Quantitative Analysis of the Intra- and Inter-Individual Variability of the Normal Urinary Proteome

Prostate cancer reshapes the secreted and extracellular vesicle urinary proteomes

Urine is a complex biofluid that reflects both overall physiologic state and the state of the genitourinary tissues through which it passes. It contains both secreted proteins and proteins encapsulated in tissue-derived extracellular vesicles (EVs). To understand the population variability and clinical utility of urine, we quantified the secreted and EV proteomes from 190 men, including a subset with prostate cancer. We demonstrate that a simple protocol enriches prostatic proteins in urine. Secreted and EV proteins arise from different subcellular compartments. Urinary EVs are faithful surrogates of tissue proteomes, but secreted proteins in urine or cell line EVs are not. The urinary proteome is longitudinally stable over several years. It can accurately and non-invasively distinguish malignant from benign prostatic lesions and can risk-stratify prostate tumors. This resource quantifies the complexity of the urinary proteome and reveals the synergistic value of secreted and EV proteomes for translational and biomarker studies.

Liquid biomarkers in prostate cancer: recent advancements and future directions

PURPOSE OF REVIEW

Traditional diagnostic approaches of prostate cancer like PSA are limited by high false-positive rates and insufficient capture of tumour heterogeneity, necessitating the development of more precise tools. This review examines the latest advancements in liquid biomarkers for prostate cancer, focusing on their potential to refine diagnostic accuracy and monitor disease progression.

RECENT FINDINGS

Liquid biomarkers have gained prominence because of their minimally invasive nature and ability to reflect the molecular characteristics of prostate cancer. Circulating tumour cells provide insight into tumour cell dissemination and are indicative of aggressive disease phenotypes, with single-cell analyses revealing genomic instability and treatment resistance. Circulating tumour DNA offers real-time tumour genomic information, aiding in treatment decision-making in advanced prostate cancer, where it has been associated with clinical progression. MicroRNAs act as oncogenes or tumour suppressors and exhibit diagnostic and prognostic potential; however, their clinical utility is constrained by the lack of consistent validation. Extracellular vesicles contain tumour-derived biomolecules, with specific proteins demonstrating prognostic relevance. Applications of these markers to urinary testing have been demonstrated.

SUMMARY

Liquid biomarkers show potential in refining prostate cancer management. Future research should aim to integrate these biomarkers into a cohesive framework in line with precision medicine principles.

Proteomic Profiling of Muscular Adaptations to Short-Term Concentric Versus Eccentric Exercise Training in Humans

The molecular mechanisms underlying muscular adaptations to concentric (CON) and eccentric (ECC) exercise training have been extensively explored. However, most previous studies have focused on specifically selected proteins, thus, unable to provide a comprehensive protein profile and potentially missing the crucial mechanisms underlying muscular adaptation to exercise training. We herein aimed to investigate proteomic profiles of human skeletal muscle in response to short-term resistance training. Twenty young males were randomly and evenly assigned to two groups to complete a 4-week either ECC or CON training program. Measurements of body composition and physiological function of the quadriceps femoris were conducted both before and after the training. Muscle biopsies from the vastus lateralis of randomly selected participants (five in ECC and four in CON) of both before and after the training were analyzed using the liquid-chromatography tandem mass spectrometry in combination with bioinformatics analysis. Neither group presented a significant difference in body composition or leg muscle mass; however, muscle peak torque, total work, and maximal voluntary contraction were significantly increased after the training in both groups. Proteomics analysis revealed 122 differentially abundant proteins (DAPs; p value < 0.05 & fold change >1.5 or <0.67) in ECC, of which the increased DAPs were mainly related to skeletal muscle contraction and cytoskeleton and enriched specifically in the pentose phosphate pathway, extracellular matrix-receptor interaction, and PI3K-Akt signaling pathway, whereas the decreased DAPs were associated with the mitochondrial respiratory chain. One hundred one DAPs were identified in CON, of which the increased DAPs were primarily involved in translation/protein synthesis and the mitochondria respiratory, whereas the decreased DAPs were related to metabolic processes, cytoskeleton, and de-ubiquitination. In conclusion, the 4-week CON and ECC training resulted in distinctly different proteomic profiles, especially in proteins related to muscular structure and metabolism.

Prostate cancer research: tools, cell types, and molecular targets

Multiple cancer cell types are found in prostate tumors. They are either luminal-like adenocarcinoma or less luminal-like and more stem-like non-adenocarcinoma and small cell carcinoma. These types are lineage related through differentiation. Loss of cancer differentiation from luminal-like to stem-like is mediated by the activation of stem cell transcription factors (scTF) such as LIN28A, NANOG, POU5F1 and SOX2. scTF expression leads to down-regulation of β2-microglobulin (B2M). Thus, cancer cells can change from the scT F ˜ B 2 M hi phenotype of differentiated to that of scT F ˙ B 2 M lo of dedifferentiated in the disease course. In development, epithelial cell differentiation is induced by stromal signaling and cell contact. One of the stromal factors specific to prostate encodes proenkephalin (PENK). PENK can down-regulate scTF and up-regulate B2M in stem-like small cell carcinoma LuCaP 145.1 cells indicative of exit from the stem state and differentiation. In fact, prostate cancer cells can be made to undergo dedifferentiation or reprogramming by scTF transfection and then to differentiate by PENK transfection. Therapies need to be designed for treating the different cancer cell types. Extracellular anterior gradient 2 (eAGR2) is an adenocarcinoma antigen associated with cancer differentiation that can be targeted by antibodies to lyse tumor cells with immune system components. eAGR2 is specific to cancer as normal cells express only the intracellular form (iAGR2). For AGR2-negative stem-like cancer cells, factors like PENK that can target scTF could be effective in differentiation therapy.

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.

Urinary proteomics reveals biological processes related to acute kidney injury in Bothrops atrox envenomings

Acute kidney injury (AKI) is a critical systemic complication caused by Bothrops envenoming, a neglected health problem in the Brazilian Amazon. Understanding the underlying mechanisms leading to AKI is crucial for effectively mitigating the burden of this complication. This study aimed to characterize the urinary protein profile of Bothrops atrox snakebite victims who developed AKI. We analyzed three groups of samples collected on admission: healthy subjects (controls, n = 10), snakebite victims who developed AKI (AKI, n = 10), and those who did not evolve to AKI (No-AKI, n = 10). Using liquid-chromatography tandem mass spectrometry, we identified and quantified (label-free) 1190 proteins. A panel of 65 proteins was identified exclusively in the urine of snakebite victims, with 32 exclusives to the AKI condition. Proteins more abundant or exclusive in AKI's urine were associated with acute phase response, endopeptidase inhibition, complement cascade, and inflammation. Notable proteins include serotransferrin, SERPINA-1, alpha-1B-glycoprotein, and NHL repeat-containing protein 3. Furthermore, evaluating previously reported biomarkers candidates for AKI and renal injury, we found retinol-binding protein, beta-2-microglobulin, cystatin-C, and hepcidin to be significant in cases of AKI induced by Bothrops envenoming. This work sheds light on physiological disturbances caused by Bothrops envenoming, highlighting potential biological processes contributing to AKI. Such insights may aid in better understanding and managing this life-threatening complication.

Recent progress in mass spectrometry-based urinary proteomics

Serum or plasma is frequently utilized in biomedical research; however, its application is impeded by the requirement for invasive sample collection. The non-invasive nature of urine collection makes it an attractive alternative for disease characterization and biomarker discovery. Mass spectrometry-based protein profiling of urine has led to the discovery of several disease-associated biomarkers. Proteomic analysis of urine has not only been applied to disorders of the kidney and urinary bladder but also to conditions affecting distant organs because proteins excreted in the urine originate from multiple organs. This review provides a progress update on urinary proteomics carried out over the past decade. Studies summarized in this review have expanded the catalog of proteins detected in the urine in a variety of clinical conditions. The wide range of applications of urine analysis-from characterizing diseases to discovering predictive, diagnostic and prognostic markers-continues to drive investigations of the urinary proteome.

