The LDL receptor is regulated by membrane cholesterol as revealed by fluorescence fluctuation analysis.

Membrane cholesterol-rich domains have been shown to be important for regulating a range of membrane protein activities. Low-density lipoprotein receptor (LDLR)-mediated internalization of cholesterol-rich LDL particles is tightly regulated by feedback mechanisms involving intracellular sterol sensors. Since LDLR plays a role in maintaining cellular cholesterol homeostasis, we explore the role that membrane domains may have in regulating LDLR activity. We expressed a fluorescent LDLR-mEGFP construct in HEK293T cells and imaged the unligated receptor or bound to an LDL/DiI fluorescent ligand using total internal reflection fluorescence microscopy. We studied the receptor's spatiotemporal dynamics using fluorescence fluctuation analysis methods. Image cross correlation spectroscopy reveals a lower LDL-to-LDLR binding fraction when membrane cholesterol concentrations are augmented using cholesterol esterase, and a higher binding fraction when the cells are treated with methyl-ß-cyclodextrin) to lower membrane cholesterol. This suggests that LDLR's ability to metabolize LDL particles is negatively correlated to membrane cholesterol concentrations. We then tested if a change in activity is accompanied by a change in membrane localization. Image mean-square displacement analysis reveals that unligated LDLR-mEGFP and ligated LDLR-mEGFP/LDL-DiI constructs are transiently confined on the cell membrane, and the size of their confinement domains increases with augmented cholesterol concentrations. Receptor diffusion within the domains and their domain-escape probabilities decrease upon treatment with methyl-ß-cyclodextrin, consistent with a change in receptor populations to more confined domains, likely clathrin-coated pits. We propose a feedback model to account for regulation of LDLR within the cell membrane: when membrane cholesterol concentrations are high, LDLR is sequestered in cholesterol-rich domains. These LDLR populations are attenuated in their efficacy to bind and internalize LDL. However, when membrane cholesterol levels drop, LDL has a higher binding affinity to its receptor and the LDLR transits to nascent clathrin-coated domains, where it diffuses at a slower rate while awaiting internalization.

An economic and robust TMT labeling approach for high throughput proteomic and metaproteomic analysis.

Multiplexed quantitative proteomics using tandem mass tag (TMT) is increasingly used in -omic study of complex samples. While TMT-based proteomics has the advantages of the higher quantitative accuracy, fewer missing values, and reduced instrument analysis time, it is limited by the additional reagent cost. In addition, current TMT labeling workflows involve repeated small volume pipetting of reagents in volatile solvents, which may increase the sample-to-sample variations and is not readily suitable for high throughput applications. In this study, we demonstrated that the TMT labeling procedures could be streamlined by using pre-aliquoted dry TMT reagents in a 96 well plate or 12-tube strip. As little as 50 µg dry TMT per channel was used to label 6-12 µg peptides, yielding high TMT labeling efficiency (∼99%) in both microbiome and mammalian cell line samples. We applied this workflow to analyze 97 samples in a study to evaluate whether ice recrystallization inhibitors improve the cultivability and activity of frozen microbiota. The results demonstrated tight sample clustering corresponding to groups and consistent microbiome responses to prebiotic treatments. This study supports the use of TMT reagents that are pre-aliquoted, dried, and stored for robust quantitative proteomics and metaproteomics in high throughput applications.

MetaLab-MAG: A Metaproteomic Data Analysis Platform for Genome-Level Characterization of Microbiomes from the Metagenome-Assembled Genomes Database.

The studies of microbial communities have drawn increased attention in various research fields such as agriculture, environment, and human health. Recently, metaproteomics has become a powerful tool to interpret the roles of the community members by investigating the expressed proteins of the microbes. However, analyzing the metaproteomic data sets at genome resolution is still challenging because of the lack of efficient bioinformatics tools. Here we develop MetaLab-MAG, a specially designed tool for the characterization of microbiomes from metagenome-assembled genomes databases. MetaLab-MAG was evaluated by analyzing various human gut microbiota data sets and performed comparably or better than searching the gene catalog protein database directly. MetaLab-MAG can quantify the genome-level microbiota compositions and supports both label-free and isobaric labeling-based quantification strategies. MetaLab-MAG removes the obstacles of metaproteomic data analysis and provides the researchers with in-depth and comprehensive information from the microbiomes.

