A molecular network of conserved factors keeps ribosomes dormant in the egg.

Ribosomes are produced in large quantities during oogenesis and are stored in the egg. However, the egg and early embryo are translationally repressed1-4. Here, using mass spectrometry and cryo-electron microscopy analyses of ribosomes isolated from zebrafish (Danio rerio) and Xenopus laevis eggs and embryos, we provide molecular evidence that ribosomes transition from a dormant state to an active state during the first hours of embryogenesis. Dormant ribosomes are associated with four conserved factors that form two modules, consisting of Habp4-eEF2 and death associated protein 1b (Dap1b) or Dap in complex with eIF5a. Both modules occupy functionally important sites and act together to stabilize ribosomes and repress translation. Dap1b (also known as Dapl1 in mammals) is a newly discovered translational inhibitor that stably inserts into the polypeptide exit tunnel. Addition of recombinant zebrafish Dap1b protein is sufficient to block translation and reconstitute the dormant egg ribosome state in a mammalian translation extract in vitro. Thus, a developmentally programmed, conserved ribosome state has a key role in ribosome storage and translational repression in the egg.

Label-free single cell proteomics utilizing ultrafast LC and MS instrumentation: A valuable complementary technique to multiplexing.

The ability to map a proteomic fingerprint to transcriptomic data would master the understanding of how gene expression translates into actual phenotype. In contrast to nucleic acid sequencing, in vitro protein amplification is impossible and no single cell proteomic workflow has been established as gold standard yet. Advances in microfluidic sample preparation, multi-dimensional sample separation, sophisticated data acquisition strategies, and intelligent data analysis algorithms have resulted in major improvements to successfully analyze such tiny sample amounts with steadily boosted performance. However, among the broad variation of published approaches, it is commonly accepted that highest possible sensitivity, robustness, and throughput are still the most urgent needs for the field. While many labs have focused on multiplexing to achieve these goals, label-free SCP is a highly promising strategy as well whenever high dynamic range and unbiased accurate quantification are needed. We here focus on recent advances in label-free single-cell mass spectrometry workflows and try to guide our readers to choose the best method or combinations of methods for their specific applications. We further highlight which techniques are most propitious in the future and which applications but also limitations we foresee for the field.

MS Annika 2.0 Identifies Cross-Linked Peptides in MS2-MS3-Based Workflows at High Sensitivity and Specificity.

Cross-linking mass spectrometry has become a powerful tool for the identification of protein-protein interactions and for gaining insight into the structures of proteins. We previously published MS Annika, a cross-linking search engine which can accurately identify cross-linked peptides in MS2 spectra from a variety of different MS-cleavable cross-linkers. In this publication, we present MS Annika 2.0, an updated version implementing a new search algorithm that, in addition to MS2 level, only supports the processing of data from MS2-MS3-based approaches for the identification of peptides from MS3 spectra, and introduces a novel scoring function for peptides identified across multiple MS stages. Detected cross-links are validated by estimating the false discovery rate (FDR) using a target-decoy approach. We evaluated the MS3-search-capabilities of MS Annika 2.0 on five different datasets covering a variety of experimental approaches and compared it to XlinkX and MaXLinker, two other cross-linking search engines. We show that MS Annika detects up to 4 times more true unique cross-links while simultaneously yielding less false positive hits and therefore a more accurate FDR estimation than the other two search engines. All mass spectrometry proteomics data along with result files have been deposited to the ProteomeXchange consortium via the PRIDE partner repository with the dataset identifier PXD041955.

Robust and Easy-to-Use One-Pot Workflow for Label-Free Single-Cell Proteomics.

The analysis of ultralow input samples or even individual cells is essential to answering a multitude of biomedical questions, but current proteomic workflows are limited in their sensitivity and reproducibility. Here, we report a comprehensive workflow that includes improved strategies for all steps, from cell lysis to data analysis. Thanks to convenient-to-handle 1 µL sample volume and standardized 384-well plates, the workflow is easy for even novice users to implement. At the same time, it can be performed semi-automatized using CellenONE, which allows for the highest reproducibility. To achieve high throughput, ultrashort gradient lengths down to 5 min were tested using advanced µ-pillar columns. Data-dependent acquisition (DDA), wide-window acquisition (WWA), data-independent acquisition (DIA), and commonly used advanced data analysis algorithms were benchmarked. Using DDA, 1790 proteins covering a dynamic range of four orders of magnitude were identified in a single cell. Using DIA, proteome coverage increased to more than 2200 proteins identified from single-cell level input in a 20 min active gradient. The workflow enabled differentiation of two cell lines, demonstrating its suitability to cellular heterogeneity determination.

