Mid-regional pro-adrenomedullin and lactate levels for risk stratification in patients with out-of-hospital cardiac arrest.

AIMS: Adrenomedullin (ADM) is a free-circulating peptide that regulates endothelial barrier function and vascular tone. Here, we sought to study the relationship of ADM in combination with lactate and the risk of death in patients with out-of-hospital cardiac arrest (OHCA). METHODS AND RESULTS: Mid-regional pro-adrenomedullin (MR-proADM) and lactate concentrations were measured in patients with OHCA who survived at least 24 h after the return of spontaneous circulation. The outcome of interest was all-cause death. Patients were characterized by the quartiles (Q) of MR-proADM and lactate concentrations. Cox models were adjusted for age, sex, shockable rhythm, bystander resuscitation, simplified acute physiology score II (SAPS II), and estimated glomerular filtration rate (eGFR). A total of 232 patients were included in the present study (28% women, 67 years, SAPS II 80). The median MR-proADM and lactate levels at 24 h were 1.4 nmol/L [interquartile range (IQR) 0.8-2.8 nmol/L] and 1.8 mmol/L (IQR 1.3-3.4 mmol/L), respectively. Mid-regional pro-adrenomedullin concentrations correlated weakly with lactate levels (r = 0.36, P < 0.001). High (Q4) vs. low (Q1-Q3) MR-proADM concentrations were significantly associated with an increased rate of death at 28 days (75.9 vs. 45.4%; P < 0.001). After multivariable adjustment (including lactate levels at 24 h), higher MR-proADM levels were significantly associated with an increased risk of death [Q4 vs. Q1-Q3: adjusted hazard ratio (adj-HR) 1.67, 95% confidence interval (CI) 1.12-2.50; adj-HR for a 1-unit increase in a standardized biomarker 1.44, 95% CI 1.19-1.73]. This relationship remained significant even after further adjustment for baseline NT-proBNP and high-sensitivity troponin T levels. The combination of high MR-proADM and high lactate (Q4) concentrations identified patients at a particularly elevated risk (adj-HR 3.50; 95% CI 1.92-6.39). CONCLUSION: Higher MR-proADM concentrations are associated with an increased risk of death in patients with OHCA, and the combination of high MR-proADM and lactate levels identifies patients at a distinctly elevated risk.

Dataset containing physiological amounts of spike-in proteins into murine C2C12 background as a ground truth quantitative LC-MS/MS reference.

In this article, we present a data dependent acquisition (DDA) dataset which was generated as a reference and ground truth quantitative dataset. While initially used to compare samples measured with DDA and data independent acquisition (DIA) (Barkovits et al., 2020), the presented dataset holds potential value as a benchmark reference for any workflows working on DDA data. The entire dataset consists of 15 LC-MS/MS measurements composed of five distinct spike-in-states, each with three replicates. To generate the data set, a C2C12 (immortalized mouse myoblast) cell lysate was used as a complex background for five different states which were simulated by spiking 13 defined proteins at different concentrations. For this purpose, the cell lysate was used in a constant amount of 20 µg for all samples and different amounts of the 13 selected proteins ranging from 0.1  to 10 pmol were added, reflecting physiological amounts of proteins. Afterwards, all samples were tryptically digested using the same method. From each sample 200 ng tryptic peptides were measured in triplicates on a Q Exactive HF (Thermo Fisher Scientific). The mass range for MS1 was set to 350-1400 m/z with a resolution of 60,000 at 200 m/z. HCD fragmentation of the Top10 abundant precursor ions was performed at 27% NCE. The fragment analysis (MS2) was performed with a resolution of 30,000 at 200 m/z. Additionally to the raw files, the dataset contains centroided mzML files and spectrum identification results for peptide identifications performed by Mascot (Perkins et al., 1999), MS-GF+ (Kim et al., 2010) and X!Tandem (Craig and Beavis, 2004) for each separate MS analysis. The corresponding FASTA containing protein sequences as well as a combination of all identification runs performed by PIA (Uszkoreit et al., 2019, 2015) and a peptide and protein quantification performed by OpenMS (Pfeuffer et al., 2017) is included. All data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository (Perez-Riverol et al., 2018) with the dataset identifier PXD012986.

