Development of novel methods for non-canonical myeloma protein analysis with an innovative adaptation of immunofixation electrophoresis, native top-down mass spectrometry, and middle-down de novo sequencing

OBJECTIVES: Multiple myeloma (MM) is a malignant plasma cell neoplasm, requiring the integration of clinical examination, laboratory and radiological investigations for diagnosis. Detection and isotypic identification of the monoclonal protein(s) and measurement of other relevant biomarkers in serum and urine are pivotal analyses. However, occasionally this approach fails to characterize complex protein signatures. Here we describe the development and application of next generation mass spectrometry (MS) techniques, and a novel adaptation of immunofixation, to interrogate non-canonical monoclonal immunoproteins. METHODS: Immunoprecipitation immunofixation (IP-IFE) was performed on a Sebia Hydrasys Scan2. Middle-down de novo sequencing and native MS were performed with multiple instruments (21T FT-ICR, Q Exactive HF, Orbitrap Fusion Lumos, and Orbitrap Eclipse). Post-acquisition data analysis was performed using Xcalibur Qual Browser, ProSight Lite, and TDValidator. RESULTS: We adapted a novel variation of immunofixation electrophoresis (IFE) with an antibody-specific immunosubtraction step, providing insight into the clonal signature of gamma-zone monoclonal immunoglobulin (M-protein) species. We developed and applied advanced mass spectrometric techniques such as middle-down de novo sequencing to attain in-depth characterization of the primary sequence of an M-protein. Quaternary structures of M-proteins were elucidated by native MS, revealing a previously unprecedented non-covalently associated hetero-tetrameric immunoglobulin. CONCLUSIONS: Next generation proteomic solutions offer great potential for characterizing complex protein structures and may eventually replace current electrophoretic approaches for the identification and quantification of M-proteins. They can also contribute to greater understanding of MM pathogenesis, enabling classification of patients into new subtypes, improved risk stratification and the potential to inform decisions on future personalized treatment modalities

It is time for top-down venomics

Abstract The protein composition of animal venoms is usually determined by peptide-centric proteomics approaches (bottom-up proteomics). However, this technique cannot, in most cases, distinguish among toxin proteoforms, herein called toxiforms, because of the protein inference problem. Top-down proteomics (TDP) analyzes intact proteins without digestion and provides high quality data to identify and characterize toxiforms. Denaturing top-down proteomics is the most disseminated subarea of TDP, which performs qualitative and quantitative analyzes of proteoforms up to ~30 kDa in high-throughput and automated fashion. On the other hand, native top-down proteomics provides access to information on large proteins (> 50 kDA) and protein interactions preserving non-covalent bonds and physiological complex stoichiometry. The use of native and denaturing top-down venomics introduced novel and useful techniques to toxinology, allowing an unprecedented characterization of venom proteins and protein complexes at the toxiform level. The collected data contribute to a deep understanding of venom natural history, open new possibilities to study the toxin evolution, and help in the development of better biotherapeutics

Mapping Proteoforms and Protein Complexes From King Cobra Venom Using Both Denaturing and Native Top-down Proteomics

Typical urban development under Stalin; Stalinist architecture is a stylistic term referring to architecture built from the 1930s to the 1950s under Stalin’s regime in the USSR and to comparable architecture built in Warsaw Pact countries after World War II. It is characterized by its orientation towards a classical tradition, its monumentality and its representational ornament. Towards the end of the 1950s the style was gradually abandoned because it was considered uneconomical. Source: Grove Art Online; http://www.oxfordartonline.com/ (accessed 5/13/2009

Seeing beyond the tip of the iceberg: A deep analysis of the venome of the Brazilian Rattlesnake, Crotalus durissus terrificus

