Multidimensional proteomics for cell biology

The proteome and its dynamics: A missing piece for integrative multi-omics in schizophrenia

The complex and heterogeneous pathophysiology of schizophrenia can be deconstructed by integration of large-scale datasets encompassing genes through behavioral phenotypes. Genome-wide datasets are now available for genetic, epigenetic and transcriptomic variations in schizophrenia, which are then analyzed by newly devised systems biology algorithms. A missing piece, however, is the inclusion of information on the proteome and its dynamics in schizophrenia. Proteomics has lagged behind omics of the genome, transcriptome and epigenome since analytic platforms were relatively less robust for proteins. There has been remarkable progress, however, in the instrumentation of liquid chromatography (LC) and mass spectrometry (MS) (LCMS), experimental paradigms and bioinformatics of the proteome. Here, we present a summary of methodological innovations of recent years in MS based proteomics and the power of new generation proteomics, review proteomics studies that have been conducted in schizophrenia to date, and propose how such data can be analyzed and integrated with other omics results. The function of a protein is determined by multiple molecular properties, i.e., subcellular localization, posttranslational modification (PTMs) and protein-protein interactions (PPIs). Incorporation of these properties poses additional challenges in proteomics and their integration with other omics; yet is a critical next step to close the loop of multi-omics integration. In sum, the recent advent of high-throughput proteome characterization technologies and novel mathematical approaches enable us to incorporate functional properties of the proteome to offer a comprehensive multi-omics based understanding of schizophrenia pathophysiology.

Review of Three-Dimensional Liquid Chromatography Platforms for Bottom-Up Proteomics

Proteomics is a large-scale study of proteins, aiming at the description and characterization of all expressed proteins in biological systems. The expressed proteins are typically highly complex and large in abundance range. To fulfill high accuracy and sensitivity of proteome analysis, the hybrid platforms of multidimensional (MD) separations and mass spectrometry have provided the most powerful solution. Multidimensional separations provide enhanced peak capacity and reduce sample complexity, which enables mass spectrometry to analyze more proteins with high sensitivity. Although two-dimensional (2D) separations have been widely used since the early period of proteomics, three-dimensional (3D) separation was barely used by low reproducibility of separation, increased analysis time in mass spectrometry. With developments of novel microscale techniques such as nano-UPLC and improvements of mass spectrometry, the 3D separation becomes a reliable and practical selection. This review summarizes existing offline and online 3D-LC platforms developed for proteomics and their applications. In detail, setups and implementation of those systems as well as their advances are outlined. The performance of those platforms is also discussed and compared with the state-of-the-art 2D-LC. In addition, we provide some perspectives on the future developments and applications of 3D-LC in proteomics.

Toxicity of mycotoxins in vivo on vertebrate organisms: A review

Mycotoxins are considered to be a major risk factor affecting human and animal health as they are one of the most dangerous contaminants of food and feed. This review aims to compile the research developed up to date on the toxicological effects that mycotoxins can induce on human health, through the examination of a selected number of studies in vivo. AFB1 shows to be currently the most studied mycotoxin in vivo, followed by DON, ZEA and OTA. Scarce data was found for FBs, PAT, CIT, AOH and Fusarium emerging mycotoxins. The majority of them concerned the investigation of immunotoxicity, whereas the rest consisted in the study of genotoxicity, oxidative stress, hepatotoxicity, cytotoxicity, teratogenicity and neurotoxicity. In order to assess the risk, a wide range of different techniques have been employed across the reviewed studies: qPCR, ELISA, IHC, WB, LC-MS/MS, microscopy, enzymatic assays, microarray and RNA-Seq. In the last decade, the attention has been drawn to immunologic and transcriptomic aspects of mycotoxins' action, confirming their toxicity at molecular level. Even though, more in vivo studies are needed to further investigate their mechanism of action on human health.

Protein Turnover in Epithelial Cells and Mucus along the Gastrointestinal Tract Is Coordinated by the Spatial Location and Microbiota

The gastrointestinal tract is covered by a single layer of epithelial cells that, together with the mucus layers, protect the underlying tissue from microbial invasion. The epithelium has one of the highest turnover rates in the body. Using stable isotope labeling, high-resolution mass spectrometry, and computational analysis, we report a comprehensive dataset of the turnover of more than 3,000 and the expression of more than 5,000 intestinal epithelial cell proteins, analyzed under conventional and germ-free conditions across five different segments in mouse intestine. The median protein half-life is shorter in the small intestine than in the colon. Differences in protein turnover rates along the intestinal tract can be explained by distinct physiological and immune-related functions between the small and large intestine. An absence of microbiota results in an approximately 1 day longer protein half-life in germ-free animals.

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Dataset of protein turnover rate and expression along the mice intestinal tract

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Protein turnover rate is slower in colon than in small intestine

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Median protein half-life is 1 day longer in germ-free mice

Dissecting intercellular signaling with mass spectrometry-based proteomics

Physiological functions depend on a coordinated interplay of numerous different cell types. Proteins serve as major signaling molecules between cells; however, their comprehensive investigation in physiologically relevant settings has remained challenging. Mass spectrometry (MS)-based shotgun proteomics is emerging as a powerful technology for the systematic analysis of protein-mediated intercellular signaling and regulated post-translational modifications. Here, we discuss recent advancements in cell biological, chemical, and biochemical MS-based approaches for the profiling of cellular messengers released by sending cells, receptors expressed on the cell surface, and their interactions. We highlight methods tailored toward the mapping of dynamic signal transduction mechanisms at cellular interfaces and approaches to dissect communication cell specifically in heterocellular systems. Thereby, MS-based proteomics contributes a unique systems biology perspective for the identification of intercellular signaling pathways deregulated in disease.

