Key Technologies and Challenges in De Novo Sequencing
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Monoclonal antibody sequence determination
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Proteomic analysis of exosomes, cerebrospinal fluid, and other trace biological samples
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Protein expression profiling in non-model species
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Discovery and validation of novel post-translationally modified peptide segments
In proteomics research, spectral data are typically interpreted by matching them against existing protein databases. However, in advanced applications such as studies of non-model organisms, the discovery of novel protein modifications, single-cell proteomics, and antibody characterization, these databases often fail to provide adequate coverage. As a result, de novo peptide sequencing has emerged as a critical technique for deciphering unknown protein sequences.
De novo sequencing is a methodology that imposes stringent demands on mass spectrometric precision, algorithmic robustness, and sample preparation strategies. It requires a high level of instrumentation performance, optimized workflows, and sophisticated data analysis pipelines. This paper systematically reviews the fundamental technologies and common challenges associated with de novo sequencing, and discusses its practical value in both scientific research and industrial applications.
Fundamental Principles of De Novo Sequencing
De novo sequencing refers to the process of inferring amino acid sequences of peptides or proteins directly from mass spectrometry data, without relying on existing protein databases. The core workflow involves the following steps:
1. Sample digestion and mass spectrometry analysis: Enzymes such as trypsin are employed to enzymatically cleave proteins into shorter peptides.
2. MS/MS spectrum acquisition: High-resolution mass spectrometry platforms (e.g., Orbitrap or TOF) are used to obtain tandem mass spectra (MS/MS) of fragmented peptides.
3. Spectrum interpretation: Advanced algorithms are utilized to identify b- and y-ion series within the spectra, from which peptide sequences are deduced.
4. Sequence assembly and validation: Multiple peptide sequences are assembled to reconstruct full-length proteins or candidate protein sequences.
Key Technological Advances in De Novo Sequencing
1. High-Resolution Mass Spectrometry Platforms
The accuracy of de novo sequencing is critically dependent on the quality of MS/MS spectra. State-of-the-art instruments such as the Orbitrap Eclipse, Q Exactive HF-X, and timsTOF Pro 2 offer exceptional mass accuracy and rapid scan rates, enabling the generation of high-quality, information-dense spectral data. At MtoZ Biolabs, we integrate the Orbitrap with the TIMS-PASEF platform to enhance peptide fragmentation efficiency and increase data coverage, thereby establishing a robust foundation for reliable de novo sequencing.
2. Advanced Algorithmic Support
Spectrum interpretation lies at the heart of de novo sequencing. Current mainstream algorithms—including PEAKS, Novor, pNovo, and DeepNovo—leverage graph-theoretical approaches, scoring functions, or deep learning frameworks to automate the identification of fragment ions and the prediction of peptide sequences. In recent years, artificial intelligence models—particularly those based on Transformer architectures—have demonstrated remarkable performance in sequence prediction, leading to significant improvements in both accuracy and coverage.
3. Multi-Enzyme Digestion and Labeling Strategies
Employing multiple proteases (e.g., GluC, Chymotrypsin) in parallel digestion workflows enhances peptide coverage and mitigates the sequence biases associated with single-enzyme specificity. Additionally, the incorporation of isobaric labeling techniques such as TMT or iTRAQ can moderately improve the accuracy of spectrum interpretation, particularly in complex biological samples.
Application Scenarios
1. Antibody Sequence Determination
In the development of monoclonal antibodies, de novo sequencing is employed to determine the light and heavy chain sequences of antibodies produced by hybridoma cells. This process serves as a prerequisite for antibody reengineering and humanization design.
2. Research on Non-Model Species
For samples from non-model plant and animal species that lack reference protein databases, de novo sequencing remains the only reliable approach for obtaining protein sequences. It is widely applied in studies of evolutionary biology and ecological proteomics.
3. Identification of PTMs and Discovery of Novel Peptide Segments
De novo sequencing enables the detection of novel translation initiation sites, alternative splicing products, or rare post-translationally modified peptides that are absent from existing protein databases. This capability facilitates the identification of previously uncharacterized biomarkers.
Technical Challenges and Solutions
1. Spectral Complexity and High Noise Levels
Low-abundance peptides and interference from co-fragmented ions often result in highly complex spectra, which compromise the accuracy of spectral interpretation.
Solution: Enhance sample preparation workflows (e.g., high-pH reverse-phase fractionation, desalting) and improve LC-MS sensitivity. Techniques such as FAIMS and PASEF can be employed to increase signal resolution.
2. High False Positive Rates in Algorithms
Current de novo sequencing algorithms may produce incorrect sequence predictions or assemble peptide fragments in inaccurate order, especially for long peptide chains.
Solution: Implement cross-validation using multiple algorithms, and enhance sequence confidence through isotopic labeling and tandem mass spectrometry-based sequencing strategies.
3. Lack of a Standardized Validation Framework
There is currently no unified standard for validating de novo sequencing results, which hampers large-scale applications.
Solution: Conduct orthogonal validation through mass spectrometry confirmation, antibody affinity assays, and functional studies to ensure sequence reliability.
MtoZ Biolabs Solutions
MtoZ Biolabs has developed a comprehensive de novo sequencing workflow that integrates multi-enzyme digestion strategies, high-resolution mass spectrometry platforms, and AI-driven data analysis. This workflow is suitable for a wide range of research applications, including:
Our team offers customized analytical workflows tailored to specific project needs, ensuring rigorous quality control and validation throughout the entire process—from data acquisition to sequence reconstruction. At MtoZ Biolabs, we are dedicated to advancing the frontiers of proteomics by supporting research and industry clients in addressing analytical challenges and uncovering novel biological insights. For de novo sequencing inquiries or collaboration opportunities, please contact us for personalized technical consultation.
MtoZ Biolabs, an integrated chromatography and mass spectrometry (MS) services provider.
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