A High-Sensitivity Low-Nanoflow LC-MS Configuration for High-Throughput Sample-Limited Proteomics.

This work demonstrates the utility of high-throughput nanoLC-MS and label-free quantification (LFQ) for sample-limited bottom-up proteomics analysis, including single-cell proteomics (SCP). Conditions were optimized on a 50 µm internal diameter (I.D.) column operated at 100 nL/min in the direct injection workflow to balance method sensitivity and sample throughput from 24 to 72 samples/day. Multiple data acquisition strategies were also evaluated for proteome coverage, including data-dependent acquisition (DDA), wide-window acquisition (WWA), and wide-window data-independent acquisition (WW-DIA). Analyzing 250 pg HeLa digest with a 10-min LC gradient (72 samples/day) provided >900, >1,800, and >3,000 protein group identifications for DDA, WWA, and WW-DIA, respectively. Total method cycle time was further reduced from 20 to 14.4 min (100 samples/day) by employing a trap-and-elute workflow, enabling 70% mass spectrometer utilization. The method was applied to library-free DIA analysis of single-cell samples, yielding >1,700 protein groups identified. In conclusion, this study provides a high-sensitivity, high-throughput nanoLC-MS configuration for sample-limited proteomics.

Deep Proteome Profiling with Reduced Carryover Using Superficially Porous Microfabricated nanoLC Columns.

In the field of liquid chromatography-mass spectrometry (LC-MS)-based proteomics, increases in the sampling depth and proteome coverage have mainly been accomplished by rapid advances in mass spectrometer technology. The comprehensiveness and quality of the data that can be generated do, however, also depend on the performance provided by nano-liquid chromatography (nanoLC) separations. Proper selection of reversed-phase separation columns can be important to provide the MS instrument with peptides at the highest possible concentration and separated at the highest possible resolution. In the current contribution, we evaluate the use of the prototype generation 2 µPAC nanoLC columns, which use C18-functionalized superficially porous micropillars as a stationary phase. When compared to traditionally used fully porous silica stationary phases, more precursors could be characterized when performing single shot data-dependent LC-MS/MS analyses of a human cell line tryptic digest. Up to 30% more protein groups and 60% more unique peptides were identified for short gradients (10 min) and limited sample amounts (10-100 ng of cell lysate digest). With LC-MS gradient times of 10, 60, 120, and 180 min, respectively, we identified 2252, 6513, 7382, and 8174 protein groups with 25, 500, 1000, and 2000 ng of the sample loaded on the column. Reduction of sample carryover to the next run (up to 2 to 3%) and decreased levels of methionine oxidation (up to 3-fold) were identified as additional figures of merit. When analyzing a disuccinimidyl dibutyric urea-crosslinked synthetic library, 29 to 59 more unique crosslinked peptides could be identified at an experimentally validated false discovery rate of 1-2%.

Cleavable Cross-Linkers and Mass Spectrometry for the Ultimate Task of Profiling Protein-Protein Interaction Networks in Vivo.

Cross-linking mass spectrometry (XL-MS) has matured into a potent tool to identify protein-protein interactions or to uncover protein structures in living cells, tissues, or organelles. The unique ability to investigate the interplay of proteins within their native environment delivers valuable complementary information to other advanced structural biology techniques. This Review gives a comprehensive overview of the current possible applications as well as the remaining limitations of the technique, focusing on cross-linking in highly complex biological systems like cells, organelles, or tissues. Thanks to the commercial availability of most reagents and advances in user-friendly data analysis, validation, and visualization tools, studies using XL-MS can, in theory, now also be utilized by nonexpert laboratories.

MS Annika: A New Cross-Linking Search Engine.

