The Analyst

Luminescence is a powerful method for detecting trace analytes and monitoring biological processes. However, most bioluminescence reagents, including luciferase and its substrates, are sensitive to temperature, limiting their useable shelf lives, and resulting in inconsistent performance. Enhancing the stability of these reagents could improve data quality, simplify workflows, and address cold chain storage issues. In this study, we demonstrate the application of the platform stabilization technology, capillary-assisted vitrification (CAV), as a tool to stabilize different luciferases and their substrates, and the application of the stabilized reagents in both in vitro and in vivo bioluminescent assays. We demonstrate that CAV-stabilized reagents can be stored and shipped ambiently, maintain consistent performance over time, and are suitable for use in cell viability quantification, tumor monitoring, in vivo imaging, microbial detection, and immunoassays. Additionally, different reagents can be co-formulated to make ready-to-use assay kits that can also be shipped and stored ambiently. Our results demonstrate that CAV stabilization is a viable alternative to traditional storage methods, with broad potential to improve bioluminescence workflows.

Efficient and reproducible protein extraction is a critical step in mass spectrometry-based proteomics workflows, particularly for complex host-pathogen systems where low-abundance immune-associated proteins are difficult to detect. Probe sonication methods used for cell lysis requiring mitigation of excessive heat generation, to prevent degradation of biologically important proteins, while also limiting throughput and potentially introducing sample-to-sample variability. In this study, we evaluated adaptive focused acoustics (AFA) technology as an alternative approach for macrophage lysis and protein extraction and digestion within a standard proteomics workflow coupled with mass spectrometry. We observed that AFA technology reduced hands-on processing times and overall workflow timelines and single-sample AFA technology improves proteome coverage, dynamic range, and reproducibility. We also evaluated multiplexed AFA technology for lysis, and we observed an exclusive macrophage proteome and influence on replicate reproducibility and dynamic range detection for low abundant proteins. Moreover, multiplexed AFA technology for macrophage lysis and digestion further increased protein identifications, replicate reproducibility, and dynamic range. Considering the AFA-exclusive proteome, 86 proteins were detected across all AFA-based lysis and digestion methods, including low-abundance proteins associated with macrophage homeostasis, inflammatory response, and transport. Together, these findings demonstrate that AFA technology enhances reproducibility, throughput, and proteome depth for macrophage protein extraction while enabling the detection of biologically relevant low-abundance immune-associated proteins. These improvements provide a strong foundation for future investigation of host-pathogen infection models, where pathogen-derived proteins remain challenging to detect within complex host proteomes.

Thermodynamic characterization of biomolecular interactions is essential for understanding the enthalpic and entropic driving forces of molecular recognition, but established label-free techniques are limited either by bulk refractive-index sensitivity or by the lengthy thermal equilibration required to suppress it. Here, we used focal molography to investigate the temperature-dependent binding of the protein kinase A regulatory subunit (PKA-R) to cyclic AMP (cAMP) derivatives and to derive apparent thermodynamic signatures from kinetic measurements. We first validated the diffractometric readout under conditions that challenge refractometric sensors: the coherent mass density channel strongly suppressed temperature-induced bulk refractive-index effects and resolved binding in 50% human serum despite measurable non-specific adsorption, reducing the need for lengthy equilibration and buffer matching. We then combined focal molography with DNA-directed immobilization (DDI), allowing five cAMP derivatives to be presented in parallel on the same multiplexed chip and followed across five temperatures. This format yielded distinct, internally consistent apparent thermodynamic fingerprints for each derivative, separating ligands with similar affinities by their enthalpic and entropic contributions. Together, these results establish focal molography with DDI as a multiplexed workflow for comparative thermodynamic fingerprinting of biomolecular interactions at higher throughput.

