Aggregation Methods for Quantifying PTM and Structural Changes in Bottom-Up Proteomics.

High resolution data-independent acquisition with electron transfer dissociation mass spectrometry: Multiplexed analysis of post-translationally modified proteins

Many bacterial hosts in recent years have been shown to have a profound effect on host behavior, and the endosymbiotic alphaproteobacteria Wolbachia is no exception. Present in at least 40% of the insect population, the maternally transmitted Wolbachia modulates behaviors such as male aggression, mate selection, and migration. Wolbachia have also been shown to change host response to olfactory cues, influence life span, and prevent infection by certain pathogens. This last feature of Wolbachia, specifically the prevention of infection by viral pathogens such as Dengue, Zika, and Chikungunya in mosquitos, has become of recent interest as a potential mechanism to suppress transmission of these disease‐causing viruses to humans.To tease apart the mechanisms by which Wolbachia influences host behavior and viral suppression, Drosophila, a genetically tractable model organism that is commonly used to delve into the molecular and cell biology of the symbiont behavioral, was used. A proteomic screen of changes in the Drosophila brain upon Wolbachia infection was performed using 2D Differential Gel Electrophoresis and LC‐MS. Protein abundance changes and post translational modification changes were observed and compared in both Drosophila simulans and Drosophila melanogaster as well as between male and female populations. Post translational modification changes were observed in multiple metabolic proteins and proteins responsible for neurotransmitter synthesis. This study describes the protein and post translational changes identified after Wolbachia infection and how they might contribute to behavioral changes in the host.This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

Cerebrospinal fluid (CSF) proteins and their structures have been implicated repeatedly in aging and neurodegenerative diseases. Limited proteolysis-mass spectrometry (LiP-MS) is a method that enables proteome-wide screening for changes in both protein abundance and structure. To screen for novel aging-associated changes in the CSF proteome, we performed LiP-MS on CSF from young and old mice with a modified analysis pipeline. We found 38 protein groups change in abundance with aging, most dominantly immunoglobulins of the IgM subclass. We discovered six high-confidence candidates that appeared to change in structure with aging, of which Kng1, Itih2, Lp-PLA2, and 14-3-3 proteins have binding partners or proteoforms known previously to change in the brain with Alzheimer's disease. Intriguingly, using orthogonal validation by Western blot we found the LiP-MS hit Cd5l forms a covalent complex with IgM in mouse and human CSF whose abundance increases with aging. SOMAmer probe signals for all six LiP-MS hits in human CSF, especially 14-3-3 proteins, significantly associate with several clinical features relevant to cognitive function and neurodegeneration. Together, our findings show that LiP-MS can uncover age-related structural changes in CSF with relevance to neurodegeneration.

Alzheimer's disease (AD) is characterized by progressive neurodegeneration and protein misfolding, yet the structural dynamics of proteins and their post-translational modifications during disease progression remain poorly understood. Here, we present an integrated structural and glycoproteomic analysis of paired serum and cerebrospinal fluid (CSF) samples from individuals across three clinical stages: normal cognition, mild cognitive impairment, and AD. Using limited proteolysis mass spectrometry (LiP-MS) combined with high-field asymmetric waveform ion mobility spectrometry and data-independent acquisition, we identified 54 proteins exhibiting structural alterations, two of which (clusterin and ceruloplasmin) showed structural changes in both serum and CSF. Furthermore, our findings reveal potential crosstalk between protein structural changes and N-glycosylation, supported by correlations between LiP-derived structural features and glycosylation patterns in key proteins, such as haptoglobin and kininogen-1. This study demonstrates that integrating structural proteomics with glycoproteomics in matched serum and CSF samples enhances biomarker discovery and provides novel insights into the molecular mechanisms of AD. Our approach offers a powerful platform for identifying robust, minimally invasive biomarkers and for understanding post-translational modification-induced protein remodeling in neurodegenerative diseases.

