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Assignment of individual compound identifies within mixtures of thousands of metabolites in biological extracts is a major challenge for metabolomic technology. Mass spectrometry offers high sensitivity over a large dynamic range of abundances and molecular weights but is limited in its capacity to discriminate isobaric compounds. In this article, we have extended earlier studies using isotopic labeling for elemental composition elucidation (Rodgers, R. P.; Blumer, E. N.; Hendrickson, C. L.; Marshall, A. G. d. Am. Soc. Mass Spectrom. 2000, 11, 835-40) to limit the formulas consistent with any exact mass measurement by comparing observations of metabolites extracted from Arabidopsis thaliana plants grown with (I) [sup.12]C and [sup.14]N (natural abundance), (II) [sup.12]C and [sup.15]N, (III) [sup.13]C and [sup.14]N, or (IV) [sup.13]C and [sup.15]N. Unique elemental compositions were determined over a dramatically enhanced mass range by analyzing exact mass measurement data from the four extracts using two methods. In the first, metabolite masses were matched with a library of 11 000 compounds known to be present in living cells by using values calculated for each of the four isotopic conditions. In the second method, metabolite masses were searched against masses calculated for a constrained subset of possible atomic combinations in all four isotopic regimes. In both methods, the lists of elemental compositions from each labeling regime were compared to find common formulas with similar retention properties by HPLC in at least three of the four regimes. These results demonstrate that metabolic labeling can be used to provide additional constraints for higher confidence formula assignments over an extended mass range.

Research reveals a new pyridoxal 5'-phosphate-binnding site containing an essential lysine 144 residue in the active site in an AdoCbl-dependent lysine 5,6-aminomutase from Porphyromonas gingivalis. Data indicate that lysine 144 residue is localized to the small subunit of the enzyme and its mutation to glutamine abolishes the enzyme activity.

A major limitation of electrospray ionization mass spectrometry (ESI-MS) for oligonucleotide analysis arises due to sodium adduction, a problem that increases with molecular weight. Sodium adduction can preclude useful measurements when limited sample sizes prevent off-line cleanup. A novel and generally useful on-line microdialysis technique is described for the rapid ([approximately]1-5 min) DNA sample cleanup for ESI-MS. Mass spectra of oligo-nucleotides of different size and sequence showing no significant sodium adduct peaks were obtained using the on-line microdialysis system with sodium chloride concentrations as high as 250 mM. Signal-to-noise ratios were also greatly enhanced compared to direct infusion of the original samples. By using ammonium acetate as the dialysis buffer, it was also found that the noncovalent association of double-stranded oligonucleotides could be preserved during the microdialysis process, allowing analysis by ESI-MS.

The 'lost C3-fragment' produced during the enzymatic oxidative coupling of the peptide, K-DIT-K5-DIT-K, to form thyroxine (T4) was characterized. It was shown that the 'lost C3-fragment' is not a dehydroalanine residue but rather an aminomalonic semialdehyde residue, embedded in the peptide backbone. Findings strongly implicate the intermediacy of a hydroxy quinol ether, which facilitates C-C bond scission via reverse aldolization to form a peptide containing T4 and the C3 aldehyde.

A procedure for determining the extent of phosphorylation at individual sites of multiply phosphorylated proteins was developed and applied to two polyphosphorylated proteins. The protocol, using simple chemical (Fischer methyl-esterification) and enzymatic (phosphatase) modification steps and an accessible isotopic labeling reagent (methyl alcohol-d4), is described in detail. Site-specific phosphorylation stoichiometries are derived from the comparison of chemically identical but isotopically distinct peptide species analyzed by microspray liquid chomatography-mass spectrometry (μLC-MS) using a Micromass Q-TOF2 mass spectrometer. Ten phosphorylation sites were unambiguously identified in tryptic digests of both proteins, and phosphorylation stoichiometries were determined for eight of the ten sites using the isotope-coded strategy. The extent of phosphorylation was also estimated from the mass spectral peak areas for the phosphorylated and unmodified peptides, and these estimates, when compared with stoichiometries determined using the isotope-coded technique, differed only marginally (within ∼20%). [Copyright &y& Elsevier]

Examines the existence of lysine residue in the active site of 5,6-aminomutase from Porphyromonas gingivalis. Association between carbonyls and lysine residues; Enzymatic activity of lysine; Conversion of lysine into diaminohexanoate.

