Spectrum of Apolipoprotein AI and Apolipoprotein AII Proteoforms and Their Associations With Indices of Cardiometabolic Health: The CARDIA Study

Deep Profiling of Plasma Proteoforms with Engineered Nanoparticles for Top-Down Proteomics

The dynamic range challenge for the detection of proteins and their proteoforms in human plasma has been well documented. Here, we use the nanoparticle protein corona approach to enrich low-abundance proteins selectively and reproducibly from human plasma and use top-down proteomics to quantify differential enrichment for the 2841 detected proteoforms from 114 proteins. Furthermore, nanoparticle enrichment allowed top-down detection of proteoforms between ∼1 μg/mL and ∼10 pg/mL in absolute abundance, providing up to a 105-fold increase in proteome depth over neat plasma in which only proteoforms from abundant proteins (>1 μg/mL) were detected. The ability to monitor medium and some low-abundant proteoforms through reproducible enrichment significantly extends the applicability of proteoform research by adding depth beyond albumin, immunoglobins, and apolipoproteins to uncover many involved in immunity and cell signaling. As proteoforms carry unique information content relative to peptides, this report opens the door to deeper proteoform sequencing in clinical proteomics of disease or aging cohorts.

Trypsin Partially Cleaves Apolipoprotein A-I (ApoA-I) Precursor into Mature ApoA-I Hindering the Quantification of Naturally Occurring ApoA-I Proteoforms by Liquid Chromatography in Multiple Reaction Monitoring Mode Mass Spectrometry (LC-MRM-MS)

Apolipoprotein A-I (ApoA-I), one of the most abundant proteins in plasma and the major protein component of high-density lipoprotein (HDL), is naturally found in several proteoforms; two of them are ProApoA-I and mature ApoA-I. These two proteoforms of ApoA-I coexist in biological samples and differ only in their N-terminal end. Virtually, the only way to differentiate them is by detecting the proteoform-specific N-terminal proteolytic peptides (RHFWQQDEPPQSPWDR and DEPPQSPWDR, respectively) using liquid chromatography in multiple reaction monitoring mode mass spectrometry (LC-MRM-MS). We have developed a bottom-up LC-MRM-MS method to simultaneously detect proApoA-I and mature ApoA-I. To test the specificity of the method, we digested with trypsin purified mature ApoA-I and recombinant proApoA-I. As expected, only the N-term peptide corresponding to the mature ApoA-I proteoform (DEPPQSPWDR) was detected when digesting mature ApoA-I. However, the digestion of the proApoA-I produced not only the N-terminal peptide corresponding to proApoA-I (RHFWQQDEPPQSPWDR) but also the N-terminal tryptic peptide corresponding to mature ApoA-I (DEPPQSPWDR). This effect was produced by standard and high-specificity trypsin as well as by the Arg-C enzyme in a self-limited manner (approximately 10% of the total). The synthetic proApo-I peptide is not cleaved by trypsin, suggesting that the here reported effect is dependent on protein conformation. The effect is not negligible, as it can be detected by LC-MRM-MS, and correction calculations should be applied to accurately quantify proApoA-I and mature ApoA-I in biological samples where these two proteoforms may coexist.

Mass Spectrometry-Based Top-Down Proteomics in Nanomedicine: Proteoform-Specific Measurement of Protein Corona

Conventional mass spectrometry (MS)-based bottom-up proteomics (BUP) analysis of the protein corona [i.e., an evolving layer of biomolecules, mostly proteins, formed on the surface of nanoparticles (NPs) during their interactions with biomolecular fluids] enabled the nanomedicine community to partly identify the biological identity of NPs. Such an approach, however, fails to pinpoint the specific proteoforms─distinct molecular variants of proteins in the protein corona. The proteoform-level information could potentially advance the prediction of the biological fate and pharmacokinetics of nanomedicines. Recognizing this limitation, this study pioneers a robust and reproducible MS-based top-down proteomics (TDP) technique for characterizing proteoforms in the protein corona. Our TDP approach has successfully identified about 900 proteoforms in the protein corona of polystyrene NPs, ranging from 2 to 70 kDa, revealing proteoforms of 48 protein biomarkers with combinations of post-translational modifications, signal peptide cleavages, and/or truncations─details that BUP could not fully discern. This advancement in MS-based TDP offers a more advanced approach to characterize NP protein coronas, deepening our understanding of NPs' biological identities. We, therefore, propose using both TDP and BUP strategies to obtain more comprehensive information about the protein corona, which, in turn, can further enhance the diagnostic and therapeutic efficacy of nanomedicine technologies.