Next-generation Interactomics: Considerations for the Use of Co-elution to Measure Protein Interaction Networks

Understanding how proteins interact is crucial to understanding cellular processes. Among the available interactome mapping methods, co-elution stands out as a method that is simultaneous in nature and capable of identifying interactions between all the proteins detected in a sample. The general workflow in co-elution methods involves the mild extraction of protein complexes and their separation into several fractions, across which proteins bound together in the same complex will show similar co-elution profiles when analyzed appropriately. In this review we discuss the different separation, quantification and bioinformatic strategies used in co-elution studies, and the important considerations in designing these studies. The benefits of co-elution versus other methods makes it a valuable starting point when asking questions that involve the perturbation of the interactome.

CETSA in integrated proteomics studies of cellular processes

The Cellular Thermal Shift Assay (CETSA) has recently emerged as a promising method to directly monitor functional modulations of protein interaction states in intact cells and tissue samples. Recent data support that the mass spectrometry-coupled proteome-wide implementation of CETSA (MS-CETSA) generates stringent information on a wide range of different interaction classes and is uniquely well suited to study the modulation of protein interaction states in cellular processes and during drug action. To expand the mechanistic insight of CETSA shifts, and to complement information from CETSA experiments, we outline how the integration of MS-CETSA with other proteomics techniques can provide a new platform for detailed, comprehensive, and interactive studies of the functional modulations of proteomes in situ.

ProtRank: bypassing the imputation of missing values in differential expression analysis of proteomic data

Background

Data from discovery proteomic and phosphoproteomic experiments typically include missing values that correspond to proteins that have not been identified in the analyzed sample. Replacing the missing values with random numbers, a process known as “imputation”, avoids apparent infinite fold-change values. However, the procedure comes at a cost: Imputing a large number of missing values has the potential to significantly impact the results of the subsequent differential expression analysis.

Results

We propose a method that identifies differentially expressed proteins by ranking their observed changes with respect to the changes observed for other proteins. Missing values are taken into account by this method directly, without the need to impute them. We illustrate the performance of the new method on two distinct datasets and show that it is robust to missing values and, at the same time, provides results that are otherwise similar to those obtained with edgeR which is a state-of-art differential expression analysis method.

Conclusions

The new method for the differential expression analysis of proteomic data is available as an easy to use Python package.

Multibatch TMT Reveals False Positives, Batch Effects and Missing Values

Multiplexing strategies for large-scale proteomic analyses have become increasingly prevalent, tandem mass tags (TMT) in particular. Here we used a large iPSC proteomic experiment with twenty-four 10-plex TMT batches to evaluate the effect of integrating multiple TMT batches within a single analysis. We identified a significant inflation rate of protein missing values as multiple batches are integrated and show that this pattern is aggravated at the peptide level. We also show that without normalization strategies to address the batch effects, the high precision of quantitation within a single multiplexed TMT batch is not reproduced when data from multiple TMT batches are integrated.Further, the incidence of false positives was studied by using Y chromosome peptides as an internal control. The iPSC lines quantified in this data set were derived from both male and female donors, hence the peptides mapped to the Y chromosome should be absent from female lines. Nonetheless, these Y chromosome-specific peptides were consistently detected in the female channels of all TMT batches. We then used the same Y chromosome specific peptides to quantify the level of ion coisolation as well as the effect of primary and secondary reporter ion interference. These results were used to propose solutions to mitigate the limitations of multi-batch TMT analyses. We confirm that including a common reference line in every batch increases precision by facilitating normalization across the batches and we propose experimental designs that minimize the effect of cross population reporter ion interference.

Systems biology approach in the formulation of chemically defined media for recombinant protein overproduction

The cell culture medium is an intricate mixture of components which has a tremendous effect on cell growth and recombinant protein production. Regular cell culture medium includes various components, and the decision about which component should be included in the formulation and its optimum amount is an underlying issue in biotechnology industries. Applying conventional techniques to design an optimal medium for the production of a recombinant protein requires meticulous and immense research. Moreover, since the medium formulation for the production of one protein could not be the best choice for another protein, hence, the most suitable media should be determined for each recombinant cell line. Accordingly, medium formulation becomes a laborious, time-consuming, and costly process in biomanufacturing of recombinant protein, and finding alternative strategies for medium development seems to be crucial. In silico modeling is an attractive concept to be adapted for medium formulation due to its high potential to supersede laboratory examinations. By emerging the high-throughput datasets, scientists can disclose the knowledge about the effect of medium components on cell growth and metabolism, and via applying this information through systems biology approach, medium formulation optimization could be accomplished in silico with no need of significant amount of experimentation. This review demonstrates some of the applications of systems biology as a powerful tool for medium development and illustrates the effect of medium optimization with system-level analysis on the production of recombinant proteins in different host cells.

The Encyclopedia of Proteome Dynamics: a big data ecosystem for (prote)omics

Driven by improvements in speed and resolution of mass spectrometers (MS), the field of proteomics, which involves the large-scale detection and analysis of proteins in cells, tissues and organisms, continues to expand in scale and complexity. There is a resulting growth in datasets of both raw MS files and processed peptide and protein identifications. MS-based proteomics technology is also used increasingly to measure additional protein properties affecting cellular function and disease mechanisms, including post-translational modifications, protein-protein interactions, subcellular and tissue distributions. Consequently, biologists and clinicians need innovative tools to conveniently analyse, visualize and explore such large, complex proteomics data and to integrate it with genomics and other related large-scale datasets. We have created the Encyclopedia of Proteome Dynamics (EPD) to meet this need (https://peptracker.com/epd/). The EPD combines a polyglot persistent database and web-application that provides open access to integrated proteomics data for >30 000 proteins from published studies on human cells and model organisms. It is designed to provide a user-friendly interface, featuring graphical navigation with interactive visualizations that facilitate powerful data exploration in an intuitive manner. The EPD offers a flexible and scalable ecosystem to integrate proteomics data with genomics information, RNA expression and other related, large-scale datasets.

