MtoZ Biolabs provides the Label-Free Based Quantitative Plant Proteome Analysis Service through an integrated workflow built on label-free quantification (LFQ) and LC-MS/MS proteomics to support differential protein quantification and mechanistic discovery in plant tissues and plant-derived cell samples. This service helps researchers obtain quantitative proteome datasets suitable for statistical analysis without introducing isotopic or chemical labeling.

Principle of Label-Free Quantitative Proteomics

Label-Free Quantitative Proteomics typically infers relative abundance changes by comparing MS signals of peptides or proteins across different samples. Because it does not rely on isotopic or chemical labeling, it is well-suited for multi-group comparisons and exploratory studies. In practice, two common label-free quantification approaches are widely used.

1. MS1 Intensity-Based Quantification

This approach quantifies peptides at the MS1 level by using the peak area or peak intensity of peptide features as quantitative signals. Through cross-sample retention time alignment and feature matching, peptide-level signals are summarized to the protein level to compare relative protein abundance across samples. Key advantages of MS1 intensity-based quantification include:

• A broader quantitative dynamic range and better resolution, making it more suitable for detecting subtle expression changes
• Greater compatibility with multi-group study designs, enabling downstream normalization, batch correction, and statistical modeling
• Well-structured quantitative result tables that integrate smoothly with differential analysis, clustering, and pathway enrichment workflows

2. Spectral Counting-Based Quantification

This approach is based on MS/MS identifications and uses the number of MS/MS spectra assigned to a protein, the number of identified peptides, or related metrics as a proxy for abundance. It is generally considered semi-quantitative and emphasizes trends rather than precise fold changes. Key advantages of spectral counting-based quantification include:

• Intuitive logic and simple implementation, suitable for rapid overview analysis or as supporting evidence
• Lower sensitivity to fluctuations in signal intensity, which can provide complementary information in certain complex sample types
• Useful for high-level screening to prioritize proteins with large and consistent changes

Zhu, W. et al. J Biomed Biotechnol. 2010.

Figure 1. General Approaches of Label-free Quantitative Proteomics

Without introducing labeling, label-free quantification enables flexible expansion of experimental groups and condition comparisons. This is particularly advantageous for plant studies involving multiple tissues, multiple time points, diverse stress treatments, and comparisons across cultivars or genotypes. For projects with heterogeneous sample sources, complex matrices, and frequently evolving study designs, the Label-Free Based Quantitative Plant Proteome Analysis Service can maintain data comparability while offering greater experimental flexibility and smoother downstream validation.

Label-Free Based Quantitative Plant Proteome Analysis Service at MtoZ Biolabs

MtoZ Biolabs offers an end-to-end solution for plant tissues and cell samples, spanning experimental design recommendations, protein extraction and digestion, LC-MS/MS data acquisition, protein identification, label-free quantification, and differential statistical analysis. This service supports researchers in generating quantitative proteome datasets for group comparisons and mechanistic discovery.

MS analysis is performed on high-resolution LC-MS/MS platforms (Thermo Fisher Q Exactive HF and Orbitrap Fusion Lumos) coupled with a robust nano-flow LC separation system, balancing identification depth with quantitative consistency and supporting multi-group, multi-condition, and time-course studies. In addition to label-free quantification, we also provide labeling-based quantitative proteomics services, such as TMT or iTRAQ, to meet different study designs, throughput needs, and publication requirements.

Workflow of Label-Free Based Quantitative Plant Proteome Analysis Service

Why Choose MtoZ Biolabs

• Extensive plant-focused sample preparation experience, with attention to interference risks associated with cell wall components and secondary metabolites
• Our pricing is transparent, with no hidden fees or additional costs
• MtoZ Biolabs has established an advanced label-free quantitative proteomics platform to ensure reliable, fast, and highly accurate analytical services
• No isotopic or chemical labeling is required, eliminating labeling reactions and related cleanup steps

Applications of Label-Free Based Quantitative Plant Proteome Analysis Service

• Abiotic stress research, including protein responses to drought, salt stress, temperature stress, and oxidative stress
• Growth and development mechanisms, including protein expression changes associated with germination, flowering, organ differentiation, and senescence
• Genetics and breeding studies, including differential protein discovery and candidate biomarker screening across mutants, transgenic lines, or cultivars
• Plant-pathogen interactions and immunity, including defense-related proteins and pathway-level insights during host-pathogen interactions
• Secondary metabolism and quality traits, including protein network changes associated with flavor, color, nutrition, or resistance-related phenotypes

Deliverables

• Experiment procedures
• Liquid chromatography and mass spectrometer parameters
• MS raw data files
• Peptide identifications and intensities
• Protein identifications and intensities
• Bioinformatics analysis

Start Your Project with MtoZ Biolabs

Contact us and share your research goals and sample information. We will recommend an appropriate analysis plan and deliverable package to help you move your project forward efficiently.

FAQs

Q1: What types of samples are suitable?

Suitable samples typically include:

• Plant tissues such as leaves, roots, stems, flowers, fruits, and seeds
• Plant cells and culture systems such as cell suspensions, callus tissue, and protoplasts
• Purified proteins or protein extracts, which may be accepted upon evaluation if pre-processing has been completed

To ensure comparability for label-free quantification, we recommend providing clear group information and biological replicates. For samples rich in polysaccharides, polyphenols, or pigments, please notify us before submission so we can optimize the sample processing strategy.

Q2: What is the service’s general workflow?

Q3: What data formats are provided?

MtoZ Biolabs provides results in multiple standard formats to ensure compatibility with common statistical analysis and visualization tools. Deliverables typically include

• LC-MS/MS raw data files and essential run-level QC information
• Processed data tables in CSV or Excel format, including protein identifications, label-free quantification results, and differential analysis outputs
• Summary reports in PDF format, including an overview of analytical methods, QC highlights, and key findings
• High-resolution figures and spectra or chromatograms in PNG or TIFF formats for reporting and publication

Additional data structures or file formats can be provided upon request to meet specific research or publication requirements.

Q4: How should I prepare my samples?

To obtain stable and reproducible label-free quantification results, MtoZ Biolabs recommends preparing and submitting samples according to the following guidelines:

• Sample Type: Provide information on species, tissue type or cell source, treatment conditions, sampling time points, and group design
• Sample Integrity: Process samples promptly under low-temperature conditions and avoid prolonged exposure at room temperature. Samples should be as clean as possible to minimize soil contamination, residual culture media, and visible debris
• Amount Requirement: Please provide at least 2 g of fresh plant tissue per sample. If submitting extracted protein, please provide ≥ 300 μg total protein (recommended in an MS compatible buffer). If your sample amount is limited, please inform us in advance so we can evaluate feasibility and adjust the workflow accordingly
• Storage and Shipping: Store samples at −80°C and avoid repeated freeze-thaw cycles. Ship on dry ice using leak-proof containers, and clearly label each tube with sample ID and group information
• Documentation: Include a sample information sheet detailing buffer composition or additives, as well as the desired output type and comparison scheme

For more information, please refer to Sample Submission Guidelines for Proteomics and Sample Submission Guidelines for Metabolomics.