Abstract: Prophylactic viral and bacterial vaccines have traditionally focused on eliciting antibody responses, which tend to not offer long-lasting or variant-resistant protection. Vaccines that target the activation of CD8+ T cells have the potential to overcome these challenges by providing broad and long-lasting immunity, and the strategy of vaccine activated CD8+ T cells could prevent spreading & disease (productive infection) by eliminating infected cells early in the infectious cycle. Emergex Vaccines has adopted a novel approach to discover and identify naturally processed and presented pathogen-specific MHC class I T cell epitopes, known as immunopeptidomics. The immunopeptidomics approach enables generation of a pathogen-specific peptide “ligandome” libraries that can be utilized as a source of candidate antigens to be rapidly incorporated into a vaccine formulation. Candidate selection of pathogen-specific peptides derived from proteins stemming from conserved genomic regions, which are presented throughout the infectious life cycle of the pathogen, as well as present across related pathogen family members, afford broad and long-term protective responses. Emergex’s T cell Priming (TcP) vaccine of synthetic MHC class I pathogen-specific peptides are delivered epidermally using a passivated gold nanoparticle with innate adjuvant like properties to establish and promote the growth of antigen specific CD8+ T cells. Emergex’s T cell priming vaccines are designed to be cross protective within a pathogen family, and the technology can be provided as a combination of Emergex vaccine formulations to offer protection against multiple pathogens with one vaccine application. Utilizing the T cell adaptive vaccine platform, Emergex has successfully developed clinical-stage vaccines such as the DengueTcP and CoronaTcP, and is eager to continue to provide robust solutions and protection strategies when combatting various infectious pathogens throughout the world.
Abstract: The notion of diagnostic volatiles is not a recent one. Early diagnosticians relied significantly on body odor to diagnose conditions such as gangrene, smallpox, typhoid, and others. The prospect of exploiting body odor variation for disease diagnosis continues to generate much excitement. The recent COVID-19 pandemic demonstrated the intense interest for non-invasive health screening using trained animals, electronic noses, or mass spectrometry. A recent Web of Science search identified over 26,000 published papers from the past two decades describing the use or trained animals or instrumentation to diagnose health using the volatile metabolome. The number of diseases (chronic or infectious) and injuries studied during this time is equally impressive. Yet, there is still debate. Do observed alterations in bodily odors represent a non-invasive portal into human and animal health? Or, are these observations distracting our pursuit of effective biomarkers? In a written 2016 commentary, I stated that “to fully implement biomarker discovery and realize the implied potential of volatile metabolomics, perhaps the methodology and practice of biomarker discovery must be reexamined” [1]. Nearly a decade later, what advancements have been made and are we any closer to truly exploiting the volatile metabolome for health diagnoses?
[1] Kimball, B.A. (2016). Volatile Metabolome: Problems and Prospects. Bioanalysis. 8:1987-1991.
Abstract: Proteomics experiments have typically high economic and technical barriers Abstract: Gangliosides, abundant lipids in the central nervous system (CNS), play a role in CNS conditions such as Alzheimer's, Parkinson's, Huntington's diseases, and multiple sclerosis. Analyzing gangliosides is highly challenging due to their isomeric heterogeneity, which involves structural motifs from both oligosaccharides and lipids. To address this, we use high-resolution SLIM-based separations coupled with liquid chromatography-mass spectrometry on the MOBIE device to separate gangliosides in the gas phase. Our aim is to create a high-resolution library of CCS values for endogenous gangliosides, enhancing their identification in the CNS.
Abstract: Proteomics experiments have typically high economic and technical barriers to broad biomedical scientists, which not only result in costly supplies and accessories for sample preparation but also the reluctance to adapt new techniques. We presented an effective and efficient, yet economical approach (named E3technology), for proteomics sample preparation. By immobilizing silica microparticles into a polytetrafluoroethylene (PTFE) matrix, we developed a novel filter medium (also known as Empore membrane), which could be used as a robust and reliable proteomics platform to generate LCMS-friendly samples in a rapid and low-cost fashion. Using different formats of E3technology, we explored a variety of sample types in varied complexity, quantity, volume, and size, including bacterial, fungi, mammalian cells, mouse tissue, and human body fluids. We benchmarked their performance against several established approaches. Our data suggest that E3technology outperforms many of the currently available techniques in terms of proteome identification and quantitation. It is widely applicable, and is stress-free to non-expert proteomics laboratories. An enhanced version, E4technology, also opens new avenues to sample preparation for low input and/or low-cell proteomics analysis. The technologies represent a breakthrough innovation in biomedical science, and we anticipate widespread adoption by the proteomics community.
Abstract: HotSpot Therapeutics, Inc. is pioneering the discovery and development of a new class of allosteric drugs that target certain naturally occurring pockets on proteins called “natural hotspots”. These pockets are decisive in controlling a protein’s cellular function, and we believe they have significant potential for new drug discovery by enabling the systematic design of potent and selective small molecules with novel pharmacology.
We present our implementation of microflow LC, Q-TOF-MS and Zeno MS/MS for routine intact protein analysis, label-free PTM characterization, and isobaric tag-based proteomic profiling. To maximize throughput and to minimize downtime, all protein and proteomic workflows are carried out on the same trap-elute LC system and with a single ionization source. LC-MS complements our suite of biophysical, biochemical and modeling tools for the in vitro characterization of protein-ligand binding. Furthermore, when coupled with structure-based design of chemical probes, microflow LC and Zeno-MS/MS enabled the characterization of target engagement in live cells with performance comparable to nanoLC-MS3 and produced physiologically relevant information that expedited hit-to-lead progression in our drug discovery efforts.
Robin H.J. Kemperman, PhD
Sr. Mass Spectrometrist
Children’s Hospital of Philadelphia
Bio
Dr. Robin Kemperman received his Bachelor’s in chemistry from the HAN University of Applied Sciences in The Netherlands. Thereafter, he fulfilled his MSc. and PhD in analytical chemistry at the University of Florida. Currently, he works at the Children’s Hospital of Philadelphia as a Sr. Mass Spectrometrist in the Metabolic and Advanced Diagnostics Lab. Dr. Kemperman’s work has covered a variety of aspects in mass spectrometry, including targeted analysis of steroids and ketone bodies using LC-MS/MS, in addition to bile acids, opioids, and glycan isomer separations using ion mobility spectrometry. He also worked on high-resolution mass spectrometry performing lipidomics and isotopically enriched metabolomics studies. Dr. Kemperman is experienced in clinical MS-based validations and has presented his work at a variety of national and international meetings. Focusing on the future, he is interested in working on novel innovations for biomedical and clinical applications to improve workflows.
