Urinary extracellular vesicles for biomarker source to monitor polycystic kidney disease

Extracellular vesicles (EVs) are bilayered lipid vesicles, 50–1000 nm in diameter and secreted by most types of cells. They contain many proteins, mRNAs, miRNAs, and lipids that reflect the pathophysiological state of the cells they originate from, and are therefore considered to be a rich source of potential biomarkers. In this issue (Pocsfalvi, G. et al., Proteomics Clin. Appl. 2015, 9, 552–567), Pocsfalvi et al. conducted pioneering investigations to determine whether changes in the protein content of EVs occur during progression of autosomal dominant polycystic kidney disease (ADPKD), a common genetic disorder that predominantly affects the kidneys. Most significantly, iTRAQ-based quantitative proteomics showed that cytoskeleton-regulating and Ca²⁺-binding proteins are differentially expressed in urinary EVs of ADPKD patients. Impressively, these proteins are involved in biological processes that are closely related to the pathogenic state of tubular epithelial cells in ADPKD, demonstrating the possibility to monitor the status of patients using urinary EVs.     

Proteomics is not only a biomarker discovery tool

The relatively young science of proteomics has been extensively used to identify biomarkers. However, a detailed and careful interpretation of proteomics data can also provide a clear picture of integrated biochemical systems, which can lead to a better comprehension of pathological processes. For example, the proteome analysis of human brain tissue from patients with schizophrenia, bipolar disorder, or multiple sclerosis compared with healthy controls has identified differentially expressed proteins that may not only be potential biomarkers but may also provide information that may increase the comprehension of these neurological disorders. Thus, proteomics is not only a biomarker discovery tool but can also identify potential players of relevance for diseases.     

MS‐Based Biomarker Discovery in Bronchoalveolar Lavage Fluid for Lung Cancer

Bronchoalveolar lavage fluid (BALF) is a lung fluid. BALF is extracted from the lungs by a bronchoscope. The first step is to instill saline liquid into the lungs followed by extraction. The extracted liquid is depleted from cells by low spin centrifugation. The biochemical content of BALF is mainly composed of phospholipids and proteins and to less extent nucleic acids (DNA, miRNA, mRNA). The proteins, mRNAs, miRNAs, and lipids mirror the pathophysiological state of the patient and are consequently regarded as a rich source of biomarkers with already some examples of established clinical applications. Recently, in Proteomics Clin. Appl. 2019 , 13, 1900028, Sim et al. established a novel MS‐based proteomics protocol for BALF lung cancer sample analysis by combining antibody‐based depletion of high abundant BALF proteins, high pH peptide fractionation, and label free quantitation on a high resolution Orbitrap Fusion instrument. They demonstrate an improvement in BALF sample coverage compared with some previous published methodologies. Notably, the result from the study supports the hypothesis that BALF more than serum reflects the lung cancer proteome and for this reason is a promising source for lung cancer biomarkers.     

Quantification of Biomarker Proteins Using Reverse‐Phase Protein Arrays

It is expected that antibody‐based proteomics will soon occupy a pivotal position in the discovery and validation of biomarkers and therapeutic targets. The reverse‐phase protein array (RPPA) is an antibody‐based proteomic method that can quantify the expression of multiple posttranslationally modified proteins (such as those that have been phosphorylated) across a large number of protein samples. RPPA is highly sensitive and requires only very small protein samples. This feature, in combination with large antibody libraries, makes RPPA ideal for clinical proteomics, as well as the fact that it is an expandable multiplex assay. In Volume 14, Issue 1 of Proteomics Clinical Applications, Suzuki and colleagues report for the first time a study comparing RPPA and immunohistochemistry for quantification of seven biomarker proteins used for subtyping of diffuse large B‐cell lymphoma. Such combination of multiple biomarkers is likely to increase diagnostic accuracy and can be used for precise classification of this heterogeneous disease.     

Application of proteomic techniques to the study of urine and renal tissue

The increasing application of proteomic methods to biomedical research is providing us with important new information; it holds particular promise in advancing basic and clinical renal research, but whether proteomics can ever become a routine diagnostic tool in nephrology is still uncertain. Currently, proteomic techniques are used by many groups in the search for "biomarkers" of disease, especially kidney disease, because of the ready availability of urine as an "end-product" of renal function. However, the question as to whether any disease-specific biomarkers exist or can be identified by proteomics is also uncertain. A growing application of proteomics in biomedical research is to understand the mechanism(s) of disease. This brief review is selective; in it we consider examples of proteomic studies of human urine for biomarkers, others that have explored renal physiology, and still others that have begun to probe the proteome of organelles. No single approach is sufficiently comprehensive, and the pooled application of proteomics to renal research will undoubtedly improve our understanding of renal function and enable us to explore in more detail subcellular structures, and to characterize cellular processes at the molecular level. When combined with other techniques in renal research, proteomics, and related analytical methods could prove indispensable in modeling renal function, and perhaps also in diagnosis and management of renal disease.     

