One-hour proteome analysis in yeast

The One Hour Human Proteome

We describe deep analysis of the human proteome in less than 1 h. We achieve this expedited proteome characterization by leveraging state-of-the-art sample preparation, chromatographic separations, and data analysis tools, and by using the new Orbitrap Astral mass spectrometer equipped with a quadrupole mass filter, a high-field Orbitrap mass analyzer, and an asymmetric track lossless (Astral) mass analyzer. The system offers high tandem mass spectrometry acquisition speed of 200 Hz and detects hundreds of peptide sequences per second within data-independent acquisition or data-dependent acquisition modes of operation. The fast-switching capabilities of the new quadrupole complement the sensitivity and fast ion scanning of the Astral analyzer to enable narrow-bin data-independent analysis methods. Over a 30-min active chromatographic method consuming a total analysis time of 56 min, the Q-Orbitrap-Astral hybrid MS collects an average of 4319 MS1 scans and 438,062 tandem mass spectrometry scans per run, producing 235,916 peptide sequences (1% false discovery rate). On average, each 30-min analysis achieved detection of 10,411 protein groups (1% false discovery rate). We conclude, with these results and alongside other recent reports, that the 1-h human proteome is within reach.

CZE-MS peptide mapping: To desalt or not to desalt?

BACKGROUND

In "shotgun" approaches involving high-performance liquid chromatography or capillary zone electrophoresis (CZE), matrix removal prior to sample analysis is considered as an indispensable tool. Despite the fact that CZE offers a high tolerance towards salts, most publications reported on the use of desalting. There seems to be no clear consensus on the utilization of desalting in the CZE-MS community, most probably due to the absence of works addressing the comparison of desalted and non-desalted digests. Our aim was to fill this research gap using protein samples of varying complexity in different sample matrices.

RESULTS

First, standard protein digests were analyzed to build the knowledge on the effect of sample clean-up by solid-phase extraction (SPE) pipette tips and the possible stacking phenomena induced by different sample matrices. Desalting led to a somewhat altered peptide profile, the procedure affected mostly the hydrophilic peptides (although not to a devastating extent). Nevertheless, desalting samples allowed remarkable stacking efficiency owing to their low-conductivity sample background, enabling a so-called field-amplified sample stacking phenomenon. Non-desalted samples also produced a stacking event, the mechanism of which is based on transient-isotachophoresis due to the presence of high-mobility ions in the digestion buffer itself. Adding either extra ammonium ions or acetonitrile into the non-desalted digests enhanced the stacking efficiency. A complex sample (yeast cell lysate) was also analyzed with the optimal conditions, which yielded similar tendencies.

SIGNIFICANCE

Based on these results, we propose that sample clean-up in the bottom-up sample preparation process prior to CZE-MS analysis can be omitted. The preclusion of desalting can even enhance detection sensitivity, separation efficiency or sequence coverage.

Plasma/Serum Proteomics based on Mass Spectrometry

Human blood is a window of physiology and disease. Examination of biomarkers in blood is a common clinical procedure, which can be informative in diagnosis and prognosis of diseases, and in evaluating treatment effectiveness. There is still a huge demand on new blood biomarkers and assays for precision medicine nowadays, therefore plasma/serum proteomics has attracted increasing attention in recent years. How to effectively proceed with the biomarker discovery and clinical diagnostic assay development is a question raised to researchers who are interested in this area. In this review, we comprehensively introduce the background and advancement of technologies for blood proteomics, with a focus on mass spectrometry (MS). Analyzing existing blood biomarkers and newly-built diagnostic assays based on MS can shed light on developing new biomarkers and analytical methods. We summarize various protein analytes in plasma/serum which include total proteome, protein post-translational modifications, and extracellular vesicles, focusing on their corresponding sample preparation methods for MS analysis. We propose screening multiple protein analytes in the same set of blood samples in order to increase success rate for biomarker discovery. We also review the trends of MS techniques for blood tests including sample preparation automation, and further provide our perspectives on their future directions.

Global detection of human variants and isoforms by deep proteome sequencing

An average shotgun proteomics experiment detects approximately 10,000 human proteins from a single sample. However, individual proteins are typically identified by peptide sequences representing a small fraction of their total amino acids. Hence, an average shotgun experiment fails to distinguish different protein variants and isoforms. Deeper proteome sequencing is therefore required for the global discovery of protein isoforms. Using six different human cell lines, six proteases, deep fractionation and three tandem mass spectrometry fragmentation methods, we identify a million unique peptides from 17,717 protein groups, with a median sequence coverage of approximately 80%. Direct comparison with RNA expression data provides evidence for the translation of most nonsynonymous variants. We have also hypothesized that undetected variants likely arise from mutation-induced protein instability. We further observe comparable detection rates for exon-exon junction peptides representing constitutive and alternative splicing events. Our dataset represents a resource for proteoform discovery and provides direct evidence that most frame-preserving alternatively spliced isoforms are translated.

On-Chip Comparison of the Performance of First- and Second-Generation Micropillar Array Columns

Because of its dimensions, the recently introduced micropillar array columns are most suited for high-efficiency liquid chromatography separations in proteomics. Unlike the packed bed columns and capillary-based column formats, the micropillar array concept still has significant room to progress in terms of the reduction of its characteristic size (i.e., pillar diameter and interpillar distance) to open the road to even higher-efficiency separations and their applications. We report here on the on-chip comparison between first-generation (Gen 1) and second-generation (Gen 2) micropillar array columns wherein the pillar and interpillar size have been halved. Because of the on-chip measurements, the observed plate heights H represent the fundamental band broadening, devoid of any extra-column band-broadening effects. The observed reduction of H with a factor of 2 around the uopt-velocity and with a factor of 4 in the C-term dominated regime of the van Deemter-curve is in full agreement with the theoretically expected gain. This shows the pillar and interpillar size reduction could be effectuated without affecting the theoretical separation potential of the micropillar arrays. Compared to Gen 1, Gen 2 offers a 4-fold reduction of the required analysis time around the optimal velocity and about a 16-fold reduction in the C-term-dominated range.

HIV-1 virological synapse formation enhances infection spread by dysregulating Aurora Kinase B

HIV-1 spreads efficiently through direct cell-to-cell transmission at virological synapses (VSs) formed by interactions between HIV-1 envelope proteins (Env) on the surface of infected cells and CD4 receptors on uninfected target cells. Env-CD4 interactions bring the infected and uninfected cellular membranes into close proximity and induce transport of viral and cellular factors to the VS for efficient virion assembly and HIV-1 transmission. Using novel, cell-specific stable isotope labeling and quantitative mass spectrometric proteomics, we identified extensive changes in the levels and phosphorylation states of proteins in HIV-1 infected producer cells upon mixing with CD4+ target cells under conditions inducing VS formation. These coculture-induced alterations involved multiple cellular pathways including transcription, TCR signaling and, unexpectedly, cell cycle regulation, and were dominated by Env-dependent responses. We confirmed the proteomic results using inhibitors targeting regulatory kinases and phosphatases in selected pathways identified by our proteomic analysis. Strikingly, inhibiting the key mitotic regulator Aurora kinase B (AURKB) in HIV-1 infected cells significantly increased HIV activity in cell-to-cell fusion and transmission but had little effect on cell-free infection. Consistent with this, we found that AURKB regulates the fusogenic activity of HIV-1 Env. In the Jurkat T cell line and primary T cells, HIV-1 Env:CD4 interaction also dramatically induced cell cycle-independent AURKB relocalization to the centromere, and this signaling required the long (150 aa) cytoplasmic C-terminal domain (CTD) of Env. These results imply that cytoplasmic/plasma membrane AURKB restricts HIV-1 envelope fusion, and that this restriction is overcome by Env CTD-induced AURKB relocalization. Taken together, our data reveal a new signaling pathway regulating HIV-1 cell-to-cell transmission and potential new avenues for therapeutic intervention through targeting the Env CTD and AURKB activity.

