Proteomic applications in identifying protein-protein interactions.

There are many things that can be used to characterize a protein. Size, isoelectric point, hydrophobicity, structure (primary to quaternary), and subcellular location are just a few parameters that are used. The most important feature of a protein, however, is its function. While there are many experiments that can indicate a protein's role, identifying the molecules it interacts with is probably the most definitive way of determining its function. Owing to technology limitations, protein interactions have historically been identified on a one molecule per experiment basis. The advent of high throughput multiplexed proteomic technologies in the 1990s, however, made identifying hundreds and thousands of proteins interactions within single experiments feasible. These proteomic technologies have dramatically increased the rate at which protein-protein interactions (PPIs) are discovered. While the improvement in mass spectrometry technology was an early driving force in the rapid pace of identifying PPIs, advances in sample preparation and chromatography have recently been propelling the field. In this chapter, we will discuss the importance of identifying PPIs and describe current state-of-the-art technologies that demonstrate what is currently possible in this important area of biological research.

Huntington's Disease Drug Development: A Phase 3 Pipeline Analysis.

Huntington's Disease (HD) is a severely debilitating neurodegenerative disorder in which sufferers exhibit different combinations of movement disorders, dementia, and behavioral or psychiatric abnormalities. The disorder is a result of a trinucleotide repeat expansion mutation that is inherited in an autosomal dominant manner. While there is currently no treatment to alter the course of HD, there are medications that lessen abnormal movement and psychiatric symptoms. ClinicalTrials.gov was searched to identify drugs that are currently in or have completed phase III drug trials for the treatment of HD. The described phase III trials were further limited to interventional studies that were recruiting, active not recruiting, or completed. In addition, all studies must have posted an update within the past year. PubMed was used to gather further information on these interventional studies. Of the nine clinical trials that met these criteria, eight involved the following drugs: metformin, dextromethorphan/quinidine, deutetrabenazine, valbenazine, Cellavita HD, pridopidine, SAGE-718, and RO7234292 (RG6042). Of these drug treatments, four are already FDA approved. This systematic review provides a resource that summarizes the present therapies for treating this devastating condition that are currently in phase III clinical trials in the United States.

Biomarker Analysis of Formalin-Fixed Paraffin-Embedded Clinical Tissues Using Proteomics.

The relatively recent developments in mass spectrometry (MS) have provided novel opportunities for this technology to impact modern medicine. One of those opportunities is in biomarker discovery and diagnostics. Key developments in sample preparation have enabled a greater range of clinical samples to be characterized at a deeper level using MS. While most of these developments have focused on blood, tissues have also been an important resource. Fresh tissues, however, are difficult to obtain for research purposes and require significant resources for long-term storage. There are millions of archived formalin-fixed paraffin-embedded (FFPE) tissues within pathology departments worldwide representing every possible tissue type including tumors that are rare or very small. Owing to the chemical technique used to preserve FFPE tissues, they were considered intractable to many newer proteomics techniques and primarily only useful for immunohistochemistry. In the past couple of decades, however, researchers have been able to develop methods to extract proteins from FFPE tissues in a form making them analyzable using state-of-the-art technologies such as MS and protein arrays. This review will discuss the history of these developments and provide examples of how they are currently being used to identify biomarkers and diagnose diseases such as cancer.

Quantitative analysis of specific androgens in serum and urine samples from male, pre, and postmenopausal subjects using LC-MRM-MS.

Androgens are endogenous hormones that play a crucial role in the paracrine and intracrine hormone system to perform and maintain vital physiological functions. Altered levels of androgens are implicated in many diseases such as sexual dysregulation, breast cancer, prostate cancer, and heart diseases etc. In this manuscript we describe a liquid chromatography-mass spectrometry (LC-MS) method using multiple reaction monitoring (MRM) for quantitatively measuring specific androgens such as dehydroepiandrosterone, testosterone, androsterone sulphate, androstenedione, and dihydrotestosterone in serum and urine samples. Serum acquired from nine different subjects (three pre-menopausal women, three postmenopausal women, and three healthy males) were used to evaluate the developed methods. In the sample preparation methods for serum either protein precipitation or liquid-liquid extraction (LLE) was used while the analysis of urinary androgens used LLE. The extracted androgens were quantitatively measured using LC-MRM-MS to which known amounts of stable isotope labeled standards were added. This manuscript also presents a LC-MRM-MS method mode for the analysis of oxime derivatized androgens potentially to enhance the sensitivity of the assay if required, from urine and venous-drawn serum samples.

