Proteomics evaluation of five economical commercial abundant protein depletion kits for enrichment of diseases-specific biomarkers from blood serum.

Blood serum is arguably the most analyzed biofluid for disease prediction and diagnosis. Herein, we benchmarked five different serum abundant protein depletion (SAPD) kits with regard to the identification of disease-specific biomarkers in human serum using bottom-up proteomics. As expected, the IgG removal efficiency among the SAPD kits is highly variable, ranging from 70% to 93%. A pairwise comparison of database search results showed a 10%-19% variation in protein identification among the kits. Immunocapturing-based SAPD kits against IgG and albumin outperformed the others in the removal of these two abundant proteins. Conversely, non-antibody-based methods (i.e., kits using ion exchange resins) and kits leveraging a multi-antibody approach were proven to be less efficient in depleting IgG/albumin from samples but led to the highest number of identified peptides. Notably, our results indicate that different cancer biomarkers could be enriched up to 10% depending on the utilized SAPD kit compared with the undepleted sample. Additionally, functional analysis of the bottom-up proteomic results revealed that different SAPD kits enrich distinct disease- and pathway-specific protein sets. Overall, our study emphasizes that a careful selection of the appropriate commercial SAPD kit is crucial for the analysis of disease biomarkers in serum by shotgun proteomics.

Development and Validation of High Performance Liquid Chromatographic Method for Determination of Gentisic Acid and Related Renal Cell Carcinoma Biomarkers in Urine.

A reversed phase liquid chromatographic (RPLC) method was developed to simultaneously detect and quantify creatinine, quinolinic acid, gentisic acid and 4-hydroxybenzoic acid in urine. These four bio-markers are present in relatively high concentrations in urine. Using a 5% methanol in water mobile phase with 0.6% acetic acid and a Zorbax C18 column, baseline resolution for all four biomarkers in synthetic urine was achieved. Better resolution was obtained for the separation of these four compounds when water rich mobile phases were used. Detection of the four biomarkers in urine using the proposed RPLC method is limited by background from the urine matrix for the later eluting compounds and from the dead marker for earlier eluting compounds.

Comparative Seed Proteome Profile Reveals No Alternation of Major Allergens in High-Yielding Mung Bean Cultivars.

Mung bean contains up to 32.6% protein and is one of the great sources of plant-based protein. Because many allergens also function as defense-related proteins, it is important to determine their abundance levels in the high-yielding, disease-resistant cultivars. In this study, for the first time, we compared the seed proteome of high-yielding mung bean cultivars developed by a conventional breeding approach. Using a label-free quantitative proteomic platform, we successfully identified and quantified a total of 1373 proteins. Comparative analysis between the high-yielding disease-resistant cultivar (MC5) and the other three cultivars showed that a total of 69 common proteins were significantly altered in their abundances across all cultivars. Bioinformatic analysis of these altered proteins demonstrated that PDF1 (a defensin-like protein) exhibited high sequence similarity and epitope matching with the established peanut allergens, indicating a potential mung bean allergen that showed a cultivar-specific response. Conversely, known mung bean allergen proteins such as PR-2/PR-10 (Vig r 1), Vig r 2, Vig r 4, LTP1, ß-conglycinin, and glycinin G4 showed no alternation in the MC5 compared to other cultivars. Taken together, our findings suggest that the known allergen profiles may not be impacted by the conventional plant breeding method to develop improved mung bean cultivars.

Partial enzymatic elimination and quantification of sarcosine from alanine using liquid chromatography-tandem mass spectrometry.

Since sarcosine and D,L-alanine co-elute on reversed-phase high-performance liquid chromatography (HPLC) columns and the tandem mass spectrometer cannot differentiate them due to equivalent parent and fragment ions, derivatization is often required for analysis of sarcosine in LC/MS systems. This study offers an alternative to derivatization by employing partial elimination of sarcosine by enzymatic oxidation. The decrease in apparent concentration from the traditionally merged sarcosine-alanine peak associated with the enzymatic elimination has been shown to be proportional to the total sarcosine present (R(2) = 0.9999), allowing for determinations of urinary sarcosine. Sarcosine oxidase was shown to eliminate only sarcosine in the presence of D,L-alanine, and was consequently used as the selective enzyme. This newly developed technique has a method detection limit of 1 µg/L (parts per billion) with a linear range of 3 ppb-1 mg/L (parts per million) in urine matrices. The method was further validated through spiked recoveries of real urine samples, as well as the analysis of 35 real urine samples. The average recoveries for low, middle, and high sarcosine concentration spikes were 111.7, 90.8, and 90.1 %, respectively. In conclusion, this simple enzymatic approach coupled with HPLC/MS/MS is able to resolve sarcosine from D,L-alanine leading to underivatized quantification of sarcosine.

