Literature DB >> 18412540

Development of affinity columns for the removal of high-abundance proteins in cerebrospinal fluid.

Margareta Ramström1, Aida Zuberovic, Caroline Grönwall, Jörg Hanrieder, Jonas Bergquist, Sophia Hober.   

Abstract

Various approaches for removal of high-abundance components in body fluids are currently available. While most methods are constructed for plasma depletion, there is a need for body-fluid-specific strategies. The aim of the present study was to design an affinity matrix suitable for the depletion of high-abundance proteins in CSF (cerebrospinal fluid). Hence, molecules with specific affinity towards proteins present at high concentration in CSF were desired. Affibody molecules are specific binders of small size that have shown high stability under various conditions and are therefore good candidates for such a matrix. The protein composition in CSF resembles that in plasma. However, 20% of the proteins are brain-derived and are therefore present in higher proportions in CSF than in plasma, whereas larger plasma-derived proteins are less abundant in CSF. Therefore five high-abundance CSF proteins were chosen for the design of a CSF-specific depletion setup. Affibody molecules with specificity towards HSA (human serum albumin), IgG, transferrin and transthyretin were combined in an affinity column. In addition, polyclonal antibodies against cystatin C were coupled to chromatographic beads and packed in a separate column. Highly reproducible and efficient removal of the five target proteins was observed. The proportion of depleted proteins were estimated to be 99, 95, 74, 92 and 83% for HSA, IgG, transferrin, transthyretin and cystatin C respectively. SDS/PAGE analysis was used for monitoring and identifying proteins in native CSF, depleted CSF samples and the captured fractions. Moreover, shotgun proteomics was used for protein identification in native as well as depleted CSF and the achieved data were compared. Enhanced identification of lower-abundance components was observed in the depleted fraction, in terms of more detected peptides per protein.

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Year:  2009        PMID: 18412540     DOI: 10.1042/BA20080015

Source DB:  PubMed          Journal:  Biotechnol Appl Biochem        ISSN: 0885-4513            Impact factor:   2.431


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  9 in total

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