Omics in Systems Biology: Current Progress and Future Outlook.

Biological research has undergone tremendous changes over the past three decades. Research used to almost exclusively focus on a single aspect of a single molecule per experiment. Modern technologies have enabled thousands of molecules to be simultaneously analyzed and the way that these molecules influence each other to be discerned. The change is so dramatic that it has given rise to a whole new descriptive suffix (i.e., omics) to describe these fields of study. While genomics was arguably the initial driver of this new trend, it quickly spread to other biological entities resulting in the creation of transcriptomics, proteomics, metabolomics, etc. The development of these "big four omics" created a wave of other omic fields, such as epigenomics, glycomics, lipidomics, microbiomics, and even foodomics; all with the purpose of comprehensively studying all the molecular entities or processes within their respective domain. The large number of omic fields that are invented even led to the term "panomics" as a way to classify them all under one category. Ultimately, all of these omic fields are setting the foundation for developing systems biology; in which the focus will be on determining the complex interactions that occur within biological systems.

Mass Spectrometry Techniques: Principles and Practices for Quantitative Proteomics.

In the current omics-age of research, major developments have been made in technologies that attempt to survey the entire repertoire of genes, transcripts, proteins, and metabolites present within a cell. While genomics has led to a dramatic increase in our understanding of such things as disease morphology and how organisms respond to medications, it is critical to obtain information at the proteome level since proteins carry out most of the functions within the cell. The primary tool for obtaining proteome-wide information on proteins within the cell is mass spectrometry (MS). While it has historically been associated with the protein identification, developments over the past couple of decades have made MS a robust technology for protein quantitation as well. Identifying quantitative changes in proteomes is complicated by its dynamic nature and the inability of any technique to guarantee complete coverage of every protein within a proteome sample. Fortunately, the combined development of sample preparation and MS methods have made it capable of quantitatively comparing many thousands of proteins obtained from cells and organisms.

Characterization of Phosphorylated Proteins Using Mass Spectrometry.

Phosphorylation is arguably the most important post-translational modification that occurs within proteins. Phosphorylation is used as a signal to control numerous physiological activities ranging from gene expression to metabolism. Identifying phosphorylation sites within proteins was historically a challenge as it required either radioisotope labeling or the use of phospho-specific antibodies. The advent of mass spectrometry (MS) has had a major impact on the ability to qualitatively and quantitatively characterize phosphorylated proteins. In this article, we describe MS methods for characterizing phosphorylation sites within individual proteins as well as entire proteome samples. The utility of these methods is illustrated in examples that show the information that can be gained using these MS techniques.

LC-MS-sMRM method development and validation of different classes of pain panel drugs and analysis of clinical urine samples.

Urine drug testing (UDT) is an important analytical/bio-analytical technique that has inevitably become an integral and vital part of a testing programme for diagnostic purposes. This manuscript presents a tailor-made LC-MS/MS quantitative assay method development and validation for a custom group of 33 pain panel drugs and their metabolites belonging to different classes (opiates, opioids, benzodiazepines, illicit, amphetamines, etc.) that are prescribed in pain management and depressant therapies. The LC-MS/MS method incorporates two experiments to enhance the sensitivity of the assay and has a run time of about 7 minutes with no prior purification of the samples required and a flow rate of 0.7 mL/min. The method also includes the second-stage metabolites for some drugs that belong to different classes but have first-stage similar metabolic pathways that will enable to correctly identify the right drug or to flag the drug that might be due to specimen tampering. Some real case examples and difficulties in peak picking were provided with some of the analytes in subject samples. Finally, the method was deliberated with some randomly selected de-identified clinical subject samples, and the data evaluated from "direct dilute and shoot analysis" and after "glucuronide hydrolysis" were compared. This method is now used to run routinely more than 100 clinical subject samples on a daily basis.

Preparation of the Low Molecular Weight Serum Proteome for Mass Spectrometry Analysis.

