Clustering and curation of electropherograms: an efficient method for analyzing large cohorts of capillary electrophoresis glycomic profiles for bioprocessing operations
The accurate assessment of antibody glycosylation during bioprocessing requires the high-throughput generation of large amounts of glycomics data. This allows bioprocess engineers to identify critical process parameters that control the glycosylation critical quality attributes. The advances made in...
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doaj-3a87638c992641a195d5dc6c94c19a482021-04-02T12:22:25ZengBeilstein-InstitutBeilstein Journal of Organic Chemistry1860-53972020-08-011612087209910.3762/bjoc.16.1761860-5397-16-176Clustering and curation of electropherograms: an efficient method for analyzing large cohorts of capillary electrophoresis glycomic profiles for bioprocessing operationsIan Walsh0Matthew S. F. Choo1Sim Lyn Chiin2Amelia Mak3Shi Jie Tay4Pauline M. Rudd5Yang Yuansheng6Andre Choo7Ho Ying Swan8Terry Nguyen-Khuong9Analytics Group, Bioprocessing Technology Institute - Agency for Science Technology and Research. Singapore 138668Analytics Group, Bioprocessing Technology Institute - Agency for Science Technology and Research. Singapore 138668Analytics Group, Bioprocessing Technology Institute - Agency for Science Technology and Research. Singapore 138668Analytics Group, Bioprocessing Technology Institute - Agency for Science Technology and Research. Singapore 138668Analytics Group, Bioprocessing Technology Institute - Agency for Science Technology and Research. Singapore 138668Analytics Group, Bioprocessing Technology Institute - Agency for Science Technology and Research. Singapore 138668Animal Cell Technology Group, Bioprocessing Technology Institute, Agency for Science Technology and Research, Singapore 138668Stem Cells 1 Group, Bioprocessing Technology Institute - Agency for Science Technology and Research, Singapore 138668Department of Biomedical Engineering, Faculty of Engineering, National University of Singapore (NUS), Singapore 117575Analytics Group, Bioprocessing Technology Institute - Agency for Science Technology and Research. Singapore 138668The accurate assessment of antibody glycosylation during bioprocessing requires the high-throughput generation of large amounts of glycomics data. This allows bioprocess engineers to identify critical process parameters that control the glycosylation critical quality attributes. The advances made in protocols for capillary electrophoresis-laser-induced fluorescence (CE-LIF) measurements of antibody N-glycans have increased the potential for generating large datasets of N-glycosylation values for assessment. With large cohorts of CE-LIF data, peak picking and peak area calculations still remain a problem for fast and accurate quantitation, despite the presence of internal and external standards to reduce misalignment for the qualitative analysis. The peak picking and area calculation problems are often due to fluctuations introduced by varying process conditions resulting in heterogeneous peak shapes. Additionally, peaks with co-eluting glycans can produce peaks of a non-Gaussian nature in some process conditions and not in others. Here, we describe an approach to quantitatively and qualitatively curate large cohort CE-LIF glycomics data. For glycan identification, a previously reported method based on internal triple standards is used. For determining the glycan relative quantities our method uses a clustering algorithm to ‘divide and conquer’ highly heterogeneous electropherograms into similar groups, making it easier to define peaks manually. Open-source software is then used to determine peak areas of the manually defined peaks. We successfully applied this semi-automated method to a dataset (containing 391 glycoprofiles) of monoclonal antibody biosimilars from a bioreactor optimization study. The key advantage of this computational approach is that all runs can be analyzed simultaneously with high accuracy in glycan identification and quantitation and there is no theoretical limit to the scale of this method.https://doi.org/10.3762/bjoc.16.176capillary electrophoresisclusteringdata analysiselectropherogramglycosylationmonoclonal antibodiespeak pickingprocess development |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ian Walsh Matthew S. F. Choo Sim Lyn Chiin Amelia Mak Shi Jie Tay Pauline M. Rudd Yang Yuansheng Andre Choo Ho Ying Swan Terry Nguyen-Khuong |
spellingShingle |
Ian Walsh Matthew S. F. Choo Sim Lyn Chiin Amelia Mak Shi Jie Tay Pauline M. Rudd Yang Yuansheng Andre Choo Ho Ying Swan Terry Nguyen-Khuong Clustering and curation of electropherograms: an efficient method for analyzing large cohorts of capillary electrophoresis glycomic profiles for bioprocessing operations Beilstein Journal of Organic Chemistry capillary electrophoresis clustering data analysis electropherogram glycosylation monoclonal antibodies peak picking process development |
author_facet |
Ian Walsh Matthew S. F. Choo Sim Lyn Chiin Amelia Mak Shi Jie Tay Pauline M. Rudd Yang Yuansheng Andre Choo Ho Ying Swan Terry Nguyen-Khuong |
author_sort |
Ian Walsh |
title |
Clustering and curation of electropherograms: an efficient method for analyzing large cohorts of capillary electrophoresis glycomic profiles for bioprocessing operations |
title_short |
Clustering and curation of electropherograms: an efficient method for analyzing large cohorts of capillary electrophoresis glycomic profiles for bioprocessing operations |
title_full |
Clustering and curation of electropherograms: an efficient method for analyzing large cohorts of capillary electrophoresis glycomic profiles for bioprocessing operations |
title_fullStr |
Clustering and curation of electropherograms: an efficient method for analyzing large cohorts of capillary electrophoresis glycomic profiles for bioprocessing operations |
title_full_unstemmed |
Clustering and curation of electropherograms: an efficient method for analyzing large cohorts of capillary electrophoresis glycomic profiles for bioprocessing operations |
title_sort |
clustering and curation of electropherograms: an efficient method for analyzing large cohorts of capillary electrophoresis glycomic profiles for bioprocessing operations |
publisher |
Beilstein-Institut |
series |
Beilstein Journal of Organic Chemistry |
issn |
1860-5397 |
publishDate |
2020-08-01 |
description |
The accurate assessment of antibody glycosylation during bioprocessing requires the high-throughput generation of large amounts of glycomics data. This allows bioprocess engineers to identify critical process parameters that control the glycosylation critical quality attributes. The advances made in protocols for capillary electrophoresis-laser-induced fluorescence (CE-LIF) measurements of antibody N-glycans have increased the potential for generating large datasets of N-glycosylation values for assessment. With large cohorts of CE-LIF data, peak picking and peak area calculations still remain a problem for fast and accurate quantitation, despite the presence of internal and external standards to reduce misalignment for the qualitative analysis. The peak picking and area calculation problems are often due to fluctuations introduced by varying process conditions resulting in heterogeneous peak shapes. Additionally, peaks with co-eluting glycans can produce peaks of a non-Gaussian nature in some process conditions and not in others. Here, we describe an approach to quantitatively and qualitatively curate large cohort CE-LIF glycomics data. For glycan identification, a previously reported method based on internal triple standards is used. For determining the glycan relative quantities our method uses a clustering algorithm to ‘divide and conquer’ highly heterogeneous electropherograms into similar groups, making it easier to define peaks manually. Open-source software is then used to determine peak areas of the manually defined peaks. We successfully applied this semi-automated method to a dataset (containing 391 glycoprofiles) of monoclonal antibody biosimilars from a bioreactor optimization study. The key advantage of this computational approach is that all runs can be analyzed simultaneously with high accuracy in glycan identification and quantitation and there is no theoretical limit to the scale of this method. |
topic |
capillary electrophoresis clustering data analysis electropherogram glycosylation monoclonal antibodies peak picking process development |
url |
https://doi.org/10.3762/bjoc.16.176 |
work_keys_str_mv |
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