The pixel size of imaging mass spectrometry (IMS) is fundamentally limited by several factors, including the diameter of the incident probe and the raster step size of the sample stage. We have previously demonstrated that hydrogel-based tissue expansion, originally developed for microscopy (ExM), can also be adapted for imaging mass spectrometry to physically magnify the size of the tissue. Expansion imaging mass spectrometry (ExIMS) uses a superabsorbent hydrogel to isotropically expand thin tissue sections, which can then be sampled via imaging mass spectrometry, resulting in improved effective spatial resolution. Separately, multimodal image fusion has been used to computationally upsample the effective spatial resolution in imaging mass spectrometry by predictively mapping mass spectrometric intensity values to the smaller diameter pixel sizes of a microscopy image of the same tissue section. Here, we present ExFusion, a unified workflow that combines these two approaches by computationally fusing structurally detailed fluorescent ExM and chemically detailed lipid ExIMS data obtained from the same 9.4-fold expanded mouse brain tissue. Following a 10-fold upsampling from image fusion, multimodal expansion image fusion enabled prediction of MS images at a [~]106 nm pixel size on a commercial mass spectrometer using a 10 m raster step size. At this resolution, lipids in the Purkinje cells of the cerebellum are clearly defined with intracellular distributions.

AO_SCPLOWBSTRACTC_SCPLOWHigh-resolution mass spectrometry is routinely used for the analysis of complex samples in pharmaceutical, environmental, and omics related studies. Such applications require instrumentation to be capable of combining sub-ppm mass accuracy, high resolving power, rapid full m/z range acquisition, and a wide dynamic range. Achieving these requirements simultaneously places constraints on analyzer design and performance. Multi-reflecting time-of-flight (MRT) based analyzers have been previously reported as a means of extending effective flight path length in compact TOF designs. Here, further instrument and functionality advances in a compact MRT mass spectrometer design are described and the impact of these enhancements is demonstrated for omics applications.

Native mass spectrometry (nMS) is well established for measuring protein masses and stoichiometries using nano-electrospray ionization (nESI), yet salt adduction and source activation energies can limit routine measurements. In this study, we benchmark submicron quartz nanopipette nESI emitters (<50 nm internal diameter) across three mass spectrometry platforms (quadrupole-time-of-flight, quadrupole-Orbitrap, and tribrid-Orbitrap platforms) and a wide protein mass range (17-800 kDa). We analysed holo-myoglobin (17 kDa) over a range of concentrations (10 M-10 nM) and capillary voltages to determine limits of detection and define a gentle operating regime. We additionally observe reduced Na+ adduction and preservation of the Zn2+-bound metalloproteoform of carbonic anhydrase II (29 kDa). Proteins and protein complexes spanning the mid-to-high mass range including ovalbumin ([~]44 kDa), malate dehydrogenase ([~]70 kDa), glutamate dehydrogenase ([~]350 kDa), {beta}-galactosidase ([~]465 kDa), and GroEL ([~]800 kDa), were readily detected using nanopipette emitters. Compared with conventional 1-2 m internal diameter borosilicate emitters, quartz nanopipettes provided higher signal-to-noise ratios and fewer adducts. Finally, direct analysis of clarified bacterial lysate expressing -synuclein yielded a clear monomeric charge-state distribution, demonstrating compatibility with complex biological matrices. Collectively, these results establish quartz nanopipette nESI as an instrument-portable, salt-tolerant approach suitable for routine nMS analysis across a broad range of protein molecular weights and sample complexities.

