Production of Isotopically Labeled KRAS4b.

Isotopically labelled proteins are important reagents in structural biology as well as in targeted drug development. The field continues to advance with complex multi-isotope labeling. We have combined our experience in high-level soluble KRAS4b expression with protocols for isotope incorporation, to achieve reliable and efficient approaches for several labeling strategies. Typical experiments achieve nearly 100% 15N incorporation, with yields in the range of 1.3-24.6 mg/L (median = 6.4 mg/L, n = 53). Improvements in the growth parameters in the presence of deuterium reduce the standard time of fermentation from 5 days to 3 days by modifying the medium used during the weaning process. The methods described are compatible with multi-isotope labeling and site-specific labeling.

Efficient palladium-catalyzed electrocarboxylation enables late-stage carbon isotope labelling.

Carbon isotope labelling of bioactive molecules is essential for accessing the pharmacokinetic and pharmacodynamic properties of new drug entities. Aryl carboxylic acids represent an important class of structural motifs ubiquitous in pharmaceutically active molecules and are ideal targets for the installation of a radioactive tag employing isotopically labelled CO2. However, direct isotope incorporation via the reported catalytic reductive carboxylation (CRC) of aryl electrophiles relies on excess CO2, which is incompatible with carbon-14 isotope incorporation. Furthermore, the application of some CRC reactions for late-stage carboxylation is limited because of the low tolerance of molecular complexity by the catalysts. Herein, we report the development of a practical and affordable Pd-catalysed electrocarboxylation setup. This approach enables the use of near-stoichiometric 14CO2 generated from the primary carbon-14 source Ba14CO3, facilitating late-stage and single-step carbon-14 labelling of pharmaceuticals and representative precursors. The proposed isotope-labelling protocol holds significant promise for immediate impact on drug development programmes.

Endogenous Production and Vibrational Analysis of Heavy-Isotope-Labeled Peptides from Cyanobacteria.

Stable isotope labeling is an extremely useful tool for characterizing the structure, tracing the metabolism, and imaging the distribution of natural products in living organisms using mass-sensitive measurement techniques. In this study, a cyanobacterium was cultured in 15 N/13 C-enriched media to endogenously produce labeled, bioactive oligopeptides. The extent of heavy isotope incorporation in these peptides was determined with LC-MS, while the overall extent of heavy isotope incorporation in whole cells was studied with nanoSIMS and AFM-IR. Up to 98 % heavy isotope incorporation was observed in labeled cells. Three of the most abundant peptides, microcystin-LR (MCLR), cyanopeptolin-A (CYPA), and aerucyclamide-A (ACAA), were isolated and further studied with Raman and FTIR spectroscopies and DFT calculations. This revealed several IR and Raman active vibrations associated with functional groups not common in ribosomal peptides, like diene, ester, thiazole, thiazoline, and oxazoline groups, which could be suitable for future vibrational imaging studies. More broadly, this study outlines a simple and relatively inexpensive method for producing heavy-labeled natural products. Manipulating the bacterial culture conditions by the addition of specific types and amounts of heavy-labeled nutrients provides an efficient means of producing heavy-labeled natural products for mass-sensitive imaging studies.

PyMIDA: A Graphical User Interface for Mass Isotopomer Distribution Analysis.

Mass isotopomer distribution analysis (MIDA) is an analytical technique that measures the synthesis rate of biological polymers using combinatorial probabilities and stable isotope labeling. Over the past few decades, this method has been developed and applied to a wide range of uses that have increased our understanding of metabolism and the etiology and monitoring of disease. There is currently no publicly available piece of software for performing MIDA calculations in a targeted manner without its functionality being limited to a specific use case. We present a cross-platform Python graphical user interface implementation for research to obtain kinetic parameters easily from stable-isotope labeling studies and provide the code and user manual on GitHub.

In-vivo tracking of deuterium metabolism in mouse organs using LC-MS/MS.

