A Double-Barrel Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS) System to Quantify 96 Interactomes per Day

Storing liquid chromatographic separations on surface energy traps: decoupling the LC and the mass spectrometer

We report a micro-fractionation device for high performance liquid chromatography-mass spectrometry to archive chromatographic separations on an array of optimized surface energy traps (SETs). The method has the potential to significantly alter nanoflow LC-MS workflow, decoupling separation and analysis. The wetting characteristics of the SETs cause the HPLC eluent stream to spontaneously split into droplet microfractions. The droplet mirofractions are then dried down to enable facile storage and transport of the archived separation. Discontinuously dewetting array parameters were explored to maximize array volume and resolution using a combination of SET design, shape, size, and spacing. Mass spectrometry analysis is performed utilizing a liquid micro-junction surface sampling probe to extract dried analytes from the surface of the SETs followed by electrospray ionisation. A reverse phase separation of pharmaceutical compounds is "recorded" using the micro-fractionation device followed by "reading" the chromatographic trace with a mass spectrometer 24 hours after the separation was performed/archived, demonstrating a true decoupling of LC, and MS. Additionally, we demonstrate the ability to collect microfractions with sub-one-second integration time, approaching the scan time of a mass spectrometer or UV-Vis detector. With further improvements to the device, sub-1-second micro-fractionation may enable seamless reconstruction of archived chromatograms indistinguishable from online LC-MS data, while also providing the benefits of easy storage and transport of archived separations.

High-Throughput Proteomics and Phosphoproteomics of Rat Tissues Using Microflow Zeno SWATH

High-throughput tissue proteomics has great potential in the advancement of precision medicine. Here, we investigated the combined sensitivity of trap-elute microflow liquid chromatography with a ZenoTOF for DIA proteomics and phosphoproteomics. Method optimization was conducted on HEK293T cell lines to determine the optimal variable window size, MS2 accumulation time and gradient length. The ZenoTOF 7600 was then compared to the previous generation TripleTOF 6600 using eight rat organs, finding up to 23% more proteins using a fifth of the sample load and a third of the instrument time. Spectral reference libraries generated from Zeno SWATH data in FragPipe (MSFragger-DIA/DIA-NN) contained 4 times more fragment ions than the DIA-NN only library and quantified more proteins. Replicate single-shot phosphopeptide enrichments of 50-100 μg of rat tryptic peptide were analyzed by microflow HPLC using Zeno SWATH without fractionation. Using Spectronaut we quantified a shallow phosphoproteome containing 1000-3000 phosphoprecursors per organ. Promisingly, clear hierarchical clustering of organs was observed with high Pearson correlation coefficients >0.95 between replicate enrichments and median CV of 20%. The combined sensitivity of microflow HPLC with Zeno SWATH allows for the high-throughput quantitation of an extensive proteome and shallow phosphoproteome from small tissue samples.

Multicolumn Nanoflow Liquid Chromatography with Accelerated Offline Gradient Generation for Robust and Sensitive Single-Cell Proteome Profiling

Peptide separations that combine high sensitivity, robustness, peak capacity, and throughput are essential for extending bottom-up proteomics to smaller samples including single cells. To this end, we have developed a multicolumn nanoLC system with offline gradient generation. One binary pump generates gradients in an accelerated fashion to support multiple analytical columns, and a single trap column interfaces with all analytical columns to reduce required maintenance and simplify troubleshooting. A high degree of parallelization is possible, as one sample undergoes separation while the next sample plus its corresponding mobile phase gradient are transferred into the storage loop and a third sample is loaded into a sample loop. Selective offline elution from the trap column into the sample loop prevents salts and hydrophobic species from entering the analytical column, thus greatly enhancing column lifetime and system robustness. With this design, samples can be analyzed as fast as every 20 min at a flow rate of just 40 nL/min with close to 100% MS utilization time and continuously for as long as several months without column replacement. We utilized the system to analyze the proteomes of single cells from a multiple myeloma cell line upon treatment with the immunomodulatory imide drug lenalidomide.

