Invited Speaker Abstracts
Alphabetical order by presenter
Decoding the Planet’s Chemistry using Ultrahigh Resolution Mass Spectrometry
Aleksandar Goranov, PhD
Old Dominion University, Norfolk, Virginia
The global carbon cycle is a fundamental framework governing the movement and transformations of organic matter on Earth. It is driven by a complex interplay of physical, biological, and chemical processes, which collectively impact Earth’s ecosystems and climate. A critical knowledge gap exists in our understanding of the exact chemical pathways that occur during environmental processes impacting the fate of organic matter as it cycles through terrestrial, oceanic, and atmospheric systems. The sheer chemical complexity of environmental matrices, having thousands of different molecular species of unknown structure, has historically limited our ability to unravel environmental processes on the molecular level.
Ultrahigh resolution mass spectrometry, namely FT-ICR and Orbitrap technologies, is the most powerful tool for elucidating chemical reactions on the molecular level. By providing unprecedented mass accuracy and resolving power, these technologies allow for identifying molecular formulas for thousands of individual compounds within a single sample. This molecular fingerprinting approach allows to investigate environmental processes on the molecular level and detail reaction mechanisms. In this talk, the use of FT-ICR-MS will be exemplified in several studies of dissolved organic matter photochemistry. By tracking changes in the molecular composition of organic matter over time, we can pinpoint specific molecules that are being degraded to CO2 (or other gasses) or transformed into new products. Using molecular data, we reveal that terrestrial organic matter in fluvial environments is transformed to marine-like species, large quantities of which likely end up in the global ocean. These findings challenge the current view that oceanic organic matter is primarily derived from algae, which impacts the global models of carbon cycling and sequestration and necessitates their urgent re-evaluation.
Mass.Wiki as novel informatics resource for confident and transparent compound annotations in metabolomics, lipidomics and exposome research
Oliver Fiehn, PhD
UC Davis, Davis, California
Nontargeted metabolomic annotations are currently performed by subjective criteria and an uncoherent selection of criteria and mass spectral libraries. While some companies do not disclose any metadata to their annotations, even academics may state that ‘in-house libraries’ were used. MS/MS data of most studies that are published in the literature are not available on public resources such as GNPS, MetabolomicsWorkbench or MetaboLights. At the same time, accurate mass and MS/MS data may often be insufficient to unambiguously annotate compounds from mass spectral libraries. Mass.Wiki is the first standardized MS/MS metabolomics database that invites both public use and criticism.
Oliver Fiehn1; Fanzhou Kong2; Quentin Wang2; Gert Wohlgemuth2; Yuanyue Li2
1UC Davis, Davis, CA; 2West Coast Metabolomics Center, University of California, DAVIS, CA
Top-down Proteomics: Ready for Prime Time?
Ying Ge, PhD
University of Wisconsin-Madison, Madison, Wisconsin
Proteoforms — the diverse protein products resulting from genetic variations, alternative splicing, and post-translational modifications — play pivotal roles in biology and disease. Top-down proteomics (TDP) analyzes intact proteoforms, enabling deeper insights into molecular mechanisms and advancing precision medicine. However, challenges such as protein solubility, proteome complexity, and analytical sensitivity have hindered broader adoption of TDP. In this seminar, I will present our multi-faceted approach to address these challenges through innovative strategies. We have developed new MS-compatible surfactants for improved protein solubilization, novel materials and methodologies for enhanced multi-dimensional chromatography separation, and nanomaterials for enriching low-abundance proteins. Additionally, I will highlight our recent advancements in high-sensitivity LC-MS methods, including a high-sensitivity TDP platform for single-cell proteoform analysis that reveals cellular heterogeneity. Our development of small-scale serial size exclusion chromatography (s3SEC) coupled with capillary RPLC-MS/MS has enabled comprehensive proteoform coverage from minimal sample inputs. Currently, we are developing a multi-dimensional liquid chromatography approach that incorporates multiple orthogonal separation modes to expand proteome coverage and detect proteins and protein complexes directly from human heart tissues for native TDP. Furthermore, I will describe our newly developed native nanoproteomics strategy for enriching and characterizing endogenous cardiac troponin complexes directly from human heart tissue. Lastly, I will introduce our new comprehensive user-friendly software package for both denatured and native TDP data analysis. These advancements collectively address the challenges of TDP, paving the way for broader adaptation of TDP to achieve deeper insights into complex biological systems and improved understanding of disease mechanisms.
Exhaled Breath Research at the Air Force Research Lab over the Last Decade
Sean Harshman, PhD
Wright State University / Air Force Research Laboratory, Fairborn, Ohio
The Air Force Research Lab, specifically the 711th Human Performance Wing, has made it a priority to lead, discovery, develop, and deliver solutions to enable, enhance, sustain and restore personnel to optimum capacity with decision superiority as the central focus for accelerated technology transition. In line with this goal, the USAF has made a multimillion-dollar investment in non-invasive biomarker discovery efforts. Exhaled breath analysis is an attractive alternative to saliva, sweat, and urine for non-invasive biomarker discovery, due to the ease of sampling and the ability to detect several hundred volatile organic compounds (VOCs) from a single sample. Over the last 10+ years, our research group has embraced the hypothesis that specific exhaled breath volatiles change in response to various physiological conditions and can be utilized to monitor human performance readiness. As a result, I will discuss the four main themes (method development & standardization, aircrew exposures & monitoring, acute hypoxia exposures, and fatigue) of our volatiles work since 2014 highlighting recent studies surrounding acute normobaric hypoxia, real-time pattern recognition, and the impact of the oral microbiome on exhaled breath results.
