Carina Sihlbom Wallem’s team at the Proteomics Core Facility, University of Gothenburg (Sweden)—a part of BioMS and SciLifeLab—was seeking a robust and user-friendly solution for comprehensive plasma profiling. Their objective was to implement a platform capable of efficiently and cost-effectively processing large-scale sample sets, while maintaining high standards of data quality and reproducibility.
Biognosys’ P2 Enrichment System is transforming plasma proteomics by enabling deep profiling of low-abundance proteins in human plasma and other biofluids. Powered by proprietary enrichment particles and optimized reagents, the system delivers exceptional plasma depth, reproducibility, and high-throughput performance—making it ideally suited for large-cohort studies.
The team at the University of Gothenburg engaged in detailed discussions with Biognosys to explore the potential of implementing the P2 Enrichment System in their core facility. Following a comprehensive evaluation, they chose to proceed with the adoption of the platform. Below, Carina Sihlbom Wallem, Head of Unit at the Proteomics Core Facility, shares her firsthand experience with the implementation process.
Can you tell us about your organization and the mission that drives your work?
We are an open-access academic facility specializing in advanced mass spectrometry-based proteomics, including the analysis of post-translational modifications and protein quantification. It is incredibly rewarding to contribute to cutting-edge research projects, and I am particularly passionate about leveraging the latest technological advancements. This field thrives on continuous innovation.
What key benefits does P2 bring to your customers, and how does it enhance your existing plasma proteomics offering?
Our goal is always to detect as many proteins as possible. Many disease-related biomarkers remain elusive due to their low abundance, so increasing the number of quantifiable circulating proteins is crucial. The P2 platform enables comprehensive, unbiased protein discovery at a cost-effective rate for users.
Can you walk us through how you implemented P2 in your lab and what the role of the Biognosys implementation team was in this process?
Before implementation, we held several productive virtual meetings to discuss the methodology, protocols, and required materials. Our samples were initially analyzed at Biognosys, followed by an on-site visit from the project manager. During this visit, the same samples were processed and analyzed in our facility under the guidance of the implementation team. The entire process was expertly coordinated, meeting our expectations and demonstrating the team’s high level of competence.
Did you know that the first mass spectrometer was built in 1912? A lot has changed since then.
Even in the 21st century, with the possibility to “just Google it!”, there are still many misconceptions around MS. In this article, we collect the top 7 facts about modern mass spectrometry (MS) that you might not know. So, let’s find out what MS has to offer and bust the myths surrounding this technology.
One of the first myths that needs to be debunked is about sensitivity.
In the past, MS had a bad reputation for being less sensitive than other proteomics methods. However, technological improvements mean that one can now achieve much higher dynamic range sensitivity with MS, rivaling and in some cases improving on affinity-based assays.
Recent years have seen 10- to 100-fold increases in the sensitivity of liquid chromatography-mass spectrometry (LC-MS). This is mostly thanks to advances in chromatography performance, which has tripled over the past 10 years, as well as improvements to the MS instruments.
Targeted proteomics quantification with high-resolution Parallel Reaction Monitoring (PRM) is now possible with a mass accuracy in the 1 ppm range. This technology now rivals or even exceeds traditional antibody-based approaches, such as immunohistochemistry (IHC) and enzyme-linked immunosorbent assay (ELISAs), in the clinical setting.
MS can now quantify a larger number of proteins per sample than other techniques. While the highest-end antibody-based approach can identify and quantify around 3,000 proteins in plasma, for MS, the depth of coverage of cutting-edge technology platforms now extends to 4,200 proteins in blood plasma, 11,000 in other biofluids, and 13,800 in tissue.
Specificity is an area where you can be confident that MS will deliver.
Unlike affinity-based approaches which are dependent on the availability and specificity of reagents that function as proxies, MS is a physical method that directly measures the presence and quantity of specific proteins.
With the latest MS technology, one can measure 10 peptides per protein on average, offering robust quantitation of hundreds of thousands of peptides per sample.
MS also works across different species and sample types, from cultured cells to tissue biopsies, blood plasma, cerebrospinal fluid, and more. This is in contrast with many affinity-based proteomics approaches, which are confined to plasma.
And while the binding specificity of affinity reagents can be affected by the functional state of the protein and modifications such as phosphorylation, MS can identify and quantitate proteoforms and modifications across the whole proteome, providing valuable functional data.