Abstract: Targeted molecular panels allow clinicians to track disease state(s) and/or therapeutic response(s). In the field of lab medicine, targeted panels utilize a variety of analytical methodologies, generating actionable results. These results are stored in patients’ electronic health records (EHR). For example, thyroid panels monitor thyroid status (euthyroid, thyrotoxicosis, etc.), while amino acid (AA) panels assess for inborn errors of metabolism (IEM) (Maple Syrup Urine Disease (MSUD), Phenylketonuria (PKU) etc.). The modality of testing may be different, but the goals remain the same in both cases, i.e., to capture a molecular picture of a patient’s physiological status, and to rule-in or -out a disease state. Clinical chemistry labs today are taking advantage of track automation, using it across multiple stages, from sample receiving to sample storage. However, for more advanced assays, such as those using mass spectrometry (MS), more advanced workflows are required due to the complex nature of the sample pre-processing steps.
In the pharmaceutical industry, scientists use targeted panels to gain insights into the drug development and/or manufacturing processes. The molecular lens now shifts towards identifying quality attributes (QAs) or critical quality attributes (CQAs). These are molecules that provide an indication of ‘asset’ quality during the molecule-to-medicine pipeline. An ‘asset’ in the pharmaceutical industry often refers to a large molecule, such as an antibody and/or oligonucleotide, which has the potential to become a new medicine. Multiple attribute monitoring (MAM) of QAs, or, in generalist terms, targeted omics, is turning towards automated workflows.
These workflows operate from bioreactor sampling through to MS detection and are designed to monitor the lifecycle of an ‘asset’ using high-resolution (HR) instrumentation, such as HRMS.
This session will discuss targeted omics, including automation possibilities in an ‘at-line’ and an ’online’ workflow. Attendees will understand how the pharmaceutical industry is leveraging automation workflows to evaluate automated walk-up platforms for monitoring QAs; and, how such practices could be useful in other fields, such as clinical diagnostics. By the end of the session, attendees should be able to:
1. Understand both clinical and pharmaceutical targeted omics practices and terminologies
2. Identify the possibilities for implementing automation into a workflow
3. Think critically about the future of analytical testing/monitoring
Mass Spectrometry Imaging (MSI) is a powerful technology that allows scientists to visualize the spatial distribution of molecules such as biomarkers and metabolites. Here I will describe our efforts to create tools for MSI analysis guided by principles of open-access and ease of use, starting with an R Shiny app called MSI.EAGLE. This app was developed using the R Shiny web application framework and builds on top of the Cardinal package for R. This is designed to be an open-source, flexible tool to implement new methods while also being easy to use for researchers with diverse backgrounds and skill sets. MSI.EAGLE has a modular structure that makes it easy to customize and collaborate on its development. It features a user-friendly interface that allows researchers to perform tasks such as segmentation using Uniform Manifold Approximation Projection (UMAP), background segmentation/removal from tissues, and phenotype assignment based on periodic frequencies of pixels in x/y or based on manual parameters.
I will describe a specific application of MSI.EAGLE in a workflow for custom micro-well surface design suitable for desorption electrospray ionization (DESI-MS). This application serves to address a demand for cheap and rapid mass spectrometry testing of biofluids. The workflow consists of three steps: customizing PARAFILM surfaces using 3D printed molds; spotting samples using high-throughput robotics on the Opentrons platform; and analyzing data using MSI.EAGLE. This system allows researchers to access custom surface design workflows and perform high-throughput analyses in a cost-effective manner.
Infrared (IR) spectra of gas-phase ions provide detailed fingerprints that are sensitive to the minutest differences in molecular structure and hence can easily distinguish between isomeric species. Although practiced in many academic research laboratories, gas-phase IR spectroscopy has not yet found its way into the world of analytical mass spectrometry. There are at least two obvious reasons for this: (1) the addition of a spectroscopic dimension to an analytical measurement has typically taken tens of minutes for each species, making it poorly suited to high-throughput analysis; and (2) the complex, expensive lasers required have made spectroscopic measurements impractical for biomedical research.
We have overcome these problems in an approach that combines ultrahighresolution SLIM-based ion mobility, cryogenic IR spectroscopy, and mass in a single instrument. By increasing sensitivity and implementing a multiplexing approach to spectral measurement, we can measure an IR fingerprint spectrum of a molecule in as little as 10 seconds. Moreover, we do this using a simple, user-friendly, fiber-pumped IR laser no larger than a shoebox.
After demonstrating the capabilities of our technique, this talk will focus on its application in distinguishing isomeric glycans and glycan-related metabolites. We also have developed schemes to generate IR reference spectra starting from a relatively small number of simple, readily available standards from which we can grow a database for more complex species.
Accurate quantitation of intracellular phosphorylated analbolites from nucleotide analogs (NA) was critical to understand NA drug exposure and efficacy. Strategies for selective and sensitive LC-MS/MS assay development, robust PBMC collection and effective analyte stabilization were discussed through a case study.
P-GSK1 is a novel pro-drug that is designed to extend the half-life of the drug GSK1 for HIV treatment. GSK1 is metabolized intracellularly to form the mono-, di- and the active tri-phosphate (GSK1-MP, GSK1-DP and GSK1-TP) anabolites. A single analytical method to quantify both di and tri-phosphate anabolites were required but method development encountered many analytical challenges. A chemical derivatization with 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide (EDC) and hexylamine was used to reduce the polarity of the analytes and enables direct analysis on reversed phased LC-MS/MS. Extensive efforts were spent to optimize the assay and minimize the analyte loss during PBMC isolation, processing, lysis, and storage. Treatment of PBMC with 30/70/2 (v/v/v) RPMI-1640/methanol/trichloroacetic acid was found effective for analyte stabilization and recovery. Methods were developed for simultaneous analysis of GSK1-DP and GSK1-TP over the ranges of 2-2,000 ng/mL in dog and rat PBMC to support preclinical studies.