A Standardized and Reproducible Proteomics Protocol for Bottom-Up Quantitative Analysis of Protein Samples Using SP3 and Mass Spectrometry

The broad utility of mass spectrometry (MS) for investigating the proteomes of a diverse array of sample types has significantly expanded the use of this technology in biological studies. This widespread use has resulted in a substantial collection of protocols and acquisition approaches designed to obtain the highest-quality data for each experiment. As a result, distilling this information to develop a standard operating protocol for essential workflows, such as bottom-up quantitative shotgun whole proteome analysis, can be complex for users new to MS technology. Further complicating this matter, in-depth description of the methodological choices is seldom given in the literature. In this work, we describe a workflow for quantitative whole proteome analysis that is suitable for biomarker discovery, giving detailed consideration to important stages, including (1) cell lysis and protein cleanup using SP3 paramagnetic beads, (2) quantitative labeling, (3) offline peptide fractionation, (4) MS analysis, and (5) data analysis and interpretation. Special attention is paid to providing comprehensive details for all stages of this proteomics workflow to enhance transferability to external labs. The standardized protocol described here will provide a simplified resource to the proteomics community toward efficient adaptation of MS technology in proteomics studies.

Comparative proteomics analysis reveals the difference during antler regeneration stage between red deer and sika deer

Deer antler, as the only mammalian regenerative appendage, provides an optimal model to study regenerative medicine. Antler harvested from red deer or sika deer were mainly study objects used to disclose the mechanism underlying antler regeneration over past decades. A previous study used proteomic technology to reveal the signaling pathways of antler stem cell derived from red deer. Moreover, transcriptome of antler tip from sika deer provide us with the essential genes, which regulated antler development and regeneration. However, antler comparison between red deer and sika deer has not been well studied. In our current study, proteomics were employed to analyze the biological difference of antler regeneration between sika deer and red deer. The proteomics profile was completed by searching the UniProt database, and differentially expressed proteins were identified by bioinformatic software. Thirty-six proteins were highly expressed in red deer antler, while 144 proteins were abundant in sika deer. GO and KEGG analysis revealed that differentially expressed proteins participated in the regulation of several pathways including oxidative phosphorylation, ribosome, extracellular matrix interaction, and PI3K-Akt pathway.

Nanokits for the electrochemical quantification of enzyme activity in single living cells

The development of more intricate devices for the analysis of enzyme activity in single cells, and even in individual intracellular compartments, would advance the knowledge of cellular heterogeneity and protein function at subcellular locations. This chapter describes construction and implementation of nano-capillary electrodes kits, named as "Nanokits," for unprecedented cost-effective analysis of enzyme activity within single living cells and even at single lysosomes. The nanokit that is specific for the target enzyme is assembled in a nanometer-sized capillary with a working electrode, and electrochemically loaded into the cell allowing the electrochemical quantification of the enzyme activity. Furthermore, the enzyme activity in individual intracellular compartments can be characterized by reversed electrochemical pumping to confine the targeted organelle in the nano-capillary tip with the nanokit. The use of commercially available reagent kits marketed for cell population studies permits direct application of the nano-capillary electrode for targeting a variety of enzymes in single cells. This protocol will likely spark expansion in the number of groups embarking on enzyme activity investigations by clearly providing a cookbook description of new cost-effective technology for single cell analysis.

Proteomics insights into the pathology and prognosis of chronic lymphocytic leukemia

Chronic lymphocytic leukemia (CLL) is an incurable malignant disease of B-lymphocytes characterized by drastically heterogeneous clinical courses. Proteomics is an advanced approach that allows a global profiling of protein expression, providing a valuable chance for the discovery of disease-related proteins. In the last 2 decades, several proteomics studies were conducted on CLL to identify aberrant protein expression underpinning the malignant transformation and progression of the disease. Overall, these studies provided insights into the pathology and prognosis of CLL and reveal protein candidates with the potential to serve as biomarkers and/or therapeutic targets of the tumor. The major findings reported in these studies are discussed here.

Inferring Protein-Protein Interaction Networks From Mass Spectrometry-Based Proteomic Approaches: A Mini-Review

Studying protein-protein interaction networks provide key evidence for the underlying molecular mechanisms. Mass spectrometry-based proteomic approaches have been playing a pivotal role in deciphering these interaction networks, along with precise quantification for individual interactions. In this mini-review we discuss the available techniques and methods for qualitative and quantitative elucidation of protein-protein interaction networks. We then summarize the down-stream computational strategies for identification and quantification of interactions from those techniques. Finally, we highlight the challenges and limitations of current computational pipelines in eliminating false positive interactors, followed by a summary of the innovative algorithms to address these issues, along with the scope for future improvements.

The RTK Interactome: Overview and Perspective on RTK Heterointeractions

Receptor tyrosine kinases (RTKs) play important roles in cell growth, motility, differentiation, and survival. These single-pass membrane proteins are grouped into subfamilies based on the similarity of their extracellular domains. They are generally thought to be activated by ligand binding, which promotes homodimerization and then autophosphorylation in trans. However, RTK interactions are more complicated, as RTKs can interact in the absence of ligand and heterodimerize within and across subfamilies. Here, we review the known cross-subfamily RTK heterointeractions and their possible biological implications, as well as the methodologies which have been used to study them. Moreover, we demonstrate how thermodynamic models can be used to study RTKs and to explain many of the complicated biological effects which have been described in the literature. Finally, we discuss the concept of the RTK interactome: a putative, extensive network of interactions between the RTKs. This RTK interactome can produce unique signaling outputs; can amplify, inhibit, and modify signaling; and can allow for signaling backups. The existence of the RTK interactome could provide an explanation for the irreproducibility of experimental data from different studies and for the failure of some RTK inhibitors to produce the desired therapeutic effects. We argue that a deeper knowledge of RTK interactome thermodynamics can lead to a better understanding of fundamental RTK signaling processes in health and disease. We further argue that there is a need for quantitative, thermodynamic studies that probe the strengths of the interactions between RTKs and their ligands and between different RTKs.

