Center for Proteomics and Bioinformatics Information Packet

Proteomic Mass Spec:What it can do for youand why you NEED touse itSara E. Tomechko, Ph.D.sew65@case.edu216‐368‐4784Who are we?• $15 million initial commitment from CWRU• Over $80 million in funded grants ($25 M in ID)• 14 primary faculty, 12 secondary faculty• 9,000 sq. feet of laboratory space on the 9 th floor of the Biomedical Research Bldgoccupied, space expansion plan formulated• 8mass spectrometry instruments and GE 2‐D gel system installed by 2010• 2 additional Velos instruments installed by spring‐2012• 4 beamlines at the National Synchrotron Light Source, Brookhaven laboratories operated;• 7 new beamlines recently approved for NSLS‐2• Used by 38 Department and Centers at Case Western Reserve University• 100 institutions worldwide using the facilities• ~200 publications in 2009‐2010, over 1000 publications since 2005• New Ph.D. program approved• Funded research cores from: the CTSC, CCCD and CFARGoal Achieved: World Class Structural and Systems Biology Center…understanding cellular functions anddisease associations of proteins.23

Proteomics research is exploding# Publications (x10 4 )353025201510502000 2002 2004 2006 2008 2010Publication Year# Publications (x10 3 )DNARNA1086420A Pubmed search on 3/1/12…RNA growth at 7.57%DNA growth at 9.32%Proteomics growth at 25.6%Proteomic MS growth at 26.68%2000 2002 2004 2006 2008 2010Publication YearProteomicsProteomics & MS…understanding cellular functions anddisease associations of proteins.3Systems biology is growing rapidly# Publications# Citations…understanding cellular functions anddisease associations of proteins.44

Sole site of S-nitrosylation (C199) in OxyREndogenous protein S-nitrosylation in E. coli: regulation by OxyRDivya Seth 1 , Alfred Hausladen 1 , Ya-Juan Wang 2 , Jonathan S. Stamler 1,31 Institute for Transformative Molecular Medicine & Dept of Medicine, 2 Center for Proteomics & BioinformaticsScience. 2012Goal: Determine site of SNOHSNCSHSNO-OxyRSNO± MMTS± AscorbateCH 3 SSNCSHSSCH 3CH 3 SSS NSX CSSSCH 3SDigestionDTTIAALC-MS/MSSNO is involved in:• Muscle, heart and lung disease• Cancer• Neurodegenerative disorders…understanding cellular functions anddisease associations of proteins.15Types of proteomics studiesClinical Proteomics•BiomarkerDiscovery•DrugDevelopment•Disease State•PTMs•Diseaseprediction &preventionStructural Biology•Proteinconfirmation•Drug targetcharacterization•Protein folding•Protein pathways dynamics•Protein Macromolecular dynamicscomplexinteractionsStructural Biology…understanding cellular functions anddisease associations of proteins.1610

Footprinting can determine structure & dynamics of membrane proteinsStructural Waters define a functional channel mediating activation of the GPCR, rhodopsinThomas E. Angel 1 , Sayan Gupta 2,3 , Beata Jastrzebska 1 , Krzysztof Palczewski 1 , Mark R. Chance 2-41 Department of Pharmacology, 2 Center for Prroteomics & Bioninformatics, 3 Department of Physiology & BiophysicsAngel, Thomas. PNAS. 2009. 106(34):14367-72.Goal: Determine structure of active form of RhodopsinRhodopsin (TM domains)CNBr fragmentsPeptic fragments…understanding cellular functions anddisease associations of proteins.19What information does each proteomic technique provide?Expression Proteomics: Provides a fingerprint of what is happening in a cellPost-Translational Modification Proteomics: Can give information about changes in signaling pathwaysInteraction Proteomics: Gives information about networks of interacting proteins not just information about individualproteins.Bioinformatics & Biostatistics: Provides networks and pathways of proteins that interact (inhibition or activation).Systems Medicine & Data Analysis: Integrates –omics data in the context of protein-protein interaction networksX-Ray Footprinting Understand macromolecular folding and interactions in solution and solvent accessibility oflocal sites (tertiary contacts) within a macromolecule.…understanding cellular functions anddisease associations of proteins.2012

http://proteomics.case.edu/How to reach us…Sara E. Tomechko, Ph.D.sew65@case.edu216-368-4784…understanding cellular functions anddisease associations of proteins.2113

What information does each proteomictechnique provide?(Detailed information about each service follows this page.)Expression Proteomics:Provides a fingerprint of what is happening in a cellGives quantitative information about changes in a cell due to stimulation (forexample drug treatment or environmental change)Post-Translational Modification Proteomics:Can give information about changes in signaling pathwaysExcessive PTMs can induce conformational changes that may make aprotein inactiveInteraction Proteomics:Gives information about networks of interacting proteins not just informationabout individual proteins.Bioinformatics & Biostatistics:Provides networks and pathways of proteins that interact (inhibition oractivation).Systems Medicine & Data Analysis:Integrates –omics data in the context of protein-protein interaction networksto provide a functional framework for integrating different types of dataMacromolecular Crystallography:Provides structure and function information of bio-molecules.X-Ray Spectroscopy:Provides information on the local geometric and electronic structure oftargeted atoms as well as detailed atomic structure within 5-10Å of thetarget.Can provide information about metal active sites in a proteinX-Ray Footprinting:Understand macromolecular folding and interactions in solution even forvery large assemblies.Provides a measure of solvent accessibility of local sites (tertiary contacts)within a macromolecule. At every backbone position for cleavage basedfootprinting and ~50% of side chain residues for hydroxyl radical mediatedfootprinting of proteins.Can probe dynamics on millisecond timescales or equilibrium structures.Requires femtomoles to picomoles of material.14

Expression Proteomic TechniquesTop DownShotgun (Bottom Up)2D-PAGEMethodsSILACIn vitro LabelingLabel Freecontrol treatProteinIsolation2D gelscontrol“Light”mediatreatIn vivolabeling“Heavy”mediaProteinIsolationcontrol treatProteinIsolationDigestioncontrol treatProteinIsolationDigestionDigestionLabelingGel AnalysisSpot ExcisionLC-MS/MSLC-MS/MSProteomic ProfilingLC-MS/MSLC-MS/MSProteomic ProfilingProteomic ProfilingProteomic Profiling15

Label Free Protein Expression• Provides accurate quantitative information about changes inprotein expression as a function of stimulation.• Advantages– Can accommodate complex experimental designs, ideal forclinical samples and provide increased proteome coverage– Easy transition to a ‘bottom up’ validation analysis– Amendable to low sample concentration (600 nanograms for LC‐MS/MS• Disadvantages– Difficulty quantifying post translational modifications– High degree of sample complexity for the mass spectrometer• Preferred sample format:– Cell pellet– In tact tissue• At least 1ug of total protein is required for this workflowWorkflow16

18O Protein Expression• Provides accurate quantitative information about response tostimulation. Ideal for pairwise comparisons.• Advantages– Can provide increase proteome coverage– Accurate quantitation– Amendable to low sample concentration (600 nanograms for LC‐MS/MS• Disadvantages– Difficulty accommodating complex experimental designs• Preferred sample format:– Cell pellet– In tact tissue• At least 10ug of total protein is required for this workflowC T C TWorkflowWorkflow from this point on issame as Label free(pick up with data processingstep)DigestionCTC 16 O 16 OHC 18 O 18 OHMSQuantitative Info18O Labelingm/z, amuC 16 O 16 OHC 16 O 16 OHC 16 O 16 OHC 18 O 18 OHC 18 O 18 OHC 18 O 18 OHIntensity, cps7.0e46.5e46.0e45.5e45.0e44.5e44.0e43.5e43.0e4C 16 O 16 OHC 18 O 18 OH2.5e42.0e41.5e41.0e4C 16 O 16 OHC 18 O 18 OH5000.00.02 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34Time, min17

