Beyond mass spectrometry, the next step in proteomics

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Abstract

This survey illuminates alternatives for sequencing proteins with the brightest prospects for displacing mass spectrometry.

Abstract

Proteins can be the root cause of a disease, and they can be used to cure it. The need to identify these critical actors was recognized early (1951) by Sanger; the first biopolymer sequenced was a peptide, insulin. With the advent of scalable, single-molecule DNA sequencing, genomics and transcriptomics have since propelled medicine through improved sensitivity and lower costs, but proteomics has lagged behind. Currently, proteomics relies mainly on mass spectrometry (MS), but instead of truly sequencing, it classifies a protein and typically requires about a billion copies of a protein to do it. Here, we offer a survey that illuminates a few alternatives with the brightest prospects for identifying whole proteins and displacing MS for sequencing them. These alternatives all boast sensitivity superior to MS and promise to be scalable and seem to be adaptable to bioinformatics tools for calling the sequence of amino acids that constitute a protein.

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On the frequency of protein glycosylation, as deduced from analysis of the SWISS-PROT database.

R. Apweiler, H Hermjakob, N. Sharon (1999)

The SWISS-PROT protein sequence data bank contains at present nearly 75,000 entries, almost two thirds of which include the potential N-glycosylation consensus sequence, or sequon, NXS/T (where X can be any amino acid but proline) and thus may be glycoproteins. The number of proteins filed as glycoproteins is however considerably smaller, 7942, of which 749 have been characterized with respect to the total number of their carbohydrate units and sites of attachment of the latter to the protein, as well as the nature of the carbohydrate-peptide linking group. Of these well characterized glycoproteins, about 90% carry either N-linked carbohydrate units alone or both N- and O-linked ones, attached at 1297 N-glycosylation sites (1.9 per glycoprotein molecule) and the rest are O-glycosylated only. Since the total number of sequons in the well characterized glycoproteins is 1968, their rate of occupancy is 2/3. Assuming that the same number of N-linked units and rate of sequon occupancy occur in all sequon containing proteins and that the proportion of solely O-glycosylated proteins (ca. 10%) will also be the same as among the well characterized ones, we conclude that the majority of sequon containing proteins will be found to be glycosylated and that more than half of all proteins are glycoproteins.

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Annotation-free quantification of RNA splicing using LeafCutter

Yang I. Li, David Knowles, Jack Humphrey … (2017)

The excision of introns from pre-mRNA is an essential step in mRNA processing. We developed LeafCutter to study sample and population variation in intron splicing. LeafCutter identifies variable splicing events from short-read RNA-seq data and finds events of high complexity. Our approach obviates the need for transcript annotations and circumvents the challenges in estimating relative isoform or exon usage in complex splicing events. LeafCutter can be used both for detecting differential splicing between sample groups, and for mapping splicing quantitative trait loci (sQTLs). Compared to contemporary methods, we find 1.4–2.1 times more sQTLs, many of which help us ascribe molecular effects to disease-associated variants. Strikingly, transcriptome-wide associations between LeafCutter intron quantifications and 40 complex traits increased the number of associated disease genes at 5% FDR by an average of 2.1-fold as compared to using gene expression levels alone. LeafCutter is fast, scalable, easy to use, and available online.

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Nanopore native RNA sequencing of a human poly(A) transcriptome

Rachael E. Workman, Alison Tang, Paul Tang … (2019)

High throughput cDNA sequencing technologies have advanced our understanding of transcriptome complexity and regulation. However, these methods lose information contained in biological RNA because the copied reads are often short and because modifications are not retained. We address these limitations using a native poly(A) RNA sequencing strategy developed by Oxford Nanopore Technologies (ONT). Our study generated 9.9 million aligned sequence reads for the human cell line GM12878, using thirty MinION flow cells at six institutions. These native RNA reads had a median length of 771 bases, and a maximum aligned length of over 21,000 bases. Mitochondrial poly(A) reads provided an internal measure of read length quality. We combined these long nanopore reads with higher accuracy short-reads and annotated GM12878 promoter regions, to identify 33,984 plausible RNA isoforms. We describe strategies for assessing 3′ poly(A) tail length, base modifications, and transcript haplotypes.

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Author and article information

Journal

Journal ID (nlm-ta): Sci Adv

Journal ID (iso-abbrev): Sci Adv

Journal ID (publisher-id): SciAdv

Journal ID (hwp): advances

Title: Science Advances

Publisher: American Association for the Advancement of Science

ISSN (Electronic): 2375-2548

Publication date Collection: January 2020

Publication date (Electronic): 10 January 2020

Volume: 6

Issue: 2

Electronic Location Identifier: eaax8978

Affiliations

[1 ]Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.

[2 ]Departments of Electrical Engineering and Biological Sciences, University of Notre Dame, Notre Dame, IN, USA.

Author notes

[* ]Corresponding author. Email: gtimp@ 123456nd.edu

Author information

Winston Timp http://orcid.org/0000-0003-2083-6027

Gregory Timp http://orcid.org/0000-0003-4418-5679

Article

Publisher ID: aax8978

DOI: 10.1126/sciadv.aax8978

PMC ID: 6954058

PubMed ID: 31950079

SO-VID: 7f4937d5-f9b0-4afa-811d-8fd043cff993

Copyright © Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution License 4.0 (CC BY).

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This is an open-access article distributed under the terms of the Creative Commons Attribution license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

History

Date received : 03 May 2019

Date accepted : 19 November 2019

Funding

Funded by: Open Philanthropy Project;

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Copyeditor Nielsen Marquez

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Beyond mass spectrometry, the next step in proteomics

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Most cited references 120

On the frequency of protein glycosylation, as deduced from analysis of the SWISS-PROT database.

Annotation-free quantification of RNA splicing using LeafCutter

Nanopore native RNA sequencing of a human poly(A) transcriptome

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