Quantitative determination of taurine and related biomarkers in urine by liquid chromatography-tandem mass spectrometry.

Current urinary bladder cancer diagnosis is commonly based on a biopsy obtained during cystoscopy. This invasive method causes discomfort and pain in patients. Recently, taurine and several other compounds such as L-phenylalanine and hippuric acid in urine were found to be indicators of bladder cancer. However, because of a lack of sensitive and accurate analytical techniques, it is impossible to detect these compounds in urine at low levels. In this study, using liquid chromatography-tandem mass spectrometry (LC-MS/MS), a noninvasive method was developed to separate and detect these compounds in urine. (15)N(2)-L-glutamine was used as the internal standard, and creatinine acted as an indicator for urine dilution. A phenyl-hexyl column was used for the separation at an isocratic condition of 0.2% formic acid in water and 0.2% formic acid in methanol. Analytes were detected in multiple-reaction monitoring with positive ionization mode. The limit of detection range is 0.18-6 nM and the limit of quantitation ranges from 0.6 to 17.6 nM. The parameters affecting separation and quantification were also investigated and optimized. Proper clinical validation of these biomarkers can be done using this reliable, fast, and simple method. Furthermore, with simple modifications, this method could be applied to other physiological fluids and other types of diseases.

Lentil allergens identification and quantification: An update from omics perspective.

Among legumes, the lentil (Lens culinaris) is a major dietary component in many Mediterranean and Asian countries due to its high nutritional value, especially protein. However, allergic reactions triggered by lentil consumption have also been documented in many countries. Complete allergens profiling is critical for better management of lentil food allergies. Earlier studies suggested Len c 1, a 47 kDa vicilin, Len c 2, a seed-specific-biotinylated 66-kDa protein, and Len c 3, low molecular weight lipid transfer proteins (LTPs) were major allergenic proteins in lentils. Recently, mass-spectrometry-based proteomic platforms successfully identified proteins from lentil samples homologous to known plant allergens. Furthermore, in silico analysis using 337 protein sequences revealed lentil allergens that have not previously been identified as potential allergens in lentil. Herein, we discuss the feasibility of omics platforms utilized for lentil allergens profiling and quantification. In addition, we propose some future strategies that might be beneficial for profiling and development of precise assays for lentil allergens and could facilitate identification of the low allergen-containing lentil cultivars.

Evaluation of statistical techniques to normalize mass spectrometry-based urinary metabolomics data.

Human urine recently became a popular medium for metabolomics biomarker discovery because its collection is non-invasive. Sometimes renal dilution of urine can be problematic in this type of urinary biomarker analysis. Currently, various normalization techniques such as creatinine ratio, osmolality, specific gravity, dry mass, urine volume, and area under the curve are used to account for the renal dilution. However, these normalization techniques have their own drawbacks. In this project, mass spectrometry-based urinary metabolomic data obtained from prostate cancer (n = 56), bladder cancer (n = 57) and control (n = 69) groups were analyzed using statistical normalization techniques. The normalization techniques investigated in this study are Creatinine Ratio, Log Value, Linear Baseline, Cyclic Loess, Quantile, Probabilistic Quotient, Auto Scaling, Pareto Scaling, and Variance Stabilizing Normalization. The appropriate summary statistics for comparison of normalization techniques were created using variances, coefficients of variation, and boxplots. For each normalization technique, a principal component analysis was performed to identify clusters based on cancer type. In addition, hypothesis tests were conducted to determine if the normalized biomarkers could be used to differentiate between the cancer types. The results indicate that the determination of statistical significance can be dependent upon which normalization method is utilized. Therefore, careful consideration should go into choosing an appropriate normalization technique as no method had universally superior performance.

Effect of Process Parameters and Material Properties on Laser Micromachining of Microchannels.

