We have developed an algorithm called fast maximum likelihood reconstruction (FMLR) that performs spectral deconvolution of 1D–2D NMR spectra for the purpose of accurate signal quantification. FMLR constructs the simplest time-domain model (e.g., the model with the fewest number of signals and parameters) whose frequency spectrum matches the visible regions of the spectrum obtained from identical Fourier processing of the acquired data. We describe the application of FMLR to quantitative metabolomics and demonstrate the accuracy of the method by analysis of complex, synthetic mixtures of metabolites and liver extracts. The algorithm demonstrates greater accuracy (0.5–5.0% error) than peak height analysis and peak integral analysis with greatly reduced operator intervention. FMLR has been implemented in a Java-based framework that is available for download on multiple platforms and is interoperable with popular NMR display and processing software. Two-dimensional 1H–13C spectra of mixtures can be acquired with acquisition times of 15 min and analyzed by FMLR in the range of 2–5 min per spectrum to identify and quantify constituents present at concentrations of 0.2 mM or greater.

The flash-induced electrochromic shift, measured by the amplitude of the rapid absorbance increase at 518 nanometers (AA518), was used to determine the amount of charge separation within photosystems 11 and I in spinach (Spinacia oleracea L.) leaves. The recovery time of the reaction centers was determined by comparing the amplitudes of AA518 induced by two flashes separated by a variable time interval. The recovery of the AA518 on the second flash revealed that 20% of the reaction centers exhibited a recovery half-time of 1.7 ± 0.3 seconds, which is 1000 times slower than normally active reaction centers. Measurements using isolated thylakoid membranes showed that photosystem I constituted 38% of the total number of reaction centers, and that the photosystem I reaction centers were nearly fully active, indicating that the slowly tuming over reaction centers were due solely to photosystem I. The results demonstrate that in spinach leaves approximately 32% of the photosystem 11 complexes are effectively inactive, in that their contribution to energy conversion is negligible. Additional evidence for inactive photosystem 11 complexes in spinach leaves was provided by fluorescence induction measurements, used to monitor the oxidation kinetics of the primary quinone acceptor of photosystem 11, QA, after a short flash. The measurements showed that in a fraction of the photosystem 11 complexes the oxidation of QA was slow, displaying a half-time of 1.5 ± 0.3 seconds. The kinetics of QOA oxidation were virtually identical to the kinetics of the recovery of photosystem 11 determined from the electrochromic shift. The key difference between active and inactive photosystem 11 centers is that in the inactive centers the oxidation rate of QOA is slow compared to active centers. Measurements of the electrochromic shift in detached leaves from several different species of plants revealed a significant fraction of slowly tuming over reaction centers, raising the possibility that reaction centers that are inefficient in energy conversion may be a common feature in plants.In normally functioning PSII complexes, bound plastoquinone is reduced by electrons from water, and subsequently released into the thylakoid membrane (reviewed in Crofts and Wraight [4] two bound plastoquinone molecules, QA2 and QB, operating in series. QA acts as a single electron carrier and is permanently bound in PSII. The plastoquinone molecule at the QB site differs from QA in that it becomes fully reduced to plastoquinol after two turnovers of the reaction center, and it exchanges rapidly with the freely mobile plastoquinone in the membrane. In reaction centers in which QA and QB are initially oxidized, the first light reaction drives an electron from P680, the primary donor of PSII, to pheophytin, which in turn reduces QA. The electron is then transferred from QA to QB, enabling the reaction center to turn over a second time. In the second light reaction an electron is transferred over the same path to QB-, and together with two protons results i...

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A general theory has been developed for the application of the maximum likelihood (ML) principle to the estimation of NMR parameters (frequency and amplitudes) from multidimensional time-domain NMR data. A computer program (ChiFit) has been written that carries out ML parameter estimation in the D-1 indirectly detected dimensions of a D-dimensional NMR data set. The performance of this algorithm has been tested with experimental three-dimensional (HNCO) and four-dimensional (HN(CO)-CAHA) data from a small protein labeled with 13C and 15N. These data sets, with different levels of digital resolution, were processed using ChiFit for ML analysis and employing conventional Fourier transform methods with prior extrapolation of the time-domain dimensions by linear prediction. Comparison of the results indicates that the ML approach provides superior frequency resolution compared to conventional methods, particularly under conditions of limited digital resolution in the time-domain input data, as is characteristic of D-dimensional NMR data of biomolecules. Close correspondence is demonstrated between the results of analyzing multidimensional time-domain NMR data by Fourier transformation, Bayesian probability theory [Chylla, R.A. and Markley, J.L. (1993) J. Biomol. NMR, 3, 515-533], and the ML principle.