Four-dimensional proteomics analysis of human cerebrospinal fluid with trapped ion mobility spectrometry using PASEF

Liquid-phase separations coupled with ion mobility-mass spectrometry for next-generation biopharmaceutical analysis

INTRODUCTION

The pharmaceutical industry continues to expand its search for innovative biotherapeutics. The comprehensive characterization of such therapeutics requires many analytical techniques to fully evaluate critical quality attributes, making analysis a bottleneck in discovery and development timelines. While thorough characterization is crucial for ensuring the safety and efficacy of biotherapeutics, there is a need to further streamline analytical characterization and expedite the overall timeline from discovery to market.

AREAS COVERED

This review focuses on recent developments in liquid-phase separations coupled with ion mobility-mass spectrometry (IM-MS) for the development and characterization of biotherapeutics. We cover uses of IM-MS to improve the characterization of monoclonal antibodies, antibody-drug conjugates, host cell proteins, glycans, and nucleic acids. This discussion is based on an extensive literature search using Web of Science, Google Scholar, and SciFinder.

EXPERT OPINION

IM-MS has the potential to enhance the depth and efficiency of biotherapeutic characterization by providing additional insights into conformational changes, post-translational modifications, and impurity profiles. The rapid timescale of IM-MS positions it well to enhance the information content of existing assays through its facile integration with standard liquid-phase separation techniques that are commonly used for biopharmaceutical analysis.

Data-independent acquisition: A milestone and prospect in clinical mass spectrometry-based proteomics

Data-independent acquisition (DIA) has revolutionized the field of mass spectrometry (MS)-based proteomics over the past few years. DIA stands out for its ability to systematically sample all peptides in a given mass-to-charge range, allowing an unbiased acquisition of proteomics data. This greatly mitigates the issue of missing values and significantly enhances quantitative accuracy, precision, and reproducibility compared to many traditional methods. This review focuses on the critical role of DIA analysis software tools, primarily focusing on their capabilities and the challenges they address in proteomic research. Advances in MS technology, such as trapped ion mobility spectrometry, or high field asymmetric waveform ion mobility spectrometry require sophisticated analysis software capable of handling the increased data complexity and exploiting the full potential of DIA. We identify and critically evaluate leading software tools in the DIA landscape, discussing their unique features, and the reliability of their quantitative and qualitative outputs. We present the biological and clinical relevance of DIA-MS and discuss crucial publications that paved the way for in-depth proteomic characterization in patient-derived specimens. Furthermore, we provide a perspective on emerging trends in clinical applications and present upcoming challenges including standardization and certification of MS-based acquisition strategies in molecular diagnostics. While we emphasize the need for continuous development of software tools to keep pace with evolving technologies, we advise researchers against uncritically accepting the results from DIA software tools. Each tool may have its own biases, and some may not be as sensitive or reliable as others. Our overarching recommendation for both researchers and clinicians is to employ multiple DIA analysis tools, utilizing orthogonal analysis approaches to enhance the robustness and reliability of their findings.

Differential impact of sex on regulation of skeletal muscle mitochondrial function and protein homeostasis by hypoxia-inducible factor-1α in normoxia

Hypoxia-inducible factor (HIF)-1α is continuously synthesized and degraded in normoxia. During hypoxia, HIF1α stabilization restricts cellular/mitochondrial oxygen utilization. Cellular stressors can stabilize HIF1α even during normoxia. However, less is known about HIF1α function(s) and sex-specific effects during normoxia in the basal state. Since skeletal muscle is the largest protein store in mammals and protein homeostasis has high energy demands, we determined HIF1α function at baseline during normoxia in skeletal muscle. Untargeted multiomics data analyses were followed by experimental validation in differentiated murine myotubes with loss/gain of function and skeletal muscle from mice without/with post-natal muscle-specific Hif1a deletion (Hif1amsd). Mitochondrial oxygen consumption studies using substrate, uncoupler, inhibitor, titration protocols; targeted metabolite quantification by gas chromatography-mass spectrometry; and post-mitotic senescence markers using biochemical assays were performed. Multiomics analyses showed enrichment in mitochondrial and cell cycle regulatory pathways in Hif1a deleted cells/tissue. Experimentally, mitochondrial oxidative functions and ATP content were higher with less mitochondrial free radical generation with Hif1a deletion. Deletion of Hif1a also resulted in higher concentrations of TCA cycle intermediates and HIF2α proteins in myotubes. Overall responses to Hif1amsd were similar in male and female mice, but changes in complex II function, maximum respiration, Sirt3 and HIF1β protein expression and muscle fibre diameter were sex-dependent. Adaptive responses to hypoxia are mediated by stabilization of constantly synthesized HIF1α. Despite rapid degradation, the presence of HIF1α during normoxia contributes to lower mitochondrial oxidative efficiency and greater post-mitotic senescence in skeletal muscle. In vivo responses to HIF1α in skeletal muscle were differentially impacted by sex. KEY POINTS: Hypoxia-inducible factor -1α (HIF1α), a critical transcription factor, undergoes continuous synthesis and proteolysis, enabling rapid adaptive responses to hypoxia by reducing mitochondrial oxygen consumption. In mammals, skeletal muscle is the largest protein store which is determined by a balance between protein synthesis and breakdown and is sensitive to mitochondrial oxidative function. To investigate the functional consequences of transient HIF1α expression during normoxia in the basal state, myotubes and skeletal muscle from male and female mice with HIF1α knockout were studied using complementary multiomics, biochemical and metabolite assays. HIF1α knockout altered the electron transport chain, mitochondrial oxidative function, signalling molecules for protein homeostasis, and post-mitotic senescence markers, some of which were differentially impacted by sex. The cost of rapid adaptive responses mediated by HIF1α is lower mitochondrial oxidative efficiency and post-mitotic senescence during normoxia.

