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The development of multidimensional NMR spectroscopy enabled an explosion of structural and dynamical investigations on proteins and other biomacromolecules. Practical limitations on data sampling, based on the Jeener paradigm of parametric sampling of indirect time domains, have long placed limits on resolution in the corresponding frequency dimensions. The emergence of nonuniform sampling (NUS) in indirect time dimensions circumvents those limitations, affording high resolution spectra from short data records collected in practically realized measurement times. In addition to substantially improved resolution, NUS can also be exploited to improve sensitivity, with gains comparable to those obtained using cryogenically cooled probes. We describe a general approach for acquiring and processing multidimensional NUS NMR data for improving sensitivity. [ABSTRACT FROM AUTHOR]

Non-Fourier methods are increasingly utilized in NMR spectroscopy because of their ability to handle nonuniformly-sampled data. However, non-Fourier methods present unique challenges due to their nonlinearity, which can produce nonrandom noise and render conventional metrics for spectral quality such as signal-to-noise ratio unreliable. The lack of robust and transferable metrics (i.e. applicable to methods exhibiting different nonlinearities) has hampered comparison of non-Fourier methods and nonuniform sampling schemes, preventing the identification of best practices. We describe a novel method, in situ receiver operating characteristic analysis (IROC), for characterizing spectral quality based on the Receiver Operating Characteristic curve. IROC utilizes synthetic signals added to empirical data as “ground truth”, and provides several robust scalar-valued metrics for spectral quality. This approach avoids problems posed by nonlinear spectral estimates, and provides a versatile quantitative means of characterizing many aspects of spectral quality. We demonstrate applications to parameter optimization in Fourier and non-Fourier spectral estimation, critical comparison of different methods for spectrum analysis, and optimization of nonuniform sampling schemes. The approach will accelerate the discovery of optimal approaches to nonuniform sampling experiment design and non-Fourier spectrum analysis for multidimensional NMR. [ABSTRACT FROM AUTHOR]

Porphyromonas gingivalis produces five classes of serine/glycine lipids that are recovered in lipid extracts from periodontitis‐afflicted teeth and diseased gingival tissues, particularly at sites of periodontitis. Because these lipids are recovered in diseased gingival tissues, the purpose of the present study was to evaluate the capacity of cultured human gingival fibroblasts (HGF), keratinocytes, and macrophages to hydrolyze these lipids. We hypothesize that one or more of these cell types will hydrolyze the serine/glycine lipids. The primary aim was to treat these cell types for increasing time in culture with individual highly enriched serine/glycine lipid preparations. At specified times, cells and culture media samples were harvested and extracted for hydrolysis products. The serine/glycine lipids and hydrolysis products were quantified using liquid chromatography–mass spectrometry (LC–MS) and free fatty acids were quantified using gas chromatograph–mass spectrometer. LC–MS analysis used two different mass spectrometric methods. This study revealed that treatment of HGF or macrophage (THP1) cells with lipid (L) 654 resulted in breakdown to L342 and subsequent release into culture medium. However, L654 was converted only to L567 in gingival keratinocytes. By contrast, L1256 was converted to L654 by fibroblasts and macrophages but no further hydrolysis or release into medium was observed. Gingival keratinocytes showed no hydrolysis of L1256 to smaller lipid products but because L1256 was not recovered in these cells, it is not clear what hydrolysis products are produced from L1256. Although primary cultures of gingival fibroblasts and macrophages are capable of hydrolyzing specific serine/glycine lipids, prior analysis of lipid extracts from diseased gingival tissues revealed significantly elevated levels of L1256 in diseased tissues. These results suggest that the hydrolysis of bacterial lipids in gingival tissues may reduce the levels of specific lipids, but the hydrolysis of L1256 is not sufficiently rapid to prevent significant accumulation at periodontal disease sites. [ABSTRACT FROM AUTHOR]

• A quantitative analysis of nonuniform sampling (NUS) schemes is conducted by IROC. • The probability density function (PDF) that underlies NUS plays a critical role. • Broad sampling across short evolution times is key for enhancing sensitivity. • Minimal sampling at long evolution times is sufficient for improved resolution. • A workflow for improving sampling in high-variance, low-coverage regime is given. The goal of nonuniform sampling (NUS) is to select a subset of free induction decays (FIDs) from the conventional, uniform grid in a manner that sufficiently samples short evolution times needed for improved sensitivity and long evolution times needed for enhanced resolution. In addition to specifying the number of FIDs to be collected from a uniform grid, NUS schemes also specify the distribution of the selected FIDs, which directly impacts sampling-induced artifacts. Sampling schemes typically address these heuristic guidelines by utilizing a probability density function (PDF) to bias the distribution of sampled evolution times. Given this common approach, schemes differentiate themselves by how the evolution times are distributed within the envelope of the PDF. Here, we employ maximum entropy reconstruction and utilize in situ receiver operating characteristic (IROC) to conduct a critical comparison of the sensitivity and resolution that can be achieved by three types of biased sampling schemes: exponential (PDF is exponentially decaying), Poisson-gap (PDF derived from a sine function), and quantile-directed (PDF defined by simple polynomial decay). This methodology reveals practical insights and trends regarding how the sampling schemes and bias can provide the highest sensitivity and resolution for two nonuniformly sampled dimensions in a three-dimensional biomolecular NMR experiment. The IROC analysis circumvents the limitations of common metrics when used with nonlinear spectral estimation (a characteristic of all methods used with NUS) by quantifying the spectral quality via synthetic signals that are added to the empirical dataset. Recovery of these synthetic signals provides a proxy for the quality of the empirical portion of the spectrum. The central finding is that differences in spectral quality are primarily driven by the strength of bias in the PDF. In addition, a sampling coverage threshold is observed that appears to be connected to the dependence of each NUS method on its random seed. The differences between sampling schemes and biases are most relevant below 20% coverage where seed-dependence is high, whereas at higher coverages, the performance metrics for all of the sampling schemes begin to converge and approach a seed-independent regime. The results presented here show that aggressive sampling at low coverage can produce high-quality spectra by employing a sampling scheme that adheres to a decaying PDF with a bias to a broad range of short evolution times and includes relatively few FIDs at long evolution times. [ABSTRACT FROM AUTHOR]