Clinical Proteomics: Methods and Protocols

273 Pages·2021·8.309 MB·English

by  Fernando J. Corrales, Alberto Paradela, Miguel Marcilla

Methods in
Molecular Biology 2420
Fernando J. Corrales · Alberto Paradela
Miguel Marcilla Editors
Clinical
Proteomics
Methods and Protocols
M M B
ETHODS IN OLECULAR IO LO GY
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Clinical Proteomics
Methods and Protocols
Edited by
Fernando J. Corrales
Proteomics Unit, Centro Nacional de Biotecnología
(CNB-CSIC), Madrid, Spain
Alberto Paradela
Proteomics Unit, Centro Nacional de Biotecnologia
(CNB-CSIC), Madrid, Spain
Miguel Marcilla
Proteomics Unit, Centro Nacional de Biotecnología
(CNB-CSIC), Madrid, Spain
Editors
FernandoJ.Corrales AlbertoParadela
ProteomicsUnit ProteomicsUnit
CentroNacionaldeBiotecnolog´ıa CentroNacionaldeBiotecnologia
(CNB-CSIC) (CNB-CSIC)
Madrid,Spain Madrid,Spain
MiguelMarcilla
ProteomicsUnit
CentroNacionaldeBiotecnolog´ıa
(CNB-CSIC)
Madrid,Spain
ISSN1064-3745 ISSN1940-6029 (electronic)
MethodsinMolecularBiology
ISBN978-1-0716-1935-3 ISBN978-1-0716-1936-0 (eBook)
https://doi.org/10.1007/978-1-0716-1936-0
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Preface
Proteomics addresses the study of the proteome or the protein component of biological
systems.Itsexponentialtechnologicaldevelopmentinthelast15yearsmakesproteomicsa
mature discipline that provides accurate measurements of proteins either in massive or
targetedformats.Amongother-omicapproaches,proteomicsoffersunprecedentedoppor-
tunities to describe individuals’ phenotypes as proteins translate the genetic information,
respondtoenvironmentalperturbationsaswellastreatments,and,ingeneral,mediatemost
cellular processes. Therefore, there is an increasing interest in clinical proteomics, an
emerging discipline aimed at deciphering the molecular mechanisms underlying the pro-
gression of diseases and at the identification of new biomarkers and therapeutic targets to
expand the physicians’ toolbox for precision medicine-based patient care. In the following
chapters, state-of-the-art clinical proteomics protocols are described in detail for their
straightforwardimplementation.
Sampleprocessingisakeysteptoensureoptimalperformanceofaproteomicexperiment,
especially when clinical specimens must be analyzed. Ciordia et al. describe a method that
increasesthebileproteomecoverageandreducestheamountofsamplerequiredbyafactorof
sixcomparedtopreviousprotocols.Theinterestinmicrovesicleproteomicshasgrowninthelast
fewyearsasitoffersattractiveopportunitiesforclinicalinterventionsinanoninvasivemanner.
Hereamethodfortheisolationandcharacterizationofhighlypuremicrovesiclesandexosomes
secreted by helminths is described and provides the basis for the discovery of new vaccine
candidates against these devastating infections. Biofluid analysis represents a challenge for
proteomicsduetothepresenceofveryhighabundanceproteinsthathamper thedetectionof
mediumandlowabundanceproteins.Amethodispresentedthatallowsdetectionofmorethan
3000cerebrospinalfluidproteinsandoffersapowerfultoolforprofilingavarietyofcomplex
biofluid samples and clinical specimens. In a similar way, enhanced quantitative LC-MS/MS
proteomeanalysisfromdriedbloodspotsisdescribedusingsodiumcarbonateprecipitationand
adata-independentacquisitionmode.Thestudyofhumangutmicrobiotausingametaproteo-
mics strategyhascaptured the attention of the life sciencescommunity as increasing evidence
shows its association with human health and disease. An optimized protocol to prepare feces
samplesforaproteomicsanalysisisdescribed.Theincreasingsensitivityandaccuracyofstate-of-
the-artmassspectrometersmakepossiblesingle-cellproteomicsanalysis.However,optimized
sample processing workflows are needed to ensure good recoveries throughout the whole
process.Atypicalexampleofmassspectrometry-basedsingle-cellproteomicsworkflowallowing
quantification of >1000 proteins is described. Details about the critical steps of analysis and
alternativemethodsusefulforoptimizationpurposesarediscussed.