Proteome-wide structural changes measured with limited proteolysis-mass spectrometry: an advanced protocol for high-throughput applications

Proteins regulate biological processes by changing their structure or abundance to accomplish a specific function. In response to a perturbation, protein structure may be altered by various molecular events, such as post-translational modifications, protein-protein interactions, aggregation, allostery or binding to other molecules. The ability to probe these structural changes in thousands of proteins simultaneously in cells or tissues can provide valuable information about the functional state of biological processes and pathways. Here, we present an updated protocol for LiP-MS, a proteomics technique combining limited proteolysis with mass spectrometry, to detect protein structural alterations in complex backgrounds and on a proteome-wide scale. In LiP-MS, proteins undergo a brief proteolysis in native conditions followed by complete digestion in denaturing conditions, to generate structurally informative proteolytic fragments that are analyzed by mass spectrometry. We describe advances in the throughput and robustness of the LiP-MS workflow and implementation of data-independent acquisition-based mass spectrometry, which together achieve high reproducibility and sensitivity, even on large sample sizes. We introduce MSstatsLiP, an R package dedicated to the analysis of LiP-MS data for the identification of structurally altered peptides and differentially abundant proteins. The experimental procedures take 3 d, mass spectrometric measurement time and data processing depend on sample number and statistical analysis typically requires ~1 d. These improvements expand the adaptability of LiP-MS and enable wide use in functional proteomics and translational applications.

Recent advances in top-down proteome sample processing ahead of MS analysis

Top-down proteomics is emerging as a preferred approach to investigate biological systems, with objectives ranging from the detailed assessment of a single protein therapeutic, to the complete characterization of every possible protein including their modifications, which define the human proteoform. Given the controlling influence of protein modifications on their biological function, understanding how gene products manifest or respond to disease is most precisely achieved by characterization at the intact protein level. Top-down mass spectrometry (MS) analysis of proteins entails unique challenges associated with processing whole proteins while maintaining their integrity throughout the processes of extraction, enrichment, purification, and fractionation. Recent advances in each of these critical front-end preparation processes, including minimalistic workflows, have greatly expanded the capacity of MS for top-down proteome analysis. Acknowledging the many contributions in MS technology and sample processing, the present review aims to highlight the diverse strategies that have forged a pathway for top-down proteomics. We comprehensively discuss the evolution of front-end workflows that today facilitate optimal characterization of proteoform-driven biology, including a brief description of the clinical applications that have motivated these impactful contributions.

Lagovirus Non-structural Protein p23: A Putative Viroporin That Interacts With Heat Shock Proteins and Uses a Disulfide Bond for Dimerization

The exact function(s) of the lagovirus non-structural protein p23 is unknown as robust cell culture systems for the Rabbit haemorrhagic disease virus (RHDV) and other lagoviruses have not been established. Instead, a range of in vitro and in silico models have been used to study p23, revealing that p23 oligomerizes, accumulates in the cytoplasm, and possesses a conserved C-terminal region with two amphipathic helices. Furthermore, the positional homologs of p23 in other caliciviruses have been shown to possess viroporin activity. Here, we report on the mechanistic details of p23 oligomerization. Site-directed mutagenesis revealed the importance of an N-terminal cysteine for dimerization. Furthermore, we identified cellular interactors of p23 using stable isotope labeling with amino acids in cell culture (SILAC)-based proteomics; heat shock proteins Hsp70 and 110 interact with p23 in transfected cells, suggesting that they ‘chaperone’ p23 proteins before their integration into cellular membranes. We investigated changes to the global transcriptome and proteome that occurred in infected rabbit liver tissue and observed changes to the misfolded protein response, calcium signaling, and the regulation of the endoplasmic reticulum (ER) network. Finally, flow cytometry studies indicate slightly elevated calcium concentrations in the cytoplasm of p23-transfected cells. Taken together, accumulating evidence suggests that p23 is a viroporin that might form calcium-conducting channels in the ER membranes.

Practical Effects of Intramolecular Hydrogen Rearrangement in Electron Transfer Dissociation-Based Proteomics

Ion-ion reactions are valuable tools in mass-spectrometry-based peptide and protein sequencing. To boost the generation of sequence-informative fragment ions from low charge-density precursors, supplemental activation methods, via vibrational and photoactivation, have become widely adopted. However, long-lived radical peptide cations undergo intramolecular hydrogen atom transfer from c-type ions to z^•-type ions. Here we investigate the degree of hydrogen transfer for thousands of unique peptide cations where electron transfer dissociation (ETD) was performed and was followed by beam-type collisional activation (EThcD), resonant collisional activation (ETcaD), or concurrent infrared photoirradiation (AI-ETD). We report on the precursor charge density and the local amino acid environment surrounding bond cleavage to illustrate the effects of intramolecular hydrogen atom transfer for various precursor ions. Over 30% of fragments from EThcD spectra comprise distorted isotopic distributions, whereas over 20% of fragments from ETcaD have distorted distributions and less than 15% of fragments derived from ETD and AI-ETD reveal distorted isotopic distributions. Both ETcaD and EThcD give a relatively high degree of hydrogen migration, especially when D, G, N, S, and T residues were directly C-terminal to the cleavage site. Whereas all postactivation methods boost the number of c- and z^•-type fragment ions detected, the collision-based approaches produce higher rates of hydrogen migration, yielding fewer spectral identifications when only c- and z^•-type ions are considered. Understanding hydrogen rearrangement between c- and z^•-type ions will facilitate better spectral interpretation.

Data-Dependent Acquisition Ladder for Capillary Electrophoresis Mass Spectrometry-Based Ultrasensitive (Neuro)Proteomics

Measurement of broad types of proteins from a small number of cells to single cells would help to better understand the nervous system but requires significant leaps in sensitivity in high-resolution mass spectrometry (HRMS). Microanalytical capillary electrophoresis electrospray ionization (CE-ESI) offers a path to ultrasensitive proteomics by integrating scalability with sensitivity. Here, we systematically evaluate performance limitations in this technology to develop a data acquisition strategy with deeper coverage of the neuroproteome from trace amounts of starting materials than traditional dynamic exclusion. During standard data-dependent acquisition (DDA), compact migration challenged the duty cycle of second-stage transitions and redundant targeting of abundant peptide signals lowered their identification success rate. DDA was programmed to progressively exclude a static set of high-intensity peptide signals throughout replicate measurements, essentially forming rungs of a "DDA ladder." The method was tested for ∼500 pg portions of a protein digest from cultured hippocampal (primary) neurons (mouse), which estimated the total amount of protein from a single neuron. The analysis of ∼5 ng of protein digest over all replicates, approximating ∼10 neurons, identified 428 nonredundant proteins (415 quantified), an ∼35% increase over traditional DDA. The identified proteins were enriched in neuronal marker genes and molecular pathways of neurobiological importance. The DDA ladder enhances CE-HRMS sensitivity to single-neuron equivalent amounts of proteins, thus expanding the analytical toolbox of neuroscience.

