Investigation of Inter- and Intra-Day Variability of Tear Fluid Regarding Flow Rate, Protein Concentration as well as Protein Composition.

Purpose: The purpose of this study was to present the determination of inter- and intra-day variations in tear flow rate, and tear fluid protein concentration, as well as protein composition regarding their impact for future biomarker studies. Methods: Tear fluid was collected noninvasively from 18 healthy subjects by performing Schirmer tests at 4 different time points repetitive in a period of 2 days. The tear flow rate on the Schirmer test strips was measured. Proteins were extracted from strips and quantified using amino acid analysis. Protein composition was analyzed by the strips data-independent (DIA) based mass spectrometry. To exclude any impairments to health, volunteers underwent a detailed neurological as well as an ophthalmological examination. Results: Whether tear fluid was collected from oculus sinister or oculus dexter did not affect the tear flow rate (P ≈ 0.63) or protein concentration (P ≈ 0.97) of individual subjects. Moreover, protein concentration was independent from the tear volume, so that a change in volume may only influence the total protein amount. When the examination days were compared, investigation of tear flow rate (P ≈ 0.001) and protein concentration (P ≈ 0.0003) indicated significant differences. Further, mass spectrometric analysis of tear fluid revealed 11 differentially regulated proteins when comparing both examination days. Conclusions: Our findings provide evidence of inter-day variation in tear flow rate, tear proteome concentration, and composition in healthy subjects, suggesting that inter-day variation needs to be taken into consideration in biomarker research of tear fluid. Identified proteins were assigned to functions in the immune response, oxidative and reducing processes, as well as mannose metabolism.

Quality Control-A Stepchild in Quantitative Proteomics: A Case Study for the Human CSF Proteome.

Proteomic studies using mass spectrometry (MS)-based quantification are a main approach to the discovery of new biomarkers. However, a number of analytical conditions in front and during MS data acquisition can affect the accuracy of the obtained outcome. Therefore, comprehensive quality assessment of the acquired data plays a central role in quantitative proteomics, though, due to the immense complexity of MS data, it is often neglected. Here, we address practically the quality assessment of quantitative MS data, describing key steps for the evaluation, including the levels of raw data, identification and quantification. With this, four independent datasets from cerebrospinal fluid, an important biofluid for neurodegenerative disease biomarker studies, were assessed, demonstrating that sample processing-based differences are already reflected at all three levels but with varying impacts on the quality of the quantitative data. Specifically, we provide guidance to critically interpret the quality of MS data for quantitative proteomics. Moreover, we provide the free and open source quality control tool MaCProQC, enabling systematic, rapid and uncomplicated data comparison of raw data, identification and feature detection levels through defined quality metrics and a step-by-step quality control workflow.

Rat retinae data for use as spectral library, for pathway remodeling as well as protein mapping.

This article describes a mass spectrometric data set from rat retinae spiked with indexed Retention Time (iRT) peptides. The provided data set can be used as a spectral library to investigate for instance eye disorders as well as ocular function by data-independent acquisition (DIA) based mass spectrometry. Consequently, there is no urgent need to create an own spectral library, which requires money, time, effort as well as tissue. Besides the use as a spectral library, this data set can improve our knowledge about proteins present in the rat retina and thus the protein pathways within this tissue. The data set may also help to determine optimal parameters for peptide identification by mass spectrometry. To generate the presented data set, six rat retinae were homogenized with glass beads and pooled. The pooled sample was fractionated by SDS-PAGE (sodium dodecyl sulfate polyacrylamide gel electrophoresis) followed by tryptic in-gel digestion. The fractionation of the pooled sample was repeated for further 4 times, to end up with in total 5 technical replicates. Peptide extracts were spiked with iRT peptides and analyzed by data-dependent (DDA) nanoHPLC-ESI-MS/MS resulting in 60 files. All resulting data files are hosted in the public repository ProteomeXchange under the identifier PXD021937.

Good Old-Fashioned Protein Concentration Determination by Amino Acid Analysis.