The views, opinions, and/or findings contained in this presentation are those of the author and should not be interpreted as representing official views or policies, either expressed or implied, of the Air Force Research Laboratory or the United States Department of Defense.
Spatial metabolomics and toxicology with mass spectrometry imaging
Autumn Qiu, PhD
Michigan State University, East Lansing, Michigan
The biological heterogeneity of cells and tissues is crucial for their biological functions and responses to environmental exposure in spatial contexts. Elucidating the spatial molecular landscape of heterogeneous biological systems represents a frontier in many areas of biology. However, conventional spatial biology approaches such as microscopy and staining often lack molecular specificity, while chromatography-mass spectrometry (MS)-based -omics methods such as metabolomics can provide comprehensive molecular information but lacks spatial resolution. Mass spectrometry imaging (MSI) represents a set of powerful tools to map the spatial distribution of elements and molecules in situ, leveraging both spatial resolution and molecular and elemental specificity. My lab utilizes MSI tools, mostly matrix-assisted laser desorption/ionization (MALDI)-MS, to elucidate the spatial chemical landscape in various biological systems. In this talk, I will focus on three recent developments in my lab. Firstly, I will describe the development of sample preparation workflows to enable both chemical and elemental imaging in a classical model animal in biology, the nematode Caenorhabditis elegans (C. elegans), using MALDI-MS and laser ablation inductively coupled plasma (LA-ICP)-MS imaging. The second part of the talk will describe our recent development in mapping the spatial distribution of metabolites in mouse gut-lumen systems which reveal intriguing spatial patterns of various metabolites. Lastly, I will briefly talk about our recent work on enabling analysis of per- and poly-fluoroalkyl substances (PFAS), a class of emerging environmental contaminants, using MALDI-MS coupled with trapped ion mobility spectrometry (TIMS), and demonstrate its application in evaluating PFAS spatial distribution in mouse tissues after exposure.
Lunch and Learn Abstracts (Sponsored)
Alphabetical order by presenter
AI-powered molecular profiling for Ion Mobility–Mass Spectrometry Omics Data
Aivett Bilbao, PhD
Pacific Northwest National Laboratory, Richland, Washington
(sponsored by Agilent)
The convergence of mass spectrometry (MS) and modern artificial intelligence (AI) offers transformative advantages, and a paradigm shift in the way we process and interpret complex omics datasets. In this presentation, I will showcase AI-enabled tools that transform raw proteomics, metabolomics, and lipidomics datasets into meaningful biological insights across applications in biology, environmental science, and synthetic biology.
Central to this effort is PeakDecoder, a sophisticated molecular annotation and quantitation approach for multidimensional datasets from analyses with LC-IM-MS and data-independent acquisition. Our AI-powered tools leverage computer vision and generative AI to overcome existing bottlenecks, accelerate discovery and enable deeper insights into the underlying mechanisms of biological systems.
Trapped Ion Mobility Spectrometry for Small Molecules with timsMetabo
Erica Forsberg, PhD
Bruker Scientific, La Mesa, California
(sponsored by Bruker)
A novel hardware design for enhancing low mass transmission over a broad mobility range has been developed for small molecule applications. The timsMetabo focuses low mass ions with the TIMS-MX cartridge and enhances signal sensitivity with the Athena Ion Processor. This expands the benefits of trapped ion mobility for isomeric and isobaric separations for untargeted and targeted metabolomics in addition to the high confidence annotations provided by the measured CCS values. This seminar will cover an overview of hardware design and practical metabolomics applications.
Improved Results with the New Orbitrap Ascend Editions Mass Spectrometers: Expand Your Research in MultiOmics, Structural Biology, and BioPharma Applications
Amanda Lee, PhD
Thermo Fisher Scientific, Worcester, Massachusetts
(sponsored by Thermo Fisher Scientific)
The Thermo Scientific Orbitrap Tribrid family of mass spectrometers has been propelling research forward in unique and interesting ways. The combination of three mass analyzers, seven ion-manipulation techniques (ETD, EThcD, ETciD, UVPD, HCD, CID, and PTCR), and a plethora of software features (including real-time search, Thermo Scientific AcquireX data acquisition software, and many method filters), allows for researchers to utilize the system for virtually any application.
The latest in this family of products is the Thermo Scientific Orbitrap Ascend Editions Tribrid MS, which comes in three “flavors” to help users know which options may be best for their research, including MultiOmics, Structural Biology, and BioPharma editions. This presentation will go over these innovations and how they help scientists do what was impossible before.
Applications of Atmospheric Pressure MALDI Imaging with the iMScope QT
Francine Yanchik-Slade, PhD
Shimadzu Scientific Instruments, Columbia, Maryland
(sponsored by Shimadzu)
Join Shimadzu Scientific Instruments for an engaging Lunch and Learn presentation exploring the cutting-edge capabilities of Atmospheric Pressure Matrix-Assisted Laser Desorption/Ionization (AP-MALDI) imaging using the iMScope QT. This session will highlight how AP-MALDI imaging enables high-resolution, label-free molecular visualization directly from tissue samples, offering powerful insights for pharmaceutical research, pathology, and metabolomics. Attendees will gain an understanding of the iMScope QT’s integrated optical and mass spectrometry imaging platform, its workflow advantages, and real-world applications that are transforming spatial omics and molecular diagnostics.