Untargeted metabolomics based on reverse phase LC-MS (RPLC-MS) plays a crucial role in biomarker discovery across physiological and disease states. Standardizing the development process of untargeted methods requires paying attention to critical factors that are under discussed or easily overlooked, such as injection parameters, performance assessment, and matrix effect evaluation. In this study, we developed an untargeted metabolomics method for plasma and fecal samples with the optimization and evaluation of these factors. Our results showed that optimizing the reconstitution solvent and sample injection amount was critical for achieving the balance between metabolites coverage and signal linearity. Method validation with representative stable isotopically labeled standards (SILs) provided insights into the analytical performance evaluation of our method. To tackle the issue of the matrix effect, we implemented a postcolumn infusion (PCI) approach to monitor the overall absolute matrix effect (AME) and relative matrix effect (RME). The monitoring revealed distinct AME and RME profiles in plasma and feces. Comparing RME data obtained for SILs through postextraction spiking with those monitored using PCI compounds demonstrated the comparability of these two methods for RME assessment. Therefore, we applied the PCI approach to predict the RME of 305 target compounds covered in our in-house library and found that targets detected in the negative polarity were more vulnerable to the RME, regardless of the sample matrix. Given the value of this PCI approach in identifying the strengths and weaknesses of our method in terms of the matrix effect, we recommend implementing a PCI approach during method development and applying it routinely in untargeted metabolomics. [ABSTRACT FROM AUTHOR]

Rising population density and global mobility are among the reasons why pathogens such as SARS-CoV-2, the virus that causes COVID-19, spread so rapidly across the globe. The policy response to such pandemics will always have to include accurate monitoring of the spread, as this provides one of the few alternatives to total lockdown. However, COVID-19 diagnosis is currently performed almost exclusively by reverse transcription polymerase chain reaction (RT-PCR). Although this is efficient, automatable, and acceptably cheap, reliance on one type of technology comes with serious caveats, as illustrated by recurring reagent and test shortages. We therefore developed an alternative diagnostic test that detects proteolytically digested SARS-CoV-2 proteins using mass spectrometry (MS). We established the Cov-MS consortium, consisting of 15 academic laboratories and several industrial partners to increase applicability, accessibility, sensitivity, and robustness of this kind of SARS-CoV-2 detection. This, in turn, gave rise to the Cov-MS Digital Incubator that allows other laboratories to join the effort, navigate, and share their optimizations and translate the assay into their clinic. As this test relies on viral proteins instead of RNA, it provides an orthogonal and complementary approach to RT-PCR using other reagents that are relatively inexpensive and widely available, as well as orthogonally skilled personnel and different instruments. Data are available via ProteomeXchange with identifier PXD022550., Competing Interests: The authors declare the following competing financial interest(s): L. Van Oudenhove, J. Claereboudt, S. Oehrle, N. Tanna, and J. P. C. Vissers are employed by Waters Corporation. C. S. Lane, S. El Ouadi, J.-B. Vincendet, and N. Morrice are employed by Sciex. F. Sigloch and A. Bhangu-Uhlmann are employed by Polyquant GmbH. M. Razavi and L. Anderson are employed by SISCAPA., (© 2021 The Authors. Published by American Chemical Society.)

In recent years, a variety of approaches have been developed using decoy databases to empirically assess the error associated with peptide identifications from large-scale proteomics experiments. We have developed an approach for calculating the expected uncertainty associated with false-positive rate determination using concatenated reverse and forward protein sequence databases. After explaining the theoretical basis of our model, we compare predicted error with the results of experiments characterizing a series of mixtures containing known proteins. In general, results from characterization of known proteins show good agreement with our predictions. Finally, we consider how these approaches may be applied to more complicated data sets, as when peptides are separated by charge state prior to false-positive determination.