XA-Novo: high-throughput mass spectrometry-based de novo sequencing technology for monoclonal antibodies and antibody mixtures

Elucidating antibody sequences by mass spectrometry-based de novo sequencing is essential but remains technically challenging. Here we present XA-Novo, an accurate and high-throughput de novo sequencing solution that integrates a single-pot multi-enzymatic gradient digestion method with a beam search-based assembler (Fusion) to reconstruct full-length antibody sequences directly from bottom-up mass spectrometry data. Benchmarking across well-characterized antibodies from multiple species demonstrates that XA-Novo outperforms commercial solutions in identification sensitivity, sequence completeness, and reconstruction accuracy. Furthermore, XA-Novo successfully reconstructs six immunotherapeutic antibodies with unknown sequences, and in vitro/vivo assays validate that these generated antibodies exhibit functionality equivalent to their commercial counterparts. Moreover, XA-Novo achieves over 99.54% accurate sequence coverage in distinguishing mixed COVID-19 neutralizing antibodies, exceeding the performance of current assemblers reported for single-antibody sequencing. Overall, XA-Novo establishes a reliable, scalable, and broadly applicable workflow for routine antibody sequencing, thereby accelerating both fundamental antibody research and therapeutic antibody development.

Authors

Institutions

Publication Details

Journal
Nature Communications
Published
2026-03-12
DOI
https://doi.org/10.1038/s41467-026-70496-y
Primary Topic
Monoclonal and Polyclonal Antibodies Research
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

XA-Novo: high-throughput mass spectrometry-based de novo sequencing technology for monoclonal antibodies and antibody mixtures

Zhenjian Jiang, Ningshao Xia, Yueting Xiong, Rongshan Yu et al.
Nature Communications
Monoclonal and Polyclonal Antibodies Research
article

XA-Novo: high-throughput mass spectrometry-based de novo sequencing technology for monoclonal antibodies and antibody mixtures

Zhenjian Jiang, Ningshao Xia, Yueting Xiong, Rongshan Yu, Xiaoqing Chen, Qingfang Bu, Wenbin Jiang, Yangtao Wu, Ling Luo, Quan Yuan, Fan Liu, Yijie Qiu, Jingyi Wang, Jin Xiao
article en

Abstract

Elucidating antibody sequences by mass spectrometry-based de novo sequencing is essential but remains technically challenging. Here we present XA-Novo, an accurate and high-throughput de novo sequencing solution that integrates a single-pot multi-enzymatic gradient digestion method with a beam search-based assembler (Fusion) to reconstruct full-length antibody sequences directly from bottom-up mass spectrometry data. Benchmarking across well-characterized antibodies from multiple species demonstrates that XA-Novo outperforms commercial solutions in identification sensitivity, sequence completeness, and reconstruction accuracy. Furthermore, XA-Novo successfully reconstructs six immunotherapeutic antibodies with unknown sequences, and in vitro/vivo assays validate that these generated antibodies exhibit functionality equivalent to their commercial counterparts. Moreover, XA-Novo achieves over 99.54% accurate sequence coverage in distinguishing mixed COVID-19 neutralizing antibodies, exceeding the performance of current assemblers reported for single-antibody sequencing. Overall, XA-Novo establishes a reliable, scalable, and broadly applicable workflow for routine antibody sequencing, thereby accelerating both fundamental antibody research and therapeutic antibody development.

Nature Communications
Xiamen University (CN), Zhongshan Hospital of Xiamen University (CN)
National Natural Science Foundation of China, Natural Science Foundation of Fujian Province, National Science and Technology Major Project
Openalex Percentile: Top 26%
Monoclonal and Polyclonal Antibodies Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.