding/trwg/TRWG-definition-and-TR-continuum; accessed October26, 2011). “Translational proteomics” focuses on the translationof basic proteomics science and is defined by Rice et al. as “theprocess and platforms that facilitate the delivery of applica-tions derived from proteomics analysis” [10]. Translationalproteomics research can be further defined as “a meaningfulway to think and conduct proteomics research with the mainobjective of delivering fruitful applications to solve societalissues.” As Sir Peter Medawar once said: “No branch of sciencecan be called truly mature until it has developed some form ofpredictive capacity”. This quote perfectly describes translation-al proteomics.

Translational plant proteomics can thus be defined as“applying the outcome of any discovery or technologicaldevelopment in plant proteomics to solve issues related butnot limited to the recreational and economic values of plants,food security and safety, energy sustainability, and humanhealth”. Fig. 1 depicts translational plant proteomics taking itsinput from the field of plant proteomics, which is typicallyunderpinned by the two pillars of gel-based and gel-freeproteomics in conjunction with mass spectrometry (MS) andbioinformatics. Translational plant proteomics is certainlydriven by advances in plant proteomics but can also enrichplant proteomics. In the following sections different areaswithintranslational plant proteomics are discussed: information trans-fer between model and non-model plants, proteogenomics,

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biodiversity, crop improvement, and food analysis, safety, andnutrition.

3. Information transfer between model andnon-model plants to advance knowledge inplant biology

Model plants (or reference plants) have been assigned based ontheir important characteristic features including small genomesize, short life cycle, ease of use and cultivation, usefulness inaddressing the biological question/s of interest, and theavailability of sufficient sample material to conduct theresearch of interest. In the 21st century, the availability ofgenomesequenceshas becomea critical feature for a plant to becalled a model plant. Within translational plant proteomics,model plants typically have sequenced genomes while non-model plants have their genome rarely sequenced. Thus,modelplant proteomics (e.g., of Arabidopsis and rice) is far moreadvanced than non-model plant proteomics [see 1,5,7,8,11,12].

Knowledge gained earlier from the model plants ofArabidopsis and rice has been transferred to develop theproteomes of non-model plants by applying and/or optimizingtechniques and strategies used in the model plants. Today,proteomes of many economically important non-model plantsare available including banana, papaya, sugarbeet, and sugar-cane, which has been largely due to the transfer of proteomicsdata and technology obtained from model plants. The reversehas also been seenwhere proteomics knowledge obtained fromnon-model plants was utilized for the analysis and develop-ment ofmodel proteomes; progress in evolutionary proteomicsis one example. There are a few excellent reviews thatcomprehensively cover the transfer of knowledge (such astechniques) between model and non-model plants [13–19].

There are also a number of areas in plant biology that can betaken as excellent examples including seed biology [20,21],organelle proteomics [22], stress proteomics in plants (seeSection 6), protein phosphorylation [9, and references therein],and trees [23]. Knowledge transfer between model and non-model plant proteomeshas revealed that each plant needs to beuniquely/independently studied as many proteins and modifi-cations are highly plant-specific.

4. Proteogenomics to annotate genomes

4.1. The past and present of plant genomes and theirannotation

The implementation of third generation DNA sequencing hasaccelerated genome-wide sequencing of plant species. Manymajor food crop genomes are now available after the firstplant genomes were completedmore than a decade ago— themodel plant Arabidopsis thaliana in 2000 [24] and rice in 2002[25,26] (http://www.plantgdb.org/OsGDB/) (map-based se-quence annotation in 2005 [27], http://rice.plantbiology.msu.edu/). Examples are maize [28], sorghum [29], soybean [30],potato [31], and domesticated apple [32], to name but a few[33,34]. The list is increasing rapidly as many more plantgenomes of economic importance are being sequenced.However, plant genome sequencing and annotation are chal-lenging as plant genome sizes are typically large, containing asubstantial proportion of repetitive transposable elements. Forinstance, the maize genome is constituted of 2.3 billion basepairs [28]. In addition, polyploidy is yet another challenginggenome trait common to numerous, if not most of the majorcrops, such as wheat, potato, tomato, oil seed rape, Brassica sp.,banana, and strawberry. For these, independent sequencing ofeach of the wild-type haplotypes is required [35].

4.2. Structural and functional gene annotation

In functional genomics analyses, DNA sequences are notcomprehensively informative per se. Genemodels and function-al annotation of such gene models help to elucidate biologicalprocesses. The structure of eukaryotic genes is constituted bydiscontinuous coding regions (exons) interrupted by non-codingregions (introns). Structural annotation (bioinformatics transla-tion) of a genome is to find the coordinates of the protein-encoding genes. Alternative bioinformatics approaches are usedin conjunction to generate open reading frame (ORF) genemodels, e.g., in silico prediction of protein-encoding genes. Genestructure features such as the start and end of a coding region orthe splice junctions between exons and introns are predicted abinitio using several gene finder algorithms (such as Eugene,FGENESH, Augustus, Genscan or GeneMark) [36,37]. However,such prediction tools arenot highly reliable and genemodels areoften inaccurate, in particular if the analysis is performed usinggene finder algorithms trained on a different template species.Therefore gene modeling is improved by using machinelearning based prediction programs fed with a training set ofESTs or messenger RNA (mRNA; transcript) sequences from thespecies being annotated [38] (Fig. 2). The larger the training set,

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Sample Preparation & Fractionation

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PLANT PROTEOMICS

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Safety, & Nutrition• Crop Improvement

• Biodiversity• Proteogenomics-Genome Revisit• Model to Non-model & vice-versa

&Bioinformatics

Fig. 1 – Translational proteomics in plants. Proteomics isevolving as a technology to plant proteomics and now totranslational plant proteomics in exploiting the discoveriesinto applications and enriching the existing knowledge ofplant biology.

