Analytical Biochemistry

Coenzyme A is an essential cofactor synthesized from pantothenate, cysteine, and ATP, and is involved in numerous processes of cellular metabolism through its ability to carry activated acyl groups. Coenzyme A participates in catabolism of carbohydrate, fat and amino acids; biosynthesis of fatty acids, cholesterol and heme; and protein modification including acetylation and 4-phosphopantetheinylation. Despite CoAs critical functions, the regulation of CoA levels and the rate of CoA synthesis in different cell types and disease states are not well understood. One reason for this gap is that many acyl-CoA species are analytically challenging to measure due to factors including instability, poor ionization, and the wide range of biochemical properties conferred by different acyl chain lengths. In addition, most current methods do not support analysis of CoA isotopic labeling, which is required to quantify CoA synthesis rate or to measure absolute concentration using isotope-labeled internal standards. Here, we describe a method to quantify the concentration and isotopic labeling of total CoA, defined as the sum of CoASH plus all acyl-CoA species. Acyl-CoA species are hydrolyzed using sodium hydroxide to remove acyl chains, then CoA is derivatized on the thiol with N-ethylmaleimide (NEM). Following protein precipitation and solid phase extraction, samples are analyzed by liquid chromatography-mass spectrometry. This method is linear in a wide range that captures mouse tissue CoA levels, with accuracy within 15% error and precision below 15% relative standard deviation for both pure standards and tissue samples. We applied this method to measure total CoA concentration in five tissues from male and female mice, and total CoA synthesis rate in mouse liver via infusion of 13C-15N-pantothenate. Overall, this method offers a tractable approach to measure total CoA concentration and isotopic labeling to enable study of total CoA synthesis rates and concentrations in health and disease.

We have developed a fluorometric assay for detecting reductase activity in biological samples through 4-methoxy-1-naphthalenemethanol (MONOL-41) formation. The enzyme carbonyl reductase 1 (CBR1) and four members of the aldo-keto reductase (AKR) 1 family (AKR1A1, AKR1B1, AKR1B10, AKR1C3) were evaluated for their ability to reduce 4-methoxy-1-naphthaldehyde (MONAL-41). AKR1B1 and CBR1 followed Michaelis-Menten kinetics, whereas AKR1B10, AKR1A1, and AKR1C3 showed substrate inhibition above 10 {micro}M (70 {micro}M for AKR1C3). Among the tested enzymes, AKR1B10 displayed the highest catalytic efficiency in the absence of substrate inhibition. The MONOL-41 assay was compared with the standard NADPH-based method, showing improved sensitivity, robustness, and lower detection limits (0.77 {micro}g/mL vs. 1.49 {micro}g/mL). These results confirm its suitability for monitoring AKR1B10 activity. The assay was then applied to A549 cell extracts, which express multiple reductases. Activity decreased at substrate concentrations above 10 {micro}M, suggesting a predominant role of AKR1B10. Inhibition studies using tolrestat and high MONAL-41 concentrations indicated a limited contribution of CBR1 ([~]7-8%). Considering both catalytic efficiency and expression levels, AKR1B10 appears to be the main contributor to reductase activity in this model. In A549 living cells, MONAL-41 showed no cytotoxicity up to 50 {micro}M and enabled real-time monitoring due to its membrane permeability. However, oxidation by aldehyde dehydrogenases can generate MONOIC-41, which has similar spectral properties but a lower quantum yield, potentially affecting signal interpretation. Overall, this assay represents a sensitive and cost-effective tool for detecting reductase activity and screening inhibitors.

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.