High-Throughput Proteomics Enabled by a Fully Automated Dual-Trap and Dual-Column LC-MS

This Technical Note describes a dual-column liquid chromatography system coupled to mass spectrometry (LC-MS) for high-throughput bottom-up proteomic analysis. This system made full use of two 2-position 10-port valves and a binary pump with an integrated loading pump of a commercial LC instrument to provide successive operation of two parallel subsystems. Each subsystem consisted of a set of trap columns and an analytical column. A T-junction union was used to split the mobile phase from the loading pump into two parts. This allowed one set of columns to be washed and equilibrated, followed by the injection of the next sample, while the previous sample was eluting and being analyzed on the other set of columns, thereby greatly increasing the analysis throughput. This approach showed high reproducibility for the analysis of HeLa tryptic digests with average relative standard deviation (RSD) values of 1.75%, 6.90%, and 5.19% for the identification number of proteins, peptides, and peptide-spectrum matches (PSMs), respectively, across 10 consecutive runs. The capacity for peptide and protein identification, as well as proteome depth, of the dual-column LC system was comparable to a conventional single-column system. Due to its simple equipment requirements and set up process, this method should be highly accessible for other laboratories.

High-Throughput Nanoflow Proteomics Using a Dual-Column Electrospray Source

With current trends in proteomics, especially regarding clinical and low input (to single cell) samples, it is increasingly important to both maximize the throughput of the analysis and maintain as much sensitivity as possible. The new generation of mass spectrometers (MS) are taking a huge leap in sensitivity, allowing analysis of samples with shorter liquid chromatography (LC) methods while digging as deep in the proteome. However, the throughput can be doubled by implementing a dual column nano-LC-MS configuration. For this purpose, we used a dual-column setup with a two-outlet electrospray source and compared it to a classic dual-column setup with a single-outlet source.

Triboelectric Nanogenerator-Coated Blade Spray Mass Spectrometry for Volume-Limited Drug Analysis

The demand for analytical tools for the analysis of low-concentration volume-limited samples has driven researchers to explore new analytical approaches. Mass spectrometry excels at trace analysis due to its high sensitivity and specificity, whereas ambient methods simplify, or completely eliminate sample preparation. Herein, we report a triboelectric nanogenerator-coated blade spray ambient mass spectrometry (TENG-CBS MS) method for the extraction, elution, and ionization of volume-limited, low-concentration small molecule drug samples with minimum sample preparation. Using a TENG device as the CBS power supply, we show it is possible to extract and analyze drug samples in a pulsed fashion at sub-nanogram to picogram levels with good stability and reproducibility. A wide range of analytes polarities were tested. Results indicated this method could also be useful for the analysis of low-level analytes in precious, volume limited samples in a simple single step.

Multidimensional Separations in Top-Down Proteomics

Top-down proteomics (TDP) identifies, quantifies, and characterizes proteins at the intact proteoform level in complex biological samples to understand proteoform function and cellular mechanisms. However, analyzing complex biological samples using TDP is still challenging due to high sample complexity and wide dynamic range. High-resolution separation methods are often applied prior to mass spectrometry (MS) analysis to decrease sample complexity and increase proteomics throughput. These separation methods, however, may not be efficient enough to characterize low abundance intact proteins in complex samples. As such, multidimensional separation techniques (combination of two or more separation methods with high orthogonality) have been developed and applied that demonstrate improved separation resolution and more comprehensive identification in TDP. A suite of multidimensional separation methods that couple various types of liquid chromatography (LC), capillary electrophoresis (CE), and/or gel electrophoresis-based separation approaches have been developed and applied in TDP to analyze complex biological samples. Here, we reviewed multidimensional separation strategies employed for TDP, summarized current applications, and discussed the gaps that may be addressed in the future.

Chromatographic separation of peptides and proteins for characterization of proteomes

Characterization of proteomes aims to comprehensively characterize proteins in cells or tissues via two main strategies: (1) bottom-up strategy based on the separation and identification of enzymatic peptides; (2) top-down strategy based on the separation and identification of intact proteins. However, it is challenged by the high complexity of proteomes. Consequently, the improvements in peptide and protein separation technologies for simplifying the sample should be critical. In this feature article, separation columns for peptide and protein separation were introduced, and peptide separation technologies for bottom-up proteomic analysis as well as protein separation technologies for top-down proteomic analysis were summarized. The achievement, recent development, limitation and future trends are discussed. Besides, the outlook on challenges and future directions of chromatographic separation in the field of proteomics was also presented.

