Human body fluid proteome analysis

Machine-learning based classification of 2D-IR liquid biopsies enables stratification of melanoma relapse risk

Non-linear laser spectroscopy methods such as two-dimensional infrared (2D-IR) produce large, information-rich datasets, while developments in laser technology have brought substantial increases in data collection rates. This combination of data depth and quantity creates the opportunity to unite advanced data science approaches, such as Machine Learning (ML), with 2D-IR to reveal insights that surpass those from established data interpretation methods. To demonstrate this, we show that ML and 2D-IR spectroscopy can classify blood serum samples collected from patients with melanoma according to diagnostically-relevant groupings. Using just 20 μL samples, 2D-IR measures 'protein amide I fingerprints', which reflect the protein profile of blood serum. A hyphenated Partial Least Squares-Support Vector Machine (PLS-SVM) model was able to classify 2D-protein fingerprints taken from 40 patients with melanoma according to the presence, absence or later development of metastatic disease. Area under the receiver operating characteristic curve (AUROC) values of 0.75 and 0.86 were obtained when identifying samples from patients who were radiologically cancer free and with metastatic disease respectively. The model was also able to classify (AUROC = 0.80) samples from a third group of patients who were radiologically cancer-free at the point of testing but would go on to develop metastatic disease within five years. This ability to identify post-treatment patients at higher risk of relapse from a spectroscopic measurement of biofluid protein content shows the potential for hybrid 2D-IR-ML analyses and raises the prospect of a new route to an optical blood-based test capable of risk stratification for melanoma patients.

Blood-based biomarkers in pancreatic ductal adenocarcinoma: developments over the last decade and what holds for the future- a review

Pancreatic Ductal Adenocarcinoma (PDAC) accounts for a significant burden of global cancer deaths worldwide. The dismal outcomes associated with PDAC can be overcome by detecting the disease early and developing tools that predict response to treatment, allowing the selection of the most optimal treatment. Over the last couple of years, significant progress has been made in the development of novel biomarkers that aid in diagnosis, prognosis, treatment selection, and monitoring response. Blood-based biomarkers offer an alternative to tissue-based diagnosis and offer immense potential in managing PDAC. In this review, we have discussed the advances in blood-based biomarkers in PDAC, such as DNA (mutations and methylations), RNA, protein biomarkers and circulating tumor cells (CTC) over the last decade and also elucidated all aspects of practical implementation of these biomarkers in clinical practice. We have also discussed implementing multiomics utilizing more than one biomarker and targeted therapies that have been developed using these biomarkers.

Proteomic Analysis of Biological Fluids

Biological fluids are proteinaceous liquids or suspensions released through different body orifices or through penetration of the skin. These fluids are the result of multiple tissues and cell types and contain extensive, highly complex, and dynamic protein populations that reflect both the transcriptional program of the originating cells and a record of the individual's health status. Body fluids are readily accessible to clinicians and researchers, and as such proteomic analyses are an important component of clinical studies, fertility studies, oral health studies, and forensic investigations. Current mass spectrometry (MS) datasets have a dynamic range of up to six orders of magnitude and are as diverse as the originating tissue types. Mass spectrometry has the potential to provide information across a wide range of applications, including basic research into human biology and pathology, biochemical analysis of protein function, biomarker discovery and detection, as well as forensic investigations wherein investigators interpret a protein profile to identify the body site origin of a biological fluid. The method below describes a specimen processing workflow that is flexible in terms of biological fluid type, sample state (e.g., a dried sample extracted from evidence or neat fluid), and level of degradation. The method described here is compatible with both high sensitivity shotgun liquid chromatography-mass spectrometry LC/MS analysis and targeted (qualitative or quantitative) MS-based analysis of biomarker candidates.

Identification of potential differences in salivary proteomic profiles between estrus and diestrus stage of estrous cycle in dairy cows

In the present study, a comparative global high-throughput proteomic analysis strategy was used to identify proteomic differences between estrus and diestrus stage of estrous cycle in dairy cows. Saliva was collected from cows during estrus and diestrus, and subjected to LC-MS/MS-based proteomic analysis. A total of 2842 proteins were detected in the saliva of cows, out of which, 2437 and 1428 non-redundant proteins were identified in estrous and diestrous saliva, respectively. Further, it was found that 1414 and 405 salivary proteins were specific to estrus and diestrus, respectively while 1023 proteins were common to both groups. Among the significantly dysregulated proteins, the expression of 56 proteins was down-regulated (abundance ratio <0.5) while 40 proteins were up-regulated (abundance ratio > 2) in estrous compared to diestrous saliva. The proteins, such as HSD17B12, INHBA, HSP70, ENO1, SRD5A1, MOS, AMH, ECE2, PDGFA, OPRK1, SYN1, CCNC, PLIN5, CETN1, AKR1C4, NMNAT1, CYP2E1, and CYP19A1 were detected only in the saliva samples derived from estrous cows. Considerable number of proteins detected in the saliva of estrous cows were found to be involved in metabolic pathway, PI3K-Akt signaling pathway, toll-like receptor signaling pathway, steroid biosynthesis pathway, insulin signaling pathway, calcium signaling pathway, estrogen signaling pathway, oxytocin signaling pathway, TGF-β signaling pathway and oocyte meiosis. On the other hand, proteins detected in saliva of diestrous cows were involved mainly in metabolic pathway. Collectively, these data provide preliminary evidence of a potential difference in salivary proteins at different stages of estrous cycle in dairy cows.

Aggregation-Induced Emission Luminogen: Role in Biopsy for Precision Medicine

Biopsy, including tissue and liquid biopsy, offers comprehensive and real-time physiological and pathological information for disease detection, diagnosis, and monitoring. Fluorescent probes are frequently selected to obtain adequate information on pathological processes in a rapid and minimally invasive manner based on their advantages for biopsy. However, conventional fluorescent probes have been found to show aggregation-caused quenching (ACQ) properties, impeding greater progresses in this area. Since the discovery of aggregation-induced emission luminogen (AIEgen) have promoted rapid advancements in molecular bionanomaterials owing to their unique properties, including high quantum yield (QY) and signal-to-noise ratio (SNR), etc. This review seeks to present the latest advances in AIEgen-based biofluorescent probes for biopsy in real or artificial samples, and also the key properties of these AIE probes. This review is divided into: (i) tissue biopsy based on smart AIEgens, (ii) blood sample biopsy based on smart AIEgens, (iii) urine sample biopsy based on smart AIEgens, (iv) saliva sample biopsy based on smart AIEgens, (v) biopsy of other liquid samples based on smart AIEgens, and (vi) perspectives and conclusion. This review could provide additional guidance to motivate interest and bolster more innovative ideas for further exploring the applications of various smart AIEgens in precision medicine.

