Autoinhibited kinesin-1 adopts a hierarchical folding pattern.

Conventional kinesin-1 is the primary anterograde motor in cells for transporting cellular cargo. While there is a consensus that the C-terminal tail of kinesin-1 inhibits motility, the molecular architecture of a full-length autoinhibited kinesin-1 remains unknown. Here, we combine cross-linking mass spectrometry (XL-MS), electron microscopy (EM), and AlphaFold structure prediction to determine the architecture of the full-length autoinhibited kinesin-1 homodimer [kinesin-1 heavy chain (KHC)] and kinesin-1 heterotetramer [KHC bound to kinesin light chain 1 (KLC1)]. Our integrative analysis shows that kinesin-1 forms a compact, bent conformation through a break in coiled coil 3. Moreover, our XL-MS analysis demonstrates that kinesin light chains stabilize the folded inhibited state rather than inducing a new structural state. Using our structural model, we show that disruption of multiple interactions between the motor, stalk, and tail domains is required to activate the full-length kinesin-1. Our work offers a conceptual framework for understanding how cargo adaptors and microtubule-associated proteins relieve autoinhibition to promote activation.

Implementing the MSFragger Search Engine as a Node in Proteome Discoverer.

Here, we describe the implementation of the fast proteomics search engine MSFragger as a processing node in the widely used Proteome Discoverer (PD) software platform. PeptideProphet (via the Philosopher tool kit) is also implemented as an additional PD node to allow validation of MSFragger open (mass-tolerant) search results. These two nodes, along with the existing Percolator validation module, allow users to employ different search strategies and conveniently inspect search results through PD. Our results have demonstrated the improved numbers of PSMs, peptides, and proteins identified by MSFragger coupled with Percolator and significantly faster search speed compared to the conventional SEQUEST/Percolator PD workflows. The MSFragger-PD node is available at https://github.com/nesvilab/PD-Nodes/releases/.

EML2-S constitutes a new class of proteins that recognizes and regulates the dynamics of tyrosinated microtubules.

Tubulin post-translational modifications (PTMs) alter microtubule properties by affecting the binding of microtubule-associated proteins (MAPs). Microtubule detyrosination, which occurs by proteolytic removal of the C-terminal tyrosine from ɑ-tubulin, generates the oldest known tubulin PTM, but we lack comprehensive knowledge of MAPs that are regulated by this PTM. We developed a screening pipeline to identify proteins that discriminate between Y- and ΔY-microtubules and found that echinoderm microtubule-associated protein-like 2 (EML2) preferentially interacts with Y-microtubules. This activity depends on a Y-microtubule interaction motif built from WD40 repeats. We show that EML2 tracks the tips of shortening microtubules, a behavior not previously seen among human MAPs in vivo, and influences dynamics to increase microtubule stability. Our screening pipeline is readily adapted to identify proteins that specifically recognize a wide range of microtubule PTMs.

Kinesin-binding protein remodels the kinesin motor to prevent microtubule binding.

Kinesins are regulated in space and time to ensure activation only in the presence of cargo. Kinesin-binding protein (KIFBP), which is mutated in Goldberg-Shprintzen syndrome, binds to and inhibits the catalytic motor heads of 8 of 45 kinesin superfamily members, but the mechanism remains poorly defined. Here, we used cryo­electron microscopy and cross-linking mass spectrometry to determine high-resolution structures of KIFBP alone and in complex with two mitotic kinesins, revealing structural remodeling of kinesin by KIFBP. We find that KIFBP remodels kinesin motors and blocks microtubule binding (i) via allosteric changes to kinesin and (ii) by sterically blocking access to the microtubule. We identified two regions of KIFBP necessary for kinesin binding and cellular regulation during mitosis. Together, this work further elucidates the molecular mechanism of KIFBP-mediated kinesin inhibition and supports a model in which structural rearrangement of kinesin motor domains by KIFBP abrogates motor protein activity.

IonQuant Enables Accurate and Sensitive Label-Free Quantification With FDR-Controlled Match-Between-Runs.

