Targeted peptide measurements in biology and medicine: best practices for mass spectrometry-based assay development using a fit-for-purpose approach

Quantitative protein mass spectrometry for multiplex measurement of coagulation and fibrinolytic proteins towards clinical application: What, why and how?

Plasma proteins involved in coagulation and fibrinolysis are essential to hemostasis. Consequently, their circulating levels and functionality are critical in bleeding and thrombosis development. Well-established laboratory tests to assess these are available; however, said tests do not allow high multiplicity, require large volumes of plasma and are often costly. A novel technology to quantify plasma proteins is quantitative protein mass spectrometry (QPMS). Aided by stable isotope-labeled internal standards a large number of proteins can be quantified in one single analytical run requiring <30 μL of plasma. This provides an opportunity to improve insight in the etiology and prognosis of bleeding and thrombotic disorders, in which the balance between different proteins plays a crucial role. This manuscript aims to give an overview of the QPMS potential applications in thrombosis and hemostasis research (quantifying the 38 proteins assigned to coagulation and fibrinolysis by the KEGG database), but also to explore the potential and hurdles if designed for clinical practice. Advantages and limitations of QPMS are described and strategies for improved analysis are proposed, using as an example the test requirements for antithrombin. Application of this technology in the future could represent a step towards individualized patient care.

Differential Analysis of Cereblon Neosubstrates in Rabbit Embryos Using Targeted Proteomics

Targeted protein degradation is the selective removal of a protein of interest through hijacking intracellular protein cleanup machinery. This rapidly growing field currently relies heavily on the use of the E3 ligase cereblon (CRBN) to target proteins for degradation, including the immunomodulatory drugs (IMiDs) thalidomide, lenalidomide, and pomalidomide which work through a molecular glue mechanism of action with CRBN. While CRBN recruitment can result in degradation of a specific protein of interest (e.g., efficacy), degradation of other proteins (called CRBN neosubstrates) also occurs. Degradation of one or more of these CRBN neosubstrates is believed to play an important role in thalidomide-related developmental toxicity observed in rabbits and primates. We identified a set of 25 proteins of interest associated with CRBN-related protein homeostasis and/or embryo/fetal development. We developed a targeted assay for these proteins combining peptide immunoaffinity enrichment and high-resolution mass spectrometry and successfully applied this assay to rabbit embryo samples from pregnant rabbits dosed with three IMiDs. We confirmed previously reported in vivo decreases in neosubstrates like SALL4, as well as provided evidence of neosubstrate changes for proteins only examined in vitro previously. While there were many proteins that were similarly decreased by all three IMiDs, no compound had the exact same neosubstrate degradation profile as another. We compared our data to previous literature reports of IMiD-induced degradation and known developmental biology associations. Based on our observations, we recommend monitoring at least a major subset of these neosubstrates in a developmental test system to improve CRBN-binding compound-specific risk assessment. A strength of our assay is that it is configurable, and the target list can be readily adapted to focus on only a subset of proteins of interest or expanded to incorporate new findings as additional information about CRBN biology is discovered.

Serum proteome signatures associated with ileal and colonic ulcers in Crohn's disease

At a clinical level, ileal and colonic Crohn's disease (CD) are considered as separate entities. These subphenotypes need to be better supported by biological data to develop personalised medicine in CD. To this end, we combined different technologies (proximity extension assay, selected reaction monitoring, and high-sensitivity turbidimetric immunoassay (hsCRP)) to measure 207 immune-related serum proteins in CD patients presenting no endoscopic lesions (endoscopic remission) (n = 23), isolated ileal ulcers (n = 17), or isolated colonic ulcers (n = 16). We showed that isolated ileal ulcers and isolated colonic ulcers were specifically associated with 6 and 18 serum proteins, respectively: (high level: JUN, CNTNAP2; low level: FCRL6, LTA, CLEC4A, NTF4); (high level: hsCRP, IL6, APCS, CFB, MBL2, IL7, IL17A, CCL19, CXCL10, CSF3, IL10, CLEC4G, MMP12, VEGFA; low level: CLEC3B, GSN, TNFSF12, TPSAB1). Isolated ileal ulcers and isolated colonic ulcers were detected by hsCRP with an area under the receiver operating characteristics curve of 0.64 (p-value = 0.07) and 0.77 (p-value = 0.001), respectively. We highlighted distinct serum proteome profiles associated with ileal and colonic ulcers in CD, this finding might support the development of therapeutics and biomarkers tailored to disease location. SIGNIFICANCE: Although ileal and colonic Crohn's disease present important clinical differences (eg, progression, response to treatment and reliability of biomarkers), these two entities are managed with the same therapeutic strategy. The biological specificities of ileal and colonic Crohn's disease need to be better characterised to develop more personalised approaches. The present study used robust technologies (selected reaction monitoring, proximity extension assays and turbidimetric immunoassay) to quantify precisely 207 serum immune-related proteins in three groups of Crohn's disease patients presenting: 1) no endoscopic lesions (endoscopic remission) (n = 23); 2) isolated ileal ulcers (n = 17); 3) isolated colonic ulcers (n = 16). We found distinct serum proteome signatures associated with ileal and colonic ulcers. Our findings could foster the development of biomarkers and treatments tailored to Crohn's disease location.

Cohort profile: Improved Pregnancy Outcomes via Early Detection (IMPROvED), an International Multicentre Prospective Cohort

Background

Improved Pregnancy Outcomes via Early Detection (IMPROvED) is a multi-centre, European phase IIa clinical study. The primary aim of IMPROvED is to enable the assessment and refinement of innovative prototype preeclampsia risk assessment tests based on emerging biomarker technologies. Here we describe IMPROvED's profile and invite researchers to collaborate.

Methods

A total of 4,038 low-risk nulliparous singleton pregnancies were recruited from maternity units in Ireland (N=1,501), United Kingdom (N=1,108), The Netherlands (N=810), and Sweden (N=619) between November 2013 to August 2017. Participants were interviewed by a research midwife at ~11 weeks (optional visit), ~15 weeks, ~20 weeks, ~34 weeks' gestation (optional visit), and postpartum (within 72-hours following delivery).

Findings to date

Clinical data included information on maternal sociodemographic, medical history, and lifestyle factors collected at ~15 weeks' gestation, and maternal measurements, collected at each study visit. Biobank samples included blood, urine, and hair collected at each study visit throughout pregnancy in all units plus umbilical cord/blood samples collected at birth in Ireland and Sweden. A total of 74.0% (N=2,922) had an uncomplicated pregnancy, 3.1% (N=122) developed preeclampsia, 3.6% (N=143) had a spontaneous preterm birth, and 10.5% (N=416) had a small for gestational age baby. We evaluated a panel of metabolite biomarkers and a panel of protein biomarkers at 15 weeks and 20 weeks' gestation for preeclampsia risk assessment. Their translation into tests with clinical application, as conducted by commercial entities, was hampered by technical issues and changes in test requirements. Work on the panel of proteins was abandoned, while work on the use of metabolite biomarkers for preeclampsia risk assessment is ongoing.

Future plans

In accordance with the original goals of the IMPROvED study, the data and biobank are now available for international collaboration to conduct high quality research into the cause and prevention of adverse pregnancy outcomes.

Progression from healthy periodontium to gingivitis and periodontitis: Insights from bioinformatics-driven proteomics - A systematic review with meta-analysis

AIM

The current study aimed to: (1) systematically review the published literature regarding the proteomics analyses of saliva and gingival crevicular fluid (GCF) in healthy humans and gingivitis and/or periodontitis patients; and (2) to identify the differentially expressed proteins (DEPs) based on the systematic review, and comprehensively conduct meta-analyses and bioinformatics analyses.

METHODS

An online search of Web of Science, Scopus, and PubMed was performed without any restriction on the year and language of publication. After the identification of the DEPs reported by the included human primary studies, gene ontology (GO), the Kyoto encyclopedia of genes and genomes pathway (KEGG), protein-protein interaction (PPI), and meta-analyses were conducted. The risk of bias among the included studies was evaluated using the modified Newcastle-Ottawa quality assessment scale.

RESULTS

The review identified significant differences in protein expression between healthy individuals and those with gingivitis and periodontitis. In GCF, 247 proteins were upregulated and 128 downregulated in periodontal diseases. Saliva analysis revealed 79 upregulated and 70 downregulated proteins. There were distinct protein profiles between gingivitis and periodontitis, with 159 and 31 unique upregulated proteins in GCF, respectively. Meta-analyses confirmed significant upregulation of various proteins in periodontitis, including ALB and MMP9, while CSTB and GSTP1 were downregulated. AMY1A and SERPINA1 were upregulated in periodontitis saliva. HBD was upregulated in gingivitis GCF, while DEFA3 was downregulated. PPI analysis revealed complex networks of interactions among DEPs. GO and KEGG pathway analyses provided insights into biological processes and pathways associated with periodontal diseases.

CONCLUSION

The ongoing MS-based proteomics studies emphasize the need for a highly sensitive and specific diagnostic tool for periodontal diseases. Clinician acceptance of the eventual diagnostic method relies on its ability to provide superior or complementary information to current clinical assessment procedures. Future research should prioritize the multiplex measurement of multiple biomarkers simultaneously to enhance diagnostic accuracy and large study cohorts are necessary to ensure the validity and reliability of research findings.