Comparative analysis of plasma affinity depletion methods: Impact on protein composition and phosphopeptide abundance in human plasma

Affinity-based protein depletion and TiO2 enrichment methods play a crucial role in detection of low-abundant proteins and phosphopeptides enrichment, respectively. Here, we assessed the effectiveness of HSA/IgG (HU2) and Human 7 (HU7) depletion methods and their impact on phosphopeptides coverage through comparative proteome analysis, utilizing in-solution digestion and nano-LC-Orbitrap mass spectrometry (MS). Our results demonstrated that both HU2 and HU7 affinity depletion significantly decreased high-abundant proteins by 1.5-7.8-fold (p < 0.001). A total of 1491 proteins were identified, with 48 proteins showing significant expression in the depleted groups. Notably, cadherin-13, neutrophil defensin 1, APM1, and desmoplakin variant protein were exclusively detected in the HU2/HU7-depleted groups. Furthermore, study on effect of depletion on phosphopeptides revealed an increase in tandem MS spectral counts with notable decrease (∼50%) in peptide spectrum matching in depleted groups, which was attributed to significant reduction in protein counts. Our post translation modification workflow for phosphoproteomics detected 42 phosphorylated peptides, corresponding to 12 phosphoproteins with unique peptide match ≥2 (high false discovery rates confidence). Among them, 10 phosphorylated proteins are highly expressed in depleted groups. Overall, these findings offer valuable insights in selection of protein depletion methods for comprehensive plasma proteomics analysis.

Enhanced CRISPR/Cas-Based Immunoassay through Magnetic Proximity Extension and Detection

Clustered regularly interspaced short palindromic repeats (CRISPR)/Cas-associated systems have recently emerged as a focal point for developing next-generation molecular diagnosis, particularly for nucleic acid detection. However, the detection of proteins is equally critical across diverse applications in biology, medicine, and the food industry, especially for diagnosing and prognosing diseases like cancer, Alzheimer's and cardiovascular conditions. Despite recent efforts to adapt CRISPR/Cas systems for protein detection with immunoassays, these methods typically achieved sensitivity only in the femtomolar to picomolar range, underscoring the need for enhanced detection capabilities. To address this, we developed CRISPR-AMPED, an innovative CRISPR/Cas-based immunoassay enhanced by magnetic proximity extension and detection. This approach combines proximity extension assay (PEA) with magnetic beads that converts protein into DNA barcodes for quantification with effective washing steps to minimize non-specific binding and hybridization, therefore reducing background noise and increasing detection sensitivity. The resulting DNA barcodes are then detected through isothermal nucleic acid amplification testing (NAAT) using recombinase polymerase amplification (RPA) coupled with the CRISPR/Cas12a system, replacing the traditional PCR. This integration eliminates the need for thermocycling and bulky equipment, reduces amplification time, and provides simultaneous target and signal amplification, thereby significantly boosting detection sensitivity. CRISPR-AMPED achieves attomolar level sensitivity, surpassing ELISA by over three orders of magnitude and outperforming existing CRISPR/Cas-based detection systems. Additionally, our smartphone-based detection device demonstrates potential for point-of-care applications, and the digital format extends dynamic range and enhances quantitation precision. We believe CRISPR-AMPED represents a significant advancement in the field of protein detection.

Promises and Challenges of populational Proteomics in Health and Disease

Advances in proteomic assay technologies have significantly increased coverage and throughput, enabling recent increases in the number of large-scale population-based proteomic studies of human plasma and serum. Improvements in multiplexed protein assays have facilitated the quantification of thousands of proteins over a large dynamic range, a key requirement for detecting the lowest-ranging, and potentially the most disease-relevant, blood-circulating proteins. In this perspective, we examine how populational proteomic datasets in conjunction with other concurrent omic measures can be leveraged to better understand the genomic and non-genomic correlates of the soluble proteome, constructing biomarker panels for disease prediction, among others. Mass spectrometry workflows are discussed as they are becoming increasingly competitive with affinity-based array platforms in terms of speed, cost, and proteome coverage due to advances in both instrumentation and workflows. Despite much success, there remain considerable challenges such as orthogonal validation and absolute quantification. We also highlight emergent challenges associated with study design, analytical considerations, and data integration as population-scale studies are run in batches and may involve longitudinal samples collated over many years. Lastly, we take a look at the future of what the nascent next-generation proteomic technologies might provide to the analysis of large sets of blood samples, as well as the difficulties in designing large-scale studies that will likely require participation from multiple and complex funding sources and where data sharing, study designs, and financing must be solved.

ESMSec: Prediction of Secreted Proteins in Human Body Fluids Using Protein Language Models and Attention

The secreted proteins of human body fluid have the potential to be used as biomarkers for diseases. These biomarkers can be used for early diagnosis and risk prediction of diseases, so the study of secreted proteins of human body fluid has great application value. In recent years, the deep-learning-based transformer language model has transferred from the field of natural language processing (NLP) to the field of proteomics, leading to the development of protein language models (PLMs) for protein sequence representation. Here, we propose a deep learning framework called ESM Predict Secreted Proteins (ESMSec) to predict three types of proteins secreted in human body fluid. The ESMSec is based on the ESM2 model and attention architecture. Specifically, the protein sequence data are firstly put into the ESM2 model to extract the feature information from the last hidden layer, and all the input proteins are encoded into a fixed 1000 × 480 matrix. Secondly, multi-head attention with a fully connected neural network is employed as the classifier to perform binary classification according to whether they are secreted into each body fluid. Our experiment utilized three human body fluids that are important and ubiquitous markers. Experimental results show that ESMSec achieved average accuracy of 0.8486, 0.8358, and 0.8325 on the testing datasets for plasma, cerebrospinal fluid (CSF), and seminal fluid, which on average outperform the state-of-the-art (SOTA) methods. The outstanding performance results of ESMSec demonstrate that the ESM can improve the prediction performance of the model and has great potential to screen the secretion information of human body fluid proteins.

Proteomic Analysis of Domestic Cat Blastocysts and Their Secretome Produced in an In Vitro Culture System without the Presence of the Zona Pellucida

Domestic cat blastocysts cultured without the zona pellucida exhibit reduced implantation capacity. However, the protein expression profile has not been evaluated in these embryos. The objective of this study was to evaluate the protein expression profile of domestic cat blastocysts cultured without the zona pellucida. Two experimental groups were generated: (1) domestic cat embryos generated by IVF and cultured in vitro (zona intact, (ZI)) and (2) domestic cat embryos cultured in vitro without the zona pellucida (zona-free (ZF group)). The cleavage, morula, and blastocyst rates were estimated at days 2, 5 and 7, respectively. Day 7 blastocysts and their culture media were subjected to liquid chromatography-tandem mass spectrometry (LC-MS/MS). The UniProt Felis catus database was used to identify the standard proteome. No significant differences were found in the cleavage, morula, or blastocyst rates between the ZI and ZF groups (p > 0.05). Proteomic analysis revealed 22 upregulated and 20 downregulated proteins in the ZF blastocysts. Furthermore, 14 proteins involved in embryo development and implantation were present exclusively in the culture medium of the ZI blastocysts. In conclusion, embryo culture without the zona pellucida did not affect in vitro development, but altered the protein expression profile and release of domestic cat blastocysts.

