Poster Session A (Molecular & cellular proteomics, 2017)
A.1PPKs mediate direct signal transfer from phytochrome photoreceptors to transcription factor PIF3Weimin Ni1, Shou-Ling Xu2, Eduardo González-Grandáío1, Robert J. Chalkley3, Andreas F. R. Huhmer4, A. L. Burlingame3, Zhi-Yong Wang2, Peter H. Quail11University of California, Berkeley, CA, USA; 2Carnegie Institution, Stanford, CA, USA; 3University of California, San Francisco, CA, USA; 4Thermo Scientific, San Jose, CA, USAUpon light-induced nuclear translocation, phytochrome (phy) sensory photoreceptors interact with, and induce rapid phosphorylation and consequent ubiquitin-mediated degradation of, transcription factors, called PIFs, thereby regulating target gene expression and plant development. Nevertheless, the biochemical mechanism of phy-induced PIF phosphorylation has remained ill-defined. Here we identify a family of nuclear protein kinases, designated Photoregulatory Protein Kinases (PPK1-4; formerly called MUT9-Like Kinases (MLKs)), that interact with PIF3 and phyB in a light-induced manner in vivo. Genetic analyses demonstrate that the PPKs are collectively necessary for the normal light-induced phosphorylation and degradation of PIF3. PPK1 directly phosphorylates PIF3 in vitro, with a phosphosite pattern that strongly mimics the light-induced pattern in vivo. These data establish that the PPKs are directly involved in catalyzing the photoactivated-phy-induced phosphorylation of PIF3 in vivo, and thereby are critical components of a transcriptionally-centered signaling hub that pleiotropically regulates plant growth and development in response to multiple signaling pathways.This work was supported by NIH (2R01 GM-047475), DOE (DEFG03-87ER13742), and USDA ARS Current Research Information System (5335-21000-032-00D) to P.H.Q.; by NIH (5R01GM066258) and DOE (DEFG02-08ER15973) to Z.Y.W.; and by NIH (8P41GM103481) to A.L.B.A.2Mass Spectrometry-based Proteomics of Human Breast Milk to Identify Potential Breast Cancer BiomarkersRoshanak Aslebagh1, Devika Channaveerappa1, Kathleen F. Arcaro2, Costel C. Darie11Clarkson University, Potsdam, NY, USA; 2University of Massachusetts, Amherst, MA, USAEarly detection of breast cancer, as the second common cancer and second leading cause of cancer death in American women, has been a challenging subject of study especially in young women. Mammography is not effective on the dense breast tissue of young women, and they also face a transient increased risk of pregnancy-associated breast cancer. Investigation of biomarkers in different types of bodily fluids has been a potential tool for early detection of cancers. In this study, we applied mass spectrometry- based proteomics on human breast milk as an appropriate cancer microenvironment for identification of potential protein biomarkers of breast cancer. Intact human breast milk samples from breast cancer suffering mothers and matched controls were subjected to one dimensional and two dimensional polyacrylamide gel electrophoresis (2D-PAGE), quantified, and the protein spots were cut and digested with trypsin. The peptides were extracted and zip-tipped followed by nanoliquod chromatography-tandem mass spectrometry (nanoLC-MS/MS) analysis using a nanoAcquity UPLC coupled with a Q-TOF Ultima Mass spectrometer. Data base search was done by Mascot Daemon (version 2.5.1.) software and the results were analyzed by Scaffold Proteome (version 4.2.1) software. Protein alterations (upregulation and downregulation in protein expression) in breast milk samples were identified and are under further investigation and considered as potential breast cancer biomarkers.Acknowledgement: The authors would like to thank all the participants for generously donating their breast milk and participating in this study.A.3Profiling Biochemical Individuality: Human Personal Omics Profiling (hPOP)Sara Ahadi, Hannes Rost, Liang Liang, Mike SnyderStanford University, Stanford, CA, USARecent advances in high throughput technologies allow profiling of thousands of analytes within a single experiment. These measurements could potentially be used to diagnose disease early, monitor treatment progression and stratify patient groups to ensure each individual obtains the treatment best suited to their needs. This personalized approach to medicine would include continuous monitoring of thousands of parameters over a whole lifetime. However, in order to be able to interpret such data, we need to have a better understanding of the underlying natural variation of biological molecules in large crowds. If we know the natural ranges of individual analytes, the expected responses to perturbations and the long-term trends in their levels, we can draw meaningful conclusions from comprehensive personalized profiling. Tryptic peptides of plasma samples were separated on a NanoLC™ 425 System (SCIEX). 