Improving identification of low abundance and hydrophobic proteins using fluoroalcohol mediated supramolecular biphasic systems with quaternary ammonium salts

In this study, a newly discovered Supramolecular Biphasic System (S-BPS) was used in bottom-up proteomics of the Saccharomyces cerevisiae strain of yeast. We took advantage of S-BPS in bottom-up proteomics of this strain of yeast as the protein sample, while the results were compared to routinely used solubilizing reagents, such as urea, and sodium dodecyl sulfate (SDS). With the S-BPS, we identified 3043 proteins as compared to 2653 proteins that were identified in the control system. Interestingly, of the additional 390 proteins characterized by the S-BPS, 300 proteins were low abundance (less than 4000 molecules/cell). Remarkably, the identification of proteins at very low abundance (less than 2000 molecule/cell) was improved by 106%. This suggests that the S-BPS is particularly advantageous for detecting low abundance proteins. Gene Ontology (GO) analysis was conducted to find fractionation pattern of proteins in our two-phase system, and in nearly every gene ontology category, the S-BPS provided greater coverage than the control experiment, i.e., coverage for integral membrane proteins and mitochondrial ribosome proteins are improved by 18% and 58%, respectively. The improvements in proteins coverage for low abundance and membrane proteins can be attributed to the strong solubilizing power of the amphiphile-rich phase of this S-BPS and its capability for concomitant extraction, fractionation, and enrichment of the complex proteomics samples. Each phase has selectivity towards specific yeast protein groups, this selectivity is generally based on pI and hydrophobicity of proteins. Therefore, more hydrophobic proteins and acidic proteins exhibit greater affinities for the amphiphile-rich phase due to the hydrophobic effect and electrostatic interactions.

Proteomics, lipidomics, metabolomics and 16S DNA sequencing of dental plaque from patients with diabetes and periodontal disease

Oral microbiome influences human health, specifically prediabetes and type 2 diabetes (Pre-DM/DM) and periodontal diseases (PDs), through complex microbial interactions. To explore these relations, we performed 16S rDNA sequencing, metabolomics, lipidomics, and proteomics analyses on supragingival dental plaque collected from individuals with Pre-DM/DM (n = 39), Pre-DM/DM and PD (n = 37), PD alone (n = 11), or neither (n = 10). We identified on average 2790 operational taxonomic units and 2025 microbial and host proteins per sample and quantified 110 metabolites and 415 lipids. Plaque samples from Pre-DM/DM patients contained higher abundance of Fusobacterium and Tannerella than plaques from metabolically healthy patients. Phosphatidylcholines, plasmenyl phosphatidylcholines, ceramides containing non-OH fatty acids, and host proteins related to actin filament rearrangement were elevated in plaques from PD versus non-PD samples. Cross-omic correlation analysis enabled the detection of a strong association between Lautropia and monomethyl phosphatidylethanolamine (PE-NMe), which is striking because synthesis of PE-NMe is uncommon in oral bacteria. Lipidomics analysis of in vitro cultures of Lautropia mirabilis confirmed the synthesis of PE-NMe by the bacteria. This comprehensive analysis revealed a novel microbial metabolic pathway and significant associations of host-derived proteins with PD.

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Patients with periodontal disease or diabetes have unique microbial dysbiosis.

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Proteomics and 16S data provide complementary information about microbial diversity.

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Cross-omic correlation reveals host signatures associated with periodontal disease.

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Multi-omic data lead to finding about microbially synthesized lipids.

Dual role of Fam208a during zygotic cleavage and early embryonic development

Maintenance of genome stability is essential for every living cell as genetic information is repeatedly challenged during DNA replication in each cell division event. Errors, defects, delays, and mistakes that arise during mitosis or meiosis lead to an activation of DNA repair processes and in case of their failure, programmed cell death, i.e. apoptosis, could be initiated. Fam208a is a protein whose importance in heterochromatin maintenance has been described recently. In this work, we describe the crucial role of Fam208a in sustaining genome stability during cellular division. The targeted depletion of Fam208a in mice using CRISPR/Cas9 led to embryonic lethality before E12.5. We also used the siRNA approach to downregulate Fam208a in zygotes to avoid the influence of maternal RNA in the early stages of development. This early downregulation increased arresting of the embryonal development at the two-cell stage and the occurrence of multipolar spindles formation. To investigate this further, we used the yeast two-hybrid (Y2H) system and identified new putative interaction partners Gpsm2, Svil, and Itgb3bp. Their co-expression with Fam208a was assessed by RT-qPCR profiling and in situ hybridization [1] in multiple murine tissues. Based on these results we proposed that Fam208a functions within the HUSH complex by interaction with Mphosph8 as these proteins are not only able to physically interact but also co-localise. We are bringing new evidence that Fam208a is a multi-interacting protein affecting genome stability on the cell division level at the earliest stages of development and by interaction with methylation complex in adult tissues. In addition to its epigenetic functions, Fam208a appears to have an important role in the zygotic division, possibly via interaction with newly identified putative partners Gpsm2, Svil, and Itgb3bp.

Mutant Presenilin 1 Dysregulates Exosomal Proteome Cargo Produced by Human-Induced Pluripotent Stem Cell Neurons

The accumulation and propagation of hyperphosphorylated tau (p-Tau) is a neuropathological hallmark occurring with neurodegeneration of Alzheimer's disease (AD). Extracellular vesicles, exosomes, have been shown to initiate tau propagation in the brain. Notably, exosomes from human-induced pluripotent stem cell (iPSC) neurons expressing the AD familial A246E mutant form of presenilin 1 (mPS1) are capable of inducing tau deposits in the mouse brain after in vivo injection. To gain insights into the exosome proteome cargo that participates in propagating tau pathology, this study conducted proteomic analysis of exosomes produced by human iPSC neurons expressing A246E mPS1. Significantly, mPS1 altered the profile of exosome cargo proteins to result in (1) proteins present only in mPS1 exosomes and not in controls, (2) the absence of proteins in the mPS1 exosomes which were present only in controls, and (3) shared proteins which were upregulated or downregulated in the mPS1 exosomes compared to controls. These results show that mPS1 dysregulates the proteome cargo of exosomes to result in the acquisition of proteins involved in the extracellular matrix and protease functions, deletion of proteins involved in RNA and protein translation systems along with proteasome and related functions, combined with the upregulation and downregulation of shared proteins, including the upregulation of amyloid precursor protein. Notably, mPS1 neuron-derived exosomes displayed altered profiles of protein phosphatases and kinases involved in regulating the status of p-tau. The dysregulation of exosome cargo proteins by mPS1 may be associated with the ability of mPS1 neuron-derived exosomes to propagate tau pathology.

The clinical potential of prm-PASEF mass spectrometry

INTRODUCTION

The continuous technical improvement in sensitivity and specificity placed mass spectrometry as an alternative method for analyzing clinical samples. In parallel to the rapid development of discovery proteomics, targeted acquisition has been implemented as a complementary option for measuring a small set of proteins with high sensitivity and robustness in a large sample cohort. The combination of trapped ion mobility with a rapid time-of-flight (TOF) mass spectrometer improves the sensitivity even further and triggers the development of prm-PASEF.

AREAS COVERED

This article discusses the development of prm-PASEF and its advantages over the existing targeted and discovery methods for analyzing clinical samples. We are also highlighting the different requirements for the use of prm-PASEF on clinical samples.