Laser micromachining has emerged as a promising technique for mass production of microfluidic devices. However, control and optimization of process parameters, and design of substrate materials are still ongoing challenges for the widespread application of laser micromachining. This article reports a systematic study on the effect of laser system parameters and thermo-physical properties of substrate materials on laser micromachining. Three dimensional transient heat conduction equation with a Gaussian laser heat source was solved using finite element based Multiphysics software COMSOL 5.2a. Large heat convection coefficients were used to consider the rapid phase transition of the material during the laser treatment. The depth of the laser cut was measured by removing material at a pre-set temperature. The grid independent analysis was performed for ensuring the accuracy of the model. The results show that laser power and scanning speed have a strong effect on the channel depth, while the level of focus of the laser beam contributes in determining both the depth and width of the channel. Higher thermal conductivity results deeper in cuts, in contrast the higher specific heat produces shallower channels for a given condition. These findings can help in designing and optimizing process parameters for laser micromachining of microfluidic devices.

Analysis of gentisic acid and related renal cell carcinoma biomarkers using reversed-phase liquid chromatography with water-rich mobile phases.

The problem of longer retention times using water-rich mobile phases in reversed phase liquid chromatography (RPLC) has been addressed using hydrophobic alcohols such as butanol in very low quantities (approximately 0.1%) as the organic modifier. Advantages of water-rich mobile phases in RPLC for the separation of water-soluble and weakly retained compounds are improved separation of congeners and better tuning of RPLC separations. This is demonstrated in the separation of gentisic acid and related renal cell carcinoma (RCC) biomarkers in urine with a Zorbax C18 column and a mobile phase of 0.1% (volume/volume) butanol in water with 0.6% (volume/volume) acetic acid. Calibration curves for the RCC biomarkers were linear over the concentration range investigated (5 ppm to 1000 ppm). Detection limits for the RCC biomarkers were 0.85ppm (quinolinic acid), 1.75ppm (gentisic acid), and 1.25ppm (4-hydroxybenzoic acid). Recovery tests using synthetic urine samples containing 20 ppm, 100 ppm, and 700 pm of each RCC biomarker were successful for all compounds.

Biomarker analysis for oncology.

Cancer biomarkers are biological, chemical or biophysical entities that are present in tumor tissues or body fluids which give valuable information about current and future behavior of cancer. This review discusses the applicability of biomarkers in different stages of cancer from cancer risk assessment to recurrence. In medical practice, biomarkers can be helpful in finding out one's potential cancer risk, confirming whether or not one is already affected with a particular type of cancer, to which drug will the cancer respond best and in what doses should it be administered, the effectiveness of the treatment and whether the cancer will recur. Although biomarker discovery and validation is a very challenging process, when considering its applications and advantages, it is well worth the effort.

Simultaneous detection of perchlorate and bromate using rapid high-performance ion exchange chromatography-tandem mass spectrometry and perchlorate removal in drinking water.

Perchlorate and bromate occurrence in drinking water causes health concerns due to their effects on thyroid function and carcinogenicity, respectively. The purpose of this study was threefold: (1) to advance a sensitive method for simultaneous rapid detection of perchlorate and bromate in drinking water system, (2) to systematically study the occurrence of these two contaminants in Missouri drinking water treatment systems, and (3) to examine effective sorbents for minimizing perchlorate in drinking water. A rapid high-performance ion exchange chromatography-tandem mass spectrometry (HPIC-MS/MS) method was advanced for simultaneous detection of perchlorate and bromate in drinking water. The HPIC-MS/MS method was rapid, required no preconcentration of the water samples, and had detection limits for perchlorate and bromate of 0.04 and 0.01 µg/L, respectively. The method was applied to determine perchlorate and bromate concentrations in total of 23 selected Missouri drinking water treatment systems during differing seasons. The water systems selected include different source waters: groundwater, lake water, river water, and groundwater influenced by surface water. The concentrations of perchlorate and bromate were lower than or near to method detection limits in most of the drinking water samples monitored. The removal of perchlorate by various adsorbents was studied. A cationic organoclay (TC-99) exhibited effective removal of perchlorate from drinking water matrices.

Validation study of urinary metabolites as potential biomarkers for prostate cancer detection.