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.

Lithographically defined encoded magnetic heterostructures for the targeted screening of kidney cancer

Renal cell carcinoma (RCC) is the 7th commonest cancer in the UK and the most lethal urological malignancy; 50% of all RCC patients will die from the condition. However, if identified early enough, small RCCs are usually cured by surgery or percutaneous procedures, with 95% 10 year survival. This study describes a newly developed non-invasive urine-based assay for the early detection of RCC. Our approach uses encoded magnetically controllable heterostructures as a substrate for immunoassays. These heterostructures have molecular recognition abilities and embedded patterned codes for a rapid identification of RCC biomarkers. The magnetic heterostructures developed for this study have a magnetic configuration designed for a remote multi axial control of their orientation by external magnetic fields, this control facilitates the code readout when the heterostructures are in liquid. Furthermore, the optical encoding of each set of heterostructures provides a multiplexed analyte capture platform, as different sets of heterostructures, specific to different biomarkers can be mixed together in a patient sample. Our results show a precise magnetic control of the heterostructures with an efficient code readout during liquid immunoassays. The use of functionalised magnetic heterostructures as a substrate for immunoassay is validated for urine specimen spiked with recombinant RCC biomarkers. Initial results of the newly proposed screening method on urine samples from RCC patients, and controls with no renal disorders are presented in this study. Comprehensive optimisation cycles are in progress to validate the robustness of this technology as a novel, non-invasive screening method for RCC.

Urinary biomarkers for amyotrophic lateral sclerosis: candidates, opportunities and considerations

Amyotrophic lateral sclerosis is a relentless neurodegenerative disease that is mostly fatal within 3-5 years and is diagnosed on evidence of progressive upper and lower motor neuron degeneration. Around 15% of those with amyotrophic lateral sclerosis also have frontotemporal degeneration, and gene mutations account for ∼10%. Amyotrophic lateral sclerosis is a variable heterogeneous disease, and it is becoming increasingly clear that numerous different disease processes culminate in the final degeneration of motor neurons. There is a profound need to clearly articulate and measure pathological process that occurs. Such information is needed to tailor treatments to individuals with amyotrophic lateral sclerosis according to an individual's pathological fingerprint. For new candidate therapies, there is also a need for methods to select patients according to expected treatment outcomes and measure the success, or not, of treatments. Biomarkers are essential tools to fulfil these needs, and urine is a rich source for candidate biofluid biomarkers. This review will describe promising candidate urinary biomarkers of amyotrophic lateral sclerosis and other possible urinary candidates in future areas of investigation as well as the limitations of urinary biomarkers.

Multiomic Approaches for Cancer Biomarker Discovery in Liquid Biopsies: Advances and Challenges

Cancer is a complex and heterogeneous disease that poses a significant threat to global health. Early diagnosis and treatment are critical for improving patient outcomes, and the use of liquid biopsies has emerged as a promising approach for cancer detection and monitoring. Traditionally, cancer diagnosis has relied on invasive tissue biopsies, the collection of which can prove challenging for patients and the results of which may not always provide accurate results due to tumor heterogeneity. Liquid biopsies have gained increasing attention as they provide a non-invasive and accessible source of cancer biomarkers, which can be used to diagnose cancer, monitor treatment response, and detect relapse. The integration of -omics technologies, such as proteomics, genomics, and metabolomics, has further enhanced the capabilities of liquid biopsies by introducing precision oncology and enabling the tailoring of treatment for individual patients based on their unique tumor biology. In this review, we will discuss the challenges and advances in the field of cancer liquid biopsies and the integration of -omics technologies for different types of liquid biopsies, including blood, tear, urine, sweat, saliva, and cerebrospinal fluid.

The amniotic fluid proteome changes across gestation in humans and rhesus macaques

Amniotic fluid is a complex biological medium that offers protection to the fetus and plays a key role in normal fetal nutrition, organogenesis, and potentially fetal programming. Amniotic fluid is also critically involved in longitudinally shaping the in utero milieu during pregnancy. Yet, the molecular mechanism(s) of action by which amniotic fluid regulates fetal development is ill-defined partly due to an incomplete understanding of the evolving composition of the amniotic fluid proteome. Prior research consisting of cross-sectional studies suggests that the amniotic fluid proteome changes as pregnancy advances, yet longitudinal alterations have not been confirmed because repeated sampling is prohibitive in humans. We therefore performed serial amniocenteses at early, mid, and late gestational time-points within the same pregnancies in a rhesus macaque model. Longitudinally-collected rhesus amniotic fluid samples were paired with gestational-age matched cross-sectional human samples. Utilizing LC-MS/MS isobaric labeling quantitative proteomics, we demonstrate considerable cross-species similarity between the amniotic fluid proteomes and large scale gestational-age associated changes in protein content throughout pregnancy. This is the first study to compare human and rhesus amniotic fluid proteomic profiles across gestation and establishes a reference amniotic fluid proteome. The non-human primate model holds promise as a translational platform for amniotic fluid studies.

Targeted Workflow Investigating Variations in the Tear Proteome by Liquid Chromatography Tandem Mass Spectrometry

Proteins in tears have an important role in eye health and have been shown as a promising source of disease biomarkers. The goal of this study was to develop a robust, sensitive, and targeted method for profiling tear proteins to examine the variability within a group of healthy volunteers over three days. Inter-individual and inter-day variabilities were examined to contribute to understanding the normal variations in the tear proteome, as well as to establish which proteins may be better candidates as eventual biomarkers of specific diseases. Tear samples collected on Schirmer strips were subjected to bottom-up proteomics, and resulting peptides were analyzed using an optimized targeted method measuring 226 proteins by liquid chromatography-scheduled multiple reaction monitoring. This method was developed using an in-house database of identified proteins from tears compiled from high-resolution data-dependent liquid chromatography tandem mass spectrometry data. The measurement of unique peptide signals can help better understand the dynamics of each of these proteins in tears. Some interesting trends were seen in specific pathways or protein classes, including higher variabilities for those involved in glycolysis, glutathione metabolism, and cytoskeleton proteins and lower variation for those involving the degradation of the extracellular matrix. The overall aim of this study was to contribute to the field of tear proteomics with the development of a novel and targeted method that is highly amenable to the clinical laboratory using high flow LC and commonly used triple quadrupole mass spectrometry while ensuring that protein quantitation was reported based on unique peptides for each protein and robust peak areas with data normalization. These results report on variabilities on over 200 proteins that are robustly detected in tear samples from healthy volunteers with a simple sample preparation procedure.

Prostate Cancer Reshapes the Secreted and Extracellular Vesicle Urinary Proteomes

Urine is a complex biofluid that reflects both overall physiologic state and the state of the genitourinary tissues through which it passes. It contains both secreted proteins and proteins encapsulated in tissue-derived extracellular vesicles (EVs). To understand the population variability and clinical utility of urine, we quantified the secreted and EV proteomes from 190 men, including a subset with prostate cancer. We demonstrate that a simple protocol enriches prostatic proteins in urine. Secreted and EV proteins arise from different subcellular compartments. Urinary EVs are faithful surrogates of tissue proteomes, but secreted proteins in urine or cell line EVs are not. The urinary proteome is longitudinally stable over several years. It can accurately and non-invasively distinguish malignant from benign prostatic lesions, and can risk-stratify prostate tumors. This resource quantifies the complexity of the urinary proteome, and reveals the synergistic value of secreted and EV proteomes for translational and biomarker studies.

