Detection Of Low-abundance Proteins Research Articles

An enrichment strategy based on hydrophobic tagging and reversed-phase chromatographic separation for the analysis of lysine-containing peptides

Lysine (K) is widely used in the design of lysine-targeted crosslinkers, structural elucidation of protein complexes, and analysis of protein-protein interactions. In "shotgun" proteomics, which is based on liquid chromatography-tandem mass spectrometry (LC-MS/MS), proteins from complex samples are enzymatically digested, generating thousands of peptides and presenting significant challenges for the direct analysis of K-containing peptides. In view of the lack of effective methods for the enrichment of K-containing peptides, this work developed a method which based on a hydrophobic-tag-labeling reagent C10-S-S-NHS and reversed-phase chromatography (termed as HYTARP) to achieve the efficient enrichment and identification of K-containing peptides from complex samples. The C10-S-S-NHS synthesized in this work successfully labeled standard peptides containing various numbers of K and the labeling efficiency achieved up to 96% for HeLa cell protein tryptic digests. By investigating the retention behavior of these labeled peptides in C18 RP column, we found that most K-labeled peptides were eluted once when acetonitrile percentage reached 57.6% (v/v). Further optimization of the elution gradient enabled the efficient separation and enrichment of the K-labeled peptides in HeLa digests via a stepwise elution gradient. The K-labeled peptides accounted for 90% in the enriched peptides, representing an improvement of 35% compared with the number of peptides without the enrichment. The dynamic range of proteins quantified from the enriched K-containing peptides spans 5-6 orders of magnitude, and realized the detection of low-abundance proteins in the complex sample. In summary, the HYTARP strategy offers a straightforward and effective approach for reducing sample complexity and improving the identification coverage of K-containing peptides and low-abundance proteins.

Ultrasensitive detection of MMP-8 in saliva for monitoring periodontitis using an Immuno-CRISPR/Cas12a assay

Periodontitis is one of the most prevalent oral diseases, and the diagnosis and monitoring of periodontitis rely on clinical and imaging examinations. Matrix metalloproteinase-8 (MMP-8) in saliva is a reliable indicator of periodontitis. The traditional detection method is enzyme-linked immunosorbent assay (ELISA), which requires professional expertise and is not sensitive enough to low-abundance protein detection. In this study, we developed a nanoimmunoassay combined with clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR associated protein (Cas)12a for ultrasensitive detection of MMP-8 in saliva. Antibody-DNA-gold nanoparticles (AuNPs) and trans-cleavage activity of CRISPR/Cas12a were employed for signal amplification. With this protocol, the limit of detection (LoD) for MMP-8 was reduced to the fg/mL, indicating 100-fold higher sensitivity than that of the commercial ELISA kit and its amenability for ultrasensitive detection of trace proteins. The diagnostic sensitivity of the assay was 100 %, and the specificity was 83.3 % based on the testing of 23 clinical saliva samples. The sensitivity and specificity were considerably higher than those for ELISA. Thus, this immuno-CRISPR/Cas12a assay holds promise for both diagnosing and monitoring periodontitis in clinical settings.

Enhancing saliva diagnostics: The impact of amylase depletion on MALDI-ToF MS profiles as applied to COVID-19

IntroductionHuman saliva contains a wealth of proteins that can be monitored for disease diagnosis and progression. Saliva, which is easy to collect, has been extensively studied for the diagnosis of numerous systemic and infectious diseases. However, the presence of amylase, the most abundant protein in saliva, can obscure the detection of low-abundance proteins by matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-ToF MS), thus reducing its diagnostic utility. ObjectivesIn this study, we used a device to deplete salivary amylase from water-gargle samples by affinity adsorption. Following depletion, saliva proteome profiling was performed using MALDI-ToF MS on gargle samples from individuals confirmed to have COVID-19 based on nasopharyngeal (NP) swab reverse transcription quantitative polymerase chain reaction (RT-qPCR). ResultsThe depletion of amylase led to increased signal intensities of various peaks and the detection of previously unobserved peaks in the MALDI-ToF MS spectra. The overall specificity and sensitivity after amylase depletion were 100% and 85.17%, respectively, for detecting COVID-19. ConclusionThis simple, rapid, and inexpensive technique for depleting salivary amylase can reveal spectral diversity in saliva using MALDI-ToF MS, expose low-abundance proteins, and assist in establishing novel biomarkers for diseases.

Proximity Ligation Assay to Detect the Proximity Between Host Proteins and Viral Proteins of HIV-1.

