Development of Spheroid-FPOP: An In-Cell Protein Footprinting Method for 3D Tumor Spheroids

Real-time monitoring and quantitative analysis of 3D tumor spheroids using portable cellular imaging system

Three-dimensional (3D) tumor spheroid models closely mimic in vivo tumor environment and play a vital role in studying oncological research. Despite their significance, the existing methods for analyzing 3D tumor spheroids often suffer from limitations, including low throughput, high cost, and insufficient resolution. To address these challenges, we developed a portable imaging system for the real-time sensing and quantitative analysis of the 3D tumor spheroids. The system integrated the seamless workflow of spheroid generation, cell morphology tracking, and drug screening. The spheroid generation was successfully characterized using MCF-7 breast cancer cells by optimizing cell concentration (5-20 × 106 cells/mL), incubation time (24-96 h) and microwell diameter (400-600 μm). A custom-written algorithm was developed for automated analysis of spheroids, exhibiting high sensitivity (98.99%) and specificity (98.21%). Confusion matrices and receiver operating characteristic curve analysis further confirmed the robustness of the algorithm with an area under the curve value of 93.75% and an equal error rate of 0.79%. Following the characterization, the real-time sensing of spheroid generation and the response of spheroids to drug treatment were successfully demonstrated. Furthermore, the live/dead assays with chemotherapy provided a detailed insight into the efficacy and cytotoxic effects of the drug, demonstrating a significant dose-dependent decrease in a spheroid viability. Therefore, our system offers considerable potential for enhancing drug development processes and personalized treatment strategies, thereby contributing to more effective cancer therapies.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13534-025-00470-y.

Recent Advances in Mass Spectrometry-Based Bottom-Up Proteomics

Mass spectrometry-based proteomics is about 35 years old, and recent progress appears to be speeding up across all subfields. In this review, we focus on advances over the last two years in select areas within bottom-up proteomics, including approaches to high-throughput experiments, data analysis using machine learning, drug discovery, glycoproteomics, extracellular vesicle proteomics, and structural proteomics.

Spatiotemporally Resolved Approach for Profiling Ferroptosis-Associated Metabolic Vulnerabilities in Tumors Using Mass Spectrometry Imaging and Stable Isotope Tracing

Ferroptosis, as an iron-dependent cell death mediated by lipid peroxidation, has sparked great interest in the tumor research community. Targeting ferroptosis has been proven to be a new therapeutic opportunity for inhibiting tumor growth. However, it is challenging to precisely characterize the metabolic pattern of ferroptosis in heterogeneous tumors and further identify ferroptosis-associated metabolic vulnerabilities for tumor treatment. In this work, we developed a spatiotemporally resolved method to image ferroptosis-associated metabolic alterations in 3D tumor spheroids by combining mass spectrometry imaging and stable isotope tracing techniques. The construction of a 3D tumor spheroid model allows for a more accurate simulation of ferroptosis, and the introduction of MALDI-MSI enables in situ screening of abnormal molecules in tumor tissues. Using this method, we showed that the expression proportion of nC═C = 4 polyunsaturated fatty acids, including arachidonic acid (FA-20:4) and adrenic acid (FA-22:4), were upregulated in RSL3-induced 3D tumor ferroptosis models. And the isotope tracing experiment revealed that the absorption of fatty acids and the biosynthesis of polyunsaturated fatty acids were significantly increased during ferroptosis. In addition, we discovered that arachidonic acid and adrenic acid supplementation render tumor cell sensitive to ferroptosis, thereby limiting the growth of tumor cells and the formation of 3D tumor spheroids. Such findings provide significant clues for understanding the metabolic signatures of tumor ferroptosis and raise the possibility to screen potential metabolic vulnerabilities for better tumor treatment in combination with ferroptosis.