2D‐DIGE• Provides accurate quantitative information about response tostimulation.• Advantages– Accurate quantitation– The only top down platform– High resolving power of samples at protein level• Disadvantages– This technique requires large amounts of protein.– Difficulty identifying membrane proteins• Preferred sample format:– Cell pellet– In tact tissue• At least 250ug of total protein is required for this workflowWorkflowFluor ATest SampleFluor BControl SampleFluor CInt. sta. SampleMix2D gelImage gelExcitation 1Excitation 2Excitation 3Image testImage controlGel Imagesanalysis18Image Int.sta.Differential Protein IDLC-MS/MS

• Provides information about protein post‐translationalmodifications as a result of stimulation. Can be quantitative.– Accurately identify site of PTM– Enrichment increases probability of identifying PTMs in lowabundance– Gives added information about disease• Preferred sample format:– Cell pellet– In tact tissue– Coomassie gel bandPTMs• At least 50ug of total protein or 3‐4 strong gel bands arerequired for this workflowWorkflowDigestionModified Protein IDYYPeptide EnrichmentEnriched PeptidesRaw Data AcquisitionLC/MS/MS19

Affinity Purification MS / IP‐pulldowns MS• Provides information on proteins and their complexes and howthey interact with one another• Can provide information about novel drug targets• Help understand mechanism and side‐effects of therapeuticcompounds• Can help reconstruct pathways• Can provide functional information based on the function ofproteins that are interacting with the protein of interest.• Provides information about protein molecular environment• Can provide information about protein complex cross‐talkWorkflowAP‐MS: protein complexBait selectionNoisereductionEpitopetaggingModeling protein complexesExpressionin cell lineMS‐proteinidentificationAffinity purificationof the protein complexBait: Protein of interest with epitope tagged.Prey: Protein associated with bait protein complex.20

Systems Medicine & Data Analysis: Integrative –omics analysis• Provides integration of system specific experimental data withhigh‐throughput large dataset utilizing computational tools.• Advantages– Can accommodate complex experimental designs– Can reduce complexity that is introduced by large scaleexperiments ‐ Easily scalable– Can provide functional links to novel targets• Disadvantages– Can generate large networks and increased number of targets.– Rarely studied targets would lead to limited/hypothetical results– Specialized data analysis takes longer time• Preferred sample format:– Target genes/protein lists, preferably with accompanying tissuespecific high‐throughput data or pointers to publicly available datasources.Hypotheses:Genes/proteinspostulated to beinvolved in thedisease/phenotype1. Query Target Genes/ProteinsHypothesis DrivenWorkflowPathway Analysis Framework5. Evaluate core targets fora) Signal transductionb) Therapeutic intervention2. Connect candidategenes‘omics4. Identify functionallycoherent coreAnnotated Networks3. Evaluate biologicalsignificanceof subnetwork(s)21

X‐Ray Absorption Spectroscopy• Provides information on electronic and atomic structure forboth crystalline and non‐crystalline systems• Fast probe therefore, suitable for multiple‐scale time‐resolvedexperiments.• No “spectroscopically quiet” metals; always detectable, unlike UV‐VIS and EPR.• Provides insights to metal site’s electronic structure, includingmetal valence and site geometry (XANES).• Local probe of metal site structure, and is sensitive to within 4‐5Åof metal sites (EXAFS).• Bond lengths determined more accurately (± 0.02 Å) than in X‐raycrystallography.• Well suited to probing reactive intermediates in solution.• Preferred Sample format• Purified Protein• At least 35 mL (prefer 100 mL) of 250 mM ‐ 1 mM for the metalof interest for EXAFS; 50‐100 mM for XANES data only.Concentration needs decrease as metal atomic numberincreases.Workflow22

X‐Ray Footprinting MS• Provides information about protein structure & dynamics• Structure Information– Good for macromolecular assemblies that can not be crystallized orare too big for NMR– Can resolve membrane protein structure– Provides information about proteins in various physiologicalconditions– Provides information about interactions of bulk proteins, boundproteins and how water orders itself.• Protein Dynamics Information– Binding interfaces– Conformational changes during activation, ligand binding, function,etc.– Water dynamics within the transmembrane region– Structure of mobile protein regions• Preferred sample format– Purified Protein• At least 100L of a 1M solution is required for equilibriumfootprinting and 100L of a 5M solution is required for stopflow footprintingWorkflowH 2 OX‐ray/Fenton•OHSModificationOHSProteinOHDigestion30ms20msRANativeOxidizedFraction Unmodified1.000.980.950.93Dose Response0.900 20 40 60 80 100Exposure time (ms)MS/MS+ LigandLigandSOHS10ms0msx x + 16m/zAbundanceb 4 +16y 2y 3y 4 +16b 3 +16y 5 +16b 6 +16m/zProtein + LigandLC‐MS analysis23

Macromolecular Crystallography• Provides high resolution 3‐D information about biologicalmacromolecules• The Synchrotron radiation has some unique propertiescompared to laboratory X‐ray sources– High X‐ray intensity (flux)– Tightly focused X‐ray beam (200 x 200um or smaller)– Tunability of the wavelength (energy)– Can provide structure information for small or poorly diffractingcrystals– Can screen large number of crystals in short period of timeWorkflowCrystalsDiffraction DataPhase ProblemMap InterpretationModel RefinementProtein Structure24

Center for Proteomics & Bioinformatics PricingNew pricing effective February 1, 2012!Preparatory Services1D Gel Electrophoresis $65Up to 9 samples per gelProtein Concentration Analysis$35/sampleSample Clean‐up$35/sampleAffinity Separation$75/sampleAgilent Hu‐14C18 Processing$15/sampleDigestion$10/sampleIncludes reduction, alkylation and enzymePost‐translational Modification and Structural AnalysisGlobal Phophoproteome AnalysisIncludes digestion, enrichment, LC‐MS/MS and analysisPhosphorylation IDIncludes digestion, enrichment, LC‐MS/MS and analysisCall for quote$500/sampleLC‐MS/MS AnalysisShort gradient0‐90 minutesMedium gradient91‐180 minutesLong gradient181‐240 minutes$150/sample$250/sample$475/sampleELISA AnalysisELISAIncludes plate, analysis and report generation$1500/plateQuantitative AnalysisLabel FreeiTRAQSILACHeavy PeptideMultiple Reaction Monitoring (MRM)Call for quoteCall for quoteCall for quoteCall for quoteCall for quote25

Intact Mass AnalysisFT‐LTQ or MALDI‐ToF$65/sampleIndependent Instrument UsageMALDI‐ToFOff‐line HPLC$45/30 min or $65/hr$105/sampleData Analysis ServicesMolecular and systems Biology and Standard Data Analysis$80/hrInstrument TrainingMALDTI‐ToF $250Contact Center to schedule2D Gel ServicesDeep Purple Staining$250/sampleIncludes scanningGel Scanning using Typhoon Imager$60/gelIndependent Typhoon Usage$52/hrSpot Picking for Digestion $1052D Gel Run without labeling $110Cell Pellet tissue processing$220/sample2D Gel sample processingRun and Image 1 sample in 1 gel $350Includes labelingRun and Image 2 sample in 1 gel $460Includes labelingRun and Image 3 sample in 1 gel $570Includes labeling96 Well MALDI Service $1575Includes raw data and imagesInvesitgators are highly encouraged to contact Janna Kiselar (janna.kiselar@case.edu) for allgrants and Daniela Schlatzer (daniela.schlatzer@case.edu) for quantitative projects. We arehappy to discuss experimental design and provide and support/assistance for your project.26