The study of host-pathogen interaction often requires interrogating the protein-protein interactions and examining post-translational modifications of the proteins. Traditional protein detection strategies are limited in their sensitivity, specificity, and multiplexing capabilities. The Proximity Ligation Assay (PLA), a versatile and powerful molecular technique, can overcome these limitations. PLA blends the specificity of antibodies, two antibodies detecting two different epitopes on the same or two different proteins, with the amplification efficiency of a polymerase to allow highly specific and sensitive detection of low-abundant proteins, protein-protein interactions, or protein modifications. In this protocol, we describe the application of PLA to detect the proximity between HIV-1 Tat with one of its cellular partners, p65, in an infected host cell. The protocol could be applied to any other context with slight modifications. Of note, PLA can only confirm the physical proximity between two epitopes or proteins; however, the proximity need not necessarily allude to the functional interaction between the two proteins.

Deep Learning-Assisted Single-Molecule Detection of Protein Post-translational Modifications with a Biological Nanopore.

Protein post-translational modifications (PTMs) play a crucial role in countless biological processes, profoundly modulating protein properties on both spatial and temporal scales. Protein PTMs have also emerged as reliable biomarkers for several diseases. However, only a handful of techniques are available to accurately measure their levels, capture their complexity at a single molecule level, and characterize their multifaceted roles in health and disease. Nanopore sensing provides high sensitivity for the detection of low-abundance proteins, holding the potential to impact single-molecule proteomics and PTM detection, in particular. Here, we demonstrate the ability of a biological nanopore, the pore-forming toxin aerolysin, to detect and distinguish α-synuclein-derived peptides bearing single or multiple PTMs, namely, phosphorylation, nitration, and oxidation occurring at different positions and in various combinations. The characteristic current signatures of the α-synuclein peptide and its PTM variants could be confidently identified by using a deep learning model for signal processing. We further demonstrate that this framework can quantify α-synuclein peptides at picomolar concentrations and detect the C-terminal peptides generated by digestion of full-length α-synuclein. Collectively, our work highlights the advantage of using nanopores as a tool for simultaneous detection of multiple PTMs and facilitates their use in biomarker discovery and diagnostics.

A micro-flow, high-pH, reversed-phase peptide fractionation and collection system for targeted and in-depth proteomics of low-abundance proteins in limiting samples

We present a method and a simple system for high-pH RP-LC peptide fractionation of small sample amounts (30–60 µg), at micro-flow rates with micro-liter fraction collection using ammonium bicarbonate as an optimized buffer for system stability and robustness. The method is applicable to targeted mass spectrometry approaches and to in-depth proteomic studies where the amount of sample is limited. Using targeted proteomics with peptide standards, we present the method's analytical parameters, and potential in increasing the detection of low-abundance proteins that are difficult to quantify with direct targeted or global LC-MS analyses. This fractionation system increased peptide signals by up to 18-fold, while maintaining high quantitative precision, with high fractionation reproducibility across varied sample sets. In real applications, it increased the detection of targeted endogenous peptides by two-fold in a 25 cell-cycle-control protein panel, and in-depth MS analyses of nuclear extracts, it allowed the detection of up to 8,896 proteins with 138,417 peptides in 24-concatenated fractions compared to 3,344 proteins with 23,093 peptides without fractionation. In a relevant biological problem of CDK4/6-inhibitors and breast cancer, the method reproduced known information and revealed novel insights, highlighting that it can be successfully applied in studies involving low-abundance proteins and limited samples.•Tested nine high-pH buffer/solvent systems to obtain a robust, effective, and reproducible micro-flow fractionation method which was devoid of commonly encountered LC clogging/pressure issues after months of use.•Peptide enrichment method to improve detection and quantitation of low-abundance proteins in targeted and in-depth proteomic studies.•Can be applied to diverse protein samples where the available amount is limited.

Abstract 5305: Detection and quantification of proteins using protein identification by short-epitope mapping (PrISM)