Peptidome Profiling of Bubalus bubalis Urine and Assessment of Its Antimicrobial Activity against Mastitis-Causing Pathogens

Urinary proteins have been studied quite exhaustively in the past, however, the small sized peptides have remained neglected for a long time in dairy cattle. These peptides are the products of systemic protein turnover, which are excreted out of the body and hence can serve as an important biomarker for various pathophysiologies. These peptides in other species of bovine have been reported to possess several bioactive properties. To investigate the urinary peptides in buffalo and simultaneously their bioactivities, we generated a peptidome profile from the urine of Murrah Buffaloes (n = 10). Urine samples were processed using <10 kDa MWCO filter and filtrate obtained was used for peptide extraction using Solid Phase Extraction (SPE). The nLC-MS/MS of the aqueous phase from ten animals resulted in the identification of 8165 peptides originating from 6041 parent proteins. We further analyzed these peptide sequences to identify bioactive peptides and classify them into anti-cancerous, anti-hypertensive, anti-microbial, and anti-inflammatory groups with a special emphasis on antimicrobial properties. With this in mind, we simultaneously conducted experiments to evaluate the antimicrobial properties of urinary aqueous extract on three pathogenic bacterial strains: S. aureus, E. coli, and S. agalactiae. The urinary peptides observed in the study are the result of the activity of possibly 76 proteases. The GO of these proteases showed the significant enrichment of the antibacterial peptide production. The total urinary peptide showed antimicrobial activity against the aforementioned pathogenic bacterial strains with no significant inhibitory effects against a buffalo mammary epithelial cell line. Just like our previous study in cows, the present study suggests the prime role of the antimicrobial peptides in the maintenance of the sterility of the urinary tract in buffalo by virtue of their amino acid composition.

Starch treatment improves the salivary proteome for subject identification purposes

Identification of subjects, including perpetrators, is one of the most crucial goals of forensic science. Saliva is among the most common biological fluids found at crime scenes, containing identifiable components. DNA has been the most prominent identifier to date, but its analysis can be complex due to low DNA yields and issues preserving its integrity at the crime scene. Proteins are emerging as viable candidates for subject identification. Previous work has shown that the salivary proteome of the least-abundant proteins may be helpful for subject identification, but more optimized techniques are needed. Among them is removing the most abundant proteins, such as salivary α-amylase. Starch treatment of saliva samples elicited the removal of this enzyme and that of glycosylated, low-molecular-weight proteins, proteases, and immunoglobulins, resulting in a saliva proteome profile enriched with a subset of proteins, allowing a more reliable and nuanced subject identification.

Chicken muscle antibody array reveals the regulations of LDHA on myoblast differentiation through energy metabolism

Myoblast proliferation and differentiation are highly dynamic and regulated processes in skeletal muscle development. Given that proteins serve as the executors for the majority of biological processes, exploring key regulatory factors and mechanisms at the protein level offers substantial opportunities for understanding the skeletal muscle development. In this study, a total of 607 differentially expressed proteins between proliferation and differentiation in myoblasts were screened out using our chicken muscle antibody array. Biological function analysis revealed the importance of energy production processes and compound metabolic processes in myogenesis. Our antibody array specifically identified an upregulation of LDHA during differentiation, which was associated with the energy metabolism. Subsequent investigation demonstrated that LDHA promoted the glycolysis and TCA cycle, thereby enhancing myoblasts differentiation. Mechanistically, LDHA promotes the glycolysis and TCA cycle but inhibits the ETC oxidative phosphorylation through enhancing the NADH cycle, providing the intermediate metabolites that improve the myoblasts differentiation. Additionally, increased glycolytic ATP by LDHA induces Akt phosphorylation and activate the PI3K-Akt pathway, which might also contribute to the promotion of myoblasts differentiation. Our studies not only present a powerful tool for exploring myogenic regulatory factors in chicken muscle, but also identify a novel role for LDHA in modulating myoblast differentiation through its regulation of cellular NAD+ levels and subsequent downstream effects on mitochondrial function.

Optical Screening and Classification of Drug Binding to Proteins in Human Blood Serum

Protein-drug interactions in the human bloodstream are important factors in applications ranging from drug design, where protein binding influences efficacy and dose delivery, to biomedical diagnostics, where rapid, quantitative measurements could guide optimized treatment regimes. Current measurement approaches use multistep assays, which probe the protein-bound drug fraction indirectly and do not provide fundamental structural or dynamic information about the in vivo protein-drug interaction. We demonstrate that ultrafast 2D-IR spectroscopy can overcome these issues by providing a direct, label-free optical measurement of protein-drug binding in blood serum samples. Four commonly prescribed drugs, known to bind to human serum albumin (HSA), were added to pooled human serum at physiologically relevant concentrations. In each case, spectral changes to the amide I band of the serum sample were observed, consistent with binding to HSA, but were distinct for each of the four drugs. A machine-learning-based classification of the serum samples achieved a total cross-validation prediction accuracy of 92% when differentiating serum-only samples from those with a drug present. Identification on a per-drug basis achieved correct drug identification in 75% of cases. These unique spectroscopic signatures of the drug-protein interaction thus enable the detection and differentiation of drug containing samples and give structural insight into the binding process as well as quantitative information on protein-drug binding. Using currently available instrumentation, the 2D-IR data acquisition required just 1 min and 10 μL of serum per sample, and so these results pave the way to fast, specific, and quantitative measurements of protein-drug binding in vivo with potentially invaluable applications for the development of novel therapies and personalized medicine.

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.

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.

Straightforward fabrication of electrochemical aptasensors with outstanding antifouling performance

Self-assembled monolayers (SAMs) are popular tools for many different applications - SAMs of commercially available chemicals that convincingly inhibit unspecific binding for electrochemical sensors, however, have yet to be developed. While adsorption of foulants prohibits the reliable analysis of biological samples, unspecific binding of the analyte similarly impedes the investigation of binding characteristics from buffer solutions. In this communication, diglycolamine is introduced for the modification of electrodes with outstanding antifouling performance. The presented sensor design, solely consisting of diglycolamine and an aptamer of choice, convinces with its ease of preparation, low cost, and, most importantly, an exceptional specificity. The latter was found to rely on a gentle but potent cleaning of the electrodes, as only our optimized cleaning procedure granted the diglycolamine layer its excellent fouling minimization performance, while literature standard protocols failed to do so. Each step of the sensor fabrication protocol was optimized by electrochemical impedance spectroscopy, while square-wave voltammetry, surface-enhanced Raman spectroscopy, and zeta potential measurement were performed for further characterization. The presented approach of surface modification with diglycolamine is a versatile method applicable not just to electrochemical measurements, but to a variety of other detection techniques, too, and has the potential to change the way we investigate binding characteristics and fabricate sensors for the analysis of complex biological samples.