Covalent Labeling Automated Data Analysis Platform for High Throughput in R (coADAPTr): A Proteome-Wide Data Analysis Platform for Covalent Labeling Experiments

Covalent labeling methods coupled to mass spectrometry have emerged in recent years for studying the higher order structure of proteins. Quantifying the extent of modification of proteins in multiple states (i.e., ligand free vs ligand-bound) can provide information on protein interaction sites and regions of conformational change. Though there are several software platforms that are used to quantify the extent of modification, the process can still be time-consuming, particularly for proteome-wide studies. Here, we present an open-source software for quantitation called Covalent labeling Automated Data Analysis Platform for high Throughput in R (coADAPTr). coADAPTr tackles the need for more efficient data analysis in covalent labeling mass spectrometry for techniques such as hydroxyl radical protein footprinting (HRPF). Traditional methods like Excel's Power Pivot (PP) are cumbersome and time-intensive, posing challenges for large-scale analyses. coADAPTr simplifies analysis by mimicking the functions used in the previous quantitation platform using PowerPivot in Microsoft Excel but with fewer steps, offering proteome-wide insights with enhanced graphical interpretations. Several features have been added to improve the fidelity and throughput compared to those of PowerPivot. These include filters to remove any duplicate data and the use of the arithmetic mean rather than the geometric mean for quantitation of the extent of modification. Validation studies confirm coADAPTr's accuracy and efficiency while processing data up to 200 times faster than conventional methods. Its open-source design and user-friendly interface make it accessible for researchers exploring intricate biological phenomena via HRPF and other covalent labeling MS methods. coADAPTr marks a significant leap in structural proteomics, providing a versatile and efficient platform for data interpretation. Its potential to transform the field lies in its seamless handling of proteome-wide data analyses, empowering researchers with a robust tool for deciphering complex structural biology data.

Enrichable Protein Footprinting for Structural Proteomics

Protein footprinting is a useful method for studying protein higher order structure and conformational changes induced by interactions with various ligands via addition of covalent modifications onto the protein. Compared to other methods that provide single amino acid-level structural resolution, such as cryo-EM, X-ray diffraction, and NMR, mass spectrometry (MS)-based methods can be advantageous as they require lower protein amounts and purity. As with other MS-based proteomic methods, such as post-translational modification analysis, enrichment techniques have proven necessary for both optimal sensitivity and sequence coverage when analyzing highly complex proteomes. Currently used reagents for footprinting via covalent labeling, such as hydroxyl radicals and carbodiimide-based methods, do not yet have a suitable enrichment method, limiting their applicability to whole proteome analysis. Here, we report a method for enrichable covalent labeling built upon the GEE/EDC system commonly used to covalently label aspartic acid and glutamic acid residues. Novel labeling reagents containing alkynyl functionality can be "clicked" to any azido-containing molecule with copper-catalyzed azide-alkyne cycloaddition (CuAAC), allowing for enrichment or further labeling. Multiple azide- and alkyne-containing GEE-like molecules were tested, and the most efficient method was determined to be the EDC-facilitated coupling of glycine propargyl amide (GPA) to proteins. The pipeline we report includes clicking via CuAAC to a commercially available biotin-azide containing a photocleavable linker, followed by enrichment using a streptavidin resin and subsequent cleavage under ultraviolet light. The enrichment process was optimized through the screening of clickable amines, coupling reagents, and enrichment scaffolds and methods with pure model proteins and has also been applied to complex mixtures of proteins isolated from the model plant, Arabidopsis thaliana, suggesting that our method may ultimately be used to measure protein conformation on a proteomic scale.

Metabolic adaptation in epithelial ovarian cancer metastasis

Epithelial ovarian cancer (EOC) is highly lethal due to its unique metastatic characteristics. EOC spheroids enter a non-proliferative state, with hypoxic cores and reduced oncogenic signaling, all of which contribute to tumour dormancy during metastasis. We investigated the metabolomic states of EOC cells progressing through the three steps to metastasis. Metabolomes of adherent, spheroid, and re-adherent cells were validated by isotopic metabolic flux analysis and mitochondrial functional assays to identify metabolic pathways that were previously unknown to promote EOC metastasis. Although spheroids were thought to exist in a dormant state, metabolomic analysis revealed an unexpected upregulation of energy production pathways in spheroids, accompanied by increased abundance of tricarboxylic acid (TCA) cycle and electron transport chain proteins. Tracing of 13C-labelled glucose and glutamine showed increased pyruvate carboxylation and decreased glutamine anaplerosis in spheroids. Increased reductive carboxylation suggests spheroids adjust redox homeostasis by shuttling cytosolic NADPH into mitochondria via isocitrate dehydrogenase. Indeed, we observed spheroids have increased respiratory capacity and mitochondrial ATP production. Relative to adherent cells, spheroids reduced serine consumption and metabolism, processes which were reversed upon spheroid re-adherence. The data reveal a distinct metabolism in EOC spheroids that enhances energy production by the mitochondria while maintaining a dormant state with respect to growth and proliferation. The findings advance our understanding of EOC metastasis and identify the TCA cycle and mitochondrional activity as novel targets to disrupt EOC metastasis, providing new approaches to treat advanced disease.