Probe design for super-multiplexed vibrational imaging

Optical microscopy has served biomedical research for decades due to its high temporal and spatial resolutions. Among various optical imaging techniques, fluorescence imaging offers superb sensitivity down to single molecule level but its multiplexing capacity is limited by intrinsically broad bandwidth. To simultaneously capture a vast number of targets, the newly emerging vibrational microscopy technique draws increasing attention as vibration spectroscopy features narrow transition linewidth. Nonetheless, unlike fluorophores that have been studied for centuries, a systematic investigation on vibrational probes is underemphasized. Herein, we reviewed some of the recent developments of vibrational probes for multiplex imaging applications, particularly those serving stimulated Raman scattering (SRS) microscopy, which is one of the most promising vibrational imaging techniques. We wish to summarize the general guidelines for developing bioorthogonal vibrational probes with high sensitivity, chemical specificity and most importantly, tunability to fulfill super-multiplexed optical imaging. Future directions to significantly improve the performance are also discussed.

Single-pot, solid-phase-enhanced sample preparation for proteomics experiments

A critical step in proteomics analysis is the optimal extraction and processing of protein material to ensure the highest sensitivity in downstream detection. Achieving this requires a sample-handling technology that exhibits unbiased protein manipulation, flexibility in reagent use, and virtually lossless processing. Addressing these needs, the single-pot, solid-phase-enhanced sample-preparation (SP3) technology is a paramagnetic bead-based approach for rapid, robust, and efficient processing of protein samples for proteomic analysis. SP3 uses a hydrophilic interaction mechanism for exchange or removal of components that are commonly used to facilitate cell or tissue lysis, protein solubilization, and enzymatic digestion (e.g., detergents, chaotropes, salts, buffers, acids, and solvents) before downstream proteomic analysis. The SP3 protocol consists of nonselective protein binding and rinsing steps that are enabled through the use of ethanol-driven solvation capture on the surface of hydrophilic beads, and elution of purified material in aqueous conditions. In contrast to alternative approaches, SP3 combines compatibility with a substantial collection of solution additives with virtually lossless and unbiased recovery of proteins independent of input quantity, all in a simplified single-tube protocol. The SP3 protocol is simple and efficient, and can be easily completed by a standard user in ~30 min, including reagent preparation. As a result of these properties, SP3 has successfully been used to facilitate examination of a broad range of sample types spanning simple and complex protein mixtures in large and very small amounts, across numerous organisms. This work describes the steps and extensive considerations involved in performing SP3 in bottom-up proteomics, using a simplified protein cleanup scenario for illustration.

Molecular insights into cancer drug resistance from a proteomics perspective

INTRODUCTION

Resistance to chemotherapy and development of specific and effective molecular targeted therapies are major obstacles facing current cancer treatment. Comparative proteomic approaches have been employed for the discovery of putative biomarkers associated with cancer drug resistance and have yielded a number of candidate proteins, showing great promise for both novel drug target identification and personalized medicine for the treatment of drug-resistant cancer. Areas covered: Herein, we review the recent advances and challenges in proteomics studies on cancer drug resistance with an emphasis on biomarker discovery, as well as understanding the interconnectivity of proteins in disease-related signaling pathways. In addition, we highlight the critical role that post-translational modifications (PTMs) play in the mechanisms of cancer drug resistance. Expert opinion: Revealing changes in proteome profiles and the role of PTMs in drug-resistant cancer is key to deciphering the mechanisms of treatment resistance. With the development of sensitive and specific mass spectrometry (MS)-based proteomics and related technologies, it is now possible to investigate in depth potential biomarkers and the molecular mechanisms of cancer drug resistance, assisting the development of individualized therapeutic strategies for cancer patients.

Proteomic Analysis of Human Plasma during Intermittent Fasting

Intermittent fasting (IF) increases lifespan and decreases metabolic disease phenotypes and cancer risk in model organisms, but the health benefits of IF in humans are less clear. Human plasma derived from clinical trials is one of the most difficult sample sets to analyze using mass spectrometry-based proteomics due to the extensive sample preparation required and the need to process many samples to achieve statistical significance. Here, we describe an optimized and accessible device (Spin96) to accommodate up to 96 StageTips, a widely used sample preparation medium enabling efficient and consistent processing of samples prior to LC-MS/MS. We have applied this device to the analysis of human plasma from a clinical trial of IF. In this longitudinal study employing 8-weeks IF, we identified significant abundance differences induced by the IF intervention, including increased apolipoprotein A4 (APOA4) and decreased apolipoprotein C2 (APOC2) and C3 (APOC3). These changes correlated with a significant decrease in plasma triglycerides after the IF intervention. Given that these proteins have a role in regulating apolipoprotein particle metabolism, we propose that IF had a positive effect on lipid metabolism through modulation of HDL particle size and function. In addition, we applied a novel human protein variant database to detect common protein variants across the participants. We show that consistent detection of clinically relevant peptides derived from both alleles of many proteins is possible, including some that are associated with human metabolic phenotypes. Together, these findings illustrate the power of accessible workflows for proteomics analysis of clinical samples to yield significant biological insight.