Transcription factors (TFs) are master regulators of gene expression and control a wide range of cellular functions including embryonic development, signaling pathways, immune response, and differentiation. A tight regulation of gene expression is crucial during all stages of life and changes in the TF function can lead to developmental abnormalities, diseases such as cancer, or resistance to treatment. Therefore, TFs are a promising class of drug targets, and the techniques that would contribute to the development of TF modulators are critical. Electrophoretic Mobility Shift Assay (EMSA) has been a primary tool to verify protein-DNA interactions, where a fluorescent, biotin, or isotope end-labelled DNA probe is used to quantify binding. Such labeling techniques, however, can be costly, time consuming, possess safety hazard risks and require capital equipment for imaging. Here, we optimized a label-free, staining-based EMSA to characterize a potential drug target, homeodomain (HD) TF Pre-B-cell leukemia homeobox-1 (Pbx1) and its binding partner Homeobox A9 (HoxA9). Staining the polyacrylamide EMSA gel with a DNA intercalating green cyanine dye - SYBR safe - allowed the visualization of Pbx1 homeodomain interactions with DNA at nanomolar concentrations and enabled quantitative determination of protein-DNA apparent binding affinity in the sub-micromolar range. Furthermore, a ternary complex of homeodomains of Pbx1 with HoxA9 and the DNA was also visible in the assay. We have shown that the staining-based EMSA can be used to evaluate inhibitors of Pbx1 that block the interaction with DNA. We have further validated the data from our assay with fluorophore labeling-based EMSA. Overall, using HD transcription factors Pbx1 and HoxA9 as a model, we have optimized a reliable and cost-effective staining-based EMSA that enables the high-sensitivity visualization and quantitative evaluation of transcription factor-DNA complexes without the need for end-labeled DNA probes. The streamlined workflow could be readily adapted to other DNA-binding proteins to study their interactions with the DNA, inhibitors, and other proteins.

Advances in Electrostatic Linear Ion Trap (ELIT) Charge Detection Mass Spectrometry (CDMS) over the past 10 years have revolutionized its use for analyzing very high-molecular-weight species such as protein complexes, viral vectors, vaccines, viruses, and amyloid fibrils. Nonetheless, ELIT-based CDMS has remained confined to a small number of specialized instrumentation groups, predominantly in academia, where large and complex home-built instruments are operated by highly skilled scientists in dedicated facilities. In this report, we discuss the primary challenges addressed in the design of a benchtop ELIT-based CDMS instrument. We highlight key design aspects of the hardware, acquisition modes, and control software, and we present important performance metrics (mass range, resolution and sensitivity) demonstrated using samples representative of the technology's key application areas.

Botanical dietary supplements (like wheat, barley, teff, oats, white lupin, pumpkin seed, and chickpeas) may contain trace amounts of toxicants in addition to important micronutrients. Developing and validating a reliable protocol for the simultaneous quantification of Cu, Fe, Zn, Mo, Se, Mn, Pb, Al, Ni, and Cr using a PerkinElmer (NexIONTM2000 model) quadrupole ICP MS (including a He collision and reaction cell when needed) with closed vessel microwave digestion using (HNO3 + H2O2) was the aim of this study.The method was subsequently utilized in a sample survey, and the outcomes were evaluated against WHO/JECFA standards. From five study regions, twenty-seven farm-collected botanical powder samples representing seven species were acquired. To create one composite per species, field subsamples were cleaned, air dried, ground, and blended (nine subsamples per botanical: three grabs from each of three farms). HNO3/H2O2 was used to digest aliquots (0.250-0.500gm) in closed microwave containers. Internal standards, multi-point external calibration, procedural blanks, verified reference materials, matrix spikes, and duplicates were all used in ICP MSs multi-element quantitation. Method LODs/LOQs, accuracy (CRM recoveries), and precision (RSD) were calculated.The technique produced low LODs that were suitable for dietary evaluation (typical LOD ranges: Cu, Fe, Zn, Mn, Ni, Cr (0.001-0.01) mg/kg; Mo, Se, Pb, Al (0.002-0.05) mg/kg. For the majority of analytes, within-run RSDs were less than 5%, while CRM recoveries ranged from 88.9 to 110%. The concentrations of essential elements varied greatly (average mg/kg: Fe (280.7{+/-}25.6); Zn (6.0{+/-}0.541); Cu (2.8{+/-}0.269); Mn (398.3{+/-}23.8); {micro}gm/kg: Se (0.061{+/-}0.006); Mo (1.0 {+/-}0.022). Although some composites approached or exceeded conservative intake thresholds for Pb and Al under high consumption scenarios, toxic elements were generally low (mean mg/kg: Pb (0.062{+/-}0.007); Al(185.2{+/-}18.5); Ni(1.6{+/-}0.163); Cr(1.8{+/-}0.171).For the simultaneous nutritional and contaminant profiling of supplements derived from cereals and those not, the validated ICP- MS workflow with microwave HNO3 and H2O2 digestion is suitable. Accurate labeling and consumer safety can be supported by routine screening and supply chain controls.