Mass spectrometry-based metabolomics with stable isotope labeling (SIL) is an established tool for sensitive and precise analyses of tissue metabolism, its flux, and pathway activities in diverse models of physiology and disease. Despite the simplicity and broad applicability of deuterium (2H)-labeled precursors for tracing metabolic pathways with minimal biological perturbations, they are rarely employed in LC-MS/MS-guided metabolomics. In this study, we have developed a LC-MS/MS-guided workflow to trace deuterium metabolism in mouse organs following 2H7 -glucose infusion. The workflow includes isotopically labeled glucose infusion, mouse organ isolation and metabolite extraction, zwitterion-based hydrophilic interaction liquid chromatography (HILIC) coupled to high-resolution tandem mass spectrometry, targeted data acquisition for sensitive detection of deuterated metabolites, a spectral library of over 400 metabolite standards, and multivariate data analysis with pathway mapping. The optimized method was validated for matrix effects, normalization, and quantification to provide both tissue metabolomics and tracking the in-vivo metabolic fate of deuterated glucose through key metabolic pathways. We quantified more than 100 metabolites in five major mouse organ tissues (liver, kidney, brain, brown adipose tissue, and heart). Furthermore, we mapped isotopologues of deuterated metabolites from glycolysis, tricarboxylic acid (TCA) cycle, and amino acid pathways, which are significant for studying both health and various diseases. This study will open new avenues in LC-MS based analysis of 2H-labeled tissue metabolism research in animal models and clinical settings.

Lipidome isotope labelling of gut microbes (LILGM): A method of discovering endogenous microbial lipids.

Lipidomics analysis of gut microbiome has become critical in recent surge of extensive human disease studies that investigate microbiome contributions. However, challenges remain in comprehending the origins of thousands of lipid species produced by the diverse microbes. Here, we proposed the development and utilization of a liquid chromatography-mass spectrometry-based approach, named lipidome isotope labelling of gut microbes (LILGM), which enables confident detection and identification of endogenous gut microbial lipidome via 13C/15N labeling strategy and high-resolution mass spectrometry. Our method leveraged in vitro microbial cultures and stable isotope-labeled 13C and 15N, allowing a reasonable degree of isotope incorporation into microbial lipids over short-term of inoculation. We then systematically detected the mass spectral patterns of 182 labeled lipid species by our in-house data analysis pipeline. Further bioinformatics analyses confidently identified biologically relevant microbial lipids from lipid classes such as diacylglycerols (DGs), fatty acids (FAs), phosphatidylglycerols (PGs), and phosphatidylethanolamines (PEs) that may have profound impacts to human physiology. Our study also demonstrated the application of LILGM by showcasing the confident detection of dysregulated microbial lipids post antibiotic perturbation. The debiased sparse partial correlation analysis provides insights into lipid metabolism intricacies. Overall, our method can provide unambiguous analyses to the endogenous microbial lipids in given biological context, and can also instantly reflect the lipidomic changes of gut microbes in response to environmental factors. We believe our LILGM approach has the potential to provide new body of knowledge by combining promising analytical approaches for sensitive and specific lipid detection to support functional microbiome studies.

Stable isotope labeling-based two-step derivatization strategy for analysis of Phosphopeptides.

Investigating site-specific protein phosphorylation remains a challenging task. The present study introduces a two-step chemical derivatization method for accurate identification of phosphopeptides. Methylamine neutralizes carboxyl groups, thus reducing the adsorption of non-phosphorylated peptides during enrichment, while dimethylamine offers a cost-effective reagent for stable isotope labeling of phosphorylation sites. The derivatization improves the mass spectra obtained through liquid chromatography-tandem mass spectrometry. The product ions at m/z 58.07 and 64.10 Da, resulting from dimethylamine-d0 and dimethylamine-d6 labeled phosphorylation sites respectively, can serve as report ions. Derivatized phosphopeptides from casein demonstrate enhanced ionization and formation of product ions, yielding a significant increase in the number of identifiable peptides. When using the parallel reaction monitoring technique, it is possible to distinguish isomeric phosphopeptides with the same amino acid sequence but different phosphorylation sites. By employing a proteomic software and screening the report ions, we identified 29 endogenous phosphopeptides in 10 µL of human saliva with high reliability. These findings indicate that the two-step derivatization strategy has great potential in site-specific phosphorylation and large-scale phosphoproteomics research. SIGNIFICANCE: There is a significant need to improve the accuracy of identifying phosphoproteins and phosphopeptides and analyzing them quantitatively. Several chemical derivatization techniques have been developed to label phosphorylation sites, thus enabling the identification and relative quantification of phosphopeptides. Nevertheless, these methods have limitations, such as incomplete conversion or the need for costly isotopic reagents. Building upon previous contributions, our study moves the field forward due to high efficiency in site-specific labeling, cost-effectiveness, improved sensitivity, and comprehensive product ion coverage. Using the two-step derivatization approach, we successfully identified 29 endogenous phosphopeptides in 10 µL of human saliva with high reliability. The outcomes underscore the possibility of the method for site-specific phosphorylation and large-scale phosphoproteomics investigations.