Frequently Asked QuestionsQ: I am interested in using the proteomics center. What now?A: 1. To request follow up information, contact Sara Tomechko at 216‐368‐4784 orsew65@case.edu.2. If you are interested in quantitative experiments, contact Daniela Schlatzer at 216‐368‐4014 or daniela.schaltzer@case.edu3. If you are interested in structural or PTM experiments, contact Janna Kiselar at 216‐368‐0979 or janna.kiselar@case.edu4. The Center staff will work with you to design experiments that meet your scientific needsand provide a quote based upon the planned experiments.5. You will complete a sample submission form (available on our website:http://proteomics.case.edu or this section of the packet).6. We will work with you to schedule a time for you to drop off your samples.7. We will conduct the agreed upon experiments and provide you data.Q: Who should prep the samples?A: We strongly encourage letting the Center for Proteomics and Bioinformatics staff prep yoursamples for your experiment.Q: What information does the Center for Proteomics and Bioinformations need if we prep ourown samples? Why do they need it?A: The Center for Proteomics and Bioinformatics needs detailed information (buffercomposition and concentration) about all solutions used during sample prep. Simply tellingus you used a RIPA buffer during cell lysis is not sufficient; different manufacturers usedifferent components. Certain buffers contain compounds that can harm our instrumentsand cause substantial downtime and costly repairs.Q: I have a 1D gel band that I would like to identify the proteins from. What is the cost to dothis?A: For this type of sample, we would perform a digest, analyze with a short gradient and thenrun a database search. You would then receive a report indicating the proteins identifiedwithin a given cutoff.Digestion $10LC‐MS/MS Short gradient $150Data Analysis (3 hrs included) $0Total$160/sampleQ: We are interested in changes that may occur in the liver of mice +/‐ drug treatment. Howmuch would this cost?A: Please contact Daniela Schlatzer to discuss feasibility at 216‐368‐4014 orDaniela.schlatzer@case.edu27

Q: We are interested in Phosphotproteome changes in cells that have been exposed tohypoxia. How much would this cost?A: Please contact Janna Kiselar at 216‐368‐0979 or janna.kiselar@case.edu to discuss the projectand pricing.Q: Is the CCPB available for use by researchers outside of the Center and/or Case WesternReserve University?A: The Case Center for Proteomics and Bioinformatics (CPB) facility is available to allinvestigators at Case Western Reserve University, University Hospitals, MetroHealth System,the Cleveland Clinic Research Institute, and the Cleveland Clinic Foundation. Depending onresearch needs and availability, the Center’s research core facilities may also be available toresearchers at other non‐profit or for‐profit research institutions across the country. Manyinvestigators and projects require a close collaboration with CCPB faculty and staff members.CCPB members work closely with collaborators to design and run experiments as well asanalyze data, publish results and submit grant proposals.Q: What type of facilities do you have at your Center for Synchrotron Biosciences atBrookhaven National Laboratory at the National Synchrotron Light Source in New York?A: Three of our research cores (Macromolecular Crystallography, X‐ray Spectroscopy, and X‐rayFootprinting) are available to a national community of users at the Center for SynchrotronBiosciences (CSB) which operates 4 beamlines. Please visit the CSB Website(http://csb.case.edu) to learn more about the X29A, X3A, X3B and X28C beamlines.Q: I have a set of candidate genes/proteins, and I'm interested in doing a systems‐levelpathway analysis of the data. Can you help me with that?A: Certainly! The Center provides pathway analysis services using both commercial software(MetaCore and Ingenuity Pathway Analysis), as well as technology developed in house. Weare also developing methods to couple various high‐throughput datasets (e.g. 2D DIGE +microarray data; SNP data + microarray data) to guide hypothesis development towards themost biologically functional parts of the system. Contact Rob Ewing at 216‐368‐4380 orrobert.ewing@case.edu for more information.Q: How can I receive more information about the Center's seminars, workshops and otherevents?A: You can request to join our email distribution list by sending an email tomaita.diaz@case.edu.28

Center for ProteomicsThe ClevelandFoundationCenter for Proteomics9 th Floor, BRB10900 Euclid AvenueCleveland, Ohio 44106-4988Phone 216.368.1490Fax 216.368.6846http://proteomics.case.edu/Project Submission FormInstructions1 Fill out the appropriate information on each of the following pages.2. Schedule an appointment:For LC MS/MS service contact Dr. Janna Kiselar at (216) 368-0979 or janna.kiselar@case.eduor Katy Lundberg at (216) 368-4159 or katy@case.eduFor 2 D Gel service contactDr. Elizabeth Yohannes at (216) 368-0289 or elizabeth.yohannes@case.edu2 Bring samples and submission form to initial meeting.Case Center for ProteomicsCWRU, School of Medicine2109 Adelbert Rd. BRB 947Cleveland, OH 44106-4988(216) 368-029129

PROPOSED SAMPLE DETAILS(Required for sample processing)Is this in gelin solutionProtein in solution: Specify concentration of protein and molarity of other constituents (detergents, salts, buffers, etc)_________________________________________________________________________________Please attach sample protocol for samples that are in solutionGenus and species of source organism:_______________________________________________Additional Comments: ____________________________________________________________PLEASE NOTE: Case Center for Proteomics CANNOT ACCEPT RADIOACTIVEor HAZARDOUS MATERIALSSERVICES REQUESTEDTo be filled out by CCP representativePROTEIN LABORATORY SERVICES(Please check all that apply)Large format 2-DE Protein Concentration Analysis Sample Clean-UpImage Analysis Protein Excision Data AnalysisCell Pellet ProcessingOther (Please specify)__________________________________PROTEIN AND PEPTIDE MASS SPECTROMETRY SERVICES(Please check all that apply)Intact Mass MALDI ElectrosprayProtein ID by LC/MSOther (please specify)_____________________________________Data Analysis*this charge is for manual sequencing beyond Protein IDADDITIONAL COMMENTS30

PROJECT CONTACT INFORMATIONPlease provide the following information on this page.Thank you.Grant Title:Investigator Name:Principal Investigator: _________________________CCP Project ID: ______________________________eRA Commons Name:________________________Is the PI part of the CTSC? Yes NoIs the PI part of CFAR? Yes NoDepartment / Company:Who to contact with questions regarding project?Name:_________________________________Address:Phone:_________________________________Email:__________________________________Phone:_____________________________Fax:_______________________________Email:_____________________________BILLING INFORMATIONGrant Number / Speedtype:_______________________Billing contact:______________________________Phone:____________________________________Email:_____________________________________Billing Address (if different from above):ACCEPTANCE OF TERMSThe information provided in the Sample Submission Form is true to my knowledgeClient Signature _____________________________________ Date_____________________________CCP Representative __________________________________ Date_____________________________31