Assessing the Dark Field of Metaproteome.

The human gut microbiome is a complex system composed of hundreds of species, and metaproteomics can be used to explore their expressed functions. However, many lower abundance species are not detected by current metaproteomic techniques and represent the dark field of metaproteomics. We do not know the minimal abundance of a bacterium in a microbiome(depth) that can be detected by shotgun metaproteomics. In this study, we spiked 15N-labeled E. coli peptides at different percentages into peptides mixture derived from the human gut microbiome to evaluate the depth that can be achieved by shotgun metaproteomics. We observed that the number of identified peptides and peptide intensity from 15N-labeled E. coli were linearly correlated with the spike-in levels even when 15N-labeled E. coli was down to 0.5% of the biomass. Below that level, it was not detected. Interestingly, the match-between-run strategy significantly increased the number of quantified peptides even when 15N-labeled E. coli peptides were at low abundance. This is indicative that in metaproteomics of complex gut microbiomes many peptides from low abundant species are likely observable in MS1 but are not selected for MS2 by standard shotgun strategies.

Exploring the Microbiome-Wide Lysine Acetylation, Succinylation, and Propionylation in Human Gut Microbiota.

Lysine acylations are important post-translational modifications that are present in both eukaryotes and prokaryotes and regulate diverse cellular functions. Our knowledge of the microbiome lysine acylation remains limited due to the lack of efficient analytical and bioinformatics methods for complex microbial communities. Here, we show that the serial enrichment using motif antibodies successfully captures peptides containing lysine acetylation, propionylation, and succinylation from human gut microbiome samples. A new bioinformatic workflow consisting of an unrestricted database search confidently identified >60,000 acetylated, and ∼20,000 propionylated and succinylated gut microbial peptides. The characterization of these identified modification-specific metaproteomes, i.e., meta-PTMomes, demonstrates that lysine acylations are differentially distributed in microbial species with different metabolic capabilities. This study provides an analytical framework for the study of lysine acylations in the microbiome, which enables functional microbiome studies at the post-translational level.

Studying the Temporal Dynamics of the Gut Microbiota Using Metabolic Stable Isotope Labeling and Metaproteomics.

The gut microbiome and its metabolic processes are dynamic systems. Surprisingly, our understanding of gut microbiome dynamics is limited. Here, we report a metaproteomic workflow that involves protein stable isotope probing (protein-SIP) and identification/quantification of partially labeled peptides. We also developed a package, which we call MetaProfiler, that corrects for false identifications and performs phylogenetic and time series analysis for the study of microbiome dynamics. From the stool sample of five mice that were fed with 15N hydrolysate from Ralstonia eutropha, we identified 12 326 nonredundant unlabeled peptides, of which 8256 of their heavy counterparts were quantified. These peptides revealed incorporation profiles over time that were different between and within taxa, as well as between and within clusters of orthologous groups (COGs). Our study helps unravel the complex dynamics of protein synthesis and bacterial dynamics in the mouse microbiome. MetaProfiler and the bioinformatic pipeline are available at https://github.com/northomics/MetaProfiler.git.

Differential Lysis Approach Enables Selective Extraction of Taxon-Specific Proteins for Gut Metaproteomics.

Changes in microbiome composition and function have been linked to human health and diseases. Metaproteomics provides invaluable functional information on the state of a microbiome. However, lower-abundance bacteria in complex microbiomes are difficult to observe by metaproteomics. In this study, stepwise differential lysis protocols were developed for human stool microbiomes to separate different microbial species and to increase the depth of metaproteomic measurements. We achieved differential lysis of Gram-positive (G+) and Gram-negative (G-) bacteria, selective enrichment of specific bacteria, and functional enrichment by our stepwise differential lysis protocols. Therefore, differential lysis can serve as a fractionation method to reduce sample complexity and selectively extract proteins from specific taxa for deep metaproteomic studies.