Targeted MRM Quantification of Urinary Proteins in Chronic Kidney Disease Caused by Glomerulopathies

Glomerulopathies with nephrotic syndrome that are resistant to therapy often progress to end-stage chronic kidney disease (CKD) and require timely and accurate diagnosis. Targeted quantitative urine proteome analysis by mass spectrometry (MS) with multiple-reaction monitoring (MRM) is a promising tool for early CKD diagnostics that could replace the invasive biopsy procedure. However, there are few studies regarding the development of highly multiplexed MRM assays for urine proteome analysis, and the two MRM assays for urine proteomics described so far demonstrate very low consistency. Thus, the further development of targeted urine proteome assays for CKD is actual task. Herein, a BAK270 MRM assay previously validated for blood plasma protein analysis was adapted for urine-targeted proteomics. Because proteinuria associated with renal impairment is usually associated with an increased diversity of plasma proteins being present in urine, the use of this panel was appropriate. Another advantage of the BAK270 MRM assay is that it includes 35 potential CKD markers described previously. Targeted LC-MRM MS analysis was performed for 69 urine samples from 46 CKD patients and 23 healthy controls, revealing 138 proteins that were found in ≥2/3 of the samples from at least one of the groups. The results obtained confirm 31 previously proposed CKD markers. Combination of MRM analysis with machine learning for data processing was performed. As a result, a highly accurate classifier was developed (AUC = 0.99) that enables distinguishing between mild and severe glomerulopathies based on the assessment of only three urine proteins (GPX3, PLMN, and A1AT or SHBG).

Urinary proteome profiles associated with cognitive decline in community elderly residents—A pilot study

Non-invasive and simple methods enabling easy identification of individuals at high risk of cognitive decline are needed as preventive measures against dementia. This pilot study aimed to explore protein biomarkers that can predict cognitive decline using urine, which can be collected non-invasively. Study subjects were selected from participants in a cohort study of middle-aged and older community-dwelling adults who underwent cognitive testing using the Mini-Mental State Examination and provided spot urine samples at two time points with an interval of approximately 5 years. Seven participants whose cognitive function declined 4 or more points from baseline (Group D) and 7 sex- and age-matched participants whose cognitive function remained within the normal range during the same period (Group M) were selected. Urinary proteomics using mass spectrometry was performed and discriminant models were created using orthogonal partial least squares-discriminant analysis (OPLS-DA). OPLS-DA yielded two models that significantly discriminated between the two groups at baseline and follow-up. Both models had ORM1, ORM2, and SERPINA3 in common. A further OPLS-DA model using baseline ORM1, ORM2, and SERPINA3 data showed similar predictive performance for data at follow-up as it did for baseline data (sensitivity: 0.85, specificity: 0.85), with the receiver operating characteristic curve analysis yielding an area under the curve of 0.878. This prospective study demonstrated the potential for using urine to identify biomarkers of cognitive decline.

A Practical and Analytical Comparative Study of Gel-Based Top-Down and Gel-Free Bottom-Up Proteomics Including Unbiased Proteoform Detection

Proteomics is an indispensable analytical technique to study the dynamic functioning of biological systems via different proteins and their proteoforms. In recent years, bottom-up shotgun has become more popular than gel-based top-down proteomics. The current study examined the qualitative and quantitative performance of these two fundamentally different methodologies by the parallel measurement of six technical and three biological replicates of the human prostate carcinoma cell line DU145 using its two most common standard techniques, label-free shotgun and two-dimensional differential gel electrophoresis (2D-DIGE). The analytical strengths and limitations were explored, finally focusing on the unbiased detection of proteoforms, exemplified by discovering a prostate cancer-related cleavage product of pyruvate kinase M2. Label-free shotgun proteomics quickly yields an annotated proteome but with reduced robustness, as determined by three times higher technical variation compared to 2D-DIGE. At a glance, only 2D-DIGE top-down analysis provided valuable, direct stoichiometric qualitative and quantitative information from proteins to their proteoforms, even with unexpected post-translational modifications, such as proteolytic cleavage and phosphorylation. However, the 2D-DIGE technology required almost 20 times as much time per protein/proteoform characterization with more manual work. Ultimately, this work should expose both techniques' orthogonality with their different contents of data output to elucidate biological questions.

Urinary protein biomarkers based on LC-MS/MS analysis to discriminate vascular dementia from Alzheimer's disease in Han Chinese population

Objective

This study aimed to identify the potential urine biomarkers of vascular dementia (VD) and unravel the disease-associated mechanisms by applying Liquid chromatography tandem-mass spectrometry (LC-MS/MS).

Methods

LC-MS/MS proteomic analysis was applied to urine samples from 3 groups, including 14 patients with VD, 9 patients with AD, and 21 normal controls (NC). By searching the MS data by Proteome Discoverer software, analyzing the protein abundances qualitatively and quantitatively, comparing between groups, combining bioinformatics analysis using Gene Ontology (GO) and pathway crosstalk analysis using Kyoto Encyclopedia of Genes and Genomes (KEGG), and literature searching, the differentially expressed proteins (DEPs) of VD can be comprehensively determined at last and were further quantified by receiver operating characteristic (ROC) curve methods.

Results

The proteomic findings showed quantitative changes in patients with VD compared to patients with NC and AD groups; among 4,699 identified urine proteins, 939 and 1,147 proteins displayed quantitative changes unique to VD vs. NC and AD, respectively, including 484 overlapped common DEPs. Then, 10 unique proteins named in KEGG database (including PLOD3, SDCBP, SRC, GPRC5B, TSG101/STP22/VPS23, THY1/CD90, PLCD, CDH16, NARS/asnS, AGRN) were confirmed by a ROC curve method.

Conclusion

Our results suggested that urine proteins enable detection of VD from AD and VC, which may provide an opportunity for intervention.

Comparison of urine proteomes from tumor-bearing mice with those from tumor-resected mice

Objective

This study aimed to address on the most important concern of surgeons-whether to completely resect tumor. Urine can indicate early changes associated with physiological or pathophysiological processes. Based on these ideas, we conducted experiments to explore changes in the urine proteome between tumor-bearing mice and tumor-resected mice.

Method

The tumor-bearing mouse model was established with MC38 mouse colon cancer cells, and the mice were divided into the control group, tumor-resected group, and tumor-bearing group. Urine was collected 7 and 30 days after tumor resection. Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) was used to identify the urine proteome, which was analyzed for differentially expressed proteins and functional annotation.

Results

(1) Seven days after tumor resection, 20 differentially expressed proteins distinguished the tumor-resected group and the tumor-bearing group. The identified biological processes included circadian rhythm, Notch signaling pathway, leukocyte cell-cell adhesion, and heterophilic cell-cell adhesion via plasma membrane cell adhesion molecules. (2) Thirty days after tumor resection, 33 differentially expressed proteins distinguished the tumor-resected group and the tumor-bearing group. The identified biological processes included cell adhesion; complement activation, the alternative pathway; the immune system process; and angiogenesis. (3) The difference in the urine proteome between the tumor-resected group and the healthy control group was smaller 30 days after tumor resection.

Conclusion

Changes in the urinary proteome can reflect the complete resection of MC38 tumors.