EXPERT OPINION

prm-PASEF takes advantage of a dual ion-mobility trap enabling highly multiplexed targeted acquisition. It allows the implementation of a short chromatographic separation setup without sacrificing the number of targeted peptides. Analyzing clinical samples by prm-PASEF holds the promise to significantly improve throughput while maintaining sensitivity to detect the selected target proteins.

DIA-based systems biology approach unveils E3 ubiquitin ligase-dependent responses to a metabolic shift

The yeast Saccharomyces cerevisiae is a powerful model system for systems-wide biology screens and large-scale proteomics methods. Nearly complete proteomics coverage has been achieved owing to advances in mass spectrometry. However, it remains challenging to scale this technology for rapid and high-throughput analysis of the yeast proteome to investigate biological pathways on a global scale. Here we describe a systems biology workflow employing plate-based sample preparation and rapid, single-run, data-independent mass spectrometry analysis (DIA). Our approach is straightforward, easy to implement, and enables quantitative profiling and comparisons of hundreds of nearly complete yeast proteomes in only a few days. We evaluate its capability by characterizing changes in the yeast proteome in response to environmental perturbations, identifying distinct responses to each of them and providing a comprehensive resource of these responses. Apart from rapidly recapitulating previously observed responses, we characterized carbon source-dependent regulation of the GID E3 ligase, an important regulator of cellular metabolism during the switch between gluconeogenic and glycolytic growth conditions. This unveiled regulatory targets of the GID ligase during a metabolic switch. Our comprehensive yeast system readout pinpointed effects of a single deletion or point mutation in the GID complex on the global proteome, allowing the identification and validation of targets of the GID E3 ligase. Moreover, this approach allowed the identification of targets from multiple cellular pathways that display distinct patterns of regulation. Although developed in yeast, rapid whole-proteome-based readouts can serve as comprehensive systems-level assays in all cellular systems.

Survival Following Traumatic Brain Injury in Drosophila Is Increased by Heterozygosity for a Mutation of the NF-κB Innate Immune Response Transcription Factor Relish

Traumatic brain injury (TBI) pathologies are caused by primary and secondary injuries. Primary injuries result from physical damage to the brain, and secondary injuries arise from cellular responses to primary injuries. A characteristic cellular response is sustained activation of inflammatory pathways commonly mediated by nuclear factor-κB (NF-κB) transcription factors. Using a Drosophila melanogaster TBI model, we previously found that the main proximal transcriptional response to primary injuries is triggered by activation of Toll and Imd innate immune response pathways that engage NF-κB factors Dif and Relish (Rel), respectively. Here, we found by mass spectrometry that Rel protein level increased in fly heads at 4-8 hr after TBI. To investigate the necessity of Rel for secondary injuries, we generated a null allele, Reldel , by CRISPR/Cas9 editing. When heterozygous but not homozygous, the Reldel mutation reduced mortality at 24 hr after TBI and increased the lifespan of injured flies. Additionally, the effect of heterozygosity for Reldel on mortality was modulated by genetic background and diet. To identify genes that facilitate effects of Reldel on TBI outcomes, we compared genome-wide mRNA expression profiles of uninjured and injured +/+, +/Reldel , and Reldel /Reldel flies at 4 hr following TBI. Only a few genes changed expression more than twofold in +/Reldel flies relative to +/+ and Reldel /Reldel flies, and they were not canonical innate immune response genes. Therefore, Rel is necessary for TBI-induced secondary injuries but in complex ways involving Rel gene dose, genetic background, diet, and possibly small changes in expression of innate immune response genes.

Target identification and validation of natural products with label-free methodology: A critical review from 2005 to 2020

Natural products (NPs) have been an important source of therapeutic drugs in clinic use and contributed many chemical probes for research. The usefulness of NPs is however often marred by the incomplete understanding of their direct cellular targets. A number of experimental methods for drug target identification have been developed over the years. One class of methods, termed "label-free" methodology, exploits the energetic and biophysical features accompanying the association of macromolecules with drugs and other compounds in their native forms. Herein we review the working principles, assay implementations, and key applications of the most important approaches, and also give examples where they have been applied to NPs. We also assess the key advantages and limitations of each method. Furthermore, we address when and how the label-free methodology can be particularly useful considering some of the unique features of NP chemistry and bioactivation.

Proteomics in Non-model Organisms: A New Analytical Frontier

For the last century we have relied on model organisms to help understand fundamental biological processes. Now, with advancements in genome sequencing, assembly, and annotation, non-model organisms may be studied with the same advanced bioanalytical toolkit as model organisms. Proteomics is one such technique, which classically relies on predicted protein sequences to catalog and measure complex proteomes across tissues and biofluids. Applying proteomics to non-model organisms can advance and accelerate biomimicry studies, biomedical advancements, veterinary medicine, agricultural research, behavioral ecology, and food safety. In this postmodel organism era, we can study almost any species, meaning that many non-model organisms are, in fact, important emerging model organisms. Herein we specifically focus on eukaryotic organisms and discuss the steps to generate sequence databases, analyze proteomic data with or without a database, and interpret results as well as future research opportunities. Proteomics is more accessible than ever before and will continue to rapidly advance in the coming years, enabling critical research and discoveries in non-model organisms that were hitherto impossible.

SPOCD1 is an essential executor of piRNA-directed de novo DNA methylation

In mammals, the acquisition of the germline from the soma provides the germline with an essential challenge: the need to erase and reset genomic methylation1. In the male germline, RNA-directed DNA methylation silences young, active transposable elements2-4. The PIWI protein MIWI2 (PIWIL4) and its associated PIWI-interacting RNAs (piRNAs) instruct DNA methylation of transposable elements3,5. piRNAs are proposed to tether MIWI2 to nascent transposable element transcripts; however, the mechanism by which MIWI2 directs the de novo methylation of transposable elements is poorly understood, although central to the immortality of the germline. Here we define the interactome of MIWI2 in mouse fetal gonocytes undergoing de novo genome methylation and identify a previously unknown MIWI2-associated factor, SPOCD1, that is essential for the methylation and silencing of young transposable elements. The loss of Spocd1 in mice results in male-specific infertility but does not affect either piRNA biogenesis or the localization of MIWI2 to the nucleus. SPOCD1 is a nuclear protein whose expression is restricted to the period of de novo genome methylation. It co-purifies in vivo with DNMT3L and DNMT3A, components of the de novo methylation machinery, as well as with constituents of the NURD and BAF chromatin remodelling complexes. We propose a model whereby tethering of MIWI2 to a nascent transposable element transcript recruits repressive chromatin remodelling activities and the de novo methylation apparatus through SPOCD1. In summary, we have identified a previously unrecognized and essential executor of mammalian piRNA-directed DNA methylation.

