Biology subjects

Searle, B. C.

Publications and source records attributed to Searle, B. C..

At least 19 recordsLinked to original sources

bioRxiv2025

Benchmarking Spectral Library and Database Search Approaches for Metaproteomics Using a Ground-Truth Microbiome Dataset

Mass spectrometry-based metaproteomics, the identification and quantification of thousands of proteins expressed by complex microbial communities, has become pivotal for unraveling functional interactions within microbiomes. However, metaproteomics data analysis encounters many challenges, including the search of tandem mass spectra against a protein sequence database using proteomics database search algorithms. We used a ground-truth dataset to assess a spectral library searching method against established database searching approaches. Mass spectrometry data collected by data-dependent acquisition (DDA-MS) was analyzed using database searching approaches (MaxQuant and FragPipe), as well as using Scribe with Prosit predicted spectral libraries. We used FASTA databases that included protein sequences from microbial species present in the ground-truth dataset along with background protein sequences, to estimate error rates and assess the effects on detection, peptide-spectral match quality, and quantification. Using the Scribe search engine resulted in more proteins detected at a 1% false discovery rate (FDR) compared to MaxQuant or FragPipe, while FragPipe detected more peptides verified by PepQuery. Scribe was able to detect more low-abundance proteins in the microbiome dataset and was more accurate in quantifying the microbial community composition. This research provides insights and guidance for metaproteomics researchers aiming to optimize results in their analysis of DDA-MS data.

bioinformatics↗

bioRxiv2025

Improving proteomic dynamic range with Multiple Accumulation Precursor Mass Spectrometry (MAP-MS)

Orbitrap (OT) -based mass spectrometer platforms are a gold standard in high-resolution mass spectrometry, where their primary disadvantage is slower-scanning speed in comparison to time-of-flight or linear ion trap mass analyzers. In this study, we utilize long OT transients to extend the precursor dynamic range by modifying the selected ion monitoring method to multiplex several precursor m/z ranges from 400 to 1000 m/z into a single scan called "Multiple Accumulation Precursor Mass Spectrometry" (MAP-MS). Our approach requires no software or hardware modifications and hides the additional ion accumulation steps during the time it takes to make other Orbitrap measurements, producing precursor spectra with nearly 2x dynamic range and essentially no consequences. We collected data using both data-dependent acquisition (DDA) and data-independent acquisition (DIA) methods to evaluate a range of approaches. With DDA, MAP-MS precursor quantification improves with higher quality measurements. At the same time, DIA detection is enhanced by up to 11% when combining precursor and tandem mass spectra for peptide detection.

biochemistry↗

bioRxiv2025

Proteomic profiling of zinc homeostasis mechanisms in Pseudomonas aeruginosa through data-dependent and data-independent acquisition mass spectrometry

Zinc is central to the function of many proteins, yet the mechanisms of zinc homeostasis and their interplay with other cellular systems remain underexplored. In this study, we employ data-dependent acquisition (DDA) and data-independent acquisition (DIA) mass spectrometry to investigate proteome changes in Pseudomonas aeruginosa under conditions of different zinc availability. Using these methods, we detected 2143 unique proteins, 1578 of which were identified by both DDA and DIA. We demonstrated that most of the previously described Zn homeostasis systems exhibit proteomic responses that follow similar trends to those seen in transcriptomics studies. However, some proteins that are considered instrumental in Zn homeostasis, notably those in Zn transporter ZnuABC, were not detected by our methods, although other proteins of other uptake systems were abundant. Furthermore, changes in abundance of multiple Zn-metalloproteins and Zn-independent homologs were clearly observable, with respective increases and decreases when Zn was provided, though the magnitude of these changes varied. Most of the Zn-metalloproteins observed were located in one of two Zur-regulated operons between PA5534 and PA5541. This study provides a view of Zn homeostasis mechanisms that is complementary to existing transcriptomics investigations: as gene transcripts are not strictly proportional to the actual distribution of proteins within a cell, analysis of the proteome offers another way to assess the relative use and importance of similar or ostensibly redundant systems in different conditions and can highlight shifts in metal prioritization between metalloproteins.

