Biology subjects

Haynes, S. E.

Publications and source records attributed to Haynes, S. E..

9 recordsLinked to original sources

bioRxiv2025

Analysis of isobaric quantitative proteomic data using TMT-Integrator and FragPipe computational platform

Isobaric mass tags, such as iTRAQ and TMT, are widely utilized for peptide and protein quantification in multiplex quantitative proteomics. We present TMT-Integrator, a bioinformatics tool for processing quantitation results from TMT and iTRAQ experiments, offering integrative reports at the gene, protein, peptide, and post-translational modification site levels. We demonstrate the versatility of TMT-Integrator using five publicly available TMT datasets: an E. coli dataset with 13 spike-in proteins, the clear cell renal cell carcinoma (ccRCC) whole proteome and phosphopeptide-enriched datasets from the Clinical Proteomic Tumor Analysis Consortium, and two human cell lysate datasets showcasing the latest advances with the Astral instrument and TMT 35-plex reagents. Integrated into the widely used FragPipe computational platform (https://fragpipe.nesvilab.org/), TMT-Integrator is a core component of TMT and iTRAQ data analysis workflows. We evaluate the FragPipe/TMT-Integrator analysis pipelines performance against MaxQuant and Proteome Discoverer with multiple benchmarks, facilitated by the bioinformatics tool OmicsEV. Our results show that FragPipe/TMT-Integrator quantifies more proteins in the E. coli and ccRCC whole proteome datasets, identifies more phosphorylated sites in the ccRCC phosphoproteome dataset, and delivers overall more robust quantification performance compared to other tools.

bioinformatics↗

bioRxiv2023

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.

biophysics↗

bioRxiv2022

CRF neurons of the BNST promote resilience by blunting the internal experience of aversion.

The Bed Nucleus of the Stria Terminalis (BNST) has been studied extensively for its coordination of opposing adaptive behaviors. Previously, we uncovered a critical role for Corticotropin-Releasing Factor (CRF)-expressing neurons of the oval nucleus of the BNST (BNSTovCRF) in maintaining resilience to social defeat through stress-dependent self-sustaining neuronal activity.1 However, as mice develop resilience, it is not well-understood how affect and motivation are altered to achieve adaptive behavior in the face of ongoing threat. Here, we explore how this neuronal population exerts a powerful influence over internal state in various stress contexts to promote adaptive social responding. Using cell-type-selective optogenetics, a suite of behavioral paradigms, and transgenic Crf-ChR2 mice, we show that BNSTovCRF neurons induce resiliency by altering the encoding of psychosocial stress, enhancing the appetitiveness of social interaction, and enhancing tolerability to physical stress. Adaptive responses to stress typically emanate as a response to negative internal states by external stimuli; here, we show that in resilient mice, stressful environments are less aversive than susceptible mice, suggesting a different motivational capacity to endure stress in this group. Thus, we describe a novel role for BNSTovCRF neurons in resisting the emotional effects of cumulative stress by reducing the internal experience of aversion

neuroscience↗

bioRxiv2022

CRF Neurons Establish Resilience via Stress-History-Dependent BNST Modulation

IntroductionCumulative stress is a major risk factor for developing major depressive disorder (MDD), yet not everyone experiencing chronic stress develops MDD. In those who do not, it is unclear at what point, or by what mechanism, a trajectory of stable resiliency emerges. MethodsUtilizing a 10-day repeated social defeat stress model (RSDS) for MDD, we observed that a critical period between 7 and 10 daily defeats marks the phenotypical divergence of resilient from susceptible mice. Using cell-type selective electrophysiology, chemogenetics, optogenetics, fiber photometry and RNA quantification was employed to investigate the nature of stress effects on neuroadaptation in the oval nucleus of the bed nucleus of the stria terminalis (BNSTov) required to determine resilience. ResultsIn response to ongoing stress, corticotropin-releasing factor (CRF+, but not CRF-) neurons of the (BNSTov) displayed a sustained increased firing rate in resilient, but not susceptible mice. This neurophysiological adaptation was self-sustaining, but only after 7 critical stress exposures, indicating that the process of developing resilience is dependent on stress history. ConclusionOur study reveals a novel process by which individuals might persist in the face of adversity by way of stress-provoked activation, not inhibition of a key CRF limbic region that establishes a pathway to resilience.