Radical Protein Footprinting in Mammalian Whole Blood

Hydroxyl Radical Protein Footprinting (HRPF) is a powerful method to probe the solvent-accessible surface area of proteins. It is mostly used to study the higher-order structure of proteins, as well as protein-protein and protein-carbohydrate interactions. Hydroxyl radicals are generated by the photolysis of hydrogen peroxide and these radicals modify the surface amino acids. Bottom-up proteomics is then applied and peptide oxidation is calculated and correlated with solvent accessibility. It is mainly performed in vitro; however, it has been recently used in living systems, including live cells, live nematodes, and 3D cell cultures. Mammalian tissues are still out of reach as they absorb UV strongly, hindering radical generation. Here, we describe the first example of RPF in mammalian stabilized whole blood. Using photoactivation of persulfate with a commercially available FOX Photolysis System modified for sample handling and inline mixing, we demonstrate the first labeling of proteins in whole blood. We demonstrate that the RPF protocol does not alter the blood cell gross morphology outside of a moderate hypertonicity equivalent to sodium chloride exposure prior to labeling. We detail an improved quenching protocol to limit background labeling in persulfate RPF. We describe the labeling of the top ten most abundant proteins in the blood. We demonstrate the equivalence of ex vivo labeling in whole blood with labeling of the same structure in vitro using hemoglobin as a test system. Overall, these results now open the possibility of performing RPF-based structural proteomics in pre-clinical models and using readily available clinical samples.

Lipidomics Profiling Reveals Differential Alterations after FAS Inhibition in 3D Colon Cancer Cell Culture Models

Cancerous cells synthesize most of their lipids de novo to keep up with their rapid growth and proliferation. Fatty acid synthase (FAS) is a key enzyme in the lipogenesis pathway that is upregulated in many cancers and has gained popularity as a druggable target of interest for cancer treatment. The first FAS inhibitor discovered, cerulenin, initially showed promise for chemotherapeutic purposes until it was observed that it had adverse side effects in mice. TVB-2640 (Denifanstat) is part of the newer generation of inhibitors. With multiple generations of FAS inhibitors being developed, it is vital to understand their distinct molecular downstream effects to elucidate potential interactions in the clinic. Here, we profile the lipidome of two different colorectal cancer (CRC) spheroids treated with a generation 1 inhibitor (cerulenin) or a generation 2 inhibitor (TVB-2640). We observe that the cerulenin causes drastic changes to the spheroid morphology as well as alterations to the lipid droplets found within CRC spheroids. TVB-2640 causes higher abundances of polyunsaturated fatty acids (PUFAs) whereas cerulenin causes a decreased abundance of PUFAs. The increase in PUFAs in TVB-2640 exposed spheroids indicates it is causing cells to die via a ferroptotic mechanism rather than a conventional apoptotic or necrotic mechanism.

The path forward for protein footprinting, covalent labeling, and mass spectrometry-based protein conformational analyses

Mass spectrometry-based approaches to assess protein conformation have become widely utilized due to their sensitivity, low sample requirements, and broad applicability to proteins regardless of size and environment. Their wide applicability and sensitivity also make these techniques suitable for the analysis of complex mixtures of proteins, and thus, they have been applied at the cell and even the simple organism levels. These works are impressive, but they predominately employ "bottom-up" workflows and require proteolytic digestion prior to analysis. Once digested, it is not possible to distinguish the proteoform from which any single peptide is derived and therefore, one cannot associate distal-in primary structure-concurrent post-translational modifications (PTMs) or covalent labels, as they would be found on separate peptides. Thus, analyses via bottom-up proteomics report the average PTM status and higher-order structure (HOS) of all existing proteoforms. Second, these works predominately employ promiscuous reagents to probe protein HOS. While this does lead to improved conformational resolution, the formation of many products can divide the signal associated with low-copy number proteins below signal-to-noise thresholds and complicate the bioinformatic analysis of these already challenging systems. In this perspective, I further detail these limitations and discuss the positives and negatives of top-down proteomics as an alternative.