Triplex glycan quantification by metabolic labeling with isotopically labeled glucose in yeast.

Mass spectrometry-based approaches encompass a powerful collection of tools for the analysis biological molecules, including glycans and glycoconjugates. Unlike most traditional bioanalytical methods focusing on these molecules, mass spectrometry is especially suited for multiplexing, by utilizing stable-isotope labeling. Indeed, stable isotope-based multiplexing can be regarded as the gold-standard approach in reducing noise and uncertainty in quantitative mass spectrometry and quantitative analyses generally. The increasing sophistication and depth of biological questions being asked continue to challenge the practitioners of mass spectrometry method development. To understand the biological relevance of glycans, many stable isotope labeling-based mass spectrometry methods have been developed. Based on the duplex MILPIG (metabolic isotope labeling of polysaccharides with isotopic glucose), we establish here a novel triplex isotope labeling method using baker's yeast as the model system. Two differentially isotope-labeled glucoses (medium: 1-13C1 and heavy: 1,2-13C2), in addition to natural abundance glucose (light), were successfully used to label each monosaccharide ring in N-linked glycans in three different cell culture conditions, that, after sample mixing, resulted in a predictable triplet spectrum amenable for relative quantitation. We demonstrate excellent accuracy and precision of relative quantitation for a 1:1:1 mixture of glycans labeled in such a fashion. In addition, we applied triplex MILPIG to interrogate differential N-glycan profiles in tunicamycin-treated and control yeast cells and show that different N-glycans respond differently to tunicamycin.

Unraveling the potential of segment scan mass spectral acquisition for chemical isotope labeling LC-MS-based metabolome analysis: Performance assessment across different types of biological samples.

BACKGROUND: Chemical isotope labeling (CIL) LC-MS is a powerful tool for metabolome analysis with high metabolomic coverage and quantification accuracy. In CIL LC-MS, the overall metabolite detection efficiency using Orbitrap MS can be further improved by employing a segment scan method where the full m/z range is divided into multiple segments for spectral acquisition with a significant increase in the in-spectrum dynamic range. Considering the metabolic complexity in different types of biological samples (e.g., feces, urine, serum/plasma, cell/tissue extracts, saliva, etc.), we report the development and evaluation of the segment scan method for metabolome analysis of different sample types. RESULTS: It was found that sample complexity significantly influenced the performance of the segment scan method. In metabolically complex samples such as feces and urine, the method yielded a substantial increase (up to 94 %) in detected peak pairs or metabolites, compared to conventional full scan. Conversely, less complex samples like saliva exhibited more modest gains (approximately 25 %). Based on the observations, a 120-m/z segment scan method was determined as a routine approach for CIL LC-Orbitrap-MS-based metabolomics with good compatibility with different types of biological samples. For this method, a further investigation on relative quantification accuracy was done. The peak area ratios of 12C-/13-labeled metabolites were slightly reduced with 72%-84 % of peak pairs falling within the ±25 % range of the anticipated peak ratio of 1.0 among different samples, as opposed to 81%-90 % in the full scan, which was attributed to the inclusion of more low-abundance peak pairs within the narrow MS segments. However, the overall peak ratio measurement precision was not significantly affected by the segment scan. SIGNIFICANCE AND NOVELTY: The segment scan method was found to be useful for CIL LC-Orbitrap-MS-based metabolome analysis of different types of samples with significant improvement in metabolite detectability (25-94 % increase), compared to the conventional full scan method.