Early Prediction of COVID-19 Patient Survival by Targeted Plasma Multi-Omics and Machine Learning

The recent surge of coronavirus disease 2019 (COVID-19) hospitalizations severely challenges healthcare systems around the globe and has increased the demand for reliable tests predictive of disease severity and mortality. Using multiplexed targeted mass spectrometry assays on a robust triple quadrupole MS setup which is available in many clinical laboratories, we determined the precise concentrations of hundreds of proteins and metabolites in plasma from hospitalized COVID-19 patients. We observed a clear distinction between COVID-19 patients and controls and, strikingly, a significant difference between survivors and nonsurvivors. With increasing length of hospitalization, the survivors' samples showed a trend toward normal concentrations, indicating a potential sensitive readout of treatment success. Building a machine learning multi-omic model that considers the concentrations of 10 proteins and five metabolites, we could predict patient survival with 92% accuracy (area under the receiver operating characteristic curve: 0.97) on the day of hospitalization. Hence, our standardized assays represent a unique opportunity for the early stratification of hospitalized COVID-19 patients.

Investigation of urine metabolome of BALB/c mouse infected with an avirulent strain of Toxoplasma gondii

Background

The protozoan parasite Toxoplasma gondii is a major concern for human and animal health. Although the metabolic understanding of toxoplasmosis has increased in recent years, the analysis of metabolic alterations through noninvasive methodologies in biofluids remains limited.

Methods

Here, we applied liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based metabolomics and multivariate statistical analysis to analyze BALB/c mouse urine collected from acutely infected, chronically infected and control subjects.

Results

In total, we identified 2065 and 1409 metabolites in the positive electrospray ionization (ESI +) mode and ESI − mode, respectively. Metabolomic patterns generated from principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) score plots clearly separated T. gondii-infected from uninfected urine samples. Metabolites with altered levels in urine from T. gondii-infected mice revealed changes in pathways related to amino acid metabolism, fatty acid metabolism, and nicotinate and nicotinamide metabolism.

Conclusions

This is the first study to our knowledge on urine metabolic profiling of BALB/c mouse with T. gondii infection. The urine metabolome of infected mouse is distinctive and has value in the understanding of Toxoplasmosis pathogenesis and improvement of treatment.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s13071-022-05408-2.

Proteomics for Biomarker Discovery for Diagnosis and Prognosis of Kidney Transplantation Rejection

Renal transplantation is currently the treatment of choice for end-stage kidney disease, enabling a quality of life superior to dialysis. Despite this, all transplanted patients are at risk of allograft rejection processes. The gold-standard diagnosis of graft rejection, based on histological analysis of kidney biopsy, is prone to sampling errors and carries high costs and risks associated with such invasive procedures. Furthermore, the routine clinical monitoring, based on urine volume, proteinuria, and serum creatinine, usually only detects alterations after graft histologic damage and does not differentiate between the diverse etiologies. Therefore, there is an urgent need for new biomarkers enabling to predict, with high sensitivity and specificity, the rejection processes and the underlying mechanisms obtained from minimally invasive procedures to be implemented in routine clinical surveillance. These new biomarkers should also detect the rejection processes as early as possible, ideally before the 78 clinical outputs, while enabling balanced immunotherapy in order to minimize rejections and reducing the high toxicities associated with these drugs. Proteomics of biofluids, collected through non-invasive or minimally invasive analysis, e.g., blood or urine, present inherent characteristics that may provide biomarker candidates. The current manuscript reviews biofluids proteomics toward biomarkers discovery that specifically identify subclinical, acute, and chronic immune rejection processes while allowing for the discrimination between cell-mediated or antibody-mediated processes. In time, these biomarkers will lead to patient risk stratification, monitoring, and personalized and more efficient immunotherapies toward higher graft survival and patient quality of life.

Many kinds of oxidized proteins are present more in the urine of the elderly

Background

Many studies have shown an association between aging and oxidation. To our knowledge, there have been no studies exploring aging-related urine proteome modifications. The purpose of this study was to explore differences in global chemical modifications of urinary protein at different ages.

Methods

Discovery (n=38) cohort MS data including children, young and old groups were downloaded from three published studies, and this data was analyzed using open-pFind for identifying modifications. Verification cohort human samples (n=28) including young, middle-aged, and old groups, rat samples (n=7) at three-time points after birth, adulthood, and old age were collected and processed in the laboratory simultaneously based on label-free quantification combined with pFind.

Results

Discovery cohort: there were 28 kinds of differential oxidations in the old group that were higher than those in the young or children group in. Verification cohort: there were 17 kinds of differential oxidations of 49 oxidized proteins in the middle and old groups, which were significantly higher than those in the young group. Both oxidations and oxidized proteins distinguished different age groups well. There were also 15 kinds of differential oxidations in old age higher than others in the rat cohort. The results showed that the validation experiment was basically consistent with the results of the discovery experiment, showing that the level of oxidized proteins in urine increased significantly with age.

Conclusions

Our study is the first to show that oxidative proteins occur in urine and that oxidations are higher in older than younger ages. Perhaps improving the degree of excretion of oxidative protein in vivo through the kidney is helpful for maintaining the homeostasis of the body’s internal environment, delaying aging and the occurrence of senile diseases.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12014-022-09360-2.

Mass Spectrometry-Based Analysis of Serum N-Glycosylation Changes in Patients with Parkinson's Disease

It is urgently needed to find reliable biofluid biomarkers for early diagnosis of Parkinson's disease in order to achieve better treatment. Promising biomarkers can be found in Parkinson's disease-related glycoproteins as aberrant protein glycosylation plays an important role in disease progression. However, current information on serum N-glycoproteomic changes in Parkinson's disease is still limited. Here, we used glycoproteomics methods, which combine the solid-phase chemoenzymatic method, lectin affinity chromatography, and hydrophilic interaction chromatography with high-resolution mass spectrometry, to analyze the glycans, glycosites, and intact glycopeptides of serum. Increased abundance of glycans containing core fucose, sialic acid, and bisecting N-acetyl glucosamine was detected at the overall glycan level and also at specific glycosites of glycopeptides. Five Parkinson's disease-associated proteins with this type of N-glycosylation changes were also identified. We propose that the revealed site-specific N-glycosylation changes in serum can be potential biomarkers for Parkinson's disease.

Proteomics of Human Biological Fluids for Biomarker Discoveries: Technical Advances and Recent Applications

INTRODUCTION

Biological fluids are routine samples for diagnostic testing and monitoring. Blood samples are typically measured because of their moderate collection invasiveness and high information content on health and disease. Several body fluids, such as cerebrospinal fluid (CSF), are also studied and suited to specific pathologies. Over the last two decades proteomics has quested to identify protein biomarkers but with limited success. Recent technologies and refined pipelines have accelerated the profiling of human biological fluids.

AREAS COVERED

We review proteomic technologies for the identification of biomarkers. Those are based on antibodies/aptamers arrays or mass spectrometry (MS), but new ones are emerging. Advances in scalability and throughput have allowed to better design studies and cope with the limited sample size that had until now prevailed due to technological constraints. With these enablers, plasma/serum, CSF, saliva, tears, urine, and milk proteomes have been further profiled; we provide a non-exhaustive picture of some recent highlights (mainly covering literature from last five years in the Scopus database) using MS-based proteomics.

EXPERT OPINION

While proteomics has been in the shadow of genomics for years, proteomic tools and methodologies have reached a certain maturity. They are better suited to discover innovative and robust biofluid biomarkers.

