Urine Proteomics: Evaluation of Different Sample Preparation Workflows for Quantitative, Reproducible, and Improved Depth of Analysis

Benchmarking low- and high-throughput protein cleanup and digestion methods for human fecal metaproteomics

The application of fecal metaproteomics to large-scale studies of the gut microbiota requires high-throughput analysis and standardized experimental protocols. Although high-throughput protein cleanup and digestion methods are increasingly used in shotgun proteomics, no studies have yet critically compared such protocols using human fecal samples. In this study, human fecal protein extracts were processed using several different protocols based on three main approaches: filter-aided sample preparation (FASP), solid-phase-enhanced sample preparation (SP3), and suspension trapping (S-Trap). These protocols were applied in both low-throughput (i.e., microtube-based) and high-throughput (i.e., microplate-based) formats, and the final peptide mixtures were analyzed by liquid chromatography coupled to high-resolution tandem mass spectrometry. The FASP-based methods and the combination of SP3 with in-StageTips (iST) yielded the best results in terms of the number of peptides identified through a database search against gut microbiome and human sequences. The efficiency of protein digestion, the ability to preserve hydrophobic peptides and high molecular weight proteins, and the reproducibility of the methods were also evaluated for the different protocols. Other relevant variables, including interindividual variability of stool, duration of protocols, and total costs, were considered and discussed. In conclusion, the data presented here can significantly contribute to the optimization and standardization of sample preparation protocols in human fecal metaproteomics. Furthermore, the promising results obtained with the high-throughput methods are expected to encourage the development of automated workflows and their application to large-scale gut microbiome studies.IMPORTANCEFecal metaproteomics is an experimental approach that allows the investigation of gut microbial functions, which are involved in many different physiological and pathological processes. Standardization and automation of sample preparation protocols in fecal metaproteomics are essential for its application in large-scale studies. Here, we comparatively evaluated different methods, available also in a high-throughput format, enabling two key steps of the metaproteomics analytical workflow (namely, protein cleanup and digestion). The results of our study provide critical information that may be useful for the optimization of metaproteomics experimental pipelines and their implementation in laboratory automation systems.

Assessing the precision of a detergent-assisted cartridge precipitation workflow for non-targeted quantitative proteomics

Detergent-based workflows incorporating sodium dodecyl sulfate (SDS) necessitate additional steps for detergent removal ahead of mass spectrometry (MS). These steps may lead to variable protein recovery, inconsistent enzyme digestion efficiency, and unreliable MS signals. To validate a detergent-based workflow for quantitative proteomics, we herein evaluate the precision of a bottom-up sample preparation strategy incorporating cartridge-based protein precipitation with organic solvent to deplete SDS. The variance of data-independent acquisition (SWATH-MS) data was isolated from sample preparation error by modelling the variance as a function of peptide signal intensity. Our SDS-assisted cartridge workflow yield a coefficient of variance (CV) of 13%-14%. By comparison, conventional (detergent-free) in-solution digestion increased the CV to 50%; in-gel digestion provided lower CVs between 14% and 20%. By filtering peptides predicting to display lower precision, we further enhance the validity of data in global comparative proteomics. These results demonstrate the detergent-based precipitation workflow is a reliable approach for in depth, label-free quantitative proteome analysis.

Quantitative comparison of the renal pelvic urine and bladder urine to examine modifications of the urine proteome by the lower urinary tract

PURPOSE

Urine proteome is a valuable reservoir of biomarkers for disease diagnosis and monitoring. Following formation as the plasma filtrate in the kidney, urine is progressively modified by the active reabsorption and secretion of the urinary tract. However, little is known about how the urine proteome changes as it passes along the urinary tract.

EXPERIMENTAL DESIGN

To investigate this, we compared the proteome composition of the renal pelvis urine (RPU) and individually self-voided bladder urine (BU) collected from seven unilateral urinary tract obstruction male patients by LC-MS/MS screening. To our knowledge, this is the first proteomic comparison of RPU and BU samples from the same individual.