Chemoenzymatic Method for Glycoproteomic N-Glycan Type Quantitation.

Glycosylation is one of the most important post-translational modifications in biological systems. Current glycoproteome methods mainly focus on qualitative identification of glycosylation sites or intact glycopeptides. However, the systematic quantitation of glycoproteins has remained largely unexplored. Here, we developed a chemoenzymatic method to quantitatively investigate N-glycoproteome based on the N-glycan types. Taking advantage of the specificity of different endoglycosidases and isotope dimethyl labeling, six N-glycan types of structures linked on each glycopeptide, including high-mannose/hybrid, biantennary, and triantennary with/without core fucose, were quantified. As a proof of principle, the glycoproteomic N-glycan type quantitative (glyco-TQ) method was first used to determine the N-glycan type composition of the immunoglobulin G1 (IgG1) Fc fragment. Then we applied the method to analyze the glycan type profile of proteins from the breast cancer cell line MCF7, and we quantitatively revealed the N-glycan type microheterogeneity at the glycopeptide and glycoprotein level. The novel quantitative strategy to evaluate the relative intensity of the six states of N-glycan type glycosylation on each site provides a new avenue to investigate the function of glycoproteins in broad areas, such as cancer biomarker research, pharmaceuticals characterization, and antiglycan vaccine development.

The enigma of soluble LDLR: could inflammation be the key?

Soluble low-density lipoprotein receptor (sLDLR) is the circulating ectodomain of transmembrane LDLR. Its blood level strongly correlates with that of triglycerides (TG). This correlation has eluded satisfactory explanation. Hypertriglyceridemia and shedding of the ectodomain of many transmembrane receptors often accompany inflammatory states. The shedding mostly occurs through cleavage by a disintegrin-and-metalloproteinase-17 (ADAM-17), an enzyme activated by inflammation. It reduces the cellular uptake of TG-loaded lipoproteins, causing their accumulation in circulation; hence the correlation between plasma sLDLR and TG. Soluble LDLR could become a new surrogate marker of inflammation.

Metaproteomic and Metabolomic Approaches for Characterizing the Gut Microbiome.

The gut microbiome has been shown to play a significant role in human healthy and diseased states. The dynamic signaling that occurs between the host and microbiome is critical for the maintenance of host homeostasis. Analyzing the human microbiome with metaproteomics, metabolomics, and integrative multi-omics analyses can provide significant information on markers for healthy and diseased states, allowing for the eventual creation of microbiome-targeted treatments for diseases associated with dysbiosis. Metaproteomics enables functional activity information to be gained from the microbiome samples, while metabolomics provides insight into the overall metabolic states affecting/representing the host-microbiome interactions. Combining these functional -omic platforms together with microbiome composition profiling allows for a holistic overview on the functional and metabolic state of the microbiome and its influence on human health. Here the benefits of metaproteomics, metabolomics, and the integrative multi-omic approaches to investigating the gut microbiome in the context of human health and diseases are reviewed.

Therapeutic Targeting of Casein Kinase 1δ/ε in an Alzheimer's Disease Mouse Model.

Sleep disturbances and memory impairment are common symptoms of Alzheimer's disease (AD). Given that the circadian clock regulates sleep, hippocampal function, and neurodegeneration, it represents a therapeutic target against AD. Casein kinase 1δ/ε (CK1δ/ε) are clock regulators and overexpressed in AD brains, making them viable targets to improve sleep and cognition. In this study, we evaluated the therapeutic potential of a small molecule CK1δ/ε inhibitor (PF-670462) in a triple transgenic mouse model of AD (3xTg-AD). Mass spectrometry-based proteomic analyses revealed that PF-670462 administration in 3xTg-AD mice reversed hippocampal proteomic alterations in several AD-related and clock-regulated pathways, including synaptic plasticity and amyloid precursor protein processing. Furthermore, PF-670462 administration rescued working memory deficits and normalized behavioral circadian rhythm disturbances in 3xTg-AD mice. Our study provides in vivo proof of concept for CK1δ/ε inhibition against AD-associated hippocampal proteomic changes, memory impairment, and circadian disturbances.

iMetaLab 1.0: a web platform for metaproteomics data analysis.