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the more accurate the gene models might become. Therefore,massive sequencing of transcripts similar to recently publishedwork, describing over 20,000 uniquely assembled cDNA se-quences of barley [39] andmaize [40], is desirable. However, it isoften possible to annotate the genome using established geneprediction tools, which have been “trained” for related species.In any case, it is best practice to validate the choice of thereference organism selected for the structural annotation of thegenome of a particular species by preliminary annotation of asmall set of genes. At a second stage, structural annotation canbe improved bymanual intervention using the BLAST sequencealignment tool for comparing and matching the predicted genemodels to known genes or proteins of similar sequence. Again,cross species information is being used.

Finally, a more definitive validation of gene prediction canbe achieved by protein expression analysis. If the genome ofthe species of interest is sequenced, large-scale shotgunproteomics can be employed for the detection and characteri-zation (e.g., sequencing) of expressed proteins at the proteome-wide level. Such an approach is commonly called proteoge-nomics. As there can be a significant discrepancy between thelevel of transcripts and proteins expressed, partly due to theexistence of non-coding mRNAs, proteogenomics analysis is theultimate proof for a gene model. Analogous to the information

provided by transcript sequencing proving the existence ofmRNAs, peptide sequence information generated by MS-basedproteomics shows the existence of proteins. Such peptideinformation can also be used for the discovery of unpredictedORFs [reviewed in 38,41]. This is even true for the well-characterized and annotated genomes of model organisms suchas fly, human,mouse [42],Arabidopsis [43], and rice. The power ofproteogenomics to re-annotate the genome is exemplified bythe identification of novel ORFs (13% of the total ORF set) in anin-depth proteogenomics study in Arabidopsis [43], which werepreviously undetected by ab initio gene prediction or transcrip-tomics data. Other proteogenomics studies have been describedfor rice [44] and pathogenic fungi of wheat and barley [45,46].

4.3. The proteogenomics workflow

There are several reviews that describe the proteogenomicsapproach [16,36,38,47–49]. Fig. 2 summarizes the proteoge-nomics approach in the context of a wider genome annotationworkflow in combination with other methods from the fieldsof genomics, transcriptomics, and bioinformatics. Althoughproteogenomics approaches are extremely valuable in vali-dating and discovering new ORFs, as described in the sectionabove, such approaches remain challenging for the following

Identification of peptidesusing

protein search engineand

genomic DNA contigs databaseor assembled ESTs database

ESTs or other transcriptomics data

Re-annotation of gene models(similarity searches, GO, PFAM,

structure prediction, etc…)

Grouping of peptides to existinggene models

Mapping of peptides to genome

Large scale shotgun proteomicsusing different tissues,treatments, time points

Genome (DNA) sequencing

Genome assembly

Identification of ORFs using genefinder programs

Validation, modificationand / or creation of new

gene models

mRNA / cDNA sequencingusing different tissues,treatments, time points

Genome informationmRNA information Protein information

Genome draft template

Generation of an improved ORF database

des

Fig. 2 – A schematic depiction of the general workflow for genome annotation, involving proteogenomics analysis. Proteins arefractionated, and peptides are generated by digestion and separated by liquid chromatography. Peptides are then analyzed byhigh-accuracy MS and MS/MS and identified by matching them to a DNA genomic contig database translated into 6 framesprior to mapping the peptides back onto the genome. Genomic contigs can be directly downloaded and used by search enginessuch as Mascot. Other search engines such as Sequest require the translation of the genomic contigs into six (6) frames.Mapped peptides are then grouped into proteins. The obtained peptides as well as transcripts and expressed sequence tag(EST) sequences are used to validate in silico designed genemodels and help themanual (re-)annotation/curation. In absence ofa completely sequenced genome, extensive transcript and EST sequences can serve as a database for protein identification inproteogenomics. The whole process can be iterative.



reasons. Even in the best case scenarios large-scale proteo-mics studies are typically limited to very low proteomecoverage, let alone the low sequence coverage of individualproteins identified by a few peptide sequences. In the case ofgreen plant tissue, the problem of high dynamic range ofprotein concentrationwith over-representation of chloroplasticproteins, in particular of ribulose 1,5-bisphosphate carboxylase/oxygenase (RuBisCO) is another challenge to overcome. For anin-depth proteogenomics study, proteomes from differenttissues, ages and physiological states are required. In addition,several alternative protein and peptide fractionation techniquesare often employed as they substantially increase the number ofproteins identified [44], including gel-based and gel-free sepa-ration methods. As the goal is to validate predicted ORFs and todiscover new ones, peptides are identified against genomicdatabases rather than against protein sequence databases[47–49]. Inclusion of the six frames and the non-coding DNAsequences increases the search spacedramatically. Fortunately,modernmass analyzers provide high speed, greater sequencingdepth, and high mass accuracy, which can alleviate some ofthese effects by providing high-confidence data.