RESULTS

Overall, RPU and BU proteomes did not exhibit proteins that were exclusively present in all samples of one urine type while in none of the other type. Nonetheless, BU had more overrepresented proteins that were observed at a higher frequency than RPU. Label-free quantitative analyses revealed BU-RPU differential proteins that are enriched in exosomes and extracellular proteins. However, the differences were not significant after corrections for multiple testing. Interestingly, we observed a significant increase of collagen peptides with hydroxyproline modifications in the BU samples, suggesting differences in protein modifications.

CONCLUSIONS AND CLINICAL RELEVANCE

Our study revealed no substantial differences at the protein level between the BU and RPU samples. Future investigations with expanded cohorts would provide more insights about the urothelial-urinary interactions.

Stratification of neurogenic bladder risk in spina bifida using the urinary peptidome

Neurogenic bladder poses a major morbidity in children with spina bifida (SB), and videourodynamic studies (VUDS) are used to stratify this risk. This small-scale pilot study utilized current mass-spectrometry-based proteomic approaches to identify peptides or proteins in urine that may differentiate children at high risk of developing renal complications from a neurogenic bladder. Twenty-two urine samples of which nine had high bladder pressure storage that put the upper urinary tract at risk, while 13 with a lower risk for renal compromise were analyzed. More than 1,900 peptides across all 22 samples were quantified, and 115 peptides differed significantly (P < 0.05) between the two groups. Using machine learning approaches five peptides that showed the greatest differences between these two clinical categories were used to build a classifier. We tested this classifier by blind analysis of an additional six urine samples and showed that it correctly assigned the unknown samples in their proper risk category. These promising results indicate that a urinary screening test based on peptides could be performed on a regular basis to stratify the neurogenic bladder into low or high-risk categories. Expanding this work to larger cohorts as well as across a broad spectrum of urodynamics outcomes may provide a useful diagnostic test for neurogenic bladder.NEW & NOTEWORTHY This approach could help risk stratify the neurogenic bladder in patients with spina bifida and could allow us to safely defer on up to 1/3 of urodynamic studies. These pilot data justify a larger trial before this approach becomes a clinical tool.

Comparison of clean catch and bag urine using LC-MS/MS proteomics in infants

BACKGROUND

Urinary proteomics identifies the totality of urinary proteins and can therefore help in getting an early and precise diagnosis of various pathological processes in the kidneys. In infants, non-invasive urine collection is most commonly accomplished with a urine bag or clean catch. The influence of those two collection methods on urinary proteomics was assessed in this study.

METHODS

Thirty-two urine samples were collected in infants using urine bag and clean catch within 24 h. Nine boys and seven girls with a mean age of 4.3 ± 2.9 months were included (5 × post-pyelonephritis, 10 × non-kidney disease, 1 × chronic kidney disease (CKD)). Liquid chromatography-mass spectrometry (LC-MS/MS) was performed in data-independent acquisition (DIA) mode. Protein identification and quantification were achieved using Spectronaut.

RESULTS

A total of 1454 urinary proteins were detected. Albumin and α-1-microglobulin were detected the most. The 18 top-abundant proteins accounted for 50% of total abundance. The number of proteins was slightly, but insignificantly higher in clean catch (957 ± 245) than in bag urine (876 ± 255). The median intensity was 1.2 × higher in the clean catch. Overall, differential detection of proteins was 29% between the collection methods; however, it diminished to 3% in the 96 top-abundant proteins. Pearson's correlation coefficient was 0.81 ± 0.11, demonstrating a high intraindividual correlation. A principal component analysis and a heat map showed clustering according to diagnoses and patients rather than to the collection method.

CONCLUSION

Urinary proteomics shows a high correlation with minor variation in low-abundant proteins between the two urine collection methods. The biological characteristics overrule this variation. Graphical abstract A higher resolution version of the Graphical abstract is available as Supplementary information.

Circulating Proteins as Diagnostic Markers in Gastric Cancer

Gastric cancer (GC) is a highly malignant disease affecting humans worldwide and has a poor prognosis. Most GC cases are detected at advanced stages due to the cancer lacking early detectable symptoms. Therefore, there is great interest in improving early diagnosis by implementing targeted prevention strategies. Markers are necessary for early detection and to guide clinicians to the best personalized treatment. The current semi-invasive endoscopic methods to detect GC are invasive, costly, and time-consuming. Recent advances in proteomics technologies have enabled the screening of many samples and the detection of novel biomarkers and disease-related signature signaling networks. These biomarkers include circulating proteins from different fluids (e.g., plasma, serum, urine, and saliva) and extracellular vesicles. We review relevant published studies on circulating protein biomarkers in GC and detail their application as potential biomarkers for GC diagnosis. Identifying highly sensitive and highly specific diagnostic markers for GC may improve patient survival rates and contribute to advancing precision/personalized medicine.