Protein oligomerization equilibria are central to many biological processes and are often highly sensitive to environmental conditions such as ionic strength, pH, and ligand binding. Quantitative characterization of these equilibria remains experimentally challenging because stable protein complexes frequently dissociate only at concentrations that are difficult to access with conventional biophysical methods. Fluorescence correlation spectroscopy (FCS) is uniquely suited to this problem, as it provides direct access to diffusion coefficients of fluorescently labeled proteins at nanomolar concentrations. However, the quantitative interpretation of FCS data from oligomeric systems requires a rigorous mathematical framework and careful experimental practice that have not previously been described in sufficient detail to guide implementation. Here, we provide a comprehensive description of the experimental workflow and analytical framework for determining dissociation equilibrium constants by FCS, covering instrument calibration, sample preparation, data quality control, after-pulse correction, and nonlinear least-squares fitting. We discuss common sources of error and provide practical guidance on critical experimental considerations including surface passivation, buffer preparation, equilibration time, and the role of labeling efficiency. Using the homotrimeric sliding clamp PCNA as a model system, we demonstrate the complete workflow under a range of KCl concentrations and show that moderate ionic strength stabilizes the PCNA trimer while very high salt partially destabilizes the complex. The approach is general and applicable to any reversible protein self-association reaction accessible by fluorescence detection at low protein concentrations.

Chemical exchange saturation transfer (CEST) has become an indispensable NMR method to characterize slow exchange affecting biomacromolecules, especially for cases involving exchange between a major state and a minor state, the latter of which is often invisible in the spectrum. The CEST method is based on successive irradiation of selective regions of the NMR spectrum using a weak radiofrequency field, B1, while observing the effect on the visible major state when the B1 field saturates the invisible minor state. The need for selective saturation of narrow spectral regions has to date required acquisition of many tens of two-dimensional CEST spectra to sample the entire spectrum with sufficient resolution. Here we present the ACCEST method which measures an entire CEST profile from a single two-dimensional accordion-CEST spectrum plus a reference spectrum. ACCEST is based on the concept of accordion spectroscopy, where in the present implementation the carrier frequency of the weak saturating B1 field is stepped in synchrony with the dwell-time incrementation in the indirect dimension of the two-dimensional spectrum. We benchmarked ACCEST against conventional CEST, resulting in excellent agreement for both backbone 15N and methyl 13C CEST profiles. ACCEST offers substantial time savings that scale linearly with the number of spectra required in the corresponding conventional CEST experiment. Thus, ACCEST can dramatically speed up lengthy serial experiments, such as ligand titrations or temperature-dependent studies, and enable studies of non-equilibrium systems or samples with limited lifetimes.