The assay was later optimized for the analysis of GSK1-TP over the range of 0.1-100 ng/mL in human PBMC to support a First Time in Human study. All three assays were found to be precise and accurate and matrix effect experiments indicated that the analysis of GSK1-TP and GSK1-DP was not affected by the lysed cell concentration of PBMC over the range of 1-25×106 lysed cells/mL. Robust and reliable PBMC isolation, counting and process procedures were explored. The analyte stock, matrix, bench-top, long term, freeze/thaw and processed extract stability were systematically evaluated and proved to be stable.
Per- and Polyfluoroalkyl Substances (PFAS) have been linked to a wide range of health concerns including delayed metacognition and behavioral problems in children, impaired kidney function and kidney cancer, thyroid disease and thyroid cancers, testicular cancer, ulcerative colitis, and obesity and lipid dysregulation. There are thousands of different PFAS chemicals in the environment, and the proportion of PFAS not measured in common approaches to known PFAS commonly measured has increased over the last two decades. To understand the prevalence, fate and transport, and health impacts of these PFAS not commonly screened non-targeted mass spectrometry must be deployed. The bottleneck in non-targeted mass spectrometry is filtering, annotating the tens to thousands of detectable PFAS, and distinguishing PFAS from the tens of thousands of other chemical signals. For this purpose we have released the FluoroMatch Suite, an open-source vendor neutral platform covering the entire non-targeted PFAS workflow. In this talk we will introduce the software, and applications to dried blood spots, leachate, waste water, and mice.
Small molecule biomarkers are a critical component of the drug discovery process, enabling understanding of the non-genetic factors that influence biological processes, disease progression, and drug responsiveness. To date, however, systematic discovery of small molecule biomarkers has been limited by bioanalytical constraints that preclude assessment of the thousands of circulating factors on a population scale.
In this session, Sapient will discuss its next-generation mass spectrometry-based platform that can assay >11,000 circulating factors per biosample in
About Sapient:
Sapient is an end-to-end biomarker discovery partner for pharmaceutical and biotechnology sponsors, providing solutions from large-scale untargeted discovery screening through development of targeted, quantitative CLIA assays to support drug programs at every phase. Our platform combines advanced mass spectrometry technologies – able to assay >11,000 molecules per biosample – computational learning, and an expansive proprietary Human Biology Database of several hundred thousand biosamples to discover circulating biomarkers at unprecedented speed and scale, and rapidly deliver actionable insights that align patients, disease biology, and specific therapies.
Native-like ions are generated using electrospray ionization of proteins, nucleic acids, lipids, and other biological molecules in aqueous solutions. These gas-phase ions can retain noncovalent interactions that were present in the original solution, and consequently, native ion mobility (IM) mass spectrometry (MS) has great potential for answering many questions in biophysics and structural biology that have eluded condensed-phased strategies. I will report new technologies that my lab developed to probe the structures and interactions of proteins. I will then discuss how my lab has applied these technologies to answer questions related to ubiquitin-mediated protein degradation.
Protein glycosylation is important yet understudied with important roles in biology and disease. Aberrant glycosylation is a well-known feature of cancer, however relatively little is known about the specific proteins and biological pathways affected by these modifications in tumor initiation, progression, and metastasis. Recent developments in mass spectrometry have enabled intact glycopeptides to be analyzed, thereby retaining information about the site and type of glycosylation on a protein. We have been developing and applying novel glycoproteomic analysis workflows for the analysis of a variety of human tissue and fluid samples. Our methodology includes a variety of different methods for glycopeptide enrichment to make samples more amenable for mass spectrometry-based glycopeptide analysis. Examples from various sample types and cancers will be shown and potential hints to underlying biology will be discussed.
Intact protein analysis provides proteoform-specific understanding of biological phenomena that cannot be achieved by analysis of digested peptides. However, top-down analysis is complicated by incomplete protein separation, low fragmentation efficiency, slow spectral acquisition rate, low S/N, and high spectral complexity. These effects limit proteoform detection and characterization and grow exponentially worse as mass increases. The 21 Tesla FT-ICR mass spectrometer at the National High Magnetic Field Laboratory (NHMFL) offers high mass resolving power, mass accuracy, dynamic range, and scan rate, and achieves unprecedented performance with respect to intact protein sequence analysis. The 21 T is part of the NHMFL FT-ICR User Facility and is available to all qualified users.
The instrument is equipped with an external quadrupole accumulator, which enables multiple fills of manipulated ions prior to high resolution mass analysis in the ICR cell. Multiple fills improve spectral signal-to-noise more rapidly than spectral averaging and facilitate acquisition of sequence-informative tandem mass spectra (MS/MS) on a chromatographic time-scale. Available fragmentation techniques include ETD, CID, beam-CAD, IRMPD and UVPD, which combine to produce hundreds of fragment ions for sequence determination and characterization of PTMs.
This talk will provide performance benchmarks of the 21 T FT-ICR mass spectrometer for characterization of intact proteins and highlight results from ongoing top-down proteomics projects. Recent efforts have focused on enabling new ion manipulation strategies prior to FTMS. For example, we have enabled chimeric ion loading, high resolution SWIFT ion isolation, proton transfer reactions (PTR) and parallel ion parking (PIP). Use of PTR reactions, when coupled with PIP, combine the majority of the initial protein charge state distribution into just a few charge states. This increases S/N, which enables observation of proteoforms that are not observed if PTR/PIP is not employed. The techniques described facilitate rapid identification of intact proteins and extend the mass range available for top-down proteomics applications.
Proteomics as a discipline has steadily matured over the past 25+ years. More recently, proteomics is enjoying a renaissance of sorts with wide adoption and embrace of various methodologies that include reagent-based profiling approaches (antibodies / aptamers-based profiling techniques) in addition to mass spectrometry. Like all technologies, mass spectrometry based proteomics has been through it’s own Gartner hype cycle over the past ~25 years. As LC-MS platforms and technologies have matured we are certainly on the plateau of productivity and continue to rapidly build on the successes.
Even with this advances the discipline is still not quite as mature as genomics. There are still barriers (technical, training & others) that curtail the wide adoption across the biological and biopharma research continuum. However, the significant value proteomics investigations bring when performed with appropriate rigor is undeniable.