Targeted protein quantitation in human body fluids by mass spectrometry

Human body fluids (biofluids) contain various proteins, some of which reflect individuals' physiological conditions or predict diseases. Therefore, the analysis of biofluids can provide substantial information on novel biomarkers for clinical diagnosis and prognosis. In the past decades, mass spectrometry (MS)-based technologies have been developed as proteomic strategies not only for the identification of protein biomarkers but also for biomarker verification/validation in body fluids for clinical applications. The main advantage of targeted MS-based methodologies is the accurate and specific simultaneous quantitation of multiple biomarkers with high sensitivity. Here, we review MS-based methodologies that are currently used for the targeted quantitation of protein components in human body fluids, especially in plasma, urine, cerebrospinal fluid, and saliva. In addition, the currently used MS-based methodologies are summarized with a specific focus on applicable clinical sample types, MS configurations, and acquisition modes.

Advances in proteomics: characterization of the innate immune system after birth and during inflammation

Proteomics is the characterization of the protein composition, the proteome, of a biological sample. It involves the large-scale identification and quantification of proteins, peptides, and post-translational modifications. This review focuses on recent developments in mass spectrometry-based proteomics and provides an overview of available methods for sample preparation to study the innate immune system. Recent advancements in the proteomics workflows, including sample preparation, have significantly improved the sensitivity and proteome coverage of biological samples including the technically difficult blood plasma. Proteomics is often applied in immunology and has been used to characterize the levels of innate immune system components after perturbations such as birth or during chronic inflammatory diseases like rheumatoid arthritis (RA) and inflammatory bowel disease (IBD). In cancers, the tumor microenvironment may generate chronic inflammation and release cytokines to the circulation. In these situations, the innate immune system undergoes profound and long-lasting changes, the large-scale characterization of which may increase our biological understanding and help identify components with translational potential for guiding diagnosis and treatment decisions. With the ongoing technical development, proteomics will likely continue to provide increasing insights into complex biological processes and their implications for health and disease. Integrating proteomics with other omics data and utilizing multi-omics approaches have been demonstrated to give additional valuable insights into biological systems.

Urine-HILIC: Automated Sample Preparation for Bottom-Up Urinary Proteome Profiling in Clinical Proteomics

Urine provides a diverse source of information related to a patient's health status and is ideal for clinical proteomics due to its ease of collection. To date, most methods for the preparation of urine samples lack the throughput required to analyze large clinical cohorts. To this end, we developed a novel workflow, urine-HILIC (uHLC), based on an on-bead protein capture, clean-up, and digestion without the need for bottleneck processing steps such as protein precipitation or centrifugation. The workflow was applied to an acute kidney injury (AKI) pilot study. Urine from clinical samples and a pooled sample was subjected to automated sample preparation in a KingFisher™ Flex magnetic handling station using the novel approach based on MagReSyn® HILIC microspheres. For benchmarking, the pooled sample was also prepared using a published protocol based on an on-membrane (OM) protein capture and digestion workflow. Peptides were analyzed by LCMS in data-independent acquisition (DIA) mode using a Dionex Ultimate 3000 UPLC coupled to a Sciex 5600 mass spectrometer. The data were searched in Spectronaut™ 17. Both workflows showed similar peptide and protein identifications in the pooled sample. The uHLC workflow was easier to set up and complete, having less hands-on time than the OM method, with fewer manual processing steps. Lower peptide and protein coefficient of variation was observed in the uHLC technical replicates. Following statistical analysis, candidate protein markers were filtered, at ≥8.35-fold change in abundance, ≥2 unique peptides and ≤1% false discovery rate, and revealed 121 significant, differentially abundant proteins, some of which have known associations with kidney injury. The pilot data derived using this novel workflow provide information on the urinary proteome of patients with AKI. Further exploration in a larger cohort using this novel high-throughput method is warranted.