Understanding the dynamics of protein post-translational modification patterns and
howthisassociateswithpathogenicprocessesisapriorityinclinicalproteomics.Amethodis
described to identify lysine acetylation sites and estimate their site occupancy at the prote-
ome scale. The procedure has been applied to cell line cultures and to clinically relevant
samples stored as both snap-frozen and formalin-fixed paraffin-embedded tissues. A label-
free mass spectrometry protocol for proteomic and phosphoproteomic analysis compatible
withroutineanalysisofclinicalsamplesisprovided.Theauthorsalsooutlinebioinformatic
v
vi Preface
pipelinesbasedonstatisticallearningthatusetheseproteomicsdatasetsasinputtoquantify
kinase activities and predict drug responses in cancer cells. Finally, in this section, an
optimized method to enhance the number of proteome-wide citrullinated residues confi-
dentlyidentifiedisprovided.
The analysis of the peptide repertoire displayed by HLA molecules has been widely
appliedtoresearchonautoimmunedisordersandviralimmunology.Morerecently,theuse
of immunopeptidomics has been adopted by the cancer research community aiming to
detect neoantigens that might promote the development of personalized vaccination pro-
cedures.HerewedescribeaprotocoltoprocesshumanthymussamplestopurifyHLAclass
I-orHLA-DR-associatedpeptidomes.Thedevelopmentoftoolsthatenablethedeconvo-
lution of immunopeptidomes in the context of disease can help to improve the specificity
andeffectivenessoftherapeuticstrategiestargetingthesepeptides.Inthisregard,acompu-
tational workflow that facilitates the processing and interpretation of Data-Independent
Acquisition Mass Spectrometry of HLA peptides is presented. In addition to conventional
non-modified peptides, immunopeptidomes also contain phosphorylated species, which
maybeofgreatinterestforpersonalizedcancerimmunotherapy.Here,weprovideadetailed
protocoltoidentifyphosphopeptidesdisplayedbyhumanHLAclassImolecules.
Targeted proteomics has a tremendous potential to quantify specific proteins in the
biomedical and clinical domains. Biomarker validation initiatives and patient stratification
programs based on protein panels for which there are no reliable antibodies available might
greatly benefit from this technology. A protocol is described to quantify 13 enzymes of the
one-carbonmetabolism (1CM)in liver tissue specimens. Since1CM impairment in hepato-
cytes is a recognized factor associated with chronic liver disorders and hepatocellular carci-
noma,thismethodprovidesausefultooltofollowuptheprogressionofthediseaseandassess
itsseverityinpatients.Otherclinicallyrelevantmethodologyinclinicalproteomicsismatrix-
assistedlaserdesorption/ionization(MALDI)imagingmassspectrometry(IMS)thatallows
for the analysis of the spatial distribution of peptides, small proteins, and other molecules
withinbiologicaltissues,enablingtheso-called“molecularhistology.”Achapterfocusingon
theapplicationofthistechnologytotheanalysisofcryopreservedsamplesisincluded.Tissue
imaging is typically associated with antibody-based methods such as immunohistochemistry
thatallowfor theexplorationofproteinexpressionatsingle-cellresolutionwithintheintact
tissue environment. The entire workflow utilized within the Human Protein Atlas, from
sample preparation to annotation of the IHC staining patterns, is described in detail, with
important notes onvarious factors that can affect the outcome of IHC. MALDI-TOF mass
spectrometryhasbeenappliedwithhugesuccesstotheidentificationofculturedmicroorgan-
ismsinClinical Microbiologylaboratories, whereithasbecomethegoldstandardduetoits
simplicity, speed, and high reproducibility. Different procedures used in the routine for
®
pathogenidentificationusingtheBrukerMALDIBiotyper systemaredescribed.
Lastbutnotleast,twoemergingmethodologiesthatwillprobetheirrelevanceinclinical
proteomicspipelinesarerevised.Protein-proteininteractionnetworksmustbedescribedin
detailtofullyunderstandcellbiologyanddisease.Structuralbiologyhasrecentlywitnessed
the benefits of the combined use of two complementary techniques: electron microscopy
(EM)andcross-linkingmassspectrometry(XL-MS).Theprotocoldescribedhereispartic-
ularlywellsuitedfor thestudyofproteincomplexeswhoseintrinsicallyflexibleor transient
nature prevents their high-resolution characterization by other structural techniques.
Preface vii
Finally, omics integration is needed to discover inter-omics interactions and regulatory
changes, which are not observed when analyzing a single omic profile. The multi-omics
approach, therefore, provides additional insights to help understand and treat complex
diseases. In this book, proteogenomics data integration is discussed, and an overview of
thedifferentomiclayersinvolvedindefiningtheproteomeofalivingorganismisprovided.