Summary: The human gut microbiota, a complex, dynamic and biodiverse community, has been increasingly shown to influence many aspects of health and disease. Metaproteomic analysis has proven to be a powerful approach to study the functionality of the microbiota. However, the processing and analyses of metaproteomic mass spectrometry data remains a daunting task in metaproteomics data analysis. We developed iMetaLab, a web based platform to provide a user-friendly and comprehensive data analysis pipeline with a focus on lowering the technical barrier for metaproteomics data analysis. Availability and implementation: iMetaLab is freely available through at http://imetalab.ca. Supplementary information: Supplementary data are available at Bioinformatics online.

Evaluating in Vitro Culture Medium of Gut Microbiome with Orthogonal Experimental Design and a Metaproteomics Approach.

In vitro culture based approaches are time- and cost-effective solutions for rapidly evaluating the effects of drugs or natural compounds against microbiomes. The nutritional composition of the culture medium is an important determinant for effectively maintaining the gut microbiome in vitro. This study combines orthogonal experimental design and a metaproteomics approach to obtaining functional insights into the effects of different medium components on the microbiome. Our results show that the metaproteomic profile respond differently to medium components, including inorganic salts, bile salts, mucin, and short-chain fatty acids. Multifactor analysis of variance further revealed significant main and interaction effects of inorganic salts, bile salts, and mucin on the different functional groups of gut microbial proteins. While a broad regulating effect was observed on basic metabolic pathways, different medium components also showed significant modulations on cell wall, membrane, and envelope biogenesis and cell motility related functions. In particular, flagellar assembly related proteins were significantly responsive to the presence of mucin. This study provides information on the functional influences of medium components on the in vitro growth of microbiome communities and gives insight on the key components that must be considered when selecting and optimizing media for culturing ex vivo microbiotas.

Quantitative phosphoproteomics reveals involvement of multiple signaling pathways in early phagocytosis by the retinal pigmented epithelium.

One of the major biological functions of the retinal pigmented epithelium (RPE) is the clearance of shed photoreceptor outer segments (POS) through a multistep process resembling phagocytosis. RPE phagocytosis helps maintain the viability of photoreceptors that otherwise could succumb to the high metabolic flux and photo-oxidative stress associated with visual processing. The regulatory mechanisms underlying phagocytosis in the RPE are not fully understood, although dysfunction of this process contributes to the pathogenesis of multiple human retinal degenerative disorders, including age-related macular degeneration. Here, we present an integrated transcriptomic, proteomic, and phosphoproteomic analysis of phagocytosing RPE cells, utilizing three different experimental models: the human-derived RPE-like cell line ARPE-19, cultured murine primary RPE cells, and RPE samples from live mice. Our combined results indicated that early stages of phagocytosis in the RPE are mainly characterized by pronounced changes in the protein phosphorylation level. Global phosphoprotein enrichment analysis revealed involvement of PI3K/Akt, mechanistic target of rapamycin (mTOR), and MEK/ERK pathways in the regulation of RPE phagocytosis, confirmed by immunoblot analyses and in vitro phagocytosis assays. Most strikingly, phagocytosis of POS by cultured RPE cells was almost completely blocked by pharmacological inhibition of phosphorylation of Akt. Our findings, along with those of previous studies, indicate that these phosphorylation events allow the RPE to integrate multiple signals instigated by shed POS at different stages of the phagocytic process.

Mucosal-luminal interface proteomics reveals biomarkers of pediatric inflammatory bowel disease-associated colitis.