Missing values weaken the power of label-free quantitative proteomic experiments to uncover true quantitative differences between biological samples or experimental conditions. Match-between-runs (MBR) has become a common approach to mitigate the missing value problem, where peptides identified by tandem mass spectra in one run are transferred to another by inference based on m/z, charge state, retention time, and ion mobility when applicable. Though tolerances are used to ensure such transferred identifications are reasonably located and meet certain quality thresholds, little work has been done to evaluate the statistical confidence of MBR. Here, we present a mixture model-based approach to estimate the false discovery rate (FDR) of peptide and protein identification transfer, which we implement in the label-free quantification tool IonQuant. Using several benchmarking datasets generated on both Orbitrap and timsTOF mass spectrometers, we demonstrate superior performance of IonQuant with FDR-controlled MBR compared with MaxQuant (19-38 times faster; 6-18% more proteins quantified and with comparable or better accuracy). We further illustrate the performance of IonQuant and highlight the need for FDR-controlled MBR, in two single-cell proteomics experiments, including one acquired with the help of high-field asymmetric ion mobility spectrometry separation. Fully integrated in the FragPipe computational environment, IonQuant with FDR-controlled MBR enables fast and accurate peptide and protein quantification in label-free proteomics experiments.

Parthenolide Destabilizes Microtubules by Covalently Modifying Tubulin.

Detyrosination of the α-tubulin C-terminal tail is a post-translational modification (PTM) of microtubules that is key for many biological processes.1 Although detyrosination is the oldest known microtubule PTM,2-7 the carboxypeptidase responsible for this modification, VASH1/2-SVBP, was identified only 3 years ago,8,9 precluding genetic approaches to prevent detyrosination. Studies examining the cellular functions of detyrosination have therefore relied on a natural product, parthenolide, which is widely believed to block detyrosination of α-tubulin in cells, presumably by inhibiting the activity of the relevant carboxypeptidase(s).10 Parthenolide is a sesquiterpene lactone that forms covalent linkages predominantly with exposed thiol groups; e.g., on cysteine residues.11-13 Using mass spectrometry, we show that parthenolide forms adducts on both cysteine and histidine residues on tubulin itself, in vitro and in cells. Parthenolide causes tubulin protein aggregation and prevents the formation of microtubules. In contrast to epoY, an epoxide inhibitor of VASH1/2-SVBP,9 parthenolide does not block VASH1-SVBP activity in vitro. Lastly, we show that epoY is an efficacious inhibitor of microtubule detyrosination in cells, providing an alternative chemical means to block detyrosination. Collectively, our work supports the notion that parthenolide is a promiscuous inhibitor of many cellular processes and suggests that its ability to block detyrosination may be an indirect consequence of reducing the polymerization-competent pool of tubulin in cells.

Teaching Python for Data Science: Collaborative development of a modular & interactive curriculum.

We are bioinformatics trainees at the University of Michigan who started a local chapter of Girls Who Code to provide a fun and supportive environment for high school women to learn the power of coding. Our goal was to cover basic coding topics and data science concepts through live coding and hands-on practice. However, we could not find a resource that exactly met our needs. Therefore, over the past three years, we have developed a curriculum and instructional format using Jupyter notebooks to effectively teach introductory Python for data science. This method, inspired by The Carpentries organization, uses bite-sized lessons followed by independent practice time to reinforce coding concepts, and culminates in a data science capstone project using real-world data. We believe our open curriculum is a valuable resource to the wider education community and hope that educators will use and improve our lessons, practice problems, and teaching best practices. Anyone can contribute to our Open Educational Resources on GitHub.

Identification of modified peptides using localization-aware open search.

Identification of post-translationally or chemically modified peptides in mass spectrometry-based proteomics experiments is a crucial yet challenging task. We have recently introduced a fragment ion indexing method and the MSFragger search engine to empower an open search strategy for comprehensive analysis of modified peptides. However, this strategy does not consider fragment ions shifted by unknown modifications, preventing modification localization and limiting the sensitivity of the search. Here we present a localization-aware open search method, in which both modification-containing (shifted) and regular fragment ions are indexed and used in scoring. We also implement a fast mass calibration and optimization method, allowing optimization of the mass tolerances and other key search parameters. We demonstrate that MSFragger with mass calibration and localization-aware open search identifies modified peptides with significantly higher sensitivity and accuracy. Comparing MSFragger to other modification-focused tools (pFind3, MetaMorpheus, and TagGraph) shows that MSFragger remains an excellent option for fast, comprehensive, and sensitive searches for modified peptides in shotgun proteomics data.