The ability to cure or manage many diseases is highly dependent on the ability to correctly diagnose them at the earliest possible stage. Diagnosis relies heavily on biomarkers whether these be visual symptoms or molecules found within samples acquired from the patient. For conditions that lack useful biomarkers, researchers are often faced with the task of sifting through very complex biological samples (i.e., serum, plasma, urine, tissue, cells, etc.) with the hope of discovering a small number of molecules that are exquisitely diagnostic for the condition of interest. One discovery strategy that has been frequently used is to fractionate the biological samples being studied into simpler aliquots that can be more easily characterized using existing technologies. One such fractionation method is to isolate a specific portion based on a specific property (i.e., size, phosphorylation state, charge, etc.) of the proteins within the sample. This method provides a simplified sample that can be characterized at a higher coverage level than the complex sample from which it was derived. This chapter details one of these methods, the extraction and analysis of the low molecular weight proteome of human serum.

Integrated proteotranscriptomics of breast cancer reveals globally increased protein-mRNA concordance associated with subtypes and survival.

BACKGROUND: Transcriptome analysis of breast cancer discovered distinct disease subtypes of clinical significance. However, it remains a challenge to define disease biology solely based on gene expression because tumor biology is often the result of protein function. Here, we measured global proteome and transcriptome expression in human breast tumors and adjacent non-cancerous tissue and performed an integrated proteotranscriptomic analysis. METHODS: We applied a quantitative liquid chromatography/mass spectrometry-based proteome analysis using an untargeted approach and analyzed protein extracts from 65 breast tumors and 53 adjacent non-cancerous tissues. Additional gene expression data from Affymetrix Gene Chip Human Gene ST Arrays were available for 59 tumors and 38 non-cancerous tissues in our study. We then applied an integrated analysis of the proteomic and transcriptomic data to examine relationships between them, disease characteristics, and patient survival. Findings were validated in a second dataset using proteome and transcriptome data from "The Cancer Genome Atlas" and the Clinical Proteomic Tumor Analysis Consortium. RESULTS: We found that the proteome describes differences between cancerous and non-cancerous tissues that are not revealed by the transcriptome. The proteome, but not the transcriptome, revealed an activation of infection-related signal pathways in basal-like and triple-negative tumors. We also observed that proteins rather than mRNAs are increased in tumors and show that this observation could be related to shortening of the 3' untranslated region of mRNAs in tumors. The integrated analysis of the two technologies further revealed a global increase in protein-mRNA concordance in tumors. Highly correlated protein-gene pairs were enriched in protein processing and disease metabolic pathways. The increased concordance between transcript and protein levels was additionally associated with aggressive disease, including basal-like/triple-negative tumors, and decreased patient survival. We also uncovered a strong positive association between protein-mRNA concordance and proliferation of tumors. Finally, we observed that protein expression profiles co-segregate with a Myc activation signature and separate breast tumors into two subgroups with different survival outcomes. CONCLUSIONS: Our study provides new insights into the relationship between protein and mRNA expression in breast cancer and shows that an integrated analysis of the proteome and transcriptome has the potential of uncovering novel disease characteristics.

LC-MS-sMRM Method Development and Validation of Different Classes of Pain Panel Drugs and Analysis of Clinical Urine Samples.

Urine Drug Testing (UDT) is an important analytical/bio-analytical technique that has inevitably become an integral and vital part of a testing program for diagnostic purposes. This manuscript presents a tailor-made LC-MS/MS quantitative assay method development and validation for a custom group of 33 pain panel drugs and their metabolites belonging to different classes (opiates, opioids, benzodiazepines, illicit, amphetamines, etc.) that are prescribed in pain management and depressant therapies. The LC-MS/MS method incorporates two experiments to enhance the sensitivity of the assay and has a run time of about 7 min. with no prior purification of the samples required and a flow rate of 0.7 mL/min. The method also includes the second stage metabolites for some drugs that belong to different classes but have first stage similar metabolic pathways that will enable to correctly identify the right drug or to flag the drug that might be due to specimen tampering. Some real case examples and difficulties in peak picking were provided with some of the analytes in subject samples. Finally, the method was deliberated with some randomly selected de-identified clinical subject samples, and the data evaluated from "direct dilute and shoot analysis" and after "glucuronide hydrolysis" were compared. This method is now used to run routinely more than 100 clinical subjects samples on a daily basis. This article is protected by copyright. All rights reserved.