Case Western Reserve University School of Medicine’s Case Center for ProteomicsTERMS AND CONDITIONS OF SERVICESClients Who Are Not Case Faculty or Employees1 Governing Terms And Scope These terms and conditions (here in after “Terms”) govern the providing of proteinanalytical and other services ("Services") by Case Western Reserve University by and through its School of Medicine byand Case Center for Proteomics ("CCP") for you (the "Client"). Performance of any Services does not constitute CCP'sacceptance of any new or different terms, including pre-printed terms on Client's purchase order. These terms may onlybe modified by authorized representatives of CCP and the client.2 Services. Client shall designate a representative for receipt of communications under this Agreement (the"Designated Representative"). The Designated Representative shall fill out and sign a sample submission form, whichwhen signed by an authorized CCP representative will constitute acceptance of terms of the agreement, including theseterms of service Upon completion of the project, the test results shall be delivered to the Designated Representative.All services shall be performed at, and in accordance with CCP's then current rates, terms and policies. Such rates, termsand policies are subject to change, unless CCP provides a quotation for specific work and such work is accepted by theclient by signing a contract and is scheduled within the quotation validity period. Copies of current applicable rates, termsand policies will be posted on the CCP website. (http://casemed.case.edu/proteomics/)3 Specimens Client shall submit all specimens or materials for analysis, including gel plugs, cells and tissue samples("Specimens") in compliance with applicable import, export, customs and other laws and regulations. CLIENT SHALL NOTSUBMIT SPECIMENS WHICH ARE RADIOACTIVE, WHICH CONTAIN LIVE BIOLOGICAL AGENTS OR WHICH OTHERWISEPRESENT ANY HEALTH OR ENVIRONMENTAL RISKS OR WHICH COULD CAUSE DIRECT OR INDIRECT DAMAGE OR HARMTO CCP PERSONNEL OR PROPERTY. CLIENT SHALL NOT SUBMIT SPECIMENS WHICH ARE TRANSMITTED WITH ANYIDENTIFIABLE PROTECTED HEALTH INFORMATION (PHI) AS DEFINED BY HIPAA REGULATIONS.4 Handling of Specimens. All specimens and materials shall be submitted in accordance with the CCP guidelines inSection 3 above. CCP shall not be responsible for lost or contaminated materials.5 Pricing and Payment. All orders shall be subject to acceptance by CCP. Prices are in U.S. dollars. Terms ofpayment are net thirty (30) days from the date of invoice. CCP will assess late payment charges on amounts not paidwithin thirty (30) days of the invoice date at the maximum rate allowed by law or 1-1/2% per month, whichever is less.6 Warranties. CCP agrees to perform all services in manner consistent with the provision of similar services byqualified organizations in Northeast Ohio. CCP shall endeavor to perform all tests within the time period indicated butshall not be liable for failure to meet such period. CCP shall not be responsible for Client's use of or inability to use the testor project results. CCP MAKES NO WARRANTIES REGARDING THE QUALITY OF ITS SERVICES OR THE TEST OR PROJECTRESULTS. WITHOUT LIMITING THE GENERALITY OF THE FOREGOING, CCP EXPRESSLY DISCLAIMS ANY WARRANTIES OFDURABILITY, MERCHANTABILITY, OR FITNESS FOR A PARTICULAR PURPOSE AND DISCLAIMS THAT SERVICES WILL MEETALL OF CLIENT'S NEEDS OR THAT RESULTS WILL BE ERROR FREE.7 Damages And Limitation Of Liability IN NO EVENT SHALL CCP BE LIABLE FOR INDIRECT, SPECIAL, INCIDENTAL,CONSEQUENTIAL OR PUNITIVE DAMAGES WHETHER OR NOT SUCH DAMAGES ARE FORESEEABLE AND WHETHER OR NOTPERSONS HAVE BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGES, INCLUDING, BUT NOT LIMITED TO, LOSS OFPROFITS OR REVENUE, LOSS OF DATA, OR ATTORNEYS' FEES, WHETHER UNDER NEGLIGENCE, STRICT LIABILITY,ENTERPRISE LIABILITY OR OTHER PRODUCT LIABILITY THEORIES. CCP’S TOTAL LIABILITY SHALL NOT EXCEED THE AMOUNTPAID TO CCP DURING THE TWELVE-MONTH PERIOD IMMEDIATELY PRECEDING THE OCCURRENCE OF THE DAMAGE ORLOSS.8 Indemnity. Client shall defend, indemnify and hold CCP harmless from all losses, damages, costs or expenses ofany kind or nature, without limitation, which CP, its employees, representatives or consultants or other third parties mayincur as a result of Client's transmission of specimens with associated PHI, submission of harmful or potentially harmfulspecimens or materials or any specimens or materials or any CCP equipment that are submitted in violation of thisAgreement. Client agrees that it will be solely responsible for ensuring that any specimens or materials will be returned topermissible recipients in compliance with all import and export laws, and client will indemnify CCP against any losses,damages, cost or expenses incurred in connection there with. Client shall defend, indemnify and hold harmless CCP andits employees, agents, contractors and consultants from any liabilities, damages or claims, including costs and attorneyfees, arising out of Client's breach of these terms or any claims of infringement of third party intellectual property rightsrelated to the Specimens. (Note Specimens is defined in section 3)9 Entire Agreement. These Terms and Conditions of service constitute the entire agreement of the parties withrespect to the Services and may be modified only by a written instrument signed by the parties.10 Governing Law. The Agreement including terms shall be governed by and interpreted and construed inaccordance with the laws of the State of Ohio. The parties consent to exclusive jurisdiction in any State or Federal Courtlocated in Cuyahoga County, Ohio.32

Center for Proteomics & Bioinformatics ContactsMark Chance, Ph. D.,DirectorJanna Kiselar, Ph.D., Assistant DirectorContact Janna for information on all grants and footprinting projects.216‐368‐0979 janna.kiselar@case.eduJoan Schenkel, M.S.Instructor and Senior AdministratorContact Joan for billing information.216‐368‐4268 joan.schenkel@case.eduMaita DiazAssistant to Mark ChanceContact Maita to schedule appointments with Mark, to join our email distribution list,for information about the Center’s seminars, workshops and other events.216‐368‐0291 maita.diaz@case.eduKaty Lundberg, M.S., LIMS Administrator & Project CoordinatorContact Katy for quotes.216‐368‐4159 katy@case.eduDanie Schlatzer, B.S. Senior Research Associate (Operations Group Leader)Contact Danie for label free proteomic experimental design or information.216‐368‐4014 daniela.schlatzer@case.eduSara Tomechko, Ph.D. Research AssociateContact Sara for general questions, follow up presentations or collaborations, lab tours,etc.216‐368‐4784 sew65@case.edu33

Endogenous protein S‐nitrosylation in E. coli: regulation by OxyRSeth D, Hausladen A, Wang YJ, Stamler JS.Science. 336(6080):470‐473,2012. PMID: 22539721Endogenous S‐nitrosylation of proteins, a principal mechanism of cellular signaling ineukaryotes, has not been observed in microbes. We report that protein S‐nitrosylation is anobligate concomitant of anaerobic respiration on nitrate in E. coli. Endogenous S‐nitrosylationduring anaerobic respiration is controlled by the transcription factor OxyR, previously thought tooperate only under aerobic conditions. Deletion of OxyR resulted in large increases in protein S‐nitrosylation, and S‐nitrosylation of OxyR induced transcription from a regulon that is distinctfrom the regulon induced by OxyR oxidation. Furthermore, products unique to the anaerobicregulon protected against S‐nitrosothiols, and anaerobic growth of E.coli lacking OxyR wasimpaired on nitrate. Thus, OxyR serves as a master regulator of S‐nitrosylation, and alternativeposttranslational modifications of OxyR control distinct transcriptional responses.Figure: MS/MS spectra of the cysteine‐containing peptides in SNO‐OxyR identified after SNO‐RAC enrichment and LC‐MS/MS analysis. Shown are representative annotated MS/MSfragmentation spectra for the Cys199‐containing peptide with ascorbate. Cys199‐containingpeptide was not observed in the absence of ascorbate. Peptide sequence is shown at the top ofeach spectrum, with the annotation of the identified matched amino terminus‐containing ions(b ions) in black and the carboxyl terminus‐containing ions (y ions) in red. For clarity,only major identified peaks are labeled.34

Network biology methods integrating biological data for translational scienceBebek G, Koyutürk M, Price ND, Chance MR.Brief Bioinform. 2012.The explosion of biomedical data, both on the genomic and proteomic side as well as clinicaldata, will require complex integration and analysis to provide new molecular variables to betterunderstand the molecular basis of phenotype. Currently, much data exist in silos and is notanalyzed in frameworks where all data are brought to bear in the development of biomarkersand novel functional targets. This is beginning to change. Network biology approaches, whichemphasize the interactions between genes, proteins and metabolites provide a framework fordata integration such that genome, proteome, metabolome and other ‐omics data can be jointlyanalyzed to understand and predict disease phenotypes. In this review, recent advances innetwork biology approaches and results are identified. A common theme is the potential fornetwork analysis to provide multiplexed and functionally connected biomarkers for analyzingthe molecular basis of disease, thus changing our approaches to analyzing and modelinggenome‐ and proteome‐wide data.35