Although a lot of new methods for protein concentration determination have been developed and established the last years, the amino acid analysis has still this relevance within proteomics for multiple reasons especially in the quantitative protein analysis. Amino acid analysis enables indirectly both the protein and peptide concentration determination which are essential for using the same amounts for comparative quantitative experiments. Moreover, the quantity and quality of synthetic peptides can be verified. The method itself is robust in comparison with colorimetric assays, especially when detergents or chaotropes are present in the sample buffer. Furthermore, it is highly sensitive. Nevertheless, amino acid analysis needs a certain experience to be set up and is time-consuming compared to other protein concentration determination techniques.

Proteomic Analysis of Retinal Tissue in an S100B Autoimmune Glaucoma Model.

Glaucoma is a neurodegenerative disease that leads to damage of retinal ganglion cells and the optic nerve. Patients display altered antibody profiles and increased antibody titer, e.g., against S100B. To identify the meaning of these antibodies, animals were immunized with S100B. Retinal ganglion cell loss, optic nerve degeneration, and increased glial cell activity were noted. Here, we aimed to gain more insights into the pathophysiology from a proteomic point of view. Hence, rats were immunized with S100B, while controls received sodium chloride. After 7 and 14 days, retinae were analyzed through mass spectrometry and immunohistology. Using data-independent acquisition-based mass spectrometry, we identified more than 1700 proteins on a high confidence level for both study groups, respectively. Of these 1700, 43 proteins were significantly altered in retinae after 7 days and 67 proteins revealed significant alterations at 14 days. For example, α2-macroglobulin was found significantly increased not only by mass spectrometry analysis, but also with immunohistological staining in S100B retinae at 7 and 14 days. All in all, the identified proteins are often associated with the immune system, such as heat shock protein 60. Once more, these data underline the important role of immunological factors in glaucoma pathogenesis.

Comparative proteomic analysis of osteogenic differentiated human adipose tissue and bone marrow-derived stromal cells.

Mesenchymal stromal cells are promising candidates for regenerative applications upon treatment of bone defects. Bone marrow-derived stromal cells (BMSCs) are limited by yield and donor morbidity but show superior osteogenic capacity compared to adipose-derived stromal cells (ASCs), which are highly abundant and easy to harvest. The underlying reasons for this difference on a proteomic level have not been studied yet. Human ASCs and BMSCs were characterized by FACS analysis and tri-lineage differentiation, followed by an intraindividual comparative proteomic analysis upon osteogenic differentiation. Results of the proteomic analysis were followed by functional pathway analysis. 29 patients were included with a total of 58 specimen analysed. In these, out of 5148 identified proteins 2095 could be quantified in >80% of samples of both cell types, 427 in >80% of ASCs only and 102 in >80% of BMSCs only. 281 proteins were differentially regulated with a fold change of >1.5 of which 204 were higher abundant in BMSCs and 77 in ASCs. Integrin cell surface interactions were the most overrepresented pathway with 5 integrins being among the proteins with highest fold change. Integrin 11a, a known key protein for osteogenesis, could be identified as strongly up-regulated in BMSC confirmed by Western blotting. The integrin expression profile is one of the key distinctive features of osteogenic differentiated BMSCs and ASCs. Thus, they represent a promising target for modifications of ASCs aiming to improve their osteogenic capacity and approximate them to that of BMSCs.

Human cerebrospinal fluid data for use as spectral library, for biomarker research.

Spectral libraries generated by data dependent acquisition (DDA) are a useful tool for the analysis of data created by data independent acquisition (DIA) in mass spectrometry. The quality of DIA analysis is dependent on the quality of the spectral library. We used cerebrospinal fluid (CSF) of patients with Parkinson's disease and healthy controls to create a spectral library of human CSF proteome. To this date, there is no validated CSF biomarker for Parkinson's disease. This data set may therefore be valuable for the future analysis of CSF proteins. Part of the samples consisted of fractions that were separated by gel electrophoresis. After tryptic digestion, all samples were spiked with indexed retention time (iRT) peptides and were measured using a DDA mass spectrometry approach. The here provided data set can be used as a CSF-specific spectral library. Data files generated from the described workflow are hosted in the public repository ProteomeXchange under the identifier PXD013487.