Abstract Introduction: Here, we demonstrate Protein Identification by Short-epitope Mapping (PrISM), which aims to provide comprehensive proteome analysis with broad dynamic range at single-molecule resolution by interrogating immobilized, intact proteins in parallel using multi-affinity probes. Improving the dynamic range and scale for protein analyses will enable a deeper understanding of low abundant protein in all stages of cancer progression. In addition, enabling the interrogation of single-molecules will provide a deeper understanding of protein diversity, such as the proteoforms resulting from non-canonical post-translational modifications inherent to cancer1. The combination of single-molecule sensitivity with comprehensive proteome coverage could also open the door for highly sensitive and specific diagnostics. Methods: PrISM uses non-traditional affinity reagents with high affinity and low specificity that bind to short epitopes in multiple proteins. Sample proteins were conjugated to DNA nanoparticles and deposited on a high-density patterned flow cell at optically resolvable locations. Multi-affinity probes were applied to sample proteins over multiple cycles to generate binding patterns for each single-molecule protein, which are translated to protein identifications and quantities using a custom machine learning approach. We acquired PrISM data on native biological and control samples using dozens of multi-affinity probes targeting trimer or tetramer sequences. Results: We report single-molecule deposition of over 1 billion DNA nanoparticle complexes on a flow cell. We demonstrate how the PrISM methodology identifies individual protein molecules through iterative probing with our multi-affinity probes. Further, we provide an analytical assessment of the sensitivity and specificity of PrISM and demonstrate the ability to accurately estimate the false identification rate of these proteins using a target-decoy based statistical approach. Conclusions: Combining single-molecule analysis, intact (non-digested) proteins, and iterative probing, PrISM provides a new tool for quantitative proteomics. We demonstrate linear and reproducible quantification of proteins using PrISM, potentially enabling detection of low abundant proteins and proteoforms associated with cancer. The ability to make comprehensive measurements of intact proteins at single-molecule resolution could accelerate basic cancer research through to the clinic.

Photoactive hydrogels for pre-concentration, labelling, and controlled release of proteins.

We report a novel hydrogel for pre-concentration, fluorescent labelling, and light-triggered release of proteins for detection of low abundance biomarkers. The hydrogel was a co-polymer of acrylamide/bisacrylamide and methacrylamide attached to fluorescein isothiocyanate via a light cleavable bond and a poly(ethylene glycol) spacer arm of molecular weight of 3400 g mol-1. Unlike previous work, proteins were captured by an irreversible chemical reaction rather than by non-covalent affinity binding or physical entrapment. Because the protein-reactive group was attached to fluorescein, which in turn was coupled to the hydrogel by a photocleavable bond, on release the protein was labelled with fluorescein. Our hydrogel offered a pre-concentration factor of up to 236 for a model protein, streptavidin. Each protein molecule was labelled with 85 fluorescein molecules, and 50% of the proteins in the hydrogel were released after UV exposure for ∼100 s. The proteins released from the hydrogel were captured in biotinylated microtitre plates and detected by fluorescence, allowing measurement of at least 0.01 ppm (or ∼166 pM) of protein in sample solutions. The reported hydrogel is promising for detection of low abundance proteins while being less laborious than enzyme-linked immunosorbent assay and less affected by changes in environmental conditions than label-free biosensors.

Carbon dots-functionalized extended gate organic field effect transistor-based biosensors for low abundance proteins.

Organic field effect transistors have emerged as promising platforms for biosensing applications. However, the challenge lies in optimizing functionalization strategies for the sensing interface, enabling the simultaneous detection of low abundance proteins while maintaining device performance. Here, we designed a carbon dots-functionalized extended gate organic field effect transistor. Leveraging the advantages of facile synthesis, tunable modification, small particle size, and cost-effectiveness of carbon dots, we implemented their integration onto the electrode surface. Through harnessing the covalent interactions of functional groups on the surface of carbon dots, we achieved effective immobilization of low abundance proteins without compromising device performance. Consequently, this biosensor exhibits a remarkably low limit of detection of 2.7 pg mL-1 and demonstrates high selectivity for the carcinoembryonic antigen. These findings highlight the superior capabilities of carbon dots in enhancing biosensor performance and emphasize their potential for early cancer detection.

Ultrasensitive detection of gastric cancer biomarkers via a frequency shift-based SERS microfluidic chip.

Highly sensitive protein biomarker detection is critical for the diagnosis of gastric cancer (GC), however the accurate and sensitive detection of low-abundance proteins in early-stage GC is still a challenge. Herein, a surface-enhanced Raman scattering frequency shift assay was performed on a developed microfluidic chip for the detection of GC protein biomarkers carcinoembryonic antigen (CEA) and vascular endothelial growth factor (VEGF). The chip is made up of three groups of parallel channels and each parallel channel consists of two reaction regions, enabling the simultaneous analysis of multiple biomarkers in multiple samples. The presence of CEA and VEGF in the sample can be captured by the 4-mercaptobenzoic acid (4-MBA)-conjugated antibody functionalized gold nano-sheet (GNS-) substrate, resulting in the Raman frequency shift. As a result, a typical Raman frequency shift of 4-MBA presented a linear relationship with the concentration of CEA and VEGF. The limit of detection (LOD) of the proposed SERS microfluidic chip reaches as low as 0.38 pg mL-1 for CEA and 0.82 pg mL-1 for VEGF. During the detection process, only one step of sample addition is involved, which eliminates the multiple reaction step-induced nonspecific adsorption and significantly increases the convenience and specificity. In addition, serum samples from GC patients and healthy subjects were tested and the results were in good agreement with the current gold-standard method ELISA, suggesting the potential application of the SERS microfluidic chip in clinical settings for early diagnosis and prognosis of GC.