Dysregulation of Exosome Cargo by Mutant Tau Expressed in Human-induced Pluripotent Stem Cell (iPSC) Neurons Revealed by Proteomics Analyses

Accumulation and propagation of hyperphosphorylated Tau (p-Tau) is a common neuropathological hallmark associated with neurodegeneration of Alzheimer's disease (AD), frontotemporal dementia and parkinsonism linked to chromosome 17 (FTDP-17), and related tauopathies. Extracellular vesicles, specifically exosomes, have recently been demonstrated to participate in mediating Tau propagation in brain. Exosomes produced by human induced pluripotent stem cell (iPSC)-derived neurons expressing mutant Tau (mTau), containing the P301L and V337M Tau mutations of FTDP-17, possess the ability to propagate p-Tau pathology after injection into mouse brain. To gain an understanding of the mTau exosome cargo involved in Tau pathogenesis, these pathogenic exosomes were analyzed by proteomics and bioinformatics. The data showed that mTau expression dysregulates the exosome proteome to result in 1) proteins uniquely present only in mTau, and not control exosomes, 2) the absence of proteins in mTau exosomes, uniquely present in control exosomes, and 3) shared proteins which were significantly upregulated or downregulated in mTau compared with control exosomes. Notably, mTau exosomes (not control exosomes) contain ANP32A (also known as I1PP2A), an endogenous inhibitor of the PP2A phosphatase which regulates the phosphorylation state of p-Tau. Several of the mTau exosome-specific proteins have been shown to participate in AD mechanisms involving lysosomes, inflammation, secretases, and related processes. Furthermore, the mTau exosomes lacked a substantial portion of proteins present in control exosomes involved in pathways of localization, vesicle transport, and protein binding functions. The shared proteins present in both mTau and control exosomes represented exosome functions of vesicle-mediated transport, exocytosis, and secretion processes. These data illustrate mTau as a dynamic regulator of the biogenesis of exosomes to result in acquisition, deletion, and up- or downregulation of protein cargo to result in pathogenic mTau exosomes capable of in vivo propagation of p-Tau neuropathology in mouse brain.

Orthogonal Proteomic Platforms and Their Implications for the Stable Classification of High-Grade Serous Ovarian Cancer Subtypes

The National Cancer Institute (NCI) Clinical Proteomic Tumor Analysis Consortium (CPTAC) established a harmonized method for large-scale clinical proteomic studies. SWATH-MS, an instance of data-independent acquisition (DIA) proteomic methods, is an alternate proteomic approach. In this study, we used SWATH-MS to analyze remnant peptides from the original retrospective TCGA samples generated for the CPTAC ovarian cancer proteogenomic study. The SWATH-MS results recapitulated the confident identification of differentially expressed proteins in enriched pathways associated with the robust Mesenchymal high-grade serous ovarian cancer subtype and the homologous recombination deficient tumors. Hence, SWATH/DIA-MS presents a promising complementary or orthogonal alternative to the CPTAC proteomic workflow, with the advantages of simpler and faster workflows and lower sample consumption, albeit with shallower proteome coverage. In summary, both analytical methods are suitable to characterize clinical samples, providing proteomic workflow alternatives for cancer researchers depending on the context-specific goals of the studies.

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SWATH-MS and iTRAQ-DDA are used to classify 103 high-grade serous ovarian cancer

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SWATH-MS re-capitulates differentially expressed proteins in ovarian cancer subtypes

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SWATH-MS is a robust proteomic approach for large-scale clinical proteomic studies

Spatially resolved proteomics in osteoarthritis: State of the art and new perspectives

Osteoarthritis (OA) is one of the most common diseases worldwide caused by chronic degeneration of the joints. Its high prevalence and the involvement of several tissues define OA as a highly heterogeneous disease. New biological markers to evaluate the progression of the pathology and improve its prognosis are needed. Among all the different -omic strategies applied to OA, solution phase bottom-up proteomics has made an extensive contribution to the field of biomarker research. However, new technologies for protein analysis should be considered for a better understanding of the disease. This review focuses on complementary proteomic methodologies and new technologies for translational research of OA and other rheumatic pathologies, especially mass spectrometry imaging and protein imaging methods not applied by the OA community yet.

Shot-gun proteomics: why thousands of unidentified signals matter

Mass spectrometry-based proteomics has become a constitutional part of the multi-omics toolbox in yeast research, advancing fundamental knowledge of molecular processes and guiding decisions in strain and product developmental pipelines. Nevertheless, post-translational protein modifications (PTMs) continue to challenge the field of proteomics. PTMs are not directly encoded in the genome; therefore, they require a sensitive analysis of the proteome itself. In yeast, the relevance of post-translational regulators has already been established, such as for phosphorylation, which can directly affect the reaction rates of metabolic enzymes. Whereas, the selective analysis of single modifications has become a broadly employed technique, the sensitive analysis of a comprehensive set of modifications still remains a challenge. At the same time, a large number of fragmentation spectra in a typical shot-gun proteomics experiment remain unidentified. It has been estimated that a good proportion of those unidentified spectra originates from unexpected modifications or natural peptide variants. In this review, recent advancements in microbial proteomics for unrestricted protein modification discovery are reviewed, and recent research integrating this additional layer of information to elucidate protein interaction and regulation in yeast is briefly discussed.

Discovery of Missing Methylation Sites on Endogenous Peptides of Human Cell Lines

Methylation of proteins has considerable impacts on physiological processes including signal transduction, DNA damage repair, transcriptional regulation, gene activation, and inhibition of gene expression. However, the traditional proteomics-based approach suffers from limited identification rates of these critical methylation sites on endogenous peptides. In this work, a peptidomics-based workflow was established to discover and characterize the global methylome of endogenous peptides in human cells. The reliability of our strategy was validated by methyl-SILAC labeling, resulting in 83% true-positive identifications in the HeLa cell line. We applied this approach to seven human cell lines, and 700 methylated forms on 646 putative methylation sites were identified in total, with over 61% of the methylation sites being newly identified. This study provides a complementary strategy for a traditional proteomics-based approach that enables identification of missing methylation sites and creates a first methylome draft of endogenous peptides of human cell lines, offering a valuable resource for in-depth studies of biological functions of methylated endogenous peptides.

Advanced Proteomics as a Powerful Tool for Studying Toxins of Human Bacterial Pathogens

Exotoxins contribute to the infectious processes of many bacterial pathogens, mainly by causing host tissue damages. The production of exotoxins varies according to the bacterial species. Recent advances in proteomics revealed that pathogenic bacteria are capable of simultaneously producing more than a dozen exotoxins. Interestingly, these toxins may be subject to post-transcriptional modifications in response to environmental conditions. In this review, we give an outline of different bacterial exotoxins and their mechanism of action. We also report how proteomics contributed to immense progress in the study of toxinogenic potential of pathogenic bacteria over the last two decades.

Maximizing Tandem Mass Spectrometry Acquisition Rates for Shotgun Proteomics

Advances in tandem mass spectrometry (MS/MS) acquisition rate have steadily led to increased performance in shotgun proteomics experiments. To that end, contemporary mass spectrometers are outfitted with multiple analyzers allowing for the simultaneous collection of survey (MS1) and MS/MS spectra. In the latest generation Orbitrap hybrid, MS/MS scans can be acquired at a high rate using the dual cell linear ion trap analyzer, all while the next precursor is being dissociated in a collision cell and a MS1 scan is occurring in the Orbitrap. Often overlooked in these experiments is that the ion trap scan duration is highly variable and dependent upon precursor mass. Here, we examine the use of various static mass-to-charge ratio scan ranges for ion trap MS/MS acquisition and determine performance relative to conventional dynamic mass-to-charge ratio range scanning. We demonstrate that a fixed mass-to-charge ratio scan range can generate 12% more MS/MS scans and more unique peptide identifications as compared to the standard dynamic approach, respectively.