Parallelization with Dual-Trap Single-Column Configuration Maximizes Throughput of Proteomic Analysis

Proteomic analysis on the scale that captures population and biological heterogeneity over hundreds to thousands of samples requires rapid mass spectrometry methods, which maximize instrument utilization (IU) and proteome coverage while maintaining precise and reproducible quantification. To achieve this, a short liquid chromatography gradient paired to rapid mass spectrometry data acquisition can be used to reproducibly quantify a moderate set of analytes. High-throughput profiling at a limited depth is becoming an increasingly utilized strategy for tackling large sample sets but the time spent on loading the sample, flushing the column(s), and re-equilibrating the system reduces the ratio of meaningful data acquired to total operation time and IU. The dual-trap single-column configuration (DTSC) presented here maximizes IU in rapid analysis (15 min per sample) of blood and cell lysates by parallelizing trap column cleaning and sample loading and desalting with the analysis of the previous sample. We achieved 90% IU in low microflow (9.5 μL/min) analysis of blood while reproducibly quantifying 300-400 proteins and over 6000 precursor ions. The same IU was achieved for cell lysates and over 4000 proteins (3000 at CV below 20%) and 40,000 precursor ions were quantified at a rate of 15 min/sample. Thus, DTSC enables high-throughput epidemiological blood-based biomarker cohort studies and cell-based perturbation screening.

Label-Free Profiling of up to 200 Single-Cell Proteomes per Day Using a Dual-Column Nanoflow Liquid Chromatography Platform

Single-cell proteomics (SCP) has great potential to advance biomedical research and personalized medicine. The sensitivity of such measurements increases with low-flow separations (<100 nL/min) due to improved ionization efficiency, but the time required for sample loading, column washing, and regeneration in these systems can lead to low measurement throughput and inefficient utilization of the mass spectrometer. Herein, we developed a two-column liquid chromatography (LC) system that dramatically increases the throughput of label-free SCP using two parallel subsystems to multiplex sample loading, online desalting, analysis, and column regeneration. The integration of MS1-based feature matching increased proteome coverage when short LC gradients were used. The high-throughput LC system was reproducible between the columns, with a 4% difference in median peptide abundance and a median CV of 18% across 100 replicate analyses of a single-cell-sized peptide standard. An average of 621, 774, 952, and 1622 protein groups were identified with total analysis times of 7, 10, 15, and 30 min, corresponding to a measurement throughput of 206, 144, 96, and 48 samples per day, respectively. When applied to single HeLa cells, we identified nearly 1000 protein groups per cell using 30 min cycles and 660 protein groups per cell for 15 min cycles. We explored the possibility of measuring cancer therapeutic targets with a pilot study comparing the K562 and Jurkat leukemia cell lines. This work demonstrates the feasibility of high-throughput label-free single-cell proteomics.

Label-free visual proteomics: Coupling MS- and EM-based approaches in structural biology

Combining diverse experimental structural and interactomic methods allows for the construction of comprehensible molecular encyclopedias of biological systems. Typically, this involves merging several independent approaches that provide complementary structural and functional information from multiple perspectives and at different resolution ranges. A particularly potent combination lies in coupling structural information from cryoelectron microscopy or tomography (cryo-EM or cryo-ET) with interactomic and structural information from mass spectrometry (MS)-based structural proteomics. Cryo-EM/ET allows for sub-nanometer visualization of biological specimens in purified and near-native states, while MS provides bioanalytical information for proteins and protein complexes without introducing additional labels. Here we highlight recent achievements in protein structure and interactome determination using cryo-EM/ET that benefit from additional MS analysis. We also give our perspective on how combining cryo-EM/ET and MS will continue bridging gaps between molecular and cellular studies by capturing and describing 3D snapshots of proteomes and interactomes.

Cryo-EM reconstructions of inhibitor-bound SMG1 kinase reveal an autoinhibitory state dependent on SMG8

