Yanbao Yu (Presenter)
J. Craig Venter Institute
Authorship: Yanbao Yu (1),*, Patricia Sikorski (1),, Madeline Smith (1), Cynthia Bowman-Gholston (2), Nicolas Cacciabeve (3), Karen E. Nelson (4), Rembert Pieper (1),*
(1). J. Craig Venter Institute (2). Quest Diagnostics at Shady Grove Adventist Hospital (3). Advanced Pathology Associates LLC at Shady Grove Adventist Hospital; Rockville, MD 20850
| Short Abstract Non-invasively collected urine is a valuable source to clinical diagnosis and prognosis. However, most urinary proteomic studies reported to date worked with supernatant. The resulting sediment/pellet was often discarded as wastes. Urine sediments were recently found to be informative regarding urinary tract infections. In this study, we first used a metaproteomic approach to profile the human and microbial proteomes of the entire urine specimens. Second, we quantitatively analyzed the differences of the two urine fractions with label-free approach. Finally, we identified proteomic differences in both fractions in the context of identifications for uropathogens and commensal organisms and evidence of urothelial injury and hematuria. |
Long Abstract
Introduction:
Urine, as a non-invasively collected body fluid, has been a valuable source to clinical diagnosis and prognosis for centuries.1 Since majority of the substances in urine are from glomerular filtrate of blood plasma, they often reflects the physiological or pathological conditions of the urinary system as well many other organs of human body.2 However, most proteomic studies reported to date worked with urine supernatant, the resulting sediment/pellet after a typical centrifugation step was often discarded as wastes. Interestingly, the urine sediments were recently found to be informative regarding infections in urinary tract and co-existing microorganisms.3-5 To more comprehensively understand the pathogenesis and immune responses that are associated with urinary tract, in this study we used a metaproteomic approach to explore such relationships for urine specimens, including both urine supernatant and pellet, from 33 human subjects. First, we performed an overall profile of human and microbial proteomes of the whole urine specimens. Second, we quantitatively analyzed the differences of the two urine fractions with label-free approach followed by functional analysis of proteins that were differentially present. Finally, we identified proteomic differences in both fractions in the context of identifications for uropathogens and commensal organisms and evidence of urothelial injury and hematuria.
Methods:
The human subjects involved in this study included 12 cases of urinary tract infection (UTI), 3 cases with evidence of urogenital injury (ERY), 9 cases indicative of either vaginal contamination or urethral colonization (VCO), and 9 cases without evidence of bacteria and inflammation (NoB). The urine samples (20~50 ml) were first centrifuged at 3000 × rpm for 15 minutes at 10°C to separate the SU and UP fractions. Following a method published previously,6 the SU fraction was concentrated and subjected to FASP processing. The UP fraction was first lysed with an 8 M urea buffer and processed with the same FASP protocol (10 kDa MWKO, Sartorius, Germany). Peptide digests were desalted afterwards using the spinnable StageTip protocol.7 LC-MS/MS analysis was performed on an Ultimate 3000 nano LC and Q Exactive mass spectrometer system coupled to a FLEX nano-electrospray ion source (all components were from Thermo Scientific) following a standard protocol published previously.6 The LCMS raw data were processed using the Proteome Discoverer platform (version 1.4, Thermo Scientific) and the MaxQuant software suite (version 1.5). In Proteome Discoverer, an embedded workflow with the Sequest HT (version 2.4, Matrix Science) algorithm was employed. For protein quantitation, most of the default settings provided in the MaxQuant-Andromeda software suite, which are similar to Proteome Discoverer settings, were accepted. Both the label-free quantitation (LFQ) and the intensity-based absolute quantitation (iBAQ) tools were enabled. For statistical analysis, non-parametric Welch t-test (p < 0.01) was applied with a permutation-based testing correction that was controlled by using a FDR threshold of 0.01. Hierarchical clustering and Principle Component Analysis (PCA) of proteins were performed in Perseus software (version 1.5) using Euclidean distances and logarithmized LFQ values.
Results And Conclusions:
We identified 5,327 non-redundant human proteins, 2,638 and 4,379 of which were associated with soluble urine (SU) and urinary pellet (UP) fractions, respectively. Approximately 1,206 non-redundant protein orthology groups were derived from pathogens and commensal organisms of the urogenital tract. The bacterial sub-proteome fraction, compared to the entire UP proteome, varied between 20 to 400 proteins among the urine samples. Label-free quantitation followed by clustering analysis revealed 508 proteins that showed significant differences (p < 0.01) between the SU and UP proteomes. Proteins associated with innate immunity, particularly those found in neutrophil granules, were more abundant in UP fractions of specimens with identified urinary tract pathogens compared to the corresponding soluble fractions, or those where pathogenic bacteria were absent. Proteins involved in coagulation and the complement system were frequently enriched in UP fractions. Global biological process analysis suggested that both SU and UP fractions were enriched for categories such as ‘response to acute inflammation’ and ‘response to wounding’, which reflects that 40% of the analyses pertained to UTI cases. The expression of bacterial proteins with bivalent metal acquisition and oxidative stress response functions were limited to pathogens, confirming both their importance in the battle for iron with the human host as well as protection from reactive oxygen species produced by neutrophils. Our data not only advances the understanding of host-pathogen functional networks in the urinary tract, but also reveals a fact that urinary pellet is not just cell debris and physical concentrates of urine supernatant; both fractions are enrich in different urinary proteomes, and both can serve as valuable resources for disease biomarker discovery and clinical diagnosis.
References & Acknowledgements:
References:
(1) Decramer, S.; de Peredo, A. G.; Breuil, B.; Mischak, H.; Monsarrat, B.; Bascands, J.-L.; Schanstra, J. P. Mol. Cell. Proteomics 2008, 7, 1850-1862.
(2) Fliser, D.; Novak, J.; Thongboonkerd, V.; Argilés, À.; Jankowski, V.; Girolami, M. A.; Jankowski, J.; Mischak, H. J. Am. Soc. Nephrol. 2007, 18, 1057-1071.
(3) Yu, Y.; Pieper, R. Urinary Pellet Sample Preparation for Shotgun Proteomic Analysis of Microbial Infection and Host–Pathogen Interactions. In Posch A (ed) Proteomic Profiling, Edition Springer New York 2015; 65-74.
(4) Yu, Y.; Sikorski, P.; Bowman-Gholston, C.; Cacciabeve, N.; Nelson, K.; Pieper, R. J. Transl. Med. 2015, 13, 1-14.
(5) Yu, Y.; Zielinski, M. D.; Rolfe, M. A.; Kuntz, M. M.; Nelson, H.; Nelson, K. E.; Pieper, R. Infect. Immun. 2015, 83, 4142-4153.
(6) Yu, Y.; Suh, M.-J.; Sikorski, P.; Kwon, K.; Nelson, K. E.; Pieper, R. Anal. Chem. 2014, 86, 5470–5477.
(7) Yu, Y.; Smith, M.; Pieper, R. Protocol Exchange 2014, doi:10.1038/protex.2014.1033.
Acknowledgments:
We thank the National Institute of General Medical Sciences, National Institutes of Health, for partially funding the research, via grant 5R01GM103598-02, and the JCVI and Dr. J. Craig Venter for additional funding support. Finally, we thank the Ruggles Family Foundation for a contribution to fund the mass spectrometry system used in this research. The funding bodies did not have a role in study design, data collection and analysis, decision to publish, and preparation of the manuscript.
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