diaTracer enables spectrum-centric analysis of diaPASEF proteomics data

Data-independent acquisition (DIA) has become a widely used strategy for peptide and protein quantification in mass spectrometry-based proteomics studies. The integration of ion mobility separation into DIA analysis, such as the diaPASEF technology available on Bruker's timsTOF platform, further improves the quantification accuracy and protein depth achievable using DIA. We introduce diaTracer, a new spectrum-centric computational tool optimized for diaPASEF data. diaTracer performs three-dimensional (m/z, retention time, ion mobility) peak tracing and feature detection to generate precursor-resolved "pseudo-MS/MS" spectra, facilitating direct ("spectral-library free") peptide identification and quantification from diaPASEF data. diaTracer is available as a stand-alone tool and is fully integrated into the widely used FragPipe computational platform. We demonstrate the performance of diaTracer and FragPipe using diaPASEF data from cerebrospinal fluid (CSF) and plasma samples, data from phosphoproteomics and HLA immunopeptidomics experiments, and low-input data from a spatial proteomics study. We also show that diaTracer enables unrestricted identification of post-translational modifications from diaPASEF data using open/mass offset searches.

GCMSFormer: A Fully Automatic Method for the Resolution of Overlapping Peaks in Gas Chromatography-Mass Spectrometry

Gas chromatography-mass spectrometry (GC-MS) is one of the most important instruments for analyzing volatile organic compounds. However, the complexity of real samples and the limitations of chromatographic separation capabilities lead to coeluting compounds without ideal separation. In this study, a Transformer-based automatic resolution method (GCMSFormer) is proposed to resolve mass spectra from GC-MS peaks in an end-to-end manner, predicting the mass spectra of components directly from the raw overlapping peaks data. Furthermore, orthogonal projection resolution (OPR) was integrated into GCMSFormer to resolve minor components. The GCMSFormer model was trained, validated, and tested using 100,000 augmented data. It achieves 99.88% of the bilingual evaluation understudy (BLEU) value on the test set, significantly higher than the 97.68% BLEU value of the baseline sequence-to-sequence model long short-term memory (LSTM). GCMSFormer was also compared with two nondeep learning resolution tools (MZmine and AMDIS) and two deep learning resolution tools (PARAFAC2 with DL and MSHub/GNPS) on a real plant essential oil GC-MS data set. Their resolution results were compared on evaluation metrics, including the number of compounds resolved, mass spectral match score, correlation coefficient, explained variance, and resolution speed. The results demonstrate that GCMSFormer has better resolution performance, higher automation, and faster resolution speed. In summary, GCMSFormer is an end-to-end, fast, fully automatic, and accurate method for analyzing GC-MS data of complex samples.

Next-Generation Proteomics of Brain Extracellular Vesicles in Schizophrenia Provide New Clues on the Altered Molecular Connectome

Extracellular vesicles (EVs) are tiny membranous structures that mediate intercellular communication. The role(s) of these vesicles have been widely investigated in the context of neurological diseases; however, their potential implications in the neuropathology subjacent to human psychiatric disorders remain mostly unknown. Here, by using next-generation discovery-driven proteomics, we investigate the potential role(s) of brain EVs (bEVs) in schizophrenia (SZ) by analyzing these vesicles from the three post-mortem anatomical brain regions: the prefrontal cortex (PFC), hippocampus (HC), and caudate (CAU). The results obtained indicate that bEVs from SZ-affected brains contain region-specific proteins that are associated with abnormal GABAergic and glutamatergic transmission. Similarly, these vesicles from the analyzed regions were implicated in synaptic decay, abnormal brain immunity, neuron structural imbalances, and impaired cell homeostasis. Our findings also provide evidence, for the first time, that networks of molecular exchange (involving the PFC, HC, and CAU) are potentially active and mediated by EVs in non-diseased brains. Additionally, these bEV-mediated networks seem to have become partially reversed and largely disrupted in the brains of subjects affected by SZ. Taken as a whole, these results open the door to the uncovering of new biological markers and therapeutic targets, based on the compositions of bEVs, for the benefit of patients affected by SZ and related psychotic disorders.