As part of a comprehensive survey of the impact of the environmental pollutant and hepatocarcinogen 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) on the proteome of hepatic cells, we have performed a high resolution two-dimensional gel electrophoresis study on the rat hepatoma cell line 5L. 78 protein species corresponding to 73 different proteins were identified as up- or down-regulated following exposure of the cells to 1 nm TCDD for 8 h. There was an overlap of only nine proteins with those detected as altered by TCDD in our recent study using the non-gel-based isotope-coded protein label method (Sarioglu, H., Brandner, S., Jacobsen, C., Meindl, T., Schmidt, A., Kellermann, J., Lottspeich, F., and Andrae, U. (2006) Quantitative analysis of 2,3,7,8-tetrachlorodibenzo-p-dioxin-induced proteome alterations in 5L rat hepatoma cells using isotope-coded protein labels. Proteomics 6, 2407-2421) indicating a strong complementarity of the two approaches. For the majority of the altered proteins, an effect of TCDD on their abundance or posttranslational modifications had not been known before. Several observations suggest that a sizable fraction of the proteins with altered abundance was induced as an adaptive response to TCDD-induced oxidative stress that was demonstrated using the fluorescent probe dihydrorhodamine 123. A prominent group of these proteins comprised various enzymes for which there is evidence that their expression is regulated via the Keap1/Nrf2/antioxidant response element pathway. Other proteins included several involved in the maintenance of mitochondrial energy production and the regulation of the mitochondrial apoptotic pathway. A particularly intriguing finding was the up-regulation of the mitochondrial outer membrane pore protein, voltage-dependent anion channel-selective protein 2 (VDAC2), which was dependent on the presence of a functional aryl hydrocarbon receptor. The regulatability of VDAC2 protein abundance has not been described previously. In view of the recently discovered central role of VDAC2 as an inhibitor of the activation of the proapoptotic protein BAK and the mitochondrial apoptotic pathway, the present data point to a hitherto unrecognized mechanism by which TCDD may affect cellular homeostasis and survival.

Bottom-up proteomics relies on the use of proteases and is the method of choice for identifying thousands of protein groups in complex samples. Top-down proteomics has been shown to be robust for direct analysis of small proteins and offers a solution to the “peptide-to-protein” inference problem inherent with bottom-up approaches. Here, we describe the first large-scale integration of genomic, bottom-up and top-down proteomic data for the comparative analysis of patient-derived mouse xenograft models of basal and luminal B human breast cancer, WHIM2 and WHIM16, respectively. Using these well-characterized xenograft models established by the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium, we compared and contrasted the performance of bottom-up and top-down proteomics to detect cancer-specific aberrations at the peptide and proteoform levels and to measure differential expression of proteins and proteoforms. Bottom-up proteomic analysis of the tumor xenografts detected almost 10 times as many coding nucleotide polymorphisms and peptides resulting from novel splice junctions than top-down. For proteins in the range of 0–30 kDa, where quantitation was performed using both approaches, bottom-up proteomics quantified 3,519 protein groups from 49,185 peptides, while top-down proteomics quantified 982 proteoforms mapping to 358 proteins. Examples of both concordant and discordant quantitation were found in a ∼60:40 ratio, providing a unique opportunity for top-down to fill in missing information. The two techniques showed complementary performance, with bottom-up yielding eight times more identifications of 0–30 kDa proteins in xenograft proteomes, but failing to detect differences in certain posttranslational modifications (PTMs), such as phosphorylation pattern changes of alpha-endosulfine. This work illustrates the potency of a combined bottom-up and top-down proteomics approach to deepen our knowledge of cancer biology, especially when genomic data are available.

The Age of Omics-Driven Precision Medicine.

Diurnal dark to light transition causes profound physiological changes in plant metabolism. These changes require distinct modes of regulation as a unique feature of photosynthetic lifestyle. The activities of several key metabolic enzymes are regulated by light-dependent post-translational modifications (PTM) and have been studied at depth at the level of individual proteins. In contrast, a global picture of the light-dependent PTMome dynamics is lacking, leaving the response of a large proportion of cellular function undefined. Here, we investigated the light-dependent metabolome and proteome changes in Arabidopsis rosettes in a time resolved manner to dissect their kinetic interplay, focusing on phosphorylation, lysine acetylation, and cysteine-based redox switches. Of over 24 000 PTM sites that were detected, more than 1700 were changed during the transition from dark to light. While the first changes, as measured 5 min after onset of illumination, occurred mainly in the chloroplasts, PTM changes at proteins in other compartments coincided with the full activation of the Calvin-Benson cycle and the synthesis of sugars at later timepoints. Our data reveal connections between metabolism and PTM-based regulation throughout the cell. The comprehensive multiome profiling analysis provides unique insight into the extent by which photosynthesis reprograms global cell function and adds a powerful resource for the dissection of diverse cellular processes in the context of photosynthetic function.