Application of Electrostatic Linear Ion Trap Charge Detection Mass Spectrometry for Mega-Dalton Size Biologics
Ying Qing Yu, PhD
Waters Corporation, Milford, Massachusetts
(sponsored by Waters)
The Electrostatic Linear Ion Trap (ELIT) Charge Detection Mass Spectrometry (CDMS) technology allows for the precise and direct measurement of both the charge and mass-to-charge ratio (m/z) of individual ions. This capability enables direct molecular weight determination, eliminating the need for complex deconvolution methods typically required in conventional mass spectrometry—especially when analyzing highly complex, high-mass biomolecules. Consequently, ELIT CDMS is particularly transformative for studying: (1) large protein complexes, (2) viruses, (3) intact ribosomes and nucleic acids, and (4) next-generation biologics, including gene and cell therapy vectors. This presentation will showcase examples demonstrating the application of ELIT CDMS to characterize a variety of large biologics.
Oral Presentations (Submitted Abstracts)
Alphabetical order by presenter
Collision-Induced Unfolding (CIU) Reveals the pH-Induced Aggregation Propensity of Glycoengineered Mabs
Addison E. Bergman, Michael Armbruster, Devin Makey, Nicole Rivera Fuentes, Valentina Rangel-Angarita, Trey Theobald, and Brandon T. Ruotolo
Department of Chemistry, University of Michigan, Ann Arbor, Michigan 48109, United States
Monoclonal antibody (mAb) therapeutics dominate global biotherapeutic sales due to their structural complexity. A major contributor is glycosylation, a post-translational modification that affects function and stability. Glycan microheterogeneity influences activity and aggregation, making glycoengineering vital for optimizing mAb performance. However, fully characterizing glycosylated mAb structures remains challenging. Herein, we leveraged a Waters Select Series Cyclic Ion Mobility (cIM) system to investigate mAb structural dynamics via collision-induced unfolding (CIU), IM-CIU, and CIU-electron capture dissociation (CIU-ECD) towards predicting mAb pH-induced aggregation.
By integrating enzymology and degradation studies, we assessed glycoform-specific impacts on mAb structure and aggregation. Herceptin (trastuzumab) was enzymatically modified with TransGlycit © (Genovis) enzymes to produce distinct glycoforms. To initiate IM-CIU, we quadrupole-select individual charge states for single-pass cIM-MS separations. Ions fractionated across the IM ATD are stored in the cIM-MS pre-array and subjected to CIU for difference analyses. These data were evaluated and processed with CIUSuite 3.
In this study, we demonstrate the utility of CIU for predicting pH-induced monoclonal antibody (mAb) aggregation. High-energy transitions of trastuzumab were linked to Fc destabilization, modulated by glycosylation and pH stress. We identify a high-energy bimodal feature, the “A/B ratio,” as a predictive metric for aggregation propensity. This ratio correlates strongly with solution-phase data: DLS showed monomer loss coincided with decreasing A/B ratio (R² = 0.96), and SEC-UV confirmed increasing aggregation paralleled decreasing A/B ratio (R² = 0.99). IM-CIU revealed that the aggregation-prone “B” isoform is an extended Fc-destabilized conformation, and low pH drives conversion from “A” to “B.” CIU-ECD showed the “B” isoform undergoes 4.4× more fragmentation and has unique fragments in the CH2 domain, underscoring its link to pH-induced aggregation pathways. Application to glycoengineered mAbs identified G2S2F/G2S2F as the most aggregation-resistant glycoform. Future work will refine IM-CIU for mapping structural dynamics and glycan microheterogeneity effects.
mmOligo: Direct Sequencing of Small RNAs via LC-MS/MS
Cameron Divoky1, Olivia Miller1, Herman Singh2, John Rose2, Mike Kollich2, Andrii Albatov2, Nikolai But2, & Michael A. Fretias1,2
1) OSU, Biological Chemistry and Pharmacology, Columbus, Ohio, 43210
2) MassMatrix, Columbus, Ohio, 43210
Next-generation sequencing (NGS) of RNA can generate large amounts of sequencing data, however, current NGS methods often mask post-transcriptional modifications (PTMs) or limit the scope of modifications that can be identified on a given RNA. While LC-MS/MS has been used to identify a broader range of RNA modifications, this is typically achieved through enzymatic digestion of the RNA, limiting the analysis to only include the nucleosides and thereby removing the sequence context in which the modifications occur. mmOligo, a bioinformatic tool, was developed to bridge this gap and provide an intuitive, user-friendly platform to enable the direct sequencing of RNAs or peptides via LC-MS/MS while preserving the sequence context in which modifications occur. Preliminary LC-MS/MS data indicate that complex RNA pools can be reliably separated by LC, and a mass analyzer optimized for negative-ion mode can generate sufficient sequencing data for mmOligo analysis. For this symposium, our mmOligo software was benchmarked against two currently available direct-RNA sequencing algorithms for LC-MS/MS data—Pytheas and the Nucleic Acid Search Engine (NASE)—using publicly available MS data for a synthetic let-7 miRNA and SARS-CoV-2 mRNA vaccine. In both cases, mmOligo was able to outperform the other two software for spectral matching leading to comparable or increased sequencing coverage as well as identification of the modified residues.