microbiology↗

bioRxiv2024

Data-Independent Acquisition Mass Spectrometry as a Tool for Metaproteomics: Interlaboratory Comparison Using a Model Microbiome

Mass spectrometry (MS)-based metaproteomics is used to identify and quantify proteins in microbiome samples, with the frequently used methodology being Data-Dependent Acquisition mass spectrometry (DDA-MS). However, DDA-MS is limited in its ability to reproducibly identify and quantify lower abundant peptides and proteins. To address DDA-MS deficiencies, proteomics researchers have started using Data-Independent Acquisition Mass Spectrometry (DIA-MS) for reproducible detection and quantification of peptides and proteins. We sought to evaluate the reproducibility and accuracy of DIA-MS metaproteomic measurements relative to DDA-MS using a mock community of known taxonomic composition. Artificial microbial communities of known composition were analyzed independently in three laboratories using DDA- and DIA-MS acquisition methods. DIA-MS yielded more protein and peptide identifications than DDA-MS in each laboratory. In addition, the protein and peptide identifications were more reproducible in all laboratories and provided an accurate quantification of proteins and taxonomic groups in the samples. We also identified some limitations of current DIA tools when applied to metaproteomic data, highlighting specific needs to improve DIA tools enabling analysis of metaproteomic datasets from complex microbiomes. Ultimately, DIA-MS represents a promising strategy for MS-based metaproteomics due to its large number of detected proteins and peptides, reproducibility, deep sequencing capabilities, and accurate quantitation.

systems biology↗

bioRxiv2024

A workflow for targeted proteomics assay development using a versatile linear ion trap

Advances in proteomics and mass spectrometry have enabled the study of limited cell populations, such as single-cell proteomics, where high-mass accuracy instruments are typically required. While triple quadrupoles offer fast and sensitive nominal resolution measurements, these instruments are effectively limited to targeted proteomics. Linear ion traps (LITs) offer a versatile, cost-effective alternative capable of both targeted and global proteomics. We demonstrate a workflow using a newly released, hybrid quadrupole-LIT instrument for developing targeted proteomics assays from global data-independent acquisition (DIA) measurements without needing high-mass accuracy. Gas-phase fraction-based DIA enables rapid target library generation in the same background chemical matrix as each quantitative injection. Using a new software tool embedded within EncyclopeDIA for scheduling parallel reaction monitoring assays, we show consistent quantification across three orders of magnitude of input material. Using this approach, we demonstrate measuring peptide quantitative linearity down to 25x dilution in a background of only a 1 ng proteome without requiring stable isotope labeled standards. At 1 ng total protein on column, we found clear consistency between immune cell populations measured using flow cytometry and immune markers measured using LIT-based proteomics. We believe hybrid quadrupole-LIT instruments represent an economic solution to democratizing mass spectrometry in a wide variety of laboratory settings.

biochemistry↗

bioRxiv2023

Evaluating the performance of the Astral mass analyzer for quantitative proteomics using data independent acquisition

We evaluate the quantitative performance of the newly released Asymmetric Track Lossless (Astral) analyzer. Using data independent acquisition, the Thermo Scientific Orbitrap Astral mass spectrometer quantifies 5 times more peptides per unit time than state-of-the-art Thermo Scientific Orbitrap mass spectrometers, which have long been the gold standard for high resolution quantitative proteomics. Our results demonstrate that the Orbitrap Astral mass spectrometer can produce high quality quantitative measurements across a wide dynamic range. We also use a newly developed extra-cellular vesicle enrichment protocol to reach new depths of coverage in the plasma proteome, quantifying over 5,000 plasma proteins in a 60-minute gradient with the Orbitrap Astral mass spectrometer.

biochemistry↗

bioRxiv2023

Deep learning from harmonized peptide libraries enables retention time prediction of diverse post translational modifications