Insights into substrate specificity and metal activation of mammalian tetrahedral aspartylaminopeptidaseChen Y, Farquhar ER, Chance MR, Palczewski K, Kiser, J.J. Biol. Chem. 2012Aminopeptidases are key enzymes involved in the regulation of signaling peptide activity. Herewe present a detailed biochemical and structural analysis of an evolutionary highly conservedaspartyl aminopeptidase called DNPEP. We show that this peptidase can cleave multiplephysiologically relevant substrates including angiotensins and thus may play a key role inregulating neuron function. Using a combination of X‐ray crystallography, X‐ray absorptionspectroscopy and single particle electron microscopy analysis, we provide the first detailedstructural analysis of DNPEP. We show that this enzyme possesses a binuclear Zn active site inwhich one of the Zn ions is readily exchangeable with other divalent cations such as Mn, whichstrongly stimulates the enzymatic activity of the protein. The plasticity of this metal binding sitesuggests a mechanism for regulation of DNPEP activity. We also demonstrate that DNPEPassembles into a functionally relevant tetrahedral complex that restricts access of peptidesubstrates to the active site. This structural data allows rationalization of the enzyme'spreference for short peptide substrates with N‐terminal acidic residues. This study provides astructural basis for understanding the physiology and bioinorganic chemistry of DNPEP andother M18 family aminopeptidases.Figure: Structure and topology ofDNPEP. Crystallographic structureof the DNPEP monomer.36

Novel urinary protein biomarkers predicting the development of microalbuminuria and renalfunction decline in type 1 diabetesSchlatzer D, Maahs DM, Chance MR, Dazard JE, Li X, Hazlett F, Rewers M, Snell‐Bergeon JK.Diabetes Care. 35(3):549‐55, 2012. PMID: 22238279OBJECTIVE To define a panel of novel protein biomarkers of renal disease.RESEARCH DESIGN AND METHODS Adults with type 1 diabetes in the Coronary ArteryCalcification in Type 1 Diabetes study who were initially free of renal complications (n = 465)were followed for development of micro‐ or macroalbuminuria (MA) and early renal functiondecline (ERFD, annual decline in estimated glomerular filtration rate of ≥3.3%). The label‐freeproteomic discovery phase was conducted in 13 patients who progressed to MA by the 6‐yearvisit and 11 control subjects, and four proteins (Tamm‐Horsfall glycoprotein, α‐1 acidglycoprotein, clusterin, and progranulin) identified in the discovery phase were measured byenzyme‐linked immunosorbent assay in 74 subjects: group A, normal renal function (n = 35);group B, ERFD without MA (n = 15); group C, MA without ERFD (n = 16); and group D, both ERFDand MA (n = 8). RESULTS In the label‐free analysis, a model of progression to MA was built using252 peptides, yielding an area under the curve (AUC) of 84.7 ± 5.3%. In the validation study,ordinal logistic regression was used to predict development of ERFD, MA, or both. A panelincluding Tamm‐Horsfall glycoprotein (odds ratio 2.9, 95% CI 1.3‐6.2, P = 0.008), progranulin(1.9, 0.8‐4.5, P = 0.16), clusterin (0.6, 0.3‐1.1, P = 0.09), and α‐1 acid glycoprotein (1.6, 0.7‐3.7, P= 0.27) improved the AUC from 0.841 to 0.889. CONCLUSIONS A panel of four novel proteinbiomarkers predicted early renal damage in type 1 diabetes. These findings require furthervalidation in other populations for prediction of renal complications and treatment monitoring.Figure 1: Significant differences were observed between groups A and D for THP (Figure A) andprogranulin (Figure B). Both THP and progranulin followed a stepwise pattern, with the lowestlevels in those patients who maintained normal renal function and normoalbuminuria (GroupA), increasing non‐significantly in those patients with either ERFD (Group B) or MA (Group C),and significantly increased in patients with both ERFD and MA (Group D).37

Streptomyces erythraeus trypsin inactivates α 1 ‐antitrypsinVukoti, KM, Rao Kadiyala, CS, Miyagi MFEBS Letters. 585(24):2898‐3902, 2012. PMCID: PMC3236438Streptomyces erythraeus trypsin (SET) is a serine protease that is secreted extracellularly by S.erythraeus. We investigated the inhibitory effect of α 1 ‐antitrypsin on the catalytic activity of SET.Intriguingly, we found that SET is not inhibited by α 1 ‐antitrypsin. Our investigations into themolecular mechanism underlying this observation revealed that SET hydrolyzes the Met–Serbond in the reaction center loop of α 1 ‐antitrypsin. However, SET somehow avoids entrapmentby α 1 ‐antitrypsin. We also confirmed that α 1 ‐antitrypsin loses its inhibitory activity afterincubation with SET. Thus, our study demonstrates that SET is not only resistant to α 1 ‐antitrypsinbut also inactivates α 1 ‐antitrypsin.38

Structural Analysis of Proinsulin Hexamer Assembly by Hydroxyl Radical Footprinting andComputational ModelingKiselar, JG, Datt M, Chance MR, Weiss, MAJ. Biol. Chem. 286(51): 43710‐6. PMCID: PMC3243561Mutations in the insulin gene can impair proinsulin folding and cause diabetes mellitus.Although crystal structures of insulin dimers and hexamers are well established, proinsulin isrefractory to crystallization. Although an NMR structure of an engineered proinsulin monomerhas been reported, structures of the wild‐type monomer and hexamer remain undetermined.We have utilized hydroxyl radical footprinting and molecular modeling to characterize thesestructures. Differences between the footprints of insulin and proinsulin, defining a “shadow” ofthe connecting (C) domain, were employed to refine the model. Our results demonstrate that inits monomeric form, (i) proinsulin contains a native‐like insulin moiety and (ii) the C‐domainfootprint resides within an adjoining segment (residues B23–B29) that is accessible tomodification in insulin but not proinsulin. Corresponding oxidation rates were observed withincore insulin moieties of insulin and proinsulin hexamers, suggesting that the proinsulin hexamerretains an A/B structure similar to that of insulin. Further similarities in rates of oxidationbetween the respective C‐domains of proinsulin monomers and hexamers suggest that this loopin each case flexibly projects from an outer surface. Although dimerization or hexamer assemblywould not be impaired, an ensemble of predicted C‐domain positions would block hexamerhexamerstacking as visualized in classical crystal lattices. We anticipate that proteinfootprinting in combination with modeling, as illustrated here, will enable comparative studiesof diabetes‐associated mutant proinsulins and their aberrant modes of aggregation.Domain organization of proinsulin and sites of modification.The modeled structure of wild‐type proinsulin depicting theamino acid residues undergoing modification in proteinfootprinting experiments. The A‐chain is in magenta, and theC‐chain is in green. The three peptide fragments in the B‐chain are rendered in different shades of blue.39

A quantitative proteomic approach for detecting protein profiles of activated human myeloiddendritic cellsSchlazter DM, Sugalski J, Dazard JE, Chance MR, Anthony DDJ. Immunol. Methods. 375(1‐2):39‐45, 2012. PMCID: PMC3253886Dendritic cells (DC) direct the magnitude, polarity and effector function of the adaptive immuneresponse. DC express toll‐like receptors (TLR), antigen capturing and processing machinery, andcostimulatory molecules, which facilitate innate sensing and T cell activation. Once activated, DCcan efficiently migrate to lymphoid tissue and prime T cell responses. Therefore, DC play anintegral role as mediators of the immune response to multiple pathogens. Elucidating themolecular mechanisms involved in DC activation is therefore central in gaining an understandingof host response to infection. Unfortunately, technical constraints have limited system‐wide‘omic’ analysis of human DC subsets collected ex vivo. Here we have applied novel proteomicapproaches to human myeloid dendritic cells (mDCs) purified from 100 mL of peripheral bloodto characterize specific molecular networks of cell activation at the individual patient level, andhave successfully quantified over 700 proteins from individual samples containing as little as200,000 mDCs. The proteomic and network readouts after ex vivo stimulation of mDCs withTLR3 agonists are measured and verified using flow cytometry.Figure: IRF signaling pathway thatwas generated from pathwayanalysis of proteins with significantfold changes across both studies.The proteins highlighted in redwere detected in our analysis andhad a significant increase inabundance upon stimulation.40