OBJECTIVE: Improved biomarkers are an unmet clinical need for suspected inflammatory bowel disease (IBD). Need is greatest for children, since current biomarkers suffers from low specificity, particularly in this population; thus, invasive testing methods, with the accompanying risk of complications, are necessary. Additionally, current biomarkers do not delineate disease extent assessment for ulcerative colitis (UC), a factor involved in therapeutic decisions. METHODS: Intestinal mucosal-luminal interface (MLI) aspirates from the ascending colon (AC) and descending colon (DC) were collected during diagnostic colonoscopy from treatment-naïve children. The MLI proteomes of 18 non-IBD and 42 IBD patients were analyzed by liquid chromatography mass spectrometry. Analyses of proteomic data generated protein panels distinguishing IBD from non-IBD and pancolitis from non-pancolitis (UC disease extent). Select protein biomarkers were evaluated in stool samples by enzyme-linked immunosorbent assay (n = 24). RESULTS: A panel of four proteins discriminated active IBD from non-IBD (discovery cohort) with a sensitivity of 0.954 (95% confidence interval (CI): 0.772-0.999) and >0.999 (95% CI: 0.824-1.00) for the AC and DC, respectively, and a specificity of >0.999 (AC, 95% CI: 0.815-1.00; DC, 95% CI:0.692-1.00) for both the AC and DC. A separate panel of four proteins distinguished pancolitis from non-pancolitis in UC patients with sensitivity >0.999 (95% CI: 0.590-1.00) and specificity >0.999 (95% CI: 0.715-1.00). Catalase (p < 0.0001) and LTA4H (p = 0.0002) were elevated in IBD stool samples compared to non-IBD stool samples. CONCLUSION: This study identified panels of proteins that have significantly different expression levels and contribute to accurate IBD diagnosis and disease extent characterization in children with UC. Biomarkers identified from the MLI demonstrate transferable results in stool samples.

Circulating PCSK9 is lowered acutely following surgery.

BACKGROUND: A decrease in serum low-density lipoprotein cholesterol (LDL-C) is well documented after acute stress. Plasma proprotein convertase subtilisin kexin 9 (PCSK9), which promotes degradation of low-density lipoprotein receptor (LDL-R) resulting in reduced plasma clearance of low-density lipoproteins (LDL) and an increase in serum LDL-C, would be predicted to decrease. Yet, a few studies have demonstrated an increase 1-8 days after acute stress. Our objective was to assess the earlier status of plasma PCSK9, within the first 24 hours of onset of stress. METHODS: We measured serum lipids and plasma PCSK9 in 39 patients before and soon after an elective surgical procedure (abdominal aortic aneurysm (AAA) repair). RESULTS: We observed an early decrease in PCSK9 following surgery, as well as a decrease in total cholesterol (TC), LDL-C, high-density lipoprotein cholesterol (HDL-C), non-high-density lipoprotein cholesterol (non-HDL-C) and triglycerides (TG). CONCLUSION: Unlike other studies which showed an increase in PCSK9 after the onset of stress, our study detected a fall in PCSK9 following acute surgical stress. The observed difference is likely due to the earlier timing of PCSK9 measurement in our study. Further studies involving serial poststress measurements for several days are needed to determine whether PCSK9 behaves as an acute-phase reactant, whether it displays a biphasic response to acute stress, and whether changes in circulating PCSK9 are responsible for lipoprotein changes observed after surgical stress. (Clinical Trial Registration: ClinicalTrials.gov study ID NCT00493389).

Deep Metaproteomics Approach for the Study of Human Microbiomes.

Host-microbiome interactions have been shown to play important roles in human health and diseases. Most of the current studies of the microbiome have been performed by genomic approaches through next-generation sequencing. Technologies, such as metaproteomics, for functional analysis of the microbiome are needed to better understand the intricate host-microbiome interactions. However, significant efforts to improve the depth and resolution of gut metaproteomics are still required. In this study, we combined an efficient sample preparation technique, high resolution mass spectrometry, and metaproteomic bioinformatics tools to perform ultradeep metaproteomic analysis of human gut microbiome from stool. We reported the deepest analysis of the microbiome to date with an average of 20 558 protein groups identified per sample analysis. Moreover, strain resolution taxonomic and pathway analysis using deep metaproteomics revealed strain level variations, in particular for Faecalibacterium prausnitzii, in the microbiome from the different individuals. We also reported that the human proteins identified in stool samples are functionally enriched in extracellular region pathways and in particular those proteins involved in defense response against microbial organisms. Deep metaproteomics is a promising approach to perform in-depth microbiome analysis and simultaneously reveals both human and microbial changes that are not readily apparent using the standard genomic approaches.