Characterization of New, Alternative Plastics Using MALDI-MS, DART Analysis, and ESI Analysis
Justin Dyer1, Luciana Rivera1, Calum Bochenek1, Dimitrios Bikiaris2, and Chrys Wesdemiotis1
1The University of Akron, Department of Chemistry, Akron, OH, 44325
2The Aristotle University of Thessaloniki, Thessaloniki, Greece, 541 24
Plastic has become the dominating product for all industrial and commercial use containers. While physical properties like strength have been the past focus, current efforts aim at the development of more versatile plastics that display multiple properties, such as flexibility, hydrophobicity, and biodegradability. Environmental concerns have also arisen due to large volumes of plastic waste and the inability for them to break down completely, causing the production of micro(nano)plastics (MNPs). To circumvent these issues, (co)polymers are being developed to allow modern plastics to exhibit a combination of flexibility, rigid strength, biodegradability, and generation through green reactants. Polyethylene furanoate (PEF), a rigid, non-permeable plastic with high thermal stability, poses as an excellent candidate for its low synthesis cost and its environmental friendliness when compared to other alternatives. Since PEF is a polymer with unique properties depending on viscosity, mass spectrometry (MS) can be used to determine and optimize the chemical properties causing these unique properties, whether it be the polymer’s molecular structure, molecular weight distribution, or end group differences. Four PEFs with unique viscosities—0.29, 0.38, 0.48, 0.57— were analyzed by a combination of MS techniques: MALD-MS, ESI-MS, and DART-MS. MALDI-MS experiments revealed different molecular weight distributions as well as different end groups among the four samples. Dart-MS analysis was used to not only confirm end groups, but also to track thermal desorption and degradation products for each sample. This technique was also able to identify sample constituents in a lower mass range that the MALDI-MS could not detect. Finally, ESI-IM-MS was used to separate sample components not only by charge, but overall shape in a 3-dimensional space, allowing for identification of minor products and architectures that otherwise reside within the noise of conventional MS spectra.
Proteomic signatures of idiopathic male infertility identified by data independent acquisition mass spectrometry
Regina M. Edgington1, Charles H. Muller2, Damien B. Wilburn1,3
¹Department of Chemistry and Biochemistry, The Ohio State University, Columbus, OH 43210
2Deparment of Urology, University of Washington School of Medicine, Seattle, WA 98195
3Center for RNA Biology, Columbus, OH 43210
Infertility affects roughly 1 in 6 people worldwide, with male and female partners contributing equally. Male infertility presents across a wide phenotypic spectrum. At the most severe end are men with azoospermia, where sperm are completely absent from the ejaculate and usually have a direct, identifiable cause that is structural, developmental, or genetic in origin. Intermediate forms are defined by abnormal semen parameters, including reduced sperm concentration, motility, or morphology. These assessments are made through semen analysis (SA), the current clinical standard that measures a limited set of observable features and compares them to reference thresholds. Despite its central role, SA can only describe infertility in terms of observable causes, and up to 70% of infertile men pass SA criteria without an identifiable macroscopic abnormality, a condition known as idiopathic infertility.
Mass spectrometry–based proteomics has been a powerful tool for interrogating sperm biology, but most large studies have focused on men with overt semen abnormalities. These efforts reveal striking proteomic changes and candidate biomarkers, in some cases with fold changes as high as eightfold when measured by data-dependent acquisition (DDA)1. Expanding on these studies, we are performing quantitative proteomics on fertile men (N=8) and men with chronic idiopathic infertility who pass SA thresholds (N=11). By leveraging data-independent acquisition (DIA), we aim to capture subtle but biologically meaningful proteomic differences with maximal quantitative accuracy. Our findings will be compared directly to proteomic alterations documented in more severe infertility, with the goal of identifying shared pathways that span the infertility spectrum. Pilot studies (N=3) already validate known biomarkers and suggest novel proteomic signatures related to sperm maturation in idiopathically infertile men. A larger cohort will provide the statistical power needed to uncover pathways underlying idiopathic infertility while establishing the basis for a molecular semen analysis to refine diagnosis and classification.
Targeted and Untargeted Metabolomics of Tricarboxylic Acid Cycle Metabolites in ACC1 Knockout Mice under High-Fat and Low-Fat Diets
Christeen Fernando1, Anupama Binoy2, Shouan Zhu2, Mengliang Zhang1
1Department of Chemistry and Biochemistry, Ohio University, Athens, Ohio, 45701
2Department of Biomedical Sciences, Ohio Musculoskeletal and Neurological Institute (OMNI), Ohio University, Athens, Ohio 45701
Metabolomics has become significantly important at present, as all living organisms have diverse metabolic pathways crucial in carrying out biological functions. Typically, the analysis of metabolites is conducted using either untargeted or targeted approaches. The main analytical platform in metabolomics is Mass-Spectrometry (MS) coupled with Liquid Chromatography (LC) or Gas Chromatography (GC), but GC-MS is largely limited to the detection of volatile metabolites in extracts.
In this study, both untargeted and targeted metabolomics analysis were conducted using a Thermo Scientific Vanquish UHPLC system coupled with an Orbitrap Exploris 120 MS. An Xbridge BEH Amide column was used in the LC separation for the targeted analysis of polar metabolites. Parallelly an untargeted lipidomics study was also carried out using an Accucore™ C30 column. The goal was to investigate the effect of Acetyl-CoA Carboxylase1 (ACC1) knockout on the upregulation of tricarboxylic acid (TCA) cycle metabolites, given ACC1’s role in osteoarthritis development. Tissue extracts from wild-type and ACC1 knockout mice under high-fat diet (HFD) and low-fat diet (LFD) conditions were analyzed. The major TCA cycle metabolites in mammalian tissues, including Arginine, Alanine, Asparagine, Isoleucine, Leucine, Glutamine, Glycine, Phenylalanine, Proline, Valine, Serine, Acetyl CoA, Pyruvate, Oxaloacetate, Aconitate, Malate, Fumarate, Succinate, Citrate, Isocitrate, and α-Ketoglutarate, were analyzed. Detection was significantly influenced by the ion polarity modes, as amino acids were predominantly observed in positive mode and the organic acids in negative mode. Oxaloacetate was recognized as an unstable metabolite, as it tends to convert to pyruvate under acidic conditions.
