Publications

This study evaluates Seer’s multi nanoparticles- based Proteograph workflow performance compared to neat plasma workflow in capturing glycoproteins and a conventional glycol-enrichment workflow using magnetic Fe-NTA beads. This poster demonstrates how by compressing the dynamic range and making the low abundance proteins and corresponding peptides more visible to the downstream LC-MS, nanoparticles can facilitate the detection of peptides with increased sensitivity and more efficiency, significantly enhancing the coverage of these proteins in blood plasma even without subsequent enrichment.

This poster demonstrates how nanoparticle coronas provide deep coverage of biological content, including the identification of low abundant cytokines and chemokines, and post-translationally modified peptides. Understanding the nanoparticle-protein interactions on the quantitative level enables the design of NP-based assays to interrogate specific physicochemical fraction of the proteome occupied by hundreds to thousands of proteoforms.

This poster highlights current challenges in large-scale DIA data analysis and evaluates the impact of various spectral library approaches. The study leverages the Proteograph workflow and Bruker timsTOF platforms to investigate ~900 patient serum samples with controls.

This poster demonstrates how the Proteograph workflow enables, deep, and rapid multi-omic analysis of plasma in a study that resulted in ~5X better protein groups coverage versus neat plasma digestion workflow with a single injection DDA LC-MS workflow with FAIMS Pro interface on the Orbitrap MS system.

This poster demonstrates the deployment of well-established community accepted LC-MS algorithms in a smart cloud infrastructure to enable large-scale proteomics data analysis not possible in desktop environments. Seer's data analysis platform cost-effectively scales up to tens of thousands of samples in a single aggregate analysis. The challenges of cross-file analysis are addressed using the distributed processing ecosystem such as Apache Spark, Databricks and Delta Lake. Here we demonstrate proof of concept using peptide-centric approaches to re-interrogate raw signals using such an ecosystem for ultra-fast signal detection of terabytes of data in minutes, extending the microservice architecture as well as employ

This poster demonstrates the utility of the Proteograph™ Product Suite workflow to conduct unbiased, deep, and rapid interrogation of the plasma proteome and to enable large-scale studies to detect novel biological insights. Plasma samples from 100 Alzheimer and 100 healthy matched controls, 1000 injections, and 5,000+ protein groups were analyzed in three weeks using a multi-nanoparticle workflow combined with LC-MS analysis. Classification analysis and pQTL mapping enabled the identification of known and novel plasma biomarkers and showed enrichment for disease-relevant pathways.

This poster demonstrates how the Proteograph™ Product Suite enables deep, unbiased, rapid, and scalable access to the plasma proteome. The study shows the power of the Proteograph in a proof-of-concept proteoform analysis of 80 healthy controls and 61 early-stage non-small-cell lung cancer (NSCLC) samples to infer proteoforms derived from alternative gene splicing or post-translational cleavage. We identified 20 proteoform candidates, including four that showed differential abundance between NSCLC and control samples. This peptide-centric analyses revealed disease-associated proteoforms that were masked with protein-centric analyses.

This poster demonstrates how the Proteograph™ Analysis Suite and Proteogenomics workflow enables user-friendly and reproducible multi-omics analyses of proteomic and genomic data at scale. PAS provides automated data processing and analysis with intuitive, easy-to-interpret visualizations and its Proteogenomics feature integrates genomic variant calls with proteomics data to identify subject-specific variant peptides, offering a comprehensive proteogenomic analysis software suite that facilitates a seamless journey from raw data to biological insight.

This poster demonstrates ultra-high coverage of serum proteins with over 5,000 protein groups identified in a 105-sample cohort and over 3,000 protein groups identified on average per sample. Proteins were quantified at 3-5 fold higher levels compared to depleted and un-depleted serum, with 30% enhanced coverage of low abundant cytokines. This data supports a comprehensive serum proteomics workflow that can be used for patient stratification as well as potential identification of novel biomarkers which are not accessible through other strategies.

This poster describes a multi-omics platform facilitating the evaluation of the global proteome and lipidome in a pancreatic cancer cohort and identified multiple putative biomarker candidates across analyte classes for early disease detection.