Fast Quantitative Analysis of timsTOF PASEF Data with MSFragger and IonQuant.

Ion mobility brings an additional dimension of separation to LC-MS, improving identification of peptides and proteins in complex mixtures. A recently introduced timsTOF mass spectrometer (Bruker) couples trapped ion mobility separation to TOF mass analysis. With the parallel accumulation serial fragmentation (PASEF) method, the timsTOF platform achieves promising results, yet analysis of the data generated on this platform represents a major bottleneck. Currently, MaxQuant and PEAKS are most used to analyze these data. However, because of the high complexity of timsTOF PASEF data, both require substantial time to perform even standard tryptic searches. Advanced searches (e.g. with many variable modifications, semi- or non-enzymatic searches, or open searches for post-translational modification discovery) are practically impossible. We have extended our fast peptide identification tool MSFragger to support timsTOF PASEF data, and developed a label-free quantification tool, IonQuant, for fast and accurate 4-D feature extraction and quantification. Using a HeLa data set published by Meier et al. (2018), we demonstrate that MSFragger identifies significantly (∼30%) more unique peptides than MaxQuant (1.6.10.43), and performs comparably or better than PEAKS X+ (∼10% more peptides). IonQuant outperforms both in terms of number of quantified proteins while maintaining good quantification precision and accuracy. Runtime tests show that MSFragger and IonQuant can fully process a typical two-hour PASEF run in under 70 min on a typical desktop (6 CPU cores, 32 GB RAM), significantly faster than other tools. Finally, through semi-enzymatic searching, we significantly increase the number of identified peptides. Within these semi-tryptic identifications, we report evidence of gas-phase fragmentation before MS/MS analysis.

Crystal-C: A Computational Tool for Refinement of Open Search Results.

Shotgun proteomics using liquid chromatography coupled to mass spectrometry (LC-MS) is commonly used to identify peptides containing post-translational modifications. With the emergence of fast database search tools such as MSFragger, the approach of enlarging precursor mass tolerances during the search (termed "open search") has been increasingly used for comprehensive characterization of post-translational and chemical modifications of protein samples. However, not all mass shifts detected using the open search strategy represent true modifications, as artifacts exist from sources such as unaccounted missed cleavages or peptide co-fragmentation (chimeric MS/MS spectra). Here, we present Crystal-C, a computational tool that detects and removes such artifacts from open search results. Our analysis using Crystal-C shows that, in a typical shotgun proteomics data set, the number of such observations is relatively small. Nevertheless, removing these artifacts helps to simplify the interpretation of the mass shift histograms, which in turn should improve the ability of open search-based tools to detect potentially interesting mass shifts for follow-up investigation.

Identification of Pirin as a Molecular Target of the CCG-1423/CCG-203971 Series of Antifibrotic and Antimetastatic Compounds.

A series of compounds (including CCG-1423 and CCG-203971) discovered through an MRTF/SRF-dependent luciferase screen has shown remarkable efficacy in a variety of in vitro and in vivo models, including significant reduction of melanoma metastasis and bleomycin- induced fibrosis. Although these compounds are efficacious in these disease models, the molecular target is unknown. Here, we describe affinity isolation-based target identification efforts which yielded pirin, an iron-dependent cotranscription factor, as a target of this series of compounds. Using biophysical techniques including isothermal titration calorimetry and X-ray crystallography, we verify that pirin binds these compounds in vitro. We also show with genetic approaches that pirin modulates MRTF- dependent luciferase reporter activity. Finally, using both siRNA and a previously validated pirin inhibitor, we show a role for pirin in TGF-ß- induced gene expression in primary dermal fibroblasts. A recently developed analog, CCG-257081, which co crystallizes with pirin, is also effective in the prevention of bleomycin-induced dermal fibrosis.

DIA-SIFT: A Precursor and Product Ion Filter for Accurate Stable Isotope Data-Independent Acquisition Proteomics.

