Plasma, the soluble component of the human blood, is believed to harbor thousands of distinct proteins, which originate from a variety of cells and tissues through either active secretion or leakage from blood cells or tissues. The dynamic range of plasma protein concentrations comprises at least nine orders of magnitude. Proteins involved in coagulation, immune defense, small molecule transport, and protease inhibition, many of them present in high abundance in this body fluid, have been functionally characterized and associated with disease processes. For example, protein sequence mutations in coagulation factors cause various serious disease states. Diagnosing and monitoring such diseases in blood plasma of affected individuals has typically been conducted by use of enzyme-linked immunosorbent assays, which using a specific antibody quantitatively measure only the affected protein in the tested plasma samples. The discovery of protein biomarkers in plasma for diseases with no known correlations to genetic mutations is challenging. It requires a highly parallel display and quantitation strategy for proteins. We fractionated blood serum proteins prior to display on two-dimensional electrophoresis (2-DE) gels using immunoaffinity chromatography to remove the most abundant serum proteins, followed by sequential anion-exchange and size-exclusion chromatography. Serum proteins from 74 fractions were displayed on 2-DE gels. This approach succeeded in resolving approximately 3700 distinct protein spots, many of them post-translationally modified variants of plasma proteins. About 1800 distinct serum protein spots were identified by mass spectrometry. They collapsed into 325 distinct proteins, after sequence homology and similarity searches were carried out to eliminate redundant protein annotations. Although a relatively insensitive dye, Coomassie Brilliant Blue G-250, was used to visualize protein spots, several proteins known to be present in serum in < 10 ng/mL concentrations were identified such as interleukin-6, cathepsins, and peptide hormones. Considering that our strategy allows highly parallel protein quantitation on 2-DE gels, it holds promise to accelerate the discovery of novel serum protein biomarkers.

BackgroundClinical dogma is that healthy urine is sterile and the presence of bacteria with an inflammatory response is indicative of urinary tract infection (UTI). Asymptomatic bacteriuria (ABU) represents the state in which bacteria are present but the inflammatory response is negligible. Differentiating ABU from UTI is diagnostically challenging, but critical because overtreatment of ABU can perpetuate antimicrobial resistance while undertreatment of UTI can result in increased morbidity and mortality. In this study, we describe key characteristics of the healthy and ABU urine microbiomes utilizing 16S rRNA gene (16S rDNA) sequencing and metaproteomics, with the future goal of utilizing this information to personalize the treatment of UTI based on key individual characteristics.MethodsA cross-sectional study of 26 healthy controls and 27 healthy subjects at risk for ABU due to spinal cord injury-related neuropathic bladder (NB) was conducted. Of the 27 subjects with NB, 8 voided normally, 8 utilized intermittent catheterization, and 11 utilized indwelling Foley urethral catheterization for bladder drainage. Urine was obtained by clean catch in voiders, or directly from the catheter in subjects utilizing catheters. Urinalysis, urine culture and 16S rDNA sequencing were performed on all samples, with metaproteomic analysis performed on a subsample.ResultsA total of 589454 quality-filtered 16S rDNA sequence reads were processed through a NextGen 16S rDNA analysis pipeline. Urine microbiomes differ by normal bladder function vs. NB, gender, type of bladder catheter utilized, and duration of NB. The top ten bacterial taxa showing the most relative abundance and change among samples were Lactobacillales, Enterobacteriales, Actinomycetales, Bacillales, Clostridiales, Bacteroidales, Burkholderiales, Pseudomonadales, Bifidobacteriales and Coriobacteriales. Metaproteomics confirmed the 16S rDNA results, and functional human protein-pathogen interactions were noted in subjects where host defenses were initiated.ConclusionsCounter to clinical belief, healthy urine is not sterile. The healthy urine microbiome is characterized by a preponderance of Lactobacillales in women and Corynebacterium in men. The presence and duration of NB and method of urinary catheterization alter the healthy urine microbiome. An integrated approach of 16S rDNA sequencing with metaproteomics improves our understanding of healthy urine and facilitates a more personalized approach to prevention and treatment of infection.