Interactive Peptide Spectral Annotator: A Versatile Web-based Tool for Proteomic Applications

Here we present IPSA, an innovative web-based spectrum annotator that visualizes and characterizes peptide tandem mass spectra. A tool for the scientific community, IPSA can visualize peptides collected using a wide variety of experimental and instrumental configurations. Annotated spectra are customizable via a selection of interactive features and can be exported as editable scalable vector graphics to aid in the production of publication-quality figures. Single spectra can be analyzed through provided web forms, whereas data for multiple peptide spectral matches can be uploaded using the Proteomics Standards Initiative file formats mzTab, mzIdentML, and mzML. Alternatively, peptide identifications and spectral data can be provided using generic file formats. IPSA provides supports for annotating spectra collecting using negative-mode ionization and facilitates the characterization of experimental MS/MS performance through the optional export of fragment ion statistics from one to many peptide spectral matches. This resource is made freely accessible at http://interactivepeptidespectralannotator.com, whereas the source code and user guides are available at https://github.com/coongroup/IPSA for private hosting or custom implementations.

Proteome response of two natural strains of Saccharomyces cerevisiae with divergent lignocellulosic inhibitor stress tolerance

Strains of Saccharomyces cerevisiae with improved tolerance to plant hydrolysates are of utmost importance for the cost-competitive production of value-added chemicals and fuels. However, engineering strategies are constrained by a lack of understanding of the yeast response to complex inhibitor mixtures. Natural S. cerevisiae isolates display niche-specific phenotypic and metabolic diversity, encoded in their DNA, which has evolved to overcome external stresses, utilise available resources and ultimately thrive in their challenging environments. Industrial and laboratory strains, however, lack these adaptations due to domestication. Natural strains can serve as a valuable resource to mitigate engineering constraints by studying the molecular mechanisms involved in phenotypic variance and instruct future industrial strain improvement to lignocellulosic hydrolysates. We, therefore, investigated the proteomic changes between two natural S. cerevisiae isolates when exposed to a lignocellulosic inhibitor mixture. Comparative shotgun proteomics revealed that isolates respond by regulating a similar core set of proteins in response to inhibitor stress. Furthermore, superior tolerance was linked to NAD(P)/H and energy homeostasis, concurrent with inhibitor and reactive oxygen species detoxification processes. We present several candidate proteins within the redox homeostasis and energy management cellular processes as possible targets for future modification and study. Data are available via ProteomeXchange with identifier PXD010868.

Well-Defined Materials for High-Performance Chromatographic Separation

Chromatographic separation has been widely applied in various fields, such as chemical engineering, precision medicine, energy, and biology. Because chromatographic separation is based on differential partitioning between the mobile phase and stationary phase and affected by band dispersion and mass transfer resistance from these two phases, the materials used as the stationary phase play a decisive role in separation performance. In this review, we discuss the design of separation materials to achieve the separation with high efficiency and high resolution and highlight the well-defined materials with uniform pore structure and unique properties. The achievements, recent developments, challenges, and future trends of such materials are discussed. Furthermore, the surface functionalization of separation ma-terials for further improvement of separation performance is reviewed. Finally, future research directions and the challenges of chromatographic separation are presented.

Mass Spectrometry-Based Absolute Quantification of Single Xenopus Embryo Proteomes

Early Xenopus development is characterized by a poor correlation between global mRNA and protein abundances due to maternal mRNA and protein loading. Therefore, proteome profiling is necessary to study gene expression dynamics during early Xenopus development. In contrast to mammals, single Xenopus eggs and embryos contain enough protein to allow identification and quantification of thousands of proteins using mass spectrometry-based proteomics. In addition to investigating developmental processes, single egg or blastomere proteomes can be used to study cell-to-cell variability at an unprecedented depth. In this protocol, we describe a mass spectrometry-based proteomics approach for the identification and absolute quantification of Xenopus laevis egg or embryo proteomes, including sample preparation, peptide fractionation and separation, and data analysis.

Metabolic Remodeling during Biofilm Development of Bacillus subtilis

Bacterial biofilms are ubiquitous in natural environments and play an important role in many clinical, industrial, and ecological settings. Although much is known about the transcriptional regulatory networks that control biofilm formation in model bacteria such as Bacillus subtilis, very little is known about the role of metabolism in this complex developmental process. To address this important knowledge gap, we performed a time-resolved analysis of the metabolic changes associated with bacterial biofilm development in B. subtilis by combining metabolomic, transcriptomic, and proteomic analyses. Here, we report a widespread and dynamic remodeling of metabolism affecting central carbon metabolism, primary biosynthetic pathways, fermentation pathways, and secondary metabolism. This report serves as a unique hypothesis-generating resource for future studies on bacterial biofilm physiology. Outside the biofilm research area, this work should also prove relevant to any investigators interested in microbial physiology and metabolism.

Biofilms are structured communities of tightly associated cells that constitute the predominant state of bacterial growth in natural and human-made environments. Although the core genetic circuitry that controls biofilm formation in model bacteria such as Bacillus subtilis has been well characterized, little is known about the role that metabolism plays in this complex developmental process. Here, we performed a time-resolved analysis of the metabolic changes associated with pellicle biofilm formation and development in B. subtilis by combining metabolomic, transcriptomic, and proteomic analyses. We report surprisingly widespread and dynamic remodeling of metabolism affecting central carbon metabolism, primary biosynthetic pathways, fermentation pathways, and secondary metabolism. Most of these metabolic alterations were hitherto unrecognized as biofilm associated. For example, we observed increased activity of the tricarboxylic acid (TCA) cycle during early biofilm growth, a shift from fatty acid biosynthesis to fatty acid degradation, reorganization of iron metabolism and transport, and a switch from acetate to acetoin fermentation. Close agreement between metabolomic, transcriptomic, and proteomic measurements indicated that remodeling of metabolism during biofilm development was largely controlled at the transcriptional level. Our results also provide insights into the transcription factors and regulatory networks involved in this complex metabolic remodeling. Following upon these results, we demonstrated that acetoin production via acetolactate synthase is essential for robust biofilm growth and has the dual role of conserving redox balance and maintaining extracellular pH. This report represents a comprehensive systems-level investigation of the metabolic remodeling occurring during B. subtilis biofilm development that will serve as a useful road map for future studies on biofilm physiology.

Fam208a orchestrates interaction protein network essential for early embryonic development and cell division

Maintenance of genome stability is essential for every living cell as genetic information is repeatedly challenged during DNA replication in each cell division event. Errors, defects, delays, and mistakes that arise during mitosis or meiosis lead to an activation of DNA repair processes and in case of their failure, programmed cell death, i.e. apoptosis, could be initiated. Fam208a is a protein whose importance in heterochromatin maintenance has been described recently. In this work, we describe the crucial role of Fam208a in sustaining the genome stability during the cellular division. The targeted depletion of Fam208a in mice using CRISPR/Cas9 leads to embryonic lethality before E12.5. We also used the siRNA approach to downregulate Fam208a in zygotes to avoid the influence of maternal RNA in the early stages of development. This early downregulation increased arresting of the embryonal development at the two-cell stage and occurrence of multipolar spindles formation. To investigate this further, we used the yeast two-hybrid (Y2H) system and identified new putative interaction partners Gpsm2, Amn1, Eml1, Svil, and Itgb3bp. Their co-expression with Fam208a was assessed by qRT-PCR profiling and in situ hybridisation [1] in multiple murine tissues. Based on these results we proposed that Fam208a functions within the HUSH complex by interaction with Mphosph8 as these proteins are not only able to physically interact but also co-localise. We are bringing new evidence that Fam208a is multi-interacting protein affecting genome stability on the level of cell division at the earliest stages of development and also by interaction with methylation complex in adult tissues. In addition to its epigenetic functions, Fam208a appears to have an additional role in zygotic division, possibly via interaction with newly identified putative partners Gpsm2, Amn1, Eml1, Svil, and Itgb3bp.

