Engineered nanoparticles enable deep proteomics studies at scale by leveraging tunable nano-bio interactions

被引:52
作者
Ferdosi, Shadi [1 ]
Tangeysh, Behzad [1 ]
Brown, Tristan R. [1 ]
Everley, Patrick A. [1 ]
Figa, Michael [1 ]
McLean, Matthew [1 ]
Elgierari, Eltaher M. [1 ]
Zhao, Xiaoyan [1 ]
Garcia, Veder J. [1 ]
Wang, Tianyu [1 ]
Chang, Matthew E. K. [2 ]
Riedesel, Kateryna [1 ]
Chu, Jessica [1 ]
Mahoney, Max [1 ]
Xia, Hongwei [1 ]
O'Brien, Evan S. [1 ]
Stolarczyk, Craig [1 ]
Harris, Damian [1 ]
Platt, Theodore L. [1 ]
Ma, Philip [1 ]
Goldberg, Martin [1 ]
Langer, Robert [3 ]
Flory, Mark R. [2 ]
Benz, Ryan [1 ]
Tao, Wei [4 ,5 ]
Cuevas, Juan Cruz [1 ]
Batzoglou, Serafim [1 ]
Blume, John E. [1 ]
Siddiqui, Asim [1 ]
Hornburg, Daniel [1 ]
Farokhzad, Omid C. [1 ,4 ,5 ]
机构
[1] Seer Inc, Redwood City, CA 94065 USA
[2] Oregon Hlth & Amp Sci Univ, Cedar Ctr, Knight Canc Inst, Portland, OR 97239 USA
[3] MIT, David H Koch Inst Integrat Canc Res, Cambridge, MA 02139 USA
[4] Harvard Med Sch, Ctr Nanomed, Brigham & Womens Hosp, Boston, MA 02115 USA
[5] Harvard Med Sch, Brigham & Womens Hosp, Dept Anesthesiol, Boston, MA 02115 USA
关键词
proteomics; nano-bio interaction; nanoparticle; mass spectrometry; machine learning; BIOMARKER DISCOVERY; PLASMA PROTEOME; PROTEINS; IDENTIFICATION; WORKFLOW; CANCER; CORONA;
D O I
10.1073/pnas.2106053119
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Deep interrogation of plasma proteins on a large scale is a challenge due to the number and concentration of proteins, which span a dynamic range of over 10 orders of magnitude. Current plasma proteomics workflows employ labor-intensive protocols combining abundant protein depletion and sample fractionation. We previously demonstrated the superiority of multinanoparticle (multi-NP) coronas for interrogating the plasma proteome in terms of proteome depth compared to simple workflows. Here we show the superior depth and precision of a multi-NP workflow compared to conventional deep workflows evaluating multiple gradients and search engines as well as data-dependent and data-independent acquisition. We link the physicochemical properties and surface functionalization of NPs to their differential protein selectivity, a key feature in NP panel profiling performance. We find that individual proteins and protein classes are differentially attracted by specific surface properties, opening avenues to design multi-NP panels for deep interrogation of complex biological samples.
引用
收藏
页数:11
相关论文
共 46 条
[1]   Plasma Proteome Profiling Reveals Dynamics of Inflammatory and Lipid Homeostasis Markers after Roux-En-Y Gastric Bypass Surgery [J].
Albrechtsen, Nicolai J. Wewer ;
Geyer, Philipp E. ;
Doll, Sophia ;
Treit, Peter V. ;
Bojsen-Moller, Kirstine N. ;
Martinussen, Christoffer ;
Jorgensen, Nils B. ;
Torekov, Signe S. ;
Meier, Florian ;
Niu, Lili ;
Santos, Alberto ;
Keilhauer, Eva C. ;
Holst, Jens J. ;
Madsbad, Sten ;
Mann, Matthias .
CELL SYSTEMS, 2018, 7 (06) :601-+
[2]   The Clinical Plasma Proteome: A Survey of Clinical Assays for Proteins in Plasma and Serum [J].
Anderson, N. Leigh .
CLINICAL CHEMISTRY, 2010, 56 (02) :177-185
[3]  
[Anonymous], 2020, R LANG ENV STAT COMP
[4]   Machine learning predicts the functional composition of the protein corona and the cellular recognition of nanoparticles [J].
Ban, Zhan ;
Yuan, Peng ;
Yu, Fubo ;
Peng, Ting ;
Zhou, Qixing ;
Hu, Xiangang .
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2020, 117 (19) :10492-10499
[5]   Mechanistic understanding of in vivo protein corona formation on polymeric nanoparticles and impact on pharmacokinetics [J].
Bertrand, Nicolas ;
Grenier, Philippe ;
Mahmoudi, Morteza ;
Lima, Eliana M. ;
Appel, Eric A. ;
Dormont, Flavio ;
Lim, Jong-Min ;
Karnik, Rohit ;
Langer, Robert ;
Farokhzad, Omid C. .
NATURE COMMUNICATIONS, 2017, 8
[6]  
Biognosys, 2020, SPECTR US MAN
[7]   Rapid, deep and precise profiling of the plasma proteome with multi-nanoparticle protein corona [J].
Blume, John E. ;
Manning, William C. ;
Troiano, Gregory ;
Hornburg, Daniel ;
Figa, Michael ;
Hesterberg, Lyndal ;
Platt, Theodore L. ;
Zhao, Xiaoyan ;
Cuaresma, Rea A. ;
Everley, Patrick A. ;
Ko, Marwin ;
Liou, Hope ;
Mahoney, Max ;
Ferdosi, Shadi ;
Elgierari, Eltaher M. ;
Stolarczyk, Craig ;
Tangeysh, Behzad ;
Xia, Hongwei ;
Benz, Ryan ;
Siddiqui, Asim ;
Carr, Steven A. ;
Ma, Philip ;
Langer, Robert ;
Farias, Vivek ;
Farokhzad, Omid C. .
NATURE COMMUNICATIONS, 2020, 11 (01)
[8]   Biological recognition of graphene nanoflakes [J].
Castagnola, V. ;
Zhao, W. ;
Boselli, L. ;
Lo Giudice, M. C. ;
Meder, F. ;
Polo, E. ;
Paton, K. R. ;
Backes, C. ;
Coleman, J. N. ;
Dawson, K. A. .
NATURE COMMUNICATIONS, 2018, 9
[9]   Detailed identification of plasma proteins adsorbed on copolymer nanoparticles [J].
Cedervall, Tommy ;
Lynch, Iseult ;
Foy, Martina ;
Berggard, Tord ;
Donnelly, Seamas C. ;
Cagney, Gerard ;
Linse, Sara ;
Dawson, Kenneth A. .
ANGEWANDTE CHEMIE-INTERNATIONAL EDITION, 2007, 46 (30) :5754-5756
[10]   1D and 2D annotation enrichment: a statistical method integrating quantitative proteomics with complementary high-throughput data [J].
Cox, Juergen ;
Mann, Matthias .
BMC BIOINFORMATICS, 2012, 13 :S12