Proteomics is the large scale study of protein structure and function from biological systems through protein identification and quantification. "Shotgun proteomics" or "bottom-up proteomics" is the prevailing strategy, in which proteins are hydrolyzed into peptides that are analyzed by mass spectrometry. Proteomics studies can be applied to diverse studies ranging from simple protein identification to studies of proteoforms, protein-protein interactions, protein structural alterations, absolute and relative protein quantification, post-translational modifications, and protein stability. To enable this range of different experiments, there are diverse strategies for proteome analysis. The nuances of how proteomic workflows differ may be challenging to understand for new practitioners. Here, we provide a comprehensive overview of different proteomics methods. We cover from biochemistry basics and protein extraction to biological interpretation and orthogonal validation. We expect this Review will serve as a handbook for researchers who are new to the field of bottom-up proteomics.

Hemoglobin (Hb) adducts are widely used in human biomonitoring due to the high abundance of hemoglobin in human blood, its reactivity toward electrophiles, and adducted protein stability for up to 120 days. In the present paper, we compared three methods of analysis of hemoglobin adducts: mass spectrometry of derivatized N-terminal Val adducts, mass spectrometry of N-terminal adducted hemoglobin peptides, and limited proteolysis mass spectrometry . Blood from human donors was incubated with a selection of contact allergens and other electrophiles, after which hemoglobin was isolated and subjected to three analysis methods. We found that the FIRE method was able to detect and reliably quantify N-terminal adducts of acrylamide, acrylic acid, glycidic acid, and 2,3-epoxypropyl phenyl ether (PGE), but it was less efficient for 2-methyleneglutaronitrile (2-MGN) and failed to detect 1-chloro-2,4-dinitrobenzene (DNCB). By contrast, bottom-up proteomics was able to determine the presence of adducts from all six electrophiles at both the N-terminus and reactive hemoglobin side chains. Limited proteolysis mass spectrometry, studied for four contact allergens (three electrophiles and a metal salt), was able to determine the presence of covalent hemoglobin adducts with one of the three electrophiles (DNCB) and coordination complexation with the nickel salt. Together, these approaches represent complementary tools in the study of the hemoglobin adductome.

Post‐translational modification and phenotype

Here, we present FLiPPR, or FragPipe LiP (limited proteolysis) Processor, a tool that facilitates the analysis of data from limited proteolysis mass spectrometry (LiP-MS) experiments following primary search and quantification in FragPipe. LiP-MS has emerged as a method that can provide proteome-wide information on protein structure and has been applied to a range of biological and biophysical questions. Although LiP-MS can be carried out with standard laboratory reagents and mass spectrometers, analyzing the data can be slow and poses unique challenges compared to typical quantitative proteomics workflows. To address this, we leverage the fast, sensitive, and accurate search and label-free quantification algorithms in FragPipe and then process its output in FLiPPR. FLiPPR formalizes a specific data imputation heuristic that carefully uses missing data in LiP-MS experiments to report on the most significant structural changes. Moreover, FLiPPR introduces a new data merging scheme (from ions to cut-sites) and a protein-centric multiple hypothesis correction scheme, collectively enabling processed LiP-MS datasets to be more robust and less redundant. These improvements substantially strengthen statistical trends when previously published data are reanalyzed with the FragPipe/FLiPPR workflow. As a final feature, FLiPPR facilitates the collection of structural metadata to identify correlations between experiments and structural features. We hope that FLiPPR will lower the barrier for more users to adopt LiP-MS, standardize statistical procedures for LiP-MS data analysis, and systematize output to facilitate eventual larger-scale integration of LiP-MS data.