Deep Profiling of Plasma Proteoforms with Engineered Nanoparticles for Top-down Proteomics

The dynamic range challenge for detection of proteins and their proteoforms in human plasma has been well documented. Here, we use the nanoparticle protein corona approach to enrich low-abundant proteins selectively and reproducibly from human plasma and use top-down proteomics to quantify differential enrichment for the 2841 detected proteoforms from 114 proteins. Furthermore, nanoparticle enrichment allowed top-down detection of proteoforms between ∼1 µg/mL and ∼10 pg/mL in absolute abundance, providing up to 10 5 -fold increase in proteome depth over neat plasma in which only proteoforms from abundant proteins (>1 µg/mL) were detected. The ability to monitor medium and some low abundant proteoforms through reproducible enrichment significantly extends the applicability of proteoform research by adding depth beyond albumin, immunoglobins and apolipoproteins to uncover many involved in immunity and cell signaling. As proteoforms carry unique information content relative to peptides, this report opens the door to deeper proteoform sequencing in clinical proteomics of disease or aging cohorts.

Comparative analysis of human tear fluid and aqueous humor proteomes

PURPOSE

Technological advancements allowing for the analysis of low-volume samples have led to the investigation of human tear fluid and aqueous humor (AH) as potential biomarker sources. However, acquiring AH samples poses significant challenges, making human tear fluid a more accessible alternative. This study aims to compare the protein compositions of these two biofluids to evaluate their suitability for biomarker discovery.

METHODS

Paired tear and AH samples were collected from 20 patients undergoing cataract surgery. Tear samples were collected using Schirmer strips prior to surgery, and AH samples were collected from the anterior chamber immediately after corneal incision. Proteins were extracted and analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS).

RESULTS

A total of 481 proteins were identified in greater than 50% of the tear samples, and 191 proteins were detected in greater than 50% of the AH samples. Of these proteins, 82 were found to be common between the two biofluids, with ALB, LTF, TF, LCN1, and IGKC being the most abundant.

CONCLUSION

Although tear fluid and the AH are functionally independent and physically separated, many of the proteins detected in AH were also detected in tears. This direct comparison of the proteomic content of tear fluid and AH may aid in further investigation of tear fluid as a source of readily accessible biomarkers for various human diseases.

Top-down proteomics

Proteoforms, which arise from post-translational modifications, genetic polymorphisms and RNA splice variants, play a pivotal role as drivers in biology. Understanding proteoforms is essential to unravel the intricacies of biological systems and bridge the gap between genotypes and phenotypes. By analysing whole proteins without digestion, top-down proteomics (TDP) provides a holistic view of the proteome and can decipher protein function, uncover disease mechanisms and advance precision medicine. This Primer explores TDP, including the underlying principles, recent advances and an outlook on the future. The experimental section discusses instrumentation, sample preparation, intact protein separation, tandem mass spectrometry techniques and data collection. The results section looks at how to decipher raw data, visualize intact protein spectra and unravel data analysis. Additionally, proteoform identification, characterization and quantification are summarized, alongside approaches for statistical analysis. Various applications are described, including the human proteoform project and biomedical, biopharmaceutical and clinical sciences. These are complemented by discussions on measurement reproducibility, limitations and a forward-looking perspective that outlines areas where the field can advance, including potential future applications.

Machine learning-based health environmental-clinical risk scores in European children

BACKGROUND

Early life environmental stressors play an important role in the development of multiple chronic disorders. Previous studies that used environmental risk scores (ERS) to assess the cumulative impact of environmental exposures on health are limited by the diversity of exposures included, especially for early life determinants. We used machine learning methods to build early life exposome risk scores for three health outcomes using environmental, molecular, and clinical data.