Madrid,Spain FernandoJ.Corrales
AlbertoParadela
MiguelMarcilla
Contents
Preface ..................................................................... v
Contributors................................................................. xi
1 BileProcessingProtocolforImprovedProteomicAnalysis................... 1
SergioCiordia,GloriaAlvarez-Sola,Marı´aRulla´n,
Jesu´sM.Urman,Matı´asA.A´vila,andFernandoJ.Corrales
2 MS-BasedExtracellularVesicle(EVs)Analysis:AnApplication
toHelminth-SecretedEVs ............................................... 11
JavierSotillo
3 ProteomicProfilingofCerebrospinalFluidby16-PlexTMT-Based
MassSpectrometry...................................................... 21
KaushikKumarDey,HuanSun,ZhenWang,MingmingNiu,
HongWang,YunJiao,XiaojunSun,YuxinLi,andJunminPeng
4 Data-IndependentAcquisitionMassSpectrometry-BasedDeep
ProteomeAnalysisforHydrophobicProteinsfromDriedBlood
SpotsEnrichedbySodiumCarbonatePrecipitation ......................... 39
DaisukeNakajima,OsamuOhara,andYusukeKawashima
5 SampleProcessingforMetaproteomicAnalysisofHumanGut
Microbiota............................................................. 53
CarmenGarcı´a-Dura´n,RaquelMartı´nez-L(cid:1)opez,
Lucı´aMonteoliva,andConchaGil
6 MassSpectrometry-BasedAnalyticalStrategyforSingle-Cell
Proteomics............................................................. 63
A´kosVe´gva´ri
7 LysineAcetylationStoichiometryAnalysisattheProteomeLevel............. 73
JeovanisGilandSergioEncarnaci(cid:1)on-Guevara
8 ImplementationofClinicalPhosphoproteomicsandProteomics
forPersonalizedMedicine................................................ 87
PedroCasado,MaruanHijazi,HenryGerdes,
andPedroR.Cutillas
9 pH/Acetonitrile-GradientReversed-PhaseFractionationofEnriched
Hyper-CitrullinatedLibraryinCombinationwithLC–MS/MSAnalysis
forConfidentIdentificationofCitrullinatedPeptides........................ 107
AnetaStachowicz,NivedaSundararaman,VidyaVenkatraman,
JenniferVanEyk,andJustynaFert-Bober
10 PurificationofHLAImmunopeptidomesfromHumanThymus.............. 127
In˜akiAlvarez
11 GenerationofHLAAllele-SpecificSpectralLibrariestoIdentify
andQuantifyImmunopeptidomesbySWATH/DIA-MS .................... 137
KevinKovalchik,DavidHamelin,andEtienneCaron
ix
x Contents
12 ImmunopeptidomicAnalysisofthePhosphopeptidomeDisplayed
byHLAClassIMolecules ............................................... 149
MiguelMarcilla
13 DevelopmentofaStandardizedMRMMethodfor theQuantification
ofOneCarbonMetabolismEnzymes ..................................... 159
LauraGuerrero,AlbertoParadela,andFernandoJ.Corrales
14 MolecularHistologyAnalysisofCryopreservedTissue
UsingPeptide/ProteinMALDI-TOFImagingMassSpectrometry
(MALDI-IMS) ......................................................... 177
IbonIloro,IraideEscobe´s,MikelAzkargorta,andFe´lixElortza
15 TheHumanProteinAtlasandAntibody-BasedTissueProfiling
inClinicalProteomics................................................... 191
BorbalaKatonaandCeciliaLindskog
16 MicrobialIdentificationintheClinicalMicrobiologyLaboratory
UsingMALDI-TOF-MS ................................................ 207
Iva´nBloise,M.TeresaCorcuera,JulioGarcı´a-Rodrı´guez,
andJesu´sMingorance
17 CombiningElectronMicroscopy(EM)andCross-LinkingMass
Spectrometry(XL-MS)forStructuralCharacterizationofProtein
Complexes............................................................. 217
Lucı´aQuintana-Gallardo,Moise´sMaestro-L(cid:1)opez,JaimeMartı´n-Benito,
MiguelMarcilla,DanielRutz,JohannesBuchner,Jose´M.Valpuesta,
andJorgeCue´llar
18 AccuratePredictionofProteinSequencesforProteogenomicsData
Integration............................................................. 233
YanickPacoHagemeijer,VictorGuryev,andPeterHorvatovich
Index ...................................................................... 261