In proteomics experiments, peptide retention time (RT) is an orthogonal property to fragmentation when assessing detection confidence. Advances in deep learning enable accurate RT prediction for any peptide from sequence alone, including those yet to be experimentally observed. Here we present Chronologer, an open-source software tool for rapid and accurate peptide RT prediction. Using new approaches to harmonize and false-discovery correct across independently collected datasets, Chronologer is built on a massive database with >2.2 million peptides including 10 common post-translational modification (PTM) types. By linking knowledge learned across diverse peptide chemistries, Chronologer predicts RTs with less than two-thirds the error of other deep learning tools. We show how RT for rare PTMs, such as OGlcNAc, can be learned with high accuracy using as few as 10-100 example peptides in newly harmonized datasets. This iteratively updatable workflow enables Chronologer to comprehensively predict RTs for PTM-marked peptides across entire proteomes.

bioinformatics↗

bioRxiv2023

Optimizing linear ion trap data independent acquisition towards single cell proteomics

A linear ion trap (LIT) is an affordable, robust mass spectrometer that proves fast scanning speed and high sensitivity, where its primary disadvantage is inferior mass accuracy compared to more commonly used time-of-flight (TOF) or orbitrap (OT) mass analyzers. Previous efforts to utilize the LIT for low-input proteomics analysis still rely on either built-in OTs for collecting precursor data or OT-based library generation. Here, we demonstrate the potential versatility of the LIT for low-input proteomics as a stand-alone mass analyzer for all mass spectrometry measurements, including library generation. To test this approach, we first optimized LIT data acquisition methods and performed library-free searches with and without entrapment peptides to evaluate both the detection and quantification accuracy. We then generated matrix-matched calibration curves to estimate the lower limit of quantification using only 10 ng of starting material. While LIT-MS1 measurements provided poor quantitative accuracy, LIT-MS2 measurements were quantitatively accurate down to 0.5 ng on column. Finally, we optimized a suitable strategy for spectral library generation from low-input material, which we used to analyze single-cell samples by LIT-DIA using LIT-based libraries generated from as few as 40 cells.

biochemistry↗

bioRxiv2023

Scribe: next-generation library searching for DDA experiments

Spectrum library searching is a powerful alternative to database searching for data dependent acquisition experiments, but has been historically limited to identifying previously observed peptides in libraries. Here we present Scribe, a new library search engine designed to leverage deep learning fragmentation prediction software such as Prosit. Rather than relying on highly curated DDA libraries, this approach predicts fragmentation and retention times for every peptide in a FASTA database. Scribe embeds Percolator for FDR correction and an interference tolerant label-free quantification integrator to enable an end-to-end proteomics workflow. By leveraging expected relative fragmentation and retention time values, we find that library searching with Scribe can outperform traditional database searching tools, both in terms of sensitivity and quantitative precision. Scribe and its graphical interface are easy to use, freely accessible, and fully open source.

bioinformatics↗

bioRxiv2022

A Peptide-Centric Quantitative Proteomics Dataset for the Phenotypic Assessment of Alzheimer's Disease

Alzheimers disease (AD) is a looming public health disaster with limited interventions. Alzheimers is a complex disease that can present with or without causative mutations and can be accompanied by a range of age-related comorbidities. This diverse presentation makes it difficult to study molecular changes specific to AD. To better understand the molecular signatures of disease we constructed a unique human brain sample cohort inclusive of autosomal dominant AD dementia (ADD), sporadic ADD, and those without dementia but with high AD histopathologic burden, and cognitively normal individuals with no/minimal AD histopathologic burden. All samples are clinically well characterized, and brain tissue was preserved postmortem by rapid autopsy. Samples from four brain regions were processed and analyzed by data-independent acquisition LC-MS/MS. Here we present a high-quality quantitative dataset at the peptide and protein level for each brain region. Multiple internal and external control strategies were included in this experiment to ensure data quality. All data are deposited in the ProteomeXchange repositories and available from each step of our processing.

neuroscience↗

bioRxiv2022

nf-encyclopedia: A cloud-ready pipeline for chromatogram library data-independent acquisition proteomics workflows