In order to discover novel protein markers indicative of disease processes or drug effects, the proteomics technology platform most commonly used consists of high resolution protein separation by two-dimensional electrophoresis (2-DE), mass spectrometric identification of proteins from stained gel spots and a bioinformatic data analysis process supported by statistics. This approach has been more successful in profiling proteins and their disease- or treatment-related quantitative changes in tissue homogenates than in plasma samples. Plasma protein display and quantitation suffer from several disadvantages: very high abundance of a few proteins; high heterogeneity of many proteins resulting in long charge trains; crowding of 2-DE separated protein spots in the molecular mass range between 45-80 kD and in the isoelectric point range between 4.5 and 6. Therefore, proteomic technologies are needed that address these problems and particularly allow accurate quantitation of a larger number of less abundant proteins in plasma and other body fluids. The immunoaffinity-based protein subtraction chromatography (IASC) described here removes multiple proteins present in plasma and serum in high concentrations effectively and reproducibly. Applying IASC as an upfront plasma sample preparation process for 2-DE, the protein spot pattern observed in gels changes dramatically and at least 350 additional lower abundance proteins are visualized. Affinity-purified polyclonal antibodies (pAbs) are the immunoaffinity reagents used to specifically remove the abundant proteins such as albumin, immunoglobulin G, immunoglobulin A, transferrin, haptoglobin, alpha-1-antitrypsin, hemopexin, transthyretin, alpha-2-HS glycoprotein, alpha-1-acid glycoprotein, alpha-2-macroglobulin and fibrinogen from human plasma samples. To render the immunoaffinity subtraction procedure recyclable, the pAbs are immobilized and cross-linked on chromatographic matrices. Antibody-coupled matrices specific for one protein each can be pooled to form mixed-bed IASC columns. We show that up to ten affinity-bound plasma proteins with similar solubility characteristics are eluted from a mixed-bed column in one step. This facilitates automated chromatographic processing of plasma samples in high throughput, which is desirable in proteomic disease marker discovery projects.

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Rheumatoid arthritis (RA) is associated with atherosclerosis. However, the relationship between RA and peripheral arterial occlusive disease (PAOD) remains unclear. We used a national health insurance database to identify a cohort of 30,812 patients diagnosed with RA between 2000 and 2011. Each RA patient was frequency-matched according to age and sex with a patient without RA from a control cohort. A multivariate Cox proportional hazards model was used to analyse the adjusted risk of PAOD. The incidence of PAOD was 1.73-fold higher (95% confidence interval [CI] = 1.57-1.91) in the RA cohort than in the non-RA cohort. The adjusted risk of PAOD was the highest in the patients with RA aged ≤ 49 years (hazard ratio [HR] = 3.39, 95% CI = 2.66-4.32). Patients with RA and various comorbidities showed a significantly higher risk of PAOD (HR = 9.62, 95% CI = 4.86-19.1) compared with control patients without comorbidity. The risk of PAOD increased during the first year of follow-up. In conclusion, patients with RA have an independently higher risk of PAOD compared with the general population. Patients with RA and various comorbidities and those at a young age and early stage of the disease have an increased risk of PAOD.

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BackgroundDespite the recommendations of statins treatment for secondary prevention of atherosclerotic cardiovascular disease (ASCVD), treatment adherence and persistence are still a concern. This study examined the real world practice of long-term adherence and persistence to statins treatment initiated after hospital discharge for ASCVD, and their associated factors in a nationwide cohort.MethodsPost discharge statin prescriptions between 2006 and 2012 were extracted from the Taiwan National Health Insurance claims database. Good adherence, defined as proportion of days covered (PDC) ≥0.8 and mean medication possession ratio (MPR), was measured every 180-day period. Non-persistence was defined on the date patients failed to refill statin for 90 days after the end of the last prescription. Their associations with influential factors were analyzed using a generalized estimating equation and Cox’s proportional hazard model.ResultsThere was a total of 185,252 post-discharge statin initiations (from 169,624 patients) and followed for 467,398 patient-years in the study cohort. Percentage of good adherence (mean MPR) was 71% (0.87) at 6-months; declined to 54% (0.68), 47% (0.59), and 42% (0.50) at end of year 1, 2, and 7, respectively. Persistence in statin treatment was 86, 67, 50, and 25% at 6-month, 1-, 2-, and 7-year, respectively. Comparing the statin-cohort initiated from year 2006 to 2012, 1-year persistence increased from 58 to 73%, and 1-year good adherence improved from 45 to 61%. Factors associated with sub-optimal adherence and non-persistence included: prescription by primary care clinics or non-cardiology specialties; patients’ age > 75 years; no history of previous statin use; ASCVD events with ischemic stroke diagnosis; comorbidities of renal disease, liver disease, depression, and chronic obstructive pulmonary disease.ConclusionsDespite the improving trends, long-term adherence and persistence of statin treatment were suboptimal in Taiwan. Strategies to maintain statin treatment adherence and persistence need to be implemented to further enhance the positive trend.