1Sex steroid hormones are not exclusively localised in the circulation and can be found in numerous extragonadal tissues, in concentrations unrelated to the circulating fraction. Existing methodology to measure intramuscular steroid hormone concentrations includes both immune-based assays and liquid chromatography-mass spectrometry (LC-MS), the gold standard for hormone measurements. To date, no LC-MS based methods validation has been published on the measurement of intramuscular sex steroid hormones, despite clear biological relevance. Here, we describe the development and validation of a simple, high-throughput LC-MS Orbitrap method for the measurement of 10 intramuscular sex steroid hormones, including pregnenolone, progesterone, dehydroepiandrosterone, androstenedione, testosterone, epitestosterone, dihydrotestosterone, oestrone, oestradiol, and oestriol. In brief, isotope labelled standards were added to 5-6 milligrams of lyophilised muscle tissue, homogenised and extracted with ethyl acetate. The extracts were dried down and sequentially derivatised with 1-methylimidazole-2-sulfonyl chloride and hydroxylamine hydrochloride to target both the phenolic hydroxyl groups and ketone groups. The limit of detection was 1.0 {+/-} 1.0 pg/mg (range 0.36 - 3.26 pg/mg), with a R2 > 0.99 for all analytes. Matrix effects were 90-110% for all analytes except for dihydrotestosterone (143.6%), and precision was <10 CV% for all analytes in the presence of a muscle matrix. Our method allows for 20-40 samples to be prepared in [~]4 h, with a sample data acquisition time of 13 minutes. Moreover, our method provides the opportunity for specific analysis of steroid hormone concentrations in skeletal muscle, allowing target tissue specificity instead of relying on proxy measures from the circulation.

The catalytic rate constant (kcat) for product formation is considered a turnover number. Therefore, it is often mistakenly believed that kcat equals the turnover number and the number of substrate molecules changed per unit of time. Therefore, the aim of this study is to show that the rate constant for product synthesis and release is not always the same as the rate constant [Formula] for substrate utilization. To determine the precise substrate concentration at which these two rate constants are identical, it is appropriate to derive equations that allow the computation of [Formula]. In the end, the study will provide the most likely concentration of enzymes that can guarantee minimal or no recycling. An analysis of the literature on invertase (EC 3.2.1.26) and the Bernfeld method of generating Michaelian kinetic parameters for human salivary alpha-amylase (HSAA, EC 3.2.1.1) revealed that all kinetic parameters except [Formula] increased with substrate concentration. Meanwhile, the values for invertase decreased from 0.0697 to 0.0361/min, and the values for HSAA decreased from 5,802.4687 to 3,213.0124/min. The magnitude of [Formula] for each substrate concentration ([ST]) is not always equal, except when [ST] is determined post-assay by computation or extrapolation. The lower [ST] at which [Formula] and kcat for [HSAA] are equal is 3.667540128 g/L (5.682584642 M), which is similar to the molarity of HSAA (5.6101967709 M). The kcat for HSAA was 11,930.9885/min. Future assays should aim to generate large amounts of data for a robust statistical analysis. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=164 SRC="FIGDIR/small/728646v1_ufig1.gif" ALT="Figure 1"> View larger version (36K): org.highwire.dtl.DTLVardef@c49b65org.highwire.dtl.DTLVardef@1b60655org.highwire.dtl.DTLVardef@159ba67org.highwire.dtl.DTLVardef@1dce0af_HPS_FORMAT_FIGEXP M_FIG C_FIG

Proteins are dynamically regulated by a myriad of post-translational modifications (PTMs) that control their stability, conformation, activity, subcellular localization, and local interactions. Capturing the precise composition of these various modification states, or proteoforms, is a principal objective of top-down proteomics (TDP). By ionizing intact proteoforms and combining measurements of precursor ion and fragment ion masses, the position, stoichiometry, and combination of PTMs can be determined. Despite the highly valuable measurements that TDP can provide, it is typically less sensitive than corresponding peptide-level analysis with many reports utilizing input material in the microgram to milligram range. Contributing to this lack of sensitivity is the risk of sample loss due to non-specific binding to surfaces during sample preparation. The most widely employed sample preparation approaches for TDP either require high sample input (e.g. precipitation and ultra-filtration) or fail to effectively remove surfactants (e.g. solid-phase extraction). These limitations have hindered advancement of targeted TDP applications involving immunoprecipitation and other enrichment strategies. Bead-assisted protein aggregation, also referred to as single-pot, solid-phase-enhanced sample preparation (SP3), has emerged as a popular sample preparation strategy for bottom-up proteomic workflows, but has only been used in TDP with secondary ion exchange chromatography cleanup. We envisioned a magnetic bead based protein cleanup approach that proceeds directly to MS analysis with judicious choice of bead surface chemistry and elution conditions. Here we report a sample preparation method using hydroxyl-functionalized magnetic beads for top-down proteomics applications.