The PI3K-related kinase (PIKK) SMG1 monitors the progression of metazoan nonsense-mediated mRNA decay (NMD) by phosphorylating the RNA helicase UPF1. Previous work has shown that the activity of SMG1 is impaired by small molecule inhibitors, is reduced by the SMG1 interactors SMG8 and SMG9, and is downregulated by the so-called SMG1 insertion domain. However, the molecular basis for this complex regulatory network has remained elusive. Here, we present cryo-electron microscopy reconstructions of human SMG1-9 and SMG1-8-9 complexes bound to either a SMG1 inhibitor or a non-hydrolyzable ATP analog at overall resolutions ranging from 2.8 to 3.6 Å. These structures reveal the basis with which a small molecule inhibitor preferentially targets SMG1 over other PIKKs. By comparison with our previously reported substrate-bound structure (Langer et al.,2020), we show that the SMG1 insertion domain can exert an autoinhibitory function by directly blocking the substrate-binding path as well as overall access to the SMG1 kinase active site. Together with biochemical analysis, our data indicate that SMG1 autoinhibition is stabilized by the presence of SMG8. Our results explain the specific inhibition of SMG1 by an ATP-competitive small molecule, provide insights into regulation of its kinase activity within the NMD pathway, and expand the understanding of PIKK regulatory mechanisms in general.

Nse5/6 inhibits the Smc5/6 ATPase and modulates DNA substrate binding

Eukaryotic cells employ three SMC (structural maintenance of chromosomes) complexes to control DNA folding and topology. The Smc5/6 complex plays roles in DNA repair and in preventing the accumulation of deleterious DNA junctions. To elucidate how specific features of Smc5/6 govern these functions, we reconstituted the yeast holo-complex. We found that the Nse5/6 sub-complex strongly inhibited the Smc5/6 ATPase by preventing productive ATP binding. This inhibition was relieved by plasmid DNA binding but not by short linear DNA, while opposing effects were observed without Nse5/6. We uncovered two binding sites for Nse5/6 on Smc5/6, based on an Nse5/6 crystal structure and cross-linking mass spectrometry data. One binding site is located at the Smc5/6 arms and one at the heads, the latter likely exerting inhibitory effects on ATP hydrolysis. Cysteine cross-linking demonstrated that the interaction with Nse5/6 anchored the ATPase domains in a non-productive state, which was destabilized by ATP and DNA. Under similar conditions, the Nse4/3/1 module detached from the ATPase. Altogether, we show how DNA substrate selection is modulated by direct inhibition of the Smc5/6 ATPase by Nse5/6.

Calcitriol Promotes Differentiation of Glioma Stem-Like Cells and Increases Their Susceptibility to Temozolomide

Simple Summary

Cancer cells with a stem-like phenotype that are thought to be highly tumorigenic are commonly described in glioblastoma, the most common primary adult brain cancer. This phenotype comprises high self-renewal capacity and resistance against chemotherapy and radiation therapy, thereby promoting tumor progression and disease relapse. Here, we show that calcitriol, the hormonally active form of the “sun hormone” vitamin D₃, effectively suppresses stemness properties in glioblastoma stem-like cells (GSCs), supporting the hypothesis that calcitriol sensitizes them to additional chemotherapy. Indeed, a physiological organotypic brain slice model was used to monitor tumor growth of GSCs, and the effectiveness of combined treatment with temozolomide, the current standard-of-care, and calcitriol was proven. These findings indicate that further research on applying calcitriol, a well-known and safe drug, as a potential adjuvant therapy for glioblastoma is both justified and necessary.

Abstract

Glioblastoma (GBM) is the most common and most aggressive primary brain tumor, with a very high rate of recurrence and a median survival of 15 months after diagnosis. Abundant evidence suggests that a certain sub-population of cancer cells harbors a stem-like phenotype and is likely responsible for disease recurrence, treatment resistance and potentially even for the infiltrative growth of GBM. GBM incidence has been negatively correlated with the serum levels of 25-hydroxy-vitamin D₃, while the low pH within tumors has been shown to promote the expression of the vitamin D₃-degrading enzyme 24-hydroxylase, encoded by the CYP24A1 gene. Therefore, we hypothesized that calcitriol can specifically target stem-like glioblastoma cells and induce their differentiation. Here, we show, using in vitro limiting dilution assays, quantitative real-time PCR, quantitative proteomics and ex vivo adult organotypic brain slice transplantation cultures, that therapeutic doses of calcitriol, the hormonally active form of vitamin D₃, reduce stemness to varying extents in a panel of investigated GSC lines, and that it effectively hinders tumor growth of responding GSCs ex vivo. We further show that calcitriol synergizes with Temozolomide ex vivo to completely eliminate some GSC tumors. These findings indicate that calcitriol carries potential as an adjuvant therapy for a subgroup of GBM patients and should be analyzed in more detail in follow-up studies.