Evaluating Mass Spectrometry-Based Hydroxyl Radical Protein Footprinting of a Benchtop Flash Oxidation System against a Synchrotron X-ray Beamline

Hydroxyl radical protein footprinting (HRPF) using synchrotron X-ray radiation (XFP) and mass spectrometry is a well-validated structural biology method that provides critical insights into macromolecular structural dynamics, such as determining binding sites, measuring affinity, and mapping epitopes. Numerous alternative sources for generating the hydroxyl radicals (•OH) needed for HRPF, such as laser photolysis and plasma irradiation, complement synchrotron-based HRPF, and a recently developed commercially available instrument based on flash lamp photolysis, the FOX system, enables access to laboratory benchtop HRPF. Here, we evaluate performing HRPF experiments in-house with a benchtop FOX instrument compared to synchrotron-based X-ray footprinting at the NSLS-II XFP beamline. Using lactate oxidase (LOx) as a model system, we carried out •OH labeling experiments using both instruments, followed by nanoLC-MS/MS bottom-up peptide mass mapping. Experiments were performed under high glucose concentrations to mimic the highly scavenging conditions present in biological buffers and human clinical samples, where less •OH are available for reaction with the biomolecule(s) of interest. The performance of the FOX and XFP HRPF methods was compared, and we found that tuning the •OH dosage enabled optimal labeling coverage for both setups under physiologically relevant highly scavenging conditions. Our study demonstrates the complementarity of FOX and XFP labeling approaches, demonstrating that benchtop instruments such as the FOX photolysis system can increase both the throughput and the accessibility of the HRPF technique.

Quantitative mass spectrometry imaging: therapeutics & biomolecules

Mass spectrometry imaging (MSI) has become increasingly utilized in the analysis of biological molecules. MSI grants the ability to spatially map thousands of molecules within one experimental run in a label-free manner. While MSI is considered by most to be a qualitative method, recent advancements in instrumentation, sample preparation, and development of standards has made quantitative MSI (qMSI) more common. In this feature article, we present a tailored review of recent advancements in qMSI of therapeutics and biomolecules such as lipids and peptides/proteins. We also provide detailed experimental considerations for conducting qMSI studies on biological samples, aiming to advance the methodology.

Systematic Fe(II)-EDTA Method of Dose-Dependent Hydroxyl Radical Generation for Protein Oxidative Footprinting

Correlating the structure and dynamics of proteins with biological function is critical to understanding normal and dysfunctional cellular mechanisms. We describe a quantitative method of hydroxyl radical generation via Fe(II)-ethylenediaminetetraacetic acid (EDTA)-catalyzed Fenton chemistry that provides ready access to protein oxidative footprinting using equipment commonly found in research and process control laboratories. Robust and reproducible dose-dependent oxidation of protein samples is observed and quantitated by mass spectrometry with as fine a single residue resolution. An oxidation analysis of lysozyme provides a readily accessible benchmark for our method. The efficacy of our oxidation method is demonstrated by mapping the interface of a RAS-monobody complex, the surface of the NIST mAb, and the interface between PRC2 complex components. These studies are executed using standard laboratory tools and a few pennies of reagents; the mass spectrometry analysis can be streamlined to map the protein structure with single amino acid residue resolution.