Submitted by Manoel Barata ([email protected]) on 2017-10-04T13:06:16Z No. of bitstreams: 1 melaniSeeingok.pdf: 2022243 bytes, checksum: af40fd146ab51b3642423c42bdca7a74 (MD5)Approved for entry into archive by Manoel Barata ([email protected]) on 2017-10-05T13:23:19Z (GMT) No. of bitstreams: 1 melaniSeeingok.pdf: 2022243 bytes, checksum: af40fd146ab51b3642423c42bdca7a74 (MD5)Made available in DSpace on 2017-10-05T13:23:19Z (GMT). No. of bitstreams: 1 melaniSeeingok.pdf: 2022243 bytes, checksum: af40fd146ab51b3642423c42bdca7a74 (MD5) Previous issue date: 2015Universidade Federal do Rio de Janeiro. Departamento de Bioquímica. Rede Proteômica do Rio de Janeiro. Unidade Proteômica. Rio de Janeiro, RJ, Brasil.Universidade Federal do Rio de Janeiro. Departamento de Bioquímica. Rede Proteômica do Rio de Janeiro. Unidade Proteômica. Rio de Janeiro, RJ, Brasil.Fundação Oswaldo Cruz. Instituto Carlos Chagas. Laboratório de Proteômica e Engenharia de Proteínas. Curitiba, PR, Brasil.Universidade Federal do Rio de Janeiro. Departamento de Bioquímica. Rede Proteômica do Rio de Janeiro. Unidade Proteômica. Rio de Janeiro, RJ, Brasil.Universidade Federal do Rio de Janeiro. Departamento de Bioquímica. Rede Proteômica do Rio de Janeiro. Unidade Proteômica. Rio de Janeiro, RJ, Brasil.Universidade Federal do Rio de Janeiro. Departamento de Bioquímica. Rede Proteômica do Rio de Janeiro. Unidade Proteômica. Rio de Janeiro, RJ, Brasil.Universidade Federal do Rio de Janeiro. Departamento de Bioquímica. Rede Proteômica do Rio de Janeiro. Unidade Proteômica. Rio de Janeiro, RJ, Brasil.The complete characterization of the snake venom protein components is a requirement for a systems-wide understanding of their biological context. In this work, we provide a deep proteomic characterization of Crotalus durissus terrificus venom using different bottom-up approaches. We identified more than five times more protein families than the sum of all identifications previously reported. For the first time in this sub-species, we report the identification of three new toxin families: CRISP, phospholipase-B, and SVVEGF. This work also describes proteins involved in regulation of toxin synthesis and processing that are present in venom

Deeper Protein Identification by Using FAIMS in Top-down Proteomics

Field Asymmetric Ion Mobility Spectrometry (FAIMS), when used in proteomics studies, provides superior selectivity, and enables more proteins to be identified by providing additional gas phase separation. Here, we tested the performance of cylindrical FAIMS for the identification and characterization of proteoforms by top-down mass spectrometry of heterogeneous protein mixtures. Combining FAIMS with chromatographic separation resulted in a 62% increase in protein identifications and an 8% increase in proteoform identifications as compared to samples analyzed without FAIMS. This increase was attributable, in part, to improved signal-to-noise for proteoforms with similar retention times. Additionally, our results show that the optimal compensation voltage of any given proteoform was correlated with the molecular weight of the analyte. Collectively these results suggest that the addition of FAIMS can enhance top-down proteomics in both discovery and targeted applications. </div

Divergent Antibody Repertoires Found for Omicron versus Wuhan SARS-CoV‑2 Strains Using Ig-MS

SARS-CoV-2 Omicron (B.1.1.529) and its subvariants are currently the most common variants of concern worldwide, featuring numerous mutations in the spike protein and elsewhere that collectively make Omicron variants more transmissible and more resistant to antibody-mediated neutralization provided by vaccination, previous infections, and monoclonal antibody therapies than their predecessors. We recently reported the creation and characterization of Ig-MS, a new mass spectrometry-based serology platform that can define the repertoire of antibodies against an antigen of interest at single proteoform resolution. Here, we applied Ig-MS to investigate the evolution of plasma antibody repertoires against the receptor-binding domain (RBD) of SARS-CoV-2 in response to the booster shot and natural viral infection. We also assessed the capacity for antibody repertoires generated in response to vaccination and/or infection with the Omicron variant to bind to both Wuhan- and Omicron-RBDs. Our results show that (1) the booster increases antibody titers against both Wuhan- and Omicron- RBDs and elicits an Omicron-specific response and (2) vaccination and infection act synergistically in generating anti-RBD antibody repertoires able to bind both Wuhan- and Omicron-RBDs with variant-specific antibodies

Automated imaging and identification of proteoforms directly from ovarian cancer tissue

Abstract The molecular identification of tissue proteoforms by top-down mass spectrometry (TDMS) is significantly limited by throughput and dynamic range. We introduce AutoPiMS, a single-ion MS based multiplexed workflow for top-down tandem MS (MS2) directly from tissue microenvironments in a semi-automated manner. AutoPiMS directly off human ovarian cancer sections allowed for MS2 identification of 73 proteoforms up to 54 kDa at a rate of <1 min per proteoform. AutoPiMS is directly interfaced with multifaceted proteoform imaging MS data modalities for the identification of proteoform signatures in tumor and stromal regions in ovarian cancer biopsies. From a total of ~1000 proteoforms detected by region-of-interest label-free quantitation, we discover 303 differential proteoforms in stroma versus tumor from the same patient. 14 of the top proteoform signatures are corroborated by MSI at 20 micron resolution including the differential localization of methylated forms of CRIP1, indicating the importance of proteoform-enabled spatial biology in ovarian cancer