Quantitation of Monophosphorylated Lipid A in the Oil-in-Water Adjuvant Delivery Systems Using Transesterification and GC-MS.

Vaccine delivery systems play pivotal role in effective antigen delivery. These systems often contain adjuvants that stimulate specific immune response and are important for vaccines' efficacy and safety. Oil-in-water vaccine delivery lipid emulsion systems containing monophosphoryl lipid A (MPLA) as immune modulator have been extensively investigated in vaccine trials. Herein, we describe a simple orthogonal method, for quantitative measurement of MPLA in an oil-in-water lipid delivery system using direct transesterification reaction followed by gas-chromatography-mass spectrometry analysis. In this protocol, the transesterification reaction results in the release of fatty acid methyl esters followed by gas-chromatography-mass spectrometry-based targeted quantification of the specific 3-hydroxytetradecanoate fatty acid methyl ester to measure the concentration of MPLA in an oil-in-water lipid emulsion system.

Neuroproteomic tools for battling Alzheimer's disease.

With the life expectancy of individuals in the developed nations reaching historic highs, the incidence of dementia within the aging population is also increasing. Of the known causes of dementia, the major culprit is Alzheimer's disease (AD). The numbers of individuals suffering from AD is expected to nearly triple over the next 35 years unless medical science can identify better methods for diagnosing and treating AD. Fortunately, proteomics technologies have not only rapidly matured in the past few decades but also have been effectively applied so that the biomarkers of AD can be more effectively vetted and analyzed. The effectiveness of the technologies described in this paper enable the efficacy of drugs aimed at treating AD to be tested much faster than the previously possible and enable the more accurate selection of patients that are suitable for clinical trials.

Microfilariae of Brugia malayi Inhibit the mTOR Pathway and Induce Autophagy in Human Dendritic Cells.

Immune modulation is a hallmark of patent filarial infection, including suppression of antigen-presenting cell function and downmodulation of filarial antigen-specific T cell responses. The mammalian target of rapamycin (mTOR) signaling pathway has been implicated in immune regulation, not only by suppressing T cell responses but also by regulating autophagy (through mTOR sensing amino acid availability). Global proteomic analysis (liquid chromatography-tandem mass spectrometry) of microfilaria (mf)-exposed monocyte-derived dendritic cells (DC) indicated that multiple components of the mTOR signaling pathway, including mTOR, eIF4A, and eIF4E, are downregulated by mf, suggesting that mf target this pathway for immune modulation in DC. Utilizing Western blot analysis, we demonstrate that similar to rapamycin (a known mTOR inhibitor), mf downregulate the phosphorylation of mTOR and its regulatory proteins, p70S6K1 and 4E-BP1, a process essential for DC protein synthesis. As active mTOR signaling regulates autophagy, we examined whether mf exposure alters autophagy-associated processes. mf-induced autophagy was reflected in marked upregulation of phosphorylated Beclin 1, known to play an important role in both autophagosome formation and autolysosome fusion, in induction of LC3II, a marker of autophagosome formation, and in induced degradation of p62, a ubiquitin-binding protein that aggregates protein in autophagosomes and is degraded upon autophagy that was reduced significantly by mf exposure and by rapamycin. Together, these results suggest that Brugia malayi mf employ mechanisms of metabolic modulation in DC to influence the regulation of the host immune response by downregulating mTOR signaling, resulting in increased autophagy. Whether this is a result of the parasite-secreted rapamycin homolog is currently under study.

Relation of Serum Estrogen Metabolites with Terminal Duct Lobular Unit Involution Among Women Undergoing Diagnostic Image-Guided Breast Biopsy.