Sera proteomic biomarker profiling in HIV-1 infected subjects with cognitive impairment

HIV-1 infection of the brain commonly leads to cognitive impairments (CIs). In its most severe form, HIV-1 associated dementia (HAD) is associated with advanced immune suppression and debilitating loss of memory, behavioral, and motor functions. Despite significant research activities, diagnosis remains one of exclusion. Bioimaging, neuropsychological testing, and viral and immune biomarkers serve to support but not define a diagnosis of HIV-1 associated CI. This is timely and required as brain injury triggered by HIV-1 can be controlled, in part, by antiretroviral medicines. The recent development of proteomics has opened new ways to study viral-host interactions which may provide new insight into treatment and disease monitoring. To this end, we developed a proteomics platform for HIV-1 associated CI biomarker discovery and used it to perform a pilot study for sera-associated HAD proteins. A 2-DE map of a serum proteome was focused on differentially expressed proteins. Differential expression of two proteins was validated by Western blot tests identifying afamin and ceruloplasmin as a potential biomarkers for CI associated with advanced HIV-1 infection.     

Proteomics studies of pancreatic cancer

Pancreatic cancer is the fourth leading cause of cancer death in the United States, with 4% survival 5 years after diagnosis. Biomarkers are desperately needed to improve earlier, more curable cancer diagnosis and to develop new effective therapeutic targets. The development of quantitative proteomics technologies in recent years offers great promise for understanding the complex molecular events of tumorigenesis at the protein level, and has stimulated great interest in applying the technology for pancreatic cancer studies. Proteomic studies of pancreatic tissues, juice, serum/plasma, and cell lines have recently attempted to identify differentially expressed proteins in pancreatic cancer to dissect the abnormal signaling pathways underlying oncogenesis, and to detect new biomarkers. It can be expected that the continuing evolution of proteomics technology with better resolution and sensitivity will greatly enhance our capability in combating pancreatic cancer.     

Proteomics in the Diagnosis of Endometriosis: Opportunities and Challenges

The non‐surgical diagnosis of endometriosis is still challenging for the clinician. Ultrasonography and magnetic resonance imaging can be used to diagnose ovarian endometriotic cysts and deep infiltrating endometriosis; but their performance is poor in the diagnosis of initial stages of endometriosis. CA‐125 and other serum markers (such as CA 19‐9, serum protein PP14, interleukins, and angiogenetic factors) have been measured in women with endometriosis but they are not reliable for the diagnosis of the disease. Although several studies used proteomics technologies to identify plasmatic markers of endometriosis, the non‐invasive diagnosis of endometriosis is far from being achieved. In this issue, Manousopoulou et al. compare the integrated quantitative proteomic profile of eutopic endometrium and serum of women with endometriosis and controls. 1214 proteins are differentially expressed in the eutopic endometrium and 404 proteins in the serum of the two study groups. 21 proteins are aberrantly expressed in both eutopic endometrium and serum of women with endometriosis. More work is needed to assess if the differentially expressed proteins identified in this study can be used as clinical markers of endometriosis.     

How can proteomics elucidate the complexity of multiple sclerosis?

Multiple sclerosis affects more than 2.5 million people worldwide. Although multiple sclerosis was described almost 150 years ago, there are many knowledge gaps regarding its etiology, diagnosis, prognosis, and pathogenesis. Multiple sclerosis is an inflammatory, demyelinating, neurodegenerative disease of the CNS. During the last several decades, experimental models of multiple sclerosis have contributed to our understanding of the inflammatory disease mechanisms and have aided drug testing and development. However, little is known about the neurodegenerative mechanisms that operate during the evolution of the disease. Currently, all therapeutic approaches are primarily based on the inflammatory aspect of the disease. During the last decade, proteomics has emerged as a promising tool for revealing molecular pathways as well as identifying and quantifying differentially expressed proteins. Therefore, proteomics may be used for the discovery of biomarkers, potential drug targets, and new regulatory mechanisms. To date, a considerable number of proteomics studies have been conducted on samples from experimental models and patients with multiple sclerosis. These data form a solid base for further careful analysis and validation.     

