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Extraction of local hydrogen exchange data from HDX CAD MS measurements by deconvolution of isotopic distributions of fragment ions.

Hydrogen/deuterium exchange (HDX) coupled to protein fragmentation either in solution (by means of proteolysis) or in the gas phase (using collisional activation of protein ions) and followed by mass spectral measurements of deuterium content of individual fragments has become one of the major experimental tools to probe protein structure and dynamics. One difficulty, which often arises in the course of interpretation of HDX MS data, is a need to separate deuterium contribution to the observed isotopic patterns from that of naturally occurring isotopes. Another frequently encountered problem, especially when HDX in solution is followed by protein ion fragmentation in the gas phase, is a need to determine the deuterium content of an internal protein segment based on the measured isotopic distributions of overlapping fragments. While several algorithms were developed in the past several years to address the first problem, the second one did not enjoy as much attention. Here we report a new algorithm based on a maximum entropy principle, which is capable of extracting local exchange data form the isotope distribution of overlapping fragments, as well as subtracting the background due to the presence of natural isotopes and residual deuterium in exchange buffers. The new method is tested with several proteins and appears to generate stable solutions even under unfavorable circumstances, e.g., when the resolving power of a mass analyzer is not sufficient to avoid signal interference or when the isotopic distributions of individual fragments are complex and cannot be approximated with simple binomial distributions. The latter feature makes the algorithm particularly useful when the exchange in solution is correlated or semicorrelated, paving the way to precise structural characterization of non-native protein states in solution.

Algorithms↗

Weighted least-squares deconvolution method for discovery of group differences between complex biofluid 1H NMR spectra.

Biomarker discovery through analysis of high-throughput NMR data is a challenging, time-consuming process due to the requirement of sophisticated, dataset specific preprocessing techniques and the inherent complexity of the data. Here, we demonstrate the use of weighted, constrained least-squares for fitting a linear mixture of reference standard data to complex urine NMR spectra as an automated way of utilizing current assignment knowledge and the ability to deconvolve confounded spectral regions. Following the least-squares fit, univariate statistics were used to identify metabolites associated with group differences. This method was evaluated through applications on simulated datasets and a murine diabetes dataset. Furthermore, we examined the differential ability of various weighting metrics to correctly identify discriminative markers. Our findings suggest that the weighted least-squares approach is effective for identifying biochemical discriminators of varying physiological states. Additionally, the superiority of specific weighting metrics is demonstrated in particular datasets. An additional strength of this methodology is the ability for individual investigators to couple this analysis with laboratory specific preprocessing techniques.

Algorithms↗

Electron tomography of amplified nanogold immunolabelling: Improvement of quality based on alignment of projections with sinograms and use of post-reconstruction deconvolution.

Electron tomography of immunolabelled proteins identified with amplified nanogold particles imaged by Scanning and Transmission Electron Microscopy within thick sections is a powerful method to investigate the three-dimensional organization of complex cellular machineries. In order to increase the overall quality of the reconstructed cube, we have developed two methods that improve the tomographic reconstruction process. We first performed a very precise alignment of the projections before reconstruction with a technique using sinograms. After reconstruction, we propose to compute image restoration by calculating the Point Spread Function of the projection/back-projection system and to use it to deblur the reconstructed cubes. Improvement in the quality of the reconstructed cubes is demonstrated on images of nucleolar proteins tagged with EGFP and immunolabelled with nanogold particles.

Gold↗

Orientational deconvolution of two-dimensional static disorder by a Tikhonov regularized method for 2H solid state NMR of nano-tubular-oriented structures.

