Robust Normalization Protocols for Multiplexed Fluorescence Bioimage Analysis

Overview

Journal BioData Min

Publisher Biomed Central

Specialty Biology

Date 2016 Mar 8

PMID 26949415

Citations 7

Authors

Shan E Ahmed Raza

Daniel Langenkamper

Korsuk Sirinukunwattana

David Epstein

Tim W Nattkemper

Nasir M Rajpoot

Affiliations

Soon will be listed here.

Abstract

study of mapping and interaction of co-localized proteins at a sub-cellular level is important for understanding complex biological phenomena. One of the recent techniques to map co-localized proteins is to use the standard immuno-fluorescence microscopy in a cyclic manner (Nat Biotechnol 24:1270-8, 2006; Proc Natl Acad Sci 110:11982-7, 2013). Unfortunately, these techniques suffer from variability in intensity and positioning of signals from protein markers within a run and across different runs. Therefore, it is necessary to standardize protocols for preprocessing of the multiplexed bioimaging (MBI) data from multiple runs to a comparable scale before any further analysis can be performed on the data. In this paper, we compare various normalization protocols and propose on the basis of the obtained results, a robust normalization technique that produces consistent results on the MBI data collected from different runs using the Toponome Imaging System (TIS). Normalization results produced by the proposed method on a sample TIS data set for colorectal cancer patients were ranked favorably by two pathologists and two biologists. We show that the proposed method produces higher between class Kullback-Leibler (KL) divergence and lower within class KL divergence on a distribution of cell phenotypes from colorectal cancer and histologically normal samples.

Citing Articles

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References

Angelo M, Bendall S, Finck R, Hale M, Hitzman C, Borowsky A . Multiplexed ion beam imaging of human breast tumors. Nat Med. 2014; 20(4):436-42. PMC: 4110905. DOI: 10.1038/nm.3488. View

Gerdes M, Sevinsky C, Sood A, Adak S, Bello M, Bordwell A . Highly multiplexed single-cell analysis of formalin-fixed, paraffin-embedded cancer tissue. Proc Natl Acad Sci U S A. 2013; 110(29):11982-7. PMC: 3718135. DOI: 10.1073/pnas.1300136110. View

Friedenberger M, Bode M, Krusche A, Schubert W . Fluorescence detection of protein clusters in individual cells and tissue sections by using toponome imaging system: sample preparation and measuring procedures. Nat Protoc. 2007; 2(9):2285-94. DOI: 10.1038/nprot.2007.320. View

Stoeckli M, Chaurand P, Hallahan D, Caprioli R . Imaging mass spectrometry: a new technology for the analysis of protein expression in mammalian tissues. Nat Med. 2001; 7(4):493-6. DOI: 10.1038/86573. View

Herold J, Schubert W, Nattkemper T . Automated detection and quantification of fluorescently labeled synapses in murine brain tissue sections for high throughput applications. J Biotechnol. 2010; 149(4):299-309. DOI: 10.1016/j.jbiotec.2010.03.004. View

Bhattacharya S, Mathew G, Ruban E, Epstein D, Krusche A, Hillert R . Toponome imaging system: in situ protein network mapping in normal and cancerous colon from the same patient reveals more than five-thousand cancer specific protein clusters and their subcellular annotation by using a three symbol code. J Proteome Res. 2010; 9(12):6112-25. DOI: 10.1021/pr100157p. View

Schubert W, Bonnekoh B, Pommer A, Philipsen L, Bockelmann R, Malykh Y . Analyzing proteome topology and function by automated multidimensional fluorescence microscopy. Nat Biotechnol. 2006; 24(10):1270-8. DOI: 10.1038/nbt1250. View

Linke B, Pierre S, Coste O, Angioni C, Becker W, Maier T . Toponomics analysis of drug-induced changes in arachidonic acid-dependent signaling pathways during spinal nociceptive processing. J Proteome Res. 2009; 8(10):4851-9. DOI: 10.1021/pr900106v. View

Kolling J, Langenkamper D, Abouna S, Khan M, Nattkemper T . WHIDE--a web tool for visual data mining colocation patterns in multivariate bioimages. Bioinformatics. 2012; 28(8):1143-50. PMC: 3324520. DOI: 10.1093/bioinformatics/bts104. View

10.

Goodwin R . Sample preparation for mass spectrometry imaging: small mistakes can lead to big consequences. J Proteomics. 2012; 75(16):4893-4911. DOI: 10.1016/j.jprot.2012.04.012. View

11.

Bandura D, Baranov V, Ornatsky O, Antonov A, Kinach R, Lou X . Mass cytometry: technique for real time single cell multitarget immunoassay based on inductively coupled plasma time-of-flight mass spectrometry. Anal Chem. 2009; 81(16):6813-22. DOI: 10.1021/ac901049w. View

12.

van Manen H, Kraan Y, Roos D, Otto C . Single-cell Raman and fluorescence microscopy reveal the association of lipid bodies with phagosomes in leukocytes. Proc Natl Acad Sci U S A. 2005; 102(29):10159-64. PMC: 1177376. DOI: 10.1073/pnas.0502746102. View

13.

Kovacheva V, Khan A, Khan M, Epstein D, Rajpoot N . DiSWOP: a novel measure for cell-level protein network analysis in localized proteomics image data. Bioinformatics. 2013; 30(3):420-7. DOI: 10.1093/bioinformatics/btt676. View

14.

Loyek C, Rajpoot N, Khan M, Nattkemper T . BioIMAX: a Web 2.0 approach for easy exploratory and collaborative access to multivariate bioimage data. BMC Bioinformatics. 2011; 12:297. PMC: 3161928. DOI: 10.1186/1471-2105-12-297. View

15.

Nattkemper T, Ritter H, Schubert W . A neural classifier enabling high-throughput topological analysis of lymphocytes in tissue sections. IEEE Trans Inf Technol Biomed. 2001; 5(2):138-49. DOI: 10.1109/4233.924804. View

16.

Clarke G, Zubovits J, Shaikh K, Wang D, Dinn S, Corwin A . A novel, automated technology for multiplex biomarker imaging and application to breast cancer. Histopathology. 2013; 64(2):242-55. DOI: 10.1111/his.12240. View

17.

Raza S, Humayun A, Abouna S, Nattkemper T, Epstein D, Khan M . RAMTaB: robust alignment of multi-tag bioimages. PLoS One. 2012; 7(2):e30894. PMC: 3280195. DOI: 10.1371/journal.pone.0030894. View

18.

Schuffler P, Schapiro D, Giesen C, Wang H, Bodenmiller B, Buhmann J . Automatic single cell segmentation on highly multiplexed tissue images. Cytometry A. 2015; 87(10):936-42. DOI: 10.1002/cyto.a.22702. View

19.

Evans R, Naidu B, Rajpoot N, Epstein D, Khan M . Toponome imaging system: multiplex biomarkers in oncology. Trends Mol Med. 2012; 18(12):723-31. DOI: 10.1016/j.molmed.2012.10.003. View

20.

Fonville J, Carter C, Cloarec O, Nicholson J, Lindon J, Bunch J . Robust data processing and normalization strategy for MALDI mass spectrometric imaging. Anal Chem. 2011; 84(3):1310-9. DOI: 10.1021/ac201767g. View