In addition to genomic databases, the use of databases ofpredicted ORFs can be helpful — obviously only to associatepeptide groups to proteins of the well-predicted ORFs. Proteinidentification using a proteogenomics workflow is also feasiblewith poorly annotated genomes and non-assembled genomes.Thus, it is perfectly suitable to use an imperfect or partialgenomic database for the identification of proteins by MS[22,45,47,50]. As a consequence, the proteogenomics approachis particularly powerful to annotate short or species-specificuncharacterized ORFs. This is quite important for most plantproteomics investigations – not only for annotation-drivenproteogenomics studies – as plant protein sequences indatabases such as UniProtKB are well underrepresented incomparison to sequences from other kingdoms. For instance,there are only 31,498 entries for “viridiplantae” out of total of531,473 entries, representing less than 10% of the total proteinentries in UniProtKB (http://www.uniprot.org/program/plants/statistics — accessed in July 2011). Less than half (10,617) of thepredictedArabidopsisORFs and just only over 2000 predicted riceproteins are represented in the UniProtKB database.

Tools suitable for non-experts in bioinformatics such asthe OryaPG-DB have recently become available for mappingpeptides onto the genome and grouping them into proteins[44,51,52]. Castellana and coworkers [50] have even developeda bioinformatics tool (GenoMS) that allows de novo proteinsequencing of whole proteins such as human antibodies withhypervariable sequence regions, using incomplete or poorlysequenced genomes.

4.4. The future of plant genomes and their annotation

A. thaliana was the first plant model that was sequenced,selected for its small size, fast seed-to-seed generation, itssmall genome and the possibility to easily transform itgenetically. These features made it an ideal model systemfor molecular laboratory studies. Unfortunately, Arabidopsis isphylogenetically only distantly related to most of the culti-vated crop species, thus compromising its use for identifyingproteins from cultivated crop species by sequence homology

searching. Although the rice genome has been available since2002 as the first monocot genome sequenced, rice is still quitedistant from the other major cereal crops such as barley andwheat. Despite the increase in sequencing power with theconstant arrival of new DNA sequencing technologies, barleyand wheat genomes are large and are at the moment onlypartially available in public databases. However, Brachypodiumis now becoming the laboratory model of choice for temperatecereal crops. Like Arabidopsis, this grass has a small genomesize and a 4-month seed-to-seed life cycle. Nevertheless, thenumber of studies using Brachypodium as reference organismis still very modest in comparison to Arabidopsis. Moreover,although the use of plant models has been proven to bepowerful for advancing fundamental molecular plant research,plants are notorious for their biodiversity, i.e. for their complexand diversified secondary metabolism, of which a substantialamount is species-specific. Likewise, comparative plant geno-mic studies have shown that a large proportion of predictedgenes are species-specific, thus justifying the intensive effortand resources employed to complete the genome sequencingand annotation of commercially valuable crops. Nevertheless,since proteins are mostly conserved between related species,studying non-model plants by proteomic means, even if thoseare lacking genome or sufficient EST sequence information forprotein identification [13,53], is to some extent still possible asshown for banana [15,18,54]. Analytical software supportingerror tolerance sequence database searches for the analysis oftandem mass spectra of peptides allows the identification ofpeptides diverging slightly in sequence, thus enabling theidentification of peptides with one amino acid variation toclosely related peptides from proteins of different species.

However, for many plant species which are phylogeneti-cally distant from sequenced plant models or crops, the aboveapproach is less than ideal and genomes are rarely or onlypartially sequenced. In these non-model plants, generatingdatabase templates for proteomics studies by massive se-quencing of ESTs using the high-throughput but imperfectpyrosequencing techniques can be a practical solution [13,17].

5. Biodiversity screening

Why biodiversity? Biodiversity is essential in preserving thecapacity of organisms to survive by adapting to changingenvironments. Moreover, biodiversity is not a simple term asit works at different levels, the ecosystem, the species in theecosystem, and the genetic diversity reflected in a speciesgenome, proteome, and metabolome. The Convention onBiological Diversity (CBD) defines biodiversity as “the variabilityamong living organisms from all sources, inter alia, terrestrial,marine, and other aquatic ecosystems and the ecologicalcomplexes of which they are part; this includes diversity withinspecies, between species, and of ecosystems” [55]. Moreover,biodiversity constitutes an excellent resource for seeking genes,proteins and metabolites of interest. The growing informationof plant genomes enables proteomics to provide a new way tostudybiodiversity and tounderstandour ecosystem.Other thangene-based analysis, biodiversity screening can be applied atthe proteomics level to screen out novel proteins and peptidesfrom plants and crops with a targeted aim to understand their



phenotype and ecological and/or economic importance in thechanging environment. Mostly, the medicinal value of plants(drugs based on naturally occurring proteins) is used as arationale to preserve biodiversity. The approach can also beapplied to genetically modified (GM) crops and how they areaffecting the geneticmake-up of farmland biodiversity. Thus, inorder to identify, preserve, and utilize the beneficial products ofplant species, systematic proteomics approaches developed formodel plants will have to be employed, alone or in combinationwith other omics approaches.