Differential expression of serum/plasma proteins in various infectious diseases: Specific or nonspecific signatures

Apart from direct detection of the infecting organisms or biomarker of the pathogen itself, surrogate host markers are also useful for sensitive and early diagnosis of pathogenic infections. Early detection of pathogenic infections, discrimination among closely related diseases with overlapping clinical manifestations, and monitoring of disease progression can be achieved by analyzing blood biomarkers. Therefore, over the last decade large numbers of proteomics studies have been conducted to identify differentially expressed human serum/plasma proteins in different infectious diseases with the intent of discovering novel potential diagnostic/prognostic biomarkers. However, in-depth review of the literature indicates that many reported biomarkers are altered in the same way in multiple infectious diseases, regardless of the type of infection. This might be a consequence of generic acute phase reactions, while the uniquely modulated candidates in different pathogenic infections could be indicators of some specific responses. In this review article, we will provide a comprehensive analysis of differentially expressed serum/plasma proteins in various infectious diseases and categorize the protein markers associated with generic or specific responses. The challenges associated with the discovery, validation, and translational phases of serum/plasma biomarker establishment are also discussed.     

Proteomics and Protein Adsorption on Hemodialysis Membranes

Adsorption of plasma proteins onto the membrane surface during the hemodialysis session represents a key feature of membranes used for chronic dialysis therapy. In this issue of Proteomics—Clinical Applications, Han et al. originally describe how, by using proteomic technologies, the adsorptive properties of two membranes made from the same biomaterial (Polyamix) may have different flux characteristics (low flux and high flux, the former having smaller pore size). A total of 497 differentially expressed proteins were identified in eluates obtained after in vivo hemodialysis: 320 proteins concentrated more in low‐flux membrane (predominantly proteins with molecular weight 30–60 kDa) and 177 in high flux (most represented by proteins with molecular weight 10–15 kDa). Use of bioinformatics tools shed light on the involvement of adsorbed proteins in important biological pathways, such as the coagulation cascade and the complement system, again with some differences between the two membranes. The study indicates that flux characteristics of a biomaterial used for hemodialysis membrane strongly influence its adsorptive properties, and that proteomic application may provide information relevant to renal replacement therapy.     

Discovery of putative oocyte quality markers by comparative ExacTag proteomics

Purpose: Identification of the biomarkers of oocyte quality, and developmental and reprogramming potential is of importance to assisted reproductive technology in humans and animals. Experimental design: PerkinElmer ExacTag? Kit was used to label differentially proteins in pig oocyte extracts (oocyte proteome) and pig oocyte‐conditioned in vitro maturation media (oocyte secretome) obtained with high‐ and low‐quality oocytes. Results: We identified 16 major proteins in the oocyte proteome that were expressed differentially in high‐ versus low‐quality oocytes. More abundant proteins in the high‐quality oocyte proteome included kelch‐like ECH‐associated protein 1 (an adaptor for ubiquitin‐ligase CUL3), nuclear export factor CRM1 and ataxia‐telangiectasia mutated protein kinase. Dystrophin (DMD) was more abundant in low‐quality oocytes. In the secretome, we identified 110 proteins, including DMD and cystic fibrosis transmembrane conductance regulator, two proteins implicated in muscular dystrophy and cystic fibrosis, respectively. Monoubiquitin was identified in the low‐quality‐oocyte secretome. Conclusions and clinical implications: A direct, quantitative proteomic analysis of small oocyte protein samples can identify potential markers of oocyte quality without the need for a large amount of total protein. This approach will be applied to discovery of non‐invasive biomarkers of oocyte quality in assisted human reproduction and in large animal embryo transfer programs.     

Position of helical kinks in membrane protein crystal structures and the accuracy of computational prediction

The structural features of helical transmembrane (TM) proteins, such as helical kinks, tilts, and rotational orientations are important in modulation of their function and these structural features give rise to functional diversity in membrane proteins with similar topology. In particular, the helical kinks caused by breaking of the backbone hydrogen bonds lead to hinge bending flexibility in these helices. Therefore it is important to understand the nature of the helical kinks and to be able to reproduce these kinks in structural models of membrane proteins. We have analyzed the position and extent of helical kinks in the transmembrane helices of all the crystal structures of membrane proteins taken from the MPtopo database, which are about 405 individual helices of length between 19 and 35 residues. 44% of the crystal structures of TM helices showed a significant helical kink, and 35% of these kinks are caused by prolines. Many of the non-proline helical kinks are caused by other residues like Ser and Gly that are located at the center of helical kinks. The side chain of Ser makes a hydrogen bond with the main chain carbonyl of the i − 4th or i + 4th residue thus making a kink. We have also studied how well molecular dynamics (MD) simulations on isolated helices can reproduce the position of the helical kinks in TM helices. Such a method is useful for structure prediction of membrane proteins. We performed MD simulations, starting from a canonical helix for the 405 TM helices. 1 ns of MD simulation results show that we can reproduce about 79% of the proline kinks, only 59% of the vestigial proline kinks and 18% of the non-proline helical kinks. We found that similar results can be obtained from choosing the lowest potential energy structure from the MD simulation. 4–14% more of the vestigial prolines were reproduced by replacing them with prolines before performing MD simulations, and changing the amino acid back to proline after the MD simulations. From these results we conclude that the position of the helical kinks is dependent on the TM sequence. However the extent of helical kinking may depend on the packing of the rest of the protein and the lipid bilayer.     