Data-independent acquisition: A milestone and prospect in clinical mass spectrometry-based proteomics

Data-independent acquisition (DIA) has revolutionized the field of mass spectrometry (MS)-based proteomics over the past few years. DIA stands out for its ability to systematically sample all peptides in a given mass-to-charge range, allowing an unbiased acquisition of proteomics data. This greatly mitigates the issue of missing values and significantly enhances quantitative accuracy, precision, and reproducibility compared to many traditional methods. This review focuses on the critical role of DIA analysis software tools, primarily focusing on their capabilities and the challenges they address in proteomic research. Advances in MS technology, such as trapped ion mobility spectrometry, or high field asymmetric waveform ion mobility spectrometry require sophisticated analysis software capable of handling the increased data complexity and exploiting the full potential of DIA. We identify and critically evaluate leading software tools in the DIA landscape, discussing their unique features, and the reliability of their quantitative and qualitative outputs. We present the biological and clinical relevance of DIA-MS and discuss crucial publications that paved the way for in-depth proteomic characterization in patient-derived specimens. Furthermore, we provide a perspective on emerging trends in clinical applications and present upcoming challenges including standardization and certification of MS-based acquisition strategies in molecular diagnostics. While we emphasize the need for continuous development of software tools to keep pace with evolving technologies, we advise researchers against uncritically accepting the results from DIA software tools. Each tool may have its own biases, and some may not be as sensitive or reliable as others. Our overarching recommendation for both researchers and clinicians is to employ multiple DIA analysis tools, utilizing orthogonal analysis approaches to enhance the robustness and reliability of their findings.

Interlaboratory Comparison of Antibody-Free LC-MS/MS Measurements of C-peptide and Insulin

BACKGROUND

The enhanced precision and selectivity of liquid chromatography-tandem mass spectrometry (LC-MS/MS) makes it an attractive alternative to certain clinical immunoassays. Easily transferrable work flows could help facilitate harmonization and ensure high-quality patient care. We aimed to evaluate the interlaboratory comparability of antibody-free multiplexed insulin and C-peptide LC-MS/MS measurements.

METHODS

The laboratories that comprise the Targeted Mass Spectrometry Assays for Diabetes and Obesity Research (TaMADOR) consortium verified the performance of a validated peptide-based assay (reproducibility, linearity, and lower limit of the measuring interval [LLMI]). An interlaboratory comparison study was then performed using shared calibrators, de-identified leftover laboratory samples, and reference materials.

RESULTS

During verification, the measurements were precise (2.7% to 3.7%CV), linear (4 to 15 ng/mL for C-peptide and 2 to 14 ng/mL for insulin), and sensitive (LLMI of 0.04 to 0.10 ng/mL for C-peptide and 0.03 ng/mL for insulin). Median imprecision across the 3 laboratories was 13.4% (inter-quartile range [IQR] 11.6%) for C-peptide and 22.2% (IQR 20.9%) for insulin using individual measurements, and 10.8% (IQR 8.7%) and 15.3% (IQR 14.9%) for C-peptide and insulin, respectively, when replicate measurements were averaged. Method comparison with the University of Missouri reference method for C-peptide demonstrated a robust linear correlation with a slope of 1.044 and r2 = 0.99.

CONCLUSIONS

Our results suggest that combined LC-MS/MS measurements of C-peptide and insulin are robust and adaptable and that standardization with a reference measurement procedure could allow accurate and precise measurements across sites, which could be important to diabetes research and help patient care in the future.

Novel Multiplexed Plasma Biomarker Panel Has Diagnostic and Prognostic Potential in Children With Hypertrophic Cardiomyopathy

BACKGROUND

Hypertrophic cardiomyopathy (HCM) is defined clinically by pathological left ventricular hypertrophy. We have previously developed a plasma proteomics biomarker panel that correlates with clinical markers of disease severity and sudden cardiac death risk in adult patients with HCM. The aim of this study was to investigate the utility of adult biomarkers and perform new discoveries in proteomics for childhood-onset HCM.

METHODS

Fifty-nine protein biomarkers were identified from an exploratory plasma proteomics screen in children with HCM and augmented into our existing multiplexed targeted liquid chromatography-tandem/mass spectrometry-based assay. The association of these biomarkers with clinical phenotypes and outcomes was prospectively tested in plasma collected from 148 children with HCM and 50 healthy controls. Machine learning techniques were used to develop novel pediatric plasma proteomic biomarker panels.

RESULTS

Four previously identified adult HCM markers (aldolase fructose-bisphosphate A, complement C3a, talin-1, and thrombospondin 1) and 3 new markers (glycogen phosphorylase B, lipoprotein a and profilin 1) were elevated in pediatric HCM. Using supervised machine learning applied to training (n=137) and validation cohorts (n=61), this 7-biomarker panel differentiated HCM from healthy controls with an area under the curve of 1.0 in the training data set (sensitivity 100% [95% CI, 95-100]; specificity 100% [95% CI, 96-100]) and 0.82 in the validation data set (sensitivity 75% [95% CI, 59-86]; specificity 88% [95% CI, 75-94]). Reduced circulating levels of 4 other peptides (apolipoprotein L1, complement 5b, immunoglobulin heavy constant epsilon, and serum amyloid A4) found in children with high sudden cardiac death risk provided complete separation from the low and intermediate risk groups and predicted mortality and adverse arrhythmic outcomes (hazard ratio, 2.04 [95% CI, 1.0-4.2]; P=0.044).

CONCLUSIONS

In children, a 7-biomarker proteomics panel can distinguish HCM from controls with high sensitivity and specificity, and another 4-biomarker panel identifies those at high risk of adverse arrhythmic outcomes, including sudden cardiac death.

Data Independent Acquisition to Inform the Development of Targeted Proteomics Assays Using a Triple Quadrupole Mass Spectrometer

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.

Longitudinal markers of cerebral amyloid angiopathy and related inflammation in rTg-DI rats

Cerebral amyloid angiopathy (CAA) is a prevalent vascular dementia and common comorbidity of Alzheimer's disease (AD). While it is known that vascular fibrillar amyloid β (Aβ) deposits leads to vascular deterioration and can drive parenchymal CAA related inflammation (CAA-ri), underlying mechanisms of CAA pathology remain poorly understood. Here, we conducted brain regional proteomic analysis of early and late disease stages in the rTg-DI CAA rat model to gain molecular insight to mechanisms of CAA/CAA-ri progression and identify potential brain protein markers of CAA/CAA-ri. Longitudinal brain regional proteomic analysis revealed increased differentially expressed proteins (DEP) including ANXA3, HTRA1, APOE, CST3, and CLU, shared between the cortex, hippocampus, and thalamus, at both stages of disease in rTg-DI rats. Subsequent pathway analysis indicated pathway enrichment and predicted activation of TGF-β1, which was confirmed by immunolabeling and ELISA. Further, we identified numerous CAA related DEPs associate with astrocytes (HSPB1 and MLC1) and microglia (ANXA3, SPARC, TGF-β1) not previously associated with astrocytes or microglia in other AD models, possibly indicating that they are specific to CAA-ri. Thus, the data presented here identify several potential brain protein biomarkers of CAA/CAA-ri while providing novel molecular and mechanistic insight to mechanisms of CAA and CAA-ri pathological progression and glial cell mediated responses.

Simultaneous targeted and discovery-driven clinical proteotyping using hybrid-PRM/DIA

BACKGROUND

Clinical samples are irreplaceable, and their transformation into searchable and reusable digital biobanks is critical for conducting statistically empowered retrospective and integrative research studies. Currently, mainly data-independent acquisition strategies are employed to digitize clinical sample cohorts comprehensively. However, the sensitivity of DIA is limited, which is why selected marker candidates are often additionally measured targeted by parallel reaction monitoring.

METHODS

Here, we applied the recently co-developed hybrid-PRM/DIA technology as a new intelligent data acquisition strategy that allows for the comprehensive digitization of rare clinical samples at the proteotype level. Hybrid-PRM/DIA enables enhanced measurement sensitivity for a specific set of analytes of current clinical interest by the intelligent triggering of multiplexed parallel reaction monitoring (MSxPRM) in combination with the discovery-driven digitization of the clinical biospecimen using DIA. Heavy-labeled reference peptides were utilized as triggers for MSxPRM and monitoring of endogenous peptides.

RESULTS

We first evaluated hybrid-PRM/DIA in a clinical context on a pool of 185 selected proteotypic peptides for tumor-associated antigens derived from 64 annotated human protein groups. We demonstrated improved reproducibility and sensitivity for the detection of endogenous peptides, even at lower concentrations near the detection limit. Up to 179 MSxPRM scans were shown not to affect the overall DIA performance. Next, we applied hybrid-PRM/DIA for the integrated digitization of biobanked melanoma samples using a set of 30 AQUA peptides against 28 biomarker candidates with relevance in molecular tumor board evaluations of melanoma patients. Within the DIA-detected approximately 6500 protein groups, the selected marker candidates such as UFO, CDK4, NF1, and PMEL could be monitored consistently and quantitatively using MSxPRM scans, providing additional confidence for supporting future clinical decision-making.