Quantitative mass spectrometry-based protein profiling is widely used to measure protein levels across different treatments or disease states, yet current mass spectrometry acquisition methods present distinct limitations. While data-independent acquisition (DIA) bypasses the stochastic nature of data-dependent acquisition (DDA), fragment spectra derived from DIA are often complex and challenging to deconvolve. In-line ion mobility separation (IMS) adds an additional dimension to increase peak capacity for more efficient product ion assignment. As a similar strategy to sequential window acquisition methods (SWATH), IMS-enabled DIA methods rival DDA methods for protein annotation. Here we evaluate IMS-DIA quantitative accuracy using stable isotope labeling by amino acids in cell culture (SILAC). Since SILAC analysis doubles the sample complexity, we find that IMS-DIA analysis is not sufficiently accurate for sensitive quantitation. However, SILAC precursor pairs share common retention and drift times, and both species cofragment to yield multiple quantifiable isotopic y-ion peak pairs. Since y-ion SILAC ratios are intrinsic for each quantified precursor, combined MS1 and y-ion ratio analysis significantly increases the total number of measurements. With increased sampling, we present DIA-SIFT ( SILAC Intrinsic Filtering Tool), a simple statistical algorithm to identify and eliminate poorly quantified MS1 and/or MS2 events. DIA-SIFT combines both MS1 and y-ion ratios, removes outliers, and provides more accurate and precise quantitation (<15% CV) without removing any proteins from the final analysis. Overall, pooled MS1 and MS2 quantitation increases sampling in IMS-DIA SILAC analyses for accurate and precise quantitation.

HDAC8 Substrates Identified by Genetically Encoded Active Site Photocrosslinking.

The histone deacetylase family comprises 18 enzymes that catalyze deacetylation of acetylated lysine residues; however, the specificity and substrate profile of each isozyme remains largely unknown. Due to transient enzyme-substrate interactions, conventional co-immunoprecipitation methods frequently fail to identify enzyme-specific substrates. Additionally, compensatory mechanisms often limit the ability of knockdown or chemical inhibition studies to achieve significant fold changes observed by acetylation proteomics methods. Furthermore, measured alterations do not guarantee a direct link between enzyme and substrate. Here we present a chemical crosslinking strategy that incorporates a photoreactive, non-natural amino acid, p-benzoyl-l-phenylalanine, into various positions of the structurally characterized isozyme histone deacetylase 8 (HDAC8). After covalent capture, co-immunoprecipitation, and mass spectrometric analysis, we identified a subset of HDAC8 substrates from human cell lysates, which were further validated for catalytic turnover. Overall, this chemical crosslinking approach identified novel HDAC8-specific substrates with high catalytic efficiency, thus presenting a general strategy for unbiased deacetylase substrate discovery.

Profiling Protein S-Sulfination with Maleimide-Linked Probes.

Cysteine residues are susceptible to oxidation to form S-sulfinyl (R-SO2 H) and S-sulfonyl (R-SO3 H) post-translational modifications. Here we present a simple bioconjugation strategy to label S-sulfinated proteins by using reporter-linked maleimides. After alkylation of free thiols with iodoacetamide, S-sulfinated cysteines react with maleimide to form a sulfone Michael adduct that remains stable under acidic conditions. Using this sequential alkylation strategy, we demonstrate differential S-sulfination across mouse tissue homogenates, as well as enhanced S-sulfination following pharmacological induction of endoplasmic reticulum stress, lipopolysaccharide stimulation, and inhibitors of the electron transport chain. Overall, this study reveals a broadened profile of maleimide reactivity across cysteine modifications, and outlines a simple method for profiling the physiological role of cysteine S-sulfination in disease.

Variable-Velocity Traveling-Wave Ion Mobility Separation Enhancing Peak Capacity for Data-Independent Acquisition Proteomics.

