Evidence map›Paper›PMID 42298104›Full record

ArticleNature nanotechnology2026

High-resolution nanopore peptide sensing, profiling and sequence assembly.

Kefan Wang, Xingwang An, Xinmeng Gao, Yusheng Ouyang, Zixuan Wang, Pingping Fan, Kui Li, Yunqi Xiao, Wendong Jia, Jialu Chen and 3 more

Abstract read
PubMed Publisher
In one paragraph

Article in Nature nanotechnology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Sensing forces that shape tumours.Nature nanotechnology · 2026
    Article
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

13 authors.

Kefan WangState Key Laboratory of Analytical Chemistry for Life Sciences, School of Chemistry, Nanjing Drum Tower Hospital, Nanjing University, Nanjing, China.
Xingwang AnState Key Laboratory of Analytical Chemistry for Life Sciences, School of Chemistry, Nanjing Drum Tower Hospital, Nanjing University, Nanjing, China.ORCID http://orcid.org/0009-0007-8719-3181
Xinmeng GaoState Key Laboratory of Analytical Chemistry for Life Sciences, School of Chemistry, Nanjing Drum Tower Hospital, Nanjing University, Nanjing, China.
Yusheng OuyangState Key Laboratory of Analytical Chemistry for Life Sciences, School of Chemistry, Nanjing Drum Tower Hospital, Nanjing University, Nanjing, China.
Zixuan WangState Key Laboratory of Analytical Chemistry for Life Sciences, School of Chemistry, Nanjing Drum Tower Hospital, Nanjing University, Nanjing, China.
Pingping FanState Key Laboratory of Analytical Chemistry for Life Sciences, School of Chemistry, Nanjing Drum Tower Hospital, Nanjing University, Nanjing, China.
Kui LiState Key Laboratory of Analytical Chemistry for Life Sciences, School of Chemistry, Nanjing Drum Tower Hospital, Nanjing University, Nanjing, China.
Yunqi XiaoState Key Laboratory of Analytical Chemistry for Life Sciences, School of Chemistry, Nanjing Drum Tower Hospital, Nanjing University, Nanjing, China.
Wendong JiaState Key Laboratory of Analytical Chemistry for Life Sciences, School of Chemistry, Nanjing Drum Tower Hospital, Nanjing University, Nanjing, China.ORCID http://orcid.org/0000-0002-1685-9261
Jialu ChenState Key Laboratory of Analytical Chemistry for Life Sciences, School of Chemistry, Nanjing Drum Tower Hospital, Nanjing University, Nanjing, China.ORCID http://orcid.org/0000-0001-9847-5802
Wen SunState Key Laboratory of Analytical Chemistry for Life Sciences, School of Chemistry, Nanjing Drum Tower Hospital, Nanjing University, Nanjing, China.
Panke ZhangState Key Laboratory of Analytical Chemistry for Life Sciences, School of Chemistry, Nanjing Drum Tower Hospital, Nanjing University, Nanjing, China.ORCID http://orcid.org/0000-0001-8562-9972
Shuo HuangState Key Laboratory of Analytical Chemistry for Life Sciences, School of Chemistry, Nanjing Drum Tower Hospital, Nanjing University, Nanjing, China. shuo.huang@nju.edu.cn.ORCID http://orcid.org/0000-0001-6133-7027

Funding

China Postdoctoral Science Foundation 2022M721554;2023T160300China Postdoctoral Science Foundation 2025M780957National Natural Science Foundation of China (National Science Foundation of China) 22225405;22534004;National Natural Science Foundation of China (National Science Foundation of China) 223B2402NJU | State Key Laboratory of Analytical Chemistry for Life Science 5431ZZXM2509
6 · The paper itself

Abstract

Nanopores have been explored as a potential platform for protein analysis following the success of nanopore nucleic acid sequencing. However, protein sequencing remains technically challenging and has not yet been established for proteomics use. Here a nickel-immobilized Mycobacterium smegmatis porin A (MspA-NTA-Ni) nanopore is shown to enable the identification of a range of proteomic analytes, including amino acids and peptides up to 39 amino acids in length. Under identical conditions, signals corresponding to 20 proteinogenic amino acids, 4 post-translationally modified amino acids, 32 peptides, 6 modified peptides, 11 bioactive peptides and 2 neoantigen peptides were recorded. Machine-learning-based analysis enabled classification of these analytes with a validation accuracy of up to 97.4% within the studied dataset. The MspA-NTA-Ni nanopore supports both direct peptide identification and peptide profiling following enzymatic hydrolysis. As a proof of concept, a reference peptide was digested using exo- and endopeptidases to generate overlapping peptide fragments. Nanopore measurements combined with machine learning predictions enabled the identification of fragment compositions and partial sequences, allowing reconstruction of the original peptide sequence. This hydrolysis-based approach shows sensitivity to sequence alterations, including mutations, deletions and post-translational modifications, indicating potential utility for targeted peptide characterization.

Indexed as

NanoporesPeptidesProteomicsSequence Analysis, ProteinAmino Acid SequenceMachine LearningMycobacterium smegmatisNickelPorinsmspA protein, Mycobacterium smegmatisNickelPeptidesPorins

Identifiers

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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 Socratic graph.