A Multiplex Fragment-Ion-Based Method for Accurate Proteome Quantification

Multiplex proteome quantification with high accuracy is urgently required to achieve a comprehensive understanding of dynamic cellular and physiological processes. Among the existing quantification strategies, fragment-ion-based methods can provide highly accurate results, but the multiplex capacity is limited to 3-plex. Herein, we developed a multiplex pseudo-isobaric dimethyl labeling (m-pIDL) method to extend the capacity of the fragment-ion-based method to 6-plex by one-step dimethyl labeling with several millidalton and dalton mass differences between precursor ions and enlarging the isolation window of precursor ions to 10 m/ z during data acquisition. m-pIDL showed high quantification accuracy within the 20-fold dynamic range. Notably, the ratio compression was 1.13-fold in a benchmark two-proteome model (5:1 mixed E. coli proteins with HeLa proteins as interference), indicating that by m-pIDL, the ratio distortion of isobaric labeling approaches and the approximate 40% ratio shift of the label-free quantification strategy could be effectively eliminated. Additionally, m-pIDL did not show ratio variation among post-translational modifications (CV = 6.66%), which could benefit the measurement of universal protein properties for proteomic atlases. We further employed m-pIDL to monitor the time-resolved responses of the TGF-β-induced epithelial-mesenchymal transition (EMT) in lung adenocarcinoma A549 cell lines, which facilitated the finding of new potential regulatory proteins. Therefore, the 6-plex quantification of m-pIDL with the remarkably high accuracy might create new prospects for comprehensive proteome analysis.

MaxQuant.Live Enables Global Targeting of More Than 25,000 Peptides

Mass spectrometry (MS)-based proteomics is often performed in a shotgun format, in which as many peptide precursors as possible are selected from full or MS1 scans so that their fragment spectra can be recorded in MS2 scans. Although achieving great proteome depths, shotgun proteomics cannot guarantee that each precursor will be fragmented in each run. In contrast, targeted proteomics aims to reproducibly and sensitively record a restricted number of precursor/fragment combinations in each run, based on prescheduled mass-to-charge and retention time windows. Here we set out to unify these two concepts by a global targeting approach in which an arbitrary number of precursors of interest are detected in real-time, followed by standard fragmentation or advanced peptide-specific analyses. We made use of a fast application programming interface to a quadrupole Orbitrap instrument and real-time recalibration in mass, retention time and intensity dimensions to predict precursor identity. MaxQuant.Live is freely available (www.maxquant.live) and has a graphical user interface to specify many predefined data acquisition strategies. Acquisition speed is as fast as with the vendor software and the power of our approach is demonstrated with the acquisition of breakdown curves for hundreds of precursors of interest. We also uncover precursors that are not even visible in MS1 scans, using elution time prediction based on the auto-adjusted retention time alone. Finally, we successfully recognized and targeted more than 25,000 peptides in single LC-MS runs. Global targeting combines the advantages of two classical approaches in MS-based proteomics, whereas greatly expanding the analytical toolbox.

Prediction of skin anti-aging clinical benefits of an association of ingredients from marine and maritime origins: Ex vivo evaluation using a label-free quantitative proteomic and customized data processing approach

BACKGROUND

The application of ingredients from marine and maritime origins is increasingly common in skin care products, driven by consumer expectations for natural ingredients. However, these ingredients are typically studied for a few isolated in vitro activities.

OBJECTIVES

The purpose of this study was to carry out a comprehensive evaluation of the activity on the skin of an association of ingredients from marine and maritime origins using label-free quantitative proteomic analysis, in order to predict the clinical benefits if used in a skin care product.

METHODS

An aqueous gel containing 6.1% of ingredients from marine and maritime origins (amino acid-enriched giant kelp extract, trace element-enriched seawater, dedifferentiated sea fennel cells) was topically applied on human skin explants. The skin explants' proteome was analyzed in a label-free manner by high-performance liquid nano-chromatography coupled with tandem mass spectrometry. A specific data processing pipeline (CORAVALID) providing an objective and comprehensive interpretation of the statistically relevant biological activities processed the results.

RESULTS

Compared to untreated skin explants, 64 proteins were significantly regulated by the gel treatment (q-value ≤ 0.05). Computer data processing revealed an activity of the ingredients on the epidermis and the dermis. These significantly regulated proteins are involved in gene expression, cell survival and metabolism, inflammatory processes, dermal extracellular matrix synthesis, melanogenesis and keratinocyte proliferation, migration, and differentiation.

CONCLUSIONS

These results suggest that the tested ingredients could help to preserve a healthy epidermis and dermis, and possibly to prevent the visible signs of skin aging.

Brain-derived and circulating vesicle profiles indicate neurovascular unit dysfunction in early Alzheimer's disease

Vascular factors that reduce blood flow to the brain are involved in apparition and progression of dementia. We hypothesized that cerebral hypoperfusion (CH) might alter the molecular compositions of brain intercellular communication mechanisms while affecting the neurovascular unit in preclinical and clinical human dementias. To test that hypothesis, mice were subjected to bilateral common carotid stenosis (BCAS) and the molecular compositions of brain-derived and circulating extracellular vesicles (EVs) were assessed. Murine brain vesicle profiles were then analyzed in parallel with brain EVs from post-mortem subjects affected by preclinical Alzheimer's Disease (AD) and mixed dementias. Brain EVs were identified with molecular mediators of hypoxia responses, neuroprotection and neurotoxicity in BCAS mice, patterns also partially resembled by subjects with preclinical AD and mixed dementias. Together these findings indicate that brain EVs represent a promising source of therapeutic targets and circulating markers of neurovascular insult in idiopathic dementias. Furthermore, the results obtained generate novel and compelling hypotheses about the molecular involvement of the vascular component in the etiology of human dementias.

Deuterium-Free, Three-Plexed Peptide Diethylation for Highly Accurate Quantitative Proteomics

The deuterium, a frequently used stable isotope in isotopic labeling for quantitative proteomics, could deteriorate the accuracy and precision of proteome quantification owing to the retention time shift of deuterated peptides from the hydrogenated counterpart. We introduce a novel three-plexed peptide "diethylation" using only ¹³C isotopologues of acetaldehyde and demonstrate that the accuracy and precision of our method in proteome quantification are significantly superior to the conventional deuterium-based dimethylation labeling in both a single-shot and multidimensional LC-MS/MS analysis of the HeLa proteome. Furthermore, in time-resolved profiling of Xenopus laevis early embryogenesis, our 3-plexed diethylation outperformed isobaric labeling approaches in terms of the quantification accuracy or the number of protein identifications, generating more than two times more differentially expressed proteins. Our cost-effective and highly accurate 3-plexed diethylation method could contribute to various types of quantitative proteomics applications in which three of multiplexity would be sufficient.