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.

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.

Reproducibility, Specificity and Accuracy of Relative Quantification Using Spectral Library-based Data-independent Acquisition.

Currently data-dependent acquisition (DDA) is the method of choice for mass spectrometry-based proteomics discovery experiments, but data-independent acquisition (DIA) is steadily becoming more important. One of the most important requirements to perform a DIA analysis is the availability of suitable spectral libraries for peptide identification and quantification. Several studies were performed addressing the evaluation of spectral library performance for protein identification in DIA measurements. But so far only few experiments estimate the effect of these libraries on the quantitative level.In this work we created a gold standard spike-in sample set with known contents and ratios of proteins in a complex protein matrix that allowed a detailed comparison of DIA quantification data obtained with different spectral library approaches. We used in-house generated sample-specific spectral libraries created using varying sample preparation approaches and repeated DDA measurement. In addition, two different search engines were tested for protein identification from DDA data and subsequent library generation. In total, eight different spectral libraries were generated, and the quantification results compared with a library free method, as well as a default DDA analysis. Not only the number of identifications on peptide and protein level in the spectral libraries and the corresponding DIA analysis results was inspected, but also the number of expected and identified differentially abundant protein groups and their ratios.We found, that while libraries of prefractionated samples were generally larger, there was no significant increase in DIA identifications compared with repetitive non-fractionated measurements. Furthermore, we show that the accuracy of the quantification is strongly dependent on the applied spectral library and whether the quantification is based on peptide or protein level. Overall, the reproducibility and accuracy of DIA quantification is superior to DDA in all applied approaches.Data has been deposited to the ProteomeXchange repository with identifiers PXD012986, PXD012987, PXD012988 and PXD014956.

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.

The microRNA miR-375-3p and the Tumor Suppressor NDRG2 are Involved in Sporadic Amyotrophic Lateral Sclerosis.

BACKGROUND/AIMS: Amyotrophic lateral sclerosis (ALS) is the most common degenerative motor neuron disease in humans. However, the pathogenesis of ALS is not yet understood. The wobbler mouse is considered as an animal model for the sporadic form of ALS due to its spontaneous mutation in the Vps54 gene. Due to transactivation of NDRG2 by p53, this tumor suppressor might play a functional role in stress induced cell death in wobbler mice as well as ALS patients. Furthermore, deregulated microRNAs are often related to neurodegenerative diseases. Thus, the NDRG2 linked miR-375-3p was of interest for this study. METHODS: Here, we investigated the relevance of NDRG2 and miR-375-3p for the pathomechanism of the motor neuronal degeneration in wobbler mice by investigating expression level via qPCR and Western Blot as well as localization of these molecules in the cervical spinal cord by in situ hybridization, immunostaining and mass spectrometric analysis. RESULTS: We were able to show a differential regulation of the expression of NDRG2 as well as miR-375-3p in the cervical part of the spinal cord of wobbler mice. In addition, for the first time we were able to demonstrate an expression of NDRG2 in motor neurons using different techniques. CONCLUSION: The present study has shown NDRG2 and miR-375-3p to be promising targets for further research of the pathogenesis of sporadic ALS in the wobbler mouse model. Based on these results and in combination with previous published data we could develop a putative pro-apoptotic mechanism in the spinal cord of the wobbler mouse.

Protein variability in cerebrospinal fluid and its possible implications for neurological protein biomarker research.