BACKGROUND: Urinary metabolomic profiles have recently drawn a lot of attention owing to a debate regarding their possible role as potential clinical markers for prostate cancer. In this study, levels of proline, kynurenine, uracil and glycerol-3-phosphate in 126 patients with genitourinary malignancies were analyzed using a validated method and compared with no evidence of malignancy. RESULTS: The statistical results showed that these biomarkers cannot differentiate prostate cancer from no evidence of malignancy or from other related cancer types, such as bladder cancer. In addition, there was no significant difference in biomarker levels for T1 stages, T2 stages and Gleason scores <7, ≥7. From the correlation study, results showed/demonstrated that age or serum prostate-specific antigen levels do not influence these metabolite concentrations in urine. However, the strong correlation between these metabolites and urinary creatinine concentrations implies that their occurrence is mainly due to renal excretion. CONCLUSION: This detailed study shows that the aforementioned urinary metabolites are not reliable biomarkers for prostate cancer detection or for differentiating the aggressiveness of prostate cancer.

Biomarker analysis for prostate cancer diagnosis using LC-MS and CE-MS.

Prostate cancer is one of the most common cancer types in men. In addition, it is the second leading cause of cancer death in the USA and Canada. Prostate cancer diagnosis is not a precise science yet. Discovery of potential biomarkers for early prostate cancer diagnosis and monitoring is crucially important. LC-MS and CE-MS have been widely used analytical techniques in the biomarker discovery. This review will describe the applications of LC-MS with different ionization techniques, such as ESI, atmospheric-pressure photoionization and atmospheric-pressure chemical ionization, and CE-MS techniques used in prostate cancer biomarker analysis.

Investigation of urinary pteridine levels as potential biomarkers for noninvasive diagnosis of cancer.

BACKGROUND: Biomarkers are good potential tools for early cancer diagnosis. Here we have analyzed eight different pteridines in the urine samples of cancer patients and compared them with samples from healthy subjects. Pteridines are important cofactors in the process of cell metabolism, and they have recently become a focal point of cancer screening research because certain pteridine levels have been shown to reflect the presence of cancers. METHODS: We analyzed 8 pteridines; 6,7-dimethylpterin, 6-biopterin, d-(+)-neopterin, 6-hydroxymethylpterin, pterin, isoxanthopterin, xanthopterin and pterin-6-carboxylic acid using a house-built high-performance capillary electrophoresis with laser-induced fluorescence detection (HPCE-LIF). The levels of pteridines were reported as a ratio of pteridine to creatinine. Statistical hypothesis testing was conducted and P values were calculated to analyze the data. RESULTS: Among the eight pteridines studied, 6-biopterin, 6-hydroxymethylpterin, pterin, xanthopterin, and isoxanthopterin levels were significantly higher in samples from cancer patients than in those from healthy subjects. Further, xanthopterin and isoxanthopterin levels were compared in breast cancer and lung cancer patients, but no significant difference was observed. CONCLUSION: Some pteridine levels can be used as biomarkers for noninvasive diagnosis of cancer; however, more data is needed to support this hypothesis.

Investigation of pharmaceuticals in Missouri natural and drinking water using high performance liquid chromatography-tandem mass spectrometry.

A comprehensive method has been developed and validated in two different water matrices for the analysis of 16 pharmaceutical compounds using solid phase extraction (SPE) of water samples, followed by liquid chromatography coupled with tandem mass spectrometry. These 16 compounds include antibiotics, hormones, analgesics, stimulants, antiepileptics, and X-ray contrast media. Method detection limits (MDLs) that were determined in both reagent water and municipal tap water ranged from 0.1 to 9.9 ng/L. Recoveries for most of the compounds were comparable to those obtained using U.S. EPA methods. Treated and untreated water samples were collected from 31 different water treatment facilities across Missouri, in both winter and summer seasons, and analyzed to assess the 16 pharmaceutical compounds. The results showed that the highest pharmaceutical concentrations in untreated water were caffeine, ibuprofen, and acetaminophen, at concentrations of 224, 77.2, and 70 ng/L, respectively. Concentrations of pharmaceuticals were generally higher during the winter months, as compared to those in the summer due, presumably, to smaller water quantities in the winter, even though pharmaceutical loadings into the receiving waters were similar for both seasons.