CONCLUSIONS

Combining PRM and DIA measurements provides a new strategy for the sensitive and reproducible detection of protein markers from patients currently being discussed in molecular tumor boards in combination with the opportunity to discover new biomarker candidates.

Paradigm shift in biomarker translation: a pipeline to generate clinical grade biomarker candidates from DIA-MS discovery

Clinical biomarker development has been stymied by inaccurate protein quantification from mass spectrometry (MS) discovery data and a prolonged validation process. To mitigate these issues, we created the Targeted Extraction Assessment of Quantification (TEAQ) software package. This innovative tool uses the discovery cohort analysis to select precursors, peptides, and proteins that adhere to established targeted assay criteria. TEAQ was applied to Data-Independent Acquisition MS data from plasma samples acquired on an Orbitrap™ Astral™ MS. Identified precursors were evaluated for linearity, specificity, repeatability, reproducibility, and intra-protein correlation from 11-point loading curves under three throughputs, to develop a resource for clinical-grade targeted assays. From a clinical cohort of individuals with inflammatory bowel disease (n=492), TEAQ successfully identified 1116 signature peptides for 327 quantifiable proteins from 1180 identified proteins. Embedding stringent selection criteria adaptable to targeted assay development into the analysis of discovery data will streamline the transition to validation and clinical studies.

SWATH-MS as a strategy for CHO host cell protein identification and quantification supporting the characterization of mAb purification platforms

Host cell proteins (HCPs) are process-related impurities expressed by the host cells during biotherapeutics' manufacturing, such as monoclonal antibodies (mAbs). Some challenging HCPs evade clearance during the downstream processing and can be co-purified with the molecule of interest, which may impact product stability, efficacy, and safety. Therefore, HCP content is a critical quality attribute to monitor and quantify across the bioprocess. Here we explored a mass spectrometry (MS)-based proteomics tool, the sequential window acquisition of all theoretical fragment-ion spectra (SWATH) strategy, as an orthogonal method to traditional ELISA. The SWATH workflow was applied for high-throughput individual HCP identification and quantification, supporting characterization of a mAb purification platform. The design space of HCP clearance of two polishing resins was evaluated through a design of experiment study. Absolute quantification of high-risk HCPs was achieved (reaching 1.8 and 4.2 ppm limits of quantification, for HCP A and B respectively) using HCP-specific synthetic heavy labeled peptide calibration curves. Profiling of other HCPs was also possible using an average calibration curve (using labeled peptides from different HCPs). The SWATH approach is a powerful tool for HCP assessment during bioprocess development enabling simultaneous monitoring and quantification of different individual HCPs and improving process understanding of their clearance.

Proteomic Evolution from Acute to Post-COVID-19 Conditions

Many COVID-19 survivors have post-COVID-19 conditions, and females are at a higher risk. We sought to determine (1) how protein levels change from acute to post-COVID-19 conditions, (2) whether females have a plasma protein signature different from that of males, and (3) which biological pathways are associated with COVID-19 when compared to restrictive lung disease. We measured protein levels in 74 patients on the day of admission and at 3 and 6 months after diagnosis. We determined protein concentrations by multiple reaction monitoring (MRM) using a panel of 269 heavy-labeled peptides. The predicted forced vital capacity (FVC) and diffusing capacity of the lungs for carbon monoxide (DLCO) were measured by routine pulmonary function testing. Proteins associated with six key lipid-related pathways increased from admission to 3 and 6 months; conversely, proteins related to innate immune responses and vasoconstriction-related proteins decreased. Multiple biological functions were regulated differentially between females and males. Concentrations of eight proteins were associated with FVC, %, and they together had c-statistics of 0.751 (CI:0.732-0.779); similarly, concentrations of five proteins had c-statistics of 0.707 (CI:0.676-0.737) for DLCO, %. Lipid biology may drive evolution from acute to post-COVID-19 conditions, while activation of innate immunity and vascular regulation pathways decreased over that period. (ProteomeXchange identifiers: PXD041762, PXD029437).

Myalgic encephalomyelitis/chronic fatigue syndrome and fibromyalgia are indistinguishable by their cerebrospinal fluid proteomes

BACKGROUND

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) and fibromyalgia have overlapping neurologic symptoms particularly disabling fatigue. This has given rise to the question whether they are distinct central nervous system (CNS) entities or is one an extension of the other.

MATERIAL AND METHODS

To investigate this, we used unbiased quantitative mass spectrometry-based proteomics to examine the most proximal fluid to the brain, cerebrospinal fluid (CSF). This was to ascertain if the proteome profile of one was the same or different from the other. We examined two separate groups of ME/CFS, one with (n = 15) and one without (n = 15) fibromyalgia.

RESULTS

We quantified a total of 2083 proteins using immunoaffinity depletion, tandem mass tag isobaric labelling and offline two-dimensional liquid chromatography coupled to tandem mass spectrometry, including 1789 that were quantified in all the CSF samples. ANOVA analysis did not yield any proteins with an adjusted p value <.05.

CONCLUSION

This supports the notion that ME/CFS and fibromyalgia as currently defined are not distinct entities.Key messageME/CFS and fibromyalgia as currently defined are not distinct entities.Unbiased quantitative mass spectrometry-based proteomics can be used to discover cerebrospinal fluid proteins that are biomarkers for a condition such as we are studying.

Quantitative Measurement of Transthyretin Mistargeting by Proximity Labeling and Parallel Reaction Monitoring

Proximity labeling is a powerful approach for characterizing subcellular proteomes. We recently demonstrated that proximity labeling can be used to identify mistrafficking of secretory proteins, such as occurs during pre-emptive quality control (pre-QC) following endoplasmic reticulum (ER) stress. This assay depends on protein quantification by immunoblotting and densitometry, which sometimes suffers from poor sensitivity. Here, we integrate parallel reaction monitoring (PRM) mass spectrometry to enable a more quantitative platform, and assess how chemical ER stressors impact pre-QC of the model secretory protein transthyretin in HEK293T cells. We find that some drug treatments affect labeling efficiency, which can be controlled for by normalizing to APEX2 auto-labeling. While some chemical ER stress inducers including Brefeldin A and thapsigargin induce pre-QC, tunicamycin and dithiothreitol do not, indicating ER stress alone is not sufficient. This finding contrasts with the canonical model of pre-QC induction, and establishes the utility of our platform.

Targeted Proteomic Quantitation of NRF2 Signaling and Predictive Biomarkers in HNSCC

The NFE2L2 (NRF2) oncogene and transcription factor drives a gene expression program that promotes cancer progression, metabolic reprogramming, immune evasion, and chemoradiation resistance. Patient stratification by NRF2 activity may guide treatment decisions to improve outcome. Here, we developed a mass spectrometry-based targeted proteomics assay based on internal standard-triggered parallel reaction monitoring to quantify 69 NRF2 pathway components and targets, as well as 21 proteins of broad clinical significance in head and neck squamous cell carcinoma (HNSCC). We improved an existing internal standard-triggered parallel reaction monitoring acquisition algorithm, called SureQuant, to increase throughput, sensitivity, and precision. Testing the optimized platform on 27 lung and upper aerodigestive cancer cell models revealed 35 NRF2 responsive proteins. In formalin-fixed paraffin-embedded HNSCCs, NRF2 signaling intensity positively correlated with NRF2-activating mutations and with SOX2 protein expression. Protein markers of T-cell infiltration correlated positively with one another and with human papilloma virus infection status. CDKN2A (p16) protein expression positively correlated with the human papilloma virus oncogenic E7 protein and confirmed the presence of translationally active virus. This work establishes a clinically actionable HNSCC protein biomarker assay capable of quantifying over 600 peptides from frozen or formalin-fixed paraffin-embedded archived tissues in under 90 min.

Change of histone H3 lysine 14 acetylation stoichiometry in human monocyte derived macrophages as determined by MS-based absolute targeted quantitative proteomic approach: HIV infection and methamphetamine exposure

BACKGROUND

Histones posttranslational modification represent an epigenetic mechanism that regulate gene expression and other cellular processes. Quantitative mass spectrometry used for the absolute quantification of such modifications provides further insight into cellular responses to extracellular insults such as infections or toxins. Methamphetamine (Meth), a drug of abuse, is affecting the overall function of the immune system. In this report, we developed, validated and applied a targeted, MS-based quantification assay to measure changes in histone H3 lysine 14 acetylation (H3K14Ac) during exposure of human primary macrophages to HIV-1 infection and/or Meth.