High content imaging is being applied to achieve quantitative fluorescence readouts in increasingly complex 3-dimensional (3D) cell culture models such as spheroids and organoids. Compared to conventional 2D assays, 3D assays better represent biological heterogeneity but require more complex sample preparation, 3D imaging and 3D image analysis that can affect the accuracy and precision of such assays. We used spheroids formed from the NRAS-activated melanoma cell line 19161 modified to express an ERK kinase translocation reporter (KTR) as an exemplar 3D phenotypic assay carried out in 96-well plates. The spheroids were treated with the ERK activator TPA and a range of concentrations of the MEK inhibitor Binimetinib. 3D live-cell imaging with sub-cellular spatial resolution was performed using a dual-view oblique plane microscope (dOPM) - a form of single-objective light-sheet microscope - and the experiment was performed separately at 4 different institutes. The results were analysed using an identical 3D analysis pipeline and parameters. We assessed the variation in assay readout using a linear mixed effects model. Random variance at the well level was negligible (SD = 0.0048 relative to range of KTR biosensor readout at reference site of 0.17), indicating low technical noise. Treatment effects were dose-dependent and highly statistically significant compared to DMSO control across all sites (Dunnett-corrected p < 0.001). The range in KTR readout between the minimum (3.5 M Binimetinib) and maximum (100 nM TPA) treatments varied between 59 to 96% relative to the reference site. Measured bias in KTR readout between sites was between 6 and 12% of the range of the reference site. This study quantifies the reproducibility of a 3D live spheroid-based assay employing a fluorescence biosensor requiring readout out at the per-cell level using the dOPM platform and discusses areas where experimental protocol could be improved in the future to further improve reproducibility.

Fluorescence correlation spectroscopy (FCS) provides valuable information about molecular dynamics, however, experimental setup typically requires labour-intensive passivation to prevent non-specific binding of molecules to sample containers. Furthermore, precious samples can be wasted by having to use relatively high sample volumes in existing sample containers. We overcome these major issues using a simple method of sample encapsulation into water-in-oil droplets, using purified proteins and cell lysates as proof-of-concept. FCS of fluorescently labelled protein samples in the nanomolar (nM) range confirmed that water-in-oil droplets yield more accurate measurements than conventional open-chamber methods. We first optimized the droplet composition to prevent protein coating at the water-oil interface using pegylated-lipids. We then utilized FCS to accurately measure protein concentrations and diffusion speeds in nanolitre volumes. Additionally, we used fluorescence cross-correlation spectroscopy (FCCS) to measure enzymatic cleavage of substrate inside our droplet system, demonstrating the capacity of this platform to measure biological processes at the nanoscale. Overall, conducting FCS in droplets offers a cost-effective, robust, and accessible alternative for measuring molecular dynamics, with promising potential for high-throughput and resource-limited applications. TOC Image + Text O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=37 SRC="FIGDIR/small/734730v1_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@e0023dorg.highwire.dtl.DTLVardef@b32cb0org.highwire.dtl.DTLVardef@13ad832org.highwire.dtl.DTLVardef@47dc12_HPS_FORMAT_FIGEXP M_FIG C_FIG Conventional single-molecule fluorescence requires slow, expensive glass passivation procedures to prevent proteins adsorbing to surfaces. By encapsulating proteins in lipid-coated nanolitre water droplets, the passivation requirement is removed, enabling accurate measurement of protein dynamics in low nanolitre volumes. Water-in-oil droplets thus provide a passivation-free platform for fluorescence correlation spectroscopy.

Accurate determination of drug-to-antibody ratios (DARs) is essential for the development, quality control, and performance evaluation of antibody-drug conjugates (ADCs); yet conventional analytical approaches often require extensive sample preparation, long analysis time, and substantial sample consumption. The peak distribution of intact ADCs is highly complex due to inherent glycosylation heterogeneity and variable drug conjugation. By applying enzymatic digestion, ADC can be converted into smaller subunits or deglycosylated species, thereby significantly simplifying the mass spectral profile. This reduction in structural heterogeneity facilitates clearer peak assignment and enables more accurate and reliable DAR quantification. Herein, we report an ultrafast microdroplet digestion-mass spectrometry strategy for rapid DAR characterization of ADCs. Microdroplet enzymatic digestion of antibodies and ADCs occurs within microsecond-time scales during spray ionization, enabling direct online subunit analysis with minimal sample preparation. The method was validated using NIST monoclonal antibody (mAb) conjugated to ADC mimics spanning low to high DAR (0-14) ranges, Cetuximab-derived ADC mimics (DAR[~]5) with complex glycosylation, and the commercial ADC Kadcyla (DAR[~]3.5). Consistent DAR values were obtained across multiple enzymatic workflows (IdeS, EndoS2, and EndoF3) with good reproducibility (%CV typically <5%). This approach substantially reduces analysis time while maintaining analytical accuracy and structural specificity, providing a rapid, sensitive platform for high-throughput ADC characterization and process monitoring. Graphic Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=97 SRC="FIGDIR/small/729562v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@23145corg.highwire.dtl.DTLVardef@10ddd88org.highwire.dtl.DTLVardef@14b1370org.highwire.dtl.DTLVardef@1e94ad6_HPS_FORMAT_FIGEXP M_FIG C_FIG