High-throughput proteotyping of bacterial isolates by double barrel chromatography-tandem mass spectrometry based on microplate paramagnetic beads and phylopeptidomics

Tandem mass spectrometry-based proteotyping of microorganisms presents several advantages over whole-cell MALDI-TOF mass spectrometry: because a larger number of signals are recorded with better accuracy and precision, the approach allows for the identification of microorganisms at more resolved taxonomic levels, and can easily manage complex samples. Additionally, the use of SP3 paramagnetic beads for cell lysis and protein cleanup simplifies sample preparation for proteotyping. Based on these features, we have developed and tested a 96-well plate platform for high-throughput proteotyping of a large variety of bacteria. We evaluated the performance of the platform in terms of bacterial load and found no cross-contamination between wells. Likewise, phylopeptidomics analysis revealed no alteration in the relative quantifications of microorganisms. Finally, we applied this new format for rapid proteotyping of a large set of dental isolates using double-barrel chromatography coupled to tandem mass spectrometry, which maximizes the number of spectra per unit of time. The procedure allowed us to establish whether these isolates were pure strains or mixtures of strains and to identify the microorganisms at the most resolved taxonomic level. SIGNIFICANCE: The rapid and accurate identification of microorganisms is a clinical priority in medical diagnostics; however, specimens containing mixtures of microorganisms are difficult to analyze and the procedure is time-consuming. Tandem mass spectrometry proteotyping allows the fast identification of complex mixtures of microorganisms, known or unknown, and can also establish the biomass ratio of each component. We describe here a new workflow for preparing microbial samples in a 96-well-plate format for tandem mass spectrometry proteotyping and document its advantages and limitations. We demonstrate that this new format coupled to a highly efficient double-barrel LC-MS/MS system allows proteotyping of 96 isolates in 55 h.

Bait Correlation Improves Interactor Identification by Tandem Mass Tag-Affinity Purification-Mass Spectrometry

The quantitative multiplexing capacity of isobaric tandem mass tags (TMT) has increased the throughput of affinity purification mass spectrometry (AP-MS) to characterize protein interaction networks of immunoprecipitated bait proteins. However, variable bait levels between replicates can convolute interactor identification. We compared the Student's t-test and Pearson's R correlation as methods to generate t-statistics and assessed the significance of interactors following TMT-AP-MS. Using a simple linear model of protein recovery in immunoprecipitates to simulate reporter ion ratio distributions, we found that correlation-derived t-statistics protect against bait variance while robustly controlling type I errors (false positives). We experimentally determined the performance of these two approaches for determining t-statistics under two experimental conditions: irreversible prey association to the Hsp40 mutant DNAJB8^H31Q followed by stringent washing, and reversible association to 14-3-3ζ with gentle washing. Correlation-derived t-statistics performed at least as well as Student's t-statistics for each sample and with substantial improvement in performance for experiments with high bait-level variance. Deliberately varying bait levels over a large range fails to improve selectivity but does increase the robustness between runs. The use of correlation-derived t-statistics should improve identification of interactors using TMT-AP-MS. Data are available via ProteomeXchange with identifier PXD016613.

Proteomic Analysis of the β-Arrestin Interactomes

Protein-protein interaction is crucial to protein function and cellular signaling. A number of approaches were developed and applied to characterize protein-protein interactions in the past decades. In recent years, mass spectrometry (MS)-based proteomic methods have emerged as powerful tools to identify protein binding partners in a global and high-throughput manner. In this chapter, we describe the proteomic methods used to characterize the whole sets of proteins associated with β-arrestins (β-arrestin interactomes). The method starts with co-immunoprecipitation (co-IP) of β-arrestin signaling complexes from cells followed by protease digestion and LC/MS/MS analysis (liquid chromatography/tandem mass spectrometry) of proteins in the β-arrestin signaling complexes. To investigate changes in the amounts of binding partners under different conditions, we also describe a SILAC (stable isotope labeling by amino acids in cell culture) method to obtain quantitative information for β-arrestin interactomes.