Comprehensive detection of steroids, beyond the limited panels typically analyzed in clinical chemistry laboratories, has become increasingly important given their pivotal roles in diverse biological processes. However, steroid quantification poses several analytical challenges, including differences in ionization efficiency and structural similarities across the entire steroid metabolic network. To address these challenges, we developed a targeted ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) assay to analyze 21 steroids using reverse-phase chromatography combined with rapid polarity switching. Mass spectrometry (MS) analysis was performed in scheduled multiple reaction monitoring (sMRM) mode. Depending on the steroid and matrix, the validated lower limits of quantitation (LLOQ) ranged from 12.0 pM to 1216 pM in plasma and 41.1 pM to 384 pM in fecal sample homogenates. In adipose tissue, it was from 0.01 pmol/g to 9 pmol/g. Measured steroid concentrations obtained from the commercial control samples (MassTrak Steroid Serum QC Set 1 and the MassCheck Steroid Panel 1 Serum Control) showed close agreement with the reference values. As a proof of concept, the method was successfully applied to 469 plasma samples in several projects, 15 adipose tissue samples, and 332 fecal samples, demonstrating its applicability to large-scale studies. In conclusion, the method enables sensitive, derivatization-free quantification of an expanded steroid panel in plasma and complex biological matrices, including adipose tissue and fecal samples, representing a significant advancement in comprehensive steroid profiling.

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.

We demonstrate the use of fluorescence correlation spectroscopy (FCS) to characterize fluorescently-labeled protein production. We use cell-free protein synthesis to express the protein YFP-CopB, a fusion of Chlamydia Outer Protein (Cop) B and Yellow Fluorescent Protein (YFP). CopB is a [~]50 kDa protein believed to have a critical role in chlamydial infection.1 After adding a plasmid encoding YFP-CopB to an E. coli cell-free lysate, protein expression begins. We track the cell-free reaction over several hours using the EI-FLEX, a commercial instrument with FCS capability. As protein is expressed over time, YFP-CopB increases in concentration, and the EI-FLEX detects an increase in fluorescent signal above the background of the cell-free lysate. The FCS data collected gives information about the size, aggregation tendencies, rates of production and fluorescent protein maturation, and concentration of the YFP-CopB produced. The use of FCS concurrent with cell-free synthesis presents a simple method to characterize proteins of interest as they are produced without the need for purification.

Fluorescence-based CRISPR diagnostic assays have become a popular platform for nucleic acid detection due to their programmability, configurability, specificity, and compatibility with standard laboratory equipment. However, reported enzymatic kinetic rates and limits of detection for CRISPR trans-cleavage assays vary by several orders of magnitude across the literature. This variation in performance parameters is coupled with and exacerbated by inconsistent calibration, incomplete correction of measurement biases, and nonstandardized or incomplete data-analysis procedures. We present an experimental protocol and quantitative analysis framework for fluorescence-based enzyme assays using routine laboratory instrumentation, including thermocyclers and fluorescence microplate readers. Building on previous studies of CRISPR enzyme kinetics and fluorescence calibration, we describe procedures for flat-field and background correction; comprehensive fluorescence calibration including correction for inner-filter-effect; quantification and implications of reporter degradation; extraction of Michaelis-Menten kinetic parameters; and determination of assay limits of detection. We provide step-by-step experimental guidelines and open-source Python implementations for each stage of the workflow. Using representative Cas12 trans-cleavage datasets, we demonstrate that explicit fluorescence calibration and correction procedures substantially reduce systematic bias in measured kinetic rates and improve consistency between experiments. Our framework aims to establish standardized practices for quantitative fluorescence-based CRISPR assays and provides researchers with practical tools for reproducible kinetic characterization and rational assay design.