METHODS

The quantification assay was developed and validated to determine H3K14Ac stoichiometry in histones that were isolated from the nuclei of control (CIC) and exposed to Meth before (CIM) or/and after (MIM) HIV-infection human monocyte-derived macrophages (hMDM) of six donors. It was based on LC-MS/MS measurement using multiple reaction monitoring (MRM) acquisition of the unmodified and acetylated form of lysine K14 of histone H3 9KSTGGKAPR17 peptides and the corresponding stable isotope labeled (SIL) heavy peptide standards of the same sequences. The histone samples were propionylated (Poy) pre- and post- trypsin digestion so that the sequences of the monitored peptides were: K[Poy]STGGK[1Ac]APR, K[Poy]STGGK[1Ac]APR-heavy, K[Poy]STGGK[Poy]APR and K[Poy]STGGK[Poy]APR-heavy. The absolute amounts of the acetylated and unmodified peptides were determined by comparing to the abundances of their SIL standards, that were added to the samples in the known concentrations, and, then used for calculation of H3K14Ac stoichiometry in CIC, CIM and MIM hMDM.

RESULTS

The assay was characterized by LLOD of 0.106 fmol/µL and 0.204 fmol/µL for unmodified and acetylated H3 9KSTGGKAPR17 peptides, respectively. The LLOQ was 0.5 fmol/µL and the linear range of the assay was from 0.5 to 2500 fmol/µL. The absolute abundances of the quantified peptides varied between the donors and conditions, and so did the H3K14Ac stoichiometry. This was rather attributed to the samples nature itself, as the variability of their triplicate measurements was low.

CONCLUSIONS

The developed LC-MS/MS assay enabled absolute quantification of H3K14Ac in exposed to Meth HIV-infected hMDM. It can be further applied determination of this PTM stoichiometry in other studies on human primary macrophages.

Redefining serological diagnostics with immunoaffinity proteomics

Serological diagnostics is generally defined as the detection of specific human immunoglobulins developed against viral, bacterial, or parasitic diseases. Serological tests facilitate the detection of past infections, evaluate immune status, and provide prognostic information. Serological assays were traditionally implemented as indirect immunoassays, and their design has not changed for decades. The advantages of straightforward setup and manufacturing, analytical sensitivity and specificity, affordability, and high-throughput measurements were accompanied by limitations such as semi-quantitative measurements, lack of universal reference standards, potential cross-reactivity, and challenges with multiplexing the complete panel of human immunoglobulin isotypes and subclasses. Redesign of conventional serological tests to include multiplex quantification of immunoglobulin isotypes and subclasses, utilize universal reference standards, and minimize cross-reactivity and non-specific binding will facilitate the development of assays with higher diagnostic specificity. Improved serological assays with higher diagnostic specificity will enable screenings of asymptomatic populations and may provide earlier detection of infectious diseases, autoimmune disorders, and cancer. In this review, we present the major clinical needs for serological diagnostics, overview conventional immunoassay detection techniques, present the emerging immunoassay detection technologies, and discuss in detail the advantages and limitations of mass spectrometry and immunoaffinity proteomics for serological diagnostics. Finally, we explore the design of novel immunoaffinity-proteomic assays to evaluate cell-mediated immunity and advance the sequencing of clinically relevant immunoglobulins.

Proteomics evaluation of five economical commercial abundant protein depletion kits for enrichment of diseases-specific biomarkers from blood serum

Blood serum is arguably the most analyzed biofluid for disease prediction and diagnosis. Herein, we benchmarked five different serum abundant protein depletion (SAPD) kits with regard to the identification of disease-specific biomarkers in human serum using bottom-up proteomics. As expected, the IgG removal efficiency among the SAPD kits is highly variable, ranging from 70% to 93%. A pairwise comparison of database search results showed a 10%-19% variation in protein identification among the kits. Immunocapturing-based SAPD kits against IgG and albumin outperformed the others in the removal of these two abundant proteins. Conversely, non-antibody-based methods (i.e., kits using ion exchange resins) and kits leveraging a multi-antibody approach were proven to be less efficient in depleting IgG/albumin from samples but led to the highest number of identified peptides. Notably, our results indicate that different cancer biomarkers could be enriched up to 10% depending on the utilized SAPD kit compared with the undepleted sample. Additionally, functional analysis of the bottom-up proteomic results revealed that different SAPD kits enrich distinct disease- and pathway-specific protein sets. Overall, our study emphasizes that a careful selection of the appropriate commercial SAPD kit is crucial for the analysis of disease biomarkers in serum by shotgun proteomics.

Synthesis of S-Carbamidomethyl Cysteine and Its Use for Quantification of Cysteinyl Peptides by Targeted Proteomics

Proteomics has played a central role in the identification of reliable disease biomarkers, which are the basis of precision medicine, a promising approach for tackling recalcitrant diseases such as cancer, that elude conventional treatments. Among proteomic methodologies, targeted proteomics employing stable isotope-labeled (SIL) internal standards is particularly suited for the clinical translation of biomarker information owing to its high throughput and accuracy in the quantitative analysis of patient-derived proteomes. Using SIL internal standards ensures the utmost level of confidence in detection and precision in targeted MS experiments. For successfully establishing assays based on targeted proteomics, it is crucial to secure broad coverage when selecting the SIL standard peptide panel. However, cysteinyl peptides have often been excluded because of cysteine's high chemical reactivity. To address this limitation, a new cysteine building block was developed by incorporating a sulfhydryl group configured with an S-carbamidomethyl group, which is commonly used in proteome sampling. This compound was found to be chemically stable and applicable to a variety of solid-phase peptide synthesis (SPPS) campaigns. Furthermore, a direct comparison of the synthesized SIL peptides and tryptic endogenous peptides demonstrated the potential utility of an SPPS flow based on the new cysteine building block for improving the success of targeted proteomic applications.

The RHW1-ZCN4 regulatory pathway confers natural variation of husk leaf width in maize

Maize husk leaf - the outer leafy layers covering the ear - modulates kernel yield and quality. Despite its importance, however, the genetic controls underlying husk leaf development remain elusive. Our previous genome-wide association study identified a single nucleotide polymorphism located in the gene RHW1 (Regulator of Husk leaf Width) that is significantly associated with husk leaf-width diversity in maize. Here, we further demonstrate that a polymorphic 18-bp InDel (insertion/deletion) variant in the 3' untranslated region of RHW1 alters its protein abundance and accounts for husk leaf width variation. RHW1 encodes a putative MYB-like transcriptional repressor. Disruption of RHW1 altered cell proliferation and resulted in a narrower husk leaf, whereas RHW1 overexpression yielded a wider husk leaf. RHW1 positively regulated the expression of ZCN4, a well-known TFL1-like protein involved in maize ear development. Dysfunction of ZCN4 reduced husk leaf width even in the context of RHW1 overexpression. The InDel variant in RHW1 is subject to selection and is associated with maize husk leaf adaption from tropical to temperate regions. Overall, our results identify that RHW1-ZCN4 regulates a pathway conferring husk leaf width variation at a very early stage of husk leaf development in maize.

Monitoring Both Extended and Tryptic Forms of Stable Isotope-Labeled Standard Peptides Provides an Internal Quality Control of Proteolytic Digestion in Targeted Mass Spectrometry-Based Assays

Targeted mass spectrometry (MS)-based proteomic assays, such as multiplexed multiple reaction monitoring (MRM)-MS assays, enable sensitive and specific quantification of proteotypic peptides as stoichiometric surrogates for proteins. Efforts are underway to expand the use of MRM-MS assays in clinical environments, which requires a reliable strategy to monitor proteolytic digestion efficiency within individual samples. Towards this goal, extended stable isotope-labeled standard (SIS) peptides (hE), which incorporate native proteolytic cleavage sites, can be spiked into protein lysates prior to proteolytic (trypsin) digestion, and release of the tryptic SIS peptide (hT) can be monitored. However, hT measurements alone cannot monitor the extent of digestion and may be confounded by matrix effects specific to individual patient samples; therefore, they are not sufficient to monitor sample-to-sample digestion variability. We hypothesized that measuring undigested hE, along with its paired hT, would improve detection of digestion issues compared to only measuring hT. We tested the ratio of the SIS pair measurements, or hE/hT, as a quality control (QC) metric of trypsin digestion for two MRM assays: a direct-MRM (398 targets) and an immuno-MRM (126 targets requiring immunoaffinity peptide enrichment) assay, with extended SIS peptides observable for 54% (216) and 62% (78) of the targets, respectively. We evaluated the quantitative bias for each target in a series of experiments that adversely affected proteolytic digestion (e.g., variable digestion times, pH, and temperature). We identified a subset of SIS pairs (36 for the direct-MRM, 7 for the immuno-MRM assay) for which the hE/hT ratio reliably detected inefficient digestion that resulted in decreased assay sensitivity and unreliable endogenous quantification. The hE/hT ratio was more responsive to a decrease in digestion efficiency than a metric based on hT measurements alone. For clinical-grade MRM-MS assays, this study describes a ready-to-use QC panel and also provides a road map for designing custom QC panels.

Proteogenomic analysis of chemo-refractory high-grade serous ovarian cancer

To improve the understanding of chemo-refractory high-grade serous ovarian cancers (HGSOCs), we characterized the proteogenomic landscape of 242 (refractory and sensitive) HGSOCs, representing one discovery and two validation cohorts across two biospecimen types (formalin-fixed paraffin-embedded and frozen). We identified a 64-protein signature that predicts with high specificity a subset of HGSOCs refractory to initial platinum-based therapy and is validated in two independent patient cohorts. We detected significant association between lack of Ch17 loss of heterozygosity (LOH) and chemo-refractoriness. Based on pathway protein expression, we identified 5 clusters of HGSOC, which validated across two independent patient cohorts and patient-derived xenograft (PDX) models. These clusters may represent different mechanisms of refractoriness and implicate putative therapeutic vulnerabilities.