Suspension Trapping-Based Sample Preparation Workflow for In-Depth Plant Phosphoproteomics

Plant phosphoproteomics provides a global view of phosphorylation-mediated signaling in plants; however, it demands high-throughput methods with sensitive detection and accurate quantification. Despite the widespread use of protein precipitation for removing contaminants and improving sample purity, it limits the sensitivity and throughput of plant phosphoproteomic analysis. The multiple handling steps involved in protein precipitation lead to sample loss and process variability. Herein, we developed an approach based on suspension trapping (S-Trap), termed tandem S-Trap-IMAC (immobilized metal ion affinity chromatography), by integrating an S-Trap micro-column with a Fe-IMAC tip. Compared with a precipitation-based workflow, the tandem S-Trap-IMAC method deepened the coverage of the Arabidopsis (Arabidopsis thaliana) phosphoproteome by more than 30%, with improved number of multiply phosphorylated peptides, quantification accuracy, and short sample processing time. We applied the tandem S-Trap-IMAC method for studying abscisic acid (ABA) signaling in Arabidopsis seedlings. We thus discovered that a significant proportion of the phosphopeptides induced by ABA are multiply phosphorylated peptides, indicating their importance in early ABA signaling and quantified several key phosphorylation sites on core ABA signaling components across four time points. Our results show that the optimized workflow aids high-throughput phosphoproteome profiling of low-input plant samples.

Potential Urine Proteomic Biomarkers for Focal Segmental Glomerulosclerosis and Minimal Change Disease

Primary focal segmental glomerulosclerosis (FSGS), along with minimal change disease (MCD), are diseases with primary podocyte damage that are clinically manifested by the nephrotic syndrome. The pathogenesis of these podocytopathies is still unknown, and therefore, the search for biomarkers of these diseases is ongoing. Our aim was to determine of the proteomic profile of urine from patients with FSGS and MCD. Patients with a confirmed diagnosis of FSGS (n = 30) and MCD (n = 9) were recruited for the study. For a comprehensive assessment of the severity of FSGS a special index was introduced, which was calculated as follows: the first score was assigned depending on the level of eGFR, the second score—depending on the proteinuria level, the third score—resistance to steroid therapy. Patients with the sum of these scores of less than 3 were included in group 1, with 3 or more—in group 2. The urinary proteome was analyzed using liquid chromatography/mass spectrometry. The proteome profiles of patients with severe progressive FSGS from group 2, mild FSGS from group 1 and MCD were compared. Results of the label free analysis were validated using targeted LC-MS based on multiple reaction monitoring (MRM) with stable isotope labelled peptide standards (SIS) available for 47 of the 76 proteins identified as differentiating between at least one pair of groups. Quantitative MRM SIS validation measurements for these 47 proteins revealed 22 proteins with significant differences between at least one of the two group pairs and 14 proteins were validated for both comparisons. In addition, all of the 22 proteins validated by MRM SIS analysis showed the same direction of change as at the discovery stage with label-free LC-MS analysis, i.e., up or down regulation in MCD and FSGS1 against FSGS2. Patients from the FSGS group 2 showed a significantly different profile from both FSGS group 1 and MCD. Among the 47 significantly differentiating proteins, the most significant were apolipoprotein A-IV, hemopexin, vitronectin, gelsolin, components of the complement system (C4b, factors B and I), retinol- and vitamin D-binding proteins. Patients with mild form of FSGS and MCD showed lower levels of Cystatin C, gelsolin and complement factor I.

Synthesis of Phenylboronic Acid-Functionalized Magnetic Nanoparticles for Sensitive Soil Enzyme Assays

Soil enzymes, such as invertase, urease, acidic phosphatase and catalase, play critical roles in soil biochemical reactions and are involved in soil fertility. However, it remains a great challenge to efficiently concentrate soil enzymes and sensitively assess enzyme activity. In this study, we synthesized phenylboronic acid-functionalized magnetic nanoparticles to rapidly capture soil enzymes for sensitive soil enzyme assays. The iron oxide magnetic nanoparticles (MNPs) were firstly prepared by the co-precipitation method and then functionalized by (3-aminopropyl)triethoxysilane, polyethyleneimine and phenylboric acid in turn, obtaining the final nanoparticles (MNPPBA). Protein-capturing assays showed that the functionalized MNPs had a much higher protein-capturing capacity than the naked MNPs (56% versus 6%). Moreover, MNPPBA almost thoroughly captured the tested enzymes, i.e., urease, invertase, and alkaline phosphatase, from enzyme solutions. Based on MNPPBA, a soil enzyme assay method was developed by integration of enzyme capture, magnetic separation and trace enzyme analysis. The method was successfully applied in determining trace enzyme activity in rhizosphere soil. This study provides a strategy to sensitively determine soil enzyme activity for mechanistic investigation of soil fertility and plant–microbiome interaction.