Cystatin-C is an important renal function biomarker, and conventional quantification requires centralized laboratory analyzers, which limits timely testing in primary care and resource-limited settings. To address this need, we developed and validated a simple, rapid, and quantitative smartphone-based (SP) lateral flow immunoassay (LFIA) for measuring serum Cystatin-C. The SP-LFIA platform consists of a colorimetric LFIA strip and a custom SP reader with uniform LED illumination and macro lens for image capture. Quantitative image analysis of the colorimetric signal is performed by a dedicated application using a pre-defined third order polynomial calibration model. Following systematic optimization, the assay demonstrated a wide quantitative range of 0.32-8.00 mg/L, with a limit of detection of 0.15 mg/L. Analytical validation conducted according to CLSI guidelines showed excellent precision, with intra- and inter-assay coefficients of variation below 10%, and no significant interference from bilirubin, triglycerides, hemoglobin, or rheumatoid factor. Accelerated stability testing confirmed robust strip performance after storage at 50 {degrees}C for 28 days. Method comparison using 100 clinical serum samples showed high agreement with a commercial PETIA reference method (R{superscript 2} = 0.993) and minimal bias. These results indicate that the developed smartphone-based LFIA provides a reliable, cost-effective, and practical tool for point-of-care Cystatin-C monitoring.

Human milk contains structurally diverse glycans with key roles in shaping infant development, yet analytical constraints limit characterisation from low-volume samples. Glycosaminoglycans (GAGs), including chondroitin sulphate (CS), are understudied due to existing protocols requiring sample volumes of at least 5 mL and lengthy extraction steps prior to instrumental analysis. This study establishes a workflow for quantifying CS disaccharides from 25 {micro}L of human milk, enabling analysis of samples previously inaccessible to GAG profiling, such as those collected as salvage samples from neonatal intensive care units. For CS quantification, the CS is first enzymatically depolymerised using chondroitinase ABC to release repeating disaccharide units. Matrix complexity is reduced via two rounds of acetonitrile-based protein and lipid precipitation. Disaccharides are separated by hydrophilic interaction liquid chromatography and detected using a Triple Quadrupole Mass Spectrometer, providing robust sensitivity for all CS disaccharides. Method development and validation were performed using pooled mature human milk from term infants. This workflow facilitates detection of all CS disaccharides, with low but reproducible recoveries for total CS. Low- and high-level spike recoveries were 41.3% (RSDr 7.5%, RSDiR 15.9%) and 43.7% (RSDr 24.4%, RSDiR 27.9%), respectively. Despite modest absolute accuracy, precision remained sufficient to make relative comparison of CS concentrations between samples. This method expands the analytical toolkit for human milk glycomics, enabling same day preparation and CS profiling from sample volumes that are 200 times smaller than prior work, supporting future investigations into GAG-mediated functions in early life. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=134 SRC="FIGDIR/small/723732v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@176dffborg.highwire.dtl.DTLVardef@16ae4ccorg.highwire.dtl.DTLVardef@d333c2org.highwire.dtl.DTLVardef@1eb3216_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical abstractC_FLOATNO Schematic of sample preparation protocol 25 L of human milk is combined with lyase enzymes and TRIS buffer containing the internal standard prior to incubation. Samples then undergo multiple rounds of centrifugation and refrigeration before analysis via LC-MS/MS. Made using BioRender.com. Glycan nomenclature following Varki et al., 2015. C_FIG