Cerebrospinal fluid proteomics define the natural history of autosomal dominant Alzheimer's disease

Alzheimer's disease (AD) pathology develops many years before the onset of cognitive symptoms. Two pathological processes-aggregation of the amyloid-β (Aβ) peptide into plaques and the microtubule protein tau into neurofibrillary tangles (NFTs)-are hallmarks of the disease. However, other pathological brain processes are thought to be key disease mediators of Aβ plaque and NFT pathology. How these additional pathologies evolve over the course of the disease is currently unknown. Here we show that proteomic measurements in autosomal dominant AD cerebrospinal fluid (CSF) linked to brain protein coexpression can be used to characterize the evolution of AD pathology over a timescale spanning six decades. SMOC1 and SPON1 proteins associated with Aβ plaques were elevated in AD CSF nearly 30 years before the onset of symptoms, followed by changes in synaptic proteins, metabolic proteins, axonal proteins, inflammatory proteins and finally decreases in neurosecretory proteins. The proteome discriminated mutation carriers from noncarriers before symptom onset as well or better than Aβ and tau measures. Our results highlight the multifaceted landscape of AD pathophysiology and its temporal evolution. Such knowledge will be critical for developing precision therapeutic interventions and biomarkers for AD beyond those associated with Aβ and tau.

2022 White Paper on Recent Issues in Bioanalysis: ICH M10 BMV Guideline & Global Harmonization; Hybrid Assays; Oligonucleotides & ADC; Non-Liquid & Rare Matrices; Regulatory Inputs (Part 1A - Recommendations on Mass Spectrometry, Chromatography and Sample Preparation, Novel Technologies, Novel Modalities, and Novel Challenges, ICH M10 BMV Guideline & Global Harmonization Part 1B - Regulatory Agencies' Inputs on Regulated Bioanalysis/BMV, Biomarkers/CDx/BAV, Immunogenicity, Gene & Cell Therapy and Vaccine)

The 16th Workshop on Recent Issues in Bioanalysis (16th WRIB) took place in Atlanta, GA, USA on September 26-30, 2022. Over 1000 professionals representing pharma/biotech companies, CROs, and multiple regulatory agencies convened to actively discuss the most current topics of interest in bioanalysis. The 16th WRIB included 3 Main Workshops and 7 Specialized Workshops that together spanned 1 week in order to allow exhaustive and thorough coverage of all major issues in bioanalysis, biomarkers, immunogenicity, gene therapy, cell therapy and vaccines. Moreover, in-depth workshops on the ICH M10 BMV final guideline (focused on this guideline training, interpretation, adoption and transition); mass spectrometry innovation (focused on novel technologies, novel modalities, and novel challenges); and flow cytometry bioanalysis (rising of the 3rd most common/important technology in bioanalytical labs) were the special features of the 16th edition. As in previous years, WRIB continued to gather a wide diversity of international, industry opinion leaders and regulatory authority experts working on both small and large molecules as well as gene, cell therapies and vaccines to facilitate sharing and discussions focused on improving quality, increasing regulatory compliance, and achieving scientific excellence on bioanalytical issues. This 2022 White Paper encompasses recommendations emerging from the extensive discussions held during the workshop and is aimed to provide the bioanalytical community with key information and practical solutions on topics and issues addressed, in an effort to enable advances in scientific excellence, improved quality and better regulatory compliance. Due to its length, the 2022 edition of this comprehensive White Paper has been divided into three parts for editorial reasons. This publication (Part 1A) covers the recommendations on Mass Spectrometry and ICH M10. Part 1B covers the Regulatory Agencies' Inputs on Bioanalysis, Biomarkers, Immunogenicity, Gene & Cell Therapy and Vaccine. Part 2 (LBA, Biomarkers/CDx and Cytometry) and Part 3 (Gene Therapy, Cell therapy, Vaccines and Biotherapeutics Immunogenicity) are published in volume 15 of Bioanalysis, issues 15 and 14 (2023), respectively.

Quantitative Measurement of Secretory Protein Mistargeting by Proximity Labeling and Parallel Reaction Monitoring

Proximity labeling is a powerful approach for characterizing subcellular proteomes. We recently demonstrated that proximity labeling can be used to identify mistrafficking of secretory proteins, such as occurs during pre-emptive quality control (pre-QC) following endoplasmic reticulum (ER) stress. This assay depends on protein quantification by immunoblotting and densitometry, which is only semi-quantitative and suffers from poor sensitivity. Here, we integrate parallel reaction monitoring mass spectrometry to enable a more quantitative platform for ER import. PRM as opposed to densitometry improves quantification of transthyretin mistargeting while also achieving at least a ten-fold gain in sensitivity. The multiplexing of PRM also enabled us to evaluate a series of normalization approaches, revealing that normalization to auto-labeled APEX2 peroxidase is necessary to account for drug treatment-dependent changes in labeling efficiency. We apply this approach to systematically characterize the relationship between chemical ER stressors and ER pre-QC induction in HEK293T cells. Using dual-FLAG-tagged transthyretin (FLAGTTR) as a model secretory protein, we find that Brefeldin A treatment as well as ER calcium depletion cause pre-QC, while tunicamycin and dithiothreitol do not, indicating ER stress alone is not sufficient. This finding contrasts with the canonical model of pre-QC induction, and establishes the utility of our platform.

A single protein to multiple peptides: Investigation of protein-peptide correlations using targeted alpha-2-macroglobulin analysis

Recent advances in proteomics technologies have enabled the analysis of thousands of proteins in a high-throughput manner. Mass spectrometry (MS) based proteomics uses a peptide-centric approach where biological samples undergo specific proteolytic digestion and then only unique peptides are used for protein identification and quantification. Considering the fact that a single protein may have multiple unique peptides and a number of different forms, it becomes essential to understand dynamic protein-peptide relationships to ensure robust and reliable peptide-centric protein analysis. In this study, we investigated the correlation between protein concentration and corresponding unique peptide responses under a conventional proteolytic digestion condition. Protein-peptide correlation, digestion efficiency, matrix-effect, and concentration-effect were evaluated. Twelve unique peptides of alpha-2-macroglobulin (A2MG) were monitored using a targeted MS approach to acquire insights into protein-peptide dynamics. Although the peptide responses were reproducible between replicates, protein-peptide correlation was moderate in protein standards and low in complex matrices. The results suggest that reproducible peptide signal could be misleading in clinical studies and a peptide selection could dramatically change the outcome at protein level. This is the first study investigating quantitative protein-peptide correlations in biological samples using all unique peptides representing the same protein and opens a discussion on peptide-based proteomics.

The plasma degradome reflects later development of NASH fibrosis after liver transplant

Although liver transplantation (LT) is an effective therapy for cirrhosis, the risk of post-LT NASH is alarmingly high and is associated with accelerated progression to fibrosis/cirrhosis, cardiovascular disease and decreased survival. Lack of risk stratification strategies hampers early intervention against development of post-LT NASH fibrosis. The liver undergoes significant remodeling during inflammatory injury. During such remodeling, degraded peptide fragments (i.e., 'degradome') of the ECM and other proteins increase in plasma, making it a useful diagnostic/prognostic tool in chronic liver disease. To investigate whether liver injury caused by post-LT NASH would yield a unique degradome profile that is predictive of severe post-LT NASH fibrosis, a retrospective analysis of 22 biobanked samples from the Starzl Transplantation Institute (12 with post-LT NASH after 5 years and 10 without) was performed. Total plasma peptides were isolated and analyzed by 1D-LC-MS/MS analysis using a Proxeon EASY-nLC 1000 UHPLC and nanoelectrospray ionization into an Orbitrap Elite mass spectrometer. Qualitative and quantitative peptide features data were developed from MSn datasets using PEAKS Studio X (v10). LC-MS/MS yielded ~ 2700 identifiable peptide features based on the results from Peaks Studio analysis. Several peptides were significantly altered in patients that later developed fibrosis and heatmap analysis of the top 25 most significantly changed peptides, most of which were ECM-derived, clustered the 2 patient groups well. Supervised modeling of the dataset indicated that a fraction of the total peptide signal (~ 15%) could explain the differences between the groups, indicating a strong potential for representative biomarker selection. A similar degradome profile was observed when the plasma degradome patterns were compared being obesity sensitive (C57Bl6/J) and insensitive (AJ) mouse strains. The plasma degradome profile of post-LT patients yielded stark difference based on later development of post-LT NASH fibrosis. This approach could yield new "fingerprints" that can serve as minimally-invasive biomarkers of negative outcomes post-LT.