The objective of this presentation is to share how transformative technological leaps in LC-MS and robust deep learning data analytics pipelines when coupled with experimental scale / rigor provides a vigorous framework to deliver “just-in-time” actionable insights to drug discovery & translational research. The technological advances are awe inspiring in and of themselves. However, coupling these advances to address complex questions and generate new hypotheses at the intersection of disease pathophysiology & biopharma research brings into focus the indelible impact of proteomics.
Borrowing from the famous quote by Winston Churchill … “…but it is perhaps the end of the beginning” of what is possible with Proteomics.
The presentation is intended to demonstrate recent mass spectrometry experiments designed to facilitate chemical analysis in resource-limited settings. Science-in-reverse encourages technological developments that consider conditions in underserved communities. In our approach, we combine new levels of simplicity, modest cost, and a centralized detection strategy for accurate disease detection. I will focus on two technological advancements: 1) panoptic mass spectrometry that enable the detection of all species in all states of matter and 2) mass spectrometry-based immunoassay platform for asymptomatic malaria detection in the developing world. The science-in-reverse approach is found useful to recruit and retain minorities in STEM.
Mass spectrometry, as the enabling tool for proteomics, is well-established to provide primary structure on proteins, revolutionizing protein science. Our interest is a higher-order structure. David Hambly of my lab developed a free-radical footprinting approach we term “fast photochemical oxidation of proteins” or FPOP. FPOP provides fast, microsecond labeling of proteins. Its speed allows reports on hidden conformations of proteins and on fast-folding. FPOP is also useful for mapping epitopes, following aggregation of proteins in neurodegeneration, and affinity measurements for signaling proteins. We are complementing FPOP by implementing extensions of hydrogen-deuterium exchange for reporting on pH changes, protein aggregation, and affinity. Both HDX and FPOP, when integrated with native MS and cross-linking make a compelling approach that is becoming known as “structural mass spectrometry.”
Imaging mass spectrometry is a powerful technology that enables the visualization of biochemical processes directly in tissues by combining the molecular specificity of mass spectrometry with the spatial fidelity of microscopic imaging. Modern imaging mass spectrometry studies are already stressing the limits of current analytical technologies and improvements in molecular specificity and sensitivity are crucial in order to answer increasingly complicated biological and clinical questions. Especially when studying lipids and metabolites, there are many isobaric and isomeric ions that complicate spectral analysis, with each isoform having a potentially unique cellular function. While traditional tandem mass spectrometry (MS/MS) approaches can distinguish amongst these compounds in select instances, this is often not the case. Additionally, the ion type most readily generated from tissue is rarely the type that affords the most chemical structural information upon MS/MS. Our group is developing gas-phase reactions that afford the ability to transform the ion type without manipulating the sample. While traditional analytical analyses oftentimes simply use the mass spectrometer as a detector of molecular mass, we instead use the mass spectrometer as a reaction vessel to perform unique gas-phase transformations to provide unparalleled levels of chemical resolution. These gas-phase transformations are fast, efficient, and specific, making them ideally suited for implementation into imaging mass spectrometry workflows to enable novel structural identification and separation based on chemical reactivity.
Recent developments in intelligent data acquisition strategies are leading the next generation of multiplexed proteome quantitation. Real-time peptide spectral matching enables superior quantitation and speed compared to canonical methods. Intelligent data acquisition strategies require millisecond time-scale informatics pipelines for real time decision making. These included spectral pre-processing, analysis, peptide spectral matching, and false discovery rate estimation for spectral filtering. In this work we present a first-of-its-kind, fast and robust informatics workflow that is capable of assigning peptide-level false discovery rates on a millisecond time scale with high fidelity to offline statistical methods. The millisecond informatics pipeline, Orbiter, was built in C# to support interfacing with the Thermo Fusion API for online instrument control. We applied the real-time search module within the Orbiter pipeline to analyze large sample cohorts in half the time as previously needed for canonical analyses. We used these more efficient analytical workflows to profile murine aging across ten tissues. Covering 200 samples and more than 11,000 proteins in just 18 days, RTS enabled the determination of quantitative profiles indicative of age-based protein changes in kidney, adipose tissue, and murine brain regions.
One of the biggest bottlenecks in modern drug discovery efforts is in tackling the undruggable proteome. Currently, over 85% of the proteome is still considered undruggable because most proteins lack well-defined binding pockets that can be functionally targeted with small molecules. Tackling the undruggable proteome necessitates innovative approaches for ligand discovery against undruggable proteins as well as the development of new therapeutic modalities to functionally manipulate proteins of interest. Chemoproteomic platforms, in particular activity-based protein profiling (ABPP), have arisen to tackle the undruggable proteome by using reactivity-based chemical probes and advanced quantitative mass spectrometry-based proteomic approaches to enable the discovery of “ligandable hotspots” or proteome-wide sites that can be targeted with small-molecule ligands. These sites can subsequently be pharmacologically targeted with covalent ligands to rapidly discover functional or nonfunctional binders against therapeutic proteins of interest. Chemoproteomic approaches have also revealed unique insights into ligandability such as the discovery of unique allosteric sites or intrinsically disordered regions of proteins that can be pharmacologically and selectively targeted for biological modulation and therapeutic benefit. Chemoproteomic platforms have also expanded the scope of emerging therapeutic modalities for targeted protein degradation and proteolysis-targeting chimeras (PROTACs) through the discovery of several new covalent E3 ligase recruiters. Looking into the future, chemoproteomic approaches will unquestionably have a major impact in further expansion of existing efforts toward proteome-wide ligandability mapping, targeted ligand discovery efforts against high-value undruggable therapeutic targets, further expansion of the scope of targeted protein degradation platforms, the discovery of new molecular glue scaffolds that enable unique modulation of protein function, and perhaps most excitingly the development of next-generation small-molecule induced-proximity-based therapeutic modalities that go beyond degradation. Exciting days lie ahead in this field as chemical biology becomes an increasingly major driver in drug discovery, and chemoproteomic approaches are sure to be a mainstay in developing next-generation therapeutics.
In this presentation, the author will discuss qualitative and quantitative aspects for different purposes using MS-based detection, and he’ll also describe QuEChERSER (quick, easy, cheap, effective, rugged, safe, efficient, and robust) concepts for highly streamlined and semi-automated analysis of a wide range of LC- and GC- amenable analytes in complex matrices, such as hemp.