Data independent acquisition (DIA) mass spectrometry methods provide systematic and comprehensive quantification of the proteome; yet, relatively few open-source tools are available to analyze DIA proteomics experiments. Fewer still are tools that can leverage gas phase fractionated (GPF) chromatogram libraries to enhance the detection and quantification of peptides in these experiments. Here, we present nf-encyclopedia, an open-source NextFlow pipeline that connects three open-source tools--MSConvert, EncyclopeDIA, and MSstats--to analyze DIA proteomics experiments with or without chromatogram libraries. We demonstrate that nf-encyclopedia is reproducible both when run on a cloud platform or a local workstation and provides robust peptide and protein quantification. Additionally, we found that MSstats enhances protein-level quantitative performance over EncyclopeDIA alone. Finally, we benchmarked the ability nf-encyclopedia to scale to large experiments in the cloud by leveraging the parallelization of compute resources. The nf-encyclopedia pipeline is available under a permissive Apache 2.0 license--run it on your desktop, cluster, or in the cloud: https://github.com/TalusBio/nf-encyclopedia.

bioinformatics↗

bioRxiv2022

Profiling Mouse Brown and White Adipocytes to Identify Metabolically Relevant Small ORFs and Functional Microproteins

The absence of thousands of recently annotated small open reading frame (smORF)-encoded peptides and small proteins (microproteins) from databases has precluded their analysis in metabolism and metabolic disease. Given the outsized importance of small proteins and peptides such as insulin, leptin, amylin, glucagon, and glucagon-like peptide-1 (GLP-1) in metabolism, microproteins are a potentially rich source of uncharacterized metabolic regulators. Here, we annotate smORFs in primary differentiated brown, white, and beige mouse adipose cells. Ribosome profiling (Ribo-Seq) detected a total of 3,877 unannotated smORFs. Analysis of RNA-Seq datasets revealed diet-regulated smORF expression in adipose tissues, and validated the adipose translation of the feeding-neuron marker gene Gm8773. Gm8773 encodes the mouse homolog of FAM237B, a neurosecretory protein that stimulates food intake and promotes weight gain in chickens. Testing of recombinant mFAM237B produced similar orexigenic activity in mice further supporting a role for FAM237B as a metabolic regulator and potentially part of the brain-adipose axis. Furthermore, we demonstrated that data independent acquisition mass spectrometry (DIA-MS) proteomics can provide a sensitive, flexible, and quantitative platform for identifying microproteins by mass spectrometry. Using this system led to the detection of 58 microproteins from cell culture and an additional 33 from mouse plasma. The proteomics data established the anti-inflammatory microprotein AW112010 as a circulating factor, and found that plasma levels of a microprotein translated from a FRS2 uORF is elevated in older obese mice. Together, the data highlight the value of this database in examining understudied smORFs and microproteins in metabolic research and identifying additional regulators of metabolism.

systems biology↗

bioRxiv2022

Recurrent co-option and recombination of cytokine and three finger proteins in multiple reproductive tissues throughout salamander evolution

The proteomic composition of amphibian gametes is largely a molecular mystery, particularly for Urodeles (salamanders and newts) which have few genomic-scale resources. Lungless salamanders (family Plethodontidae) include approximately two thirds of all extant salamander species and are classic models of vertebrate mating behavior. As part of an extended, multi-stage courtship ritual, male plethodontid salamanders deliver rapidly evolving protein pheromones that modify female behavior and improve male reproductive success. Despite great interest in this set of pre-mating reproductive barriers, limited characterization of plethodontid gametes has prohibited investigation of post-mating pre-zygotic barriers such as sperm-egg recognition. In this study, we performed transcriptomic analyses of testis and ovary using long-read PacBio sequencing and proteomic analyses of sperm using mass spectrometry for two evolutionary divergent plethodontid species, Plethodon shermani and Desmognathus ocoee. In both species, many of the most abundant sperm proteins were paralogs of the courtship pheromones Plethodontid Receptivity Factor (PRF), Plethodontid Modulating Factor (PMF), and Sodefrin Precursor-like Factor (SPF). Sperm-specific paralogs of PMF and SPF are likely the most abundant secreted proteins in P. shermani and D. ocoee, respectively. In contrast, sperm PRF lacks a signal peptide and may be expressed in cytoplasm. PRF pheromone genes evolved independently multiple times through repeated gene duplication of sperm PRF genes and signal peptides recovered by recombination with PMF genes. Phylogenetic analysis of courtship pheromones and their sperm paralogs support that each protein family evolved for these two reproductive contexts at distinct evolutionary time points between 17 and 360 million years ago. As the first molecular characterization of salamander gametes, this study expands our knowledge of amphibian fertilization beyond frogs and provides novel insight into the evolutionary processes by which new, rapidly evolving reproductive proteins may evolve.