However, it must be remembered that proteomics is notthat new (as we would like to imagine) in analyzing plant/cropbiodiversity. For instance, even before the word “proteomics”was coined it had been used for differentiating cold-tolerantand cold-sensitive cultivars. Virginia Walbot and MatthiasHahn published in 1989 a paper showing the effects of cold-treatment on protein synthesis andmRNA levels in rice leaves[56]. The authors in that study used one-dimensional gelelectrophoresis (1-DGE) and RuBisCO large and small subunits(LSU and SSU, respectively) to differentiate the cold-sensitiveIndica rice varieties Wag-wag and Peta from the cold-tolerantrice Japonica varieties Calmochi-101 and Ta-Mao-Tao. Morerecently, peanuts from the US mini-core collection wereanalyzed for changes in leaf protein profiles during reproduc-tive stage growth under water-deficit stress [57]. With theobjectives to unravel molecular mechanisms conferringwater-deficit stress tolerance in peanuts and identify stress-tolerant genotypes, the authors used a variety ofmorphological,physiological, and proteomics techniques. The results of 1-DGEand two-dimensional gel electrophoresis (2-DGE) analysisallowed for the association of physiologically significantcandidate proteins with water-deficit stress tolerance mecha-nisms [57]. There are many more examples spanning the timesinceWalbot andHahnshowed the importanceof the abundantprotein RuBisCO in discriminating cold-tolerant genotypes ofrice, to the present day when proteomics is routinely utilized tostudy cultivar differences in plants from model to non-modelsin normal and abnormal growth conditions.

Natural variation of plants is as old as the history of plantbiology itself, and like any other technique proteomics toolsare bound to be utilized for investigating traits that areessential to breed better plants or crops. Again, a goodexample comes from Arabidopsis, where 2-DGE in combinationwith peptide mass fingerprinting was employed to investigatethe natural variation in the proteome among eight A. thalianaecotypes [58]. The results led Chevalier and co-authors tosuggest that proteomics comparison can help differentiateamong the physiological status of ecotypes, and importantlythat proteomics can be a powerful technique to mine thebiodiversity between ecotypes of a single plant species [58].

6. Tolerance to biotic and abiotic factors forcrop improvement

Plant performance can be severely affected by both biotic andabiotic stress conditions in the environment and this is aparticular concern in agriculturewhere stress-related alterationsin plant development, growth and productivity can translateinto huge economic losses. Understanding and more

importantly mitigating the effects of stress on plants areessential if agriculture is to keep pace with the ever increasingdemand for food [59]. Stress can be classified into two broadcategories: (i) biotic stress which encompasses damage done toplants by other living organisms such as bacteria, viruses, fungi,parasites, insects and even animals and other plants; and(ii) abiotic stress, covering extremes in temperature, light, watersupply and solute levels [60]. Literally being rooted to one place,plantsmust rely on physiological andmetabolicmechanisms toobtain the phenotypic plasticity required to withstand theadverse biotic and abiotic growth conditions with which theyare faced on a daily basis.

Proteomics, and in particular quantitative proteomics, isemerging as a powerful field of stress tolerance research,allowing the rapid identification and quantification of stress-and tolerance-related proteins. There are excellent reviewsthat summarize biotic and abiotic stress proteomics and thereaders are referred to those reviews [61–64]. Understandingthe dynamics of expression and PTMs of these proteins, andgaining direct insight into their function can provide essentialinformation that can be rapidly applied to engineer stress-tolerant crops with novel traits through biomarker selectionand transgenic strategies.

In order to rapidly disseminate information from differentstudies, species, and stresses, and drive technological appli-cations related to these findings, it is necessary to collate theinformation into collective searchable database platforms toensure that the findings are available to a wide audience. Themajority of plant proteomics resources are focused on themodel non-crop plantA. thaliana andmuch of these have beenrecently amassed into a single portal, Multinational Arabi-dopsis Steering Committee for Proteomics (MASCP; http://www.masc-proteomics.org; [65]). Only a limited amount ofstress proteomics data and/or experiments are contained inMASCP, including links to small datasets from wound-induced proteins from Arabidopsis leaves [66]. A reliable andcomprehensive database for other Arabidopsis stress proteo-mics is lacking. However, there has been tremendous progressin establishing rice proteomes and related databases inresponse to biotic and abiotic stresses [reviewed in 7,8]. Thefirst tropical crop to have its own stress proteomics databaseis banana (http://www.pdata.ua.ac.be/musa/). The databasecontains 2D-PAGE gels of protein samples collected fromosmotically stressed banana meristematic tissue and proteinidentification data for 138 identified proteins that were up ordownregulated under osmotic stress [14].

