Jörg Lambert

Microslot NMR probe for metabolomics studies.

A NMR microprobe based on microstrip technology suitable for investigations of volume-limited samples in the low nanoliter range was designed. NMR spectra of sample quantities in the 100 pmol range can be obtained with this probe in a few seconds. The planar geometry of the probe is easily adaptable to the size and geometry requirements of the samples.

Looking into Living Cell Systems: Planar Waveguide Microfluidic NMR Detector for in Vitro Metabolomics of Tumor Spheroids

The complex cell metabolism and its link to oncogenic signaling pathways have received huge interest within the last few years. But the lack of advanced analytical tools for the investigation of living cell metabolism is still a challenge to be faced. Therefore, we designed and fabricated a novel miniaturized microslot NMR detector with on-board heater integrated with a microfluidic device as NMR sample holder. For the first time, a tumor spheroid of 500 μm diameter and consisting of 9000 cells has been studied noninvasively and online for 24 h. The dynamic processes of production and degradation of 23 intra- and extracellular metabolites were monitored. Remarkably high concentrations of lactate and alanine were observed, being an indicator for a shift from oxidative to glycolytic metabolism. In summary, this methodical development has proven to be a successful analytical tool for the elucidation of cellular functions and their corresponding biochemical pathways. Additionally, the planar geometry of the microslot NMR detector allows the hyphenation with versatile lab-on-a chip (LOC) technology. This opens a new window for metabolomics studies on living cells and can be implemented into new application fields in biotechnology and life sciences.

Probing Liquid–Liquid Interfaces with Spatially Resolved NMR Spectroscopy

Phenomena occurring at the interface between two immiscible liquids have a deep impact on many processes of everyday life. The stability of emulsions depends on the interaction of proteins or surfactants at the oil–water interface. Solvent extraction and phase-transfer catalysis rely on optimizing reactions at the boundary of two liquids. Moreover, the liquid–liquid interface between an organic solvent and water represents a simple model of a biological membrane. Historically, the knowledge of the structure and dynamics of liquid–liquid interfaces mainly stemmed from surface-tension measurements and thermodynamic analysis. Over the last couple of decades probing of liquid–liquid interfaces using nonlinear optical methods has developed. Many traditional bulk techniques have been adapted for studying the interface. Second-harmonic generation and vibrational sum-frequency (VSF) spectroscopy both provide information that is inherently surface-specific. The latter, coupled with molecular dynamics, helped to unravel the structure of many interfaces. X-ray and neutron scattering have also been applied to study liquid–liquid interfaces and can provide useful and reliable information on the interfacial widths formed. Surface second-harmonic generation mainly uses molecular probes (such as push–pull molecules) to evaluate surface effects. Probing liquid–liquid interfaces with scanning probe techniques still remains a challenge, though first results from atomic force microscopy (AFM) and scanning electron microscopy (SEM) have been obtained. Transient phase grating experiments with evanescent fields resulting from total internal reflection at an interface between a polar absorbing and a nonpolar transparent phase were used to measure the dimension of liquid–liquid interfaces. Vibrational sum frequency spectroscopy (VSF) selectively probes the molecular structure at hydrocarbon–water interfaces and shows that the hydrogen bonding between adjacent water molecules at the interface is weak and results in a substantial orientation of the water molecules in the interfacial region. Scanning electrochemical microscopy (SECM) can be used to study localized processes occurring at liquid–liquid interfaces. In general, investigations of liquid–liquid interfaces impose a significant technical challenge: the discrimination between the information contained in the miniscule volume of the interface and that from the abundant bulk liquid. Apart from the above-mentioned nonlinear optical techniques, only one approach exists to obtain structural information without modifying the interface. The combination of near-field microscopy and Raman spectroscopy 17] in order to obtain information of gradual changes correlated with distance towards the interface has been also presented. Illumination of a sample surface with a near-field probe provides high spatial resolution beyond the diffraction limit, and theoretically the depth resolution for a 100 nm aperture lies at approximately 10 nm. In combination with Raman spectroscopy this results in highly resolved information on the molecular structure of the surface. The drawback of the technique is the use of a probe that must be very close to the surface. As soon as the interface contacts the tip, a meniscus is formed and the entire experiment must be restarted. In addition this probe can already influence the results by adding a further component into the system. Here, we present a technique based on volume-selective nuclear magnetic resonance (NMR) spectroscopy, which induces no mechanical perturbation of the interface while also providing a high chemical contrast. Volume-selective NMR spectroscopy restricts the detection of magnetic resonance data to a detection volume element of definable size and position. This mode is well known, for instance, from medical applications. The volume of the voxel (a volume element that represents a property on a regular grid in threedimensional space) is determined by the desired spatial resolution as well as by the required detection limit and sensitivity of the NMR experiment. The crucial point is to use a cuboid voxel geometry with a small width in the direction orthogonal to the interface of interest and larger dimensions elsewhere: in obtaining information on a liquid–liquid interface, not all three spatial dimensions are equally important. Fluctuations parallel to the interfacial surface will be slow on NMR timescales and hence can be neglected. The voxel geometry used in our experiments is shown schematically in Figure 1. Basically the number of spins required for the NMR signal is achieved by extending the voxel size parallel to the surface while at the same time reducing the size orthogonal to the surface. Thus in this voxel geometry the number of spins contributing to a signal is the same as that for a cubic voxel. The resolution in the dimension [*] Priv.-Doz. Dr. V. Deckert Department of Proteomics, ISAS—Institute for Analytical Sciences Bunsen-Kirchhoff-Strasse 11, 44139 Dortmund (Germany) and IPHT – Institut f r Photonische Technologien Albert-Einstein-Straße 9, 07745 Jena (Deutschland) Fax: (+ 49)3641-206-139 E-mail: volker.deckert@ipht-jena.de Homepage: http://www.ipht-jena.de