Age-Related Changes in Post-Translational Modifications of Proteins from Whole Male and Female Skeletal Elements

One of the key questions in forensic cases relates to some form of age inference, whether this is how old a crime scene is, when in time a particular crime was committed, or how old the victim was at the time of the crime. These age-related estimations are currently achieved through morphological methods with varying degrees of accuracy. As a result, biomolecular approaches are considered of great interest, with the relative abundances of several protein markers already recognized for their potential forensic significance; however, one of the greatest advantages of proteomic investigations over genomics ones is the wide range of post-translational modifications (PTMs) that make for a complex but highly dynamic resource of information. Here, we explore the abundance of several PTMs including the glycosylation, deamidation, and oxidation of several key proteins (collagen, fetuin A, biglycan, serum albumin, fibronectin and osteopontin) as being of potential value to the development of an age estimation tool worthy of further evaluation in forensic contexts. We find that glycosylations lowered into adulthood but deamidation and oxidation increased in the same age range.

Hollow Core-Shell Metal Oxide Heterojunctions for the Urinary Metabolic Fingerprint-Based Noninvasive Diagnostic Strategy

Urine is a preferred object for noninvasive diagnostic strategies. Urinary metabolic analysis is speculatively regarded as an ideal tool for screening diseases closely related to the genitourinary system in view of the intimate relationship between metabolomics and phenotype. Herein, we propose a urinary metabolic fingerprint-based noninvasive diagnostic strategy by designing hollow core-shell metal oxide heterojunctions (denoted as MOHs). With outstanding light absorption and electron-hole separation ability, MOHs aid in the extraction of high-performance urine metabolic fingerprints. Coupled with optimized machine learning algorithms, we establish a metabolic marker panel for accurate diagnosis of prostate cancer (PCa), which is the most common malignant tumor of the male genitourinary system, achieving accuracies of 84.72 and 83.33% in the discovery and validation sets, respectively. Furthermore, metabolite variations and related pathway analyses confirm the credibility and change correlation of key metabolic features in PCa. This work tends to advance the noninvasive diagnostic strategy toward clinical realities.

Liquid Biopsies, Novel Approaches and Future Directions

Cancer is among the leading causes of death worldwide. Early diagnosis and prognosis are vital to improve patients' outcomes. The gold standard of tumor characterization leading to tumor diagnosis and prognosis is tissue biopsy. Amongst the constraints of tissue biopsy collection is the sampling frequency and the incomplete representation of the entire tumor bulk. Liquid biopsy approaches, including the analysis of circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), circulating miRNAs, and tumor-derived extracellular vesicles (EVs), as well as certain protein signatures that are released in the circulation from primary tumors and their metastatic sites, present a promising and more potent candidate for patient diagnosis and follow up monitoring. The minimally invasive nature of liquid biopsies, allowing frequent collection, can be used in the monitoring of therapy response in real time, allowing the development of novel approaches in the therapeutic management of cancer patients. In this review we will describe recent advances in the field of liquid biopsy markers focusing on their advantages and disadvantages.

Protein glycosylation in urine as a biomarker of diseases

Human body fluids have become an indispensable resource for clinical research, diagnosis and prognosis. Urine is widely used to discover disease-specific glycoprotein biomarkers because of its recurrently non-invasive collection and disease-indicating properties. While urine is an unstable fluid in that its composition changes with ingested nutrients and further as it is excreted through micturition, urinary proteins are more stable and their abnormal glycosylation is associated with diseases. It is known that aberrant glycosylation can define tumor malignancy and indicate disease initiation and progression. However, a thorough and translational survey of urinary glycosylation in diseases has not been performed. In this article, we evaluate the clinical applications of urine, introduce methods for urine glycosylation analysis, and discuss urine glycoprotein biomarkers. We emphasize the importance of mining urinary glycoproteins and searching for disease-specific glycosylation in various diseases (including cancer, neurodegenerative diseases, diabetes, and viral infections). With advances in mass spectrometry-based glycomics/glycoproteomics/glycopeptidomics, characterization of disease-specific glycosylation will optimistically lead to the discovery of disease-related urinary biomarkers with better sensitivity and specificity in the near future.

Solid phase extraction as sample pretreatment method for top-down quantitative analysis of low molecular weight proteins from biological samples using liquid chromatography - triple quadrupole mass spectrometry

Targeting and quantifying intact proteins from biological samples is still a very challenging research area. Several crucial steps exist in the analytical workflow, including development of a reliable sample preparation method. Here, we developed and applied for the first time a non-immunoaffinity sample preparation method based on a generally widely available micro-elution solid phase extraction (μSPE) strategy for the extraction of multiple lower molecular weight intact proteins (<30 kDa) from various biological matrices. Omission of a time-consuming drying and reconstitution step after extraction resulted in a more simple and rapid sample preparation procedure. A model set of eleven intact proteins (molecular weights: 5.5-29 kDa; isoelectric points: 4.5-11.3) were analyzed in multiple biological fluids using reversed-phase liquid chromatography with a triple quadrupole mass spectrometer operated in multiple reaction monitoring mode. Various sample pre-treatment reagents, sorbent types, and washing and elution solvents were experimentally tested and optimized to obtain the μSPE clean-up condition for a broad mixture of intact proteins having variable physicochemical properties. 1% trifluoroacetic acid and 0.2% Triton 100-X were selected as suitable sample pre-treatment reagents for releasing protein-protein interactions in human serum/plasma and human urine, respectively. Hydrophilic lipophilic balanced μSPE sorbent was selected as a high performing stationary phase. Addition of 1% trifluoroacetic acid to all washing and elution solutions showed the most beneficial effect for the extraction recovery of the proteins. Under the optimized conditions, reproducible extraction recoveries >65% for all targeted proteins (up to 30 kDa) in human urine and >50% for most of the proteins in serum/plasma were achieved. The selected conditions were applied also for the analysis of clinical serum and urine samples to demonstrate the feasibility of the developed method to target intact proteins directly by more affordable μSPE sample preparation and triple quadrupole mass spectrometry, which could be beneficial in many application fields.