A comprehensive pipeline for translational top-down proteomics from a single blood draw

Top-down proteomics (TDP) by mass spectrometry (MS) is a technique by which intact proteins are analyzed. It has become increasingly popDesalting and concentrating GELFrEEular in translational research because of the value of characterizing distinct proteoforms of intact proteins. Compared to bottom-up proteomics (BUP) strategies, which measure digested peptide mixtures, TDP provides highly specific molecular information that avoids the bioinformatic challenge of protein inference. However, the technique has been difficult to implement widely because of inherent limitations of existing sample preparation methods and instrumentation. Recent improvements in proteoform pre-fractionation and the availability of high-resolution benchtop mass spectrometers have made it possible to use high-throughput TDP for the analysis of complex clinical samples. Here, we provide a comprehensive protocol for analysis of a common sample type in translational research: human peripheral blood mononuclear cells (PBMCs). The pipeline comprises multiple workflows that can be treated as modular by the reader and used for various applications. First, sample collection and cell preservation are described for two clinical biorepository storage schemes. Cell lysis and proteoform pre-fractionation by gel-eluted liquid fractionation entrapment electrophoresis are then described. Importantly, instrument setup and liquid chromatography-tandem MS are described for TDP analyses, which rely on high-resolution Fourier-transform MS. Finally, data processing and analysis are described using two different, application-dependent software tools: ProSight Lite for targeted analyses of one or a few proteoforms and TDPortal for high-throughput TDP in discovery mode. For a single sample, the minimum completion time of the entire experiment is 72 h.

Proteotoxicity from aberrant ribosome biogenesis compromises cell fitness

To achieve maximal growth, cells must manage a massive economy of ribosomal proteins (r-proteins) and RNAs (rRNAs) to produce thousands of ribosomes every minute. Although ribosomes are essential in all cells, natural disruptions to ribosome biogenesis lead to heterogeneous phenotypes. Here, we model these perturbations in Saccharomyces cerevisiae and show that challenges to ribosome biogenesis result in acute loss of proteostasis. Imbalances in the synthesis of r-proteins and rRNAs lead to the rapid aggregation of newly synthesized orphan r-proteins and compromise essential cellular processes, which cells alleviate by activating proteostasis genes. Exogenously bolstering the proteostasis network increases cellular fitness in the face of challenges to ribosome assembly, demonstrating the direct contribution of orphan r-proteins to cellular phenotypes. We propose that ribosome assembly is a key vulnerability of proteostasis maintenance in proliferating cells that may be compromised by diverse genetic, environmental, and xenobiotic perturbations that generate orphan r-proteins.

Cells are made up of thousands of different proteins that perform unique roles required for life. To create all of these proteins, cells use machines called ribosomes that are partly formed of elements known as r-proteins. When cells grow and divide, the ribosomes have to make copies of themselves through a process called ribosome biogenesis.

Although all cells need ribosomes, certain types of cells are especially sensitive to events that interfere with ribosome biogenesis. For example, patients that have mutations in genes needed for ribosome biogenesis produce fewer red blood cells, but their other cells and tissues are mostly healthy. It is not clear why some cells are more sensitive than others.

Ribosome biogenesis is very similar between different organisms, so researchers often use budding yeast as a model to study the process. Here, Tye et al. used genetic and chemical tools to interfere with ribosome biogenesis on short time scales, which made it possible to detect early on what was going wrong in the cells.

The experiments found that when ribosome biogenesis was disrupted, r-proteins that were waiting to be assembled into ribosomes quickly stuck to one another and formed clumps that reduced the ability of the yeast cells to grow. The cells responded by switching on a protein called Hsf1, which restored their ability to grow. Yeast cells that were growing quickly, and therefore making more ribosomes, were more sensitive to abnormal ribosome biogenesis than slow-growing cells.

These results indicate that how actively a cell is growing, and its ability to cope with r-proteins sticking together, may in part explain why certain cells are more vulnerable to events that interfere with ribosome biogenesis. Since human cells also have Hsf1, future experiments could investigate whether turning it on might also protect fast-growing human cells from such events.

Proteomic Atlas of the Human Brain in Alzheimer's Disease

The brain represents one of the most divergent and critical organs in the human body. Yet, it can be afflicted by a variety of neurodegenerative diseases specifically linked to aging, about which we lack a full biomolecular understanding of onset and progression, such as Alzheimer's disease (AD). Here we provide a proteomic resource comprising nine anatomically distinct sections from three aged individuals, across a spectrum of disease progression, categorized by quantity of neurofibrillary tangles. Using state-of-the-art mass spectrometry, we identify a core brain proteome that exhibits only small variance in expression, accompanied by a group of proteins that are highly differentially expressed in individual sections and broader regions. AD affected tissue exhibited slightly elevated levels of tau protein with similar relative expression to factors associated with the AD pathology. Substantial differences were identified between previous proteomic studies of mature adult brains and our aged cohort. Our findings suggest considerable value in examining specifically the brain proteome of aged human populations from a multiregional perspective. This resource can serve as a guide, as well as a point of reference for how specific regions of the brain are affected by aging and neurodegeneration.

More Is Not Always Better: Evaluation of 1D and 2D-LC-MS/MS Methods for Metaproteomics

Metaproteomics, the study of protein expression in microbial communities, is a versatile tool for environmental microbiology. Achieving sufficiently high metaproteome coverage to obtain a comprehensive picture of the activities and interactions in microbial communities is one of the current challenges in metaproteomics. An essential step to maximize the number of identified proteins is peptide separation via liquid chromatography (LC) prior to mass spectrometry (MS). Thorough optimization and comparison of LC methods for metaproteomics are, however, currently lacking. Here, we present an extensive development and test of different 1D and 2D-LC approaches for metaproteomic peptide separations. We used fully characterized mock community samples to evaluate metaproteomic approaches with very long analytical columns (50 and 75 cm) and long gradients (up to 12 h). We assessed a total of over 20 different 1D and 2D-LC approaches in terms of number of protein groups and unique peptides identified, peptide spectrum matches (PSMs) generated, the ability to detect proteins of low-abundance species, the effect of technical replicate runs on protein identifications and method reproducibility. We show here that, while 1D-LC approaches are faster and easier to set up and lead to more identifications per minute of runtime, 2D-LC approaches allow for a higher overall number of identifications with up to >10,000 protein groups identified. We also compared the 1D and 2D-LC approaches to a standard GeLC workflow, in which proteins are pre-fractionated via gel electrophoresis. This method yielded results comparable to the 2D-LC approaches, however with the drawback of a much increased sample preparation time. Based on our results, we provide recommendations on how to choose the best LC approach for metaproteomics experiments, depending on the study aims.

Fast Proteome Identification and Quantification from Data-Dependent Acquisition-Tandem Mass Spectrometry (DDA MS/MS) Using Free Software Tools

The identification of nearly all proteins in a biological system using data-dependent acquisition (DDA) tandem mass spectrometry has become routine for organisms with relatively small genomes such as bacteria and yeast. Still, the quantification of the identified proteins may be a complex process and often requires multiple different software packages. In this protocol, I describe a flexible strategy for the identification and label-free quantification of proteins from bottom-up proteomics experiments. This method can be used to quantify all the detectable proteins in any DDA dataset collected with high-resolution precursor scans and may be used to quantify proteome remodeling in response to drug treatment or a gene knockout. Notably, the method is statistically rigorous, uses the latest and fastest freely-available software, and the entire protocol can be completed in a few hours with a small number of data files from the analysis of yeast.