Reverse stable isotope labelling with Raman spectroscopy for microbial proteomics.

Global proteome changes in microbes affect the survival and overall production of commercially relevant metabolites through different bioprocesses. The existing methods to monitor proteome level changes are destructive in nature. Stable isotope probing (SIP) coupled with Raman spectroscopy is a relatively new approach for proteome analysis. However, applying this approach for monitoring changes in a large culture volume is not cost-effective. In this study, for the first time we are presenting a novel method of combining reverse SIP using 13 C-glucose and Deuterium to monitor the proteome changes through Raman spectroscopy. The findings of the study revealed visible changes (blue shifts) in proteome related peaks that can be used for monitoring proteome dynamics, that is, synthesis of nascent amino acids and its turnover with time in a non-destructive, cost-effective, and label-free manner.

Phosphoprotein dynamics of interacting T cells and tumor cells by HySic.

Functional interactions between cytotoxic T cells and tumor cells are central to anti-cancer immunity. However, our understanding of the proteins involved is limited. Here, we present HySic (hybrid quantification of stable isotope labeling by amino acids in cell culture [SILAC]-labeled interacting cells) as a method to quantify protein and phosphorylation dynamics between and within physically interacting cells. Using co-cultured T cells and tumor cells, we directly measure the proteome and phosphoproteome of engaged cells without the need for physical separation. We identify proteins whose abundance or activation status changes upon T cell:tumor cell interaction and validate our method with established signal transduction pathways including interferon γ (IFNγ) and tumor necrosis factor (TNF). Furthermore, we identify the RHO/RAC/PAK1 signaling pathway to be activated upon cell engagement and show that pharmacologic inhibition of PAK1 sensitizes tumor cells to T cell killing. Thus, HySic is a simple method to study rapid protein signaling dynamics in physically interacting cells that is easily extended to other biological systems.

An integrated workflow for quantitative analysis of the newly synthesized proteome.

The analysis of proteins that are newly synthesized upon a cellular perturbation can provide detailed insight into the proteomic response that is elicited by specific cues. This can be investigated by pulse-labeling of cells with clickable and stable-isotope-coded amino acids for the enrichment and mass spectrometric characterization of newly synthesized proteins (NSPs), however convoluted protocols prohibit their routine application. Here we report the optimization of multiple steps in sample preparation, mass spectrometry and data analysis, and we integrate them into a semi-automated workflow for the quantitative analysis of the newly synthesized proteome (QuaNPA). Reduced input requirements and data-independent acquisition (DIA) enable the analysis of triple-SILAC-labeled NSP samples, with enhanced throughput while featuring high quantitative accuracy. We apply QuaNPA to investigate the time-resolved cellular response to interferon-gamma (IFNg), observing rapid induction of targets 2 h after IFNg treatment. QuaNPA provides a powerful approach for large-scale investigation of NSPs to gain insight into complex cellular processes.

Diazo-carboxyl Click Derivatization Enables Sensitive Analysis of Carboxylic Acid Metabolites in Biosamples.

Carboxylic acids are central metabolites in bioenergetics, signal transduction, and post-translation protein regulation. However, the quantitative analysis of carboxylic acids as an indispensable part of metabolomics is prohibitively challenging, particularly in trace amounts of biosamples. Here we report a diazo-carboxyl/hydroxylamine-ketone double click derivatization method for the sensitive analysis of hydrophilic, low-molecular-weight carboxylic acids. In general, our method renders a 5- to 2000-fold higher response in mass spectrometry along with improved chromatographic separation. With this method, we presented the near-single-cell analysis of carboxylic acid metabolites in 10 mouse egg cells before and after fertilization. Malate, fumarate, and ß-hydroxybutyrate were found to decrease after fertilization. We also monitored the isotope labeling kinetics of carboxylic acids inside adherent cells cultured in 96-well plates during drug treatment. Finally, we applied this method to plasma or serum samples (5 µL) collected from mice and humans under pathological and physiological conditions. The double click derivatization method paves a way toward single-cell metabolomics and bedside diagnostics.

