23rd Human Proteome Organization World Congress

Prof.

Molecular health perspectives from self-sampled circulating proteomes

Keynote Lecture

Recent advancements in proteomics technologies have made it possible to analyze thousands of blood proteins across thousands of samples, significantly enhancing expectations for breakthroughs in precision medicine. However, despite the influx of new molecular health data, distinguishing observational associations from actionable links remains crucial for translating this new knowledge into clinically relevant information about human biology.This presentation details our research approaches to the dynamic architecture of circulating proteins as they can be associated with various human phenotypes, health status, and disease risks. The talk will also present our work studying the impact of medication use on these data. Beyond the established biobanks of liquids, we will discuss the innovative approach of self-sampling blood, enabling the exploration of population health beyond traditional hospital environments. This &quot;new&quot; sample type can simplify continuous blood collection at home, offering new immune and health monitoring opportunities.For proteomics-informed precision medicine to be realized, future efforts must prioritize improved management of pre-analytical factors, a deeper understanding of technology-centric insights, and greater emphasis on the conditions of donors at the time of sampling. As multi-modal data from novel study designs and diverse sample types emerge, there is a pressing need for data-driven approaches to learn from the community data and effectively address the heterogeneity present at baseline and throughout the longitudinal monitoring of phenotypes.

Keynote lecture

Assoc. Professor

Single-cell molecular pixelation of CAR T-cell surface proteome reveals spatial patterns characteristic of chronic stimulation

New Technology: Non MS-based Proteomics

Customized immunotherapies using CAR T-cells are already making their way into the clinic and are showing much promise for the treatment of cancers including leukemia. However, stimulating CAR T-cells against the target antigen, such as that presented on a tumor, has the challenge that chronic stimulation leads to deterioration of the treatment potential of the CAR T-cells. Identifying the effects of chronic stimulation is currently challenging, making it difficult to select CAR T-cells that are effective for treatment. We applied a recently developed antibody-based spatial profiling technique for characterizing the surface proteome, named molecular pixelation, to determine characteristic surface-based signatures of chronic CAR T-cell stimulation. This technique uses DNA-conjugated antibodies against 80 markers, 4 controls and 76 target proteins, and two rounds of gap-fill ligation and rolling circle amplification to determine the relative position of the protein molecules on the surface of a cell. We analyzed 8504 CAR T-cells at a single-cell level, collected from 3 donors and stimulated once for acutely stimulated cells and stimulated repeatedly over 14 days for chronically stimulated cells, followed by selection for live cells and a surface-based marker NGFR indicating the expression of the CAR construct. The sequencing counts that correspond to individual antibodies allow us to distinguish acutely and chronically stimulated cells, and the molecular pixelation protocol allows us to identify polarization and colocalization of the markers on the cell surface. A total of 33 of the 76 proteins (43.4%) exhibited significant changes in polarization, and there was an overall increase in polarization after chronic stimulation. Significant colocalization changes were observed for 561 proteins (19.7% of all 2850 combinations); one particular colocalization event that stood out was CD37/CD82, which increased significantly after chronic stimulation (adjusted p-value &lt; 1e-250). Molecular pixelation is a new spatial proteomics technique for the discovery of proteomic polarization and colocalization on the cell surface that can identify new types of biomarker candidates, such as were identified for chronically stimulated T-cells in this study.