N-glycolylneuraminic acid (Neu5Gc) has been repeatedly associated with human cancer, but reliable detection has remained elusive, generating controversy regarding its presence in human samples. To address this, matrix-matched calibration curves, which have been pioneered in proteomics and metabolomics for assessing changes in complex mixtures, were measured of released N-glycans at four orders of magnitude dynamic range in defined mixtures, systematically benchmarking Neu5Gc-containing N-glycan detection across multiple LC-MS platforms and sites. Orthogonally, the gold-standard analytical method, consisting of fluorescence detection of labelled monosaccharides separated by LC, was applied to the same samples, yielding absolute concentrations of Neu5Gc. LC-MS demonstrated an extended detection range of three or more orders of magnitude while retaining intact N-glycan measurement, improving assay specificity and enabling detection of the variety of Neu5Gc-bearing N-glycans. By combining orthogonal dimensions of evidence, including chromatographic separation, isotopic distribution matching, and composition-confirming MS/MS, LC-MS confidently resolved Neu5Gc signals from noise, even at low abundance. In comparison, DMB-LC-FLR was limited to two orders of magnitude dynamic range, insufficient for detection of Neu5Gc in commercially available pooled human sera. These findings strongly support that DMB-LC-FLR assay specificity and sensitivity are insufficient for Neu5Gc detection in human samples due to noise overwhelming the Neu5Gc signal. By establishing a reusable benchmarking framework for future glycomic studies, we aim to use LC-MS to improve the measurement of Neu5Gc in clinical samples.

Glycosaminoglycans (GAGs) are linear polysaccharides with essential roles in a myriad of biological processes. Despite their biological importance, methods to determine both spatial and compositional information is limited. Time-of-flight secondary ion mass spectrometry (ToF-SIMS) provides spatially resolved compositional information of biological molecules without enzymatic digestion or label incorporation, enabling unbiased analysis independent of enzyme or label selectivity, overcoming many current limitations in GAG analysis. Here, we present the identification and validation of GAG discriminatory ions from biological samples by comparison of spectra from purified GAGs and cells with genetically modified GAG biosynthetic pathways. Ions discriminatory of specific GAG sub-families are identified and related to GAG structural components. The analysis is applied to human induced pluripotent stem cells engineered to lack heparan sulphate (HS), where compensatory changes in GAG display that link to function were observed. Furthermore, the broad applicability and spatial resolution of the technique is highlighted through detection of a disease-induced reduction in HS within the individual glomeruli of diabetic mice.