Investigating the Metabolism of Plants Germinated in Heavy Water, D2O, and H218O-Enriched Media Using High-Resolution Mass Spectrometry.

Mass spectrometry has been an essential technique for the investigation of the metabolic pathways of living organisms since its appearance at the beginning of the 20th century. Due to its capability to resolve isotopically labeled species, it can be applied together with stable isotope tracers to reveal the transformation of particular biologically relevant molecules. However, low-resolution techniques, which were used for decades, had limited capabilities for untargeted metabolomics, especially when a large number of compounds are labelled simultaneously. Such untargeted studies may provide new information about metabolism and can be performed with high-resolution mass spectrometry. Here, we demonstrate the capabilities of high-resolution mass spectrometry to obtain insights on the metabolism of a model plant, Lepidium sativum, germinated in D2O and H218O-enriched media. In particular, we demonstrated that in vivo labeling with heavy water helps to identify if a compound is being synthesized at a particular stage of germination or if it originates from seed content, and tandem mass spectrometry allows us to highlight the substructures with incorporated isotope labels. Additionally, we found in vivo labeling useful to distinguish between isomeric compounds with identical fragmentation patterns due to the differences in their formation rates that can be compared by the extent of heavy atom incorporation.

Glycan/Protein-Stable Isotope Labeling in Cell Culture for Enabling Concurrent Quantitative Glycomics/Proteomics/Glycoproteomics.

The complexity and heterogeneity of protein glycosylation present an analytical challenge to the studies of characterization and quantitation. Various LC-MS-based quantitation strategies have emerged in recent decades. Metabolic stable isotope labeling has been developed to enhance the accurate LC/MS-based quantitation between different cell lines. Stable isotope labeling by amino acids in a cell culture (SILAC) is the most widely used metabolic labeling method in proteomic analysis. However, it can only label the peptide backbone and is thus limited in glycomic studies. Here, we present a metabolic isotope labeling strategy, named GlyProSILC (Glycan Protein Stable Isotope Labeling in Cell Culture), that can label both the glycan motif and peptide backbone from the same batch of cells. It was performed by feeding cells with a heavy medium containing amide-15N-glutamine, 13C6-arginine (Arg6), and 13C6-15N2-lysine (Lys8). No significant change of cell line metabolism after GlyProSILC labeling was observed based on transcriptomic, glycomic, and proteomic data. The labeling conditions, labeling efficiency, and quantitation accuracy were investigated. After quantitation correction, we simultaneously quantified 62 N-glycans, 574 proteins, and 344 glycopeptides using the same batch of mixed 231BR/231 cell lines. So far, GlyProSILC provides an accurate and effective quantitation approach for glycomics, proteomics, and glycoproteomics in a cell culture system.

Optimization of a 1,4,7-Triazacyclononane-1,4-diacetic acid (NODA) Derivative Radiofluorination by Al18 F Complexation Using a Design of Experiments Approach.

Fluorine-18 (18 F) is the most favorable positron emitter for radiolabeling Positron Emission Tomography (PET) probes. However, conventional 18 F labeling through covalent C-F bond formation is challenging, involving multiple steps and stringent conditions unsuitable for sensitive biomolecular probes whose integrity may be altered. Over the past decade, an elegant new approach has been developed involving the coordination of an aluminum fluoride {Al18 F} species in aqueous media at a late-stage of the synthetic process. The objective of this study was to implement this method and to optimize radiolabeling efficiency using a Design of Experiments (DoE). To assess the impact of various experimental parameters on {Al18 F} incorporation, a pentadentate chelating agent NODA-MP-C4 was prepared as a model compound. This model carried a thiourea function present in the final conjugates resulting from the grafting of the chelating agent onto the probe. The formation of the radioactive complex Al18 F-NODA-MP-C4 was studied to achieve the highest radiochemical conversion. A complementary "cold" series study using the natural isotope 19 F was also conducted to guide the radiochemical operating conditions. Ultimately, Al18 F-NODA-MP-C4 was obtained with a reproducible and satisfactory radiochemical conversion of 79±3.5 % (n=5).