METHODS

In this study, we analyzed data from 1622 mother-child pairs from the HELIX European birth cohorts, using over 300 environmental, 100 child peripheral, and 18 mother-child clinical markers to compute environmental-clinical risk scores (ECRS) for child behavioral difficulties, metabolic syndrome, and lung function. ECRS were computed using LASSO, Random Forest and XGBoost. XGBoost ECRS were selected to extract local feature contributions using Shapley values and derive feature importance and interactions.

RESULTS

ECRS captured 13%, 50% and 4% of the variance in mental, cardiometabolic, and respiratory health, respectively. We observed no significant differences in predictive performances between the above-mentioned methods.The most important predictive features were maternal stress, noise, and lifestyle exposures for mental health; proteome (mainly IL1B) and metabolome features for cardiometabolic health; child BMI and urine metabolites for respiratory health.

CONCLUSIONS

Besides their usefulness for epidemiological research, our risk scores show great potential to capture holistic individual level non-hereditary risk associations that can inform practitioners about actionable factors of high-risk children. As in the post-genetic era personalized prevention medicine will focus more and more on modifiable factors, we believe that such integrative approaches will be instrumental in shaping future healthcare paradigms.

Targeted Quantification of Proteoforms in Complex Samples by Proteoform Reaction Monitoring

Existing mass spectrometric assays used for sensitive and specific measurements of target proteins across multiple samples, such as selected/multiple reaction monitoring (SRM/MRM) or parallel reaction monitoring (PRM), are peptide-based methods for bottom-up proteomics. Here, we describe an approach based on the principle of PRM for the measurement of intact proteoforms by targeted top-down proteomics, termed proteoform reaction monitoring (PfRM). We explore the ability of our method to circumvent traditional limitations of top-down proteomics, such as sensitivity and reproducibility. We also introduce a new software program, Proteoform Finder (part of ProSight Native), specifically designed for the easy analysis of PfRM data. PfRM was initially benchmarked by quantifying three standard proteins. The linearity of the assay was shown over almost 3 orders of magnitude in the femtomole range, with limits of detection and quantification in the low femtomolar range. We later applied our multiplexed PfRM assay to complex samples to quantify biomarker candidates in peripheral blood mononuclear cells (PBMCs) from liver-transplanted patients, suggesting their possible translational applications. These results demonstrate that PfRM has the potential to contribute to the accurate quantification of protein biomarkers for diagnostic purposes and to improve our understanding of disease etiology at the proteoform level.

Mass spectrometry-based proteomics for advancing solid organ transplantation research

Scarcity of high-quality organs, suboptimal organ quality assessment, unsatisfactory pre-implantation procedures, and poor long-term organ and patient survival are the main challenges currently faced by the solid organ transplant (SOT) field. New biomarkers for assessing graft quality pre-implantation, detecting, and predicting graft injury, rejection, dysfunction, and survival are critical to provide clinicians with invaluable prediction tools and guidance for personalized patients' treatment. Additionally, new therapeutic targets are also needed to reduce injury and rejection and improve transplant outcomes. Proteins, which underlie phenotypes, are ideal candidate biomarkers of health and disease statuses and therapeutic targets. A protein can exist in different molecular forms, called proteoforms. As the function of a protein depends on its exact composition, proteoforms can offer a more accurate basis for connection to complex phenotypes than protein from which they derive. Mass spectrometry-based proteomics has been largely used in SOT research for identification of candidate biomarkers and therapeutic intervention targets by so-called "bottom-up" proteomics (BUP). However, such BUP approaches analyze small peptides in lieu of intact proteins and provide incomplete information on the exact molecular composition of the proteins of interest. In contrast, "Top-down" proteomics (TDP), which analyze intact proteins retaining proteoform-level information, have been only recently adopted in transplantation studies and already led to the identification of promising proteoforms as biomarkers for organ rejection and dysfunction. We anticipate that the use of top-down strategies in combination with new technological advancements in single-cell and spatial proteomics could drive future breakthroughs in biomarker and therapeutic target discovery in SOT.