Subcellular Fractionation for DIGE-Based Proteomics.

Mass spectrometry-based protein methodologies have revolutionized the field of analytical biochemistry and enable the identification of hundreds to thousands of proteins in biological fluids, cell lines, and tissue. This methodology requires the initial separation of a protein constellation, and this has been successfully achieved using gel-based techniques, particularly that of fluorescence two-dimensional difference gel electrophoresis (2D-DIGE). However, given the complexity of the proteome, fractionation techniques may be required to optimize the detection of low-abundance proteins, which are often underrepresented but which may represent important players in health and disease. Such subcellular fractionation protocols typically utilize density-gradient centrifugation and have enabled the enrichment of crude microsomes, the cytosol, the plasmalemma, the nuclei, and the mitochondria. In this chapter, we describe the experimental steps involved in the enrichment of crude microsomes from the skeletal muscle using differential centrifugation and subsequent verification of enrichment by gel electrophoresis and immunoblotting, prior to comparative 2D-DIGE analysis.

Core-shell SERS nanotags-based western blot

Western blot (WB) is the most commonly used scheme for protein identification in life science, but it still faces great challenges in the accurate quantitative detection of low-abundance proteins. Here, we proposed a novel surface-enhanced Raman scattering-based Western blot (SERS-WB) to solve this challenge. SERS nanotags were used as quantitative labels of proteins, which were composed of gold-silver core-shell nanoparticles, and Nile blue A (NBA) molecules were anchored on the interface of the core and shell. The results show that the SERS-WB possessed excellent sensitivity with detection limit of glyceraldehyde-3-phosphate dehydrogenase (GAPDH) protein of 0.15 pg, as well as wide linear dynamic range (LDR) of 382 fg to 382 ng. In addition, the target protein on nitrocellulose (NC) membrane could be directly identified by colorimetric signal due to the aggregation effect of nanoparticles, which greatly simplifies the procedure. This as-proposed strategy will bring new thoughts to technological innovation of WB.

Single Molecule-Level Detection via Liposome-Based Signal Amplification Mass Spectrometry Counting Assay.

Because of the low atomization and/or ionization efficiencies of many biological macromolecules, the application of mass spectrometry to the direct quantitative detection of low-abundance proteins and nucleic acids remains a significant challenge. Herein, we report mass spectrum tags (MS-tags) based upon gold nanoparticle (AuNP)-templated phosphatidylcholine phospholipid (DSPC) liposomes, which exhibit high and reliable signals via electrospray ionization (ESI). Using these MS-tags, we constructed a liposome signal amplification-based mass spectrometric (LSAMS) "digital" counting assay to enable ultrasensitive detection of target nucleic acids. The LSAMS system consists of liposomes modified with a gold nanoparticle core and surface-anchored photocleavable DNA. In the presence of target nucleic acids, the modified liposome and a magnetic bead simultaneously hybridize with the target nucleic acid. After magnetic separation and photolysis, the MS-tag is released and can be analyzed by ESI-MS. At very low target concentrations, one liposome particle corresponds to one target molecule; thus, the concentration of the target can be estimated by counting the number of liposomes. With this assay, hepatitis C (HCV) virus RNA was successfully analyzed in clinical samples.

Ultrasensitive Label-Free Detection of Protein–Membrane Interaction Exemplified by Toxin-Liposome Insertion

Measuring the high-affinity binding of proteins to liposome membranes remains a challenge. Here, we show an ultrasensitive and direct detection of protein binding to liposome membranes using high throughput second harmonic scattering (SHS). Perfringolysin O (PFO), a pore-forming toxin, with a highly membrane selective insertion into cholesterol-rich membranes is used. PFO inserts only into liposomes with a cholesterol concentration >30%. Twenty mole-percent cholesterol results in neither SHS-signal deviation nor pore formation as seen by cryo-electron microscopy of PFO and liposomes. PFO inserts into cholesterol-rich membranes of large unilamellar vesicles in an aqueous solution with Kd = (1.5 ± 0.2) × 10–12 M. Our results demonstrate a promising approach to probe protein–membrane interactions below sub-picomolar concentrations in a label-free and noninvasive manner on 3D systems. More importantly, the volume of protein sample is ultrasmall (<10 μL). These findings enable the detection of low-abundance proteins and their interaction with membranes.

