Dataset Information

Time-series clustering of gene expression in irradiated and bystander fibroblasts: an application of FBPA clustering.

ABSTRACT: The radiation bystander effect is an important component of the overall biological response of tissues and organisms to ionizing radiation, but the signaling mechanisms between irradiated and non-irradiated bystander cells are not fully understood. In this study, we measured a time-series of gene expression after ?-particle irradiation and applied the Feature Based Partitioning around medoids Algorithm (FBPA), a new clustering method suitable for sparse time series, to identify signaling modules that act in concert in the response to direct irradiation and bystander signaling. We compared our results with those of an alternate clustering method, Short Time series Expression Miner (STEM).While computational evaluations of both clustering results were similar, FBPA provided more biological insight. After irradiation, gene clusters were enriched for signal transduction, cell cycle/cell death and inflammation/immunity processes; but only FBPA separated clusters by function. In bystanders, gene clusters were enriched for cell communication/motility, signal transduction and inflammation processes; but biological functions did not separate as clearly with either clustering method as they did in irradiated samples. Network analysis confirmed p53 and NF-?B transcription factor-regulated gene clusters in irradiated and bystander cells and suggested novel regulators, such as KDM5B/JARID1B (lysine (K)-specific demethylase 5B) and HDACs (histone deacetylases), which could epigenetically coordinate gene expression after irradiation.In this study, we have shown that a new time series clustering method, FBPA, can provide new leads to the mechanisms regulating the dynamic cellular response to radiation. The findings implicate epigenetic control of gene expression in addition to transcription factor networks.

SUBMITTER: Ghandhi SA

PROVIDER: S-EPMC3022823 | biostudies-literature | 2011 Jan

REPOSITORIES: biostudies-literature

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Time-series clustering of gene expression in irradiated and bystander fibroblasts: an application of FBPA clustering.

Ghandhi Shanaz A SA Sinha Anshu A Markatou Marianthi M Amundson Sally A SA

BMC genomics 20110104

<h4>Background</h4>The radiation bystander effect is an important component of the overall biological response of tissues and organisms to ionizing radiation, but the signaling mechanisms between irradiated and non-irradiated bystander cells are not fully understood. In this study, we measured a time-series of gene expression after α-particle irradiation and applied the Feature Based Partitioning around medoids Algorithm (FBPA), a new clustering method suitable for sparse time series, to identif ...[more]

PMID: 21205307

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Project description:The existence of a radiation bystander effect, in which non-irradiated cells respond to signals from irradiated cells, is now well established. It raises concerns for the interpretation of risks arising from exposure to low doses of ionizing radiation. However, the regulatory mechanisms involved in the bystander response have not been well elucidated. To provide insight into the signaling pathways responding in bystanders, we have measured global gene expression four hours after bystander and direct alpha particle exposure of primary human lung fibroblasts.Although common p53-regulated radiation response genes like CDKN1A were expressed at elevated levels in the directly exposed cultures, they showed little or no change in the bystanders. In contrast, genes regulated by NFkappaB, such as PTGS2 (cyclooxygenase-2), IL8 and BCL2A1, responded nearly identically in bystander and irradiated cells. This trend was substantiated by gene ontology and pathway analyses of the microarray data, which suggest that bystander cells mount a full NFkappaB response, but a muted or partial p53 response. In time-course analyses, quantitative real-time PCR measurements of CDKN1A showed the expected 4-hour peak of expression in irradiated but not bystander cells. In contrast, PTGS2, IL8 and BCL2A1 responded with two waves of expression in both bystander and directly irradiated cells, one peaking at half an hour and the other between four and six hours after irradiation.Two major transcriptional hubs that regulate the direct response to ionizing radiation are also implicated in regulation of the bystander response, but to dramatically different degrees. While activation of the p53 response pathway is minimal in bystander cells, the NFkappaB response is virtually identical in irradiated and bystander cells. This alteration in the balance of signaling is likely to lead to different outcomes in irradiated cells and their bystanders, perhaps leading to greater survival of bystanders and increased risk from any long-term damage they have sustained.

Project description:BACKGROUND: High throughput gene expression time-course experiments provide a perspective on biological functioning recognized as having huge value for the diagnosis, treatment, and prevention of diseases. There are however significant challenges to properly exploiting this data due to its massive scale and complexity. In particular, existing techniques are found to be ill suited to finding patterns of changing activity over a limited interval of an experiments time frame. The Time-Series Explorer (TSE) was developed to overcome this limitation by allowing users to explore their data by controlling an animated scatter-plot view. MaTSE improves and extends TSE by allowing users to visualize data with missing values, cross reference multiple conditions, highlight gene groupings, and collaborate by sharing their findings. RESULTS: MaTSE was developed using an iterative software development cycle that involved a high level of user feedback and evaluation. The resulting software combines a variety of visualization and interaction techniques which work together to allow biologists to explore their data and reveal temporal patterns of gene activity. These include a scatter-plot that can be animated to view different temporal intervals of the data, a multiple coordinated view framework to support the cross reference of multiple experimental conditions, a novel method for highlighting overlapping groups in the scatter-plot, and a pattern browser component that can be used with scatter-plot box queries to support cooperative visualization. A final evaluation demonstrated the tools effectiveness in allowing users to find unexpected temporal patterns and the benefits of functionality such as the overlay of gene groupings and the ability to store patterns. CONCLUSIONS: We have developed a new exploratory analysis tool, MaTSE, that allows users to find unexpected patterns of temporal activity in gene expression time-series data. Overall, the study acted well to demonstrate the benefits of an iterative software development life cycle and allowed us to investigate some visualization problems that are likely to be common in the field of bioinformatics. The subjects involved in the final evaluation were positive about the potential of MaTSE to help them find unexpected patterns in their data and characterized MaTSE as an exploratory tool valuable for hypothesis generation and the creation of new biological knowledge.

Dataset Information

Time-series clustering of gene expression in irradiated and bystander fibroblasts: an application of FBPA clustering.

Publications

Time-series clustering of gene expression in irradiated and bystander fibroblasts: an application of FBPA clustering.

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