Methods for Radiolabeling Nanoparticles (Part 3): Therapeutic Use.

Following previously published systematic reviews on the diagnostic use of nanoparticles (NPs), in this manuscript, we report published methods for radiolabeling nanoparticles with therapeutic alpha-emitting, beta-emitting, or Auger's electron-emitting isotopes. After analyzing 234 papers, we found that different methods were used with the same isotope and the same type of nanoparticle. The most common type of nanoparticles used are the PLGA and PAMAM nanoparticles, and the most commonly used therapeutic isotope is 177Lu. Regarding labeling methods, the direct encapsulation of the isotope resulted in the most reliable and reproducible technique. Radiolabeled nanoparticles show promising results in metastatic breast and lung cancer, although this field of research needs more clinical studies, mainly on the comparison of nanoparticles with chemotherapy.

Increasing the coverage of the N-terminome with LysN amino terminal enrichment (LATE).

The field of N-terminomics has been advancing with the development of novel methods that provide a comprehensive and unbiased view of the N-terminome. Negative selection N-terminomics enables the identification of free and naturally modified protein N-termini. Here, we present a streamlined protocol that combines two negative selection N-terminomics methods, LATE and HYTANE, to increase N-terminome coverage by 1.5-fold compared to using a single methodology. Our protocol includes sample preparation and data analysis of both methods and can be applied to studying the N-terminome of diverse samples. The suggested approach enables researchers to achieve a more detailed and accurate understanding of the N-terminome.

Evaluating cPILOT Data toward Quality Control Implementation.

Multiplexing enables the monitoring of hundreds to thousands of proteins in quantitative proteomics analyses and increases sample throughput. In most mass-spectrometry-based proteomics workflows, multiplexing is achieved by labeling biological samples with heavy isotopes via precursor isotopic labeling or isobaric tagging. Enhanced multiplexing strategies, such as combined precursor isotopic labeling and isobaric tagging (cPILOT), combine multiple technologies to afford an even higher sample throughput. Critical to enhanced multiplexing analyses is ensuring that analytical performance is optimal and that missingness of sample channels is minimized. Automation of sample preparation steps and use of quality control (QC) metrics can be incorporated into multiplexing analyses and reduce the likelihood of missing information, thus maximizing the amount of usable quantitative data. Here, we implemented QC metrics previously developed in our laboratory to evaluate a 36-plex cPILOT experiment that encompassed 144 mouse samples of various tissue types, time points, genotypes, and biological replicates. The evaluation focuses on the use of a sample pool generated from all samples in the experiment to monitor the daily instrument performance and to provide a means for data normalization across sample batches. Our results show that tracking QC metrics enabled the quantification of ∼7000 proteins in each sample batch, of which ∼70% had minimal missing values across up to 36 sample channels. Implementation of QC metrics for future cPILOT studies as well as other enhanced multiplexing strategies will help yield high-quality data sets.

99mTc-linezolid as a radiotracer for brain abscess: Labeling, in silico docking, and biodistribution studies.

Brain abscess is a life-threatening condition that requires a timely and accurate diagnosis. In this study, linezolid, an oxazolidinone antibiotic, was labeled with technetium-99m according to the stannous chloride method. The labeling reaction factors were studied and optimized to achieve a high yield (97.4 ± 2.3%). The 99mTc-linezolid was radio- and physico-chemically characterized to assess its suitability as a radiopharmaceutical for the brain. In-silico docking to target peptidyltransferase showed an optimal binding fit (energy = -66.6 Kcal/mol). The complex was biologically evaluated in-vitro using binding assays in alive and heat-killed bacteria and in-vivo in an MRSA brain infection model. All results suggested that the labeled complex could potentially be a new nuclear imaging agent to diagnose and localize brain abscesses specifically.