evolutionary biology↗

bioRxiv2021

Data-independent acquisition protease-multiplexing enables increased proteome sequence coverage across multiple fragmentation modes

The use of multiple proteases has been shown to increase protein sequence coverage in proteomics experiments, however due to the additional analysis time required, it has not been widely adapted in routine data-dependent acquisition (DDA) proteomic workflows. Alternatively, data-independent acquisition (DIA) has the potential to analyze multiplexed samples from different protease digests, but has been primarily optimized for fragmenting tryptic peptides. Here we evaluate a DIA multiplexing approach that combines three proteolytic digests (Trypsin, AspN, and GluC) into a single sample. We first optimize data acquisition conditions for each protease individually with both the canonical DIA fragmentation mode (beam type CID), as well as resonance excitation CID, to determine optimal consensus conditions across proteases. Next, we demonstrate that application of these conditions to a protease-multiplexed sample of human peptides results in similar protein identifications and quantitative performance as compared to trypsin alone, but enables up to a 63% increase in peptide detections, and a 27% increase non-redundant amino acid detections. Importantly, this resulted in 100% sequence coverage for numerous proteins, suggesting the utility of this approach in applications where sequence coverage is critical, such as proteoform analysis.

systems biology↗

bioRxiv2020

2019 Association of Biomolecular Resource Facilities Multi-Laboratory Data-Independent Acquisition Study

Despite the advantages of fewer missing values by collecting fragment ion data on all analytes in the sample, as well as the potential for deeper coverage, the adoption of data-independent acquisition (DIA) in core facility settings has been slow. The Association of Biomolecular Resource Facilities conducted a large interlaboratory study to evaluate DIA performance in laboratories with various instrumentation. Participants were supplied with generic methods and a uniform set of test samples. The resulting 49 DIA datasets act as benchmarks and have utility in education and tool development. The sample set consisted of a tryptic HeLa digest spiked with high or low levels of four exogenous proteins. Data are available in MassIVE MSV000086479. Additionally, we demonstrate how the data can be analysed by focusing on two datasets using different library approaches and show the utility of select summary statistics. These data can be used by DIA newcomers, software developers, or DIA experts evaluating performance with different platforms, acquisition settings and skill levels.

bioinformatics↗

bioRxiv2019

Matrix-matched calibration curves for assessing analytical figures of merit in quantitative proteomics

Mass spectrometry is a powerful tool for quantifying protein abundance in complex samples. Advances in sample preparation and the development of data independent acquisition (DIA) mass spectrometry approaches have increased the number of peptides and proteins measured per sample. Here we present a series of experiments demonstrating how to assess whether a peptide measurement is quantitative by mass spectrometry. Our results demonstrate that increasing the number of detected peptides in a proteomics experiment does not necessarily result in increased numbers of peptides that can be measured quantitatively.

biochemistry↗

bioRxiv2019

Generating high-quality libraries for DIA-MS with empirically-corrected peptide predictions

Data-independent acquisition approaches typically rely on sample-specific spectrum libraries requiring offline fractionation and tens to hundreds of injections. We demonstrate a new library generation workflow that leverages fragmentation and retention time prediction to build libraries containing every peptide in a proteome, and then refines those libraries with empirical data. Our method specifically enables rapid library generation for non-model organisms, which we demonstrate using the malaria parasite Plasmodium falciparum, and non-canonical databases, which we show by detecting missense variants in HeLa.

systems biology↗

bioRxiv2018

Thesaurus: quantifying phosphoprotein positional isomers

Proteins can be phosphorylated at neighboring sites resulting in different functional states, and studying the regulation of these sites has been challenging. Here we present Thesaurus, a search engine that detects new positional isomers using site-specific fragment ions from parallel reaction monitoring and data independent acquisition mass spectrometry experiments. We apply Thesaurus to analyze phosphorylation events in the PI3K/AKT signaling pathway and show neighboring sites with distinct quantitative profiles, indicating regulation by different kinases.

bioinformatics↗