A new mass spectral library for high-coverage and reproducible analysis of the Plasmodium falciparum-infected red blood cell proteome.

Background Plasmodium falciparum causes the majority of malaria mortality worldwide, and the disease occurs during the asexual red blood cell (RBC) stage of infection. In the absence of an effective and available vaccine, and with increasing drug resistance, asexual RBC stage parasites are an important research focus. In recent years, mass spectrometry–based proteomics using data-dependent acquisition has been extensively used to understand the biochemical processes within the parasite. However, data-dependent acquisition is problematic for the detection of low-abundance proteins and proteome coverage and has poor run-to-run reproducibility.ResultsHere, we present a comprehensive P. falciparum–infected RBC (iRBC) spectral library to measure the abundance of 44,449 peptides from 3,113 P. falciparum and 1,617 RBC proteins using a data-independent acquisition mass spectrometric approach. The spectral library includes proteins expressed in the 3 morphologically distinct RBC stages (ring, trophozoite, schizont), the RBC compartment of trophozoite-iRBCs, and the cytosolic fraction from uninfected RBCs. This spectral library contains 87% of all P. falciparum proteins that have previously been reported with protein-level evidence in blood stages, as well as 692 previously unidentified proteins. The P. falciparum spectral library was successfully applied to generate semi-quantitative proteomics datasets that characterize the 3 distinct asexual parasite stages in RBCs, and compared artemisinin-resistant (Cam3.IIR539T) and artemisinin-sensitive (Cam3.IIrev) parasites.ConclusionA reproducible, high-coverage proteomics spectral library and analysis method has been generated for investigating sets of proteins expressed in the iRBC stage of P. falciparum malaria. This will provide a foundation for an improved understanding of parasite biology, pathogenesis, drug mechanisms, and vaccine candidate discovery for malaria.

High Resolution Proteomic Analysis of Subcellular Fractionated Boar Spermatozoa Provides Comprehensive Insights Into Perinuclear Theca-Residing Proteins.

The perinuclear theca (PT) is a highly condensed, largely insoluble protein structure that surrounds the nucleus of eutherian spermatozoa. Recent reports have indicated that the PT unexpectedly houses several somatic proteins, such as core histones, which may be important post-fertilization during re-modelling of the male pronucleus, yet little is known regarding the overall proteomic composition of the PT. Here, we report the first in depth, label-free proteomic characterization of the PT of boar spermatozoa following the implementation of a long-established subcellular fractionation protocol designed to increase the detection of low abundance proteins. A total of 1,802 proteins were identified, a result that represents unparalleled depth of coverage for the boar sperm proteome and exceeds the entire annotated proteome of the Sus scrofa species so far. In the PT structure itself, we identified 813 proteins and confirmed the presence of previously characterized PT proteins including the core histones H2A, H2B, H3 and H4, as well as Ras-related protein Rab-2A (RAB2A) and Rab-2B (RAB2B) amongst other RAB proteins. In addition to these previously characterized PT proteins, our data revealed that the PT is replete in proteins critical for sperm-egg fusion and egg activation, including: Izumo family members 1–4 (IZUMO1-4) and phosphoinositide specific phospholipase ζ (PLCZ1). Through Ingenuity Pathway Analysis, we found surprising enrichment of endoplasmic reticulum (ER) proteins and the ER-stress response in the PT. This is particularly intriguing as it is currently held that the ER structure is lost during testicular sperm maturation. Using the String and Cytoscape tools to visualize protein-protein interactions revealed an intricate network of PT protein complexes, including numerous proteasome subunits. Collectively, these data suggest that the PT may be a unique site of cellular homeostasis that houses an abundance of protein degradation machinery. This fits with previous observations that the PT structure dissociates first within the oocyte post-fertilization. It remains to be explored whether proteasome subunits within the PT actively assist in the protein degradation of paternal cell structures post-fertilization and how aberrations in PT protein content may delay embryonic development.

