BACKGROUND: Laboratory technologies have highlighted the progressive accumulation of the so-called "storage lesion," a wide series of alterations to stored red blood cells (RBCs) that may affect the safety and effectiveness of the transfusion therapy. New improvements in the field are awaited to ameliorate this lesion, such as the introduction of washing technologies in the cell processing pipeline. Laboratory studies that have tested such technologies so far rely on observational qualitative or semiquantitative techniques. STUDY DESIGN AND METHODS: A state-of-the-art quantitative proteomics approach utilizing quantitative concatamers (QconCAT) was used to simultaneously monitor fluctuations in the abundance of 114 proteins in AS-3 RBC supernatants (n = 5; 11 time points, including before and after leukoreduction, at 3 hours, on Days 1 and 2, and weekly sampling from Day 7 through Day 42). RESULTS: Leukoreduction-dependent depletion of plasma proteins was observed at the earliest time points. A subset of proteins showed very high linear correlation (r(2) > 0.9) not only with storage time, but also with absolute levels of hemoglobin α1 and β, a proxy for RBC hemolysis and vesiculation. Linear regression was performed to describe the temporal relationship between these proteins. Our findings suggest a role for supernatant glyceraldehyde-3-phosphate dehydrogenase; peroxiredoxin-1, -2, and -6; carbonic anhydrase-1 and -2; selenium binding protein-1; biliverdin reductase; aminolevulinate dehydratase; and catalase as potential biomarkers of RBC quality during storage. CONCLUSION: A targeted proteomics technology revealed novel biomarkers of the RBC storage lesion and promises to become a key analytical readout for the development and testing of alternative cell processing strategies.
BACKGROUND: Laboratory technologies have highlighted the progressive accumulation of the so-called "storage lesion," a wide series of alterations to stored red blood cells (RBCs) that may affect the safety and effectiveness of the transfusion therapy. New improvements in the field are awaited to ameliorate this lesion, such as the introduction of washing technologies in the cell processing pipeline. Laboratory studies that have tested such technologies so far rely on observational qualitative or semiquantitative techniques. STUDY DESIGN AND METHODS: A state-of-the-art quantitative proteomics approach utilizing quantitative concatamers (QconCAT) was used to simultaneously monitor fluctuations in the abundance of 114 proteins in AS-3 RBC supernatants (n = 5; 11 time points, including before and after leukoreduction, at 3 hours, on Days 1 and 2, and weekly sampling from Day 7 through Day 42). RESULTS: Leukoreduction-dependent depletion of plasma proteins was observed at the earliest time points. A subset of proteins showed very high linear correlation (r(2) > 0.9) not only with storage time, but also with absolute levels of hemoglobin α1 and β, a proxy for RBC hemolysis and vesiculation. Linear regression was performed to describe the temporal relationship between these proteins. Our findings suggest a role for supernatant glyceraldehyde-3-phosphate dehydrogenase; peroxiredoxin-1, -2, and -6; carbonic anhydrase-1 and -2; selenium binding protein-1; biliverdin reductase; aminolevulinate dehydratase; and catalase as potential biomarkers of RBC quality during storage. CONCLUSION: A targeted proteomics technology revealed novel biomarkers of the RBC storage lesion and promises to become a key analytical readout for the development and testing of alternative cell processing strategies.
Authors: Erica M Pasini; Morten Kirkegaard; Peter Mortensen; Hans U Lutz; Alan W Thomas; Matthias Mann Journal: Blood Date: 2006-08-01 Impact factor: 22.113
Authors: Angelo D'Alessandro; Travis Nemkov; Marguerite Kelher; F Bernadette West; Rani K Schwindt; Anirban Banerjee; Ernest E Moore; Christopher C Silliman; Kirk C Hansen Journal: Transfusion Date: 2014-12-30 Impact factor: 3.157
Authors: Stine L Bislev; Ulrike Kusebauch; Marius C Codrea; Robert J Beynon; Victoria M Harman; Christine M Røntved; Ruedi Aebersold; Robert L Moritz; Emøke Bendixen Journal: J Proteome Res Date: 2012-02-08 Impact factor: 4.466
Authors: Christopher C Silliman; Marguerite R Kelher; Samina Y Khan; Monica LaSarre; F Bernadette West; Kevin J Land; Barbara Mish; Linda Ceriano; Samuel Sowemimo-Coker Journal: Blood Date: 2014-04-18 Impact factor: 22.113
Authors: Steven L Spitalnik; Darrell Triulzi; Dana V Devine; Walter H Dzik; Anne F Eder; Terry Gernsheimer; Cassandra D Josephson; Daryl J Kor; Naomi L C Luban; Nareg H Roubinian; Traci Mondoro; Lisbeth A Welniak; Shimian Zou; Simone Glynn Journal: Transfusion Date: 2015-08-10 Impact factor: 3.157
Authors: Anastasios G Kriebardis; Marianna H Antonelou; Konstantinos E Stamoulis; Effrosini Economou-Petersen; Lukas H Margaritis; Issidora S Papassideri Journal: J Cell Mol Med Date: 2007 Jan-Feb Impact factor: 5.310
Authors: Benjamin R Huebner; Ernest E Moore; Hunter B Moore; Angela Sauaia; Gregory Stettler; Monika Dzieciatkowska; Kirk Hansen; Anirban Banerjee; Christopher C Silliman Journal: Transfusion Date: 2017-05-12 Impact factor: 3.157
Authors: María García-Roa; María Del Carmen Vicente-Ayuso; Alejandro M Bobes; Alexandra C Pedraza; Ataúlfo González-Fernández; María Paz Martín; Isabel Sáez; Jerard Seghatchian; Laura Gutiérrez Journal: Blood Transfus Date: 2017-05 Impact factor: 3.443
Authors: Anirban Banerjee; Christopher C Silliman; Ernest E Moore; Monika Dzieciatkowska; Marguerite Kelher; Angela Sauaia; Kenneth Jones; Michael P Chapman; Eduardo Gonzalez; Hunter B Moore; Angelo D'Alessandro; Erik Peltz; Benjamin E Huebner; Peter Einerson; James Chandler; Arsen Ghasabayan; Kirk Hansen Journal: J Trauma Acute Care Surg Date: 2018-06 Impact factor: 3.313