Multimodal Mass Spectrometry Imaging of Rat Brain Using IR-MALDESI and NanoPOTS-LC-MS/MS

Imaging with mass spectrometry: Which ionization technique is best?

The use of mass spectrometry (MS) to acquire molecular images of biological tissues and other substrates has developed into an indispensable analytical tool over the past 25 years. Imaging mass spectrometry technologies are widely used today to study the in situ spatial distributions for a variety of analytes. Early MS images were acquired using secondary ion mass spectrometry and matrix-assisted laser desorption/ionization. Researchers have also designed and developed other ionization techniques in recent years to probe surfaces and generate MS images, including desorption electrospray ionization (DESI), nanoDESI, laser ablation electrospray ionization, and infrared matrix-assisted laser desorption electrospray ionization. Investigators now have a plethora of ionization techniques to select from when performing imaging mass spectrometry experiments. This brief perspective will highlight the utility and relative figures of merit of these techniques within the context of their use in imaging mass spectrometry.

Efficient and Sensitive Sample Preparation, Separations, and Data Acquisition for Label-Free Single-Cell Proteomics

We describe a sensitive and efficient workflow for label-free single-cell proteomics that spans sample preparation, liquid chromatography separations, and mass spectrometry data acquisition. The Tecan Uno Single Cell Dispenser provides rapid cell isolation and nanoliter-volume reagent dispensing within 384-well PCR plates. A newly developed sample processing workflow achieves cell lysis, protein denaturation, and digestion in 1 h with a single reagent dispensing step. Low-flow liquid chromatography coupled with wide-window data-dependent acquisition results in the quantification of nearly 3000 proteins per cell using an Orbitrap Exploris 480 mass spectrometer. This approach greatly broadens accessibility to sensitive single-cell proteome profiling for nonspecialist laboratories.

Biological mass spectrometry enables spatiotemporal 'omics: From tissues to cells to organelles

Biological processes unfold across broad spatial and temporal dimensions, and measurement of the underlying molecular world is essential to their understanding. Interdisciplinary efforts advanced mass spectrometry (MS) into a tour de force for assessing virtually all levels of the molecular architecture, some in exquisite detection sensitivity and scalability in space-time. In this review, we offer vignettes of milestones in technology innovations that ushered sample collection and processing, chemical separation, ionization, and 'omics analyses to progressively finer resolutions in the realms of tissue biopsies and limited cell populations, single cells, and subcellular organelles. Also highlighted are methodologies that empowered the acquisition and analysis of multidimensional MS data sets to reveal proteomes, peptidomes, and metabolomes in ever-deepening coverage in these limited and dynamic specimens. In pursuit of richer knowledge of biological processes, we discuss efforts pioneering the integration of orthogonal approaches from molecular and functional studies, both within and beyond MS. With established and emerging community-wide efforts ensuring scientific rigor and reproducibility, spatiotemporal MS emerged as an exciting and powerful resource to study biological systems in space-time.

Metabolomics in drug research and development: The recent advances in technologies and applications

Emerging evidence has demonstrated the vital role of metabolism in various diseases or disorders. Metabolomics provides a comprehensive understanding of metabolism in biological systems. With advanced analytical techniques, metabolomics exhibits unprecedented significant value in basic drug research, including understanding disease mechanisms, identifying drug targets, and elucidating the mode of action of drugs. More importantly, metabolomics greatly accelerates the drug development process by predicting pharmacokinetics, pharmacodynamics, and drug response. In addition, metabolomics facilitates the exploration of drug repurposing and drug-drug interactions, as well as the development of personalized treatment strategies. Here, we briefly review the recent advances in technologies in metabolomics and update our knowledge of the applications of metabolomics in drug research and development.

Intracellular Amyloid-β Detection from Human Brain Sections Using a Microfluidic Immunoassay in Tandem with MALDI-MS

Alzheimer's disease (AD) currently affects more than 30 million people worldwide. The lack of understanding of AD's physiopathology limits the development of therapeutic and diagnostic tools. Soluble amyloid-β peptide (Aβ) oligomers that appear as intermediates along the Aβ aggregation into plaques are considered among the main AD neurotoxic species. Although a wealth of data are available about Aβ from in vitro and animal models, there is little known about intracellular Aβ in human brain cells, mainly due to the lack of technology to assess the intracellular protein content. The elucidation of the Aβ species in specific brain cell subpopulations can provide insight into the role of Aβ in AD and the neurotoxic mechanism involved. Here, we report a microfluidic immunoassay for in situ mass spectrometry analysis of intracellular Aβ species from archived human brain tissue. This approach comprises the selective laser dissection of individual pyramidal cell bodies from tissues, their transfer to the microfluidic platform for sample processing on-chip, and mass spectrometric characterization. As a proof-of-principle, we demonstrate the detection of intracellular Aβ species from as few as 20 human brain cells.