Investigating centrifugal filtration of serum-based FTIR spectroscopy for the stratification of brain tumours

Discrimination of brain cancer versus non-cancer patients using serum-based attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy diagnostics was first developed by Hands et al with a reported sensitivity of 92.8% and specificity of 91.5%. Cameron et al. then went on to stratifying between specific brain tumour types: glioblastoma multiforme (GBM) vs. primary cerebral lymphoma with a sensitivity of 90.1% and specificity of 86.3%. Expanding on these studies, 30 GBM, 30 lymphoma and 30 non-cancer patients were selected to investigate the influence on test performance by focusing on specific molecular weight regions of the patient serum. Membrane filters with molecular weight cut offs of 100 kDa, 50 kDa, 30 kDa, 10 kDa and 3 kDa were purchased in order to remove the most abundant high molecular weight components. Three groups were classified using both partial least squares-discriminate analysis (PLS-DA) and random forest (RF) machine learning algorithms; GBM versus non-cancer, lymphoma versus non-cancer and GBM versus lymphoma. For all groups, once the serum was filtered the sensitivity, specificity and overall balanced accuracies decreased. This illustrates that the high molecular weight components are required for discrimination between cancer and non-cancer as well as between tumour types. From a clinical application point of view, this is preferable as less sample preparation is required.

Proteomic Applications and Considerations: From Research to Patient Care

Despite technological advancements in the field of proteomics, the rate at which serum and plasma biomarkers identified using proteomic approaches are translated into clinical use remains extremely low. In this chapter, we describe recent technological advancements and analytical strategies in proteomic methods. We also describe the progress of proteomic blood-based biomarkers to date and discuss what the future of proteomics might entail with the use of multi-omic approaches and implementing machine learning on large proteomic datasets. Lastly, we provide several key considerations for biomarker studies, ranging from sample type to the use of reference samples, in order to achieve progress from bench to bedside, ultimately improving patient diagnosis, disease, and/or therapeutic monitoring and care.

Paper based microfluidic devices: a review of fabrication techniques and applications

A wide range of applications are possible with paper-based analytical devices, which are low priced, easy to fabricate and operate, and require no specialized equipment. Paper-based microfluidics offers the design of miniaturized POC devices to be applied in the health, environment, food, and energy sector employing the ASSURED (Affordable, Sensitive, Specific, User-friendly, Rapid and Robust, Equipment free and Deliverable to end users) principle of WHO. Therefore, this field is growing very rapidly and ample research is being done. This review focuses on fabrication and detection techniques reported to date. Additionally, this review emphasises on the application of this technology in the area of medical diagnosis, energy generation, environmental monitoring, and food quality control. This review also presents the theoretical analysis of fluid flow in porous media for the efficient handling and control of fluids. The limitations of PAD have also been discussed with an emphasis to concern on the transformation of such devices from laboratory to the consumer.

Recent Advances in Proteomics-Based Approaches to Studying Age-Related Macular Degeneration: A Systematic Review

Age-related macular degeneration (AMD) is a common ocular disease characterized by degeneration of the central area of the retina in the elderly population. Progression and response to treatment are influenced by genetic and non-genetic factors. Proteomics is a powerful tool to study, at the molecular level, the mechanisms underlying the progression of the disease, to identify new therapeutic targets and to establish biomarkers to monitor progression and treatment effectiveness. In this work, we systematically review the use of proteomics-based approaches for the study of the molecular mechanisms underlying the development of AMD, as well as the progression of the disease and on-treatment patient monitoring. The Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) reporting guidelines were followed. Proteomic approaches have identified key players in the onset of the disease, such as complement components and proteins involved in lipid metabolism and oxidative stress, but also in the progression to advanced stages, including factors related to extracellular matrix integrity and angiogenesis. Although anti-vascular endothelial growth factor (anti-VEGF)-based therapy has been crucial in the treatment of neovascular AMD, it is necessary to deepen our understanding of the underlying disease mechanisms to move forward to next-generation therapies for later-stage forms of this multifactorial disease.

Mass spectrometry-based tear proteomics for noninvasive biomarker discovery

The lacrimal film has attracted increasing interest in the last decades as a potential source of biomarkers of physiopathological states, due to its accessibility, moderate complexity, and responsiveness to ocular and systemic diseases. High-performance liquid chromatography-mass spectrometry (LC-MS) has led to effective approaches to tear proteomics, despite the intrinsic limitations in sample amounts. This review focuses on the recent progress in strategy and technology, with an emphasis on the potential for personalized medicine. After an introduction on lacrimal-film composition, examples of applications to biomarker discovery are discussed, comparing approaches based on pooled-sample and single-tear analysis. Then, the most critical steps of the experimental pipeline, that is, tear collection, sample fractionation, and LC-MS implementation, are discussed with reference to proteome-coverage optimization. Advantages and challenges of the alternative procedures are highlighted. Despite the still limited number of studies, tear quantitative proteomics, including single-tear investigation, could offer unique contributions to the identification of low-invasiveness, sustained-accessibility biomarkers, and to the development of personalized approaches to therapy and diagnosis.

Development of an artificial synovial fluid useful for studying Staphylococcus epidermidis joint infections

Staphylococcus epidermidis is a major causative agent of prosthetic joint infections (PJI). The ability to form biofilms supports this highly selective pathogenic potential. In vitro studies essentially relying on phenotypic assays and genetic approaches have provided a detailed picture of the molecular events contributing to biofilm assembly. A major limitation in these studies is the use of synthetic growth media, which significantly differs from the environmental conditions S. epidermidis encounters during host invasion. Building on evidence showing that growth in serum substantially affects S. epidermidis gene expression profiles and phenotypes, the major aim of this study was to develop and characterize a growth medium mimicking synovial fluid, thereby facilitating research addressing specific aspects related to PJI. Using fresh human plasma, a protocol was established allowing for the large-scale production of a medium that by biochemical analysis matches key characteristics of synovial fluid and therefore is referred to as artificial synovial fluid (ASF). By analysis of biofilm-positive, polysaccharide intercellular adhesion (PIA)-producing S. epidermidis 1457 and its isogenic, PIA- and biofilm-negative mutant 1457-M10, evidence is provided that the presence of ASF induces cluster formation in S. epidermidis 1457 and mutant 1457-M10. Consistent with the aggregative properties, both strains formed multilayered biofilms when analyzed by confocal laser scanning microscopy. In parallel to the phenotypic findings, expression analysis after growth in ASF found upregulation of genes encoding for intercellular adhesins (icaA, aap, and embp) as well as atlE, encoding for the major cell wall autolysin being responsible for eDNA release. In contrast, growth in ASF was associated with reduced expression of the master regulator agr. Collectively, these results indicate that ASF induces expression profiles that are able to support intercellular adhesion in both PIA-positive and PIA-negative S. epidermidis. Given the observation that ASF overall induced biofilm formation in a collection of S. epidermidis isolates from PJI, the results strongly support the idea of using growth media mimicking host environments. ASF may play an important role in future studies related to the pathogenesis of S. epidermidis PJI.