An approach to automated frequency-domain feature extraction in nuclear magnetic resonance spectroscopy

For the analysis of metabolite systems, nuclear magnetic resonance (NMR) spectroscopy has become an important quantitative monitoring technology. Automated quantitation methods are highly desired and mainly characterized by the tasks of model selection and parameter approximation. This paper proposes a promising automated two stage approach in the frequency-domain, in which signaling peaks are first identified and filtered from noise based on curvature properties of the spectrum, and then proportionally approximated based on the analytical solution of a Lorentz-function. Remarkably, in opposition to common least-squares approaches, the proposed approximation scheme does not rely on partial derivatives, and furthermore, the runtime is independent to the number of spectral datapoints. Simulations provide promising empirical evidence for successful peak selection and parameter approximation, with the results for the latter highly outperforming the Levenberg-Marquardt algorithm in terms of error minimization and robustness.

Optimized multiple-quantum filter for robust selective excitation of metabolite signals

The selective excitation of metabolite signals in vivo requires the use of specially adapted pulse techniques, in particular when the signals are weak and the resonances overlap with those of unwanted molecules. Several pulse sequences have been proposed for this spectral editing task. However, their performance is strongly degraded by unavoidable experimental imperfections. Here, we show that optimal control theory can be used to generate pulses and sequences that perform almost ideally over a range of rf field strengths and frequency offsets that can be chosen according to the specifics of the spectrometer or scanner being used. We demonstrate this scheme by applying it to lactate editing. In addition to the robust excitation, we also have designed the pulses to minimize the signal of unwanted molecular species.

Optimized selective lactate excitation with a refocused multiple-quantum filter.

Selective detection of lactate signals in in vivo MR spectroscopy with spectral editing techniques is necessary in situations where strong lipid or signals from other molecules overlap the desired lactate resonance in the spectrum. Several pulse sequences have been proposed for this task. The double-quantum filter SSel-MQC provides very good lipid and water signal suppression in a single scan. As a major drawback, it suffers from significant signal loss due to incomplete refocussing in situations where long evolution periods are required. Here we present a refocused version of the SSel-MQC technique that uses only one additional refocussing pulse and regains the full refocused lactate signal at the end of the sequence.