On Bases of BCH Codes with Designed Distance 3 and Their Extensions

We consider narrow-sense BCH codes of length p^m ? 1 over \({{\mathbb{F}}}_{p}\), m ≥ 3. We prove that neither such a code with designed distance δ = 3 nor its extension for p ≥ 5 is generated by the set of its codewords of the minimum nonzero weight. We establish that extended BCH codes with designed distance δ = 3 for p ≥ 3 are generated by the set of codewords of weight 5, where basis vectors can be chosen from affine orbits of some codewords.

     

Sub-proteome approach to the knowledge of liver

In the recent years, global proteomics approaches have been widely used to characterize a number of tissue proteomes including plasma and liver; however, the elevated complexity of these samples in combination with the high abundance of some specific proteins make the study of the lowest abundant proteins difficult. This review is focused on different strategies that have been developed to extend the proteome focused on these two tissues, as, for example, the analysis of sub-cellular proteomes. In this regard, two special kind of extracellular vesicles--exosomes and membrane plasma shedding vesicles--are emerging as excellent biological source both to extend the liver and plasma proteomes and to be applied in the discovery of non-invasive liver-specific disease biomarkers.     

Reduced Basis Techniques for Stochastic Problems

We report here on the recent application of a now classical general reduction technique, the Reduced-Basis (RB) approach initiated by C. Prud’homme et al. in J. Fluids Eng. 124(1), 70–80, 2002, to the specific context of differential equations with random coefficients. After an elementary presentation of the approach, we review two contributions of the authors: in Comput. Methods Appl. Mech. Eng. 198(41–44), 3187–3206, 2009, which presents the application of the RB approach for the discretization of a simple second order elliptic equation supplied with a random boundary condition, and in Commun. Math. Sci., 2009, which uses a RB type approach to reduce the variance in the Monte-Carlo simulation of a stochastic differential equation. We conclude the review with some general comments and also discuss possible tracks for further research in the direction.     

Comparative proteomic analysis of differentially expressed proteins in an in vitro cellular carcinogenesis model of oral squamous cell carcinoma

In vitro cellular model is an important tool to be used to investigate the cellular events related to pathophysiological conditions in humans. We have developed an in vitro cellular carcinogenesis model of oral squamous cell carcinoma (OSCC). In this study, we performed comparative proteomic analysis using 2‐DE and LC‐tandem mass chromatography to separate and identify differentially expressed proteins. Forty‐five proteins were identified, including 24 proteins with decreased expression and 19 proteins with increased expression during carcinogenesis from immortalized oral epithelial cells to squamous cancerous cells. The identified known proteins were classified into three ontologies of cellular component, molecular function, and biological process. Further validation of five identified proteins (ANXA1, ANXA2, CTSB, KRT17, and S100A6) in the cellular carcinogenesis model and cancerous tissues from OSCC patients confirmed the comparative proteomic results. Moreover, Annexin A1 and A2 expression levels correlated with the pathological differentiation grade of cancerous tissues. Thus, this work provides a dynamic protein file of differentially expressed proteins in oral squamous carcinoma cells, which could provide clues to study the mechanisms of OSCC carcinogenesis and possibly be developed as potential biomarkers for clinical diagnosis or prognostic monitoring.     

Vitreous humor in the pathologic scope: Insights from proteomic approaches

The vitreous humor (VH) is the largest component of the eye. It is a colorless, gelatinous, highly hydrated matrix that fills the posterior segment of the eye between the lens and retina in vertebrates. In VH, a diversity of proteins that can influence retinal physiology is present, including growth factors, hormones, proteins with transporter activity, and enzymes. More importantly, the protein composition of VH has been described as being altered in a number of disease states. Therefore, attempts aiming at establishing a map of VH proteins and detecting putative biomarkers for ocular illness or protein fluctuations with putative physiologic significance were conducted over the last two decades, using proteomic approaches. Proteomic strategies often involve gel-based or LC techniques as sample fractioning approaches, subsequently coupled with MS procedures. This set of studies resulted in the proteomic characterization of a range of ocular disease samples, with particular incidence on diabetic retinopathy. However, practical therapeutic applications arising from these studies are scarce at the moment. A pertinent example of therapeutic targets arising from VH proteomics has emerged concerning vasoproliferative factors present in the vitreous, which should be involved in neovascularization and subsequent fibrovascular proliferation of the retina, in ocular disease context. Therefore, this review attempts to sum up the information acquired from the proteomic approaches to ocular disease conducted in VH samples, highlighting its clinical potential for disclosing ocular disease mechanisms and engendering pharmacological therapeutic treatments.