neuroscience↗

bioRxiv2021

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 educational materials on GitHub.

scientific communication and education↗

bioRxiv2021

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

Kinesins are tightly regulated in space and time to control their activation in the absence of cargo-binding. Kinesin-binding protein (KIFBP) was recently discovered to bind the catalytic motor heads of 8 of the 45 known kinesin superfamily members and inhibit binding to microtubules. In humans, mutation of KIFBP gives rise to Goldberg-Shprintzen syndrome (GOSHS), but the kinesin(s) that is misregulated to produce clinical features of the disease is not known. Understanding the structural mechanism by which KIFBP selects its kinesin binding partners will be key to unlocking this knowledge. Using a combination of cryo-electron microscopy and crosslinking mass spectrometry, we determined structures of KIFBP alone and in complex with two mitotic kinesins, revealing regions of KIFBP that participate in complex formation. KIFBP adopts an alpha-helical solenoid structure composed of TPR repeats. We find that KIFBP uses a 2-pronged mechanism to remodel kinesin motors and block microtubule-binding. First, KIFBP engages the microtubule-binding interface and sterically blocks interaction with microtubules. Second, KIFBP induces allosteric conformational changes to the kinesin motor head that displace a key structural element in the kinesin motor head (-helix 4) required for microtubule binding. We identified two regions of KIFBP necessary for in vitro kinesin-binding as well as cellular regulation during mitosis. Taken together, this work establishes the mechanism of kinesin inhibition by KIFBP and provides the first example of motor domain remodeling as a means to abrogate kinesin activity.

cell biology↗

bioRxiv2020

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 to 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 (FAIMS) separation. Fully integrated in FragPipe computational environment, IonQuant with FDR-controlled MBR enables fast and accurate peptide and protein quantification in label-free proteomics experiments.

bioinformatics↗

bioRxiv2020

Fast quantitative analysis of timsTOF PASEF data with MSFragger and IonQuant

Ion mobility brings an additional dimension of separation to liquid chromatography-mass spectrometry, improving identification of peptides and proteins in complex mixtures. A recently introduced timsTOF mass spectrometer (Bruker) couples trapped ion mobility separation to time-of-flight 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 commonly used to analyze these data. However, due to 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 minutes 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 prior to MS/MS analysis.Competing Interest StatementThe authors have declared no competing interest.AbbreviationsLC-MSliquid chromatography-mass spectrometryTIMStrapped ion mobility spectrometryTOFtime-of-flightPASEFparallel accumulation-serial fragmentationDDAdata-dependent acquisitionDIAdata-independent acquisitionMS/MStandem mass spectrometryPSMpeptide-spectrum matchLC-IMS-MSliquid chromatography-ion mobility-mass spectrometryXICextracted ion chromatogramCVcoefficient of variationLFQlabel free quantificationFDRFalse Discovery RateCIDcollision-induced dissociationCPUcentral processing unitPTMpost-translational modificationMBRmatch-between-runsView Full Text

bioinformatics↗

bioRxiv2018

Identification of Pirin as a Molecular Target of the CCG-1423/CCG-203971 Series of Anti-Fibrotic and Anti-Metastatic 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 melanoma metastasis and bleomycin-induced fibrosis. Although these compounds are efficacious, the molecular target is unknown. Here, we describe affinity isolation-based target identification efforts which yielded pirin, an iron-dependent co-transcription 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 SRE.L Luciferase activation. Finally, using both siRNA and a previously validated pirin inhibitor, we show a role for pirin in TGF-p 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.

pharmacology and toxicology↗