Direct Mass Spectrometry-Based Detection and Antibody Sequencing of Monoclonal Gammopathy of Undetermined Significance from Patient Serum: A Case Study

A Handle on Mass Coincidence Errors in De Novo Sequencing of Antibodies by Bottom-up Proteomics

Antibody sequences can be determined at 99% accuracy directly from the polypeptide product by using bottom-up proteomics techniques. Sequencing accuracy at the peptide level is limited by the isobaric residues leucine and isoleucine, incomplete fragmentation spectra in which the order of two or more residues remains ambiguous due to lacking fragment ions for the intermediate positions, and isobaric combinations of amino acids, of potentially different lengths, for example, GG = N and GA = Q. Here, we present several updates to Stitch (v1.5), which performs template-based assembly of de novo peptides to reconstruct antibody sequences. This version introduces a mass-based alignment algorithm that explicitly accounts for mass coincidence errors. In addition, it incorporates a postprocessing procedure to assign I/L residues based on secondary fragments (satellite ions, i.e., w-ions). Moreover, evidence for sequence assignments can now be directly evaluated with the addition of an integrated spectrum viewer. Lastly, input data from a wider selection of de novo peptide sequencing algorithms are allowed, now including Casanovo, PEAKS, Novor.Cloud, pNovo, and MaxNovo, in addition to flat text and FASTA. Combined, these changes make Stitch compatible with a larger range of data processing pipelines and improve its tolerance to peptide-level sequencing errors.

N-linked glycosylation of the M-protein variable region: glycoproteogenomics reveals a new layer of personalized complexity in multiple myeloma

OBJECTIVES

Multiple myeloma (MM) is a plasma cell malignancy characterized by a monoclonal expansion of plasma cells that secrete a characteristic M-protein. This M-protein is crucial for diagnosis and monitoring of MM in the blood of patients. Recent evidence has emerged suggesting that N-glycosylation of the M-protein variable (Fab) region contributes to M-protein pathogenicity, and that it is a risk factor for disease progression of plasma cell disorders. Current methodologies lack the specificity to provide a site-specific glycoprofile of the Fab regions of M-proteins. Here, we introduce a novel glycoproteogenomics method that allows detailed M-protein glycoprofiling by integrating patient specific Fab region sequences (genomics) with glycoprofiling by glycoproteomics.

METHODS

Glycoproteogenomics was used for the detailed analysis of de novo N-glycosylation sites of M-proteins. First, Genomic analysis of the M-protein variable region was used to identify de novo N-glycosylation sites. Subsequently glycopeptide analysis with LC-MS/MS was used for detailed analysis of the M-protein glycan sites.

RESULTS

Genomic analysis uncovered a more than two-fold increase in the Fab Light Chain N-glycosylation of M-proteins of patients with Multiple Myeloma compared to Fab Light Chain N-glycosylation of polyclonal antibodies from healthy individuals. Subsequent glycoproteogenomics analysis of 41 patients enrolled in the IFM 2009 clinical trial revealed that the majority of the Fab N-glycosylation sites were fully occupied with complex type glycans, distinguishable from Fc region glycans due to high levels of sialylation, fucosylation and bisecting structures.

CONCLUSIONS

Together, glycoproteogenomics is a powerful tool to study de novo Fab N-glycosylation in plasma cell dyscrasias.

Improved detection of tryptic immunoglobulin variable region peptides by chromatographic and gas-phase fractionation techniques

The polyclonal repertoire of circulating antibodies potentially holds valuable information about an individual's humoral immune state. While bottom-up proteomics is well suited for serum proteomics, the vast number of antibodies and dynamic range of serum challenge this analysis. To acquire the serum proteome more comprehensively, we incorporated high-field asymmetric waveform ion-mobility spectrometry (FAIMS) or two-dimensional chromatography into standard trypsin-based bottom-up proteomics. Thereby, the number of variable region (VR)-related spectra increased 1.7-fold with FAIMS and 10-fold with chromatography fractionation. To match antibody VRs to spectra, we combined de novo searching and BLAST alignment. Validation of this approach showed that, as peptide length increased, the de novo accuracy decreased and BLAST performance increased. Through in silico calculations on antibody repository sequences, we determined the uniqueness of tryptic VR peptides and their suitability as antibody surrogate. Approximately one-third of these peptides were unique, and about one-third of all antibodies contained at least one unique peptide.

Longitudinal Fluctuations in Protein Concentrations and Higher-Order Structures in the Plasma Proteome of Kidney Failure Patients Subjected to a Kidney Transplant

Using proteomics and complexome profiling, we evaluated in a year-long study longitudinal variations in the plasma proteome of kidney failure patients, prior to and after a kidney transplantation. The post-transplant period was complicated by bacterial infections, resulting in dramatic changes in the proteome, attributed to an acute phase response (APR). As positive acute phase proteins (APPs), being elevated upon inflammation, we observed the well-described C-reactive protein and Serum Amyloid A (SAA), but also Fibrinogen, Haptoglobin, Leucine-rich alpha-2-glycoprotein, Lipopolysaccharide-binding protein, Alpha-1-antitrypsin, Alpha-1-antichymotrypsin, S100, and CD14. As negative APPs, being downregulated upon inflammation, we identified the well-documented Serotransferrin and Transthyretin, but added Kallistatin, Heparin cofactor 2, and interalpha-trypsin inhibitor heavy chain H1 and H2 (ITIH1, ITIH2). For the patient with the most severe APR, we performed plasma complexome profiling by SEC-LC-MS on all longitudinal samples. We observed that several plasma proteins displaying alike concentration patterns coelute and form macromolecular complexes. By complexome profiling, we expose how SAA1 and SAA2 become incorporated into high-density lipid particles, replacing largely Apolipoprotein (APO)A1 and APOA4. Overall, our data highlight that the combination of in-depth longitudinal plasma proteome and complexome profiling can shed further light on correlated variations in the abundance of several plasma proteins upon inflammatory events.

Reverse-engineering the anti-MUC1 antibody 139H2 by mass spectrometry-based de novo sequencing

Mucin 1 (MUC1) is a transmembrane mucin expressed at the apical surface of epithelial cells at mucosal surfaces. MUC1 has a barrier function against bacterial invasion and is well known for its aberrant expression and glycosylation in adenocarcinomas. The MUC1 extracellular domain contains a variable number of tandem repeats (VNTR) of 20 amino acids, which are heavily O-linked glycosylated. Monoclonal antibodies against the MUC1 VNTR are powerful research tools with applications in the diagnosis and treatment of MUC1-expressing cancers. Here, we report direct mass spectrometry-based sequencing of anti-MUC1 hybridoma-derived 139H2 IgG, enabling reverse-engineering of the functional recombinant monoclonal antibody. The crystal structure of the 139H2 Fab fragment in complex with the MUC1 epitope was solved, revealing the molecular basis of 139H2 binding specificity to MUC1 and its tolerance to O-glycosylation of the VNTR. The available sequence of 139H2 will allow further development of MUC1-related diagnostic, targeting, and treatment strategies.