Despite the immense potential of proteomics to advancestress-tolerance crop breeding strategies, it is still an area inthe discoverymode. This is primarily due to the relatively newdevelopment of the field of plant stress proteomics and itsrecent application to crop plants, notwithstanding the smallnumber of fully sequenced crop plant genomes. While thereare many current informative reviews addressing what needsto be done [67–71], there are as yet no reported success storieswhereby the knowledge gained directly from proteomicsstudies has been applied to improve crop stress tolerance.Plant responses to stress are complex and invariably involvechanges in multiple molecular pathways. Validating theseassociations between proteins and pathways can be hugelychallenging. This is not to imply that it will not be possible in



the near future; validation of potential protein candidates cantake several years and requires independent approaches, suchas microarrays, extensive literature searches, and system-level analysis to identify candidate proteins. Furthermore notall proteins that are identified will be suitable for application.Not in any way challenging the large amount of excellentresearch done in human/animal sciences, we can drawparallels to medical proteomics and look at the success ofdisease biomarker discovery in that field which is much larger,better funded, andwith a considerably longer history thanplantproteomics. One can see that thousands of putative diseasebiomarkers have been identified through both genomics andproteomics approaches, yet only about 1% of those have beensuccessfully selected for clinical use [72]. It will requirecollaborative research efforts, combined with standardizedapproaches, and robust data analysis, but the next decadeshould see the implementation of knowledge gained fromplantproteomics studies to crop improvement in the field.

7. Food analysis, safety, and nutrition(human health)

Proteins in foods are not only important fromanutritional pointof view but from a technological point of view since they areresponsible for major changes (e.g., viscosity consistency,flavors, etc.) in food products and closely related to food quality,safety and nutrition. Staple food crops such as maize, wheatand rice deserve special attention since they represent 60% ofthe world's food energy intake. With advances in coverage ofthe deep proteome [73], there is the possibility to unravel theunknown protein composition of these major crops that mightbe translated to improvements in quality, storage, and foodprocessing conditions. The food industry so far has takenadvantage to some extent of the proteomics-driven researchmainly in the areas of quality and authentication, safety andnutritional assessment, and to a minor degree in processoptimization and monitoring [74]. This section will focus ontranslational proteomics of plant-based foods (Fig. 3).

7.1. Food composition and quality

The knowledge often gained for various crops in terms ofprotein composition using proteomics has been translated topotential improvements in industrial applications. Foodindustry has a basic rule: good quality in, good quality out.Thus, to obtain a high-quality food product, the quality of theraw material must be high. Knowledge obtained fromproteomics can be translated into direct problem solving forthe postharvest industry of horticultural crops. Physiologicaldisorders that result in huge economic losses can be detectedat a very early stage in production [75–78]. A proteomics-basedapproach has been employed to find biomarkers associatedwith optimal harvest maturity [79], thus assuring postharvestquality. Analysis of the postharvest withering process ingrapes is a key for obtaining high quality wines. An efforthas been undertaken through gel-based proteomics analysisof this process in order to support quality improvement [80].The wine industry has gained meaningful information fromproteomics research and readily translated this into improve-ments of the process. Besides understanding of the ripeningprocess of grape that has a direct impact on wine quality [80],wine spoilage and thus quality can be tracked by gel-basedproteomicsmeans [81]. Champagnewine's quality is associatedwith the foaming properties and loss of foaming properties isassociated to the loss of proteins [82].

Understanding the ripening processes and postharvestphysiology during storage (low temperature, modified atmo-sphere) has not only a direct impact on food quality but on theoptimization of the technological processes involved, given thata series of abiotic stresses is applied (low/high temperature,modified atmosphere). For such scenarios, plenty of proteomicsapplications have been carried out [76,83–85]. For example, arecent proteomics study on the application of heat treatment onpeach fruit indicated that all the proteins identified as beingdifferentially expressedwere involved in the regulation of peachfruit development and ripening, implying that this treatmentcould be used to improve fruit quality and shelf-life [85].

The cereal industry has also benefited from proteomicsresearch. For instance, based on 2-DGE fingerprinting,

• Health biomarkers

• Plant based bioactives

• Impact of food processing on nutritional aspects

• Composition & Analysis

• Authenticity

• Quality raw materials

• Tracking

• Allergens, toxins & Foodborne pathogen detection

• Controversial foods

• Impact of new technologies

• Sanitation assessment

Food Proteomics

Process Optimization &

monitoring

Quality & Traceability

Safety Assessment

Nutritional Assessment

• Early detection of problems

• Correct & Take action

• Understanding processing effects

Fig. 3 – Food proteomics. Opportunities of translational proteomics driven research in different areas in food science andtechnology: (1) process optimization and monitoring, (2) quality and traceability, (3) safety assessment and (4) nutritionalassessment. The different mentioned areas are inter-connected.



selection of appropriate durum wheat cultivar for pastamaking was feasible [86]. Flour quality is highly correlatedwith protein composition and functionality, thus proteomicshas been a useful platform to identify protein markers toselect suitable cultivars for flour [87]. Barley cultivar and thelevel of protein modification during malting are associated tobeer quality. The construction of a beer proteome map is auseful tool for detection and potential manipulation of beerproteins related to quality [88]. Unraveling the low-abundantproteome including that of beer has now become feasible [89].

