Biognosys in Publications 2023

Biognosys in Publications 2023

Publications Featuring Our Proteomics Analysis Software


Every year, our customers and in-house scientist publish their research in some of the world’s top journals. 2023 was no exception with the total number of publications mentioning our solutions exceeding the 1000 mark. Here, we share a small selection of published papers where our proteomics analysis software Spectronaut played a part in some fascinating scientific discoveries.

Exploration of cell state heterogeneity using single-cell proteomics through sensitivity-tailored data-independent acquisition
Petrosius V et al, Nature Communications 2023

Unveiling the complexities of cellular diversity demands advanced techniques, and single-cell proteomics by Mass Spectrometry (scp-MS) has proved to be a powerful tool to overcome challenges posed by limited cell material. In this study, a research group at DTU focused on orbitrap-based data-independent acquisition (DIA) for limited input material proteomics. By carefully refining a low-input DIA method using high-resolution MS1 quantification they were able to enhance sensitivity, allowing robust proteome profiling. In addition, they showcase the effectiveness of the method by examining the conditions of mouse embryonic stem cell cultures, highlighting the diversity in global proteomes, and emphasizing variations in the expression of key metabolic enzymes within specific cell subclusters.

Hybrid-DIA: intelligent data acquisition integrates targeted and discovery proteomics to analyze phospho-signaling in single spheroids

Matrínez-Val A et al, Nature Communications 2023


Achieving comprehensive coverage of regulatory phosphorylation sites in mass spectrometry (MS)-based proteomics, especially with small sample amounts, has proven to be a significant challenge. To tackle this, Matrínez-Val et al, have introduced a hybrid data-independent acquisition (DIA) strategy (hybrid-DIA) combining targeted and discovery proteomics approaches. In the method, DIA scans are dynamically intercalated with accurate triggering of multiplexed tandem mass spectrometry (MSx) scans of predefined (phospho)peptide targets. The research group evaluated hybrid-DIA by incorporating stable isotope-labeled phosphopeptide standards across seven signaling pathways in EGF-stimulated HeLa cells and compared assay results to established targeted proteomics methods. Hybrid-DIA displayed comparable quantitative accuracy and sensitivity. Retrieval and analysis of DIA data was performed in Speactronaut software and allowed to additionally profile the global phosphoproteome, demonstrating robustness and sensitivity of hybrid-DIA approach. Finally, to demonstrate hybrid-DIA’s biomedical potential they profiled chemotherapeutic agents in single colon carcinoma multicellular spheroids, highlighting phospho-signaling differences between cancer cells in 2D and 3D cultures.


A fully automated FAIMS-DIA mass spectrometry-based proteomic pipeline

Reilly L et al, Cell Reports 2023


This paper introduces a standardized proteomics pipeline for deep cellular proteome analysis using a system that operates seamlessly in a single 96-well plate, ensuring high throughput and scalability. This integrated approach combines automated sample preparation, data-independent acquisition (DIA) with a FAIMS interface, and an optimized library-free DIA database search strategy. The study revealed that a single compensation voltage (CV) at -35 V in FAIMS-DIA achieves the deepest proteome coverage and best correlation with DIA acquired without FAIMS. In depth comparison of DIA analysis tools showed that Spectronaut provides the highest number of quantifiable proteins with directDIA approach. Applying this system to human induced pluripotent stem cell (iPSC)-derived neurons, demonstrated single-shot mass spectrometry with <10% missing values and over 9,000 quantifiable proteins, showcasing its reproducibility and accuracy compared to other tested, commonly used DIA methods.


Data-independent acquisition phosphoproteomics of urinary extracellular vesicles enables renal cell carcinoma grade differentiation

Thadisurya M, et al, Molecular & Cellular Proteomics 2023


Transforming cancer signaling research into clinical applications has proven to be slow, but promising strides have been made with extracellular vesicles (EVs). These tiny vesicles offer a potential source for disease phosphoprotein markers in cancer monitoring. This study presents the development of a robust data-independent acquisition (DIA) method using mass spectrometry to profile urinary EV phosphoproteomics aiming for renal cell cancer (RCC) grade differentiation. The optimized method led to identification of 2,584 unique phosphosites in the EV phosphoproteomes from a cohort of 57 individuals representing different grades of RCC and controlled groups. Notably, cancer-related pathways, including ErbB signaling, renal cell carcinoma, and actin cytoskeleton regulation, were only upregulated in high-grade clear cell RCC. The results highlight the method as a powerful tool for future clinical applications.


A gas phase fractionation acquisition scheme integrating ion mobility for rapid diaPASEF library generation

Penny J et al, Proteomics 2023


When working with complex DIA spectra, a commonly used approach is to analyze them with reference to spectral libraries with the best-established method using offline fractionation to increase depth of coverage. Recently developed approaches, that perform comparably to deep offline fractionation-based libraries, include incorporating gas phase fractionation (GPF). Here, Penny et al present a rapid library generation method using an IM-GPF acquisition scheme in the m/z versus 1/K0 space. Compared to direct deconvolution-based analysis or deep offline fractionation, IM-GPF outperformed, approaching the performance of deep libraries. This establishes IM-GPF as a practical method for rapid library generation in diaPASEF data analysis.


The immunopeptidome landscape associated with T cell infiltration, inflammation and immune editing in lung cancer

Kraemer AI et al, Nature Cancer 2023


Improving personalized cancer immunotherapies faces a key hurdle in patient stratification based on the tumor’s antigenic landscape. While CD3+CD8+ T cell-inflamed tumors often respond better to immune checkpoint inhibitors, the substantial differences in the immunopeptidome repertoire between highly inflamed and noninflamed tumors remain unknown. Surveying 61 tumor regions and adjacent nonmalignant lung tissues from 8 lung cancer patients, Kraemer et al, conducted a thorough antigen discovery using immunopeptidomics, genomics, bulk, and spatial transcriptomics. The study linked diverse immune cell populations to the immunopeptidome, revealing a higher frequency of predicted neoantigens within HLA-I presentation hotspots in CD3+CD8+ T cell-excluded tumors. The authors associated these neoantigens with immune recognition, suggesting their involvement in immune editing, which further presents potential implications for tailoring combination therapies to the patient’s mutanome and immune microenvironment.


Data-independent acquisition boosts quantitative metaproteomics for deep characterization of gut microbiota

Zhao J et al, NPJ Biofilms and Microbiomes 2023


Metaproteomics, offers insights into human gut microbiota (GM) functions but faces challenges due to GM’s inherent complexity. In this study, library-free DIA (directDIA), a method still in early development for metaproteomics was compared with other MS-based quantification methods on simulated microbial communities and feces samples. Spectronaut’s directDIA outperformed in proteome coverage, identification accuracy, and quantification precision. In clinical fecal samples from pancreatic cancer (PC) and mild cognitive impairment (MCI) cohorts, directDIA quantified around 70,000 microbial proteins, revealing taxonomic and functional GM characteristics in different diseases. This showcases how directDIA can be used in quantitative metaproteomics for studying intestinal microbiota and related disease pathogenesis.


Detection of pancreatic ductal adenocarcinoma-associated proteins in serum

Mamie Lih T et al, Molecular & Cellular Proteomics 2023


Pancreatic ductal adenocarcinoma (PDAC) is among the most lethal types of cancer and is often identified once it has reached an advanced inoperable stage. Early detection through minimally invasive means, like blood tests, holds promise for improved outcomes but existing efforts to discover molecular signatures for early PDAC detection in blood have had limited success. This study employed a quantitative glycoproteomic approach using data-independent acquisition mass spectrometry (DIA-MS) identifying 892 N-linked glycopeptides from 141 glycoproteins showing dysregulation in 29 PDAC tissues and sera. Specificity was verified by comparing these glycoproteins in 53 PDAC patient sera and 65 cancer-free controls. The identified glycoproteins serve as potential blood test biomarkers for PDAC detection.


Urine-HILIC: automated sample preparation for bottom-up urinary proteome profiling in clinical proteomics

Govender IS et al, Proteomes 2023


Urine, an easily accessible health indicator, is ideal for clinical proteomics, yet existing methods lack the throughput for large cohorts. Here, Govender et al, introduce a novel workflow, urine-HILIC (uHLC), utilizing on-bead protein capture, cleanup, and digestion without bottleneck steps like precipitation or centrifugation. Tested in an acute kidney injury (AKI) pilot study, the group employed MagReSyn® HILIC microspheres on a KingFisher™ Flex, which outperformed an on-membrane (OM) protocol in terms of ease, hands-on time, and replicability. LCMS analysis revealed 121 significant proteins associated with kidney injury, offering valuable insights for AKI patient urinary proteomics.


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