Effect of ration level on growth performance, body composition, intermediary metabolism and serum parameters in juvenile Patagonian blennie Eleginops maclovinus

Eleginops maclovinus is an endemic species of the southern cone with beneficial physiological characteristics for aquaculture. However, this species has a low growth rate under captive conditions, and the optimal feed ration together with the metabolic process is unknown. This study aimed to determine the optimum feed ration during 90 days based on growth performance, body composition, intermediary metabolism, and serum parameters. For this, fish were randomly assigned to rations of 0.5, 1, 2 and 4% of body weight. No fish mortality was registered, but all fish, developed fatty liver. The results of weight, length, growth performance (WGR, SGR), and body parameters (HSI, VSI and K) followed a similar pattern, with the lowest values observed in the 0.5% and no significant differences between rations of 1, 2 and 4%. The feed intake and feces increased with the feed ration. However, the percentage of food consumed by the fish decreased with the ration size and the feed conversion ratio was lowest in the 1% ration. Total serum proteins and calcium were lowest in the 0.5% ration and presented no differences in the rations 1, 2 and 4%, while triglyceride content was significantly different only between the rations of 0.5 and 4%. Blood cortisol levels were significantly higher in the rations of 0.5 and 1%, and decreased in rations of 2 and 4%. The lipids, fiber, and energy of the total body mass increased with the feed ration, while dry matter, proteins, and ash of the body decreased to higher feed ration. In liver, triglyceride and protein levels decreased with a larger feed ration, amino acids increased in the rations of 0.5 and 4%, while glucose levels increased in rations of 2 and 4%. Liver enzymes Glucose-6-phosphate dehydrogenase and Glutamate dehydrogenase increased their activity at a higher feed ration, while Glycogen Phosphorylase, Aspartate aminotransferase and 3-Hydroxyacyl-CoA dehydrogenase presented their highest enzymatic activity only in the 4% ration. Fructose-1,6-bisphosphate showed low enzymatic activity in rations of 2 and 4% and Glycerol-3-phosphate dehydrogenase was significantly different only between the ration of 0.5 and 1%. Finally, our results suggests that optimal feed rations for E. maclovinus corresponds to 1% since this ration size produces the highest growth and metabolism with a minimum loss of food and feces present in the environment. Additionally, we recommend to reduce the percentage of fat in the diet to avoid the development of fatty liver.

Combining LOPIT with differential ultracentrifugation for high-resolution spatial proteomics

The study of protein localisation has greatly benefited from high-throughput methods utilising cellular fractionation and proteomic profiling. Hyperplexed Localisation of Organelle Proteins by Isotope Tagging (hyperLOPIT) is a well-established method in this area. It achieves high-resolution separation of organelles and subcellular compartments but is relatively time- and resource-intensive. As a simpler alternative, we here develop Localisation of Organelle Proteins by Isotope Tagging after Differential ultraCentrifugation (LOPIT-DC) and compare this method to the density gradient-based hyperLOPIT approach. We confirm that high-resolution maps can be obtained using differential centrifugation down to the suborganellar and protein complex level. HyperLOPIT and LOPIT-DC yield highly similar results, facilitating the identification of isoform-specific localisations and high-confidence localisation assignment for proteins in suborganellar structures, protein complexes and signalling pathways. By combining both approaches, we present a comprehensive high-resolution dataset of human protein localisations and deliver a flexible set of protocols for subcellular proteomics.

From Molecules to Mechanisms: Functional Proteomics and Its Application to Renal Tubule Physiology

Classical physiological studies using electrophysiological, biophysical, biochemical, and molecular techniques have created a detailed picture of molecular transport, bioenergetics, contractility and movement, and growth, as well as the regulation of these processes by external stimuli in cells and organisms. Newer systems biology approaches are beginning to provide deeper and broader understanding of these complex biological processes and their dynamic responses to a variety of environmental cues. In the past decade, advances in mass spectrometry-based proteomic technologies have provided invaluable tools to further elucidate these complex cellular processes, thereby confirming, complementing, and advancing common views of physiology. As one notable example, the application of proteomics to study the regulation of kidney function has yielded novel insights into the chemical and physical processes that tightly control body fluids, electrolytes, and metabolites to provide optimal microenvironments for various cellular and organ functions. Here, we systematically review, summarize, and discuss the most significant key findings from functional proteomic studies in renal epithelial physiology. We also identify further improvements in technological and bioinformatics methods that will be essential to advance precision medicine in nephrology.

Quantitative Proteomics Data in the Public Domain: Challenges and Opportunities

Mass spectrometry based proteomics is no longer only a qualitative discipline, and can be successfully employed to obtain a truly multidimensional view of the proteome. In particular, systematic protein expression profiling is now a routine part of many studies in the field and beyond. The large growth in the number of quantitative studies is accompanied by a trend to share publicly the associated analysis results and the underlying raw data. This trend, established and strongly supported by public repositories such as the PRIDE database at the European Bioinformatics Institute, opens up enormous possibilities to explore the data beyond the original publications, for instance by reusing, reanalyzing, and performing different flavors of meta-analysis studies. To help researchers and scientists realize about this potential, here we describe the mainstream public proteomics resources containing quantitative proteomics data, including the processed analysis results and/or the underlying raw data. We then present and discuss the most important points to consider when attempting to (re)use proteomics data in the public domain. We conclude by highlighting potential pitfalls of (re)using quantitative data and discuss some of our own experiences in this context.