Mass spectrometry may be used to qualitatively screen or identify chemicals in samples without providing quantitative information, but quantification of analytes without qualitative information can be worse than meaningless – it can be misleading. Thus, quantification in mass spectrometry could actually be called “quantidentification.” The degree of confidence in analyte identification needs to be fit-for-purpose for the stakes involved in the results. For regulatory purposes, different identification criteria have been established by different entities, such as the FDA/USDA, SANTE, Codex Alimentarius, et al. In a recent validation study using an “extract & inject” UHPLC-MS/MS method for 169 targeted drug residues in eggs, quantidentification results were compared using the criteria set by FDA Guidance to Industry Document #118, SANTE/12682/2019, and 2002/657/EC.
Furthermore, the use of 3 ion transitions per analyte (leading to 3 ion ratios) was compared with the use of 2 ion transitions (yielding only 1 ion ratio). The rates of false positives and negatives were similar independent of the identification criteria used, but the SANTE use of +/-30% relative ion ratio tolerance vs. the reference value was the simplest to implement in practice. Acquisition of 3 ion transitions per analyte led to 2-4 times lower rates of false negatives compared to 2 ion transitions without significantly affecting rates of false positives.
Over the last three to five years, Merck’s Biotransformation and Distribution group within the PPDM Department has invested in metabolite identification software and database solutions as well as label-free imaging capabilities with the goal of rapidly generating and disseminating data to drug discovery teams to facilitate program decisions. First, we developed a quantitative/qualitative (quan/qual) metabolic stability assay to aid new chemistry design by providing the rate of metabolism (quan) along with the site(s) of metabolism (qual). Here we describe our approach, partnership, and learnings towards efficiently and effectively executing a quan/qual assay for intrinsic clearance/ metabolite identification and use of the metabolic stability information to guide new chemical design. Second, we have expanded our label-free mass spectrometry imaging (MSI) capabilities, utilizing both MALDI-MSI, and dropletProbe MS surface analysis platforms. The current MSI platforms can perform tissue distribution analysis, on-tissue metabolite identification, and quantification. Herein, we present case studies highlighting the diverse applications of these tools in drug discovery programs, including renal toxicity elucidation, rapid on-tissue metabolite identification and whole-body drug localization. We envision these MS imaging platforms will allow us to provide efficient support and valuable impact across our active drug discovery pipeline.
Abstract:
High-Resolution Ion Mobility (HRIM) Mass Spectrometry based on SLIM is just around the corner. Employing HRIM-MS analysis for biotherapeutic characterization provides enhanced resolution of isomeric species and allows for significant increases in analytical throughput for routine assays like intact glycoform quantitation and peptide mapping. Comparisons and advantages of translating traditional LC-MS analyses to LC-IMS-MS workflows are demonstrated using the NIST RM 8671 (NISTmAb). Also discussed will be the advantages of using a flow injection (FIA)-HRIM-MS method for characterizing lipid isomer species.
Glycoproteins are implicated in many diseases including COVID19, HIV/AIDS, or cancer. Investigating how variations in glycans modulate the three-dimensional structure in a glycoprotein is crucial in designing potential antibody-based vaccines. However, structural analysis of glycoproteins by conventional biophysical methods such as NMR spectroscopy and crystallography are very challenging.
We developed, jointly with Bruker Daltonics, a tandem-trapped ion mobility spectrometer – mass spectrometer (tTIMS/MS), composed of two TIMS analyzers embedded in a ESI-QqTOF mass spectrometer. tTIMS/MS couples the ability of TIMS to retain native-like structures at high resolving powers with the ability to mobility-select and to energetically activate ions prior to conducting ion mobility measurement in the second TIMS analyzer. Additionally, ions with specific m/z range can be isolated in the quadrupole and activated in the collision cell, effectively allowing MS3 experiments of mobility- and m/z-selected ions.
This talk will discuss our progress on studying structures of glycoproteins and their complexes, with emphasis on the systems RNAse A/B and avidin. We show that tTIMS/MS retains native avidin tetramers with solvent adducts buried within binding interfaces/pockets. CID of avidin tetramers at high voltages in tTIMS generates compact monomers, dimers, and trimers, revealing the subunit topology. We identify various glycoforms and glycoform combinations in avidin monomers and oligomers. Finally, we perform top-down sequencing of mobility-selected tetrameric avidin by CID in tTIMS. Distinct avidin monomers generated by CID inside the tTIMS are then isolated in the quadrupole and exposed to a second ion activation /fragmentation stage in the collision cell. The obtained mass spectrum shows fragments of avidin base and attached N-glycans. Our results demonstrate the ability of tTIMS/MS to study the primary- and higher order structures of glycoprotein complexes. Further advances in glycoprotein structural studies employing an orthogonal configuration of tTIMS/MS is currently underway.
Speaker: Dr. Kristine Glunde
Dr. Glunde is Professor of Radiology, Oncology and Biological Chemistry at The Johns Hopkins University School of Medicine, and the inaugural Director of the Applied Imaging Mass Spectrometry (AIMS) Core. Her research program focuses on cancer biology and molecular imaging of cancer. Her lab combines molecular biology and cancer biology approaches with multi-scale molecular imaging to investigate and visualize molecular events that drive cancer growth, invasion, and metastasis. Imaging technologies used in Dr. Glunde's lab span magnetic resonance imaging, magnetic resonance spectroscopic imaging, mass spectrometry imaging, and optical and fluorescence imaging.
Mass spectrometry, as the enabling tool for proteomics, is well-established to provide primary structure on proteins, revolutionizing protein science. Our interest is higher order structure. David Hambly of my lab developed a free-radical footprinting approach we term “fast photochemical oxidation of proteins” or FPOP. FPOP provides fast, microsecond labeling of proteins. Its speed allows reports on hidden conformations of proteins and on fast folding. FPOP is also useful for mapping epitopes, following aggregation of proteins in neurodegeneration, and affinity measurements for signaling proteins. We are complementing FPOP by implementing extensions of hydrogen-deuterium exchange for reporting on pH changes, protein aggregation, and affinity. Both HDX and FPOP, when integrated with native MS and cross-linking make a compelling approach that is becoming known as “structural mass spectrometry.”
