The MacCoss laboratory is currently offering a number of quantitative proteomics assays as a service. Included in these assays is the recently developed Mag-Net plasma assay using LC-MS. This can be done using small quantities of plasma or serum across multiple species. Click here to contact us and get the process started!


Our Services:

Biofluid Proteomics

Our group has extensive experience applying quantitative proteomics to the analysis of biofluids. Additionally, we have been leaders in the development and application of data independent acquisition-mass spectrometry and targeted proteomics methods.

Plasma/Serum Extracellular Vesicle ProteomicsTo overcome the dynamic range challenges of plasma/serum we have developed a robust platform for the enrichment of extracellular vesicles, protein cleanup, and digestion of proteins for mass spectrometry. Our Mag-Net protocol enables deep and robust quantification of proteins. Our methodology is a promising option to support research projects from clinical samples or experiments in non-human specimens (e.g. mice, dogs, non-human primates, etc... For more details on the Mag-Net method and for frequently asked questions, please refer to the following sections:



Unfractionated Plasma, Serum, or Cerebrospinal Fluid (CSF) While dynamic range and coverage of biofluids is important, we recognize that it is a subfraction and some will prefer a quantitative measurement that reflects the abundance in the total and unfractionated sample.


Targeted Assay Development

We offer the expertise to develop and validate customized multiplex targeted protein assays. We have developed a workflow based on gas phase fractionation-data independent acquisition to expedite the selection of target peptides that provide robust quantitative measurements directly within the sample matrix. We can go from candidate list to scheduled peptide assay in a short time pending the peptides are above the limit of detection. All assays are developed using:

  • Single point external calibration
  • Assessment of both intra and interbatch precision.
  • Quantitative linearity and lower limit of quantitation using matrix matched calibration curves.
  • We can make highly multiplex assays using the novel Stellar MS.


If you have a question that isn't addressed in the above sections, check out our FAQs. For additional questions, please feel free to email us at

Showing: all announcements
Use of a hybrid quadrupole mass filter - radial ejection linear ion trap and intelligent data acquisition for multiplex targeted proteomics
Mike MacCoss 2024-06-10 12:46:25
At ASMS 2024 in Anaheim, the Stellar MS was released. We released two preprints describing the use of Stellar for targeted proteomics. In particular, targeted analysis of biofluids.
 Stellar MS 2D Diagram.png 
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Methodology describing the use of data independent acquisition to develop targeted methods
Mike MacCoss 2024-06-01 22:56:03

Mass spectrometry based targeted proteomics methods provide sensitive and high-throughput analysis of selected proteins. To develop a targeted bottom-up proteomics assay, peptides must be evaluated as proxies for the measurement of a protein or proteoform in a biological matrix. Candidate peptide selection typically relies on predetermined biochemical properties, data from semi-stochastic sampling, or by empirical measurements. These strategies require extensive testing and method refinement due to the difficulties associated with prediction of peptide response in the biological matrix of interest. Gas-phase fractionated (GPF) narrow window data-independent acquisition (DIA) aids in the development of reproducible selected reaction monitoring (SRM) assays by providing matrix-specific information on peptide detectability and quantification by mass spectrometry. To demonstrate the suitability of DIA data for selecting peptide targets, we reimplement a portion of an existing assay to measure 98 Alzheimer's disease proteins in cerebrospinal fluid (CSF). Peptides were selected from GPF-DIA based on signal intensity and reproducibility. The resulting SRM assay exhibits similar quantitative precision to published data, despite the inclusion of different peptides between the assays. This workflow enables development of new assays without additional up-front data acquisition, demonstrated here through generation of a separate assay for an unrelated set of proteins in CSF from the same dataset.

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2024 ASMS
Mike MacCoss 2024-06-01 19:36:02
 2024-ASMS MacCoss Lab.jpeg 
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A framework for quality control in quantitative proteomics
Mike MacCoss 2024-06-01 19:33:03

A thorough evaluation of the quality, reproducibility, and variability of bottom-up proteomics data is necessary at every stage of a workflow from planning to analysis. We share real-world case studies applying adaptable quality control (QC) measures to assess sample preparation, system function, and quantitative analysis. System suitability samples are repeatedly measured longitudinally with targeted methods, and we share examples where they are used on three instrument platforms to identify severe system failures and track function over months to years. Internal QCs incorporated at protein and peptide-level allow our team to assess sample preparation issues and to differentiate system failures from sample-specific issues. External QC samples prepared alongside our experimental samples are used to verify the consistency and quantitative potential of our results during batch correction and normalization before assessing biological phenotypes. We combine these controls with rapid analysis using Skyline, longitudinal QC metrics using AutoQC, and server-based data deposition using PanoramaWeb. We propose that this integrated approach to QC be used as a starting point for groups to facilitate rapid quality control assessment to ensure that valuable instrument time is used to collect the best quality data possible.

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Preprint describing the Mag-Net plasma enrichment strategy up on Biorxiv
Mike MacCoss 2024-06-01 19:32:00

Membrane-bound particles in plasma are composed of exosomes, microvesicles, and apoptotic bodies and represent ∼1-2% of the total protein composition. Proteomic interrogation of this subset of plasma proteins augments the representation of tissue-specific proteins, representing a “liquid biopsy,” while enabling the detection of proteins that would otherwise be beyond the dynamic range of liquid chromatography-tandem mass spectrometry of unfractionated plasma. We have developed an enrichment strategy (Mag-Net) using hyper-porous strong-anion exchange magnetic microparticles to sieve membrane-bound particles from plasma. The Mag-Net method is robust, reproducible, inexpensive, and requires <100 μL plasma input. Coupled to a quantitative data-independent mass spectrometry analytical strategy, we demonstrate that we can collect results for >37,000 peptides from >4,000 plasma proteins with high precision. Using this analytical pipeline on a small cohort of patients with neurodegenerative disease and healthy age-matched controls, we discovered 204 proteins that differentiate (q-value < 0.05) patients with Alzheimer’s disease dementia (ADD) from those without ADD. Our method also discovered 310 proteins that were different between Parkinson’s disease and those with either ADD or healthy cognitively normal individuals. Using machine learning we were able to distinguish between ADD and not ADD with a mean ROC AUC = 0.98 ± 0.06.

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