Chemical Barrier Proteins in Human Body Fluids

Chemical barriers are composed of those sites of the human body where potential pathogens can contact the host cells. A chemical barrier is made up by different proteins that are part of the antimicrobial and immunomodulatory protein/peptide (AMP) family. Proteins of the AMP family exert antibacterial, antiviral, and/or antifungal activity and can modulate the immune system. Besides these proteins, a wide range of proteases and protease inhibitors can also be found in the chemical barriers maintaining a proteolytic balance in the host and/or the pathogens. In this review, we aimed to identify the chemical barrier components in nine human body fluids. The interaction networks of the chemical barrier proteins in each examined body fluid were generated as well.

Salivary Neurotrophins Brain-Derived Neurotrophic Factor and Nerve Growth Factor Associated with Childhood Obesity: A Multiplex Magnetic Luminescence Analysis

Obesity is linked with higher inflammatory markers and is characterized by chronic low-grade inflammation. Neurotrophins brain-derived neurotrophic factor (BDNF) and β-nerve growth factor (β-NGF), in addition to their neuronal functions, act on several immune cells and have been recently designated as metabokines due to their regulatory role in energy homeostasis and food intake. The current study evaluates the salivary BDNF and β-NGF and their association with anthropometric measurement, blood pressure, and salivary insulin in children. Anthropometric measurements and saliva samples were obtained from 76 children, aged 6–10 years. Multiplex analysis was carried out for the salivary analysis of BDNF, NGF, and insulin by human magnetic Luminex performance assay. Statistical analysis was performed to analyze the best fit diagnostic value for biomarkers and the relationship of the neurotrophic levels of BDNF and NGF with obesity measures and blood pressure. Salivary BDNF and β-NGF showed a significantly higher concentration in obese children than normal-weight children. Both neurotrophins are positively associated with obesity anthropometric measures, blood pressure, and salivary insulin. Multinominal regression analysis reported a significant association between salivary BDNF, β-NGF, insulin, and systolic pressure adjusted for age, gender, income, and maternal education. The salivary concentration of BDNF and NGF was higher in obese children, and it is positively associated with anthropometric measures, suggesting that neurotrophins can be used as a non-invasive predictor of obesity-related complications in children.

Insights on Proteomics-Driven Body Fluid-Based Biomarkers of Cervical Cancer

Cervical cancer is one of the top malignancies in women around the globe, which still holds its place despite being preventable at early stages. Gynecological conditions, even maladies like cervical cancer, still experience scrutiny from society owing to prevalent taboo and invasive screening methods, especially in developing economies. Additionally, current diagnoses lack specificity and sensitivity, which prolong diagnosis until it is too late. Advances in omics-based technologies aid in discovering differential multi-omics profiles between healthy individuals and cancer patients, which could be utilized for the discovery of body fluid-based biomarkers. Body fluids are a promising potential alternative for early disease detection and counteracting the problems of invasiveness while also serving as a pool of potential biomarkers. In this review, we will provide details of the body fluids-based biomarkers that have been reported in cervical cancer. Here, we have presented our perspective on proteomics for global biomarker discovery by addressing several pertinent problems, including the challenges that are confronted in cervical cancer. Further, we also used bioinformatic methods to undertake a meta-analysis of significantly up-regulated biomolecular profiles in CVF from cervical cancer patients. Our analysis deciphered alterations in the biological pathways in CVF such as immune response, glycolytic processes, regulation of cell death, regulation of structural size, protein polymerization disease, and other pathways that can cumulatively contribute to cervical cancer malignancy. We believe, more extensive research on such biomarkers, will speed up the road to early identification and prevention of cervical cancer in the near future.

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.

Clinical Spectroscopy: Lost in Translation?

This Focal Point Review paper discusses the developments of biomedical Raman and infrared spectroscopy, and the recent strive towards these technologies being regarded as reliable clinical tools. The promise of vibrational spectroscopy in the field of biomedical science, alongside the development of computational methods for spectral analysis, has driven a plethora of proof-of-concept studies which convey the potential of various spectroscopic approaches. Here we report a brief review of the literature published over the past few decades, with a focus on the current technical, clinical, and economic barriers to translation, namely the limitations of many of the early studies, and the lack of understanding of clinical pathways, health technology assessments, regulatory approval, clinical feasibility, and funding applications. The field of biomedical vibrational spectroscopy must acknowledge and overcome these hurdles in order to achieve clinical efficacy. Current prospects have been overviewed with comment on the advised future direction of spectroscopic technologies, with the aspiration that many of these innovative approaches can ultimately reach the frontier of medical diagnostics and many clinical applications.

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 technologies for cancer liquid biopsies

Alterations in DNAs could not reveal what happened in proteins. The accumulated alterations of DNAs would change the manifestation of proteins. Therefore, as is the case in cancer liquid biopsies, deep proteome profiling will likely provide invaluable and clinically relevant information in real-time throughout all stages of cancer progression. However, due to the great complexity of proteomes in liquid biopsy samples and the limitations of proteomic technologies compared to high-plex sequencing technologies, proteomic discoveries have yet lagged behind their counterpart, genomic technologies. Therefore, novel protein technologies are in urgent demand to fulfill the goals set out for biomarker discovery in cancer liquid biopsies.Notably, conventional and innovative technologies are being rapidly developed for proteomic analysis in cancer liquid biopsies. These advances have greatly facilitated early detection, diagnosis, prognosis, and monitoring of cancer evolution, adapted or adopted in response to therapeutic interventions. In this paper, we review the high-plex proteomics technologies that are capable of measuring at least hundreds of proteins simultaneously from liquid biopsy samples, ranging from traditional technologies based on mass spectrometry (MS) and antibody/antigen arrays to innovative technologies based on aptamer, proximity extension assay (PEA), and reverse phase protein arrays (RPPA).