Untargeted metabolomics and lipidomics data provide exciting prospects for defining biological mechanisms and finding novel hypotheses and disease associations. For years, we have relied on accurate precursor masses and matching experimental to library MS/MS spectra. However, False Discovery Rates (FDR) for this classic method remain poorly studied. FDRs may possibly be much larger than anticipated. It is not easy to discern which adduct species was formed, at which (relative) retention time a compound should be found, and how many alternative isomers and isobar molecules should be considered. Ideally, FDR for MS/MS library matching would be complemented by ion mobility (CCS) information, genetic and biological literature data, and atlases of confirmed presence of compounds in a wide array of species, organs and cells. Current software does not facilitate the incorporation of these types of information, but integrated workflows are approaching possible solutions.
At the West Coast Metabolomics Center, metabolomic and lipidomic data are acquired for over 30,000 samples per year (25% less in 2020 due to covid19). We have published 19 databases and software packages to assist in structural characterizations, including MassBank.us with more than 650,000 public MS/MS spectra. Here, we show how these packages were employed on a regular basis by identifying more than 1,000 metabolites in typical specimen such as blood, urine, microbiome GI tract or brain samples.
(1) After classic MS/MS library matching, NIST hybrid search yields chemical class information on all compounds that did not have direct hits in experimental or in-silico MS/MS libraries. (2) We have developed "Entropy Similarity" as measure for MS/MS matching that improves FDR over classic dot-product similarity matching and that outperforms 40 further MS/MS similarity algorithms. (3) We have published retention time libraries for both HILIC and RP liquid chromatography methods for more than 1,000 metabolite standards. We used these data to develop retention time prediction algorithms by Machine Learning and deployed the retip.app for use by the community. For plasma metabolomics we found a 26% reduction in the number of false-positive compound annotations, along with a 21% improvement in the true-positive identification rate. (4) Using exhaustive literaturetext mining, we found a total of 42,000 chemicals reported in blood, published in the BloodExposome.org database. For brain metabolites and brain lipids, we published atlas.metabolomics.us as hub for more than 1,700 identified compounds in 10 mouse brain sections from 3 to 59 week old mice. Both databases can be used as a-priori information to boost the confidence in compound identification by LC-MS/MS. (5) For remaining unknowns of biological interest we limit by chemical search space by the number of acidic protons in MS/MS spectra. Here, we used deuterium oxide and deuterated buffers to obtain complete H/D exchanged MS1 and MS/MS data. Isomers with incompatible numbers of acidic protons were excluded.
Additional information such as CCS data are already included in MS-DIAL vs4.0 software, while other information, especially the comparison of HDX to classic MS/MS spectra, is still investigated manually. We are working on a large cloud-based computational solution (LC-BinBase) that integrates these solutions in a seamless online database, specifically for standardized LC-MS/MS methods that use the same kits of internal standards and chromatographic parameters as established in our lab. With such unified solutions, the FDR problem might be finally enumerated, giving greater confidence in untargeted LC-MS/MS reports.
Transformative insights from a holistic approach at the systems level have great potential to elucidate disease mechanisms and to develop new therapeutic treatments for precision medicine. Proteomics is essential for deciphering how proteins interact as a system and for understanding the functions of cellular systems in human diseases. However, the unique characteristics of the human proteome, which include the large dynamic range of protein expression and the extreme complexity resulting from a plethora of post-translational modifications (PTMs) and sequence variations, make such analyses difficult. The top-down mass spectrometry (MS)-based proteomics, which is based on analysis of intact proteins, is arguably the most powerful method to comprehensively characterize proteoforms that arise from genetic variations, alternative splicing, and PTMs. My group has made significant advances in top-down MS for analysis of large intact proteins purified from complex biological samples including cell and tissue lysate as well as body fluids. Recently, we are employing a multi-pronged approach to address the challenges in top-down proteomics in a comprehensive manner by developing new MS-compatible surfactants for protein solubilization, novel materials and new strategies for multi-dimensional chromatography separation of proteins, novel nanomaterials for enrichment of low-abundance proteins, as well as a new comprehensive user-friendly software package, MASH Explorer for top-down proteomics. In this talk I will present our recent technology developments in top-down high-resolution mass spectrometry-based proteomics as well as its application to cardiac systems biology and precision medicine.
Key references:
· Tiambeng, T. N.; Roberts, D. S.; Brown, K.A.; Zhu, Y.; Chen, B.; Wu, Z.; Mitchell, S. D.; Guardado Alvarez, T.M.; Jin, Y.; Ge, Y. Nanoproteomics Enables proteoform-resolved analysis of low-abundance proteins in human serum, Nature Communications, 2020, 11, 1-12
· Wu, Z.; Roberts, D.S.; Melby, J.A.; Wenger, K.; Wetzel, M.; Gu, Y.; Ramanathan, S.G.; Bayne, E.F.; Liu, X.; Sun, R.; Ong, I.M.; McIlwain, S.J.; Ge, Y. MASH Explorer: A Universal Software Environment for Top-Down Proteomics, J. Proteome Res., 2020, Epub ahead of print. https://doi.org/10.1021/acs.jproteome.0c00469
· Brown, K; Tucholski, T; Eken, C; Knott, S; Zhu, Y; Jin, S; Ge, Y. High-throughput Proteomics Enabled by a Photocleavable Surfactant., Angew. Chem. Int. Ed. 2020, 132, 8406-8410.
· Brown, K. A.; Chen, B.; Guardado-Alvarez, T.; Lin, Z.; Hwang, L.; Ayaz-Guner, S.; Jin, S.; Ge, Y. A cleavable surfactant for top-down proteomics. Nature Methods, 2019, 16, 417-420.
· Chen, B.; Lin, Z.; Alpert, A. J.; Fu, C.; Zhang, Q.; Pritts, W. A.; Ge, Y. Online hydrophobic interaction chromatography-mass spectrometry for the analysis of intact monoclonal antibodies, Anal. Chem. 2018, 90, 7135-7138.
· Chen, B.; Brown, K.A.; Lin, Z.; Ge, Y. Top-down proteomics: ready for prime time? Anal. Chem. 2018, 90, 110-127.