Miniaturised interaction proteomics on a microfluidic platform with ultra-low input requirements

Essentially all cellular processes are orchestrated by protein-protein interactions (PPIs). In recent years, affinity purification coupled to mass spectrometry (AP-MS) has been the preferred method to identify cellular PPIs. Here we present a microfluidic-based AP-MS workflow, called on-chip AP-MS, to identify PPIs using minute amounts of input material. By using this automated platform we purify the human Cohesin, CCC and Mediator complexes from as little as 4 micrograms of input lysate, representing a 50─100-fold downscaling compared to regular microcentrifuge tube-based protocols. We show that our platform can be used to affinity purify tagged baits as well as native cellular proteins and their interaction partners. As such, our method holds great promise for future biological and clinical AP-MS applications in which sample amounts are limited.

Cross-ID: Analysis and Visualization of Complex XL-MS-Driven Protein Interaction Networks

Protein interactions enable much more complex behavior than the sum of the individual protein parts would suggest and represents a level of biological complexity requiring full understanding when unravelling cellular processes. Cross-linking mass spectrometry has emerged as an attractive approach to study these interactions, and recent advances in mass spectrometry and data analysis software have enabled the identification of thousands of cross-links from a single experiment. The resulting data complexity is, however, difficult to understand and requires interactive software tools. Even though solutions are available, these represent an agglomerate of possibilities, and each features its own input format, often forcing manual conversion. Here we present Cross-ID, a visualization platform that links directly into the output of XlinkX for Proteome Discoverer but also plays well with other platforms by supporting a user-controllable text-file importer. The platform includes features like grouping, spectral viewer, gene ontology (GO) enrichment, post-translational modification (PTM) visualization, domains and secondary structure mapping, data set comparison, previsualization overlap check, and more. Validation of detected cross-links is available for proteins and complexes with known structure or for protein complexes through the DisVis online platform ( http://milou.science.uu.nl/cgi/services/DISVIS/disvis/ ). Graphs are exportable in PDF format, and data sets can be exported in tab-separated text files for evaluation through other software.

A Novel LC System Embeds Analytes in Pre-formed Gradients for Rapid, Ultra-robust Proteomics

Because of low throughput and limited robustness, nano-scale liquid chromatography has been a bottleneck for advancing proteomics in biomedical research. Here, we developed and evaluated two new LC concepts—“pre-formed gradients” and “offset gradients for peptide re-focusing”—that are both implemented in the Evosep One instrument. We evaluated robustness with more than 2000 HeLa runs, demonstrated absence of cross-contamination with crude plasma samples, high proteome coverage by fractionated HeLa and routinely measuring more than 5000 proteins/sample in just 21 minutes.

To further integrate mass spectrometry (MS)-based proteomics into biomedical research and especially into clinical settings, high throughput and robustness are essential requirements. They are largely met in high-flow rate chromatographic systems for small molecules but these are not sufficiently sensitive for proteomics applications. Here we describe a new concept that delivers on these requirements while maintaining the sensitivity of current nano-flow LC systems. Low-pressure pumps elute the sample from a disposable trap column, simultaneously forming a chromatographic gradient that is stored in a long storage loop. An auxiliary gradient creates an offset, ensuring the re-focusing of the peptides before the separation on the analytical column by a single high-pressure pump. This simplified design enables robust operation over thousands of sample injections. Furthermore, the steps between injections are performed in parallel, reducing overhead time to a few minutes and allowing analysis of more than 200 samples per day. From fractionated HeLa cell lysates, deep proteomes covering more than 130,000 sequence unique peptides and close to 10,000 proteins were rapidly acquired. Using this data as a library, we demonstrate quantitation of 5200 proteins in only 21 min. Thus, the new system - termed Evosep One - analyzes samples in an extremely robust and high throughput manner, without sacrificing in depth proteomics coverage.

Glycomics and Proteomics Approaches to Investigate Early Adenovirus-Host Cell Interactions

Adenoviruses as most viruses rely on glycan and protein interactions to attach to and enter susceptible host cells. The Adenoviridae family comprises more than 80 human types and they differ in their attachment factor and receptor usage, which likely contributes to the diverse tropism of the different types. In the past years, methods to systematically identify glycan and protein interactions have advanced. In particular sensitivity, speed and coverage of mass spectrometric analyses allow for high-throughput identification of glycans and peptides separated by liquid chromatography. Also, developments in glycan microarray technologies have led to targeted, high-throughput screening and identification of glycan-based receptors. The mapping of cell surface interactions of the diverse adenovirus types has implications for cell, tissue, and species tropism as well as drug development. Here we review known adenovirus interactions with glycan- and protein-based receptors, as well as glycomics and proteomics strategies to identify yet elusive virus receptors and attachment factors. We finally discuss challenges, bottlenecks, and future research directions in the field of non-enveloped virus entry into host cells.