Loggerhead sea turtle Caretta caretta plasma biochemistry and proteome profile modulation during recovery

The aim of the study was to monitor and analyse injured and diseased loggerhead sea turtles (Caretta caretta) plasma proteome profiles and biochemistry parameters during their recovery period in rescue centre within different age and recovery period groups, and determine the potential biomarkers that can be used in diagnostics. The plasma biochemical parameters of total protein and glucose content, accompanied by aspartate aminotransferase (AST) and N-acetyl-cystein-activated creatinine kinase (CK-NAC) are highlighted as valuable and potential biomarkers of turtle's health status and condition. Using high throughput tandem mass tag (TMT)-based proteomic approach we identified 913 plasma proteins, 12 of which shown to be modulated in loggerheads age groups, and identified as a part of (i) platelet degranulation, (ii) neutrophil degranulation, and (iii) innate immune system pathways. The neurofascin (NFASC) is shown to be differentially abundant among all the age groups, and alpha-1-acid glycoprotein 2-like (ORM2) and alpha-1-antitrypsin-like (SERPINA1) proteins were recognized as members of all three above mentioned REACTOME pathways. Furthermore, 29 of plasma proteins were significantly differentially abundant in loggerheads age and recovery period groups. Out of 15 recognized pathways, those proteins were mostly included in three specific REACTOME pathways: (i) post-translational phosphorylation, (ii) regulation of Insulin-like Growth Factor (IGF) transport and uptake by Insulin-like Growth Factor Binding Proteins (IGFBPs), and (iii) platelet degranulation. The alpha-fetoprotein (AFP) was the only protein which showed statistically significant up-regulation patterns in all loggerhead age groups before release from the rescue centre, and the complement component 3 (C3) protein was the only protein modulated in all recovery period groups. Furthermore, C3 protein takes part in 9; and followed up with apolipoprotein A-I (APOA1) in 7; complement component 4 (C4), complement component 5 (C5) and kininogen-1 (KNG1) in 6 REACTOME pathways. Thereby, those proteins are highlighted and recommended as potential biomarkers of turtle's health status. Data are available via ProteomeXchange with identifier PXD029569. Finally, based on our results, we believe that comprehensive omics approach and routine plasma biochemical analysis, accompanied by proteins of acute phase, acid-base status and immune-response indicator analysis may significantly and reliably improve assessment of captive loggerheads rehabilitation and medication. SIGNIFICANCE: Monitoring and comparison of loggerhead sea turtles (C. caretta) blood plasma biochemistry parameters and plasma proteome profiles in relation to the age, and recovery period pointed out significantly differentially abundant proteins, along with certain biochemical parameter contents as potential biomarkers of turtle's fitness, health status and physiology.

Plasma Protein Levels Analysis in Multiple Sclerosis Sardinian Families Identified C9 and CYP24A1 as Candidate Biomarkers

Here we investigate protein levels in 69 multiple sclerosis (MS) cases and 143 healthy controls (HC) from twenty Sardinian families to search for promising biomarkers in plasma. Using antibody suspension bead array technology, the plasma levels of 56 MS-related proteins were obtained. Differences between MS cases and HC were estimated using Linear Mixed Models or Linear Quantile Mixed Models. The proportion of proteins level variability, explained by a set of 119 MS-risk SNPs as to the literature, was also quantified. Higher plasma C9 and CYP24A1 levels were found in MS cases compared to HC (p < 0.05 after Holm multiple testing correction), with protein level differences estimated as, respectively, 0.53 (95% CI: 0.25, 0.81) and 0.42 (95% CI: 0.19, 0.65) times plasma level standard deviation measured in HC. Furthermore, C9 resulted in both statistically significantly higher relapsing-remitting MS (RRMS) and secondary-progressive MS (SPMS) compared to HC, with SPMS showing the highest differences. Instead, CYP24A1 was statistically significantly higher only in RRMS as compared to HC. Respectively, 26% (95% CI: 10%, 44%) and 16% (95% CI: 9%, 39%) of CYP24A1 and C9 plasma level variability was explained by known MS-risk SNPs. Our results highlight C9 and CYP24A1 as potential biomarkers in plasma for MS and allow us to gain insight into molecular disease mechanisms.

Nipple Aspirate Fluid at a Glance

Simple Summary

Nipple aspirate fluid (NAF) is a promising source of markers for detection of breast cancer. NAF can be acquired via the nipple by aspiration using a suction device, which is well tolerated by women. Future possible applications of biomarkers for breast cancer derived from NAF could be (1) as a detection tool to identify the initiation of the cancer development process, (2) as an additional tool next to imaging (mammography and breast magnetic resonance imaging) or (3) as a replacement tool for when imaging is not advisable for women, such as during pregnancy and breastfeeding. With this paper, we present a narrative review and perspectives of NAF research at a glance.

Abstract

Nipple aspirate fluid (NAF) is an intraductal mammary fluid that, because of its close proximity to and origin from the tissue from which breast cancer originates, is a promising source of biomarkers for early breast cancer detection. NAF can be non-invasively acquired via the nipple by aspiration using a suction device; using oxytocin nasal spray helps increase yield and tolerability. The aspiration procedure is generally experienced as more tolerable than the currently used breast imaging techniques mammography and breast magnetic resonance imaging. Future applications of NAF-derived biomarkers include their use as a tool in the detection of breast carcinogenesis at its earliest stage (before a tumor mass can be seen by imaging), or as a supporting diagnostic tool for imaging, such as when imaging is less reliable (to rule out false positives from imaging) or when imaging is not advisable (such as during pregnancy and breastfeeding). Ongoing clinical studies using NAF samples will likely shed light on NAF’s content and clinical potential. Here, we present a narrative review and perspectives of NAF research at a glance.

Online μSEC2-nRPLC-MS for Improved Sensitivity of Intact Protein Detection of IEF-Separated Nonhuman Primate Cerebrospinal Fluid Proteins

Proteoform-resolved information, obtained by top-down (TD) "intact protein" proteomics, is expected to contribute substantially to the understanding of molecular pathogenic mechanisms and, in turn, identify novel therapeutic and diagnostic targets. However, the robustness of mass spectrometry (MS) analysis of intact proteins in complex biological samples is hindered by the high dynamic range in protein concentration and mass, protein instability, and buffer complexity. Here, we describe an evolutionary step for intact protein investigations through the online implementation of tandem microflow size-exclusion chromatography with nanoflow reversed-phase liquid chromatography and MS (μSEC2-nRPLC-MS). Online serial high-/low-pass SEC filtration overcomes the aforementioned hurdles to intact proteomic analysis through automated sample desalting/cleanup and enrichment of target mass ranges (5-155 kDa) prior to nRPLC-MS. The coupling of μSEC to nRPLC is achieved through a novel injection volume control (IVC) strategy of inserting protein trap columns, pre- and post-μSEC columns, to enable injection of dilute samples in high volumes without loss of sensitivity or resolution. Critical characteristics of the approach are tested via rigorous investigations on samples of varied complexity and chemical background. Application of the platform to cerebrospinal fluid (CSF) prefractionated by OFFGEL isoelectric focusing drastically increases the number of intact mass tags (IMTs) detected within the target mass range (5-30 kDa) in comparison to one-dimensional nRPLC-MS with approximately 100× less CSF than previous OFFGEL studies. Furthermore, the modular design of the μSEC2-nRPLC-MS platform is robust and promises significant flexibility for large-scale TDMS analysis of diverse samples either directly or in concert with other multidimensional fractionation steps.