· Hwang, L.; Ayaz-Guner, S.; Cai, W.; Gregorich Z. R.; Jin, S.; Ge, Y. Specific enrichment of phosphoproteins using functionalized multivalent nanoparticles, J. Am. Chem. Soc., 2015, 137, 2432-2435.
While top down mass spectrometry describes the direct analysis of intact proteins and their complexes via mass spectrometry, the term more generally denotes an approach to measurement that recognizes the value of retaining as much information as possible about a system prior to analysis. By avoiding proteolytic digestion, gene- and proteoform-specific identifications can be made – directly (i.e., avoiding the enigmatic protein inference problem). Notably, the top down philosophy is equally applicable to the level of protein-protein and protein-ligand interactions. A series of vignettes will focus on both modes of Top Down Proteomics – denatured and native. I will also describe how the community of practitioners, stakeholders and consumers of proteomics are growing, helped along by the Consortium for Top Down Proteomics (CTDPs, a not-for-profit based in Boston). The CTDPs has published six articles, established norms to make proteoforms “FAIR”, and accelerate the coming upgrade in quality of information streams emerging from ‘compositional’ proteomics. As a last item to socialize, a recent breakthrough in the detection of individual ions in orbitraps (joint work with the group of Mike Senko at Thermo Fisher Scientific) will be described. By more faithfully preserving post-translational modifications and non-covalent interaction throughout the measurement process, top down mass spectrometry is positioned to make basic and translational proteomics more efficient, particularly in the detection and assignment of function to proteoforms and their PTMs underlying human wellness and disease.Bio:Neil Kelleher is a transdisciplinary investigator who is making an impact in the field of proteomics (proteins) and the discovery of new antibiotics and anticancer molecules. He runs the Kelleher Research Group, which invents methods of understanding how human cells work at the molecular level, and Northwestern Proteomics, the leading lab in the world for the “top-down” proteomics approach to measuring proteins. In 2016, Kelleher delivered a TEDx talk about the Cell-Based Human Proteome Project, an effort to map one billion proteins throughout the human body; he is founding president of a worldwide research consortium aiming to actualize this project.Metrics & Research contributions (1999-2019):
Mass spectrometry has become the method of choice to study biological small molecules and proteomes in a global and unbiased manner. Yet, it still trails other omics technologies in terms of coverage, throughput and sensitivity. Building on trapped ion mobility spectrometry (TIMS), we have recently developed parallel accumulation - serial fragmentation (PASEF) which multiplies MS/MS acquisition rates without a loss in sensitivity, and therefore promises to overcome some of the above limitations (Meier et al., JPR 2015 and MCP 2018). This presentation will introduce the fundamentals of TIMS and PASEF, and highlight its application to proteomics and lipidomics of typical biological and clinical samples. We will give an outlook on how transferring the PASEF principle to data-independent acquisition (diaPASEF) has great potential to further improve sensitivity and data completeness. We conclude that PASEF is a valuable addition to the mass spectrometry toolbox, with a number of unique opportunities that are only beginning to be explored.
Mass spectrometry has long played a significant role in the discovery and development of pharmaceuticals. Initially, this was limited to the structural characterization of small molecules and their impurities. Dramatic advances in ionization technologies and analyzers now make it possible to perform detailed structural characterization of very large molecules, such as intact monoclonal antibodies. In small molecule drug discovery, mass spectrometry makes impactful contributions through all stages of the discovery pipeline, from target identification to candidate selection. As powerful as they are, however, most mass spectrometry techniques are too slow to make an impact in the earliest stages of drug discovery. From screening and profiling thousands to millions of molecules in a hit ID campaign to providing high content cellular readouts during lead optimization chemistry, the throughput of mass spectrometry has historically been insufficient to deliver data on a scale or at a pace necessary to make informed decisions in early discovery. Recent advances in high throughput mass spectrometry and multiplexing strategies have changed this. At GSK we have explored a number of novel strategies to increase the throughput of mass spectrometry-based experiments and used them to increase the impact of mass spectrometry such that it now contributes across all stages of the small molecule drug discovery critical path. Our experiences on this crowded, high speed ride are described.
Arguably, the highest calling for Mass Spectrometry is it's application in the clinical care of patients. Mass spectrometry incorporates the propensity to measure intrinsic properties of molecules (molecular weight, precursor and product ion mass transitions) and is considered a "direct" measure of an analyte. Fundamental clinical diagnosis that we must address with Mass spectrometry are "am I healthy?, what disease do I have?, am I taking the correct therapeutic?, taking too much or too little? and is my disease status improving?". These life altering questions require consideration to the following questions, "Are mass spectrometers truth machines?" and can we confidently say "mass spectrometry es sui generis"?
Abstract: Advances in sequencing technologies have revealed large heterogeneity on the genome and transcriptome level in tumors. However, it has often been difficult pinpoint which of the changes are important drivers of tumor growth. Proteomic technologies measuring the functional gene products directly have also improved rapidly, and they provide rich complementary information. The combined application of proteomics and genomicsto the understanding of tumor biology has the potential of driving innovative diagnostics and new treatments for cancer. I will discuss different strategies for the proteogenomic integration of data from tumors analyzed within The Cancer Genome Atlas (TCGA) and the Clinical Proteomics Tumor Analysis Consortium (CPTAC).
Abstract: Ambient mass spectrometry provides an attractive and high throughput means of generating chemical fingerprints of food products without sample preparation. Even without identification of specific molecular components, these chemical fingerprints can be used to train predictive models by means of various machine learning approaches. Analysis of subsequent samples can then provide "real time" classification of unknowns with a high level of accuracy. Rapid evaporative ionization mass spectrometry (REIMS) and direct analysis in real time (DART) are examples of two ambient approaches that can be employed for this purpose. Examples using these technologies will be described for applications in food authenticity and quality.
Abstract: This presentation comprises of two parts. In the first part, the applications of HDX-MS (hydrogen/deuterium exchange-mass spectrometry) are overviewed for the audience who are relatively new to the field. Examples of the applications include protein characterization for biosimilarity, protein-ligand interaction for classification of drug molecules, and protein-protein-interaction for epitope mapping. In the second part, methods to improve the resolution of HDX-MS data is discussed for more experienced HDX-MS practitioners. One way to improve the HDX-MS resolution is digestion by multiple enzymes. A combination of pepsin and fungus protease type XIII significantly improved the resolution of HDX-MS data compared with pepsin alone. Gas-phase fragmentation can also improve the resolution of HDX-MS data. Fragmentation of deuterated peptides by ETD (electron transfer dissociation) enabled to sub-localize the deuterium positions.