Oral presentation

Sensitivity and dynamic range of massively parallel single-molecule protein quantitation using protein identification by short-epitope mapping (PrISM)

Many biological processes in the cell are driven by protein abundance changes across the full complement of the cellular proteome. Detection of those changes requires a proteomic measurement capable of detecting minute changes in protein abundance simultaneously with high-abundance protein changes. Protein Identification by Short-epitope Mapping (PrISM) is a novel single-molecule based proteome analysis approach that may enable identification and quantification of nearly the entire human proteome in a single experiment.Here we assess the dynamic range associated with the PrISM approach utilizing a simple mixture of standard proteins. Two proteins from a twenty-one protein standard mixture were deposited in separate control lanes on the flow cell and in a sample lane as part of the twenty-one protein mixture. In a second set of lanes, the two proteins were varied over multiple orders of magnitude. PrISM data were acquired on the flow cell using 150 sequential incubate/rinse/image/remove cycles with 50 multi-affinity probes. Frequency of binding of the probes to the standard proteins in the control lanes compounded over multiple cycles of measurement provided the basis for confident identification and quantification of the two proteins in the sample lane. The results indicate that the two standard proteins were reproducibly quantified over multiple orders of magnitude in the presence of the mixture with one standard varying as much as one million fold vs the other standard. We also demonstrate that the protein decoding signal has a wider dynamic range than quantitation from any single multi-affinity probe due to the ability of the decode algorithm to increase the fidelity of quantitation by accumulating information across multiple multi-affinity probes measurement events. Furthermore, we demonstrate assay sensitivity into the yoctomole range. These attributes showcase the platform's robust capability for precise and sensitive quantification of protein variations in complex biological samples.

Resolving spectral congestion of (any?) intact glycoprotein using DIA-PTCR

New Technology: MS-based Proteomics

The molecular complexity of proteins with multiple glycosylation sites challenges traditional analytical methods for intact mass analysis. Glycans play a pivotal role in defining the functional and structural properties of proteins; however, their biosynthesis is not template-driven and are thereby (rather unpredictably) structurally diverse. This inherent molecular diversity impedes thorough characterization using only mass spectrometry (MS) or other conventional techniques, especially for the purposes of assigning function to glycoforms subpopulations or individual proteoforms. Current approaches to analyzing heterogeneous glycoprotein samples, such as those involving biotherapeutics or in targeted structural/glycobiological studies, involve fragment measurements or partial digestion of glycans.In our recent Nature Communications publication (4/2024), we present a streamlined workflow for the direct, intact analysis of heterogeneous proteins that have previously posed challenges for intact MS characterization. This innovative method, termed "DIA-PTCR," employs a data-independent approach to analyze intact glycoproteins and non-covalent complexes using proton-transfer charge-reduction tandem MS (PTCR).Owing to the high-mass range quadrupole of the new Ascend Orbitrap platform, which can isolate ions up to 8000 m/z with an exceptionally narrow m/z window, DIA-PTCR provides mass information on spectrally unresolvable proteins without the need for denaturation, upfront digestion, or separation.We tested the approach on various heavily glycosylated molecules, including cytokines, TNF-fusions, and peptide-bound MHC class II complexes to demonstrate efficacy in measuring their proteoform-level diversity while also retaining information about non-covalent structure, co-occurrence of glycans and other PTMs such as phosphorylation and acetylation. We observed subunit truncations, differential glycosylation between samples, and were able confirm subunit assembly in the midst of extreme proteoform diversity.Additionally, we establish a bioinformatic data analysis strategy for DIA-PTCR that may offer insights into glycan composition. Due to the staggering combinatorial diversity of glycosylation, probable annotations for detected intact masses –reflecting the limited set of glycan combinations– were modeled using validated glycan candidates from glycopeptide and glycomic data, providing relative abundances of putative glycoforms for each DIA-PTCR molecular weight. Notably, we inferred the glycoform abundances for hundreds of molecular weights for the eight-times glycosylated cytokine IL22-Fc dimer, enabling correlations between sialylated glycoform sub-populations and their interaction with the IL22 receptor.Further development of the DIA-PTCR workflow may incorporate top-down fragmentation for glycoform characterization as well analysis of immuno-enriched glycoproteins to elucidate the network of readers, writers and erasers of glycosylation.

Session
Technological advancements

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Vorsitzende

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SessionTechnological advancements

Termin

Vorsitzende

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Session
Technological advancements