Harnessing Human Microphysiology Systems as Key Experimental Models for Quantitative Systems Pharmacology

Two technologies that have emerged in the last decade offer a new paradigm for modern pharmacology, as well as drug discovery and development. Quantitative systems pharmacology (QSP) is a complementary approach to traditional, target-centric pharmacology and drug discovery and is based on an iterative application of computational and systems biology methods with multiscale experimental methods, both of which include models of ADME-Tox and disease. QSP has emerged as a new approach due to the low efficiency of success in developing therapeutics based on the existing target-centric paradigm. Likewise, human microphysiology systems (MPS) are experimental models complementary to existing animal models and are based on the use of human primary cells, adult stem cells, and/or induced pluripotent stem cells (iPSCs) to mimic human tissues and organ functions/structures involved in disease and ADME-Tox. Human MPS experimental models have been developed to address the relatively low concordance of human disease and ADME-Tox with engineered, experimental animal models of disease. The integration of the QSP paradigm with the use of human MPS has the potential to enhance the process of drug discovery and development.

Messenger RNA Delivery for Tissue Engineering and Regenerative Medicine Applications

The ability to control cellular processes and precisely direct cellular reprogramming has revolutionized regenerative medicine. Recent advances in in vitro transcribed (IVT) mRNA technology with chemical modifications have led to development of methods that control spatiotemporal gene expression. Additionally, there is a current thrust toward the development of safe, integration-free approaches to gene therapy for translational purposes. In this review, we describe strategies of synthetic IVT mRNA modifications and nonviral technologies for intracellular delivery. We provide insights into the current tissue engineering approaches that use a hydrogel scaffold with genetic material. Furthermore, we discuss the transformative potential of novel mRNA formulations that when embedded in hydrogels can trigger controlled genetic manipulation to regenerate tissues and organs in vitro and in vivo. The role of mRNA delivery in vascularization, cytoprotection, and Cas9-mediated xenotransplantation is additionally highlighted. Harmonizing mRNA delivery vehicle interactions with polymeric scaffolds can be used to present genetic cues that lead to precise command over cellular reprogramming, differentiation, and secretome activity of stem cells-an ultimate goal for tissue engineering.

Online Parallel Accumulation-Serial Fragmentation (PASEF) with a Novel Trapped Ion Mobility Mass Spectrometer

In bottom-up proteomics, peptides are separated by liquid chromatography with elution peak widths in the range of seconds, whereas mass spectra are acquired in about 100 microseconds with time-of-flight (TOF) instruments. This allows adding ion mobility as a third dimension of separation. Among several formats, trapped ion mobility spectrometry (TIMS) is attractive because of its small size, low voltage requirements and high efficiency of ion utilization. We have recently demonstrated a scan mode termed parallel accumulation - serial fragmentation (PASEF), which multiplies the sequencing speed without any loss in sensitivity (Meier et al., PMID: 26538118). Here we introduce the timsTOF Pro instrument, which optimally implements online PASEF. It features an orthogonal ion path into the ion mobility device, limiting the amount of debris entering the instrument and making it very robust in daily operation. We investigate different precursor selection schemes for shotgun proteomics to optimally allocate in excess of 100 fragmentation events per second. More than 600,000 fragmentation spectra in standard 120 min LC runs are achievable, which can be used for near exhaustive precursor selection in complex mixtures or accumulating the signal of weak precursors. In 120 min single runs of HeLa digest, MaxQuant identified more than 6,000 proteins without matching to a library and with high quantitative reproducibility (R > 0.97). Online PASEF achieves a remarkable sensitivity with more than 2,500 proteins identified in 30 min runs of only 10 ng HeLa digest. We also show that highly reproducible collisional cross sections can be acquired on a large scale (R > 0.99). PASEF on the timsTOF Pro is a valuable addition to the technological toolbox in proteomics, with a number of unique operating modes that are only beginning to be explored.

C/VDdb: A multi-omics expression profiling database for a knowledge-driven approach in cardiovascular disease (CVD)

The cardiovascular disease (C/VD) database is an integrated and clustered information resource that covers multi-omic studies (microRNA, genomics, proteomics and metabolomics) of cardiovascular-related traits with special emphasis on coronary artery disease (CAD). This resource was built by mining existing literature and public databases and thereafter manual biocuration was performed. To enable integration of omic data from distinct platforms and species, a specific ontology was applied to tie together and harmonise multi-level omic studies based on gene and protein clusters (CluSO) and mapping of orthologous genes (OMAP) across species. CAD continues to be a leading cause of death in the population worldwide, and it is generally thought to be an age-related disease. However, CAD incidence rates are now known to be highly influenced by environmental factors and interactions, in addition to genetic determinants. With the complexity of CAD aetiology, there is a difficulty in research studies to elucidate general elements compared to other cardiovascular diseases. Data from 92 studies, covering 13945 molecular entries (4353 unique molecules) is described, including data descriptors for experimental setup, study design, discovery-validation sample size and associated fold-changes of the differentially expressed molecular features (p-value<0.05). A dedicated interactive web interface, equipped with a multi-parametric search engine, data export and indexing menus are provided for a user-accessible browsing experience. The main aim of this work was the development of a data repository linking clinical information and molecular differential expression in several CVD-related traits from multi-omics studies (genomics, transcriptomics, proteomics and metabolomics). As an example case of how to query and identify data sets within the database framework and concomitantly demonstrate the database utility, we queried CAD-associated studies and performed a systems-level integrative analysis. URL: www.padb.org/cvd

