Biology subjects

McGann, C. D.

Publications and source records attributed to McGann, C. D..

8 recordsLinked to original sources

bioRxiv2025

Nova: A library for rapid development of mass spectrometry software applications

Nova is a software library for the reading, writing, and management of mass spectrometry data natively in the C# language. It complements similar software libraries ubiquitously used in application development for C++, Python, and Java. Few software libraries and resources for mass spectrometry data analysis have been developed for C# relative to other languages. C#, however, remains the dominant language of choice for development of real time mass spectrometry (RTMS) analysis and instrument control applications, illustrating the need for native C# libraries when developing RTMS software. Nova provides fast, easy-to-use structures and classes built upon interfaces that support open community standards, and are easily extensible for current or future mass spectrometry software development needs.

biochemistry↗

bioRxiv2024

Comet fragment-ion indexing for enhanced peptide sequencing

Fragment ion indexing has significantly improved the efficiency of proteomics database search tools. This work implements fragment ion indexing in Comet, a widely-used, open-source search engine. We demonstrate that this enhancement maintains scoring and identification accuracy while substantially increasing peptide spectral matching speeds across multiple applications, including open modification searches, immunopeptidomics, and real-time searches. Comet-FI reduced search speeds by up to 94%, enabling the rapid analysis of complex data types like immunopeptidomes. Fragment-ion indexing enables Comet to keep pace with modern instrumentation and expanding applications in proteomics, reinforcing its utility in diverse proteomics workflows and its integration with a wide range of proteomics tools and platforms.

bioinformatics↗

bioRxiv2024

The proteomic landscape and temporal dynamics of mammalian gastruloid development

Gastrulation is the process by which the early embryo establishes a body plan and primes itself for organogenesis. As gastrulation is challenging to study in vivo, stem cell-derived "gastruloids" have emerged as powerful surrogates. Although transcriptomics and imaging have been applied extensively to such embryo models, the dynamics of their proteomes remains largely unknown. Here, we apply quantitative proteomics to human and mouse gastruloids at four key stages. We leverage these data to map the expression dynamics of protein complexes, and to nominate cooperative proteins. With matched transcriptome and phosphosite data, we investigate global and stage/pathway-specific discordance between the transcriptome and proteome and nominate kinase-substrate relationships based on phosphosite dynamics. Finally, we apply co-regulation network analysis to identify genes linked to the Commander complex whose perturbation leads to morphological defects in gastruloids. Altogether, our work showcases the potential of applying proteomics to embryo models to advance our understanding of mammalian development in ways challenging through transcriptomics alone.

systems biology↗

bioRxiv2024

DNA O-MAP uncovers the molecular neighborhoods associated with specific genomic loci

The accuracy of crucial nuclear processes such as transcription, replication, and repair, depends on the local composition of chromatin and the regulatory proteins that reside there. Understanding these DNA-protein interactions at the level of specific genomic loci has remained challenging due to technical limitations. Here, we introduce a method termed "DNA O-MAP", which uses programmable peroxidase-conjugated oligonucleotide probes to biotinylate nearby proteins. We show that DNA O-MAP can be coupled with label-free or sample multiplexed quantitative proteomics, targeted chemical perturbations, and next-generation sequencing to quantify DNA-proximal proteins and DNA-DNA interactions at specific genomic loci. Furthermore, we establish that DNA O-MAP is applicable to both repetitive and unique genomic loci of varying sizes, from kilobase HOX gene clusters to megabase alpha-satellite repeats, and that DNA O-MAP can measure proximal molecular effectors in a homolog-specific manner.

systems biology↗

bioRxiv2024

Lineage-specific proteome remodeling of diverse lung cancer cells by targeted epigenetic inhibitors