Higher levels of circulating estrogens and estrogen metabolites (EMs) have been associated with higher breast cancer risk. In breast tissues, reduced levels of terminal duct lobular unit (TDLU) involution, as reflected by higher numbers of TDLUs and acini per TDLU, have also been linked to elevated breast cancer risk. However, it is unknown whether reduced TDLU involution mediates the risk associated with circulating EMs. In a cross-sectional analysis of 94 premenopausal and 92 postmenopausal women referred for clinical breast biopsy at an academic facility in Vermont, we examined the associations of 15 EMs, quantified using liquid chromatography-tandem mass spectrometry, with the number of TDLUs and acini count/TDLU using zero-inflated Poisson regression with a robust variance estimator and ordinal logistic regression models, respectively. All analyses were stratified by menopausal status and adjusted for potential confounders. Among premenopausal women, comparing the highest vs. the lowest tertiles, levels of unconjugated estradiol (risk ratio (RR) = 1.74, 95 % confidence interval (CI) = 1.06-2.87, p trend = 0.03), 2-hydroxyestrone (RR = 1.74, 95 % CI = 1.01-3.01, p trend = 0.04), and 4-hydroxyestrone (RR = 1.74, 95 % CI = 0.99-3.06, p trend = 0.04) were associated with significantly higher TDLU count. Among postmenopausal women, higher levels of estradiol (RR = 2.09, 95 % CI = 1.01-4.30, p trend = 0.04) and 16α-hydroxyestrone (RR = 2.27, 95 % CI = 1.29-3.99, p trend = 0.02) were significantly associated with higher TDLU count. Among postmenopausal women, higher levels of EMs, specifically conjugated estrone and 2- and 4-pathway catechols, were also associated with higher acini count/TDLU. Our data suggest that higher levels of serum EMs are generally associated with lower levels of TDLU involution.

Estrogen metabolites in human corpus luteum physiology: differential effects on angiogenic activity.

OBJECTIVE: To determine tissue concentrations of E2, estrone, P, and estrogens metabolites (EMs) 2-methoxyestradiol, 2-methoxyestrone, 4-hydroxyestrone, and 16-ketoestradiol in corpus luteum (CL) of different ages, and after hCG administration; and to examine the effects of EMs on vascular endothelial growth factor (VEGF) secretion and angiogenic activity released by cultured luteinizing granulosa cells in the presence and absence of hCG. DESIGN: Experimental study. SETTING: University. PATIENT(S): Thirty-two healthy women of reproductive age. INTERVENTION(S): Corpus luteum was collected at the time of minilaparotomy for tubal sterilization, at varying stages of the luteal phase (LP). Late-LP CL was collected 24 hours after IM administration of 10,000 IU hCG. Granulosa cells were isolated from follicular aspirates obtained from healthy women participating in our IVF program for male factor infertility. MAIN OUTCOMES MEASURE(S): Estrogen metabolite concentrations were determined in CL tissue, and VEGF was assessed in conditioned medium. The angiogenic activity was analyzed by bioassay. RESULT(S): Concentrations of EMs with proangiogenic activity (16-ketoestradiol and 4-hydroxyestrone) were higher in early and mid-LP CL vs. late-LP CL. These EMs and hCG increased VEGF production and angiogenic activity. Conversely, late-LP CL had significantly higher levels of 2-methoxyestrone and 2-methoxyestradiol, which have antiangiogenic activity. Administration of hCG reduced the production of these EMs. CONCLUSION(S): Our findings suggest that the EMs are important paracrine modulators of CL function. Administration of hCG increases the production of EMs with proangiogenic activity and reduces the secretion of those EMs with antiangiogenic action, suggesting a novel mechanism by which the late-LP CL is rescued in conception cycles.

Identification and Validation of Loa loa Microfilaria-Specific Biomarkers: a Rational Design Approach Using Proteomics and Novel Immunoassays.