In-depth serum proteomics reveals the trajectory of hallmarks of cancer in hepatitis B virus-related liver diseases

Hepatocellular carcinoma (HCC) is a prevalent cancer in China, with chronic hepatitis B (CHB) and liver cirrhosis (LC) being high-risk factors for developing HCC. Here, we determined the serum proteomes (762 proteins) of 125 healthy controls and Hepatitis B virus-infected CHB, LC, and HCC patients and constructed the first cancerous trajectory of liver diseases. The results not only reveal that the majority of altered biological processes were involved in the hallmarks of cancer (inflammation, metastasis, metabolism, vasculature, coagulation), but also identify potential therapeutic targets in cancerous pathways (i.e., IL17 signaling pathway). Notably, the biomarker panels for detecting HCC in CHB and LC high-risk populations were further developed using machine learning in two cohorts comprised of 200 samples (discovery cohort=125, validation cohort=75). The protein signatures significantly improved the area under the receiver operating characteristic curve (AUC) of HCC (CHB discovery and validation cohort = 0.953 and 0.891, respectively; LC discovery and validation cohort = 0.966 and 0.818, respectively) compared to using the traditional biomarker, alpha-fetoprotein (AFP), alone. Finally, selected biomarkers were validated with parallel reaction monitoring (PRM) mass spectrometry in an additional cohort (n=120). Altogether, our results provide fundamental insights into the continuous changes of cancer biology processes in liver diseases and identify candidate protein targets for early detection and intervention.

The role of clinical glyco(proteo)mics in precision medicine

Glycoproteomics reveals site-specific O- and N-glycosylation that may influence protein properties including binding, activity and half-life. The increasingly mature toolbox with glycomic- and glycoproteomic strategies is applied for the development of biopharmaceuticals and discovery and clinical evaluation of glycobiomarkers in various disease fields. Notwithstanding the contributions of glycoscience in identifying new drug targets, the current report is focused on the biomarker modality that is of interest for diagnostic and monitoring purposes. To this end it is noted that the identification of biomarkers has received more attention than corresponding quantification. Most analytical methods are very efficient in detecting large numbers of analytes but developments to accurately quantify these have so far been limited. In this perspective a parallel is made with earlier proposed tiers for protein quantification using mass spectrometry. Moreover, the foreseen reporting of multimarker readouts is discussed to describe an individual's health or disease state and their role in clinical decision-making. The potential of longitudinal sampling and monitoring of glycomic features for diagnosis and treatment monitoring is emphasized. Finally, different strategies that address quantification of a multimarker panel will be discussed.

A multiplexed assay for quantifying immunomodulatory proteins supports correlative studies in immunotherapy clinical trials

Introduction

Immunotherapy is an effective treatment for a subset of cancer patients, and expanding the benefits of immunotherapy to all cancer patients will require predictive biomarkers of response and immune-related adverse events (irAEs). To support correlative studies in immunotherapy clinical trials, we are developing highly validated assays for quantifying immunomodulatory proteins in human biospecimens.

Methods

Here, we developed a panel of novel monoclonal antibodies and incorporated them into a novel, multiplexed, immuno-multiple reaction monitoring mass spectrometry (MRM-MS)-based proteomic assay targeting 49 proteotypic peptides representing 43 immunomodulatory proteins.

Results and discussion

The multiplex assay was validated in human tissue and plasma matrices, where the linearity of quantification was >3 orders of magnitude with median interday CVs of 8.7% (tissue) and 10.1% (plasma). Proof-of-principle demonstration of the assay was conducted in plasma samples collected in clinical trials from lymphoma patients receiving an immune checkpoint inhibitor. We provide the assays and novel monoclonal antibodies as a publicly available resource for the biomedical community.

Sample Preparation Methods for Targeted Single-Cell Proteomics

We compared three cell isolation and two proteomic sample preparation methods for single-cell and near-single-cell analysis. Whole blood was used to quantify hemoglobin (Hb) and glycated-Hb (gly-Hb) in erythrocytes using targeted mass spectrometry and stable isotope-labeled standard peptides. Each method differed in cell isolation and sample preparation as follows: 1) FACS and automated preparation in one-pot for trace samples (autoPOTS); 2) limited dilution via microscopy and a novel rapid one-pot sample preparation method that circumvented the need for the solid-phase extraction, low-volume liquid handling instrumentation and humidified incubation chamber; and 3) CellenONE-based cell isolation and the same one-pot sample preparation method used for limited dilution. Only the CellenONE device routinely isolated single-cells from which Hb was measured to be 540-660 amol per red blood cell (RBC), which was comparable to the calculated SI reference range for mean corpuscular hemoglobin (390-540 amol/RBC). FACSAria sorter and limited dilution could routinely isolate single-digit cell numbers, to reliably quantify CMV-Hb heterogeneity. Finally, we observed that repeated measures, using 5-25 RBCs obtained from N = 10 blood donors, could be used as an alternative and more efficient strategy than single RBC analysis to measure protein heterogeneity, which revealed multimodal distribution, unique for each individual.

LC-MS/MS-PRM Quantification of IgG Glycoforms Using Stable Isotope Labeled IgG1 Fc Glycopeptide Standard

Targeted quantification of proteins is a standard methodology with broad utility, but targeted quantification of glycoproteins has not reached its full potential. The lack of optimized workflows and isotopically labeled standards limits the acceptance of glycoproteomics quantification. In this work, we introduce an efficient and streamlined chemoenzymatic synthesis of a library of isotopically labeled glycopeptides of IgG1 which we use for quantification in an energy optimized LC-MS/MS-PRM workflow. Incorporation of the stable isotope labeled N-acetylglucosamine enables an efficient monitoring of all major fragment ions of the glycopeptides generated under the soft higher-energy C-trap dissociation (HCD) conditions, which reduces the coefficients of variability (CVs) of the quantification to 0.7-2.8%. Our results document, for the first time, that the workflow using a combination of stable isotope labeled standards with intrascan normalization enables quantification of the glycopeptides by an electron transfer dissociation (ETD) workflow, as well as the HCD workflow, with the highest sensitivity compared to traditional workflows. This was exemplified by a rapid quantification (13 min) of IgG1 Fc glycoforms from COVID-19 patients.

Targeted proteomics links virulence factor expression with clinical severity in staphylococcal pneumonia

Introduction

The bacterial pathogen Staphylococcus aureus harbors numerous virulence factors that impact infection severity. Beyond virulence gene presence or absence, the expression level of virulence proteins is known to vary across S. aureus lineages and isolates. However, the impact of expression level on severity is poorly understood due to the lack of high-throughput quantification methods of virulence proteins.

Methods

We present a targeted proteomic approach able to monitor 42 staphylococcal proteins in a single experiment. Using this approach, we compared the quantitative virulomes of 136 S. aureus isolates from a nationwide cohort of French patients with severe community-acquired staphylococcal pneumonia, all requiring intensive care. We used multivariable regression models adjusted for patient baseline health (Charlson comorbidity score) to identify the virulence factors whose in vitro expression level predicted pneumonia severity markers, namely leukopenia and hemoptysis, as well as patient survival.

Results

We found that leukopenia was predicted by higher expression of HlgB, Nuc, and Tsst-1 and lower expression of BlaI and HlgC, while hemoptysis was predicted by higher expression of BlaZ and HlgB and lower expression of HlgC. Strikingly, mortality was independently predicted in a dose-dependent fashion by a single phage-encoded virulence factor, the Panton-Valentine leucocidin (PVL), both in logistic (OR 1.28; 95%CI[1.02;1.60]) and survival (HR 1.15; 95%CI[1.02;1.30]) regression models.

Discussion

These findings demonstrate that the in vitro expression level of virulence factors can be correlated with infection severity using targeted proteomics, a method that may be adapted to other bacterial pathogens.

LC-MS/MS: A sensitive and selective analytical technique to detect COVID-19 protein biomarkers in the early disease stage

INTRODUCTION

The COVID-19 outbreak has put enormous pressure on the scientific community to detect infection rapidly, identify the status of disease severity, and provide an immediate vaccine/drug for the treatment. Relying on immunoassay and a real-time reverse transcription polymerase chain reaction (rRT-PCR) led to many false-negative and false-positive reports. Therefore, detecting biomarkers is an alternative and reliable approach for determining the infection, its severity, and disease progression. Recent advances in liquid chromatography and mass spectrometry (LC-MS/MS) enable the protein biomarkers even at low concentrations, thus facilitating clinicians to monitor the treatment in hospitals.

AREAS COVERED

This review highlights the role of LC-MS/MS in identifying protein biomarkers and discusses the clinically significant protein biomarkers such as Serum amyloid A, Interleukin-6, C-Reactive Protein, Lactate dehydrogenase, D-dimer, cardiac troponin, ferritin, Alanine transaminase, Aspartate transaminase, gelsolin and galectin-3-binding protein in COVID-19, and their analysis by LC-MS/MS in the early stage.

EXPERT OPINION

Clinical doctors monitor significant biomarkers to understand, stratify, and treat patients according to disease severity. Knowledge of clinically significant COVID-19 protein biomarkers is critical not only for COVID-19 caused by the coronavirus but also to prepare us for future pandemics of other diseases in detecting by LC-MS/MS at the early stages.