96DRA-urine: A high throughput sample preparation method for urinary proteome analysis

Mass spectrometry (MS)-based urinary proteomics is increasingly used for clinical research. A critical step in urinary proteomic analysis comprises the implementation of a reliable sample preparation method with high yields of peptides and proteins. In this study, we developed a urinary sample preparation method, DRA-Urine (Direct reduction/alkylation in urine), which urinary proteins were directly reduced/alkylated in urine, and then precipitated by acetone, washed and digestion on an ultrafilter unit. The qualitative and quantitative comparison of different urinary sample preparation methods (in-solution methods and ultrafilter-assisted methods) showed that DRA-Urine could achieve better results. Adapting DRA-Urine protocol to a 96-well format, namely 96DRA-Urine, shortened the time for buffer change and improved sample preparation throughput. The results showed that 96DRA-Urine displayed similar proteomic performance to DRA-Urine. Finally, the 96DRA-Urine method was used in a label-free, small pilot biomarker discovery analysis for differential urinary proteome analysis of bladder cancer urine. The results showed that urinary proteins could differentiate bladder cancer (BCa) patients from healthy controls and distinguish high-grade BCa from low-grade BCa with area under the curve (AUC) values of 0.972 and 0.847, respectively. Consequently, the 96DRA-Urine method might be a high-throughput method for preparing body fluid samples used in clinical research but needs to be further verified.

Exploring Human Milk Dynamics: Interindividual Variation in Milk Proteome, Peptidome, and Metabolome

Human milk is a dynamic biofluid, and its detailed composition receives increasing attention. While most studies focus on changes over time or differences between maternal characteristics, interindividual variation receives little attention. Nevertheless, a comprehensive insight into this can help interpret human milk studies and help human milk banks provide targeted milk for recipients. This study aimed to map interindividual variation in the human milk proteome, peptidome, and metabolome and to investigate possible explanations for this variation. A set of 286 milk samples was collected from 29 mothers in the third month postpartum. Samples were pooled per mother, and proteins, peptides, and metabolites were analyzed. A substantial coefficient of variation (>100%) was observed for 4.6% and 36.2% of the proteins and peptides, respectively. In addition, using weighted correlation network analysis (WGCNA), 5 protein and 11 peptide clusters were obtained, showing distinct characteristics. With this, several associations were found between the different data sets and with specific sample characteristics. This study provides insight into the dynamics of human milk protein, peptide, and metabolite composition. In addition, it will support future studies that evaluate the effect size of a parameter of interest by enabling a comparison with natural variability.

Extracellular Vesicle Proteome in Prostate Cancer: A Comparative Analysis of Mass Spectrometry Studies

Molecular diagnostics based on discovery research holds the promise of improving screening methods for prostate cancer (PCa). Furthermore, the congregated information prompts the question whether the urinary extracellular vesicles (uEV) proteome has been thoroughly explored, especially at the proteome level. In fact, most extracellular vesicles (EV) based biomarker studies have mainly targeted plasma or serum. Therefore, in this study, we aim to inquire about possible strategies for urinary biomarker discovery particularly focused on the proteome of urine EVs. Proteomics data deposited in the PRIDE archive were reanalyzed to target identifications of potential PCa markers. Network analysis of the markers proposed by different prostate cancer studies revealed moderate overlap. The recent throughput improvements in mass spectrometry together with the network analysis performed in this study, suggest that a larger standardized cohort may provide potential biomarkers that are able to fully characterize the heterogeneity of PCa. According to our analysis PCa studies based on urinary EV proteome presents higher protein coverage compared to plasma, plasma EV, and voided urine proteome. This together with a direct interaction of the prostate gland and urethra makes uEVs an attractive option for protein biomarker studies. In addition, urinary proteome based PCa studies must also evaluate samples from bladder and renal cancers to assess specificity for PCa.

Longitudinal stability of urinary extracellular vesicle protein patterns within and between individuals

The protein content of urinary extracellular vesicles (EVs) is considered to be an attractive non-invasive biomarker source. However, little is known about the consistency and variability of urinary EV proteins within and between individuals over a longer time-period. Here, we evaluated the stability of the urinary EV proteomes of 8 healthy individuals at 9 timepoints over 6 months using data-independent-acquisition mass spectrometry. The 1802 identified proteins had a high correlation amongst all samples, with 40% of the proteome detected in every sample and 90% detected in more than 1 individual at all timepoints. Unsupervised analysis of top 10% most variable proteins yielded person-specific profiles. The core EV-protein-interaction network of 516 proteins detected in all measured samples revealed sub-clusters involved in the biological processes of G-protein signaling, cytoskeletal transport, cellular energy metabolism and immunity. Furthermore, gender-specific expression patterns were detected in the urinary EV proteome. Our findings indicate that the urinary EV proteome is stable in longitudinal samples of healthy subjects over a prolonged time-period, further underscoring its potential for reliable non-invasive diagnostic/prognostic biomarkers.

Personalized Proteome: Comparing Proteogenomics and Open Variant Search Approaches for Single Amino Acid Variant Detection

Discovery of variant peptides such as a single amino acid variant (SAAV) in shotgun proteomics data is essential for personalized proteomics. Both the resolution of shotgun proteomics methods and the search engines have improved dramatically, allowing for confident identification of SAAV peptides. However, it is not yet known if these methods are truly successful in accurately identifying SAAV peptides without prior genomic information in the search database. We studied this in unprecedented detail by exploiting publicly available long-read RNA sequences and shotgun proteomics data from the gold standard reference cell line NA12878. Searching spectra from this cell line with the state-of-the-art open modification search engine ionbot against carefully curated search databases resulted in 96.7% false-positive SAAVs and an 85% lower true positive rate than searching with peptide search databases that incorporate prior genetic information. While adding genetic variants to the search database remains indispensable for correct peptide identification, inclusion of long-read RNA sequences in the search database contributes only 0.3% new peptide identifications. These findings reveal the differences in SAAV detection that result from various approaches, providing guidance to researchers studying SAAV peptides and developers of peptide spectrum identification tools.

Urinary extracellular vesicles: A position paper by the Urine Task Force of the International Society for Extracellular Vesicles

Urine is commonly used for clinical diagnosis and biomedical research. The discovery of extracellular vesicles (EV) in urine opened a new fast-growing scientific field. In the last decade urinary extracellular vesicles (uEVs) were shown to mirror molecular processes as well as physiological and pathological conditions in kidney, urothelial and prostate tissue. Therefore, several methods to isolate and characterize uEVs have been developed. However, methodological aspects of EV separation and analysis, including normalization of results, need further optimization and standardization to foster scientific advances in uEV research and a subsequent successful translation into clinical practice. This position paper is written by the Urine Task Force of the Rigor and Standardization Subcommittee of ISEV consisting of nephrologists, urologists, cardiologists and biologists with active experience in uEV research. Our aim is to present the state of the art and identify challenges and gaps in current uEV-based analyses for clinical applications. Finally, recommendations for improved rigor, reproducibility and interoperability in uEV research are provided in order to facilitate advances in the field.

Proteome Analysis of Urinary Biomarkers in Acute Hypercoagulable State Rat Model

Thrombotic diseases are usually preceded by a hypercoagulable state in the body. This study aimed to screen potential urinary biomarkers for hypercoagulable state based on proteome analysis. Wistar rats were administered with the hemostatic agent etamsylate to establish hypercoagulable state. Urine samples were collected for proteome analysis. We found 20 proteins with levels more than 1.5-fold in difference between control rats and model rats. We searched human homologs of 20 rat proteins and identified 13 human proteins. Of the 13 human homologous proteins, nine were members of human core urinary proteome. Human homologous proteins of differential proteins were highly expressed in 31 human tissues, especially in the kidneys followed by digestive system and reproductive system. Surprisingly, we did not identify known coagulation factors as differential proteins in the urine of model rats. Hypercoagulable state of the body may not involve direct changes in coagulation factors but causes the changes upstream of the coagulation cascade system. Common differential urinary proteins between different hypercoagulable states suggest some common pathways in the formation of hypercoagulable states and may serve as potential biomarkers for the prevention and treatment of thrombotic diseases.