The proteomic landscape of the suprachiasmatic nucleus clock reveals large-scale coordination of key biological processes.

The suprachiasmatic nucleus (SCN) acts as the central clock to coordinate circadian oscillations in mammalian behavior, physiology and gene expression. Despite our knowledge of the circadian transcriptome of the SCN, how it impacts genome-wide protein expression is not well understood. Here, we interrogated the murine SCN proteome across the circadian cycle using SILAC-based quantitative mass spectrometry. Of the 2112 proteins that were accurately quantified, 20% (421 proteins) displayed a time-of-day-dependent expression profile. Within this time-of-day proteome, 11% (48 proteins) were further defined as circadian based on a sinusoidal expression pattern with a ∼24 h period. Nine circadianly expressed proteins exhibited 24 h rhythms at the transcript level, with an average time lag that exceeded 8 h. A substantial proportion of the time-of-day proteome exhibited abrupt fluctuations at the anticipated light-to-dark and dark-to-light transitions, and was enriched for proteins involved in several key biological pathways, most notably, mitochondrial oxidative phosphorylation. Additionally, predicted targets of miR-133ab were enriched in specific hierarchical clusters and were inversely correlated with miR133ab expression in the SCN. These insights into the proteomic landscape of the SCN will facilitate a more integrative understanding of cellular control within the SCN clock.

Peptide-Centric Approaches Provide an Alternative Perspective To Re-Examine Quantitative Proteomic Data.

Quantitative proteomics can provide rich information on changes in biological functions and processes. However, its accuracy is affected by the inherent information degeneration found in bottom-up proteomics. Therefore, the precise protein inference from identified peptides can be mistaken since an ad hoc rule is used for generating a list of protein groups that depends on both the sample type and the sampling depth. Herein, we propose an alternative approach for examining quantitative proteomic data which is peptide-centric instead of protein-centric. We discuss the feasibility of the peptide-centric approach which was tested on several quantitative proteomic data sets. We show that peptide-centric quantification has several advantages over protein level analysis: (1) it is more sensitive for sample segregation, (2) it avoids the issues associated with protein inference, and (3) it can retrieve significant peptides lost in protein-centric quantification for further downstream analysis.

In Vitro Metabolic Labeling of Intestinal Microbiota for Quantitative Metaproteomics.

Intestinal microbiota is emerging as one of the key environmental factors influencing or causing the development of numerous human diseases. Metaproteomics can provide invaluable information on the functional activities of intestinal microbiota and on host-microbe interactions as well. However, the application of metaproteomics in human microbiota studies is still largely limited, in part due to the lack of accurate quantitative intestinal metaproteomic methods. Most current metaproteomic microbiota studies are based on label-free quantification, which may suffer from variability during the separate sample processing and mass spectrometry runs. In this study, we describe a quantitative metaproteomic strategy, using in vitro stable isotopically ((15)N) labeled microbiota as a spike-in reference, to study the intestinal metaproteomes. We showed that the human microbiota were efficiently labeled (>95% (15)N enrichment) within 3 days under in vitro conditions, and accurate light-to-heavy protein/peptide ratio measurements were obtained using a high-resolution mass spectrometer and the quantitative proteomic software tool Census. We subsequently employed our approach to study the in vitro modulating effects of fructo-oligosaccharide and five different monosaccharides on the microbiota. Our methodology improves the accuracy of quantitative intestinal metaproteomics, which would promote the application of proteomics for functional studies of intestinal microbiota.