10 years of extracellular matrix proteomics: Accomplishments, challenges, and future perspectives

The extracellular matrix (ECM) is a complex assembly of hundreds of proteins forming the architectural scaffold of multicellular organisms. In addition to its structural role, the ECM conveys signals orchestrating cellular phenotypes. Alterations of ECM composition, abundance, structure, or mechanics, have been linked to diseases and disorders affecting all physiological systems, including fibrosis and cancer. Deciphering the protein composition of the ECM and how it changes in pathophysiological contexts is thus the first step toward understanding the roles of the ECM in health and disease and toward the development of therapeutic strategies to correct disease-causing ECM alterations. Potentially, the ECM also represents a vast, yet untapped reservoir of disease biomarkers. ECM proteins are characterized by unique biochemical properties that have hindered their study: they are large, heavily and uniquely post-translationally modified, and highly insoluble. Overcoming these challenges, we and others have devised mass-spectrometry-based proteomic approaches to define the ECM composition, or "matrisome", of tissues. This review provides a historical overview of ECM proteomics research and presents the latest advances that now allow the profiling of the ECM of healthy and diseased tissues. The second part highlights recent examples illustrating how ECM proteomics has emerged as a powerful discovery pipeline to identify prognostic cancer biomarkers. The third part discusses remaining challenges limiting our ability to translate findings to clinical application and proposes approaches to overcome them. Last, the review introduces readers to resources available to facilitate the interpretation of ECM proteomics datasets. The ECM was once thought to be impenetrable. MS-based proteomics has proven to be a powerful tool to decode the ECM. In light of the progress made over the past decade, there are reasons to believe that the in-depth exploration of the matrisome is within reach and that we may soon witness the first translational application of ECM proteomics.

TNK2/ACK1-mediated phosphorylation of ATP5F1A (ATP synthase F1 subunit alpha) selectively augments survival of prostate cancer while engendering mitochondrial vulnerability

The challenge of rapid macromolecular synthesis enforces the energy-hungry cancer cell mitochondria to switch their metabolic phenotypes, accomplished by activation of oncogenic tyrosine kinases. Precisely how kinase activity is directly exploited by cancer cell mitochondria to meet high-energy demand, remains to be deciphered. Here we show that a non-receptor tyrosine kinase, TNK2/ACK1 (tyrosine kinase non receptor 2), phosphorylated ATP5F1A (ATP synthase F1 subunit alpha) at Tyr243 and Tyr246 (Tyr200 and 203 in the mature protein, respectively) that not only increased the stability of complex V, but also increased mitochondrial energy output in cancer cells. Further, phospho-ATP5F1A (p-Y-ATP5F1A) prevented its binding to its physiological inhibitor, ATP5IF1 (ATP synthase inhibitory factor subunit 1), causing sustained mitochondrial activity to promote cancer cell growth. TNK2 inhibitor, (R)-9b reversed this process and induced mitophagy-based autophagy to mitigate prostate tumor growth while sparing normal prostate cells. Further, depletion of p-Y-ATP5F1A was needed for (R)-9b-mediated mitophagic response and tumor growth. Moreover, Tnk2 transgenic mice displayed increased p-Y-ATP5F1A and loss of mitophagy and exhibited formation of prostatic intraepithelial neoplasia (PINs). Consistent with these data, a marked increase in p-Y-ATP5F1A was seen as prostate cancer progressed to the malignant stage. Overall, this study uncovered the molecular intricacy of tyrosine kinase-mediated mitochondrial energy regulation as a distinct cancer cell mitochondrial vulnerability and provided evidence that TNK2 inhibitors can act as "mitocans" to induce cancer-specific mitophagy.Abbreviations: ATP5F1A: ATP synthase F1 subunit alpha; ATP5IF1: ATP synthase inhibitory factor subunit 1; CRPC: castration-resistant prostate cancer; DNM1L: dynamin 1 like; MAP1LC3B/LC3B: microtubule associated protein 1 light chain 3 beta; Mdivi-1: mitochondrial division inhibitor 1; Mut-ATP5F1A: Y243,246A mutant of ATP5F1A; OXPHOS: oxidative phosphorylation; PC: prostate cancer; PINK1: PTEN induced kinase 1; p-Y-ATP5F1A: phosphorylated tyrosine 243 and 246 on ATP5F1A; TNK2/ACK1: tyrosine kinase non receptor 2; Ub: ubiquitin; WT: wild type.

Targeted proteomics using stable isotope labeled protein fragments enables precise and robust determination of total apolipoprotein(a) in human plasma

Lipoprotein(a), also known as Lp(a), is an LDL-like particle composed of apolipoprotein(a) (apo(a)) bound covalently to apolipoprotein B100. Plasma concentrations of Lp(a) are highly heritable and vary widely between individuals. Elevated plasma concentration of Lp(a) is considered as an independent, causal risk factor of cardiovascular disease (CVD). Targeted mass spectrometry (LC-SRM/MS) combined with stable isotope-labeled recombinant proteins provides robust and precise quantification of proteins in the blood, making LC-SRM/MS assays appealing for monitoring plasma proteins for clinical implications. This study presents a novel quantitative approach, based on proteotypic peptides, to determine the absolute concentration of apo(a) from two microliters of plasma and qualified according to guideline requirements for targeted proteomics assays. After optimization, assay parameters such as linearity, lower limits of quantification (LLOQ), intra-assay variability (CV: 4.7%) and inter-assay repeatability (CV: 7.8%) were determined and the LC-SRM/MS results were benchmarked against a commercially available immunoassay. In summary, the measurements of an apo(a) single copy specific peptide and a kringle 4 specific peptide allow for the determination of molar concentration and relative size of apo(a) in individuals.

Absolute Quantitative Targeted Proteomics Assays for Plasma Proteins

Preclinical and clinical trials require rapid, precise, and multiplexed analytical methods to characterize the complex samples and to allow high-throughput biomarker monitoring with low consumption of sample material. Targeted proteomics has been used to address these challenges when quantifying protein abundances in complex biological matrices. In many of these studies, blood plasma is collected either as the main research or diagnostic sample or in combination with other specimens. Mass spectrometry (MS)-based targeted proteomics using multiple reaction monitoring (MRM) or parallel reaction monitoring (PRM) with stable isotope-labeled internal standard (SIS) peptides allows robust characterization of blood plasma protein via absolute quantification. Compared to other commonly used technologies like enzyme-linked immunosorbent assay (ELISA), targeted proteomics is faster, more sensitive, and more cost-effective. Here we describe a protocol for the quantification of proteins in blood plasma using targeted MRM proteomics with heavy-labeled internal standards. The 270-protein panel allows rapid and robust absolute quantitative proteomic characterization of blood plasma in a 1 h gradient. The method we describe here works for non-depleted plasma, which makes it simple and easy to implement. Moreover, the protocol works with the two most commonly used blood plasma collection methods used in practice, namely, either K₂EDTA or sodium citrate as anticoagulants.

Bioinformatics Tools and Knowledgebases to Assist Generating Targeted Assays for Plasma Proteomics

In targeted proteomics experiments, selecting the appropriate proteotypic peptides as surrogate for the target protein is a crucial pre-acquisition step. This step is largely a bioinformatics exercise that involves integrating information on the peptides and proteins and using various software tools and knowledgebases. We present here a few resources that automate and simplify the selection process to a great degree. These tools and knowledgebases were developed primarily to streamline targeted proteomics assay development and include PeptidePicker, PeptidePickerDB, MRMAssayDB, MouseQuaPro, and PeptideTracker. We have used these tools to develop and document thousands of targeted proteomics assays, many of them for plasma proteins with focus on human and mouse. An important aspect in all these resources is the integrative approach on which they are based. Using these tools in the first steps of designing a singleplexed or multiplexed targeted proteomic experiment can reduce the necessary experimental steps tremendously. All the tools and knowledgebases we describe here are Web-based and freely accessible so scientists can query the information conveniently from the browser. This chapter provides an overview of these software tools and knowledgebases, their content, and how to use them for targeted plasma proteomics. We further demonstrate how to use them with the results of the HUPO Human Plasma Proteome Project to produce a new database of 3.8 k targeted assays for known human plasma proteins. Upon experimental validation, these assays should help in the further quantitative characterizing of the plasma proteome.

Influence of rosuvastatin on apolipoproteins and coagulation factor levels: Results from the STAtin Reduce Thrombophilia trial

Background

The STAtins Reduce Thrombophilia trial showed that, in patients with prior venous thrombosis, rosuvastatin decreased various coagulation factor levels.

Objectives

Here, we investigated the hypothesis that statins decrease coagulation factor levels through shared mechanisms of synthesis or regulatory pathways with apolipoproteins.

Methods

We measured the levels of apolipoprotein (Apo)A-I, A-II, A-IV, (a), B-100, B-total, C-I, C-II, C-III, and E in patients (n = 126) randomized to 28 days of rosuvastatin use. We assessed the association between apolipoproteins and coagulation factors at baseline using linear regression. The mean difference in apolipoprotein levels between baseline and after 28 days of rosuvastatin use was determined through linear regression, adjusting for age, sex, and body mass index. Coagulation factors were added to this model to determine if the lowering of apolipoproteins by rosuvastatin was linked with coagulation factor levels.