The peak areas of the metabolites were evaluated for each sample and statistically compared between groups. The UHPLC-MS approach enabled both quantitative and qualitative analysis, providing high sensitivity, resolution, and mass accuracy. This allowed confident metabolite identification and a comprehensive assessment of metabolic changes under different biological conditions.
Study of the conformational diversity of a tRNAArg variant expressed in individuals with dextrocardia
Kaylee Grabarkewitz1-3, Moulisubhro Datta1,2,4, Susan E Cole4, Venkat Gopalan1,2, and Vicki Wysocki1-3,5
1The Department of Chemistry and Biochemistry
2Center for RNA Biology
3Resource for Native MS Guided Structural Biology
4Molecular, Cellular, and Developmental Biology Program, The Ohio State University, Columbus, OH
5School of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, GA
Situs inversus is a rare condition in which the vital organs within the chest and abdomen are positioned opposite to what is standard. Dextrocardia with situs inversus is a condition where the major axis of the heart is tilted towards the right instead of the usual left side of the thoracic cavity One possible cause of dextrocardia with situs inversus that we are investigating is a single-nucleotide polymorphism (SNP) in the 3′ UTR of the HES7 gene, specifically focusing our attention on a tRNAArgUCU isodecoder (tRNA named TCT-2-1) encoded immediately downstream to HES7 and on the opposite strand. We hypothesize that the SNP, located in the trailer sequence, causes an extension of the acceptor stem of the TCT-2-1 precursor (pTCT-2-1), a change that could potentially result in processing defects by RNase P, which cleaves the 5′-leader of precursor tRNAs. Studies mapping the native 5′-leaders and 3′-trailers led us to select two p-TCT-2-1 species to map conformational changes engendered by the point mutation: a 4-nucleotide (nt) 5′-leader with either a 4- or 8-nt 3′-trailer (termed 4L4T or 4L8T, respectively). During native gel electrophoresis, migrational differences were observed between the wildtype (WT) and the mutant (MUT) species and as a function of Mg2+. Native mass spectrometry studies confirmed the presence of exclusively monomeric species, a finding consistent with the idea that migrational differences in native gels must arise from the MUT sampling an alternate conformation. Further analysis with ion mobility mass spectrometry (IM-MS) using the Agilent 6560 IMS showed differences between the WT and MUT pTCT-2-1. Collision-induced dissociation studies too revealed unfolding differences between the WT and MUT species.
Label-Free Quantification and Visualization of RNA Nanoparticles by LC–MS and FISH
Mohammed S. Hassan1, S. Kevin Li2 ,and Patrick A. Limbach1
1 Rieveschl Laboratories for Mass Spectrometry, Department of Chemistry, University of Cincinnati, Cincinnati, OH, USA
2 Division of Pharmaceutical Sciences, James L. Winkle College of Pharmacy, University of Cincinnati, Cincinnati, OH, USA
RNA nanoparticles (RNA NPs) are promising vectors for drug delivery due to their programmability and biocompatibility. However, their clinical translation has been slowed by the lack of a reliable, universal assay for quantification. Existing methods, such as PCR, fail to detect small-sized constructs, while standard imaging approaches rely on fluorescent tags that can change biodistribution profiles. This dual gap in label-free quantification and visualization has limited accurate analysis of RNA NP biodistribution, pharmacokinetics, and pharmacodynamics.
Here, we present a liquid chromatography–mass spectrometry (LC–MS) assay for RNA NPs, applicable to all RNase-resistant constructs. Our method achieves a limit of quantification (LOQ) ranging from 2 to 12.5 fmol, enabling sensitive, label-free detection across diverse nanoparticle designs. Compared to PCR, it offers superior performance for small RNA NPs by directly measuring intact particles in the tissue.
To confirm biological uptake, we applied fluorescence in situ hybridization (FISH) to ocular tissues using sequence-specific probes that require no prior labeling of the RNA NPs themselves. This approach revealed RNA NP localization within the retina, providing spatial insight without structural modification.
Together, these complementary assays form a versatile, label-free toolkit that integrates sensitive quantification with spatial mapping of RNA NPs. By directly addressing the critical gap in biodistribution analysis, this platform lays the foundation for advancing RNA-based therapeutics toward clinical translation in both ocular and systemic disease.