The inducible kinase IKKi is required for IL‐17‐dependent signaling associated withneutrophilia and pulmonary inflammationBulek K, Liu C, Swaidani S, Wang L, Page RC, Gulen MF, Herjan T, Abbadi A, Qian W, Sun D, LauerM, Hascall V, Misra S, Chance MR, Aronica M, Hamilton T, Li X.Nat Immunol. 2011;12(9):844‐52. PMCID: PMC3282992Interleukin 17 (IL‐17) is critical in the pathogenesis of inflammatory and autoimmune diseases.Here we report that Act1, the key adaptor for the IL‐17 receptor (IL‐7R), formed a complex withthe inducible kinase IKKi after stimulation with IL‐17. Through the use of IKKi‐deficient mice, wefound that IKKi was required for IL‐17‐induced expression of genes encoding inflammatorymolecules in primary airway epithelial cells, neutrophilia and pulmonary inflammation. IKKideficiency abolished IL‐17‐induced formation of the complex of Act1 and the adaptors TRAF2and TRAF5, activation of mitogen‐activated protein kinases (MAPKs) and mRNA stability,whereas the Act1‐TRAF6‐transcription factor NF‐κB axis was retained. IKKi was required for IL‐17‐induced phosphorylation of Act1 on Ser311, adjacent to a putative TRAF‐binding motif.Substitution of the serine at position 311 with alanine impaired the IL‐17‐mediated Act1‐TRAF2‐TRAF5 interaction and gene expression. Thus, IKKi is a kinase newly identified as modulating IL‐17 signaling through its effect on Act1 phosphorylation and consequent function.Figure (a): Tandem massspectrometyr of precursor ions inthe phosphorylated Act1 peptideat a m/z of 721.33 Da. Blue linesindicate peptide cleavage(b): Tandem mass spectrometry ofprecursor ions of an unmodifiedpeptide of the same sequence asin (a) at m/z of 695.01 Da.41

Structural Mass Spectrometry of Proteins Using Hydroxyl Radical Based Protein FootprintingWang L, Chance MRAnal. Chem. 2011;83(19):7234‐41.Structural MS is a rapidly growing field with many applications in basic research andpharmaceutical drug development. In this feature article the overall technology is described andseveral examples of how hydroxyl radical based footprinting MS can be used to map interfaces,evaluate protein structure, and identify ligand dependent conformational changes in proteinsare described.Figure: Flowchart of hydroxyl radical mediated PF: (A) chromatogram of the separation ofprotein digests using LC; (B) localization of oxidation sites by tandem MS at a precursor withsequence “VFITYSMoxDTAMEVVK” (Mox = ionized Met); (C) diagram of extraction of peaksfrom target oxidized peptides and their unmodified counterparts in the same LC trace withincreasing exposure time to hydroxyl radicals from top to bottom; (D) calculation of oxidationrate by plotting the dose response curve of unmodified peptide fraction versus exposuretime of hydroxyl radicals.42

Oxidative stress status accompanying diabetic bladder cystopathy results in the activation ofprotein degradation pathwaysKanika ND, Chang J, Tong Y, Tiplitsky S, Lin J, Yohannes E, Tar M, Chance M, Christ GJ, Melman A,Davies KD.BJU Int. 2011;107(10):1676‐84. PMCID: PMC3157237The objective of this study was to investigate the role that oxidative stress plays in thedevelopment of diabetic cystopathy. Comparative gene expression in the bladder of nondiabeticand streptozotocin (STZ)-induced 2-month- old diabetic rats was carried outusing microarray analysis. Evidence of oxidative stress was investigated in the bladder byanalyzing glutathione S-transferase activity, lipid peroxidation, and carbonylation andnitrosylation of proteins. The activity of protein degradation pathways was assessed usingWestern blot analysis. Analysis of global gene expression showed that detrusor smoothmuscle tissue of STZ-induced diabetes undergoes significant enrichment in targetsinvolved in the production or regulation of reactive oxygen species (P = 1.27 × 10(-10)).The microarray analysis was confirmed by showing that markers of oxidative stress wereall significantly increased in the diabetic bladder. It was hypothesized that the sequelae tooxidative stress would be increased protein damage and apoptosis. This was confirmedby showing that two key proteins involved in protein degradation (Nedd4 and LC3B)were greatly up-regulated in diabetic bladders compared to controls by 12.2 ± 0.76 and4.4 ± 1.0-fold, respectively, and the apoptosis inducing protein, BAX, was up-regulatedby 6.76 ± 0.76-fold. Overall, the findings obtained in the present study add to thegrowing body of evidence showing that diabetic cystopathy is associated with oxidativedamage of smooth muscle cells, and results in protein damage and activation of apoptoticpathways that may contribute to a deterioration in bladder function.Figure: Canonical pathway of mitochondrial dysfunction in an ingenuity pathway analysis knowledgebase overlaid with targets changed in 2‐month diabetic bladder compared to age‐matched controls.Green indicates down‐regulation and red indicates up‐regulation in diabetes.43

Characterization of metalloproteins by high‐throughput X‐ray absorption spectroscopyShi W, Punta M, Bohon J, Sauder JM, D'Mello R, Sullivan M, Toomey J, Abel D, Lippi M, PasseriniA, Frasconi P, Burley SK, Rost B, Chance MR.Genome Res. 2011(6):898‐907. PMCID: PMC3106322High‐throughput X‐ray absorption spectroscopy was used to measure transition metal contentbased on quantitative detection of X‐ray fluorescence signals for 3879 purified proteins fromseveral hundred different protein families generated by the New York SGX Research Center forStructural Genomics. Approximately 9% of the proteins analyzed showed the presence oftransition metal atoms (Zn, Cu, Ni, Co, Fe, or Mn) in stoichiometric amounts. The method ishighly automated and highly reliable based on comparison of the results to crystal structuredata derived from the same protein set. To leverage the experimental metalloproteinannotations, we used a sequence‐based de novo prediction method, MetalDetector, to identifyCys and His residues that bind to transition metals for the redundancy reduced subset of 2411sequences sharing

Histidine Hydrogen‐Deuterium Exchange Mass Spectrometry for Probing theMicroenvironment of Histidine Residues in Dihydrofolate ReductaseMiyagi M, Wan Q, Ahmad MF, Gokulrangan G, Tomechko SE, Bennett B, Dealwis CPLoS One. 2011;(6)2:e17055. PMCID: PMC3040192Histidine Hydrogen‐Deuterium Exchange Mass Spectrometry (His‐HDX‐MS) determinesthe HDX rates at the imidazole C 2 ‐hydrogen of histidine residues. This method provides not onlythe HDX rates but also the pK a values of histidine imidazole rings. His‐HDX‐MS was used to probethe microenvironment of histidine residues of E. coli dihydrofolate reductase (DHFR), an enzymeproposed to undergo multiple conformational changes during catalysis.Using His‐HDX‐MS, the pK a values and the half‐lives (t 1/2 ) of HDX reactions of fivehistidine residues of apo‐DHFR, DHFR in complex with methotrexate (DHFR‐MTX), DHFR incomplex with MTX and NADPH (DHFR‐MTX‐NADPH), and DHFR in complex with folate andNADP + (DHFR‐folate‐NADP + ) were determined. The results showed that the two parameters (pK aand t 1/2 ) are sensitive to the changes of the microenvironment around the histidine residues.Although four of the five histidine residues are located far from the active site, ligand bindingaffected their pK a , t 1/2 or both. This is consistent with previous observations of ligand bindinginduceddistal conformational changes on DHFR. Most of the observed pK a and t 1/2 changescould be rationalized using the X‐ray structures of apo‐DHFR, DHFR‐MTX‐NADPH, and DHFRfolate‐NADP+ . The availability of the neutron diffraction structure of DHFR‐MTX enabled us tocompare the protonation states of histidine imidazole rings.Our results demonstrate the usefulness of His‐HDX‐MS in probing themicroenvironments of histidine residues within proteins.Figure: Microenvironment of histidine residues in apo‐DHFR, DHFR‐MTX, DHFR‐MTX‐NADPH andDHFR‐folate‐NADP+ structures. The carbon atoms of apo‐DHFR, DHRF‐MTX, DHFR‐MTX‐NADPHand DHFR‐folate‐NADP+ are shown in yellow, light blue, green and cyan respectively.45