A general trend of supramolecular chemistry is the building of mesoscopic-oriented nanotubes. When the typical radius of the channel almost fits the mean supramolecular cross-sectional radius, the guest supramolecule is ultraconfined in the channel. In that case, only rotational disorder around the channel axis is allowed. For sufficiently low temperatures, we expect this 2D disorder to be static on the NMR timescale, and it should reflect the local symmetry of the channels. In this article, we show that experiments performed with deuterium single crystal solid-state NMR as a function of rotation around the channel axis may lead to important information concerning the static orientational disorder of the confined supramolecules. Using an inversion method with Tikhonov regularization and a positivity constraint, that also takes into account of the nonideal pulse sequence response, the orientational probability density can be obtained from 1D experiments performed at different angles, even for significant disorder. As a first step, the method is validated on four different theoretical distributions. It is then applied to 2H NMR single crystal experiments performed on an archetype of parallel channels intergrowth compounds: selectively deuterated 1,10-decanedicarboxylic diacids in hydrogenated urea channels. The diacids form one-dimensional infinite hydrogen-bonded chains ultraconfined in urea linear channels.

Journal Article↗

Deconvoluting clonal and cellular architecture in IDH-mutant acute myeloid leukemia.

Isocitrate dehydrogenase 1/2 (IDH) mutations are early initiating events in acute myeloid leukemia (AML). The complex clonal architecture and cellular heterogeneity in IDH-mutant AML underlies the heterogeneous clinical presentation and outcomes. Integrating single-cell genotyping and transcriptomics, we demonstrate a stem-like and inflammatory phenotype of IDH-mutant AML and identify clone-specific programs associated with NPM1, NRAS, and SRSF2 co-mutations. Furthermore, these clones had distinct responses to treatment with combination IDH inhibitors and chemotherapy, including elimination, reconstitution of myeloid differentiation, or retention within progenitor populations. At relapse after IDH inhibitor monotherapy, we identify upregulated stemness, inflammation, mitochondrial metabolism, and anti-apoptotic factors, as well as downregulated major histocompatibility complex (MHC) class II antigen presentation. At the pre-leukemic stage, we observe upregulation of IDH2-associated pathways, including inflammation. We deliver a detailed phenotyping of IDH-mutant AML and a framework for dissecting contributions of recurrently mutated genes in AML at diagnosis and following therapy, with implications for precision medicine.

Leukemia, Myeloid, Acute↗

A nomogram for deconvolution of single exponential fluorescence decays.

An extremely rapid technique for deconvolving single exponential luminescence decay data is described that involves essentially no mathematical manipulation of the experimental data. The method permits "real time" measurement of deconvolved luminescence lifetimes with conventional pulsed, lifetime-fluorometers and phosphorimeters. The method assumes that the true luminescence decay of the chromophore is accurately represented by a single exponential decay function.

Kinetics↗

Derivation of Laplace transform for the general disposition deconvolution equation in drug metabolism kinetics.

This paper presents some very simplified general treatments which will allow workers to derive equations for any linear kinetic metabolic process. This is done through the use of the Laplace transforms. A general equation is presented to describe the disposition function in Laplace operators for the central compartment of a linear n compartment mammillary model with elimination occurring from any of the compartments. Input functions describes IV bolus, zero-order infusion, intramuscular injection or GI absorption. The Laplace transform for the amount of drug or metabolite in the central compartment is given by the products of the input and disposition functions.

Kinetics↗

Deconvolution by omission libraries.

Omission libraries, synthesized by omitting one amino acid in all coupling positions, are very efficient tools for the rapid identification of the amino acid components of bioactive peptides. Based on the determined amino acids, an occurrence library can be defined and prepared which is much less complex than the full one while still comprising the bioactive peptide.

Amino Acid Sequence↗

Detection of multiple protein conformational ensembles in solution via deconvolution of charge-state distributions in ESI MS.

Monitoring the changes in charge-state distributions of protein ions in electrospray ionization (ESI) mass spectra has become one of the commonly accepted tools to detect large-scale conformational changes of proteins in solution. However, these experiments produce only qualitative, low-resolution information. Our goal is to develop a procedure that would produce quantitative data on protein conformational isomers coexisting in solution at equilibrium. To that end, we have examined the evolution of positive ion charge-state distributions in the

Animals↗