Accurate biological sex estimation is a key objective in archaeological and bioanthropological research but remains challenging when skeletal remains are fragmented, juvenile, or poorly preserved. Paleoproteomics approaches based on the detection of sex-specific amelogenin peptides (AMELX/AMELY) have emerged as a powerful alternative to osteological and genetic methods. However, current workflows often lack standardized criteria for peptide-level confidence assessment, potentially affecting the reproducibility and reliability of sex assignments. In this study, I evaluated the impact of peptide-level confidence filtering on paleoproteomics-based sex estimation through the reanalysis of 164 Homo sapiens individuals from 10 published datasets and 26 Bos taurus individuals from 3 datasets, spanning contexts from the Pleistocene to the present. To address methodological inconsistencies, I developed SexPeptID, an R/Shiny-based framework that integrates Posterior Error Probability (PEP) filtering, standardized peptide selection, and explicit uncertainty assessment. Application of SexPeptID revealed that peptide-level filtering substantially affects sex assignment outcomes: 17 previously classified males (10.4%) were reclassified as non-conclusive, while 5 individuals (3.1%) were identified as potentially female. Despite this sensitivity, AMELX/AMELY-based sex estimation remained robust overall, with stable signal ratios observed across archaeological periods. Variability in peptide intensities was primarily associated with dataset-specific factors rather than temporal differences, highlighting the influence of analytical workflows and preservation conditions. By incorporating confidence-based filtering and a non-conclusive classification category, SexPeptID improves the transparency, reproducibility, and reliability of palaeoproteomics sex estimation, providing a standardized framework for future archaeological and bioanthropological studies. HighlightsO_LISexPeptID provides a reproducible framework for amelogenin-based sex estimation. C_LIO_LIPeptide-level confidence filtering significantly affects paleoproteomics sex estimates. C_LIO_LI13.4% of published male assignments were revised after confidence filtering. C_LIO_LIAMELX/AMELY ratios show temporal stability from modern to Pleistocene samples. C_LIO_LIStandardized uncertainty assessment strengthens palaeoproteomics inference. C_LI

The chorioallantoic membrane (CAM) model represents a promising three-dimensional in vivo platform for preclinical drug testing in human tissues. In this study, we investigated whether the tissue penetration and distribution of benzbromarone, a known inhibitor of the Ca2+ activated chloride channel TMEM16A and potential therapeutic agent for autosomal dominant polycystic kidney disease (ADPKD), can be successfully visualized in human renal cyst tissue cultured on the CAM. To this end, desorption electrospray ionization mass spectrometry imaging (DESI-MSI) combined with an ultrahigh-resolution time-of-flight mass spectrometer was employed. We achieved spatially resolved molecular mapping of endogenous metabolites and lipids as well as the applied compound. MSI enabled clear differentiation between CAM and cystic tissue based on their distinct lipid profiles. Benzbromarone was reproducibly detected in the cyst specimens and exhibited selective accumulation along the cyst epithelium, which is considered the principal site of action. These observations were complemented by multivariate analyses including Uniform Manifold Approximation and Projection (UMAP), and sparse multinomial logistic zero-sum classification. The data-driven approach confirmed molecular differences between tissue types and allowed accurate classification of drug-treated and untreated regions. This study demonstrates that topically applied benzbromarone penetrates human renal cyst tissue in the CAM model and localizes to pharmacologically relevant tissue regions, notably the location of the Ca2+ activated chloride channel TMEM16A in the epithelial lining. The integration of high-resolution DESI-MSI with advanced statistical analysis provides a robust and label-free method to study drug distribution in human tissue grafts. Our findings contribute to the advancement of translational research in analytical chemistry and pharmacology.

In todays world, point-of-care nucleic acid detection still remains extensively constrained and limited by the heavy dependence on centralized urban instrumentation facilities and complex assay workflows. Here, we elucidate a glucometer-based analytical platform that enables label-free detection of nucleic acids and the nucleic acid amplification products through a simple redox-mediated mechanism. The approach leverages the potassium ferricyanide (K3[Fe(CN)6])/ potassium ferrocyanide (K4[Fe(CN)6]), redox system, which is intrinsic to commercial glucometers, complementing with interactions between methylene blue (MB) and nucleic acids. These interactions transduce concentration differences in nucleic acids into quantifiable electrochemical signal readouts. Distinct varied signal outputs are observed between single-stranded and double-stranded DNA, enabling the direct detection as well as integration with nucleic acid amplification tests (NAATs), including polymerase chain reaction, rolling circle amplification, and loop-mediated isothermal amplification. Optimization of reaction parameters and conditions leads to enhancement of the overall signal discrimination and sensitivity across various assay formats. This innovation repurposes widely available off-the-shelf glucometers as a low-cost, portable nucleic acid detectors, thus eliminating the need for any specialized instrumentation. Our results enumerate and establish a generalized and scalable strategy for nucleic acid sensing. The platform thus supports sustainable and environmentally responsible point-of-care testing, thereby enabling improved accessibility and public health monitoring at resource-limited and remote settings.