BiC: a web server for calculating bimodality of coexpression between gene and proteinnetworksLinderman GC, Patel VN, Chance MR, Bebek G.Bioinformatics. 2011;27(8):1174‐5. PMCID: PMC3072551Bimodal patterns of expression have recently been shown to be useful not only in prioritizinggenes that distinguish phenotypes, but also in prioritizing network models that correlate withproteomic evidence. In particular, subgroups of strongly coexpressed gene pairs result in anincreased variance of the correlation distribution. This variance, a measure of associationbetween sets of genes (or proteins), can be summarized as the bimodality of coexpression (BiC).We developed an online tool to calculate the BiC for user‐defined gene lists and associatedmRNA expression data. BiC is a comprehensive application that provides researchers with theability to analyze both publicly available and user‐collected array data. AVAILABILITY: The freelyavailable web service and the documentation can be accessed athttp://gurkan.case.edu/software. CONTACT: gurkan@case.edu.Figure: Workflow of BiC is depicted.(A) mRNA gene expression data andgene lists are uploaded. (B) The usermay filter the uploaded samples byutilizing sample annotations. (C) Next,case and control samples areselected. (D) BiC processes the jobwhile providing console output. Atthis stage, the user can leave thewebsite or monitor the progress. (E)The BiC web interface providesbimodality of coexpression valuesand corresponding P‐values,indicating significant associationswith the target gene list. The resultsare also emailed to the user.46

A proteomic study of myosin II motor proteins during tumor cell migrationBetapudi V, Gokulrangan G, Chance MR, Egelhoff TT.J. Mol. Biol. 2011;407(5):673‐86. PMCID: PMC3072708Myosin II motor proteins play important roles in cell migration. Although myosin II filamentassembly plays a key role in the stabilization of focal contacts at the leading edge of migratingcells, the mechanisms and signaling pathways regulating the localized assembly of lamellipodialmyosin II filaments are poorly understood. We performed a proteomic analysis of myosin heavychain (MHC) phosphorylation sites in MDA‐MB 231 breast cancer cells to identify MHCphosphorylation sites that are activated during integrin engagement and lamellar extension onfibronectin. Fibronectin‐activated MHC phosphorylation was identified on novel and previouslyrecognized consensus sites for phosphorylation by protein kinase C and casein kinase II (CK‐II).S1943, a CK‐II consensus site, was highly phosphorylated in response to matrix engagement, andphosphoantibody staining revealed phosphorylation on myosin II assembled into leading‐edgelamellae. Surprisingly, neither pharmacological reduction nor small inhibitory RNA reduction inCK‐II activity reduced this stimulated S1943 phosphorylation. Our data demonstrate that S1943phosphorylation is upregulated during lamellar protrusion, and that CK‐II does not appear to bethe kinase responsible for this matrix‐induced phosphorylation event.Myosin IIA S1943 phosphorylationFigure: Abrogation of Ser‐1943phosphorylation, confirmed by CIDMS/MS spectral data as shown in thetop panel, on myosin IIA impairslocalization to the leading edge duringcell spreading. COS‐7 cells transientlyexpressing GFP‐MHC IIA constructwere allowed to spread onfibronectin for 60 min, thenprocessed for imaging.Immunostaining using S1943‐specificantibody shows concomitant leadingcell localization of Myosin IIA in theleft panel whereas dephosphorylationconfirms the role of myosin IIA for cellspreading in the right panel.47

EROS: Better than SAXS!Yang, S; Roux, BStructure. 2011;19(1):3‐4.Revealing the three‐dimensional organization of large dynamic protein complexes in solution ischallenging. To tackle this problem, Różycki and colleagues (2011) design a method combiningsmall angle X‐ray scattering (SAXS) data with the results of computer simulations. Their studyoffers new insights into the conformational transition induced by salt that occurs in anendosome‐associated ESCRT‐III CHMP3 domain.Figure: Schematic Representation of a Salt‐Induced Conformational Transition Revealed by usingSAXS Data. (A) At low salt concentration, CHMP3 adapts a compact and closed conformationwhere helix 5 (in red) is bound to the core (helices 1‐4, in blue). (B) at high salt concentration,crowed salt molecules shield electrostatic interactions between helix 5 and the core, whichpermits the detachment of helix 5 from the core, and thus CHMP3 adapts an extended and openconformation. (C) The distinction between CHMP3 compact and extended conformations isnicely caught by scattering differences in two schematic SAXS profiles (compact marked by solidlines, and extended by dashed lines).48

Systems biology analyses of gene expression and genome wide association study data inobstructive sleep apneaLiu, Y., Patel, S., Nibbe, R., Maxwell, S., Chowdhury, S.A., Koyutürk, M., Zhu, X., Larkin, E.K.,Buxbaum, S.G., Punjabi, N.M., Gharib, S.A., Redline, S., Chance, M.R. Pacific Symposium onBiocomputing 14‐25, 2011.The precise molecular etiology of obstructive sleep apnea (OSA) is unknown; however recentresearch indicates that several interconnected aberrant pathways and molecular abnormalitiesare contributors to OSA. Identifying the genes and pathways associated with OSA can help toexpand our understanding of the risk factors for the disease as well as provide new avenues forpotential treatment. Towards these goals, we have integrated relevant high dimensional datafrom various sources, such as genome‐wide expression data (microarray), protein‐proteininteraction (PPI) data and results from genome‐wide association studies (GWAS) in order todefine sub‐network elements that connect some of the known pathways related to the diseaseas well as define novel regulatory modules related to OSA. Two distinct approaches are appliedto identify sub‐networks significantly associated with OSA. In the first case we used a biasedapproach based on sixty genes/proteins with known associations with sleep disorders and/ormetabolic disease to seed a search using commercial software to discover networks associatedwith disease followed by information theoretic (mutual information) scoring of the subnetworks.In the second case we used an unbiased approach and generated an interactomeconstructed from publicly available gene expression profiles and PPI databases, followed byscoring of the network with p‐values from GWAS data derived from OSA patients to uncoversub‐networks significant for the disease phenotype. A comparison of the approaches reveals anumber of proteins that have been previously known to be associated with OSA or sleep. Inaddition, our results indicate a novel association of Phosphoinositide 3‐kinase, the STAT familyof proteins and its related pathways with OSA.Figure: Network identified byjactivemodule using p‐values fromGWAS study, color represents thep‐values and nodes with grey colorindicate that the p‐values aremissing from GWAS.49

Reversible methylation of promoter‐bound STAT3 by histone‐modifying enzymesYang, J. , Huang, J. , Dasgupta, M. , Sears, N. , Miyagi, M. , Wang, B. , Chance, M.R. , Chen, X. , Du,Y., Wang, Y., An, L. ,Wang, Q. ,Lu, T. ,Zhang, X. , Wang, Z., Stark, G.R.Proc. Natl. Acad. Sci. USA. 2010;107(50):21499‐504. PMCID: PMC3003019Following its tyrosine phosphorylation, STAT3 is methylated on K140 by the histone methyltransferase SET9 and demethylated by LSD1 when it is bound to a subset of the promoters thatit activates. Methylation of K140 is a negative regulatory event, because its blockade greatlyincreases the steady‐state amount of activated STAT3 and the expression of many (i.e., SOCS3)but not all (i.e., CD14) STAT3 target genes. Biological relevance is shown by the observation thatoverexpression of SOCS3 when K140 cannot be methylated blocks the ability of cells to activateSTAT3 in response to IL‐6. K140 methylation does not occur with mutants of STAT3 that do notenter nuclei or bind to DNA. Following treatment with IL‐6, events at the SOCS3 promoter occurin an ordered sequence, as shown by chromatin immunoprecipitations. Y705‐phosphoryl‐STAT3binds first and S727 is then phosphorylated, followed by the coincident binding of SET9 anddimethylation of K140, and lastly by the binding of LSD1. We conclude that the lysinemethylation of promoter‐bound STAT3 leads to biologically important down‐regulation of thedependent responses and that SET9, which is known to help provide an activating methylationmark to H3K4, is recruited to the newly activated SOCS3 promoter by STAT3.Figure: Nuclear import and DNAbinding are required for IL‐6.inducedS727 phosphorylation and K140dimethylation of STAT3. (C) A4 cellsexpressing wild‐type STAT3 weregrown on coverslips to 20 to 30%confluence, then treated with IL‐6 for4 h, followed by staining with primaryantibodies directed against STAT3,S727‐phosphoryl‐STAT3 and STAT3‐K140me2. Following staining with DAPI(blue nuclear stain) and fluorescentsecondary antibodies against STAT3(green), S727‐phosphoryl‐STAT3 (red)or STAT3‐K140me2 (red), the cellswere examined by confocalmicroscopy. The yellow/pink pixels inthe composite image demonstrate theclose association of the two proteins.50