Mitoproteomics: Tackling Mitochondrial Dysfunction in Human Disease

Mitochondria are highly dynamic and regulated organelles that historically have been defined based on their crucial role in cell metabolism. However, they are implicated in a variety of other important functions, making mitochondrial dysfunction an important axis in several pathological contexts. Despite that conventional biochemical and molecular biology approaches have provided significant insight into mitochondrial functionality, innovative techniques that provide a global view of the mitochondrion are still necessary. Proteomics fulfils this need by enabling accurate, systems-wide quantitative analysis of protein abundance. More importantly, redox proteomics approaches offer unique opportunities to tackle oxidative stress, a phenomenon that is intimately linked to aging, cardiovascular disease, and cancer. In addition, cutting-edge proteomics approaches reveal how proteins exert their functions in complex interaction networks where even subtle alterations stemming from early pathological states can be monitored. Here, we describe the proteomics approaches that will help to deepen the role of mitochondria in health and disease by assessing not only changes to mitochondrial protein composition but also alterations to their redox state and how protein interaction networks regulate mitochondrial function and dynamics. This review is aimed at showing the reader how the application of proteomics approaches during the last 20 years has revealed crucial mitochondrial roles in the context of aging, neurodegenerative disorders, metabolic disease, and cancer.

A yeast selection system for the detection of proteasomal activation

The ubiquitin proteasome system (UPS) is a complex cellular machinery that catalyzes degradation of misfolded or damaged proteins and regulates turnover of native proteins in eukaryotic cells, thus playing a crucial role in maintaining protein homeostasis. The UPS has emerged as a drug target for a diverse range of diseases characterized by accumulation of misfolded or aggregated proteins. While enhancement of UPS activity is widely recognized as a promising strategy to prevent accumulation of aberrant, off-pathway protein conformations and ameliorate the phenotypes of a wide range of protein misfolding diseases, the molecular mechanisms underlying activation of proteasomal degradation are poorly characterized. We report the development of a yeast selection platform for genome-wide selection of UPS activators. We engineered the Saccharomyces cerevisiae selection marker orotidine-5'-phosphate decarboxylase (URA3) to function as a substrate of proteasomal degradation through fusion to UPS-sensitive tags. The resulting UPS-sensitive URA3 variant links UPS activity to cell growth. The yeast selection platform reported in this study will open the way to high-throughput, genome-wide studies aimed at identifying modulators of UPS function that might provide novel target for therapeutic applications.

A Chemical Approach for Profiling Intracellular AKT Signaling Dynamics from Single Cells

We present here a novel chemical method to continuously analyze intracellular AKT signaling activities at single-cell resolution, without genetic manipulations. A pair of cyclic peptide-based fluorescent probes were developed to recognize the phosphorylated Ser474 site and a distal epitope on AKT. A Förster resonance energy transfer signal is generated upon concurrent binding of the two probes onto the same AKT protein, which is contingent upon the Ser474 phosphorylation. Intracellular delivery of the probes enabled dynamic measurements of the AKT signaling activities. We further implemented this detection strategy on a microwell single-cell platform, and interrogated the AKT signaling dynamics in a human glioblastoma cell line. We resolved unique features of the single-cell signaling dynamics following different perturbations. Our study provided the first example of monitoring the temporal evolution of cellular signaling heterogeneities and unveiled biological information that was inaccessible to other methods.

Sepsis: Personalized Medicine Utilizing 'Omic' Technologies-A Paradigm Shift?

Sepsis has over the years proven a considerable challenge to physicians and researchers. Numerous pharmacological and non-pharmacological interventions have been tested in trials, but have unfortunately failed to improve the general prognosis. This has led to the speculation that the sepsis population may be too heterogeneous to be targeted with the traditional one treatment suits all’ approach. Recent advances in genetic and biochemical analyses now allow genotyping and biochemical characterisation of large groups of patients via the ‘omics’ technologies. These new opportunities could lead to a paradigm shift in the approach to sepsis towards personalised treatments with interventions targeted towards specific pathophysiological mechanisms activated in the patient. In this article, we review the potentials and pitfalls of using new advanced technologies to deepen our understanding of the clinical syndrome of sepsis.

Extensive Characterization of Heavily Modified Histone Tails by 193 nm Ultraviolet Photodissociation Mass Spectrometry via a Middle-Down Strategy

The ability to map combinatorial patterns of post-translational modifications (PTMs) of proteins remains challenging for traditional bottom-up mass spectrometry workflows. There are also hurdles associated with top-down approaches related to limited data analysis options for heavily modified proteoforms. These shortcomings have accelerated interest in middle-down MS methods that focus on analysis of large peptides generated by specific proteases in conjunction with validated bioinformatics strategies to allow quantification of isomeric histoforms. Mapping multiple PTMs simultaneously requires the ability to obtain high sequence coverage to allow confident localization of the modifications, and 193 nm ultraviolet photodissociation (UVPD) has been shown to cause extensive fragmentation for large peptides and proteins. Histones are an ideal system to test the ability of UVPD to characterize multiple modifications, as the combinations of PTMs are the underpinning of the biological significance of histones and at the same time create an imposing challenge for characterization. The present study focuses on applying 193 nm UVPD to the identification and localization of PTMs on histones by UVPD and comparison to a popular alternative, electron-transfer dissociation (ETD), via a high-throughput middle-down LC/MS/MS strategy. Histone Coder and IsoScale, bioinformatics tools for verification of PTM assignments and quantification of histone peptides, were adapted for UVPD data and applied in the present study. In total, over 300 modified forms were identified, and the distributions of PTMs were quantified between UVPD and ETD. Significant differences in patterns of PTMs were found for histones from HeLa cells prior to and after treatment with a deacetylase inhibitor. Additional fragment ion types generated by UVPD proved essential for extensive characterization of the most heavily modified forms (>5 PTMs).

Precise Quantification of Platelet Proteins and Their Phosphorylation States

Systems biology and modeling approaches require quantitative data-rich temporal experiments to better understand the dynamics and regulation of the components of the signaling pathways that governs cell biology and physiology. Here we present a modified Western blotting method to rapidly analyze and accurately quantify protein copy number, and their respective phosphorylation states at specific sites over detailed time courses.