Integrative Spatial Omics for Systems-Level Mapping of Pathological Niches
Angela R.S. Kruse1,2, Roy Lardenoije3, Lukasz G. Migas4, Claire F. Scott1,2, Cody Marshall1,2, Morad C. Malek1,2, Adel Eskaros5, Thai Pham1,2, Kristie Aamodt6, Madeline Colley1,2, Lissa Ventura-Antunes7, Melissa A. Farrow1,2, Raf Van de Plas4, Joana Goncalves3, Matthew Schrag7,8,9, Alvin C. Powers5,10,11, Jeffrey M. Spraggins1,2,12,13
1 Mass Spectrometry Research Center, Vanderbilt University, Nashville, Tennessee, USA
2 Department of Cell and Developmental Biology, Vanderbilt University, Nashville, Tennessee, USA
3 Department of Intelligent Systems, Delft University of Technology, Delft, Netherlands
4 Delft Center for Systems and Control, Delft University of Technology, Delft, Netherlands
5 Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
6 Division of Pediatric Endocrinology, Department of Pediatrics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
7 Department of Neurology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
8 Vanderbilt Brain Institute, Vanderbilt University, Nashville, Tennessee, USA
9 Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, Tennessee, USA
10 Division of Diabetes, Endocrinology and Metabolism, Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
11 Veteran Affairs Tennessee Valley Healthcare System, Nashville, Tennessee, USA
12 Department of Biochemistry, Vanderbilt University, Nashville, Tennessee, USA
13 Department of Chemistry, Vanderbilt University, Nashville, Tennessee, USA
Alzheimer’s disease (AD) is a neurodegenerative disorder often associated with amyloid deposits within the brain. Amyloid aggregation is also observed in other organs and disease systems. For example, amyloid plaques composed of islet amyloid polypeptide can be found within the pancreatic islet in type 2 diabetes (T2D). These individuals have an increased risk for AD, but the cellular and molecular commonalities between these diseases are not fully understood. To compare the molecular environment of amyloid plaques in brain and pancreas, we integrate multiple imaging and analytical techniques. These include spatial transcriptomics, amyloid staining, highly multiplexed immunofluorescence, and matrix-assisted laser desorption ionization imaging mass spectrometry (MALDI IMS), enabling comprehensive characterization of AD brain and T2D pancreatic human tissues.
First, Xenium spatial transcriptomics is used to spatially profile hundreds of genes in each sample. We then remove the Xenium flow cell from the sample and perform multiplexed immunofluorescence, followed by amyloid staining using thiazine red and thioflavin S for the brain and pancreas, respectively. On a serial section, we use MALDI IMS to measure lipid species at 10-µm pixel size with a timsTOF fleX mass spectrometer. Autofluorescence microscopy is collected before and after IMS, for image registration between the sections.
By integrating multiple spatial datasets, we established a detailed molecular map of AD brain and T2D pancreas tissues at an unprecedented molecular and spatial scale. Using autofluorescence microscopy as a common modality, we co-registered each dataset using in-house developed software. Interpretable machine learning and differential expression analysis were used to identify candidate lipid and gene biomarkers associated with amyloid. This approach allowed us to discover potential biomarkers for amyloid pathology and presents a technical and analytical workflow that can be applied to other organs and disease systems.
MALDI Imaging and Spatial SILAC Proteomics of Three-Dimensional Multicellular Spheroids Dynamically Dosed with Doxorubicin-Encapsulating Liposomes
Arbil Lopez, Joseph H. Holbrook, and Amanda B. Hummon
The Ohio State University, Department of Chemistry and Biochemistry
Dynamic dosing overcomes the limitations of gas and nutrient exchange and the build-up of toxic metabolites seen in static dosing experiments. Preliminary data shows that doxorubicin-encapsulating liposomes are stable to fluidic dosing across a semipermeable membrane and deliver doxorubicin to spheroids within 48 hours. Doxorubicin-containing liposomes, tagged on the outer bilayer with the fluorophore Alexa Fluor 647, show fluorescence by nanoparticle tracking analysis. Fluorescence imaging shows the fluorophore in the outer layer of the spheroids after 48 hours of fluidic dosing. Complementary MALDI MSI shows penetration of doxorubicin, visible as the protonated (m/z 544.1807) and sodiated (m/z 566.1626) adducts, into spheroids after 48 hours. Taken together, these exciting results indicate that liposomes actively deliver doxorubicin to spheroids through the device’s semipermeable membrane and are stable to dynamic dosing. Spheroids are valuable models to evaluate dynamic dosing as they recapitulate the nutrient, oxygen, and pH gradients of solid tumors. Spheroids feature distinct cellular populations, with a necrotic core, quiescent middle layer, and proliferative outer layer. We recently demonstrated that these cellular populations can be differentially labeled by switching SILAC media label state at set time points during spheroid growth. Each population retains its isotopic “zip code” upon bulk proteomic analysis, allowing identified proteins to be mapped back to their layer of origin. In this work, we use spatial SILAC proteomics to interrogate the effects of dynamic dosing with liposomal doxorubicin on different cellular populations within spheroids. Samples cluster by drug treatment rather than label state in both the core and outer layers of spheroids. Proteomic analysis reveals the differential regulation of proteins associated with doxorubicin’s mechanism of action upon drug treatment between spheroid core and outer layer. Coupled with the results of MALDI MSI and fluorescence imaging, spatial SILAC provides a comprehensive pharmacodynamic profile of the distinct cellular regions within spheroids.