Cerebrospinal fluid is investigated in biomarker studies for various neurological disorders of the central nervous system due to its proximity to the brain. Currently, only a limited number of biomarkers have been validated in independent studies. The high variability in the protein composition and protein abundance of cerebrospinal fluid between as well as within individuals might be an important reason for this phenomenon. To evaluate this possibility, we investigated the inter- and intraindividual variability in the cerebrospinal fluid proteome globally, with a specific focus on disease biomarkers described in the literature. Cerebrospinal fluid from a longitudinal study group including 12 healthy control subjects was analyzed by label-free quantification (LFQ) via LC-MS/MS. Data were quantified via MaxQuant. Then, the intra- and interindividual variability and the reference change value were calculated for every protein. We identified and quantified 791 proteins, and 216 of these proteins were abundant in all samples and were selected for further analysis. For these proteins, we found an interindividual coefficient of variation of up to 101.5% and an intraindividual coefficient of variation of up to 29.3%. Remarkably, these values were comparably high for both proteins that were published as disease biomarkers and other proteins. Our results support the hypothesis that natural variability greatly impacts cerebrospinal fluid protein biomarkers because high variability can lead to unreliable results. Thus, we suggest controlling the variability of each protein to distinguish between good and bad biomarker candidates, e.g., by utilizing reference change values to improve the process of evaluating potential biomarkers in future studies.

Characterization of Cerebrospinal Fluid via Data-Independent Acquisition Mass Spectrometry.

Cerebrospinal fluid (CSF) is in direct contact with the brain and serves as a valuable specimen to examine diseases of the central nervous system through analyzing its components. These include the analysis of metabolites, cells as well as proteins. For identifying new suitable diagnostic protein biomarkers bottom-up data-dependent acquisition (DDA) mass spectrometry-based approaches are most popular. Drawbacks of this method are stochastic and irreproducible precursor ion selection. Recently, data-independent acquisition (DIA) emerged as an alternative method. It overcomes several limitations of DDA, since it combines the benefits of DDA and targeted methods like selected reaction monitoring (SRM). We established a DIA method for in-depth proteome analysis of CSF. For this, four spectral libraries were generated with samples from native CSF ( n = 5), CSF fractionation (15 in total) and substantia nigra fractionation (54 in total) and applied to three CSF DIA replicates. The DDA and DIA methods for CSF were conducted with the same nanoLC parameters using a 180 min gradient. Compared to a conventional DDA method, our DIA approach increased the number of identified protein groups from 648 identifications in DDA to 1574 in DIA using a comprehensive spectral library generated with DDA measurements from five native CSF and 54 substantia nigra fractions. We also could show that a sample specific spectral library generated from native CSF only increased the identification reproducibility from three DIA replicates to 90% (77% with a DDA method). Moreover, by utilizing a substantia nigra specific spectral library for CSF DIA, over 60 brain-originated proteins could be identified compared to only 11 with DDA. In conclusion, the here presented optimized DIA method substantially outperforms DDA and could develop into a powerful tool for biomarker discovery in CSF. Data are available via ProteomeXchange with the identifiers PXD010698, PXD010708, PXD010690, PXD010705, and PXD009624.

Isolation of Distinct Types of Neurons from Fresh Brain Tissue Using Laser Microdissection in Combination with High-Performance Liquid Chromatography-Mass Spectrometry.

