Evidence map›Paper›PMID 41298490›Full record

ArticleNature communications2025

Acceleration, simplification and potential parallelization of digital polymers sequencing by coupling tandem mass spectrometry with ion mobility.

Isaure Sergent, Georgette Obeid, Thibault Schutz, Jean-François Lutz, Laurence Charles

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Isaure SergentAix Marseille Université, CNRS, Institut de Chimie Radicalaire (ICR), Marseille, France.
Georgette ObeidUniversité de Strasbourg, CNRS, Institut de Science et d'Ingénierie Supramoléculaires (ISIS), Strasbourg, France.ORCID http://orcid.org/0009-0005-7418-7458
Thibault SchutzUniversité de Strasbourg, CNRS, Institut de Science et d'Ingénierie Supramoléculaires (ISIS), Strasbourg, France.
Jean-François LutzUniversité de Strasbourg, CNRS, Institut de Science et d'Ingénierie Supramoléculaires (ISIS), Strasbourg, France. jflutz@unistra.fr.ORCID http://orcid.org/0000-0002-3893-2458
Laurence CharlesAix Marseille Université, CNRS, Institut de Chimie Radicalaire (ICR), Marseille, France. laurence.charles@univ-amu.fr.ORCID http://orcid.org/0000-0003-3807-8375

Funding

Agence Nationale de la Recherche (French National Research Agency) ANR-19-CE29-0015-01Agence Nationale de la Recherche (French National Research Agency) ANR-19-CE29-0015-02
6 · The paper itself

Abstract

Tailoring the structure of digital polymers is an efficient strategy for reliable reading of large amounts of data by tandem mass spectrometry. Notably, full sequence coverage of chains containing up to 33 bytes of information is achieved for block-truncated poly(phosphodiester)s designed to undergo controlled fragmentations. However, the previously established reading methodology based on multiple MS stages performed sequentially remains slow and not prone to automation. Here, we report a full gas-phase bottom-up workflow enabling production, separation and sequencing of all sub-sequences of block-truncated poly(phosphodiester)s in a single run. To do so, a multidimensional coupling involving two activation stages in tandem with ion mobility spectrometry has been optimized. Since blocks to be sequenced have their mobility varying in a predictable manner, proper selection of tags used for their identification permits to achieve mobility resolution prior to sequencing. Performing this coupling with MALDI further paves the way to automated imaging-based reading approaches.

Identifiers

PMID41298490
PMCPMC12748738

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.