Orbitrap Mass Spectrometry and High-Field Asymmetric Waveform Ion Mobility Spectrometry (FAIMS) Enable the in-Depth Analysis of Human Serum Proteoforms

Blood serum and plasma are arguably the most commonly analyzed clinical samples, with dozens of proteins serving as validated biomarkers for various human diseases. Top-down proteomics may provide additional insights into disease etiopathogenesis since this approach focuses on protein forms, or proteoforms, originally circulating in blood, potentially providing access to information about relevant post-translational modifications, truncations, single amino acid substitutions, and many other sources of protein variation. However, the vast majority of proteomic studies on serum and plasma are carried out using peptide-centric, bottom-up approaches that cannot recapitulate the original proteoform content of samples. Clinical laboratories have been slow to adopt top-down analysis, also due to higher sample handling requirements. In this study, we describe a straightforward protocol for intact proteoform sample preparation based on the depletion of albumin and immunoglobulins, followed by simplified protein fractionation via polyacrylamide gel electrophoresis. After molecular weight-based fractionation, we supplemented the traditional liquid chromatography-tandem mass spectrometry (LC-MS2) data acquisition with high-field asymmetric waveform ion mobility spectrometry (FAIMS) to further simplify serum proteoform mixtures. This LC-FAIMS-MS2 method led to the identification of over 1000 serum proteoforms < 30 kDa, outperforming traditional LC-MS2 data acquisition and more than doubling the number of proteoforms identified in previous studies.

Advancements in portable instruments based on affinity-capture-migration and affinity-capture-separation for use in clinical testing and life science applications

The shift from testing at centralized diagnostic laboratories to remote locations is being driven by the development of point-of-care (POC) instruments and represents a transformative moment in medicine. POC instruments address the need for rapid results that can inform faster therapeutic decisions and interventions. These instruments are especially valuable in the field, such as in an ambulance, or in remote and rural locations. The development of telehealth, enabled by advancements in digital technologies like smartphones and cloud computing, is also aiding in this evolution, allowing medical professionals to provide care remotely, potentially reducing healthcare costs and improving patient longevity. One notable POC device is the lateral flow immunoassay (LFIA), which played a major role in addressing the COVID-19 pandemic due to its ease of use, rapid analysis time, and low cost. However, LFIA tests exhibit relatively low analytical sensitivity and provide semi-quantitative information, indicating either a positive, negative, or inconclusive result, which can be attributed to its one-dimensional format. Immunoaffinity capillary electrophoresis (IACE), on the other hand, offers a two-dimensional format that includes an affinity-capture step of one or more matrix constituents followed by release and electrophoretic separation. The method provides greater analytical sensitivity, and quantitative information, thereby reducing the rate of false positives, false negatives, and inconclusive results. Combining LFIA and IACE technologies can thus provide an effective and economical solution for screening, confirming results, and monitoring patient progress, representing a key strategy in advancing diagnostics in healthcare.

Preparative Electrophoresis for HDL Particle Size Separation and Intact-Mass Apolipoprotein Proteoform Analysis

The most abundant proteins on high-density lipoproteins (HDLs), apolipoproteins A-I (APOA1) and A-II (APOA2), are determinants of HDL function with 15 and 9 proteoforms (chemical-structure variants), respectively. The relative abundance of these proteoforms in human serum is associated with HDL cholesterol efflux capacity, and cholesterol content. However, the association between proteoform concentrations and HDL size is unknown. We employed a novel native-gel electrophoresis technique, clear native gel-eluted liquid fraction entrapment electrophoresis (CN-GELFrEE) paired with mass spectrometry of intact proteins to investigate this association. Pooled serum was fractionated using acrylamide gels of lengths 8 and 25 cm. Western blotting determined molecular diameter and intact-mass spectrometry determined proteoform profiles of each fraction. The 8- and 25 cm experiments generated 19 and 36 differently sized HDL fractions, respectively. The proteoform distribution varied across size. Fatty-acylated APOA1 proteoforms were associated with larger HDL sizes (Pearson's R = 0.94, p = 4 × 10-7) and were approximately four times more abundant in particles larger than 9.6 nm than in total serum; HDL-unbound APOA1 was acylation-free and contained the pro-peptide proAPOA1. APOA2 proteoform abundance was similar across HDL sizes. Our results establish CN-GELFrEE as an effective lipid-particle separation technique and suggest that acylated proteoforms of APOA1 are associated with larger HDL particles.