Humans age and the ageing process affects cells in all areas of the human body, including nerve cells within the brain. With advancing age there is also a rise in the probability of developing a neurodegenerative disorder such as, e.g., amyotrophic lateral sclerosis, Huntington's disease, Parkinson's disease, or Alzheimer's disease. In all these age-related neurodegenerative disorders, distinct neuron populations within specific brain regions are primarily affected. For example, Parkinson's disease is characterized by a slowly progressive degeneration of dopaminergic neurons in the substantia nigra whereas the entorhinal cortex is first affected in Alzheimer's disease. In patients suffering from Huntington's disease, neurons in both striatum and cortex undergo substantial cell loss and in amyotrophic lateral sclerosis the neurodegeneration arises from the spinal cord and the motor cortex. For the investigation of the differences in neuronal vulnerability, it is important to examine the protein expression pattern in these specific neural populations. By this, conclusions about the origination process of these diseases can be achieved. In order to obtain this objective, specific isolation of distinct neurons from the surrounding brain tissue is indispensable. However, discrimination as well as isolation of distinct types of neurons can be challenging, due to the brain tissue's complexity. With traditional methods such as the homogenization of tissue samples, a specific isolation of single neuron populations is not feasible because homogenization results into a mixture containing all cell types. Laser microdissection can overcome this technical limitation. First, this method enables visualization of tissues via a microscopic unit and therefore an enhanced discrimination of different brain cells. Second, a laser device guarantees a contact-free and consequently a contamination-free separation of distinct neurons from the surrounding brain tissue. In the following, we present a detailed protocol that includes a workflow for the isolation and analysis of neurons from freshly frozen post mortem human brain tissue samples. During this procedure, the brain tissue is sectioned, stained, laser microdissected, and ultimately analyzed by high-performance liquid chromatography-mass spectrometry.

Proteomic characterization of neuromelanin granules isolated from human substantia nigra by laser-microdissection.

Neuromelanin is a complex polymer pigment found primarily in the dopaminergic neurons of human substantia nigra. Neuromelanin pigment is stored in granules including a protein matrix and lipid droplets. Neuromelanin granules are yet only partially characterised regarding their structure and function. To clarify the exact function of neuromelanin granules in humans, their enrichment and in-depth characterization from human substantia nigra is necessary. Previously published global proteome studies of neuromelanin granules in human substantia nigra required high tissue amounts. Due to the limited availability of human brain tissue we established a new method based on laser microdissection combined with mass spectrometry for the isolation and analysis of neuromelanin granules. With this method it is possible for the first time to isolate a sufficient amount of neuromelanin granules for global proteomics analysis from ten 10 µm tissue sections. In total 1,000 proteins were identified associated with neuromelanin granules. More than 68% of those proteins were also identified in previously performed studies. Our results confirm and further extend previously described findings, supporting the connection of neuromelanin granules to iron homeostasis and lysosomes or endosomes. Hence, this method is suitable for the donor specific enrichment and proteomic analysis of neuromelanin granules.

Enrichment of single neurons and defined brain regions from human brain tissue samples for subsequent proteome analysis.

Brain function in normal aging and neurological diseases has long been a subject of interest. With current technology, it is possible to go beyond descriptive analyses to characterize brain cell populations at the molecular level. However, the brain comprises over 100 billion highly specialized cells, and it is a challenge to discriminate different cell groups for analyses. Isolating intact neurons is not feasible with traditional methods, such as tissue homogenization techniques. The advent of laser microdissection techniques promises to overcome previous limitations in the isolation of specific cells. Here, we provide a detailed protocol for isolating and analyzing neurons from postmortem human brain tissue samples. We describe a workflow for successfully freezing, sectioning and staining tissue for laser microdissection. This protocol was validated by mass spectrometric analysis. Isolated neurons can also be employed for western blotting or PCR. This protocol will enable further examinations of brain cell-specific molecular pathways and aid in elucidating distinct brain functions.

Proteomics in neurodegenerative diseases: Methods for obtaining a closer look at the neuronal proteome.

The analysis of brain function in normal aging and neurodegenerative, psychiatric, and neurological diseases has long been a subject of interest and has historically been investigated through descriptive analysis of macroscopic or microscopic observations. It is now possible to characterize brain cells, such as neurons and glial cells, or even their subcellular components, at the molecular level. This ability enables researchers to more closely examine brain cell specific molecular pathways to elucidate distinct brain functions. Furthermore, the analysis of neuronal maintenance and disease-causing effects is a central component of neurological investigations, which include proteomic approaches. Proteomics allows the identification of thousands of proteins through descriptive and comparative analyses and can provide a detailed overview of a distinct cellular state. Such analyses often require the isolation of individual cell types or subcellular components to investigate specific questions. This review provides an overview of the currently applied state-of-the-art prefractionation strategies in this field.