A Comprehensive Guide for Performing Sample Preparation and Top-Down Protein Analysis

Methodologies for the global analysis of proteins in a sample, or proteome analysis, have been available since 1975 when Patrick O′Farrell published the first paper describing two-dimensional gel electrophoresis (2D-PAGE). This technique allowed the resolution of single protein isoforms, or proteoforms, into single ‘spots’ in a polyacrylamide gel, allowing the quantitation of changes in a proteoform′s abundance to ascertain changes in an organism′s phenotype when conditions change. In pursuit of the comprehensive profiling of the proteome, significant advances in technology have made the identification and quantitation of intact proteoforms from complex mixtures of proteins more routine, allowing analysis of the proteome from the ‘Top-Down’. However, the number of proteoforms detected by Top-Down methodologies such as 2D-PAGE or mass spectrometry has not significantly increased since O’Farrell’s paper when compared to Bottom-Up, peptide-centric techniques. This article explores and explains the numerous methodologies and technologies available to analyse the proteome from the Top-Down with a strong emphasis on the necessity to analyse intact proteoforms as a better indicator of changes in biology and phenotype. We arrive at the conclusion that the complete and comprehensive profiling of an organism′s proteome is still, at present, beyond our reach but the continuing evolution of protein fractionation techniques and mass spectrometry brings comprehensive Top-Down proteome profiling closer.

Expanding Proteome Coverage with CHarge Ordered Parallel Ion aNalysis (CHOPIN) Combined with Broad Specificity Proteolysis

The "deep" proteome has been accessible by mass spectrometry for some time. However, the number of proteins identified in cells of the same type has plateaued at ∼8000-10 000 without ID transfer from reference proteomes/data. Moreover, limited sequence coverage hampers the discrimination of protein isoforms when using trypsin as standard protease. Multienzyme approaches appear to improve sequence coverage and subsequent isoform discrimination. Here we expanded proteome and protein sequence coverage in MCF-7 breast cancer cells to an as yet unmatched depth by employing a workflow that addresses current limitations in deep proteome analysis in multiple stages: We used (i) gel-aided sample preparation (GASP) and combined trypsin/elastase digests to increase peptide orthogonality, (ii) concatenated high-pH prefractionation, and (iii) CHarge Ordered Parallel Ion aNalysis (CHOPIN), available on an Orbitrap Fusion (Lumos) mass spectrometer, to achieve 57% median protein sequence coverage in 13 728 protein groups (8949 Unigene IDs) in a single cell line. CHOPIN allows the use of both detectors in the Orbitrap on predefined precursor types that optimizes parallel ion processing, leading to the identification of a total of 179 549 unique peptides covering the deep proteome in unprecedented detail.

Protein Interactions during the Flavivirus and Hepacivirus Life Cycle

Protein-protein interactions govern biological functions in cells, in the extracellular milieu, and at the border between cells and extracellular space. Viruses are small intracellular parasites and thus rely on protein interactions to produce progeny inside host cells and to spread from cell to cell. Usage of host proteins by viruses can have severe consequences e.g. apoptosis, metabolic disequilibria, or altered cell proliferation and mobility. Understanding protein interactions during virus infection can thus educate us on viral infection and pathogenesis mechanisms. Moreover, it has led to important clinical translations, including the development of new therapeutic and vaccination strategies. Here, we will discuss protein interactions of members of the Flaviviridae family, which are small enveloped RNA viruses. Dengue virus, Zika virus and hepatitis C virus belong to the most prominent human pathogenic Flaviviridae With a genome of roughly ten kilobases encoding only ten viral proteins, Flaviviridae display intricate mechanisms to engage the host cell machinery for their purpose. In this review, we will highlight how dengue virus, hepatitis C virus, Japanese encephalitis virus, tick-borne encephalitis virus, West Nile virus, yellow fever virus, and Zika virus proteins engage host proteins and how this knowledge helps elucidate Flaviviridae infection. We will specifically address the protein composition of the virus particle as well as the protein interactions during virus entry, replication, particle assembly, and release from the host cell. Finally, we will give a perspective on future challenges in Flaviviridae interaction proteomics and why we believe these challenges should be met.