5ul/Min flow was used with trap-elute setting using a 0.5 x 10 mm ChromXP™ (SCIEX). LC gradient was set to a 43-minute gradient from 4–32% B with 1 hour total run. Mobile phase A was 100% water with 0.1% formic acid. Mobile phase B was 100% acetonitrile with 0.1% formic acid. 8ug load of undepleted plasma on 15cm ChromXP column. MS analysis were performed using SWATH® Acquisition on a TripleTOF® 6600 System equipped with a DuoSpray™ Source and 25μm I.D. electrode (SCIEX). Variable Q1 window SWATH Acquisition methods (100 windows) were built in high sensitivity MS/MS mode with Analyst® TF Software 1.7. We were able to successfully run a pilot study on human Personal Omics Profiling (hPOP) in March 2016 during US HUPO conference in Boston and then launched the study at 2016 HUPO overall about 150 individuals participated in the study so far and their urine, stool and blood samples have been collected. Our preliminary data on plasma proteins quantified suggests large amount of variance in the data and there is variance we currently cannot explain. With little technical variance, individual variance is large in certain proteins. Using our current SWATH-MS, we used 8ug of undepleted plasma for one hour LC/MS run. In total 530 proteins with 1%FDR in peptide level were quantified over 31 subjects. Over 80% of all proteins showed less than 10% CV in SWATH data on hPOP pilot plasma samples whereas when we add technical and biological variance, the 80% of all proteins have over 50% variance. Overall there is 46.5% biological variance which includes the unknown genetic components and unknown environmental components and then there is the 21% of the variance (on average) that we can explain with variables such as age, sex, BMI and ethnicity. We expect these studies to reveal novel, multi-analyte signatures from the blood that are associated with aging and we hope to discover additional markers that are different in ethnic groups. The data to be generated here represent an unprecedented level of detail for blood-based profiling among a diverse panel of individuals and we hope that this study can propel additional multi omics work exploring factors leading to discovery of markers for aging.A.4Towards a Human Chemo-proteomic Database: Profiling Structurally Diverse Chemical Space to Map Proteome-wide InteractionsFrancisco Garcia, Kyeongmi Cheon, Huijun Wang, Andy Liaw, Vidhi Mishra, Anne Mai Wassermann, Brian Dill, Benjamin Ruprecht, An Chi, Xudong Qiao, and Ivan Cornella-TaracidoMerck Research Laboratories, Boston, MA, USAChemoproteomics utilizes affinity chromatography, high resolution mass spectrometry, biostatistics, and informatics for large-scale identification and quantification of proteins perturbed by chemical probes in biological samples. Chemoproteomics is used extensively to assess drug-target engagement, selectivity, biomarker discovery, target identification, and drug repurposing. Chemical biologists routinely apply chemoproteomics to characterize compound-target interactions for discrete project specific biosamples. A comprehensive and systematic evaluation of bioactive molecules against the whole human proteome however, has not been reported. We therefore aim to analyze proteome-wide interactions for hundreds of chemical probes against a selection of physiologically relevant and distinct human cell and tissue samples to generate an unprecedented first draft map of the human chemo-proteome. Herein we provide initial datasets towards this first-in-class experimental and unbiased map of the human “interactome” connecting biological samples with small molecules through the discovery of proteins that bind to them in affinity enrichment proteomic experiments. We compare various mass spectrometry workflows to enable robust protein identification and quantification while minimizing instrument time. We examine several statistical methods to maximize identification of compound-protein interacting partners. Furthermore, we discuss recent advances towards a medium throughput approach to survey a large set of structurally diverse compounds against biological matter to boost the chemical and biological space profiled at a time. These efforts to develop a unique human chemo-proteomic database, together with chemo-genomic and transcriptomic approaches, provide chemical biologists the means to prosecute novel target identification and subsequent validation studies to support relevant disease areas.A.5Development of Quantitative Mass Spectrometry Assays for Species-matched Surrogate Antibody Fragments in Ocular MatricesHilda Hernandez-Barry, Robert F. Kelley, Devin Tesar, Whitney Shatz, Laetitia Comps-Agrar, Joyce Chan, Keyang Xu, Luna Liu, Yanqiu Liu, Mauricio Maia, Kelly LoyetGenentech Inc., South San Francisco, CA, USAIntroduction: Species-matched antibody fragments (Fabs), e.g., rabbit and cynomolgus monkey Fab, have been developed for pharmacokinetic (PK) and safety assessments, investigating long-acting ocular delivery technologies without invoking an immune response to a humanized molecule in an animal model. Such anti-therapeutic antibodies confound the interpretation of assay res