The known unknowns of apolipoprotein glycosylation in health and disease

Apolipoproteins, the protein component of lipoproteins, play an important role in lipid transport, lipoprotein assembly, and receptor recognition. Apolipoproteins are glycosylated and the glycan moieties play an integral role in apolipoprotein function. Changes in apolipoprotein glycosylation correlate with several diseases manifesting in dyslipidemias. Despite their relevance in apolipoprotein function and diseases, the total glycan repertoire of most apolipoproteins remains undefined. This review summarizes the current knowledge and knowledge gaps regarding human apolipoprotein glycan composition, structure, glycosylation site, and functions. Given the relevance of glycosylation to apolipoprotein function, we expect that future studies of apolipoprotein glycosylation will contribute new understanding of disease processes and uncover relevant biomarkers and therapeutic targets. Considering these future efforts, we also provide a brief overview of current mass spectrometry based technologies that can be applied to define detailed glycan structures, site-specific compositions, and the role of emerging approaches for clinical applications in biomarker discovery and personalized medicine.

Resolution of apolipoprotein A1 and A2 proteoforms: their cardiometabolic correlates and implications for future research

PURPOSE OF REVIEW

A 'proteoform' is defined as one specific protein structural form that results from the combination of allelic variation, alternative RNA splicing, and/or posttranslational modifications (PTMs) in specific locations on the amino acid backbone. Apolipoproteins A1 and A2 are highly abundant apolipoproteins that mediate HDL structure and function. ApoA1 and apoA2 are known to undergo PTMs, which results in multiple proteoforms. However, the catalogue of apoA1 and apoA2 proteoforms as well as their associations with cardiometabolic health characteristics has not been described until recently. In this brief review, we discuss recent efforts to catalogue the spectrum of apoA1 and apoA2 proteoforms, to understand the relationships between the relative abundance of these proteoforms with cardiometabolic phenotypic characteristics, and we will discuss the implications of these findings to future research.

RECENT FINDINGS

A broad spectrum of apoA1 and apoA2 proteoforms has been characterized. Although, the types of apoA1 and A2 proteoforms are consistent across individuals, the relative abundances of proteoforms can vary substantially between individuals. Proteoform-specific associations with cardiometabolic characteristics in humans, independent of absolute apolipoprotein abundance, have been described. These recent findings suggest multiple levels of protein structural variation that arise from known and unknown metabolic pathways may be important markers or mediators of cardiometabolic health.

SUMMARY

Understanding the associations between apolipoprotein proteoforms and phenotype may lead to enhanced understanding of how apolipoproteins mediate lipid metabolism and affect atherosclerotic cardiovascular disease (ASCVD) risk, which may lead to discovery of novel markers of risk and/or key mechanistic insights that may drive further druggable targets for modifying lipid metabolism and reducing ASCVD risk.

Apolipoprotein A-II, a Player in Multiple Processes and Diseases

Apolipoprotein A-II (apoA-II) is the second most abundant apolipoprotein in high-density lipoprotein (HDL) particles, playing an important role in lipid metabolism. Human and murine apoA-II proteins have dissimilar properties, partially because human apoA-II is dimeric whereas the murine homolog is a monomer, suggesting that the role of apoA-II may be quite different in humans and mice. As a component of HDL, apoA-II influences lipid metabolism, being directly or indirectly involved in vascular diseases. Clinical and epidemiological studies resulted in conflicting findings regarding the proatherogenic or atheroprotective role of apoA-II. Human apoA-II deficiency has little influence on lipoprotein levels with no obvious clinical consequences, while murine apoA-II deficiency causes HDL deficit in mice. In humans, an increased plasma apoA-II concentration causes hypertriglyceridemia and lowers HDL levels. This dyslipidemia leads to glucose intolerance, and the ensuing high blood glucose enhances apoA-II transcription, generating a vicious circle that may cause type 2 diabetes (T2D). ApoA-II is also used as a biomarker in various diseases, such as pancreatic cancer. Herein, we provide a review of the most recent findings regarding the roles of apoA-II and its functions in various physiological processes and disease states, such as cardiovascular disease, cancer, amyloidosis, hepatitis, insulin resistance, obesity, and T2D.