7.2. Food safety

Food allergens are a constant threat to allergic consumers.According to EU legislation, most of the food allergens in foodproductsmust be declared if they are part of the ingredient listor if their presence might be expected due to processingcontamination (e.g., cereals containing gluten such as wheat,rye, barley, oats, etc.; peanuts, soybeans, different nuts such asalmonds, hazelnuts, etc.; celery, mustard, lupin and sesameseeds) [90]. The translation of proteomics research in the fieldof food allergens is quite extensive because development ofsensitive detection/quantification methods is crucial forallergen diagnosis, therapy, and risk assessment and forreinforcing current legislation on the subject. Commonly, acombination of 2-DGE with immunoblotting of IgE reactiveproteins using allergic patients' sera has been the approachtaken to characterize the allergenicity of certain food proteins[91,92]. Shotgun proteomics approaches have been performedfor characterization and detection of several food allergens[93,94]. The generated information is key for targeted ap-proaches such as selective reaction monitoring (SRM) whereallergens are not only detected at trace levels but alsoquantified [95,96]. A multiallergen detection method for thesimultaneous detection of seven allergenic foods (five of plantorigin) in bread based on the targeted SRM approach has beenrecently reported [95]. For confirmation, especially whenliability issues are raised, SRM is recommended as the foodallergen detection/quantification method of choice [97].

Food-borne pathogens constitute a constant hazard. Con-sumer trends toward healthier and more natural foods aredriving common food preservation techniques (e.g., steriliza-tion, freezing) into milder preservation techniques, imposingnew challenges for the food industry in terms of food safety.Matrix-assisted laser desorption/ionization-time-of-flight(MALDI-TOF) MS and electrospray ionization-tandem massspectrometry (ESI-MS/MS) are two powerful proteomics plat-forms currently used for routine identification of differentmicroorganism species and in many cases strains [98–100].Compared to traditional microbiology tests that are tediousand time consuming, MS proteomics and bioinformatics toolsare used for the characterization and detection of pathogenicmicroorganisms and toxins [98]. Additional tandem MSinformation of the tryptic peptides allows sequence identifi-cation. In addition, MS instrumentation can be automatedand there is the possibility of multiplexing for rapid screening[98]. Understanding the mechanisms of action as well as themechanisms of stress resistance of food-borne bacteria iscrucial for the development and design of effective foodpreservation techniques [101,102].

The use of GM foods in Europe is still highly controversial.To assess the same food composition of GMO (geneticallymodified organism) foods with its counterpart, the principleof ‘substantial equivalence’ is applied [92]. However, theapplied targeted approach, in which key nutrients are tested,is not enough to account for unintended effects. Therefore,other omics platforms are being used. Measuring changes atthe transcriptome level is not necessarily translated intochanges at the food composition level. Thus, metabolomicshas been the platformof choicebut it has shown limits for safetyassessment [103]. Instead, the proteome can deliver furtherinformation in terms of safety assessment since many proteinscan behave hazardously (e.g., toxins, allergens, antinutrients,etc.). However, proteomics and the other omics have failed so farin delivering translated science despite all the investments inresearchwork [103]. The large numbers of proteomics studies inthis area are quite controversial mainly because of the lack ofreproducibility, the mixed environmental effects not properlydealt with and the far from total coverage of the proteome.

7.3. Food authenticity

Food adulteration (e.g., replacement of certain ingredients bycheaper ones) is not an uncommon practice. Thus, theavailability of specific and sensitive protein markers of thesubstitutes would allow food authentication [92] and help toreduce frauds. In this research field, many proteomics studiescan be directly translated into practical use; for example,identification of the presence of cheaper substitutes for certaincoffee varieties through specific protein markers [104]. Thebeverage industry, nowadays, claims the introduction of plantand fruit extracts in the formulation of certain food products.Thus, in this case, the identification of protein markers specificto the fruit or plant extract that is claimed being used in theformulation is a way to assess the genuineness of the products.These are good examples of translational proteomics for foodauthenticity [105,106].

Methods to assess the geographical origin of products arekey to prevent illegal adulteration. Assessment of geographicalorigin is one of the main requirements for the certification ofwine authenticity, grape variety, wine age and technology forproduction and proteomics can provide the biomarkers for suchpurposes [107]. Assessment of the floral origin of honey hasbeen performed using protein markers [108]. Assessment ofproduction origin in the case of conventional versus organicallygrown products through different platforms including proteo-mics has failed so far to deliver strong results.

7.4. Nutrition

This section will focus on health biomarkers and plant-basedbioactives. Proteins are not only one of the threemacronutrients,but they are protagonists of many cellular processes, partici-pating in cell signaling and immune responses, acting asbioactive components exerting functions such as growthfactors, anti-hypertensive agents, antimicrobials, modifiers offood intake or immune regulators [109]. Modern nutrition aimsto promote health by preventing or delaying the onset ofdiseases, by optimizing performance and by assessing risks[110]. This is evaluated by studying the interaction of the food



proteome, host and microbial proteomes. Thus, proteomicstranslates scientific knowledge into discovery and quantifica-tion of biomarkers to assess predisposition, exposure, efficacyand characterization and quantification of food bioactives [110].Proteomics also tries to understand how our genome isexpressed in response to the diet and translates it into deliver-ables such as bioactives and biomarkers, information onnutritional bioavailability and bioefficacy [110,111].