Exposure of the skin to ionizing radiation leads to characteristic reactions that will often turn into a pathophysiological process called the cutaneous radiation syndrome. The study of this disorder is crucial to finding diagnostic and prognostic bioindicators of local radiation exposure or radiation effects. It is known that irradiation alters the serum proteome content and potentially post-translationally modifies serum proteins. In this study, we investigated whether localized irradiation of the skin alters the serum glycome. Two-dimensional differential in-gel electrophoresis of serum proteins from a man and from mice exposed to ionizing radiation showed that potential post-translational modification changes occurred following irradiation. Using a large-scale quantitative mass-spectrometry-based glycomic approach, we performed a global analysis of glycan structures of serum proteins from non-irradiated and locally irradiated mice exposed to high doses of γ-rays (20, 40, and 80 Gy). Non-supervised descriptive statistical analyses (principal component analysis) using quantitative glycan structure data allowed us to discriminate between uninjured/slightly injured animals and animals that developed severe lesions. Decisional statistics showed that several glycan families were down-regulated whereas others increased, and that particular structures were statistically significantly changed in the serum of locally irradiated mice. The observed increases in multiantennary N-glycans and in outer branch fucosylation and sialylation were associated with the up-regulation of genes involved in glycosylation in the liver, which is the main producer of serum proteins, and with an increase in the key proinflammatory serum cytokines IL-1β, IL-6, and TNFα, which can regulate the expression of glycosylation genes. Our results suggest for the first time a role of serum protein glycosylation in response to irradiation. These protein-associated glycan structure changes might signal radiation exposure or effects.

Citrullination of arginine residues is a post-translational modification (PTM) found on myelin basic protein (MBP), which neutralizes MBPs positive charge, and is implicated in myelin damage and multiple sclerosis (MS). Here we identify lysine acetylation as another neutralizing PTM to MBP that may be involved in myelin damage. We quantify changes in lysine and arginine PTMs on MBP derived from mice induced with an experimental autoimmune encephalomyelitis (EAE) model of MS using liquid chromatography tandem mass spectrometry. The changes in PTMs are correlated to changes in neurological disability scoring (NDS), as a marker of myelin damage. We found that lysine acetylation increased by 2-fold on MBP during peak NDS post-EAE induction. We also found that mono- and dimethyl-lysine, as well as asymmetric dimethyl-arginine residues on MBP were elevated at peak EAE disability. These findings suggest that the acetylation and methylation of lysine on MBP are PTMs associated with the neurological disability produced by EAE. Since histone deacetylase (HDAC) inhibitors have been previously shown to improve neurological disability, we also show that treatment with trichostatin A (a HDAC inhibitor) improves the NDS of EAE mice but does not change MBP acetylation.

Studies of the Plasmodium falciparum transcriptome have shown that the tightly controlled progression of the parasite through the intra-erythrocytic developmental cycle (IDC) is accompanied by a continuous gene expression cascade in which most expressed genes exhibit a single transcriptional peak. Because the biochemical and cellular functions of most genes are mediated by the encoded proteins, understanding the relationship between mRNA and protein levels is crucial for inferring biological activity from transcriptional gene expression data. Although studies on other organisms show that <50% of protein abundance variation may be attributable to corresponding mRNA levels, the situation in Plasmodium is further complicated by the dynamic nature of the cyclic gene expression cascade. In this study, we simultaneously determined mRNA and protein abundance profiles for P. falciparum parasites during the IDC at 2-hour resolution based on oligonucleotide microarrays and two-dimensional differential gel electrophoresis protein gels. We find that most proteins are represented by more than one isoform, presumably because of post-translational modifications. Like transcripts, most proteins exhibit cyclic abundance profiles with one peak during the IDC, whereas the presence of functionally related proteins is highly correlated. In contrast, the abundance of most parasite proteins peaks significantly later (median 11 h) than the corresponding transcripts and often decreases slowly in the second half of the IDC. Computational modeling indicates that the considerable and varied incongruence between transcript and protein abundance may largely be caused by the dynamics of translation and protein degradation. Furthermore, we present cyclic abundance profiles also for parasite-associated human proteins and confirm the presence of five human proteins with a potential role in antioxidant defense within the parasites. Together, our data provide fundamental insights into transcript-protein relationships in P. falciparum that are important for the correct interpretation of transcriptional data and that may facilitate the improvement and development of malaria diagnostics and drug therapy.