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PhIP-Seq characterization of serum antibodies using oligonucleotide-encoded peptidomes

A Publisher Correction to this article was published on 25 October 2018

This article has been updated

Abstract

The binding specificities of an individual’s antibody repertoire contain a wealth of biological information. They harbor evidence of environmental exposures, allergies, ongoing or emerging autoimmune disease processes, and responses to immunomodulatory therapies, for example. Highly multiplexed methods to comprehensively interrogate antibody-binding specificities have therefore emerged in recent years as important molecular tools. Here, we provide a detailed protocol for performing ‘phage immunoprecipitation sequencing’ (PhIP-Seq), which is a powerful method for analyzing antibody-repertoire binding specificities with high throughput and at low cost. The methodology uses oligonucleotide library synthesis (OLS) to encode proteomic-scale peptide libraries for display on bacteriophage. These libraries are then immunoprecipitated, using an individual’s antibodies, for subsequent analysis by high-throughput DNA sequencing. We have used PhIP-Seq to identify novel self-antigens associated with autoimmune disease, to characterize the self-reactivity of broadly neutralizing HIV antibodies, and in a large international cross-sectional study of exposure to hundreds of human viruses. Compared with alternative array-based techniques, PhIP-Seq is far more scalable in terms of sample throughput and cost per analysis. Cloning and expression of recombinant proteins are not required (versus protein microarrays), and peptide lengths are limited only by DNA synthesis chemistry (up to 90-aa (amino acid) peptides versus the typical 8- to 12-aa length limit of synthetic peptide arrays). Compared with protein microarrays, however, PhIP-Seq libraries lack discontinuous epitopes and post-translational modifications. To increase the accessibility of PhIP-Seq, we provide detailed instructions for the design of phage-displayed peptidome libraries, their immunoprecipitation using serum antibodies, deep sequencing–based measurement of peptide abundances, and statistical determination of peptide enrichments that reflect antibody–peptide interactions. Once a library has been constructed, PhIP-Seq data can be obtained for analysis within a week.

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Fig. 1: Overview of the PhIP-Seq methodology.
Fig. 2: Bioinformatics workflows.
Fig. 3: Primer-depleted, pooled VirScan PCR2 products run at a higher molecular weight than expected (shown on a 2% (wt/vol) agarose gel in lithium borate).
Fig. 4: Organization of bacteriophage genome, primer binding sites, and PCR products.
Fig. 5: Output from the sequencing data analysis pipeline.

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Change history

  • 25 October 2018

    The version of this paper originally published contained typesetter-introduced errors in some of the code commands, consisting of conversion of a closing backslash (\) to a forward slash (/). These errors have been corrected in the HTML and PDF versions of the protocol.

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Acknowledgements

The development of the PhIP-Seq technology platform has been an ongoing collaboration with S.J. Elledge of the Harvard Medical School Genetics Department and the Howard Hughes Medical Institute. Special thanks to T.M. Shi (Department of Art as Applied to Medicine, Johns Hopkins School of Medicine) for creating the artwork used in Fig. 1. Recent improvements in the PhIP-Seq methodology were supported under a U24 Resource-Related Research Projects Cooperative Agreement awarded by the NIH (U24AI118633 to H.B.L. and S.J. Elledge), a grant from the Jerome L. Greene Foundation (to H.B.L. and A.N.B.), and a grant from the Sjögren’s Syndrome Foundation (to H.B.L. and A.N.B.). A.N.B. received support from NIH grant R01DE012354 (Rosen, PI).

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Authors and Affiliations

Authors

Contributions

D.M., D.L.W., and B.M.S. performed experiments related to assay development and optimization. D.M. performed PhIP-Seq screening analysis of the serum samples used in this study. M.S.N. created a draft version of the peptidome design software. A.N.B. provided the Sjogren’s syndrome serum samples and disease-specific expertise. U.L. developed the pepsyn and phip-stat software packages. U.L. and H.B.L. wrote the manuscript.

Corresponding authors

Correspondence to Uri Laserson or H. Benjamin Larman.

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The authors declare no competing interests.

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Key references using this protocol

1. Larman, H. B. et al. Nat. Biotech. 29, 535–541 (2011) https://doi.org/10.1038/nbt.1856

2. Larman, H. B. et al. Ann. Neurol. 73, 408–418 (2013) https://doi.org/10.1002/ana.23840

3. Xu, G. J. et al. Science 384, aaa0698 (2015) https://doi.org/10.1126/science.aaa0698

Supplementary information

Supplementary Table 1

Design of 96 ad_min_BCX_P7 PCR2 i7 indexing primers

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Mohan, D., Wansley, D.L., Sie, B.M. et al. PhIP-Seq characterization of serum antibodies using oligonucleotide-encoded peptidomes. Nat Protoc 13, 1958–1978 (2018). https://doi.org/10.1038/s41596-018-0025-6

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