UNLABELLED: Immunoassays are currently needed to quantify Loa loa microfilariae (mf). To address this need, we have conducted proteomic and bioinformatic analyses of proteins present in the urine of a Loa mf-infected patient and used this information to identify putative biomarkers produced by L. loa mf. In total, 70 of the 15,444 described putative L. loa proteins were identified. Of these 70, 18 were L. loa mf specific, and 2 of these 18 (LOAG_16297 and LOAG_17808) were biologically immunogenic. We developed novel reverse luciferase immunoprecipitation system (LIPS) immunoassays to quantify these 2 proteins in individual plasma samples. Levels of these 2 proteins in microfilaremic L. loa-infected patients were positively correlated to mf densities in the corresponding blood samples (r = 0.71 and P < 0.0001 for LOAG_16297 and r = 0.61 and P = 0.0002 for LOAG_17808). For LOAG_16297, the levels in plasma were significantly higher in Loa-infected (geometric mean [GM], 0.045 µg/ml) than in uninfected (P < 0.0001), Wuchereria bancrofti-infected (P = 0.0005), and Onchocerca volvulus-infected (P < 0.0001) individuals, whereas for LOAG_17808 protein, they were not significantly different between Loa-infected (GM, 0.123 µg/ml) and uninfected (P = 0.06) and W. bancrofti-infected (P = 0.32) individuals. Moreover, only LOAG_16297 showed clear discriminative ability between L. loa and the other potentially coendemic filariae. Indeed, the specificity of the LOAG_16297 reverse LIPS assay was 96% (with a sensitivity of 77%). Thus, LOAG_16297 is a very promising biomarker that will be exploited in a quantitative point-of-care immunoassay for determination of L. loa mf densities. IMPORTANCE: Loa loa, the causative agent of loiasis, is a parasitic nematode transmitted to humans by the tabanid Chrysops fly. Some individuals infected with L. loa microfilariae (mf) in high densities are known to experience post-ivermectin severe adverse events (SAEs [encephalopathy, coma, or death]). Thus, ivermectin-based mass drug administration (MDA) programs for onchocerciasis and for lymphatic filariasis control have been interrupted in parts of Africa where these filarial infections coexist with L. loa. To allow for implementation of MDA for onchocerciasis and lymphatic filariasis, tools that can accurately identify people at risk of developing post-ivermectin SAEs are needed. Our study, using host-based proteomics in combination with novel immunoassays, identified a single Loa-specific antigen (LOAG_16297) that can be used as a biomarker for the prediction of L. loa mf levels in the blood of infected patients. Therefore, the use of such biomarker could be important in the point-of-care assessment of L. loa mf densities.

Estrogen Metabolism and Risk of Postmenopausal Endometrial and Ovarian Cancer: the B ∼ FIT Cohort.

Estrogen metabolites may have different genotoxic and mitogenic properties yet their relationship with endometrial and ovarian cancer risk remains unclear. Within the Breast and Bone Follow-up to the Fracture Intervention Trial (B ∼ FIT, n = 15,595), we conducted a case-cohort study to evaluate 15 pre-diagnostic serum estrogens and estrogen metabolites with risk of incident endometrial and ovarian cancer among postmenopausal women not on hormone therapy. Participants included 66 endometrial and 67 ovarian cancer cases diagnosed during follow-up (∼ 10 years) and subcohorts of 346 and 416 women, respectively, after relevant exclusions. Serum concentrations were measured by liquid chromatography-tandem mass spectrometry. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated using Cox proportional hazard regression. Exposures were categorized in tertiles (T) and analyzed individually, as metabolic pathways (C-2, -4, or -16) and as ratios to parent estrogens (estradiol, estrone). Estradiol was significantly associated with increased endometrial cancer risk (BMI-adjusted HRT3vsT1 = 4.09, 95% CI 1.70, 9.85; p trend = 0.003). 2-Hydroxyestrone and 16α-hydroxyestrone were not associated with endometrial risk after estradiol adjustment (2-OHE1:HRT3vsT1 = 1.97, 95% CI 0.78, 4.94; 16-OHE1:HRT3vsT1 = 1.50, 95% CI 0.65, 3.46; p trend = 0.16 and 0.36, respectively). Ratios of 2- and 4-pathway catechol-to-methylated estrogens remained positively associated with endometrial cancer after BMI or estradiol adjustment (2-pathway catechols-to-methylated: HRT3vsT1 = 4.02, 95% CI 1.60, 10.1; 4-pathway catechols-to-methylated: HRT3vsT1 = 4.59, 95% CI 1.64, 12.9; p trend = 0.002 for both). Estrogens and estrogen metabolites were not associated with ovarian cancer risk; however, larger studies are needed to better evaluate these relationships. Estrogen metabolism may be important in endometrial carcinogenesis, particularly with less extensive methylation of 2- or 4-pathway catechols associated with elevated endometrial cancer risk.