Epigenetic inhibitors exhibit powerful antiproliferative and anticancer activities. However, cellular responses to small-molecule epigenetic inhibition are heterogeneous and dependent on factors such as the genetic background and metabolic state of cells, as well as on-/off-target engagement of individual small-molecule compounds. The molecular study of the extent of this heterogeneity often measures changes in a single cell line. To more comprehensively profile the effects of small-molecule perturbations and their influence on heterogeneous cellular responses, we present a molecular resource based on the quantification of chromatin, proteome, and transcriptome remodeling due to histone deacetylase inhibitors (HDACi) in non-isogenic cell lines. Through quantitative molecular profiling of 10,621 proteins, these data reveal coordinated molecular remodeling of HDACi treated cancer cells. HDACi-regulated proteins differ greatly across cell lines with consistent (JUN, MAP2K3, CDKN1A) and divergent (CCND3, ASF1B, BRD7) cell-state effectors. Together these data provide valuable insight into cell-type driven and heterogeneous responses that must be taken into consideration when monitoring molecular perturbations in culture models. We have also built a web interface for the extensive amount of data to allow users to explore the data as a resource for understanding chemical perturbation of diverse cell types.

cancer biology↗

bioRxiv2023

Comparing peptide identifications by FAIMS versus quadrupole gas-phase fractionation

High-field asymmetric waveform ion mobility spectrometry (FAIMS) coupled to liquid chromatography-mass spectrometry (LC-MS) has been shown to increase peptide and protein detections compared to LC-MS/MS alone. However, FAIMS has not been compared to other methods of gas-phase fractionation, such as quadrupole gas-phase fractionation, which could increase our understanding of the mechanisms of improvement. The goal of this work was to assess whether FAIMS improves peptide identifications because 1) gas-phase fractionation enables the analysis of less abundant signals by excluding more abundant precursors from filling the ion trap, 2) the use of FAIMS reduces co-isolation of peptides during the MS/MS process resulting in a reduction of chimeric spectra, or 3) a combination of both. To investigate these hypotheses, pooled human brain tissue samples were measured in triplicate using FAIMS gas-phase fractionation, quadrupole gas-phase fractionation, or no gas-phase fractionation on two Thermo Eclipse Tribrid Mass Spectrometers. On both instruments, our data confirmed prior observations that FAIMS increased the number of peptides identified. We further demonstrated that the main benefit of FAIMS is due to the reduced co-isolation of persistent peptide precursor ions, which results in a decrease in chimeric spectra.

biochemistry↗

bioRxiv2023

Real-time spectral library matching for sample multiplexed quantitative proteomics.

Sample multiplexed quantitative proteomics has proved to be a highly versatile means to assay molecular phenotypes. Yet, stochastic precursor selection and precursor co-isolation can dramatically reduce the efficiency of data acquisition and quantitative accuracy. To address this, intelligent data acquisition (IDA) strategies have recently been developed to improve instrument efficiency and quantitative accuracy for both discovery and targeted methods. Towards this end, we sought to develop and implement a new real-time library searching (RTLS) workflow that could enable intelligent scan triggering and peak selection within milliseconds of scan acquisition. To ensure ease of use and general applicability, we built an application to read in diverse spectral libraries and file types from both empirical and predicted spectral libraries. We demonstrate that RTLS methods enable improved quantitation of multiplexed samples, particularly with consideration for quantitation from chimeric fragment spectra. We used RTLS to profile proteome responses to small molecule perturbations and were able to quantify up to 15% more significantly regulated proteins in half the gradient time as traditional methods. Taken together, the development of RTLS expands the IDA toolbox to improve instrument efficiency and quantitative accuracy in sample multiplexed analyses.

cell biology↗

bioRxiv2021

A flexible workflow for building spectral libraries from narrow window data independent acquisition mass spectrometry data

Advances in library-based methods for peptide detection from data independent acquisition (DIA) mass spectrometry have made it possible to detect and quantify tens of thousands of peptides in a single mass spectrometry run. However, many of these methods rely on a comprehensive, high quality spectral library containing information about the expected retention time and fragmentation patterns of peptides in the sample. Empirical spectral libraries are often generated through data-dependent acquisition and may suffer from biases as a result. Spectral libraries can be generated in silico but these models are not trained to handle all possible post-translational modifications. Here, we propose a false discovery rate controlled spectrum-centric search workflow to generate spectral libraries directly from gas-phase fractionated DIA tandem mass spectrometry data. We demonstrate that this strategy is able to detect phosphorylated peptides and can be used to generate a spectral library for accurate peptide detection and quantitation in wide window DIA data. We compare the results of this search workflow to other library-free approaches and demonstrate that our search is competitive in terms of accuracy and sensitivity. These results demonstrate that the proposed workflow has the capacity to generate spectral libraries while avoiding the limitations of other methods.

bioinformatics↗