Per- and Polyfluoroalkyl Substances (PFAS) Suspect Screening Analysis Method Validation
Derek Muensterman, Kavitha Dasu, Cameron Orth, Brian Miller, Cheryl Triplett, Larry Mullins, Denise Schumitz
Battelle Memorial Institute, 505 King Avenue, Columbus, OH, 43201, USA
As the use of suspect screening analysis becomes more routine for the investigation of per- and polyfluoroalkyl substances (PFAS), method robustness becomes paramount. Herein, the development and validation of a high-resolution mass spectrometry (HRMS)-based suspect screening workflow for PFAS, optimized for environmental matrices is presented. The analytical process utilizes a curated library of 600 LC-MS amenable PFAS compounds using time-of-flight mass spectrometry (TOF-MS) with full-scan MS and MS/MS acquisition. Data post-processing included retention time alignment, Kendrick mass defect filtering, background correction, homolog series grouping, and mass error acceptance criteria. Confidence levels for compound identification are assigned using adapted criteria from Schymanski et al. (Schymanski et al., 2014) to ensure standardized interpretation. A bootstrap simulation approach was employed for semi-quantitative analysis, yielding accuracy values of 1.29 ± 0.74 (positive mode) and 1.00 ± 0.48 (negative mode), with reliability metrics for negative mode analytes reaching median values of 89–100%. These metrics support the reproducibility and comparability of the extraction methods used across inter-day (95±4%), intra-day (88.9% to 100%), and analyst-to-analyst variations (RSD of 0 – 0.5%). The workflow advances precision in PFAS suspect screening and contributes to harmonizing mass spectral methodologies for regulatory and forensic applications. The findings herein demonstrate that the suspect screening workflow for suspect PFAS, which incorporates robust extraction and analytical methods, delivers reliable and reproducible results across multiple sources of variance, including matrix, analyst, and day-to-day differences. Overall, the study herein underscores the importance of method selection and validation for achieving high confidence for suspect PFAS identified following the suspect screening workflow.
References
Schymanski EL, Jeon J, Gulde R, Fenner K, Ruff M, Singer HP, et al. Identifying Small Molecules via High Resolution Mass Spectrometry: Communicating Confidence. Environmental Science & Technology 2014; 48: 2097-2098.
Label-free quantitative proteomics to compare protein expression between OVCAR8 3D spheroids and 2D cultures
Nicole E. Platzer1,2; Arbil Lopez1,2; Amanda B. Hummon1,2
1The Ohio State University, Columbus, OH
2The Ohio State University Department of Chemistry and Biochemistry, Columbus, OH
Epithelial ovarian cancer (EOC) is characterized by a high prevalence of drug resistance and a strong potential for metastasis. Preclinical models that accurately reflect the complex biology and tumor microenvironment of EOC are essential for evaluating chemotherapeutics. In this work, the EOC cell line OVCAR8 was cultured as 3D spheroids on non-adherent agarose, providing a physiologically relevant model compared to 2D monolayers. To investigate proteomic differences, label-free quantitative mass spectrometry was performed on OVCAR8 monolayers and day-14 spheroids in triplicate. Cells were lysed in 6% SDS, reduced, alkylated, and digested with trypsin. Peptides were analyzed by LC-MS/MS on an Orbitrap Fusion coupled to an UltiMate 3000 nano-LC with C18 reversed-phase column chromatography. Data were processed in FragPipe, resulting in 4,300 reproducibly quantified proteins (FDR < 0.01), of which 4,176 were shared between 2D and 3D cultures.
Differential expression analysis in R using MSstats identified 1,085 significantly altered proteins (adj. p-value ≤ 0.05, ≥1.5-FC), with 689 upregulated and 396 downregulated in spheroids. Gene Ontology (GO) analysis with clusterProfiler revealed enrichment of proteins linked to extracellular matrix organization, adhesion, and migration, suggesting adaptations in 3D spheroids that support tumor progression. Upregulated proteins in 3D implicated oxidative metabolism, ER function, and membrane transport, while downregulated proteins were linked to cell cycle and chromatin regulation, consistent with reduced proliferation. Reactome pathway analysis using enrichR further highlighted enrichment of oxidative phosphorylation and epithelial-mesenchymal transition (EMT) pathways in spheroids.
In conclusion, these findings emphasize the value of 3D spheroids as models of EOC biology, revealing proteomic shifts related to metabolic adaptation, structural remodeling, and migratory potential. Future work will optimize serial trypsinization for layer-specific proteomic analysis and integrate flow cytometry to validate subpopulation separation. This study will give deeper insight into proteomic adaptations in 3D tumor models and their relevance to EOC progression.
Silver Microcapillary Spray Significantly Improves Protein and Amino Acid Detection.
Adam J. Reed and Abraham K. Badu-Tawiah
Ohio State University Department of Chemistry
Electrospray ionization (ESI) and matrix-assisted laser desorption/ionization (MALDI) opened the doorway for the mass spectrometric detection of large biomolecules. But detection via ESI-MS is limited by several factors including background signal from the solvent, thus requiring some additives (e.g., acids) to enhance analytical signal although such an approach can denature proteins. Even with the best detection components, the limit of detection and quantification are fundamentally limited by signal contribution from the solvent. We have developed a variant of ESI that employs a fundamentally new ionization mechanism to enhance analyte signal for a variety of compounds while limiting solvent peaks. In ESI, the solvent is charged prior to microdroplet formation. By forming microdroplets prior to charge introduction, signal from solvent is reduced in the higher mass regimes and proteins can be detected at significantly lower limits.
To achieve this objective, we developed a chemical approach to prepare silver (Ag)-coated silica capillaries. The as-prepared Ag-coated capillaries were then assembled in the form of an ESI source, where the traditional ESI emitter was inserted into the Ag-coated capillary as the outer capillary. Then, the spray voltage was applied not to the ESI emitter but to the Ag-coated outer capillary. In this case, the sonic sprayed neutral microdroplets exiting from the ESI emitter are briefly exposed to nonthermal plasma generated from the Ag-coated outer capillary.