From Yeast to Humans: Leveraging New Approaches in Yeast to Accelerate Discovery of Therapeutic Targets for Synucleinopathies

Neurodegenerative diseases (ND) represent a growing, global health crisis, one that lacks any disease-modifying therapeutic strategy. This critical need for new therapies must be met with an exhaustive approach to exploit all tools available. A yeast (Saccharomyces cerevisiae) model of α-synuclein toxicity-the protein causally linked to Parkinson's disease and other synucleinopathies-offers a powerful approach that takes advantage of the unique offerings of this system: tractable genetics, robust high-throughput screening strategies, unparalleled data repositories, powerful computational tools, and extensive evolutionary conservation of fundamental biological pathways. These attributes have enabled genetic and small molecule screens that have revealed toxic phenotypes and drug targets that translate directly to patient-derived iPSC neurons. Extending these insights, recent advances in genetic network analyses have generated the first "humanized" α-synuclein network, which has identified druggable proteins and led to validation of the toxic phenotypes in patient-derived cells. Unbiased phenotypic small molecule screens can identify compounds targeting critical proteins within α-synuclein networks. While identification of direct drug targets for phenotypic screen hits represents a bottleneck, high-throughput chemical genetic methods provide a means to uncover cellular targets and pathways for large numbers of compounds in parallel. Taken together, the yeast α-synuclein model and associated tools can reveal insights into underlying cellular pathologies, lead molecules and their cognate targets, and strategies to translate mechanisms of toxicity and cytoprotection into complex neuronal systems.

The cellular economy of the Saccharomyces cerevisiae zinc proteome

Zinc is an essential cofactor for many proteins. A key mechanism of zinc homeostasis during deficiency is "zinc sparing" in which specific zinc-binding proteins are repressed to reduce the cellular requirement. In this report, we evaluated zinc sparing across the zinc proteome of Saccharomyces cerevisiae. The yeast zinc proteome of 582 known or potential zinc-binding proteins was identified using a bioinformatics analysis that combined global domain searches with local motif searches. Protein abundance was determined by mass spectrometry. In zinc-replete cells, we detected over 2500 proteins among which 229 were zinc proteins. Based on copy number estimates and binding stoichiometries, a replete cell contains ∼9 million zinc-binding sites on proteins. During zinc deficiency, many zinc proteins decreased in abundance and the zinc-binding requirement decreased to ∼5 million zinc atoms per cell. Many of these effects were due at least in part to changes in mRNA levels rather than simply protein degradation. Measurements of cellular zinc content showed that the level of zinc atoms per cell dropped from over 20 million in replete cells to only 1.7 million in deficient cells. These results confirmed the ability of replete cells to store excess zinc and suggested that the majority of zinc-binding sites on proteins in deficient cells are either unmetalated or mismetalated. Our analysis of two abundant zinc proteins, Fba1 aldolase and Met6 methionine synthetase, supported that hypothesis. Thus, we have discovered widespread zinc sparing mechanisms and obtained evidence of a high accumulation of zinc proteins that lack their cofactor during deficiency.

A Streamlined Sample Preparation Method for Mass Spectrometric Analysis

Mass spectrometry-based proteomic technology experienced remarkable advancement in the past decades. However, their application was still hampered by the complexity of sample preparation. Conventional strategies for sample preparation incorporate multiple time-consuming steps, including cell lysis, protein extraction, protease cleavage, and desalting. Thus, we explored a simplified method (the cell-absorb method) during which living cells were absorbed into vacuum-dried polyacrylamide gel and directly digested in gel into peptides for subsequent LC-MS/MS analysis. As a consequence, both of the steps for cell lysis and protein extraction involved in traditional protocol were skipped. In addition to the decrease in time, more proteins were identified. Indeed, 3022 proteins were identified by the cell-absorb method. Meanwhile, only 2642 and 2420 proteins were identified by the classical SDS-PAGE based method and the reported gel absorption-based method, respectively. The cell-absorb method exhibited apparent advantage in terms of the depth of proteome coverage. Furthermore, the number of proteins identified show excellent reproducibility with a CV (coefficient of variation) of 0.03 among three replicates using the cell-absorb method. These advantages suggest that cell-absorb method is a promising choice for mapping the whole proteome of cells. © 2018 by John Wiley & Sons, Inc.

Rapid Screening of Ellagitannins in Natural Sources via Targeted Reporter Ion Triggered Tandem Mass Spectrometry

Complex biomolecules present in their natural sources have been difficult to analyze using traditional analytical approaches. Ultrahigh-performance liquid chromatography (UHPLC-MS/MS) methods have the potential to enhance the discovery of a less well characterized and challenging class of biomolecules in plants, the ellagitannins. We present an approach that allows for the screening of ellagitannins by employing higher energy collision dissociation (HCD) to generate reporter ions for classification and collision-induced dissociation (CID) to generate unique fragmentation spectra for isomeric variants of previously unreported species. Ellagitannin anions efficiently form three characteristic reporter ions after HCD fragmentation that allows for the classification of unknown precursors that we call targeted reporter ion triggering (TRT). We demonstrate how a tandem HCD-CID experiment might be used to screen natural sources using UHPLC-MS/MS by application of 22 method conditions from which an optimized data-dependent acquisition (DDA) emerged. The method was verified not to yield false-positive results in complex plant matrices. We were able to identify 154 non-isomeric ellagitannins from strawberry leaves, which is 17 times higher than previously reported in the same matrix. The systematic inclusion of CID spectra for isomers of each species classified as an ellagitannin has never been possible before the development of this approach.

The Value of Activated Ion Electron Transfer Dissociation for High-Throughput Top-Down Characterization of Intact Proteins

High-throughput top-down proteomic experiments directly identify proteoforms in complex mixtures, making high quality tandem mass spectra necessary to deeply characterize proteins with many sources of variation. Collision-based dissociation methods offer expedient data acquisition but often fail to extensively fragment proteoforms for thorough analysis. Electron-driven dissociation methods are a popular alternative approach, especially for precursor ions with high charge density. Combining infrared photoactivation concurrent with electron transfer dissociation (ETD) reactions, i.e., activated ion ETD (AI-ETD), can significantly improve ETD characterization of intact proteins, but benefits of AI-ETD have yet to be quantified in high-throughput top-down proteomics. Here, we report the first application of AI-ETD to LC-MS/MS characterization of intact proteins (<20 kDa), highlighting improved proteoform identification the method offers over higher energy-collisional dissociation (HCD), standard ETD, and ETD followed by supplemental HCD activation (EThcD). We identified 935 proteoforms from 295 proteins from human colorectal cancer cell line HCT116 using AI-ETD compared to 1014 proteoforms, 915 proteoforms, and 871 proteoforms with HCD, ETD, and EThcD, respectively. Importantly, AI-ETD outperformed each of the three other methods in MS/MS success rates and spectral quality metrics (e.g., sequence coverage achieved and proteoform characterization scores). In all, this four-method analysis offers the most extensive comparisons to date and demonstrates that AI-ETD both increases identifications over other ETD methods and improves proteoform characterization via higher sequence coverage, positioning it as a premier method for high-throughput top-down proteomics.