A spiked human proteomic dataset from human osteogenic differentiated BMSCs and ASCs for use as a spectral library, for modelling pathways as well as protein mapping.

This article describes a mass spectrometry data set generated from osteogenic differentiated bone marrow stromal cells (BMSCs) and adipose tissue derived stromal cells (ASCs) of a 24-year old healthy donor. Before osteogenic differentiation and performing mass spectrometric measurements cells have been characterized as mesenchymal stromal cells via FACS-analysis positive for CD90 and CD105 and negative for CD14, CD34, CD45 and CD11b and tri-lineage differentiation. After osteogenic differentiation, both cell types were homogenized and then fractionated by SDS gel electrophoresis, resulting in 12 fractions. The proteins underwent an in-gel digestion, spiked with iRT peptides and analysed by nanoHPLC-ESI-MS/MS, resulting in 24 data files. The data files generated from the described workflow are hosted in the public repository ProteomeXchange with identifier PXD015026. The presented data set can be used as a spectral library for analysis of key proteins in the context of osteogenic differentiation of mesenchymal stromal cells for regenerative applications. Moreover, these data can be used to perform comparative proteomic analysis of different mesenchymal stromal cells or stem cells upon osteogenic differentiation. In addition, these data can also be used to determine the optimal settings for measuring proteins and peptides of interest.

Spiked human substantia nigra proteome data set for use as a spectral library for protein modelling and protein mapping.

This article describes a mass spectrometric data set generated from human substantia nigra tissue that was spiked with iRT peptides. The data set can be used as a spectral library for analysis of the human brain; especially for analysis of human substantia nigra, for example, in the context of Parkinson's disease. Obtaining a sufficient amount of high-quality substantia nigra tissue is the key limiting factor for establishing a brain region-specific spectral library. Hence, combining existing spectral libraries for data-independent acquisition analysis (DIA) can overcome this major limitation. Moreover, these data can be used to map brain region-specific proteins and to model brain region-specific pathways. Both can improve our understanding of the functioning of the brain in greater depth. In addition, these data can also be used to determine the optimal settings for measuring proteins and peptides of interest. To create the substantia nigra-specific spectral library, the tissue was first homogenized and then fractionated via different types of SDS gel electrophoresis, resulting in 18 fractions. These fractions were analysed in triplicate by nanoHPLC-ESI-MS/MS, resulting in 54 data files. The data files generated from the described workflow are hosted in the public repository ProteomeXchange with the identifier PXD011076.

Human tear fluid proteome dataset for usage as a spectral library and for protein modeling.

This article provides a detailed dataset of human tear fluid proteins. Samples were fractionated by sodium dodecyl sulfate (SDS) gel electrophoresis resulting in 48 fractions that were spiked with an indexed retention time (iRT) peptide standard. These data are based on a data-dependent acquisition (DDA) mass spectrometric approach and can be used for example as a spectral library for tear fluid proteome analysis by data-independent acquisition (DIA). Moreover, the provided data set can be used with optimized HPLC and mass spectrometric settings for proteins/peptides of interest. Besides these aspects, this dataset can serve as a protein overview for gene ontology enrichment analysis and for modeling and benchmarking of multiple signaling pathways associated with the ocular surface in healthy or disease stages. The mass spectrometry proteomics data from the described workflow have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD011075.

Indirect protein quantification of drug-transforming enzymes using peptide group-specific immunoaffinity enrichment and mass spectrometry.

Immunoaffinity enrichment of proteotypic peptides, coupled with selected reaction monitoring, enables indirect protein quantification. However the lack of suitable antibodies limits its widespread application. We developed a method in which multi-specific antibodies are used to enrich groups of peptides, thus facilitating multiplexed quantitative protein assays. We tested this strategy in a pharmacokinetic experiment by targeting a group of homologous drug transforming proteins in human hepatocytes. Our results indicate the generic applicability of this method to any biological system.