Symmetry of Charge Partitioning in Collisional and UV Photon-Induced Dissociation of Protein Assemblies

Tandem mass spectrometry can provide structural information on intact protein assemblies, generating mass fingerprints indicative of the stoichiometry and quaternary arrangement of the subunits. However, in such experiments, collision-induced dissociation yields restricted information due to simultaneous subunit unfolding, charge rearrangement, and subsequent ejection of a highly charged unfolded single subunit. Alternative fragmentation strategies can potentially overcome this and supply a deeper level of structural detail. Here, we implemented ultraviolet photodissociation (UVPD) on an Orbitrap mass spectrometer optimized for native MS and benchmark its performance to HCD fragmentation using various protein oligomers. We investigated dimeric β-lactoglobulin, dimeric superoxide dismutase, dimeric and tetrameric concanavalin A, and heptameric GroES and Gp31; ranging in molecular weight from 32 to 102 kDa. We find that, for the investigated systems, UVPD produces more symmetric charge partitioning than HCD. While HCD spectra show sporadic fragmentation over the full protein backbone sequence of the subunits with a bias toward fragmenting labile bonds, UVPD spectra provided higher sequence coverage. Taken together, we conclude that UVPD is a strong addition to the toolbox of fragmentation methods for top-down proteomics experiments, especially for native protein assemblies.

Mitochondrial Protein Interaction Mapping Identifies Regulators of Respiratory Chain Function

Mitochondria are essential for numerous cellular processes, yet hundreds of their proteins lack robust functional annotation. To reveal functions for these proteins (termed MXPs), we assessed condition-specific protein-protein interactions for 50 select MXPs using affinity enrichment mass spectrometry. Our data connect MXPs to diverse mitochondrial processes, including multiple aspects of respiratory chain function. Building upon these observations, we validated C17orf89 as a complex I (CI) assembly factor. Disruption of C17orf89 markedly reduced CI activity, and its depletion is found in an unresolved case of CI deficiency. We likewise discovered that LYRM5 interacts with and deflavinates the electron-transferring flavoprotein that shuttles electrons to coenzyme Q (CoQ). Finally, we identified a dynamic human CoQ biosynthetic complex involving multiple MXPs whose topology we map using purified components. Collectively, our data lend mechanistic insight into respiratory chain-related activities and prioritize hundreds of additional interactions for further exploration of mitochondrial protein function.

Systems-wide Identification of cis-Regulatory Elements in Proteins

Protein interactions in cis that can activate or autoinhibit protein function play an important role in the fine-tuning of regulatory and signaling processes in the cell, but thus far cis-regulatory elements (CREs) in proteins have not been systematically identified and studied. Here, we introduce a computational tool that identifies intrinsically disordered protein segments that contribute to protein function regulation via interactions in cis. We apply this tool to estimate the prevalence of CREs in the human proteome and reveal that cis regulation is enriched in several signaling pathways, including the MAP kinase pathway, for which we provide a detailed map of its "cis regulome." We also show that disease-causing mutations are highly enriched in CREs, but not in motifs that classically mediate protein-protein interactions of disordered protein segments. Our approach should facilitate the discovery and characterization of CREs in proteins and the identification of disease-causing mutations that disrupt protein regulation in cis.

Decoding protein networks during virus entry by quantitative proteomics

Virus entry into host cells relies on interactions between viral and host structures including lipids, carbohydrates and proteins. Particularly, protein–protein interactions between viral surface proteins and host proteins as well as secondary host protein–protein interactions play a pivotal role in coordinating virus binding and uptake. These interactions are dynamic and frequently involve multiprotein complexes. In the past decade mass spectrometry based proteomics methods have reached sensitivities and high throughput compatibilities of genomics methods and now allow the reliable quantitation of proteins in complex samples from limited material. As proteomics provides essential information on the biologically active entity namely the protein, including its posttranslational modifications and its interactions with other proteins, it is an indispensable method in the virologist's toolbox. Here we review protein interactions during virus entry and compare classical biochemical methods to study entry with novel technically advanced quantitative proteomics techniques. We highlight the value of quantitative proteomics in mapping functional virus entry networks, discuss the benefits and limitations and illustrate how the methodology will help resolve unsettled questions in virus entry research in the future.