Comparing Offline Hplc Fractionation of Peptides Versus Intact Proteins to Enhance Detection of Low Abundance Proteins in Liquid Chromatography–Tandem Mass Spectrometry

Comparing Offline Hplc Fractionation of Peptides Versus Intact Proteins to Enhance Detection of Low Abundance Proteins in Liquid Chromatography–Tandem Mass Spectrometry

A novel method for detecting heteromeric complexes at synaptic level by combining a modified method of proximity ligation assay with transmission electron microscopy

The heteromeric complexes of adenosine 2A receptor (A2AR) and N-methyl-D-aspartate receptor (NMDAR) have recently been confirmed in cell experiments, while its in situ detection at the subcellular level of brain tissue has not yet been achieved. Proximity Ligation Assay (PLA) enables the detection of low-abundance proteins and their interactions at the cellular level with high specificity and sensitivity, while Transmission electron microscope (TEM) is an excellent tool for observing subcellular structures. To develop a highly efficient and reproducible technique for in situ detection of protein interactions at subcellular levels, in this study, we modified the standard PLA sample preparation method to make the samples suitable for analysis by transmission electron microscopy. Using this technique, we successfully detected the heteromers of A2AR and NMDAR1, the essential subunit of NMDA receptor on the hippocampal synaptic structure in mice. Our results show that the distribution of this heteromer is different in different hippocampal subregions. This technique holds the potential for being a reliable method to detect protein interactions at the subcellular level and unravel their unknown functions.

Lattice-like 3-dimensional DNA nanostructure-based bioseparation strategy for highly accurate quantification of low-abundance cancer biomarker via mass spectrometry

Disease-associated low-abundance protein biomarkers have attracted growing attention for the diagnosis and treatment of numerous diseases. Traditional immunoassays are commonly adopted for the detection of low-abundance proteins due to fast and sensitive analyses, but the used antibodies are normally lack of satisfactory selectivity that may bring about biased results. Immunoaffinity mass spectrometry approach can remedy the deficiency of antibodies and has emerged as a powerful technique for highly selective and accurate quantification assay. However, due to extremely large dynamic range of the body fluids, efficient bioseparation of low-abundance proteins is a key issue before mass spectrometry (MS) quantification. In this study, a 3-dimensional DNA tetrahedron (DNA TET) nanomaterial, MoS2@Fe3O4@AuNPs@DNA TET@Ab, was meticulously designed and constructed for the enrichment of cancer biomarker heat shock protein 90 alpha (HSP90α) in human plasma. The nanocomposites have combined advantages of quick magnetic response, a large amount of surface antibodies and excellent stability. Furthermore, through the spatial separation by pendant probes on DNA TETs, antibodies are immobilized with appropriate density and well controlled arrangement. The feasibility of this approach was demonstrated by the pleasing quantitative performance for HSP90α with fine repeatability and a dynamic range from 20 ng/g to 480 ng/g. Compared with the extraction efficiency of conventional nanomaterials with random antibody distribution, the concentrations of HSP90α captured by our materials were at least 2 folds higher, which were more close to ELISA data. Through this ingenious assay, highly efficient enrichment by controlled antibodies arrangement on the nanomaterials and accurate quantification of low-abundance proteins by MS were achieved. This promising strategy can be extended to quantify other low-abundance proteins from the biological samples in clinic.

BoxCar increases the depth and reproducibility of diabetic urinary proteome analysis

Mass spectrometry-based proteomics performs well in high throughput detection of urinary proteins. Nonetheless, protein identification depth and reproducibility remain the challenges in diabetic urinary proteome with high complexity and broad dynamic range, especially for low-abundant proteins. As a new data acquisition strategy, the BoxCar method was reported to benefit for low-abundant protein identification. Whether it is propitious to diabetic samples with high dynamic range proteomes has not been discussed yet. We aimed to apply BoxCar method to diabetic urine sample analysis, and to compare it with standard data dependent acquisition (DDA) method on protein identification in detail. We performed seven technical replicates analysis on two urine samples from healthy individuals and diabetic patients to evaluate protein detection of BoxCar and standard DDA methods on single sample. Further comparison of two methods was made on multiple diabetic urine samples. BoxCar could increase over 20% of identified proteins and performed better quantitative reproducibility than standard DDA method either in single or multiple diabetic urinary samples. BoxCar also improved the detection of low-abundant proteins. Functional enrichment analysis of normal albuminuria or microalbuminuria samples indicated that BoxCar acquired more diabetes-related biological information. The study demonstrates that BoxCar could enhance the depth and reproducibility in diabetic urinary proteome analysis, which provides reference for mass spectrometry approach selection in clinical urinary proteomic research.