Dimethylthiourea as a Quencher in Hydroxyl Radical Protein Footprinting Experiments

Hydroxyl radical protein footprinting (HRPF) is a mass-spectrometry-based method for studying protein structures, interactions, conformations, and folding. This method is based on the irreversible labeling of solvent-exposed amino acid side chains by hydroxyl radicals. While catalase is commonly used as a quencher after the labeling of a protein by the hydroxyl radicals to efficiently remove the remaining hydrogen peroxide, it has some disadvantages. Catalase quenching adds a relatively high amount of protein to the sample, limiting the sensitivity of the method due to dynamic range issues and causing significant issues when dealing with more complex samples. We evaluated dimethylthiourea (DMTU) as a replacement for catalase in the quenching HRPF reactions. We observed that DMTU is highly effective at quenching HRPF oxidation. DMTU does not cause the background protein issues that catalase does, resulting in an increased number of protein identifications from complex mixtures. We recommend the replacement of catalase quenching with DMTU for all HRPF experiments.

Efficient Analysis of Proteome-Wide FPOP Data by FragPipe

Monitoring protein structure before and after environmental alterations (e.g., different cell states) can give insights into the role and function of proteins. Fast photochemical oxidation of proteins (FPOP) coupled with mass spectrometry (MS) allows for monitoring of structural rearrangements by exposing proteins to OH radicals that oxidize solvent-accessible residues, indicating protein regions undergoing movement. Some of the benefits of FPOP include high throughput and a lack of scrambling due to label irreversibility. However, the challenges of processing FPOP data have thus far limited its proteome-scale uses. Here, we present a computational workflow for fast and sensitive analysis of FPOP data sets. Our workflow, implemented as part of the FragPipe computational platform, combines the speed of the MSFragger search with a unique hybrid search method to restrict the large search space of FPOP modifications. Together, these features enable more than 10-fold faster FPOP searches that identify 150% more modified peptide spectra than previous methods. We hope this new workflow will increase the accessibility of FPOP to enable more protein structure and function relationships to be explored.

Proteomic and Phosphoproteomic Reprogramming in Epithelial Ovarian Cancer Metastasis

Epithelial ovarian cancer (EOC) is a high-risk cancer presenting with heterogeneous tumors. The high incidence of EOC metastasis from primary tumors to nearby tissues and organs is a major driver of EOC lethality. We used cellular models of spheroid formation and readherence to investigate cellular signaling dynamics in each step toward EOC metastasis. In our system, adherent cells model primary tumors, spheroid formation represents the initiation of metastatic spread, and readherent spheroid cells represent secondary tumors. Proteomic and phosphoproteomic analyses show that spheroid cells are hypoxic and show markers for cell cycle arrest. Aurora kinase B abundance and downstream substrate phosphorylation are significantly reduced in spheroids and readherent cells, explaining their cell cycle arrest phenotype. The proteome of readherent cells is most similar to spheroids, yet greater changes in the phosphoproteome show that spheroid cells stimulate Rho-associated kinase 1 (ROCK1)-mediated signaling, which controls cytoskeletal organization. In spheroids, we found significant phosphorylation of ROCK1 substrates that were reduced in both adherent and readherent cells. Application of the ROCK1-specific inhibitor Y-27632 to spheroids increased the rate of readherence and altered spheroid density. The data suggest ROCK1 inhibition increases EOC metastatic potential. We identified novel pathways controlled by Aurora kinase B and ROCK1 as major drivers of metastatic behavior in EOC cells. Our data show that phosphoproteomic reprogramming precedes proteomic changes that characterize spheroid readherence in EOC metastasis.

Efficient Analysis of Proteome-wide FPOP Data by FragPipe

Monitoring protein structure before and after perturbations can give insights into the role and function of proteins. Fast photochemical oxidation of proteins (FPOP) coupled with mass spectrometry (MS) allows monitoring of structural rearrangements by exposing proteins to OH radicals that oxidize solvent accessible residues, indicating protein regions undergoing movement. Some of the benefits of FPOP include high throughput and lack of scrambling due to label irreversibility. However, the challenges of processing FPOP data have thus far limited its proteome-scale uses. Here, we present a computational workflow for fast and sensitive analysis of FPOP datasets. Our workflow combines the speed of MSFragger search with a unique hybrid search method to restrict the large search space of FPOP modifications. Together, these features enable more than 10-fold faster FPOP searches that identify 50% more modified peptide spectra than previous methods. We hope this new workflow will increase the accessibility of FPOP to enable more protein structure and function relationships to be explored.