Glycerol-3-phosphate acyltransferase 1 promotes tumor cell migration and poor survival in ovarian carcinoma

Glycerophosphodiesterase EDI3 (GPCPD1; GDE5; GDPD6) has been suggested to promote cell migration, adhesion, and spreading, but its mechanisms of action remain uncertain. In this study, we targeted the glycerol-3-phosphate acyltransferase GPAM along with choline kinase-α (CHKA), the enzymes that catabolize the products of EDI3 to determine which downstream pathway is relevant for migration. Our results clearly showed that GPAM influenced cell migration via the signaling lipid lysophosphatidic acid (LPA), linking it with GPAM to cell migration. Analysis of GPAM expression in different cancer types revealed a significant association between high GPAM expression and reduced overall survival in ovarian cancer. Silencing GPAM in ovarian cancer cells decreased cell migration and reduced the growth of tumor xenografts. In contrast to these observations, manipulating CHKA did not influence cell migration in the same set of cell lines. Overall, our findings show how GPAM influences intracellular LPA levels to promote cell migration and tumor growth. Cancer Res; 77(17); 4589-601. ©2017 AACR.

A flow microslot NMR probe coupled with a capillary isotachophoresis system exhibits improved properties compared to solenoid designs

AbstractWe report on the hyphenation of capillary isotachophoresis (cITP) separations with online nuclear magnetic resonance (NMR) detection using a planar microslot waveguide probe design. While cITP is commonly coupled with a solenoidal microcoil NMR probe, the structural information provided is limited by broad resonances and poor spectral resolution due to the magnetic field created by the separation current. The microslot probe design described herein allows the separation capillary to be oriented parallel to the static magnetic field, B0, eliminating the spectral broadening produced by the secondary magnetic field induced by the separation current. This allows high-resolution nuclear magnetic resonance spectra of the charged analytes to be obtained in online mode, whereas conventional solenoidal capillary NMR designs must resort to the stopped flow mode. The potential of the microslot probe for hyphenated electrophoretic separations is demonstrated by performing cITP focusing and online NMR detection of the 1H NMR spectrum of a system containing spermine and aniline. Graphical AbstractHigh resolution NMR spectra in flow capillarelectrophoretic separations with microslot NMR probe

Impact of intratumoral heterogeneity of breast cancer tissue on quantitative metabolomics using high-resolution magic angle spinning 1H NMR spectroscopy

High‐resolution magic angle spinning (HR MAS) nuclear magnetic resonance (NMR) spectroscopy is increasingly being used to study metabolite levels in human breast cancer tissue, assessing, for instance, correlations with prognostic factors, survival outcome or therapeutic response. However, the impact of intratumoral heterogeneity on metabolite levels in breast tumor tissue has not been studied comprehensively. More specifically, when biopsy material is analyzed, it remains questionable whether one biopsy is representative of the entire tumor. Therefore, multi‐core sampling (n = 6) of tumor tissue from three patients with breast cancer, followed by lipid (0.9‐ and 1.3‐ppm signals) and metabolite quantification using HR MAS 1H NMR, was performed, resulting in the quantification of 32 metabolites. The mean relative standard deviation across all metabolites for the six tumor cores sampled from each of the three tumors ranged from 0.48 to 0.74. This was considerably higher when compared with a morphologically more homogeneous tissue type, here represented by murine liver (0.16–0.20). Despite the seemingly high variability observed within the tumor tissue, a random forest classifier trained on the original sample set (training set) was, with one exception, able to correctly predict the tumor identity of an independent series of cores (test set) that were additionally sampled from the same three tumors and analyzed blindly. Moreover, significant differences between the tumors were identified using one‐way analysis of variance (ANOVA), indicating that the intertumoral differences for many metabolites were larger than the intratumoral differences for these three tumors. That intertumoral differences, on average, were larger than intratumoral differences was further supported by the analysis of duplicate tissue cores from 15 additional breast tumors. In summary, despite the observed intratumoral variability, the results of the present study suggest that the analysis of one, or a few, replicates per tumor may be acceptable, and supports the feasibility of performing reliable analyses of patient tissue.

Feature Selection by Lorentzian Peak Reconstruction for ^1NMR Post-Processing

In recent years, nuclear magnetic resonance spectroscopy (NMR) has become more and more popular in the field of metabolomic analysis. Analyzing and interpreting the obtained data is thus still challenging due to its complex and nontrivial characteristics. Further analysis of the obtained data is still mainly based on manual assignment, manual analysis and expert knowledge, and therefore time consuming. Common approaches towards automated post processing methods are often based on binning, which leads to loss of information in any case. This paper addresses an approach for reconstructing a one-dimensional NMR spectrum into a set of distinct lorentzian peak lines as an impressive feature selection and data reduction method and evaluates the performance on a real-world as well as on different simulated spectra.