Cross-linking mass spectrometry (XL-MS) has become a powerful technique that enables insights into protein structures and protein interactions. The development of cleavable cross-linkers has further promoted XL-MS through search space reduction, thereby allowing for proteome-wide studies. These new analysis possibilities foster the development of new cross-linkers, which not every search engine can deal with out of the box. In addition, some search engines for XL-MS data also struggle with the validation of identified cross-linked peptides, that is, false discovery rate (FDR) estimation, as FDR calculation is hampered by the fact that not only one but two peptides in a single spectrum have to be correct. We here present our new search engine, MS Annika, which can identify cross-linked peptides in MS2 spectra from a wide variety of cleavable cross-linkers. We show that MS Annika provides realistic estimates of FDRs without the need of arbitrary score cutoffs, being able to provide on average 44% more identifications at a similar or better true FDR than comparable tools. In addition, MS Annika can be used on proteome-wide studies due to fast, parallelized processing and provides a way to visualize the identified cross-links in protein 3D structures.

Fast and Highly Efficient Affinity Enrichment of Azide-A-DSBSO Cross-Linked Peptides.

Cross-linking mass spectrometry is an increasingly used, powerful technique to study protein-protein interactions or to provide structural information. Due to substochiometric reaction efficiencies, cross-linked peptides are usually low abundance. This results in challenging data evaluation and the need for an effective enrichment. Here we describe an improved, easy to implement, one-step method to enrich azide-tagged, acid-cleavable disuccinimidyl bis-sulfoxide (DSBSO) cross-linked peptides using dibenzocyclooctyne (DBCO) coupled Sepharose beads. We probed this method using recombinant Cas9 and E. coli ribosome. For Cas9, the number of detectable cross-links was increased from ∼100 before enrichment to 580 cross-links after enrichment. To mimic a cellular lysate, E. coli ribosome was spiked into a tryptic HEK background at a ratio of 1:2-1:100. The number of detectable unique cross-links was maintained high at ∼100. The estimated enrichment efficiency was improved by a factor of 4-5 (based on XL numbers) compared to enrichment via biotin and streptavidin. We were still able to detect cross-links from 0.25 µg cross-linked E. coli ribosomes in a background of 100 µg tryptic HEK peptides, indicating a high enrichment sensitivity. In contrast to conventional enrichment techniques, like SEC, the time needed for preparation and MS measurement is significantly reduced. This robust, fast, and selective enrichment method for azide-tagged linkers will contribute to mapping protein-protein interactions, investigating protein architectures in more depth, and helping to understand complex biological processes.

Micropillar arrays, wide window acquisition and AI-based data analysis improve comprehensiveness in multiple proteomic applications.

Comprehensive proteomic analysis is essential to elucidate molecular pathways and protein functions. Despite tremendous progress in proteomics, current studies still suffer from limited proteomic coverage and dynamic range. Here, we utilize micropillar array columns (µPACs) together with wide-window acquisition and the AI-based CHIMERYS search engine to achieve excellent proteomic comprehensiveness for bulk proteomics, affinity purification mass spectrometry and single cell proteomics. Our data show that µPACs identify ≤50% more peptides and ≤24% more proteins, while offering improved throughput, which is critical for large (clinical) proteomics studies. Combining wide precursor isolation widths of m/z 4-12 with the CHIMERYS search engine identified +51-74% and +59-150% more proteins and peptides, respectively, for single cell, co-immunoprecipitation, and multi-species samples over a conventional workflow at well-controlled false discovery rates. The workflow further offers excellent precision, with CVs <7% for low input bulk samples, and accuracy, with deviations <10% from expected fold changes for regular abundance two-proteome mixes. Compared to a conventional workflow, our entire optimized platform discovered 92% more potential interactors in a protein-protein interaction study on the chromatin remodeler Smarca5/Snf2h. These include previously described Smarca5 binding partners and undescribed ones including Arid1a, another chromatin remodeler with key roles in neurodevelopmental and malignant disorders.

Mimicked synthetic ribosomal protein complex for benchmarking crosslinking mass spectrometry workflows.

Cross-linking mass spectrometry has matured to a frequently used tool for the investigation of protein structures as well as interactome studies up to a system-wide level. The growing community generated a broad spectrum of applications, linker types, acquisition strategies and specialized data analysis tools, which makes it challenging to decide for an appropriate analysis workflow. Here, we report a large and flexible synthetic peptide library as reliable instrument to benchmark crosslink workflows. Additionally, we provide a tool, IMP-X-FDR, that calculates the real, experimentally validated, FDR, compares results across search engine platforms and analyses crosslink properties in an automated manner. We apply the library with 6 commonly used linker reagents and analyse the data with 6 established search engines. We thereby show that the correct algorithm and search setting choice is highly important to improve identification rate and reliability. We reach identification rates of up to ~70 % of the theoretical maximum (i.e. 700 unique lysine-lysine cross-links) while maintaining a real false-discovery-rate of <3 % at cross-link level with high reproducibility, representatively showing that our test system delivers valuable and statistically solid results.