Background: Mu-opioid receptors (MORs) are expressed throughout the body including in the brain and gastrointestinal (GI) tract. Total-body PET imaging of the brain and GI tract offers a promising approach for cross-sectional in vivo evaluation of the MOR brain-GI axis. However, intestinal motility and bladder filling introduce motion throughout the GI tract over the scan window. Here we establish analysis methodology to account for motion for dynamic imaging of the brain-GI axis, to further characterize peripheral MORs throughout the body and provide a framework for semi-automatic total-body PET modeling. Methods: 4 subjects underwent 90-min dynamic [11C]-carfentanil (cfn) total-body PET acquisitions at baseline, after intravenous naloxone (central antagonist) administration, and after orally administered loperamide (peripheral agonist and P-glycoprotein substrate). Thalamic MOR availability was measured using the Logan reference tissue model. Using CT-based segmentation, the GI tract was subdivided into anatomical segments, in addition to other peripheral organs (e.g., liver, psoas muscle). Frame-by-frame semi-automatic motion correction was performed with three distinct reference frames (11-14 min post-injection, p.i., 35-40 min p.i., and 85-90 min p.i.). The performance of these three were compared to manual correction. Compartment modeling and Logan graphical analysis were performed to estimate relevant kinetic parameters (K1, VT, VTLogan). Results: Across the 4 subjects and regions, kinetic parameter estimates were highly correlated (r>0.7) for K1, VT and VT Logan when comparing semi-automatic (reference frame at 35-40 min p.i.) and manual correction. With semi-automatic motion correction, graphical-based estimation of VTLogan in the gastrointestinal tract was significantly decreased with loperamide relative to baseline (p<0.05). As expected, naloxone decreased brain thalamic MOR availability but loperamide did not. Conclusions: With semi-automatic motion correction and [11C]-cfn total-body PET, pharmacologic perturbations of MOR brain-GI axis can be quantitatively characterized, reducing the burden of image analysis for these studies.

Capillary electrophoresis-mass spectrometry (CE-MS) offers unique analytical advantages for polar metabolite profiling but has remained underutilized in metabolomics relative to liquid chromatography-MS (LC-MS), in part due to challenges in managing migration time drift during data analysis. Here we introduce the use of indexed migration time (iMT) for easily managing this aspect of CE-MS data for metabolomics. Migration time indexing using a panel of stable isotope-labeled (SIL) amino acid reference standards, stored as an iRT database in Skyline, outperformed both uncorrected migration time and relative migration time (RMT) correction across three independent analytical batches spanning 90 samples from four biological matrices. The indexed migration time approach achieved sub-1% relative standard deviation (RSD) in migration index across batches, compared to up to [~]15% RSD for uncorrected migration times. Additionally, we evaluate the use of single-point external calibration in Skyline for the purposes of metabolite quantification from complex matrices in order to ease the burden of translational metabolite quantification from metabolomics using high-resolution mass spectrometry (HRMS). Single-point external calibration using a biological matrix-based calibrator was benchmarked against a 13-point linear calibration curve across a panel of amino acids; above 1 M, greater than 95% of back-calculated concentrations fell within {+/-}20% of multi-point calibration. Application of the complete workflow to plasma, serum, urine, and NIST Standard Reference Material (SRM)-1950 demonstrated low inter-batch variability by principal components analysis, broad metabolite coverage across 126 quantifiable analytes, and strong quantitative concordance (Deming slope = 0.862, pseudo-R2 = 0.994, n = 64 analytes) with an independent comprehensive reference dataset for NIST SRM-1950. Together, these results establish a practical mCE-HRMS metabolomics workflow that bridges targeted and discovery metabolomics paradigms and lays the groundwork for single-point external calibration as a powerful tool for translational metabolomics.

A multi-omic approach utilizing a single biospecimen is important to avoid intra-sample heterogeneity associated with testing multiple omic single-samples, and for more efficient use of small volumes of precious biopsies (<30 mg). This is especially true for the microanatomy of post-mortem human brain samples. Using post-mortem human brain biospecimens from the NIH NeuroBioBank, a penta-omic sequential extraction method is described, Simultaneous Metabolomic, Proteomic, Lipidomic - DNA, RNA Extraction (SiMPL-DREx). Each sequential omic extract was compared to those obtained by the gold standard single omic method. Preserving RIN is critical for brain and tissue banks, as it is a primary measure of tissue quality. For all five omic extracts, the tissue integrity numbers and omic profiles did not significantly differ from those obtained by the respective omic gold standard method. Unlike past multi-omic studies, this study quantified the relative solvent percentages and upstream losses for both the organic and aqueous phases, confirming an omics loss of under 5%.