Sample preparation increasingly sets the throughput and reproducibility of mass spectrometry (MS)-based proteomics. StageTips (stop-and-go extraction tips) and variants thereof have long been common implements to purify samples, and we recently extended the concept to solid-phase extraction capture (SPEC) tips, in which the entire digestion takes place in sub-microliter volumes. Here we replace the hand-packed bed with a strong anion-exchange (SAX) monolith photopolymerized directly inside the pipette tip from a defined recipe (pSPEC). A liquid-handling robot casts 384 tunable tips in minutes, at low cost and in any format, adding negligibly to the workflows variance. Across biofluids, pSPEC added [~]20% more identifications than in-solution plasma and reached 3,500 protein groups from a single injection of healthy urine and 4,800 from saliva at 100 samples per day, depths usually requiring depletion or fractionation. The same light-cast chemistry should extend to single cells, affinity capture, and population-scale studies.

Volatile organic compounds (VOCs) in human breath have been explored as non-invasive biomarkers for disease, including respiratory infections and cancer, yet none are clinically validated. A major barrier is the difficulty of identifying and controlling confounding factors that affect volatile exhaled breath composition. A critical and overlooked confounder is the oral microbiome, which produces VOCs that can obscure the trace volatiles originating from the lower airways. To investigate this, we conducted an intervention study on sixteen healthy volunteers, using real-time breath analysis, which demonstrates that oral microbiota rapidly alter exhaled VOC profiles following a low-dose (0.5 g) oral glucose administration. Acetoin levels respond promptly to glucose, confirming its oral microbial origin. However, pathogenic bacteria resulting from respiratory infections can also produce acetoin, underscoring the challenge of distinguishing sources of breath VOCs. Similarly, other volatiles, such as acetic acid and ethanol, are also influenced by small glucose doses, complicating their use as biomarkers in non-targeted volatilomic studies. Recognising the metabolic context of each volatile is essential to distinguish infection signals from physiological background. Beyond serving as a cautionary note for exhaled breath research, these results may encourage the oral health and dentistry communities to adopt breathomics analytical tools for rapid chairside diagnostics, transforming respiratory confounders into clinical opportunities for dental care.

T cell exhaustion within the tumor microenvironment drives CD8+ T cells into a dysfunctional state characterized by progressive loss of proliferative capacity and effector functions, thereby limiting anti-tumor immunity and therapeutic efficacy. To investigate the biochemical alterations associated with exhaustion, an in vitro model of CD8+ T cell exhaustion was established through chronic antigenic stimulation of murine OT-1 CD8+ T cells. Phenotypic, functional, metabolic, and transcriptional characterization confirmed the acquisition of an exhausted state. Single-cell Raman spectroscopy was subsequently employed to generate biochemical signatures of activated, and exhausted CD8+ T cells. Principal component analysis (PCA) of the Raman spectral data revealed distinct separation of these two cell subsets, reflecting underlying biochemical differences associated with their functional states. Differential Raman spectral features corresponding to nucleic acids, carbohydrates, proteins, and lipids contributed significantly to this segregation, reflecting altered metabolic and biosynthetic states during exhaustion progression. Classification of the spectral data using machine-learning algorithms enabled accurate segregation of activated and exhausted T cells. Collectively, this study demonstrates that single-cell Raman spectroscopy can distinguish exhausted CD8+ T cells in a label-free and non-destructive manner, highlighting its potential as a platform for immune profiling and monitoring T cell dysfunction.