Quasi-continuous infrared matrix-assisted laser desorption electrospray ionization source coupled to a quadrupole time-of-flight mass spectrometer for direct analysis from well plates

High-throughput screening (HTS) is a technique mostly used by pharmaceutical companies to rapidly screen multiple libraries of compounds to find drug hits with biological or pharmaceutical activity. Mass spectrometry (MS) has become a popular option for HTS given that it can simultaneously resolve hundreds to thousands of compounds without additional chemical derivatization. For this application, it is convenient to do direct analysis from well plates. Herein, we present the development of an infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) source coupled directly to an Agilent 6545 for direct analysis from well plates. The source is coupled to a quadrupole time-of-flight (Q-TOF) mass spectrometer to take advantage of the high acquisition rates without sacrificing resolving power as required with Orbitrap or Fourier-transform ion cyclotron resonance (FTICR) instruments. The laser used for this source operates at 100 Hz, firing 1 pulse-per-burst, and delivers around 0.7 mJ per pulse. Continuously firing this laser for an extended duration makes it a quasi-continuous ionization source. Additionally, a metal capillary was constructed to extend the inlet of the mass spectrometer, increase desolvation of electrospray charged droplets, improve ion transmission, and increase sensitivity. Its efficiency was compared with the conventional dielectric glass capillary by measured signal and demonstrated that the metal capillary increased ionization efficiency due to its more uniformly distributed temperature gradient. Finally, we present the functionality of the source by analyzing tune mix directly from well plates. This source is a proof of concept for HTS applications using IR-MALDESI coupled to a different MS platform.

Mass Spectrometry-Based Glycoproteomic Workflows for Cancer Biomarker Discovery

Glycosylation has a clear role in cancer initiation and progression, with numerous studies identifying distinct glycan features or specific glycoproteoforms associated with cancer. Common findings include that aggressive cancers tend to have higher expression levels of enzymes that regulate glycosylation as well as glycoproteins with greater levels of complexity, increased branching, and enhanced chain length1. Research in cancer glycoproteomics over the last 50-plus years has mainly focused on technology development used to observe global changes in glycosylation. Efforts have also been made to connect glycans to their protein carriers as well as to delineate the role of these modifications in intracellular signaling and subsequent cell function. This review discusses currently available techniques utilizing mass spectrometry-based technologies used to study glycosylation and highlights areas for future advancement.

Emerging Computational Methods in Mass Spectrometry Imaging

Mass spectrometry imaging (MSI) is a powerful analytical technique that generates maps of hundreds of molecules in biological samples with high sensitivity and molecular specificity. Advanced MSI platforms with capability of high-spatial resolution and high-throughput acquisition generate vast amount of data, which necessitates the development of computational tools for MSI data analysis. In addition, computation-driven MSI experiments have recently emerged as enabling technologies for further improving the MSI capabilities with little or no hardware modification. This review provides a critical summary of computational methods and resources developed for MSI data analysis and interpretation along with computational approaches for improving throughput and molecular coverage in MSI experiments. This review is focused on the recently developed artificial intelligence methods and provides an outlook for a future paradigm shift in MSI with transformative computational methods.

Emerging insights and challenges for understanding T cell function through the proteome

T cells rapidly transition from a quiescent state into active proliferation and effector function upon exposure to cognate antigen. These processes are tightly controlled by signal transduction pathways that influence changes in chromatin remodeling, gene transcription, and metabolism, all of which collectively drive specific T cell memory or effector cell development. Dysregulation of any of these events can mediate disease and the past several years has shown unprecedented novel approaches to understand these events, down to the single-cell level. The massive explosion of sequencing approaches to assess the genome and transcriptome at the single cell level has transformed our understanding of T cell activation, developmental potential, and effector function under normal and various disease states. Despite these advances, there remains a significant dearth of information regarding how these events are translated to the protein level. For example, resolution of protein isoforms and/or specific post-translational modifications mediating T cell function remains obscure. The application of proteomics can change that, enabling significant insights into molecular mechanisms that regulate T cell function. However, unlike genomic approaches that have enabled exquisite visualization of T cell dynamics at the mRNA and chromatin level, proteomic approaches, including those at the single-cell level, has significantly lagged. In this review, we describe recent studies that have enabled a better understanding of how protein synthesis and degradation change during T cell activation and acquisition of effector function. We also highlight technical advances and how these could be applied to T cell biology. Finally, we discuss future needs to expand upon our current knowledge of T cell proteomes and disease.

Sequential paired covariance for improved visualization of mass spectrometry imaging datasets

Untargeted analyses in mass spectrometry imaging produce hundreds of ion images representing spatial distributions of biomolecules in biological tissues. Due to the large diversity of ions detected in untargeted analyses, normalization standards are often difficult to implement to account for pixel-to-pixel variability in imaging studies. Many normalization strategies exist to account for this variability, but they largely do not improve image quality. In this study, we present a new approach for improving image quality and visualization of tissue features by application of sequential paired covariance (SPC). This approach was demonstrated using previously published tissue datasets such as rat brain and human prostate with different biomolecules like metabolites and N-linked glycans. Data transformation by SPC improved ion images resulting in increased smoothing of biological features compared with commonly used normalization approaches.