Results

At baseline, levels of all apolipoproteins, except Apo(a), were positively associated with FVII, FIX, and FXI. Apolipoproteins levels, except for ApoA-I, A-IV, and Apo(a), were decreased after 28 days of rosuvastatin. ApoB-100 showed the largest mean decrease of -0.43 g/L (95% CI = -0.46 to -0.40). The decrease in ApoC-I and C-III levels was associated with a decrease in FVII, whereas the decrease in apoA-II, B-100, and B-total was associated with a decrease in FXI. The decrease in apolipoproteins was neither associated with FVIII or vWF decrease nor with endogenous thrombin potential changes.

Conclusions

Rosuvastatin decreases the level of several apolipoproteins, but this decrease was associated only with a decrease in FVII and XI and not with FVIII/vWF.

The plasma degradome reflects later development of NASH fibrosis after liver transplant

Although liver transplantation (LT) is an effective therapy for cirrhosis, the risk of post-LT NASH is alarmingly high and is associated with accelerated progression to fibrosis/cirrhosis, cardiovascular disease, and decreased survival. Lack of risk stratification strategies hamper liver undergoes significant remodeling during inflammatory injury. During such remodeling, degraded peptide fragments (i.e., 'degradome') of the ECM and other proteins increase in plasma, making it a useful diagnostic/prognostic tool in chronic liver disease. To investigate whether inflammatory liver injury caused by post-LT NASH would yield a unique degradome profile, predictive of severe post-LT NASH fibrosis, we performed a retrospective analysis of 22 biobanked samples from the Starzl Transplantation Institute (12 with post-LT NASH after 5 years and 10 without). Total plasma peptides were isolated and analyzed by 1D-LC-MS/MS analysis using a Proxeon EASY-nLC 1000 UHPLC and nanoelectrospray ionization into an Orbitrap Elite mass spectrometer. Qualitative and quantitative peptide features data were developed from MSn datasets using PEAKS Studio X (v10). LC-MS/MS yielded ∼2700 identifiable peptide features based on the results from Peaks Studio analysis. Several peptides were significantly altered in patients that later developed fibrosis and heatmap analysis of the top 25 most significantly-changed peptides, most of which were ECM-derived, clustered the 2 patient groups well. Supervised modeling of the dataset indicated that a fraction of the total peptide signal (∼15%) could explain the differences between the groups, indicating a strong potential for representative biomarker selection. A similar degradome profile was observed when the plasma degradome patterns were compared being obesity sensitive (C57Bl6/J) and insensitive (AJ) mouse strains. Both The plasma degradome profile of post-LT patients yields stark difference based on later development of post-LT NASH fibrosis. This approach could yield new "fingerprints" that can serve as minimally-invasive biomarkers of negative outcomes post-LT.

Developing quantitative assays for six urinary glycoproteins using parallel reaction monitoring, data-independent acquisition, and TMT-based data-dependent acquisition

Quantitative approaches encompassing parallel reaction monitoring (PRM), data-independent acquisition (DIA), and data-dependent acquisition (DDA) are commonly used to investigate protein expression profiles. However, analytical performances of assays developed using PRM, DIA, and Tandem Mass Tag (TMT)-based DDA for quantitative proteomics have yet not been investigated. Here, we developed assays for glycopeptides identified from six glycoproteins, including Leucine-rich alpha-2-glycoprotein (LRG1), Prostaglandin-H2 D-isomerase (PTGDS), Aminopeptidase N (ANPEP), CD63 antigen (CD63), Clusterin (CLU), and Prostatic acid phosphatase (ACPP), using PRM, DDA, and DIA and evaluated the analytical performances of each assay using the different acquisition modes. We also compared assays in each acquisition mode on three different orbitrap instruments: Thermo Fisher Q Exactive, Exploris 480, and Lumos. We found that DIA showed the largest linear range, highest sensitivity, and most reproducibility. We then applied our developed DIA assays to urine samples from non-aggressive (n = 48) and aggressive (n = 35) prostate cancer patients. In conclusion, we developed assays for the six glycoproteins, evaluated the analytical performances of each assay in DIA, PRM, and PRM acquisition modes on three types of mass spectrometry instruments, and chose the DIA assays for the quantitative analysis of urine samples from patients with aggressive and non-aggressive prostate cancer.

Development of Tier 2 LC-MRM-MS protein quantification methods for liquid biopsies

In the pursuit of personalized diagnostics and tailored treatments, quantitative protein tests contribute to a more precise definition of health and disease. The development of new quantitative protein tests should be driven by an unmet clinical need and performed in a collaborative effort that involves all stakeholders. With regard to the analytical part, mass spectrometry (MS)-based platforms are an excellent tool for quantification of specific proteins in body fluids, for example focused on cancer. The obtained readouts have great potential in determining tumor aggressiveness to facilitate treatment decisions, and can furthermore be used to monitor patient response. Internationally standardized TNM classifications of malignant tumors are beneficial for diagnosis, however treatment outcome and survival of cancer patients is poorly predicted. To this end, the importance of the tumor microenvironment has endorsed the introduction of the tumor-stroma ratio as a prognostic parameter in solid primary tumor types. Currently, the stromal content of tumor tissues is determined via routine diagnostic pathology slides. With the development of liquid chromatography (LC)-MS methods we aim at quantification of tumor-stroma specific proteins in body fluids. In this mini-review the analytical aspect of this developmental trajectory is further detailed.

Label-Free Quantification from Direct Infusion Shotgun Proteome Analysis (DISPA-LFQ) with CsoDIAq Software

Large-scale proteome analysis requires rapid and high-throughput analytical methods. We recently reported a new paradigm in proteome analysis where direct infusion and ion mobility are used instead of liquid chromatography (LC) to achieve rapid and high-throughput proteome analysis. Here, we introduce an improved direct infusion shotgun proteome analysis protocol including label-free quantification (DISPA-LFQ) using CsoDIAq software. With CsoDIAq analysis of DISPA data, we can now identify up to ∼2000 proteins from the HeLa and 293T proteomes, and with DISPA-LFQ, we can quantify ∼1000 proteins from no more than 1 μg of sample within minutes. The identified proteins are involved in numerous valuable pathways including central carbon metabolism, nucleic acid replication and transport, protein synthesis, and endocytosis. Together with a high-throughput sample preparation method in a 96-well plate, we further demonstrate the utility of this technology for performing high-throughput drug analysis in human 293T cells. The total time for data collection from a whole 96-well plate is approximately 8 h. We conclude that the DISPA-LFQ strategy presents a valuable tool for fast identification and quantification of proteins in complex mixtures, which will power a high-throughput proteomic era of drug screening, biomarker discovery, and clinical analysis.

MatrisomeDB 2.0: 2023 updates to the ECM-protein knowledge database

The extracellular matrix (ECM) is a complex assembly of proteins that constitutes the scaffold organizing cells, tissues, and organs. Over the past decade, mass-spectrometry-based proteomics has become the method of choice to profile the composition of the ECM, or the matrisome, of tissues. To assist non-specialists with the reuse of ECM proteomic datasets, we released MatrisomeDB (https://matrisomedb.org) in 2020. Here, we report the expansion of the database to include 25 new curated studies on the ECM of 24 new tissues in addition to datasets on tissues previously included, more than doubling the size of the original database and achieving near-complete coverage of the in-silico predicted matrisome. We further enhanced data visualization by maps of peptides and post-translational-modifications detected onto domain-based representations and 3D structures of ECM proteins. We also referenced external resources to facilitate the design of targeted mass spectrometry assays. Last, we implemented an abstract-mining tool that generates an enrichment word cloud from abstracts of studies in which a queried protein is found with higher confidence and higher abundance relative to other studies in MatrisomeDB.

Proteomic genotyping of SNP of Complement Factor H (CFH) Y402H and I62V using multiple reaction monitoring (MRM) assays

The single nucleotide polymorphisms (SNPs) of complement factor H (CFH) gene are well-known genetic risk factors for age-related macular degeneration (AMD). To identify whether the measurement of plasma protein concentrations of CFH variants using the multiple reaction monitoring (MRM) assay can determine the genotypes of CFH SNP rs1061170 and rs800292, 120 patients with AMD and 26 controls were included in this study. The number of cases were TT:TC:CC = 121:24:1 in CFH SNP Y402H and GG:AG:AA = 72:57:17 in CFH SNP I62V. Plasma concentrations of tryptic peptides were measured using the MRM assay, and tyrosine/histidine (Y/H) and valine/isoleucine (V/I) CFH variant protein ratios were obtained. To discriminate the genotypes by the plasma protein ratios, cut-off values were set for Y/H ratios (TT: > 4.428; TC: 1.00-4.428; CC: < 1.00) and V/I ratios (GG: > 1.09; AG: 0.0089-1.08; AA: < 0.0089). Correlation analysis revealed that the plasma CFH variant protein ratios and genotypes of CFH were exactly matched (100%) without overlap in the total patients and controls. The measurement of plasma protein CFH variants using the MRM assay can accurately identify the genotypes of CFH SNPs of Y402H and I62V.