Understanding proteoforms, i.e., the various molecular forms in which proteins can exist, is important for deciphering biological processes and diseases. While capillary zone electrophoresis (CZE) proved advantageous for proteoform separation, limited sample loading capabilities restrict its application. Here, we present a novel comprehensive two-dimensional nanoLCxCZE-MS platform for deep top-down proteomics (TDP). The 2D platform is highly automated, enabling robust performance and the possibility to perform proteoform quantitation as demonstrated by isobaric labeling experiments. The high orthogonality of reversed-phase LC and CZE leads to a peak capacity of 2200, leading to an increase in the number of identified proteoforms in a human Caucasian colon adenocarcinoma cell lysate sample by a factor of 3 compared to nanoLC-MS. Furthermore, CZE mobilities enable the attribution of many more proteoforms to a certain proteoform family on the MS1-level. Overall, the flexible platform enables highly efficient separation of intact proteoforms combined with sensitive MS-based TDP workflows, both for untargeted and targeted analysis of complex biological samples. Graphical AbstractWe report a robust and automated comprehensive nanoLCxCZE-MS platform for top-down proteomics. In addition to large volume sample injection and separation by hydrophobicity in the nanoLC, the orthogonal separation by CZE in the second dimension leads to a strong increase in peak capacity and, thus, in the number of identified proteoforms. CZE mobilities also enable the attribution of many more proteoforms to a proteoform family on the MS1-level. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=46 SRC="FIGDIR/small/725123v1_ufig1.gif" ALT="Figure 1"> View larger version (11K): org.highwire.dtl.DTLVardef@df07b6org.highwire.dtl.DTLVardef@736d5corg.highwire.dtl.DTLVardef@10cef1org.highwire.dtl.DTLVardef@1825b55_HPS_FORMAT_FIGEXP M_FIG C_FIG

Members of the transforming growth factor-{beta} (TGF-{beta}) superfamily, including inhibins and activins, are structurally related glycoprotein dimers that regulate reproductive and endocrine signaling. Their high degree of molecular similarity presents challenges for label-free analytical discrimination. To evaluate the ability of Raman spectroscopy to distinguish closely related TGF-{beta} superfamily proteins based on intrinsic vibrational fingerprints. Raman spectra of recombinant human Inhibin -subunit, Inhibin B ({beta}B homodimer), and Activin A ({beta}A--{beta}A) were acquired using confocal Raman microscopy with 532 nm excitation. Spectra were baseline-corrected, area-normalized, and analysed using principal component analysis (PCA). Distinct spectral signatures were observed across the 500--1800 cm-1 region. Differences within the S--S stretching region (500--550 cm-1) were consistent with variations in disulfide-bond environments, with the Inhibin -subunit exhibiting the highest relative intensity in this region. Variations in the amide I band (1600--1700 cm-1) suggested differences in protein secondary structure, while aromatic amino acid vibrations provided additional discriminatory features. PCA revealed clear clustering and separation of all three protein classes based on their Raman fingerprints. Raman spectroscopy enables label-free differentiation of structurally related endocrine glycoproteins and demonstrates potential for the structural characterization and classification of inhibin and activin proteins within the TGF-{beta} superfamily.

Metabolomics enables the profiling of small-molecule metabolites and thereby captures the biochemical state of a living organism at a given moment and enables to monitor its cellular responses to stimuli. This technique has become a powerful tool in pharmaceutical research, the food industry, and microbial research. Metabolomics aims to obtain an unbiased metabolic profile; however, this is complicated by compound instability, complex and often extensive sample processing, and nonlinear responses in mass spectrometry. Therefore, correcting for metabolite loss and mass spectrometry-related artifacts is essential, typically achieved through relative quantification against an isotopically labelled internal standard for each metabolite of interest. This article describes how to produce 13C-labelled yeast extract and its use as internal standard for metabolomics. More specifically, it provides step-by-step protocols for the fed-batch fermentation, quenching, metabolite extraction, and LC-MS and GC-MS characterization of the internal standard. It also includes a protocol explaining how to use the internal standard for the quantification of metabolites in yeast samples.