Dataset Information

Automated shape-based clustering of 3D immunoglobulin protein structures in chronic lymphocytic leukemia.

ABSTRACT: BACKGROUND:Although the etiology of chronic lymphocytic leukemia (CLL), the most common type of adult leukemia, is still unclear, strong evidence implicates antigen involvement in disease ontogeny and evolution. Primary and 3D structure analysis has been utilised in order to discover indications of antigenic pressure. The latter has been mostly based on the 3D models of the clonotypic B cell receptor immunoglobulin (BcR IG) amino acid sequences. Therefore, their accuracy is directly dependent on the quality of the model construction algorithms and the specific methods used to compare the ensuing models. Thus far, reliable and robust methods that can group the IG 3D models based on their structural characteristics are missing. RESULTS:Here we propose a novel method for clustering a set of proteins based on their 3D structure focusing on 3D structures of BcR IG from a large series of patients with CLL. The method combines techniques from the areas of bioinformatics, 3D object recognition and machine learning. The clustering procedure is based on the extraction of 3D descriptors, encoding various properties of the local and global geometrical structure of the proteins. The descriptors are extracted from aligned pairs of proteins. A combination of individual 3D descriptors is also used as an additional method. The comparison of the automatically generated clusters to manual annotation by experts shows an increased accuracy when using the 3D descriptors compared to plain bioinformatics-based comparison. The accuracy is increased even more when using the combination of 3D descriptors. CONCLUSIONS:The experimental results verify that the use of 3D descriptors commonly used for 3D object recognition can be effectively applied to distinguishing structural differences of proteins. The proposed approach can be applied to provide hints for the existence of structural groups in a large set of unannotated BcR IG protein files in both CLL and, by logical extension, other contexts where it is relevant to characterize BcR IG structural similarity. The method does not present any limitations in application and can be extended to other types of proteins.

SUBMITTER: Polychronidou E

PROVIDER: S-EPMC6245605 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Automated shape-based clustering of 3D immunoglobulin protein structures in chronic lymphocytic leukemia.

Polychronidou Eleftheria E Kalamaras Ilias I Agathangelidis Andreas A Sutton Lesley-Ann LA Yan Xiao-Jie XJ Bikos Vasilis V Vardi Anna A Mochament Konstantinos K Chiorazzi Nicholas N Belessi Chrysoula C Rosenquist Richard R Ghia Paolo P Stamatopoulos Kostas K Vlamos Panayiotis P Chailyan Anna A Overby Nanna N Marcatili Paolo P Hatzidimitriou Anastasia A Tzovaras Dimitrios D

BMC bioinformatics 20181120 Suppl 14

<h4>Background</h4>Although the etiology of chronic lymphocytic leukemia (CLL), the most common type of adult leukemia, is still unclear, strong evidence implicates antigen involvement in disease ontogeny and evolution. Primary and 3D structure analysis has been utilised in order to discover indications of antigenic pressure. The latter has been mostly based on the 3D models of the clonotypic B cell receptor immunoglobulin (BcR IG) amino acid sequences. Therefore, their accuracy is directly depe ...[more]

PMID: 30453883

Similar Datasets

Project description:Chronic Lymphocytic Leukemia (CLL) represents the most common leukemia in the western world and remains incurable. Leukemic cells organize and interact in the lymphoid tissues, however what actually occurs in these sites has not been fully elucidated yet. Studying primary CLL cells in vitro is very challenging due to their short survival in culture and also to the fact that traditional two-dimensional in vitro models lack cellular and spatial complexity present in vivo. Based on these considerations, we exploited for the first time three-dimensional (3D) bioprinting to advance in vitro models for CLL. This technology allowed us to print CLL cells (both primary cells and cell lines) mixed with the appropriate, deeply characterized, hydrogel to generate a scaffold containing the cells, thus avoiding the direct cell seeding onto a precast 3D scaffold and paving the way to more complex models. Using this system, we were able to efficiently 3D bioprint leukemic cells and improve their viability in vitro that could be maintained up to 28 days. We monitored over time CLL cells viability, phenotype and gene expression, thus establishing a reproducible long-term 3D culture model for leukemia. Through RNA sequencing (RNAseq) analysis, we observed a consistent difference in gene expression profile between 2D and 3D samples, indicating a different behavior of the cells in the two different culture settings. In particular, we identified pathways upregulated in 3D, at both day 7 and 14, associated with immunoglobulins production, pro-inflammatory molecules expression, activation of cytokines/chemokines and cell-cell adhesion pathways, paralleled by a decreased production of proteins involved in DNA replication and cell division, suggesting a strong adaptation of the cells in the 3D culture. Thanks to this innovative approach, we developed a new tool that may help to better mimic the physiological 3D in vivo settings of leukemic cells as well as of immune cells in broader terms. This will allow for a more reliable study of the molecular and cellular interactions occurring in normal and neoplastic conditions in vivo, and could also be exploited for clinical purposes to test individual responses to different drugs.

Dataset Information

Automated shape-based clustering of 3D immunoglobulin protein structures in chronic lymphocytic leukemia.

Publications

Automated shape-based clustering of 3D immunoglobulin protein structures in chronic lymphocytic leukemia.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets