Longitudinal Assessment of Nasopharyngeal Biomarkers Post-COVID-19: Unveiling Persistent Markers and Severity Correlations
Redondo-Calvo et al. Journal of Proteome Research October 2024
Although COVID-19 has become less notable in recent months it remains one of the most widespread and well-researched events in recent memory. We know that in some cases, there are indeed long-term physiological after-effects. Could there still be traces at the protein level years later for moderate or even mild cases of infection? This study focuses on identifying long-term nasopharyngeal biomarkers in patients two years post-COVID-19 recovery. Using DIA-based approaches, it reveals 371 proteins linked to the infection’s severity and persistence. By analyzing these proteins, the research uncovered pathways reflecting prolonged immune and metabolic disturbances caused by COVID-19. Notably, it identified persistent protein signatures in patients recovering from both mild and severe symptoms, offering insights into long-term molecular effects.
Spectronaut software was used in this work to distinguish true biomarkers from the challenging clinical samples; providing reproducible quantification, and enabling precise biomarker detection. This contribution ensured the robustness and reliability of the findings.
This research highlights the hidden molecular aftermath of COVID-19. It underscores the need for ongoing monitoring of recovered patients and aids in developing predictive tools and tailored therapies, particularly for long-COVID sufferers.
Assessment of Data-Independent Acquisition Mass Spectrometry (DIA-MS) for the Identification of Single Amino Acid Variants
Fierro-Monti et al. Proteomes November 2024
Proteogenomics, which combines genomic and proteomic data, faces challenges in identifying single amino acid variants (SAAVs) due to incomplete databases, expanded search spaces, and overlapping spectra. DIA-MS has proven effective for SAAV identification, offering reproducibility and broad proteome coverage. Despite these challenges the promise of a complete biological picture integrating multiple -omics data remains attractive.
This analysis showcased the complexities of detecting SAAVs, such as distinguishing them from wild-type peptides and accounting for factors like allelic imbalance, low variant expression, and altered proteolytic efficiencies. By incorporating advanced computational strategies, including entrapment databases and improved scoring algorithms, Spectronaut enhanced error estimation and provided reliable peptide-spectrum matches, ensuring high confidence in SAAV identification.
Simultaneous targeted and discovery-driven clinical proteotyping using hybrid-PRM/DIA
Goetze et al. Clinical Proteomics April 2024
Have you ever been in the stressful situation where you only have enough sample for a few injections or a sample that will only be stable for a few hours? What if there was a method that would allow you to get enough data from that precious sample to answer multiple questions from a single run? This study explores an innovative hybrid-PRM/DIA method, which combines targeted and discovery-driven proteomics to enhance the analysis of clinical samples. Building on the strengths of both PRM and DIA approaches this new method improves the detection and quantification of low-abundance proteins, crucial for clinical diagnostics. By integrating parallel reaction monitoring (PRM) with data-independent acquisition (DIA), the hybrid approach offers both comprehensive proteome profiling and precise measurement of specific protein markers.
Spectronaut software plays a pivotal role in this process by analyzing DIA data, ensuring accurate quantification and identification of peptides. The software’s advanced algorithms enhance the sensitivity and reproducibility of the measurements, making it a valuable tool for clinical proteotyping. This approach was validated using melanoma samples, demonstrating its potential to provide actionable insights for clinical decision-making and future research.
This hybrid method represents a significant advancement in proteomics, offering a robust solution for the comprehensive analysis of precious clinical samples which can often only be analyzed once.
Scalable single cell analysis towards 1000 samples per day using the Evosep whisper zoom methods on the timsTOF Ultra2
Krisp et al. HUPO World Congress 2024
In this application poster researchers at Bruker and Evosep have developed two innovative strategies to tackle one of the most critical problems in modern single cell research: how to efficiently analyze individual cells at a routine scale.
The first approach (label free) focuses on increasing sample throughput using the diaPASEF (data-independent acquisition Parallel Accumulation Serial Fragmentation) method. By integrating Spectronaut’s directDIA+ algorithm with cellenONE cell isolation technology and the Evosep separation system, they achieved over 120 samples per day (SPD) when analyzing single cells on the Bruker timsTOF Ultra2 mass spectrometer.
Their second strategy pushed the boundaries even further. Using a multiplexed labeling technique with ddaPASEF (data-dependent acquisition PASEF), they dramatically increased throughput to more than 1,000 samples per day. Critical to this process was SpectroMine for analyzing the TMT labeled data and pyDIAid for optimizing mass spectrometry window placement. This work represents an enlightening look into two approaches highlighting innovation in the field of single-cell proteomics.
One-Tip enables comprehensive proteome coverage in minimal cells and single zygotes
Ye et al. Nature Communications April 2024
Here is another approach to simplifying single-cell analysis, this time the authors address the traditionally complex and labor-intensive sample preparation process. This study introduces the One-Tip workflow, a method for high-throughput proteomics with minimal hands-on time, offering both efficiency and depth of analysis. By streamlining sample preparation into only two pipetting steps, it achieves precise quantification and comprehensive proteome coverage. One-Tip enables the identification of over 9,000 proteins from as few as 1,000 HeLa cells and over 3,000 proteins from single cells or extracellular vesicles, showcasing unparalleled sensitivity. The incorporation of Spectronaut software significantly enhances data processing through spectral library-free analysis, ensuring accurate quantification. This method addresses longstanding challenges in proteomics, including sample loss, complexity, and scalability. Its flexibility from single-cell to bulk applications, including mouse embryonic cells and blood plasma extracellular vesicles, demonstrates its broad utility.
Personalized phosphoproteomics of skeletal muscle insulin resistance and exercise links MINDY1 to insulin action
Needham et al. Cell Metabolism December 2024
Have you ever thought about the impact an active lifestyle or exercise has on human health at the proteome level? This study investigates how insulin resistance affects skeletal muscle signaling and how exercise can counteract these effects. Researchers used advanced mass spectrometry-based phosphoproteomics to analyze over 12,000 phosphopeptides from human muscle biopsies. Spectronaut played a crucial role in this research by enabling the precise quantification and analysis of these phosphopeptides, thus facilitating the identification of key signaling alterations.
The findings revealed that insulin resistance selectively impairs certain signaling pathways, while exercise can “prime” these pathways to improve insulin sensitivity. This research enhances our understanding of the molecular mechanisms underlying insulin resistance and highlights the potential of exercise as a therapeutic strategy. Spectronaut’s contribution was pivotal in accurately measuring and interpreting the complex data, thereby advancing the study’s main goal of elucidating the biological significance of protein modifications in insulin resistance and exercise.
µPhos: a scalable and sensitive platform for high-dimensional phosphoproteomics
Oliinyk et al. Molecular Systems Biology August 2024
Continuing on the theme of method development, this paper aims to streamline phosphoproteomics analysis by introducing a DIA based approach for high-throughput of low-input phosphor-enriched samples. The authors introduce µPhos, a scalable and sensitive platform for high-dimensional phosphoproteomics, optimized for analyzing limited biological samples with unprecedented depth and efficiency. The µPhos workflow combines low-volume cell lysis and streamlined phosphopeptide enrichment in a 96-well plate format, enabling processing of 96 samples within a single working day. It achieves over 30,000 unique phosphosite identifications from as little as 1 µg of starting material, making it highly suited for resource-limited applications.
Spectronaut software was instrumental in achieving the study’s goals by leveraging library-free DIA analysis to improve phosphosite localization and quantification, ensuring accurate results even at low input levels. By coupling the workflow with advanced mass spectrometry, the study enabled high-dimensional perturbation experiments, uncovering time-resolved drug-specific phosphoproteome signatures. The platform’s scalability, sensitivity, and reproducibility advance educational access to phosphoproteomics, offering new opportunities for studying cellular signaling and disease mechanisms.
In-Depth Host Cell Protein Analysis and Viral Protein Impurity Monitoring in Adeno-Associated Virus-Based Gene Therapy Products Using Optimized Wide Window Data-Dependent Acquisition Method
Huo et al. Analytical Chemistry September 2024
Sometimes the background is the target of the experiment. Especially when that background contains off-target species contaminating drug product precursors.
This study presents a novel analytical workflow for in-depth host cell protein (HCP) and viral impurity analysis in adeno-associated virus (AAV)-based gene therapies. By combining wide-window data-dependent acquisition (WWA) with SP3-based sample preparation, the method achieves exceptional sensitivity, detecting over 650 HCPs—a 5.4-fold improvement compared to traditional approaches. It identifies low-abundance HCPs and process-related viral proteins such as Rep 78 and E4, which pose immunogenic risks. The integration of Spectronaut further complements the workflow by enhancing the identification and quantification of impurities with robust accuracy.
The approach achieves quantitative reproducibility and a detection limit of 0.06 ng/mL, enabling comprehensive impurity profiling across AAV serotypes. With its AI-based spectrum analysis and streamlined sample preparation, this method enhances accessibility to complex proteomic data, providing a benchmark for both academic and industrial quality control in AAV therapeutic development.
Deep Proteome Analysis of Cerebrospinal Fluid from Pediatric Patients with Central Nervous System Cancer
Mirian et al. Journal of Proteome Research October 2024
In this paper focused on clinical research Mirian et al. optimized cerebrospinal fluid (CSF) analysis for pediatric central nervous system (CNS) cancer.
The study enhances cerebrospinal fluid (CSF) proteome analysis for pediatric central nervous system (CNS) cancers by delivering both speed and depth. Using advanced DIA-MS coupled to sequential ultracentrifugation for extracellular vesicle (EV) enrichment, the optimized method quantifies up to 2989 proteins—a 340% increase—while requiring only minimal CSF volumes. The workflow achieves rapid analysis with a streamlined 21-minute liquid chromatography gradient, ensuring high-throughput capability without compromising data quality. Spectronaut software enhances this approach by leveraging spectral libraries to maximize protein detection and improve quantification accuracy. By combining fast processing with unparalleled depth, the study addresses challenges like limited sample availability and high dynamic protein range. This enables the detection of critical low-abundance biomarkers, advancing clinical insights into pediatric CNS malignancies and paves the way for improved risk stratification and disease monitoring in pediatric oncology.
These are just a few of the more than 1400 (in 2024 alone) articles mentioning Spectronaut or our other tools. This increasing body of work is evidence that Biognosys software is a critical tool across a diverse range of proteomics applications, enabling discoveries from COVID-19 molecular tracing to single-cell analysis and clinical diagnostics. Its advanced algorithms have transformed complex proteomic challenges into actionable insights for researchers in all arenas of mass spectrometry-driven life science research. As we enter 2025, the software stands poised to continue driving innovative proteomic discoveries that could revolutionize our understanding of biological systems.