In the past, poor reproducibility has confined MS mainly to basic research or small-scale studies in the early stages of drug development.
However, advances in instrumentation and analysis mean that data acquired by MS is now highly reproducible, and pharmaceutical companies routinely use the technique for biomarker measurements in the clinical setting.
Parameters used to assess reproducibility, such as the coefficient of variation (CV), are comparable between MS and affinity-based approaches.
MS offers high reproducibility across multiple samples and time points, which is great for large-scale cohort studies and clinical trials, and is directly transferable across all stages of the R&D pipeline.
MS has historically been expensive to access and kept in the hands of just a few experts. This is changing fast, and MS is now more accessible than ever before.
The costs for scaling up MS are not affected by the need to develop and manufacture reagents such as antibodies. This means the benefits from automation and optimization are more striking than affinity-based assays.
In practical terms, this means more data can be collected for the same cost, and this is likely to become even more economical in the future.
When it comes to clinical research, it is important not only to be able to perform large-scale studies but also to execute them within a reasonable timeframe. MS has historically been perceived as slow and small-scale, but with improvements in workflows, automation, and parallelization, this is no longer the case.
Commercial labs with large, modern MS facilities and extensive expertise in large-scale proteomics can now routinely run 10,000 samples per study at high throughput.
The white paper, ‘Accelerating Biomarker Discovery With Large-Scale Plasma Proteomics’, explains in more detail how advances in mass spectrometry are powering large-scale studies in plasma, providing crucial insights for biomarker discovery and drug development.
Direct measurement technologies like MS have traditionally required relatively large sample sizes to achieve sufficient proteome coverage.
Advances in MS technology, such as the shift from data-dependent acquisition (DDA) to data-independent acquisition (DIA) methods that boost the signal from less abundant molecules, have greatly increased the amount of information that can be gathered from each sample.
This increasing specificity and sensitivity mean that the input material needed for MS has shrunk dramatically and is now in line with the smallest samples that can be collected from a patient.
Discovery proteomics can be done from as little as 1 mg of fresh frozen tissue or 10 μl of plasma or serum. For immunopeptidomics studies, cutting-edge workflows can quantify 10,000 immunopeptides from as little as 15 mg of tissue or 6,000 immunopeptides from 2,500 cells.
Looking ahead, advances in single-cell proteomics show that around 1,500 proteins can now be profiled from just one cell [2].
Data analysis has often been seen as a major challenge for MS, particularly for DIA approaches that result in complex fragmentation spectra and highly rich datasets.
However, advances in specialized analytical software, such as the tools pioneered by Biognosys, are allowing users to get more from their datasets than ever before.
Today’s sophisticated machine learning algorithms can pull meaningful biological insights from complex proteomic data in a user-friendly format, making this powerful technology accessible to more researchers and across a wide range of study sizes.
Together, these seven facts consign misconceptions about MS to the history books. From sensitivity and reproducibility to cost and sample requirements, MS has come a long way since its invention and now offers capabilities outstripping its rivals.
MS – and especially the DIA technology pioneered by Biognosys – is now the method of choice at all stages of the drug development pipeline, from target discovery through to large-scale biomarker studies.
Success in MS proteomics needs quality, scale, and affordability. If you can generate high-quality data at the scale required to generate true insights and at an affordable cost, you are well on the way.
At Biognosys, we have mastered these three core pillars of proteomics success, using the latest generation of mass spectrometers to help you to get the most out of your precious samples.
Thanks to AI augmentation, our Spectronaut® data analysis software offers deeper proteome coverage than any other DIA solution on the market and can analyze several thousands of proteins in a single experiment.
Our TrueDiscovery™ platform – powered by Spectronaut AI – makes this ultra-deep proteome coverage available as a research service at an attractive price, whatever your requirements.
And our TrueSignature™ biomarker panels based on high-resolution Parallel Reaction Monitoring (PRM) enable insights from discovery to be leveraged into targeted approaches to transform clinical research and precision medicine.
But we offer more than just technology. Our knowledge in proteomics and expertise with study design and data interpretation will help you to get more from your data than ever before.
We offer consultative study design to ensure the best outcomes and work closely with you to deliver meaningful insights. We also offer designated scientific project managers, who act as extended lab members and provide you with the support you need to get the most out of your data.
Talk to our experts today to discover how our proteomics solutions can help supercharge your research.
References
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