A Comprehensive Urine Proteome Database Generated From Patients With Various Renal Conditions and Prostate Cancer

Urine proteins can serve as viable biomarkers for diagnosing and monitoring various diseases. A comprehensive urine proteome database, generated from a variety of urine samples with different disease conditions, can serve as a reference resource for facilitating discovery of potential urine protein biomarkers. Herein, we present a urine proteome database generated from multiple datasets using 2D LC-MS/MS proteome profiling of urine samples from healthy individuals (HI), renal transplant patients with acute rejection (AR) and stable graft (STA), patients with non-specific proteinuria (NS), and patients with prostate cancer (PC). A total of ~28,000 unique peptides spanning ~2,200 unique proteins were identified with a false discovery rate of <0.5% at the protein level. Over one third of the annotated proteins were plasma membrane proteins and another one third were extracellular proteins according to gene ontology analysis. Ingenuity Pathway Analysis of these proteins revealed 349 potential biomarkers in the literature-curated database. Forty-three percentage of all known cluster of differentiation (CD) proteins were identified in the various human urine samples. Interestingly, following comparisons with five recently published urine proteome profiling studies, which applied similar approaches, there are still ~400 proteins which are unique to this current study. These may represent potential disease-associated proteins. Among them, several proteins such as serpin B3, renin receptor, and periostin have been reported as pathological markers for renal failure and prostate cancer, respectively. Taken together, our data should provide valuable information for future discovery and validation studies of urine protein biomarkers for various diseases.

Protein signatures from blood plasma and urine suggest changes in vascular function and IL-12 signaling in elderly with a history of chronic diseases compared with an age-matched healthy cohort

Key processes characterizing human aging are immunosenescence and inflammaging. The capacity of the immune system to adequately respond to external perturbations (e.g., pathogens, injuries, and biochemical irritants) and to repair somatic mutations that may cause cancers or cellular senescence declines. An important goal remains to identify genetic or biochemical, predictive biomarkers for healthy aging. We recruited two cohorts in the age range 70 to 82, one afflicted by chronic illnesses (non-healthy aging, NHA) and the other in good health (healthy aging, HA). NHA criteria included major cardiovascular, neurodegenerative, and chronic pulmonary diseases, diabetes, and cancers. Quantitative analysis of forty proinflammatory cytokines in blood plasma and more than 500 proteins in urine was performed to identify candidate biomarkers for and biological pathway implications of healthy aging. Nine cytokines revealed lower quantities in blood plasma for the NHA compared with the HA groups (fold change > 1.5; p value < 0.025) including IL-12p40 and IL-12p70. We note that, sampling at two timepoints, intra-individual cytokine abundance patterns clustered in 86% of all 60 cases, indicative of person-specific, highly controlled multi-cytokine signatures in blood plasma. Twenty-three urinary proteins were differentially abundant (HA versus NHA; fold change > 1.5; p value < 0.01). Among the proteins increased in abundance in the HA cohort were glycoprotein MUC18, ephrin type-B receptor 4, matrix remodeling-associated protein 8, angiopoietin-related protein 2, K-cadherin, and plasma protease C1 inhibitor. These proteins have been linked to the extracellular matrix, cell adhesion, and vascular remodeling and repair processes. In silico network analysis identified the regulation of coagulation, antimicrobial humoral immune responses, and the IL-12 signaling pathway as enriched GO terms. To validate links of these preliminary biomarkers and IL-12 signaling with healthy aging, clinical studies using larger cohorts and functional characterization of the genes/proteins in cellular models of aging need to be conducted.

Comprehensive Proteomics Analysis of In Vitro Canine Oviductal Cell-Derived Extracellular Vesicles

Simple Summary

As the dog shows unique and peculiar reproductive characteristics, assisted reproductive techniques such as in vitro maturation and in vitro fertilization have not been well-established compared with those of other mammals. Our recent work demonstrated the interplay between in vitro oviductal cell-derived extracellular vesicles (OC-EVs) and cumulus-oocyte complexes in dogs. Here, we provided for the first time a comprehensive proteomic analysis of OC-EVs. A total of 398 proteins were identified in all OC-EVs samples. A functional enrichment analysis indicated that these core proteins were involved in the key cellular metabolic process related to oocyte maturation and embryonic development. The current comprehensive description of the canine OC-EVs proteome would provide a fundamental resource for further understanding canine reproductive physiology, the interaction of sperms with female counterparts during fertilization, early pregnancy, and establishing an efficient system of in vitro embryo production.

Abstract

Dogs (Canis lupus familiaris) have unique and peculiar reproductive characteristics. While the interplay between in vitro oviductal cell-derived extracellular vesicles (OC-EVs) and cumulus-oocyte complexes in dogs has begun to be elucidated, no study has yet provided extensive information on the biological content and physiological function of OC-EVs and their role in canine oocyte development. Here, we aimed to provide the first comprehensive proteomic analysis of OC-EVs. We identified 398 proteins as present in all OC-EVs samples. The functional enrichment analysis using Gene Ontology terms and an Ingenuity Pathway Analysis revealed that the identified proteins were involved in several cellular metabolic processes, including translation, synthesis, expression, and protein metabolism. Notably, the proteins were also involved in critical canonical pathways with essential functions in oocyte and embryo development, such as ERK/MAPK, EIF2, PI3K/AKT, and mTOR signaling. These data would be an important resource for studying canine reproductive physiology and establishing a successful in vitro embryo production system in dogs.

Label-Free Liquid Chromatography-Mass Spectrometry Proteomic Analysis of Urinary Identification in Diabetic Vascular Dementia in a Han Chinese Population

Objective: This study aimed to identify potential diagnostic biomarkers of diabetic vascular dementia (DVD) and unravel the underlying mechanisms using mass spectrometry (MS).

Methods: Label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS) proteomic analysis was applied to urine samples from four groups, including 14 patients with vascular dementia (VD), 22 patients with type 2 diabetes mellitus (T2DM), 12 patients with DVD, and 21 normal controls (NCs). Searching the MS data by Proteome Discoverer software (ThermoFisher Scientific; Waltham, MA, USA), protein abundances were analyzed qualitatively and quantitatively and compared between these groups. Combining bioinformatics analysis using Gene Ontology (GO), pathway crosstalk analysis using Kyoto Encyclopedia of Genes and Genomes (KEGG), protein–protein interaction (PPI) network analysis using STRING, and literature searching, the differentially expressed proteins (DEPs) of DVD can be comprehensively judged and were further quantified by receiver operating characteristic (ROC) curve methods.

Results: The proteomic findings showed quantitative changes in patients with DVD compared to patients with NC, T2DM, and VD groups; among 4,744 identified urine proteins, 1,222, 1,152, and 1,180 proteins displayed quantitative changes unique to DVD vs. NC, T2DM, and VD, respectively, including 481 overlapped common DEPs. Then, nine unique proteins [including HP, SERPIND, ATP5PB, VNN2, ALDH3A1, U2AF2, C6, A0A5C2GRG5 (no name), and A0A5C2FZ29 (no name)] and two composite markers (CM) (A0A5C2GRG5+U2AF2 and U2AF2+C6) were confirmed by a ROC curve method.

Conclusion: This study provided an insight into the potential pathogenesis of DVD and elucidated a method for early detection.

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.

SWATH-MS Protocols in Human Diseases

Identification of molecular biomarkers for human diseases is one of the most important disciplines in translational science as it helps to elucidate their origin and early progression. Thus, it is a key factor in better diagnosis, prognosis, and treatment. Proteomics can help to solve the problem of sample complexity when the most common primary sample specimens were analyzed: organic fluids of easy access. The latest developments in high-throughput and label-free quantitative proteomics (SWATH-MS), together with more advanced liquid chromatography, have enabled the analysis of large sample sets with the sensitivity and depth needed to succeed in this task. In this chapter, we show different sample processing methods (major protein depletion, digestion, etc.) and a micro LC-SWATH-MS protocol to identify/quantify several proteins in different types of samples (serum/plasma, saliva, urine, tears).

