An optimized MALDI MSI protocol for spatial detection of tryptic peptides in fresh frozen prostate tissue

MALDI MS imaging (MSI) is a powerful analytical tool for spatial peptide detection in heterogeneous tissues. Proper sample preparation is crucial to achieve high quality, reproducible measurements. Here we developed an optimized protocol for spatially resolved proteolytic peptide detection with MALDI time-of-flight MSI of fresh frozen prostate tissue sections. The parameters tested included four different tissue washes, four methods of protein denaturation, four methods of trypsin digestion (different trypsin densities, sprayers, and incubation times), and five matrix deposition methods (different sprayers, settings, and matrix concentrations). Evaluation criteria were the number of detected and excluded peaks, percentage of high mass peaks, signal-to-noise ratio, spatial localization, and average intensities of identified peptides, all of which were integrated into a weighted quality evaluation scoring system. Based on these scores, the optimized protocol included an ice-cold EtOH+H₂O wash, a 5 min heating step at 95°C, tryptic digestion incubated for 17h at 37°C and CHCA matrix deposited at a final amount of 1.8 μg/mm². Including a heat-induced protein denaturation step after tissue wash is a new methodological approach that could be useful also for other tissue types. This optimized protocol for spatial peptide detection using MALDI MSI facilitates future biomarker discovery in prostate cancer and may be useful in studies of other tissue types.     

Hippocampal neurons responding to first-time dislocation of a target object

To examine how hippocampal neurons respond to a mismatch between retrieved and actual experience, we trained rats to find a hidden platform at a particular location in an annular watermaze and then moved the platform. Several cells that were silent at the new platform location before the move fired vigorously when the rat found the goal. The new activity was paralleled by reduced discharge in a subset of simultaneously recorded interneurons. The pattern of activity returned toward its original configuration as the rat learned the new location. The activation of specific hippocampal neurons following dislocation of a target object may be essential for synaptic plasticity and adaptive modification of the animal's representation of the environment.     

Spatial representation along the proximodistal axis of CA1

CA1 cells receive direct input from space-responsive cells in medial entorhinal cortex (MEC), such as grid cells, as well as more nonspatial cells in lateral entorhinal cortex (LEC). Because MEC projects preferentially to the proximal part of the CA1, bordering CA2, whereas LEC innervates only the distal part, bordering subiculum, we asked if spatial tuning is graded along the transverse axis of CA1. Tetrodes were implanted along the entire proximodistal axis of dorsal CA1 in rats. Data were recorded in cylinders large enough to elicit firing at more than one location in many neurons. Distal CA1 cells showed more dispersed firing and had a larger number of firing fields than proximal cells. Phase-locking of spikes to MEC theta oscillations was weaker in distal CA1 than in proximal CA1. The findings suggest that spatial firing in CA1 is organized transversally, with the strongest spatial modulation occurring in the MEC-associated proximal part.     

Path integration and the neural basis of the 'cognitive map'

The hippocampal formation can encode relative spatial location, without reference to external cues, by the integration of linear and angular self-motion (path integration). Theoretical studies, in conjunction with recent empirical discoveries, suggest that the medial entorhinal cortex (MEC) might perform some of the essential underlying computations by means of a unique, periodic synaptic matrix that could be self-organized in early development through a simple, symmetry-breaking operation. The scale at which space is represented increases systematically along the dorsoventral axis in both the hippocampus and the MEC, apparently because of systematic variation in the gain of a movement-speed signal. Convergence of spatially periodic input at multiple scales, from so-called grid cells in the entorhinal cortex, might result in non-periodic spatial firing patterns (place fields) in the hippocampus.     

Grid cells use HCN1 channels for spatial scaling

Entorhinal grid cells have periodic, hexagonally patterned firing locations that scale up progressively along the dorsal-ventral axis of medial entorhinal cortex. This topographic expansion corresponds with parallel changes in cellular properties dependent on the hyperpolarization-activated cation current (Ih), which is conducted by hyperpolarization-activated cyclic nucleotide-gated (HCN) channels. To test the hypothesis that grid scale is determined by Ih, we recorded grid cells in mice with forebrain-specific knockout of HCN1. We find that, although the dorsal-ventral gradient of the grid pattern was preserved in HCN1 knockout mice, the size and spacing of the grid fields, as well as the period of the accompanying theta modulation, was expanded at all dorsal-ventral levels. There was no change in theta modulation of simultaneously recorded entorhinal interneurons. These observations raise the possibility that, during self-motion-based navigation, Ih contributes to the gain of the transformation from movement signals to spatial firing fields.     

Identification of metabolites from 2D 1H-13C HSQC NMR using peak correlation plots

Background

Identification of individual components in complex mixtures is an important and sometimes daunting task in several research areas like metabolomics and natural product studies. NMR spectroscopy is an excellent technique for analysis of mixtures of organic compounds and gives a detailed chemical fingerprint of most individual components above the detection limit. For the identification of individual metabolites in metabolomics, correlation or covariance between peaks in ¹H NMR spectra has previously been successfully employed. Similar correlation of 2D ¹H-¹³C Heteronuclear Single Quantum Correlation spectra was recently applied to investigate the structure of heparine. In this paper, we demonstrate how a similar approach can be used to identify metabolites in human biofluids (post-prostatic palpation urine).

Results

From 50 ¹H-¹³C Heteronuclear Single Quantum Correlation spectra, 23 correlation plots resembling pure metabolites were constructed. The identities of these metabolites were confirmed by comparing the correlation plots with reported NMR data, mostly from the Human Metabolome Database.

Conclusions

Correlation plots prepared by statistically correlating ¹H-¹³C Heteronuclear Single Quantum Correlation spectra from human biofluids provide unambiguous identification of metabolites. The correlation plots highlight cross-peaks belonging to each individual compound, not limited by long-range magnetization transfer as conventional NMR experiments.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-014-0413-z) contains supplementary material, which is available to authorized users.     

Spermine and Citrate as Metabolic Biomarkers for Assessing Prostate Cancer Aggressiveness

Separating indolent from aggressive prostate cancer is an important clinical challenge for identifying patients eligible for active surveillance, thereby reducing the risk of overtreatment. The purpose of this study was to assess prostate cancer aggressiveness by metabolic profiling of prostatectomy tissue and to identify specific metabolites as biomarkers for aggressiveness. Prostate tissue samples (n = 158, 48 patients) with a high cancer content (mean: 61.8%) were obtained using a new harvesting method, and metabolic profiles of samples representing different Gleason scores (GS) were acquired by high resolution magic angle spinning magnetic resonance spectroscopy (HR-MAS). Multivariate analysis (PLS, PLS-DA) and absolute quantification (LCModel) were used to examine the ability to predict cancer aggressiveness by comparing low grade (GS = 6, n = 30) and high grade (GS≥7, n = 81) cancer with normal adjacent tissue (n = 47). High grade cancer tissue was distinguished from low grade cancer tissue by decreased concentrations of spermine (p = 0.0044) and citrate (p = 7.73·10⁻⁴), and an increase in the clinically applied (total choline+creatine+polyamines)/citrate (CCP/C) ratio (p = 2.17·10⁻⁴). The metabolic profiles were significantly correlated to the GS obtained from each tissue sample (r = 0.71), and cancer tissue could be distinguished from normal tissue with sensitivity 86.9% and specificity 85.2%. Overall, our findings show that metabolic profiling can separate aggressive from indolent prostate cancer. This holds promise for the benefit of applying in vivo magnetic resonance spectroscopy (MRS) within clinical MR imaging investigations, and HR-MAS analysis of transrectal ultrasound-guided biopsies has a potential as an additional diagnostic tool.