Abstract: This talk covers several topics which demonstrate the title claims.(1) The observation and the underlying mechanism by which reactions in small droplets are accelerated by orders of magnitude [1]. The mechanism of acceleration is addressed with the aid of experiments on levitated droplets [2] and it is shown that reactions at the interface are much faster than those in the bulk of the droplet. (2) The application of this acceleration phenomenon to high-throughput reaction screening and small-scale organic synthesis [3]. High throughput reaction screening has been automated so that chemical reactions, accelerated in DESI microdroplets, can be read at rates of over 2,000 unique reaction spots/hour so allowing exploration of high dimensional chemical reaction space. To accomplish this, the DESI-MS system was integrated with instrumentation for automated robotic pipetting, sample array transfer and a precision solvent delivery system. Data from this automated system facilitated optimization of synthetic routes to drug synthesis.[4] (3) Intraoperative brain cancer diagnostics in which DESI-MS is used in operating rooms for rapid tissue biopsy smear analysis to screen for diagnostic lipids and oncometabolites indicative of tumor type (e.g. glioma), grade and extent of tumor infiltration at surgical margins. [5] The fact that isocitrate dehydrogenase (IDH) mutation status can be determined, very rapidly and intraoperatively by DESI, offers new tumor management options that may impact extent of resection.[6] References: [1] Yan, et al. Angew. Chem. Int. Ed. 55 (2016) 12960-12972 [2] Li et al. Chem. Eur. J. 24 (2018) 7349 - 7353 [3] Wleklinski, et al. Chem. Sci. 9 (2018) 1647 - 1653 [4] Jaman, et al. Org. Process Res. Dev, (2019), DOI: 10.1021/acs.oprd.8b00387 [5] Pirro et al., PNAS, 114 (2017) 6700-6705 [6] Pu et al. Anal. Bioanal. Chem. (2019) DOI: 10.1007/s00216-019-01632-5
Abstract: The quantitation of therapeutic proteins by mass spectrometry often relies on the analysis of a surrogate peptide released by digestion of the original protein. Recent enhancements in instrumentation and sample preparation have enabled quantitation by detection of the intact molecule using MS. A comparison of three methods for quantitative analysis of therapeutic monoclonal antibodies including analysis after deglycosylation, after hinge digestion and at the fully intact antibody level will be presented. The optimized methodology provided sensitivity down to 0.1 μg/ml and a lower limit of quantitation of 0.5 μg/ml from a 30 μl sample volume. Application of this approach to a pharmacokinetic study compared with a conventional surrogate peptide and a ligand-binding assays provided consistent data with direct detection of the dosed molecule. The challenges of the intact mass based approach will be discussed and will highlight opportunities for further research.
Abstract: The presentation will review the industry-wide evolution of technologies and strategies in ADC bioanalysis. Different practices, rationales, and philosophies from different companies and at different times in the last decade will be compared and analyzed. The debate and current trend in strategies and a recommendation in choosing ADC analytes, assay platforms and assay DAR characteristics will be outlined. Stage specific and continuity of bioanalytical strategy and technology at different phrases of ADC development from Discovery to Development and submission are considered. The correlation of various technologies and platforms in ADC bioanalysis and regulatory perspectives will be discussed.
Abstract: Intrinsic nucleophiles abound but electrophiles are essentially absent among the common, proteinogenic amino acids, resulting in activity-based protein profiling (ABPP) probes that have historically targeted nucleophilic functionality2. However, by post-translational processing and binding of exogenous small molecules, proteins do incorporate and subsequently deploy more than ten classes of electrophiles for catalysis and other essential functions. At the current state of knowledge, electrophilic post-translational modifications (PTMs) are not generally predictable from primary structure, and untargeted proteomics approaches often fail to detect them. For these reasons, such species are almost certainly more prevalent than is currently appreciated. To delineate the scope of this other functional half of the proteome (the 'electrophilome'), we developed the first chemically unbiased de novo screen for protein-bound electrophiles. Using a set of probes containing reactive N-N/O nucleophiles, we detected hitherto undiscovered electrophiles in enzymes and non-enzymes that have been targets for design of drugs against Alzheimer's disease and cancer. Additionally, a previously unknown protein modification, an N-terminal glyoxylyl group formed from a cysteine residue, was found in an uncharacterized protein (human Secernin3) thought to use the encoded Cys as a nucleophile for a hydrolysis reaction. Discovery of this new species immediately raised three compelling questions that will be discussed in this seminar: (1) what novel function or reactivity does this electrophilic functional group impart to the mature Secernin3 protein (i.e., what does the glyoxylyl do?); (2) what enzyme machinery exists to install the novel PTM (i.e., how does it get there?); and (3) what other organisms and proteins/enzymes possess a glyoxylyl, and in what other reactions and pathways is it involved (i.e., where else is it and why?)? These discoveries will illuminate enzyme cofactors and other essential protein-bound modifications as druggable targets, thereby providing new strategies for therapeutic intervention in several human pathologies including cancer, neurodegenerative diseases and antibiotic-resistant bacterial infections.
Abstract: Untargeted metabolomics is a promising approach for reducing the significant attrition rate for discovering and developing drugs in the pharmaceutical industry. This review aims to highlight the practical decision-making value of untargeted metabolomics for the advancement of drug candidates in drug discovery/development including potentially identifying and validating novel therapeutic targets, creating alternative screening paradigms, facilitating the selection of specific and translational metabolite biomarkers, identifying metabolite signatures for the drug efficacy mechanism of action, and understanding potential drug-induced toxicity. The review provides an overview of the pharmaceutical process workflow to discover and develop new small molecule drugs followed by the metabolomics process workflow that is involved in conducting metabolomics studies. The pros and cons of the major components of the pharmaceutical and metabolomics workflows are reviewed and discussed. Finally, selected untargeted metabolomics literature examples, from primarily 2010 to 2016, are used to illustrate why, how, and where untargeted metabolomics can be integrated into the drug discovery/preclinical drug development process.