The tissue proteome in the multi-omic landscape of kidney disease

Kidney research is entering an era of 'big data' and molecular omics data can provide comprehensive insights into the molecular footprints of cells. In contrast to transcriptomics, proteomics and metabolomics generate data that relate more directly to the pathological symptoms and clinical parameters observed in patients. Owing to its complexity, the proteome still holds many secrets, but has great potential for the identification of drug targets. Proteomics can provide information about protein synthesis, modification and degradation, as well as insight into the physical interactions between proteins, and between proteins and other biomolecules. Thus far, proteomics in nephrology has largely focused on the discovery and validation of biomarkers, but the systematic analysis of the nephroproteome can offer substantial additional insights, including the discovery of mechanisms that trigger and propagate kidney disease. Moreover, proteome acquisition might provide a diagnostic tool that complements the assessment of a kidney biopsy sample by a pathologist. Such applications are becoming increasingly feasible with the development of high-throughput and high-coverage technologies, such as versatile mass spectrometry-based techniques and protein arrays, and encourage further proteomics research in nephrology.

The proteomic landscape of small urinary extracellular vesicles during kidney transplantation

Kidney transplantation is the preferred renal replacement therapy available. Yet, long-term transplant survival is unsatisfactory, partially due to insufficient possibilities of longitudinal monitoring and understanding of the biological processes after transplantation. Small urinary extracellular vesicles (suEVs) - as a non-invasive source of information - were collected from 22 living donors and recipients. Unbiased proteomic analysis revealed temporal patterns of suEV protein signature and cellular processes involved in both early response and longer-term graft adaptation. Complement activation was among the most dynamically regulated components. This unique atlas of the suEV proteome is provided through an online repository allowing dynamic interrogation by the user. Additionally, a correlative analysis identified putative prognostic markers of future allograft function. One of these markers - phosphoenol pyruvate carboxykinase (PCK2) - could be confirmed using targeted MS in an independent validation cohort of 22 additional patients. This study sheds light on the impact of kidney transplantation on urinary extracellular vesicle content and allows the first deduction of early molecular processes in transplant biology. Beyond that our data highlight the potential of suEVs as a source of biomarkers in this setting.

Assessing Single-Source Reproducibility of Human Head Hair Peptide Profiling from Different Regions of the Scalp

Neither microscopical hair comparisons nor mitochondrial DNA sequencing alone, or together, constitutes a basis for personal identification. Due to these limitations, a complementary technique to compare questioned and known hair shafts was investigated. Recently, scientists from Lawrence Livermore National Laboratory's Forensic Science Center and other collaborators developed a peptide profiling technique, which can infer non-synonymous single nucleotide polymorphisms (SNPs) preserved in hair shaft proteins as single amino acid polymorphisms (SAPs). In this study, peptide profiling was evaluated to determine if it can meet forensic expectations when samples are in limited quantities with the possibility that hair samples collected from different areas of a single donor's scalp (i.e., single source) might not exhibit the same SAP profile. The average dissimilarity, percent differences in SAP profiles within each source, ranged from 0% difference to 29%. This pilot study suggests that more work is needed before peptide profiling of hair can be considered for forensic comparisons.

Protein signatures from blood plasma and urine suggest changes in vascular function and IL-12 signaling in elderly with a history of chronic diseases compared with an age-matched healthy cohort

Key processes characterizing human aging are immunosenescence and inflammaging. The capacity of the immune system to adequately respond to external perturbations (e.g., pathogens, injuries, and biochemical irritants) and to repair somatic mutations that may cause cancers or cellular senescence declines. An important goal remains to identify genetic or biochemical, predictive biomarkers for healthy aging. We recruited two cohorts in the age range 70 to 82, one afflicted by chronic illnesses (non-healthy aging, NHA) and the other in good health (healthy aging, HA). NHA criteria included major cardiovascular, neurodegenerative, and chronic pulmonary diseases, diabetes, and cancers. Quantitative analysis of forty proinflammatory cytokines in blood plasma and more than 500 proteins in urine was performed to identify candidate biomarkers for and biological pathway implications of healthy aging. Nine cytokines revealed lower quantities in blood plasma for the NHA compared with the HA groups (fold change > 1.5; p value < 0.025) including IL-12p40 and IL-12p70. We note that, sampling at two timepoints, intra-individual cytokine abundance patterns clustered in 86% of all 60 cases, indicative of person-specific, highly controlled multi-cytokine signatures in blood plasma. Twenty-three urinary proteins were differentially abundant (HA versus NHA; fold change > 1.5; p value < 0.01). Among the proteins increased in abundance in the HA cohort were glycoprotein MUC18, ephrin type-B receptor 4, matrix remodeling-associated protein 8, angiopoietin-related protein 2, K-cadherin, and plasma protease C1 inhibitor. These proteins have been linked to the extracellular matrix, cell adhesion, and vascular remodeling and repair processes. In silico network analysis identified the regulation of coagulation, antimicrobial humoral immune responses, and the IL-12 signaling pathway as enriched GO terms. To validate links of these preliminary biomarkers and IL-12 signaling with healthy aging, clinical studies using larger cohorts and functional characterization of the genes/proteins in cellular models of aging need to be conducted.

Urinary Apolipoprotein C3 Is a Potential Biomarker for Alzheimer's Disease

INTRODUCTION

Biomarkers of Alzheimer's disease (AD) that can easily be measured in routine health checkups are desirable. Urine is a source of biomarkers that can be collected easily and noninvasively. We previously reported on the comprehensive profile of the urinary proteome of AD patients and identified proteins estimated to be significantly increased or decreased in AD patients by a label-free quantification method. The present study aimed to validate urinary levels of proteins that significantly differed between AD and control samples from our proteomics study (i.e., apolipoprotein C3 [ApoC3], insulin-like growth factor-binding protein 3 [Igfbp3], and apolipoprotein D [ApoD]).

METHODS

Enzyme-linked immunosorbent assays (ELISAs) were performed using urine samples from the same patient and control groups analyzed in the previous proteomics study (18 AD and 18 controls, set 1) and urine samples from an independent group of AD patients and controls (13 AD, 5 mild cognitive impairment [MCI], and 32 controls) from the National Center for Geriatrics and Gerontology Biobank (set 2).

RESULTS

In set 1, the crude urinary levels of ApoD, Igfbp3, and creatinine-adjusted ApoD were significantly higher in the AD group relative to the control group (p = 0.003, p = 0.002, and p = 0.019, respectively), consistent with our previous proteomics results. In set 2, however, the crude urinary levels of Igfbp3 were significantly lower in the AD+MCI group than in the control group (p = 0.028), and the levels of ApoD and ApoC3 did not differ significantly compared to the control group. Combined analysis of all samples revealed creatinine-adjusted ApoC3 levels to be significantly higher in the AD+MCI group (p = 0.015) and the AD-only group (p = 0.011) relative to the control group.

CONCLUSION

ApoC3 may be a potential biomarker for AD, as validated by ELISA. Further analysis of ApoC3 as a urinary biomarker for AD is warranted.