AMPK Enhances Transcription of Selected Nrf2 Target Genes via Negative Regulation of Bach1.

5'-AMP-activated protein kinase (AMPK) and the transcription factor nuclear factor erythroid 2-related factor 2 (Nrf2) are main players in the cellular adaptive response to metabolic and oxidative/xenobiotic stress, respectively. AMPK does not only balance the rate of fuel catabolism versus anabolism but also emerges as regulator of gene expression. We here examined the influence of AMPK on Nrf2-dependent gene transcription and the potential interplay of the two cellular stress hubs. Using gene expression analyses in wt and AMPKα1 -/- or Nrf2 -/- mouse embryonal fibroblasts, we could show that AMPK only affected a portion of the entire of Nrf2-dependent transcriptome upon exposure to the Nrf2 activator sulforaphane (Sfn). Focusing on selected genes with positive regulation by Nrf2 and either positive or no further regulation by AMPK, we revealed that altered Nrf2 levels could not account for the distinct extent of transactivation of certain Nrf2 targets in wt and AMPK -/- cells (assessed by immunoblot). FAIRE-qPCR largely excluded distinct chromatin accessibility of selected Nrf2-responsive antioxidant response elements (ARE) within the regulatory gene regions in wt and AMPK-/- cells. However, expression analyses and ChIP-qPCR showed that in AMPK-/- cells, levels of BTB and CNC homology 1 (Bach1), a competitor of Nrf2 for ARE sites with predominant repressor function, were higher, and Bach1 also bound to a greater relative extent to the examined ARE sites when compared to Nrf2. The negative influence of AMPK on Bach1 was confirmed by pharmacological and genetic approaches and occurred at the level of mRNA synthesis. Overall, the observed AMPK-mediated boost in transactivation of a subset of Nrf2 target genes involves downregulation of Bach1 and subsequent favored binding of activating Nrf2 over repressing Bach1 to the examined ARE sites.

AMPK leads to phosphorylation of the transcription factor Nrf2, tuning transactivation of selected target genes.

The transcription factor Nrf2 (nuclear factor (erythroid-derived 2)-like 2) and the kinase AMPK (AMP-activated protein kinase) participate in the cellular adaptive response to redox or energy stress. Despite accumulating evidence for positive cooperativity between both proteins, information about direct post-translational modification of Nrf2 by AMPK in living cells is scarce. Here, MS-based analysis of immunoprecipitated Nrf2 revealed serine 374, 408 and 433 in human Nrf2 to be hyperphosphorylated as a function of activated AMPK. A direct phosphate-transfer by AMPK to those sites was indicated by in vitro kinase assays with recombinant proteins as well as interaction of AMPK and Nrf2 in cells, evident by co-immunoprecipitation. Mutation of serine 374, 408 and 433 to alanine did not markedly affect half-life, nuclear accumulation or induction of reporter gene expression upon Nrf2 activation with sulforaphane. However, some selected endogenous Nrf2 target genes responded with decreased induction when the identified phosphosites were mutated, whereas others remained unaffected. Notably, the genes susceptible to the mutation of the phosphorylation sites in Nrf2 consistently showed reduced induction in AMPKα1 -/-cells. Overall, our data reveal AMPK-triggered phosphorylation of Nrf2 at three serine residues, apparently determining the extent of transactivation of selected target genes.

Activation of Nrf2 signaling by natural products-can it alleviate diabetes?

Type 2 diabetes mellitus (DM) has reached pandemic proportions and effective prevention strategies are wanted. Its onset is accompanied by cellular distress, the nuclear factor erythroid 2-related factor 2 (Nrf2) is a transcription factor boosting cytoprotective responses, and many phytochemicals activate Nrf2 signaling. Thus, Nrf2 activation by natural products could presumably alleviate DM. We summarize function, regulation and exogenous activation of Nrf2, as well as diabetes-linked and Nrf2-susceptible forms of cellular stress. The reported amelioration of insulin resistance, ß-cell dysfunction and diabetic complications by activated Nrf2 as well as the status quo of Nrf2 in precision medicine for DM are reviewed.