Bioactive peptides are released during either digestion byhost enzymes and microbial enzymes, food processing orripening [110]. Bioactive peptides from plant sources such aswheat, maize, soy, rice, mushrooms, pumpkin, and sorghumhave been reported [112]. Particularly bioactive peptides fromsoy have sparked attention. Lunasin, Bowman–Birk inhibitor,lectin and beta-conglycinin are some of the bioactive proteinsand peptides in soy besides the phytochemicals. The antioxi-dant properties of the proteolytically released peptides fromsoyhave been investigated [113] and this might be translated in thenear future into applications to treat oxidative-stress relateddisorders [110]. Lupin is another crop containing high amountsof storage proteins (alpha and beta-conglutins) and theseproteins seem to exert bioactive effects [114]. Certainly,current approaches based on either in vitro or in silico wouldallow the discovery and identification of bioactive peptidesfrom many more food sources.

7.5. The perspective of food science and technology

Food science and technology is one of the fields that havebenefited the most from the advances in current proteomicstechniques. It is also one of the fields that have incorporated asubstantial amount of knowledge gained through proteomicsplatforms and translated it into solutions for real scenarioproblems in food quality, safety, and nutrition, and ultimatelyhuman health. However, there is still the need to translateknowledge generated through proteomics in food processoptimization and monitoring. Proteomics could be usedthroughout the food processing steps to track the history ofallergens, adjust processing steps and even predict shelf life.In the area of nutrition, given the still limited number ofsequenced plant based genomes, there is the possibility tostudy little-known crops with potentially high amounts ofunique bioactives. Microbial proteomics knowledge can beincorporated and implemented for food and plant/facilitysanitation and safety assessment.

8. Energy sustainability

Undoubtedly, the role of biofuels will pose a concern when foodsecurity is considered. Biofuels are liquid gaseous fuels primarilyderived from plant biomass. Different factors ranging from thechanging climate, rising fuel prices, and to a general awarenessamong the public for using renewable energy sources hadgenerated interest in plants/crops as sources for biofuels (ethanoland diesel) [for review see 115–117]. Among crops, maize,sugarcane, and rapeseed are major sources of “green energy”.However, the use of these food crops for biofuel is controversial‘vis-a-vis’ food security. Yet, continuous efforts are made tosearch for suitable alternative crop sources for biofuels. One

example is the African grain plant sorghum, already being usedas food and feed, which is gaining attention as a promisingenergy crop [118,119]. Other than the fact that it is able to growin a wide range of geographical areas requiring much less offertilizer and water compared to other cereal crops, the sweet-stem varieties of sorghum yield readily soluble fermentablesugars in the stalk juice [120]. Therefore, the stems can be usedfor biofuel production. Proteomics studies in this direction havebeen initiated by Bongani Kaiser Ndimba and colleagues at theUniversity of Western Cape (South Africa), where an in vitrosystem of suspension cultured cells has been established tocomprehensively map and characterize the sorghum suspen-sion cultured cell secretome [121,122]. Another developingexample is a non-domesticated shrub of an oilseed crop,namely Jatropha curcas L. Jatropha is recently gaining attentionfor its oil that can be converted into biodiesel, and like sorghum,it can be easily cultivated in arid and semi-arid regions,including wastelands [123, and references therein]. Currently,proteomics analysis in Jatropha is mainly confined to oil bodycharacterization for understanding oil biogenesis [124–126].Identified proteins could be exploited for their suitability asmarkers in phylogenetic and molecular breeding studies [123,and references therein]. These and upcoming proteomicsstudies will be very helpful for utilization of crop plants as asource of sustainable production of biofuels.

9. Global action plan on plant proteomics(GA3P) in facilitating the transfer of knowledgeand discoveries

Historically, global organizations have demonstrated a role intransferring the research knowledge directly to the fieldapplications. One of the famous examples can be found in thevision of Consultative Group on International AgriculturalResearch (CGIAR) that established a unique worldwide networkof agricultural research centers coordinating and collaboratingactivities toward the improvement of global agriculture. Thefirst two institutes established by CGIAR were the InternationalMaize and Wheat Improvement Center (CIMMYT; http://www.cimmyt.org/) and the International Rice Research Institute (IRRI;http://www.irri.org/). CIMMYT helped to bring about the firstGreen Revolution innovations of the late 20th century thatreduced the fraction of the world's hunger from half to less thana sixth. IRRI presents a good example for transferring thediscoveries obtained via screening of the natural population ofrice and creating new cultivars tolerant to a wide range of bioticand abiotic stresses, increased yield, and seed quality. Generatedresources are further helping the scientific community to enrichthe knowledge on plant biology.