Protein biomarkers in serum as a conservation tool to assess reproduction: a case study on brown bears (Ursus arctos)

Monitoring the reproductive characteristics of a species can complement existing conservation strategies by understanding the mechanisms underlying demography. However, methodology to determine important aspects of female reproductive biology is often absent in monitoring programs for large mammals. Protein biomarkers may be a useful tool to detect physiological changes that are indicative of reproductive state. This study aimed to identify protein biomarkers of reproductive status in serum collected from free-ranging female brown bears (Ursus arctos) in Alberta, Canada, from 2001 to 2018. We hypothesized that the expression of proteins related to reproduction in addition to energetics and stress can be used to answer specific management-focused questions: (i) identify when a female is pregnant, (ii) detect if a female is lactating, (iii) determine age of sexual maturity (i.e. primiparity) and (iv) assess female fertility (i.e. reproduction rate). Furthermore, we investigated if silver spoon effects (favourable early life conditions provide fitness benefits through adulthood) could be determined using protein expression. A target panel of 19 proteins with established relationships to physiological function was measured by peptide-based analysis using liquid chromatography and multiple reaction monitoring mass spectrometry and their differential expression was evaluated using a Wilcoxon signed-rank test. We found biomarkers of pregnancy (apolipoprotein B-100 and afamin), lactation (apolipoprotein B-100 and alpha-2-macroglobulin) and sexual maturity (corticosteroid-binding globulin), but there were no statistically significant relationships with protein expression and fertility. The expression of proteins related to reproduction (afamin) and energetics (vitamin-D binding protein) was associated with the nutritional quality of the individual's present habitat rather than their early life habitat. This study highlights potential biomarkers of reproductive status and provides additional methods for monitoring physiological function in wildlife to inform conservation.

Development of molecular tools for diagnosis of Alzheimer's disease that are based on detection of amyloidogenic proteins

Alzheimer's disease (AD) is the most common form of dementia that usually occurs among older people. AD results from neuronal degeneration that leads to the cognitive impairment and death. AD is incurable, typically develops over the course of many years and is accompanied by a loss of functional autonomy, making a patient completely dependent on family members and/or healthcare workers. Critical features of AD are pathological polymerization of Aβ peptide and microtubule-associated protein tau, accompanied by alterations of their conformations and resulting in accumulation of cross-β fibrils (amyloids) in human brains. AD apparently progresses asymptomatically for years or even decades before the appearance of symptoms. Therefore, development of the early AD diagnosis at a pre-symptomatic stage is essential for potential therapies. This review is focused on current and potential molecular tools (including non-invasive methods) that are based on detection of amyloidogenic proteins and can be applicable to early diagnosis of AD.Abbreviations: Aβ - amyloid-β peptide; AβO - amyloid-β oligomers; AD - Alzheimer's disease; ADRDA - Alzheimer's Disease and Related Disorders Association; APH1 - anterior pharynx defective 1; APP - amyloid precursor protein; BACE1 - β-site APP-cleaving enzyme 1; BBB - brain blood barrier; CJD - Creutzfeldt-Jakob disease; CRM - certified reference material; CSF - cerebrospinal fluid; ELISA - enzyme-linked immunosorbent assay; FGD - 18F-fluorodesoxyglucose (2-deoxy-2-[18F]fluoro-D-glucose); IP-MS - immunoprecipitation-mass spectrometry assay; MCI - mild cognitive impairment; MDS - multimer detection system; MRI - magnetic resonance imaging; NIA-AA - National Institute on Ageing and Alzheimer's Association; NINCDS - National Institute of Neurological and Communicative Disorders and Stroke; PEN2 - presenilin enhancer 2; PET - positron emission tomography; PiB - Pittsburgh Compound B; PiB-SUVR - PIB standardized uptake value ratio; PMCA - Protein Misfolding Cycling Amplification; PrP - Prion Protein; P-tau - hyperphosphorylated tau protein; RMP - reference measurement procedure; RT-QuIC - real-time quaking-induced conversion; SiMoA - single-molecule array; ThT - thioflavin T; TSEs - Transmissible Spongiform Encephslopathies; T-tau - total tau protein.

Noninvasive urine metabolomics of prostate cancer and its therapeutic approaches: a current scenario and future perspective

INTRODUCTION

The sensitive, specific, fast, robust and noninvasive biomarkers for the evaluation of prostate cancer (PC) remain elusive in medical research. However, efforts are in full sway to investigate and resolve these puzzles for clinical practice. Advances in modern analytical techniques, sample processing, and the emergence of multiple omics approaches have created a great hope for the development of better detection modalities for PC. The objective of the present review is to provide a concise overview of the PC metabolomics-based potential discriminating molecules in urine samples using nuclear magnetic resonance spectroscopy and mass spectrometry.

AREA COVERED

A literature search was executed to find the studies reporting the noninvasive urine-based biomarkers for the diagnosis and prognosis of underlying disease. Most studies have extensivelyreported PC discriminating molecules with their respective controls. Additionally, pathophysiology and the treatment paradigm of PC are summarized and related to the insights underpinning the therapeutic intervention of PC.

EXPERT OPINION

With multi-centric, global, comprehensive omics approaches via either a non- or least-invasive bio-matrix may open new avenues of research for PC biomarker discovery, backed by a molecular mechanistic outline.

HBFP: a new repository for human body fluid proteome

Body fluid proteome has been intensively studied as a primary source for disease biomarker discovery. Using advanced proteomics technologies, early research success has resulted in increasingly accumulated proteins detected in different body fluids, among which many are promising biomarkers. However, despite a handful of small-scale and specific data resources, current research is clearly lacking effort compiling published body fluid proteins into a centralized and sustainable repository that can provide users with systematic analytic tools. In this study, we developed a new database of human body fluid proteome (HBFP) that focuses on experimentally validated proteome in 17 types of human body fluids. The current database archives 11 827 unique proteins reported by 164 scientific publications, with a maximal false discovery rate of 0.01 on both the peptide and protein levels since 2001, and enables users to query, analyze and download protein entries with respect to each body fluid. Three unique features of this new system include the following: (i) the protein annotation page includes detailed abundance information based on relative qualitative measures of peptides reported in the original references, (ii) a new score is calculated on each reported protein to indicate the discovery confidence and (iii) HBFP catalogs 7354 proteins with at least two non-nested uniquely mapping peptides of nine amino acids according to the Human Proteome Project Data Interpretation Guidelines, while the remaining 4473 proteins have more than two unique peptides without given sequence information. As an important resource for human protein secretome, we anticipate that this new HBFP database can be a powerful tool that facilitates research in clinical proteomics and biomarker discovery.

Database URL:https://bmbl.bmi.osumc.edu/HBFP/