A review of suspension trapping digestion method in bottom-up proteomics

The standard bottom-up proteomic workflow is comprised of sample preparation, data acquisition, and data analysis. While the latter two parts have made considerable advances in the last decade, sample preparation has remained an important challenge within the workflow due to the multi-step nature of complex biological samples, and still requires much development. Several sample preparation methods have been developed and used in the last two decades, including in-gel, in-solution, on-bead, filter-aided sample preparation, and suspension trapping, to improve reproducibility, efficiency, scalability, and reduce handling time of this process. One of the most recent methods developed and applied in proteomics studies in recent years is suspension trapping, which combines rapid detergent removal, reactor-type protein digestion, and peptide clean-up in a tip or spin column. Suspension trapping is a simple, rapid, and reproducible digestion method that can effectively handle proteins in low microgram or sub-microgram amounts. This review discusses the benefits of the suspension trapping digestion method in relation to its development and application in bottom-up proteomics studies. We also discuss recent applications of suspension trapping digestion to different sample types and the features of the suspension trapping digestion method compared with other sample preparation methods. This article is protected by copyright. All rights reserved.

Review of Liquid Chromatography-Mass Spectrometry-Based Proteomic Analyses of Body Fluids to Diagnose Infectious Diseases

Rapid and precise diagnostic methods are required to control emerging infectious diseases effectively. Human body fluids are attractive clinical samples for discovering diagnostic targets because they reflect the clinical statuses of patients and most of them can be obtained with minimally invasive sampling processes. Body fluids are good reservoirs for infectious parasites, bacteria, and viruses. Therefore, recent clinical proteomics methods have focused on body fluids when aiming to discover human- or pathogen-originated diagnostic markers. Cutting-edge liquid chromatography-mass spectrometry (LC-MS)-based proteomics has been applied in this regard; it is considered one of the most sensitive and specific proteomics approaches. Here, the clinical characteristics of each body fluid, recent tandem mass spectroscopy (MS/MS) data-acquisition methods, and applications of body fluids for proteomics regarding infectious diseases (including the coronavirus disease of 2019 [COVID-19]), are summarized and discussed.

Proteomics for Low Cell Numbers: How to Optimize the Sample Preparation Workflow for Mass Spectrometry Analysis

Nowadays, massive genomics and transcriptomics data can be generated at the single-cell level. However, proteomics in this setting is still a big challenge. Despite the great improvements in sensitivity and performance of mass spectrometry instruments and the better knowledge on sample preparation processing, it is widely acknowledged that multistep proteomics workflows may lead to substantial sample loss, especially when working with paucicellular samples. Still, in clinical fields, frequently limited sample amounts are available for downstream analysis, thereby hampering comprehensive characterization at protein level. To aim at better protein and peptide recoveries, we compare existing and novel approaches in the multistep sample preparation protocols for mass spectrometry studies, from sample collection, cell lysis, protein quantification, and electrophoresis/staining to protein digestion, peptide recovery, and LC-MS/MS instruments. From this critical evaluation, we conclude that the recent innovations and technologies, together with high quality management of samples, make proteomics on paucicellular samples possible, which will have immediate impact for the proteomics community.