High mass accuracy, data-dependent acquisition is the current standard method in mass spectrometry-based peptide annotation and quantification. In high complexity samples, limited instrument scan speeds often result in under-sampling. In contrast, all-ion data-independent acquisition methods bypass precursor selection, alternating high and low collision energies to analyze product and precursor ions across wide mass ranges. Despite capturing data for all events, peptide annotation is limited by inadequate alignment algorithms or overlapping ions. Ion mobility separation can add an orthogonal analytical dimension, reducing ion interference to improve reproducibility, peak capacity, and peptide identifications to rival modern hybrid quadrupole orbitrap systems. Despite the advantages of ion mobility separation in complex proteomics analyses, there has been no quantitative measure of ion mobility resolution in a complex proteomic sample. Here, we present TWIMExtract, a data extraction tool to export defined slices of liquid chromatography/ion mobility/mass spectrometry (LC-IM-MS) data, providing a route to quantify ion mobility resolution from a commercial traveling-wave ion mobility time-of-flight mass spectrometer. Using standard traveling-wave ion mobility parameters (600 m/s, 40 V), 90% of the annotated peptides occupied just 23% of the ion mobility drift space, yet inclusion of ion mobility nearly doubled the overall peak capacity. Relative to fixed velocity traveling-wave ion mobility settings, ramping the traveling-wave velocity increased drift space occupancy, amplifying resolution by 16%, peak capacity by nearly 50%, and peptide/protein identifications by 40%. Overall, variable-velocity traveling-wave ion mobility-mass spectrometry significantly enhances proteomics analysis in all-ion fragmentation acquisition.

Oxidase Activity of the Barnacle Adhesive Interface Involves Peroxide-Dependent Catechol Oxidase and Lysyl Oxidase Enzymes.

Oxidases are found to play a growing role in providing functional chemistry to marine adhesives for the permanent attachment of macrofouling organisms. Here, we demonstrate active peroxidase and lysyl oxidase enzymes in the adhesive layer of adult Amphibalanus amphitrite barnacles through live staining, proteomic analysis, and competitive enzyme assays on isolated cement. A novel full-length peroxinectin (AaPxt-1) secreted by barnacles is largely responsible for oxidizing phenolic chemistries; AaPxt-1 is driven by native hydrogen peroxide in the adhesive and oxidizes phenolic substrates typically preferred by phenoloxidases (POX) such as laccase and tyrosinase. A major cement protein component AaCP43 is found to contain ketone/aldehyde modifications via 2,4-dinitrophenylhydrazine (DNPH) derivatization, also called Brady's reagent, of cement proteins and immunoblotting with an anti-DNPH antibody. Our work outlines the landscape of molt-related oxidative pathways exposed to barnacle cement proteins, where ketone- and aldehyde-forming oxidases use peroxide intermediates to modify major cement components such as AaCP43.

Molt-dependent transcriptomic analysis of cement proteins in the barnacle Amphibalanus amphitrite.

BACKGROUND: A complete understanding of barnacle adhesion remains elusive as the process occurs within and beneath the confines of a rigid calcified shell. Barnacle cement is mainly proteinaceous and several individual proteins have been identified in the hardened cement at the barnacle-substrate interface. Little is known about the molt- and tissue-specific expression of cement protein genes but could offer valuable insight into the complex multi-step processes of barnacle growth and adhesion. METHODS: The main body and sub-mantle tissue of the barnacle Amphibalanus amphitrite (basionym Balanus amphitrite) were collected in pre- and post-molt stages. RNA-seq technology was used to analyze the transcriptome for differential gene expression at these two stages and liquid chromatography-mass spectrometry/mass spectrometry (LC-MS/MS) was used to analyze the protein content of barnacle secretions. RESULTS: We report on the transcriptomic analysis of barnacle cement gland tissue in pre- and post-molt growth stages and proteomic investigation of barnacle secretions. While no significant difference was found in the expression of cement proteins genes at pre- and post-molting stages, expression levels were highly elevated in the sub-mantle tissue (where the cement glands are located) compared to the main barnacle body. We report the discovery of a novel 114kD cement protein, which is identified in material secreted onto various surfaces by adult barnacles and with the encoding gene highly expressed in the sub-mantle tissue. Further differential gene expression analysis of the sub-mantle tissue samples reveals a limited number of genes highly expressed in pre-molt samples with a range of functions including cuticular development, biominerialization, and proteolytic activity. CONCLUSIONS: The expression of cement protein genes appears to remain constant through the molt cycle and is largely confined to the sub-mantle tissue. Our results reveal a novel and potentially prominent protein to the mix of cement-related components in A. amphitrite. Despite the lack of a complete genome, sample collection allowed for extended transcriptomic analysis of pre- and post-molt barnacle samples and identified a number of highly-expressed genes. Our results highlight the complexities of this sessile marine organism as it grows via molt cycles and increases the area over which it exhibits robust adhesion to its substrate.