When comparing a standard ESI source with our new Ag-coated ESI source, the ratio of analyte signal to background signal is improved by six orders of magnitude for the protein lysozyme. Furthermore, due to non-thermal plasma formation, selective reaction chemistry can be utilized for the analysis of neutral amino acids (AA) without the need for any added acid or base. The amino acids can be sprayed with either acetone, butanone, or another volatile ketone to give the corresponding imine product with enough distinct tandem MS fragment peaks to allow for clear identification. Since typically amino acids require significant acid for ionization, the ability to detect them without acid is an important step forward for amino acid analysis. This talk will cover the design and optimization of the Ag-coated ESI source followed by a more detailed discussion of the analyzed proteins and amino acids.
Characterization of sea urchin footprints using MALDI-MSI to uncover new underwater adhesives
Rivera Molina, Luciana; Baker, Zachary; Wesdemiotis, Chrys; Stark, Alyssa
The University of Akron, Villanova University
Sea urchins are frequently found in rough, wave-battered coastal areas. To withstand these conditions, they rely on specialized adhesive organs called tube feet. These have hydrostatic structures with a distally located disk that produces adhesive secretions for attachment. The secreted adhesive, after detachment, leaves a footprint on the substrate. Understanding the molecular structure characteristics of these adhesives is of immense interest, as they could help with the development of new biomimetic underwater adhesives and anti-fouling agents. Here, we use surface layer mass spectrometry imaging (SL-MSI) as well as conventional MSI to unveil new information about the chemical composition of sea urchin adhesives. Sea urchin samples were prepared by creating a small habitat and introducing a glass slide allowing for the urchin to attach and detach many times. Once dried, MALDI matrix (CHCA) was either sublimed (for SL-MSI) or sprayed (for conventional MSI) onto the slide for MALDI-TOF/TOF characterization. SL-MALDI-MSI experiments were performed on the footprints of purple sea urchins which can be found along the west coast of the United States. Upon secretion, sea urchin adhesive material becomes insoluble, thus a significant number of denaturants and reducing agents are required to solubilize it. Fortunately, this process is not required for MSI analysis of the collected footprints. The acquired MSI spectra showed ions in the m/z 250-500 range, and a subsequent search on the LIPID MAPS database confirmed the presence of N-acylethanolamines, phosphatidylserines, N-acetyltransferases, and sphingolipids in these footprints. The identified lipids are non-polar compounds, which are evidently necessary for underwater adhesion. Small amino acids were also found in the footprints, including asparagine, threonine, and valine; these are common in marine adhesives and could be key factors for adhesion. A comparison between different species (e.g. red vs purple urchin) could give insight into the unique composition of the sea urchins adhesive.
Unveiling the Metabolic Signature of VLCAD Deficiency: Combined Metabolomics and Seahorse Analyzer Approach
Yana I Sandlers, Olha Tsikhun and Igor Radzikh
Department of Chemistry, Cleveland State University, Cleveland OH, 44115
Very long-chain acyl-CoA dehydrogenase deficiency (VLCADD) is an inherited autosomal recessive disorder of mitochondrial β-oxidation, a critical pathway for the catabolism of long-chain fatty acids. In individuals with VLCADD, impaired long-chain fatty acid utilization results in a spectrum of clinical manifestations. These include hypoketotic hypoglycemia, cardiomyopathy, rhabdomyolysis, and potentially life-threatening metabolic crises. Given the very limited treatment options currently available, a comprehensive understanding of the diverse metabolic abnormalities associated with VLCADD is essential for effective disease management.
Our study employed untargeted metabolomics and lipidomics (LC-QTOF) to study metabolic aberrations in fibroblasts derived from subjects with three different VLCAD mutations. Chromatographic separation was achieved with Atlantis Premier HILIC-Z (2.1mm x 150 mm, 1.7 µm) and T3 HSS (2.1mm x 100 mm, 2.1 µm) columns for polar metabolites and lipids respectively. Metabolomics and lipidomics data analysis was carried out with MassProfiler Professional (Agilent), Metaboanalyst 6.0 and Lipid Annotator platforms. Mitochondrial respiration analysis has been performed with Seahorse XF analyzer (Agilent).
Detailed and conservative analysis of cellular metabolome reveals fourteen significantly increased (FC≥2, p<0.05) and eighty-six significantly decreased metabolites (FC≤2, p<0.05) in VLCADD cells, emphasizing extensive metabolic disruptions. Orthogonal Partial Least Squares—Discriminant Analysis shows clear clustering of VLCADD vs control groups. Pathway and enrichment analyses demonstrate that most of the altered metabolites are associated with energy production, Krebs cycle, and mitochondrial function. VLCADD cells also demonstrate altered lipidome with significant increases in fatty acid oxidation intermediates, ceramides, lysophosphatidylcholine (LPC), triglycerides, and diglycerides, accompanied by a decrease in sphingomyelins. Seahorse analysis revealed impaired energy metabolism reflected by reduced fatty acid oxidation capacity alongside a concomitant upregulation of glucose oxidation.
We identified secondary biochemical mechanisms contributing to VLCAD pathogenesis. Cells harboring VLCAD mutation exhibited alteration in complex lipids, mitochondrial dysfunction and deficient energy metabolism. Therefore, modulating mitochondrial energy metabolism warrants exploration as a complementary therapeutic strategy with the potential to mitigate the development of the clinical phenotype in VLCAD disease.