Native Mass Spectrometry at the Convergence of Structural Biology and Compositional Proteomics

ConspectusBiology is driven by a vast set of molecular interactions that evolved over billions of years. Just as covalent modifications like acetylations and phosphorylations can change a protein's function, so too can noncovalent interactions with metals, small molecules, and other proteins. However, much of the language of protein-level biology is left either undiscovered or inferred, as traditional methods used in the field of proteomics use conditions that dissociate noncovalent interactions and denature proteins.Just in the past few years, mass spectrometry (MS) has evolved the capacity to preserve and subsequently characterize the complete composition of endogenous protein complexes. Using this "native" type of mass spectrometry, a complex can be activated to liberate some or all of its subunits, typically via collisions with neutral gas or solid surfaces and isolated before further characterization ("Native Top-Down MS," or nTDMS). The subunit mass, the parent ion mass, and the fragment ions of the activated subunits can be used to piece together the precise molecular composition of the parent complex. When performed en masse in discovery mode (i.e., "native proteomics"), the interactions of life─including protein modifications─will eventually be clarified and linked to dysfunction in human disease states.In this Account, we describe the current and future components of the native MS toolkit, covering the challenges the field faces to characterize ever larger bioassemblies. Each of the three pillars of native proteomics are addressed: (i) separations, (ii) top-down mass spectrometry, and (iii) integration with structural biology. Complexes such as endogenous nucleosomes can be targeted now using nTDMS, whereas virus particles, exosomes, and high-density lipoprotein particles will be tackled in the coming few years. The future work to adequately address the size and complexity of mega- to gigadalton complexes will include native separations, single ion mass spectrometry, and new data types. The use of nTDMS in discovery mode will incorporate native-compatible separation techniques to maximize the number of proteoforms in complexes identified. With a new wave of innovations, both targeted and discovery mode nTDMS will expand to include extremely scarce and exceedingly heterogeneous bioassemblies. Understanding the proteinaceous interactions of life and how they go wrong (e.g., misfolding, forming complexes in dysfunctional stoichiometries and configurations) will not only inform the development of life-restoring therapeutics but also deepen our understanding of life at the molecular level.

Stent-based delivery of AAV2 vectors encoding oxidation-resistant apoA1

In-stent restenosis (ISR) complicates revascularization in the coronary and peripheral arteries. Apolipoprotein A1 (apoA1), the principal protein component of HDL possesses inherent anti-atherosclerotic and anti-restenotic properties. These beneficial traits are lost when wild type apoA1(WT) is subjected to oxidative modifications. We investigated whether local delivery of adeno-associated viral (AAV) vectors expressing oxidation-resistant apoA1(4WF) preserves apoA1 functionality. The efflux of 3H-cholesterol from macrophages to the media conditioned by endogenously produced apoA1(4WF) was 2.1-fold higher than for apoA1(WT) conditioned media in the presence of hypochlorous acid emulating conditions of oxidative stress. The proliferation of apoA1(WT)- and apoA1(4FW)-transduced rat aortic smooth muscle cells (SMC) was inhibited by 66% ± 10% and 65% ± 11%, respectively, in comparison with non-transduced SMC (p < 0.001). Conversely, the proliferation of apoA1(4FW)-transduced, but not apoA1(WT)-transduced rat blood outgrowth endothelial cells (BOEC) was increased 41% ± 5% (p < 0.001). Both apoA1 transduction conditions similarly inhibited basal and TNFα-induced reactive oxygen species in rat aortic endothelial cells (RAEC) and resulted in the reduced rat monocyte attachment to the TNFα-activated endothelium. AAV2-eGFP vectors immobilized reversibly on stainless steel mesh surfaces through the protein G/anti-AAV2 antibody coupling, efficiently transduced cells in culture modeling stent-based delivery. In vivo studies in normal pigs, deploying AAV2 gene delivery stents (GDS) preloaded with AAV2-eGFP in the coronary arteries demonstrated transduction of the stented arteries. However, implantation of GDS formulated with AAV2-apoA1(4WF) failed to prevent in-stent restenosis in the atherosclerotic vasculature of hypercholesterolemic diabetic pigs. It is concluded that stent delivery of AAV2-4WF while feasible, is not effective for mitigation of restenosis in the presence of severe atherosclerotic disease.