Identification of marker proteins of muscular dystrophy in the urine proteome from the mdx-4cv model of dystrophinopathy

Since the protein constituents of urine present a dynamic proteome that can reflect a variety of disease-related alterations in the body, the mass spectrometric survey of proteome-wide changes in urine promises new insights into pathogenic mechanisms. Urine can be investigated in a completely non-invasive way and provides valuable biomedical information on body-wide changes. In this report, we have focused on the urine proteome in X-linked muscular dystrophy using the established mdx-4cv mouse model of dystrophinopathy. In order to avoid potential artefacts due to the manipulation of the biofluid proteome prior to mass spectrometry, crude urine specimens were analyzed without the prior usage of centrifugation steps or concentration procedures. Comparative proteomics revealed 21 increased and 8 decreased proteins out of 870 identified urinary proteoforms using 50 μl of biofluid per investigated sample, i.e. 14 wild type versus 14 mdx-4cv specimens. Promising marker proteins that were almost exclusively found in mdx-4cv urine included nidogen, parvalbumin and titin. Interestingly, the mass spectrometric identification of urine-associated titin revealed a wide spread of peptides over the sequence of this giant muscle protein. The newly established urinomic signature of dystrophinopathy might be helpful for the design of non-invasive assays to improve diagnosis, prognosis, therapy-monitoring and evaluation of potential harmful side effects of novel treatments in the field of muscular dystrophy research.

Variability in protein cargo detection in technical and biological replicates of exosome-enriched extracellular vesicles

Exosomes are extracellular vesicles (EVs) of ~20-200 nm diameter that shuttle DNAs, RNAs, proteins and other biomolecules between cells. The large number of biomolecules present in exosomes demands the frequent use of high-throughput analysis. This, in turn, requires technical replicates (TRs), and biological replicates (BRs) to produce accurate results. As the number and abundance of identified biomolecules varies between replicates (Rs), establishing the replicate variability predicted for the event under study is essential in determining the number of Rs required. Although there have been few reports of replicate variability in high throughput biological data, none of them focused on exosomes. Herein, we determined the replicate variability in protein profiles found in exosomes released from 3 lung adenocarcinoma cell lines, H1993, A549 and H1975. Since exosome isolates are invariably contaminated by a small percentage of ~200-300 nm microvesicles, we refer to our samples as exosome-enriched EVs (EE-EVs). We generated BRs of EE-EVs from each cell line, and divided each group into 3 TRs. All Rs were analyzed by liquid chromatography/mass spectrometry (LC/MS/MS) and customized bioinformatics and biostatistical workflows (raw data available via ProteomeXchange: PXD012798). We found that the variability among TRs as well as BRs, was largely qualitative (protein present or absent) and higher among BRs. By contrast, the quantitative (protein abundance) variability was low, save for the H1975 cell line where the quantitative variability was significant. Importantly, our replicate strategy identified 90% of the most abundant proteins, thereby establishing the utility of our approach.

Toll-like Receptor 4-Independent Effects of Lipopolysaccharide Identified Using Longitudinal Serum Proteomics

Sepsis remains one of the most lethal and costly conditions treated in U.S. hospitals, with approximately 50% of cases caused by Gram-negative bacterial infections. Septic shock is induced when lipopolysaccharide (LPS), the main component of Gram-negative outer bacterial membrane, signals through the Toll-like receptor 4 (TLR4) complex. Lethal endotoxemia, a model for septic shock, was induced in WT C57BL6 and TLR4^-/- mice by administration of Escherichia coli LPS. WT LPS treated mice showed high morbidity, while PBS treated LPS and treated TLR4^-/- mice did not. ANOVA analysis of label-free quantification of longitudinal serum proteome revealed 182 out of 324 proteins in LPS injected WT mice that were significantly changed across four time points (0, 6, 12, and 18 h). No significant changes were identified in the two control groups. From the 182 identified proteins, examples of known sepsis biomarkers were validated by ELISA, which showed similar trends as MS proteomics data. Longitudinal analysis within individual mice produced 3-fold more significantly changed proteins than pair-wise comparison. A subsequent global analysis of WT and TLR4^-/- mice identified pathways activated independent of TLR4. These pathways represent possible compensatory mechanisms that allow for control of Gram-negative bacterial infection regardless of host immune status.

Media Optimization, Strain Compatibility, and Low-Shear Modeled Microgravity Exposure of Synthetic Microbial Communities for Urine Nitrification in Regenerative Life-Support Systems

Urine is a major waste product of human metabolism and contains essential macro- and micronutrients to produce edible microorganisms and crops. Its biological conversion into a stable form can be obtained through urea hydrolysis, subsequent nitrification, and organics removal, to recover a nitrate-enriched stream, free of oxygen demand. In this study, the utilization of a microbial community for urine nitrification was optimized with the focus for space application. To assess the role of selected parameters that can impact ureolysis in urine, the activity of six ureolytic heterotrophs (Acidovorax delafieldii, Comamonas testosteroni, Cupriavidus necator, Delftia acidovorans, Pseudomonas fluorescens, and Vibrio campbellii) was tested at different salinities, urea, and amino acid concentrations. The interaction of the ureolytic heterotrophs with a nitrifying consortium (Nitrosomonas europaea ATCC 19718 and Nitrobacter winogradskyi ATCC 25931) was also tested. Lastly, microgravity was simulated in a clinostat utilizing hardware for in-flight experiments with active microbial cultures. The results indicate salt inhibition of the ureolysis at 30 mS cm^-1, while amino acid nitrogen inhibits ureolysis in a strain-dependent manner. The combination of the nitrifiers with C. necator and V. campbellii resulted in a complete halt of the urea hydrolysis process, while in the case of A. delafieldii incomplete nitrification was observed, and nitrite was not oxidized further to nitrate. Nitrate production was confirmed in all the other communities; however, the other heterotrophic strains most likely induced oxygen competition in the test setup, and nitrite accumulation was observed. Samples exposed to low-shear modeled microgravity through clinorotation behaved similarly to the static controls. Overall, nitrate production from urea was successfully demonstrated with synthetic microbial communities under terrestrial and simulated space gravity conditions, corroborating the application of this process in space.

Determination of variability due to biological and technical variation in urinary extracellular vesicles as a crucial step in biomarker discovery studies

Urinary extracellular vesicles (EVs) are an attractive source of biomarkers for urological diseases. A crucial step in biomarker discovery studies is the determination of the variation parameters to perform a sample size calculation. In this way, a biomarker discovery study with sufficient statistical power can be performed to obtain biologically significant biomarkers. Here, a variation study was performed on both the protein and lipid content of urinary EVs of healthy individuals, aged between 52 and 69 years. Ultrafiltration (UF) in combination with size exclusion chromatography (SEC) was used to isolate the EVs from urine. Different experimental variation set-ups were used in this variation study. The calculated standard deviations (SDs) of the 90% least variable peptides and lipids did not exceed 2 and 1.2, respectively. These parameters can be used in a sample size calculation for a well-designed biomarker discovery study at the cargo of EVs.

Cytokine Levels in Inner Ear Fluid of Young and Aged Mice as Molecular Biomarkers of Noise-Induced Hearing Loss

Sensorineural hearing loss (SNHL) is the most common sensory deficit worldwide, frequently caused by noise trauma and aging, with inflammation being implicated in both pathologies. Here, we provide the first direct measurements of proinflammatory cytokines in inner ear fluid, perilymph, of adolescent and 2-year-old mice. The perilymph of adolescent mice exposed to the noise intensity resulting in permanent auditory threshold elevations had significantly increased levels of IL-6, TNF-α, and CXCL1 6 h after exposure, with CXCL1 levels being most elevated (19.3 ± 6.2 fold). We next provide the first immunohistochemical localization of CXCL1 in specific cochlear supporting cells, and its presumed receptor, Duffy antigen receptor for chemokines (DARC), in hair cells and spiral ganglion neurons. Our results demonstrate the feasibility of molecular diagnostics of SNHL using only 0.5 μL of perilymph, and motivate future sub-μL based diagnostics of human SNHL based on liquid biopsy of the inner ear to guide therapy, promote hearing protection, and monitor response to treatment.