Circulating human CD4 and CD8 T cells do not have large intracellular pools of CCR5Pilch‐Cooper HA, Sieg SF, Hope TJ, Koons A, Escola JM, Offord R, Veazey RS, Mosier DE, ClagettB, Medvik K, Jadlowsky JK, Chance MR, Kiselar JG, Hoxie JA, Collman RG, Riddick NE, Mercanti V,Hartley O, Lederman MM.Blood. 2011;118(4):1015‐9.CC Chemokine Receptor 5 (CCR5) is an important mediator of chemotaxis and the primarycoreceptor for HIV‐1. A recent report by other researchers suggested that primary T cells harborpools of intracellular CCR5. With the use of a series of complementary techniques to measureCCR5 expression (antibody labeling, Western blot, quantitative reverse transcription polymerasechain reaction), we established that intracellular pools of CCR5 do not exist and that the resultsobtained by the other researchers were false‐positives that arose because of the generation ofirrelevant binding sites for anti‐CCR5 antibodies during fixation and permeabilization of cells.51Figure: High levels of intracellular stainingfor CCR5 by flow cytometery in fixed,permeabilized T cells and GHOST cells thatdo not express CCR5. (A) Representativehistograms of CCR5 staining on fresh andfixed/permeabilized CD4_ and CD8_ T cellsfrom whole PBMCs. Fresh orfixed/permeabilized cells were initially gatedon forward and side scatter. Cellsfalling into the lymphocyte gate were furthergated on being positive for CD3. CD3_ cellswere further divided into CD4_ and CD8_ Tcells. Histograms reflect CCR5staining on CD4_ T cells (purple) and CD8_ Tcells (blue) that were either stained unfixedor fixed and permeabilized before staining.CCR5 staining is shown on the x‐axis andcount on the y‐axis. Histogram gates wereset with the appropriate fluorochromelinkedisotype control antibody so that _ 2%of the population was positive for isotype.(B) Representative histograms of CCR5staining on fresh and fixed/permeabilizedGHOST (3) parental and GHOST (3) Hi‐5(CCR5‐transfected) cells. Cells were initiallygated on forward versus side scatter.Histograms reflect CCR5 staining on the totalcell populations gated on forward and sidescatter (purple). CCR5 staining is shown onthe x‐axis and count on the y‐axis. FSCindicates forward scatter; SSC, side scatter;PE‐Cy7, phycoerythrin–indocyanine 7; andAPC, allophycocyanin

Regulation of NF‐kappaB by NSD1/FBXL11‐dependent reversible lysine methylation of p65Lu T, Jackson MW, Wang B, Yang M, Chance MR, Miyagi M, Gudkov AV, Stark GR.Proc. Natl. Acad. Sci. USA. 2010;107(1):46‐51. PMID: 20080798NF‐kappaB, a central coordinator of immune and inflammatory responses, must be tightlyregulated. We describe a NF‐kappaB regulatory pathway that is driven by reversible lysinemethylation of the p65 subunit, carried out by a lysine methylase, the nuclear receptor‐bindingSET domain‐containing protein 1 (NSD1), and a lysine demethylase, F‐box and leucine‐richrepeat protein 11 (FBXL11). Overexpression of FBXL11 inhibits NF‐kappaB activity, and a highlevel of NSD1 activates NF‐kappaB and reverses the inhibitory effect of FBXL11, whereasreduced expression of NSD1 decreases NF‐kappaB activation. The targets are K218 and K221 ofp65, which are methylated in cells with activated NF‐kappaB. Overexpression of FBXL11 slowedthe growth of HT29 cancer cells, whereas shRNA‐mediated knockdown had the opposite effect,and these phenotypes were dependent on K218/K221 methylation. In mouse embryofibroblasts, the activation of most p65‐dependent genes relied on K218/K221 methylation.Importantly, expression of the FBXL11 gene is driven by NF‐kappaB, revealing a negativeregulatory feedback loop. We conclude that reversible lysine methylation of NF‐kappaB is animportant element in the complex regulation of this key transcription factor.Figure: Mass spectrometry (MS) shows that p65 ismethylated on K218 and K221 on NF‐κBactivation. (A) GelCode blue‐stained gel, showingthat p65 is immunoprecipitated as a single strongband. The same samples were loaded intomultiple lanes. (B) Analysis of tryptic peptidesderived from p65 suggests that K218 ismonomethylated. The pure single band wasdigested in the gel and samples were analyzed byLC‐MS/MS. A mass shift of +14 was observedspanning peptide 202–218. Tandem MS analysisfurther suggested that K218 on the C‐terminalside of the peptide is modified. Another +14 massshift was also observed on the N‐terminal side,suggesting an additional methylationwithin the N‐terminal four residues. (C) Analysis oftryptic peptides derived from p65 suggests thatK221 of p65 is dimethylated. A mass shift of+28 was observed spanning peptide 219–236.Tandem MS analysis further suggested that K221on the N‐terminal is dimethylated.52

Crystal structure of native RPE65, the retinoid isomerase of the visual cycleKiser PD, Golczak M, Lodowski DT, Chance MR, Palczewski K.Proc. Natl. Acad. Sci. USA. 2009;106(41):17325‐30. PMCID: PMC2765077Vertebrate vision is maintained by the retinoid (visual) cycle, a complex enzymatic pathway thatoperates in the retina to regenerate the visual chromophore, 11‐cis‐retinal. A key enzyme in thispathway is the microsomal membrane protein RPE65. This enzyme catalyzes the conversion ofall‐trans‐retinyl esters to 11‐cis‐retinol in the retinal pigment epithelium (RPE). Mutations inRPE65 are known to be responsible for a subset of cases of the most common form of childhoodblindness, Leber congenital amaurosis (LCA). Although retinoid isomerase activity has beenattributed to RPE65, its catalytic mechanism remains a matter of debate. Also, the manner inwhich RPE65 binds to membranes and extracts retinoid substrates is unclear. To gain insight intothese questions, we determined the crystal structure of native bovine RPE65 at 2.14‐Aresolution. The structural, biophysical, and biochemical data presented here provide theframework needed for an in‐depth understanding of the mechanism of catalytic isomerizationand membrane association, in addition to the role mutations that cause LCA have in disruptingprotein function.Figure: The RPE65 iron ion‐binding site and residual electron density found in the active site cavity. (A)Stereoview of the iron cofactor and its ligands. The iron ion is shown as an orange sphere and thesecond shell water molecule is shown as a red sphere. The geometry of iron ion coordination isapproximately octahedral. The second shell Glu residues most likely help to stabilize this geometry.The side chain of Val134 is 4.9Åaway from the iron ion. Numbers indicate bond distances inangstroms. (B) Stereoview of the residual electron density found in the RPE65 active site. The greenmesh represents an unbiased, _ A‐weighted Fo _ Fc electron density map contoured at 3.5 _. Theappearance of the electron density next to the iron ion is highly suggestive of a bound fatty acidmolecule which has been modeled. The lack of features in the second region of electron densityprecludes molecular assignment. Numbers next to dashed lines indicate bond distances in angstroms.53