Organizations related to plant proteomics are also in theprocess of facilitating the transfer of the acquired knowledgeand discoveries to the scientific community and into fieldapplications. To bring these data to a single platform is a goalwe all share. The first of such initiationwas the establishmentof MASCP in the year 2000 [34]. Its most notable achievementwas the recent establishment of a GATOR portal, where theArabidopsis researcher is able to search for any AGI code orlists of AGI codes in all proteomics databases assembled byMASCP [65]. One aim behind the MASCP Gator was to translate



the Arabidopsis knowledge also to other plants. It is worthnoting that the Plant Proteomics in Europe (EuPP) group underthe European Proteomics Association (EuPA), has also been apopular and successful initiative. The EuPP is involved inbuilding up expertise in plant proteomics through an inte-grated network of European scientists to i) share and developtools for fundamental and applied research in plants, and ii)utilize the generated information for monitoring the environ-ment and food quality (http://www.cost.eu/domains_actions/fa/Actions/FA0603).

The next major effort appearing on the horizon was theestablishment of a global initiative on plant proteomicstermed the International Plant Proteomics Organization(INPPO; http://www.inppo.com), to “properly organize, preserve,and disseminate collected information on plant proteomics”[12]. To quote Wolfram Weckwerth, chairman of the MASCP,“INPPO is an excellent example of a non-profit, open-sourceinitiative. Interestingly, it is merely based on the initiative ofscientists without any funding, comparable to the early stagesof MASC and the corresponding subcommittees or othercommunities” [34]. At INPPO, the research subcommittee isconsidering the development of a comprehensive and user-friendly database for cereal and legume crops, which will be amajor milestone in the field of translational proteomics, oncecompleted (http://www.inppo.com/researchcom.jsp).

Considering how much education and training can con-tribute to the future of (translated) proteomics, the educationcommittees of the Human Proteome Organization (HUPO) andthe European Proteomics Association (EuPA) together withtheir national counterparts have recently initiated an Interna-tional Proteomics Tutorial Programme (IPTP) [for details see,127]. This ambitious program involves the leading proteomicsjournal, Journal of Proteome Research, Journal of Proteomics,Molecular andCellular Proteomics, and Proteomics, and aims toinstruct Masters/PhD level students beginning their careersin core techniques and the basics of proteomics researchusing articles and slides (http://www.proteomicstutorials.org/Proteomics_Tutorials/Welcome.html). The INPPO isclosely following the IPTP and looking forward to mutuallyenriching the plant proteomics based tutorials currently underdiscussion with the INPPO subcommittee of Education Outreach(http://www.inppo.com/eduoutreach.jsp).

10. Concluding remarks

Over the past decade, the information transfer betweenmodeland non-model proteomes, proteogenomics for the annotationof genomes, biodiversity screening, crop improvement againstbiotic and abiotic stresses, and food science and technology areamong the research areas that have highly benefited from therapid developments in plant proteomics. Current knowledge ofgene structure, organization, and evolution of a plant genome isthe result of advances in proteogenomics. Food science andtechnology has incorporated a substantial amount of knowl-edge, gained through proteomics platforms for routine analysisand other applications related to food quality, safety, andnutrition. The enrichment of basic knowledge, one dimensionof translational plant proteomics, has certainly taken place. Incontrast, very little or no progress has been made in the other

dimension of translational plant proteomics, which is the fieldapplications of the discoveries. Although hundreds of identifiedproteins have been reported as potential biomarkers formonitoring disease in plants and seed/food safety and quality,those candidate biomarkers still need to be rigorously validated.Moreover, the biological function of the majority of thesebiomarkers remains to be experimentally dissected. Neverthe-less, given the tremendous achievements at least in basicscience of plant biology, it could be stated that translationalplant proteomics has an imminent prominent future.

Plant proteomics platforms have generated a huge amountof protein data. Techniques have been optimized from samplepreparation to the identification of proteins and their bioin-formatics analysis. Equipment and bioinformatics tools havebeen updated and encompassed with new breakthroughs intechnology. Mass spectrometry instruments are sensitiveenough to identify rare proteins with high accuracy and tomeet the criteria being imposed for safe food by regulatoryagencies. However, it should be noted that mass spectrome-ters are high-end instruments and require highly experiencedtechnicians or researchers as well as substantial maintenance.Thus, it is highly unlikely for such expensive equipment to befound in many institutions in the decade to come. Proteomicscore facilities seem to be the more likely alternative.

To conclude, translational plant proteomics has alreadyexisted for a long time although not explicitly by name. Thetechnology and resources are certainly promising to furtheradvance translational plant proteomics. It only remains to beseen as to what extent and when solutions to the bigchallenges in today's world can be found. Are we going to beable to meet the needs of a growing world population in termsof food security and sustainability?

Acknowledgments

Authors acknowledge the INPPO platform for this initiative inbringing together scientists of different disciplines in con-structing this review and translating their knowledge andexperience to the global community including scientific. BJBacknowledges DGAPA, UNAM (Grant #212410) for funding theproteomics research in the laboratory. LVB and RC acknowl-edge the support by the BBSRC (grant BB/H001948/1). RRacknowledges the great support of Professors Yoshihiro Shiraiwa(Provost, Graduate School of Life and Environmental Sciences,University of Tsukuba) and Seiji Shioda and Dr. Tetsuo Ogawa(Department of Anatomy I, Showa University School of Medi-cine) in promoting interdisciplinary research and unselfishencouragement.

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Translational plant proteomics: A perspective

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