Urinary proteomics for kidney dysfunction: insights and trends

Introduction: Kidney dysfunction poses a high burden on patients and health care systems. Early detection and accurate prediction of kidney disease progression remains a major challenge. Compared to existing clinical parameters, urinary proteomics has the potential to reveal molecular alterations within the kidney that may alter its function before the onset of clinical symptoms. Thus, urinary proteomics has greater prognostic potential for assessment of kidney dysfunction progression.Areas covered: Advances in urinary proteomics for major causes of kidney dysfunction are discussed. The application of urinary extracellular vesicles for studying kidney dysfunction are discussed. Technological advances in urinary proteomics are discussed. The literature was identified using a database search for titles containing 'proteom*' and 'urin*' and published within the past 5 years. Retrieved literature was manually filtered to retain kidney dysfunctions-related studies.Expert opinion: Despite major advances, diagnosis by urinary proteomics has not been fully applied in any clinical settings. This could be attributed to the complex nature of kidney diseases, in addition to the constraints on study power and feasibility of incorporating mass spectrometry techniques in daily routine analysis. Nevertheless, we are confident that advances in urinary proteomics will soon provide superior insights into kidney disease beyond existing clinical parameters.

Urinary Proteomics Reveals Promising Biomarkers in Menstrually Related and Post-Menopause Migraine

Migraine is an invalidating neuro-vascular disorder largely spread in the world population. Currently, its pathophysiology is not yet completely understood. The purpose of this study was to investigate the urinary proteome of women suffering from menstrually related migraine (MM) and post-menopause migraine (PM) in comparison with non-headache women as controls, to search potential biomarkers of these migraine sub-types. Urine samples were analyzed by mono-dimensional gel electrophoresis (SDS-PAGE) and two-dimensional gel electrophoresis (2DE) coupled to liquid chromatography-mass spectrometry (LC-MS/MS). Twenty-one urinary proteins were found significantly dysregulated in MM and PM (p < 0.05). The STRING Analysis database revealed interaction between 15 proteins, which were mainly involved in the immune and inflammatory response. Seven of the most considerable proteins were further quantified by western blot: protein S100A8 (S10A8), up-regulated in MM, uromodulin (UROM), alpha-1-microglobulin (AMBP), gelsolin (GELS), prostaglandin-H2 D-isomerase (PTGDS), over-expressed in PM, apolipoprotein A-I (APOA1), and transthyretin (TTHY), respectively down- and up-regulated in both migraineur groups vs controls. These candidate biomarkers might be involved in the neurophysiological network of MM and PM, thus helping to better understand the pathophysiology of these migraine forms. If validated in large-scale studies, this protein cluster could become a distinctive target for clinical applications in migraine diagnosis and treatment.

Comparative nanometallomics as a new tool for nanosafety evaluation

Nanosafety evaluation is paramount since it is necessary not only for human health protection and environmental integrity but also as a cornerstone for industrial and regulatory bodies. The current nanometallomics did not cover non-metallic nanomaterials, which is an important part of nanomaterials. In this critical review, the concept of nanometallomics was expanded to incorporate all nanomaterials. The impacts on metal(loid) and metallo-biomolecular homeostasis by nanomaterials will be focused upon in nanometallomics study. Besides, the impacts on elemental and biomolecular homeostasis by metallo-nanomaterials are also considered as the research subjects of nanometallomics. Based on the new concept of nanometallomics, comparative nanometallomics was proposed as a new tool for nanosafety evaluation, which is high throughput and will be precise considering the nature of machine learning techniques. The perspectives of nanometallomics like metallo-wide association study and non-target nanometallomics were put forward.

Urinary proteome profiling for stratifying patients with familial Parkinson's disease

The prevalence of Parkinson's disease (PD) is increasing but the development of novel treatment strategies and therapeutics altering the course of the disease would benefit from specific, sensitive, and non‐invasive biomarkers to detect PD early. Here, we describe a scalable and sensitive mass spectrometry (MS)‐based proteomic workflow for urinary proteome profiling. Our workflow enabled the reproducible quantification of more than 2,000 proteins in more than 200 urine samples using minimal volumes from two independent patient cohorts. The urinary proteome was significantly different between PD patients and healthy controls, as well as between LRRK2 G2019S carriers and non‐carriers in both cohorts. Interestingly, our data revealed lysosomal dysregulation in individuals with the LRRK2 G2019S mutation. When combined with machine learning, the urinary proteome data alone were sufficient to classify mutation status and disease manifestation in mutation carriers remarkably well, identifying VGF, ENPEP, and other PD‐associated proteins as the most discriminating features. Taken together, our results validate urinary proteomics as a valuable strategy for biomarker discovery and patient stratification in PD.