Bimodal Fluorescence-Magnetic Resonance Contrast Agent for Apoptosis Imaging

Effective cancer therapy largely depends on inducing apoptosis in cancer cells via chemotherapy and/or radiation. Monitoring apoptosis in real-time provides invaluable information for evaluating cancer therapy response and screening preclinical anticancer drugs. In this work, we describe the design, synthesis, characterization, and in vitro evaluation of caspase probe 1 (CP1), a bimodal fluorescence-magnetic resonance (FL-MR) probe that exhibits simultaneous FL-MR turn-on response to caspase-3/7. Both caspases exist as inactive zymogens in normal cells but are activated during apoptosis and are unique biomarkers for this process. CP1 has three distinct components: a DOTA-Gd­(III) chelate that provides the MR signal enhancement, tetraphenylethylene as the aggregation induced emission luminogen (AIEgen), and DEVD peptide which is a substrate for caspase-3/7. In response to caspase-3/7, the water-soluble peptide DEVD is cleaved and the remaining Gd­(III)-AIEgen (Gad-AIE) conjugate aggregates leading to increased FL-MR signals. CP1 exhibited sensitive and selective dual FL-MR turn-on response to caspase-3/7 in vitro and was successfully tested by fluorescence imaging of apoptotic cells. Remarkably, we were able to use the FL response of CP1 to quantify the exact concentrations of inactive and active agents and accurately predict the MR signal in vitro. We have demonstrated that the aggregation-driven FL-MR probe design is a unique method for MR signal quantification. This probe design platform can be adapted for a variety of different imaging targets, opening new and exciting avenues for multimodal molecular imaging

Serum or Plasma (and Which Plasma), That Is the Question

Blood derivatives are the biofluids of choice formetabolomic clinical studies since blood can be collected with lowinvasiveness and is rich in biological information. However, the choiceof the blood collection tubes has an undeniable impact on the plasmaand serum metabolic content. Here, we compared the metabolomicand lipoprotein profiles of blood samples collected at the same timeand place from six healthy volunteers but using different collectiontubes (each enrolled volunteer provided multiple blood samples at adistance of a few weeks/months): citrate plasma, EDTA plasma, andserum tubes. All samples were analyzed via nuclear magnetic resonancespectroscopy. Several metabolites showed statistically significantalterations among the three blood matrices, and also metabolites'correlations were shown to be affected. The effects of blood collectiontubes on the lipoproteins'profiles are relevant too, but less marked. Overcoming the issue associated with different blood collectiontubes is pivotal to scale metabolomics and lipoprotein analysis at the level of epidemiological studies based on samples frommulticenter cohorts. We propose a statistical solution, based on regression, that is shown to be efficient in reducing the alterationsinduced by the different collection tubes for both the metabolomic and lipoprotein profile

KODAMA: an R package for knowledge discovery and data mining

Summary: KODAMA, a novel learning algorithm for unsuper-vised feature extraction, is specifically designed for analysing noisy and high-dimensional data sets. Here we present an R package of the algorithm with additional functions that allow improved interpretation of high-dimensional data. The pack-age requires no additional software and runs on all major plat-forms. Availability and Implementation: KODAMA is freely available from the R archive CRAN (http://cran.r-project.org). The soft-ware is distributed under the GNU General Public License (ver-sion 3 or later)

Drug Screening in Human Cells by NMR Spectroscopy Allows the Early Assessment of Drug Potency

Structure-based drug development is often hampered by the lack of in vivo activity of promising compounds screened in vitro, due to low membrane permeability or poor intracellular binding selectivity. Herein, we show that ligand screening can be performed in living human cells by “intracellular protein-observed” NMR spectroscopy, without requiring enzymatic activity measurements or other cellular assays. Quantitative binding information is obtained by fast, inexpensive 1H NMR experiments, providing intracellular dose- and time-dependent ligand binding curves, from which kinetic and thermodynamic parameters linked to cell permeability and binding affinity and selectivity are obtained. The approach was applied to carbonic anhydrase and, in principle, can be extended to any NMR-observable intracellular target. The results obtained are directly related to the potency of candidate drugs, that is, the required dose. The application of this approach at an early stage of the drug design pipeline could greatly increase the low success rate of modern drug development

1H nuclear magnetic resonance investigation of cobalt(II) substituted carbonic anhydrase

The structure of ClO4 and NO3 adducts of cobalt(II) substituted bovine carbonic anhydrase have been investigated through 1D NOE and 2D 1H nuclear magnetic resonance (NMR) spectroscopy. For the first time two-dimensional NMR techniques are applied to paramagnetic metalloproteins other than iron-containing proteins. Several active site signals have been assigned to specific protons on the grounds of their scalar and dipolar connectivities and T1 values. The experimental dipolar shifts for the protons belonging to noncoordinated residues have allowed the identification of a plausible orientation of the magnetic susceptibility tensor around the cobalt ion as well as of the magnitude and the anisotropy of the principal susceptibility values. In turn, a few more signals have been tentatively assigned on the grounds of their predicted dipolar shifts. The two inhibitor derivatives have a very similar orientation but a different magnitude of the chi tensor, and the protein structure around the active site is highly maintained. The results encourage a more extensive use of the two-dimensional techniques for obtaining selective structural information on the active site of metalloenzymes. With this information at hand, comparisons within homologous series of adducts with various inhibitors and/or mutants of the same enzyme of known structure should be possible using limited sets of NMR data

DHA-induced perturbation of human serum metabolome. Role of the food matrix and Co-administration of oat β-glucan and anthocyanins

Docosahexaenoic acid (DHA) has been reported to have a positive impact on many diet-related disease risks, including metabolic syndrome. Although many DHA-enriched foods have been marketed, the impact of different food matrices on the effect of DHA is unknown. As well, the possibility to enhance DHA effectiveness through the co-administration of other bioactives has seldom been considered. We evaluated DHA effects on the serum metabolome administered to volunteers at risk of metabolic syndrome as an ingredient of three different foods. Foods were enriched with DHA alone or in combination with oat beta-glucan or anthocyanins and were administered to volunteers for 4 weeks. Serum samples collected at the beginning and end of the trial were analysed by NMR-based metabolomics. Multivariate and univariate statistical analyses were used to characterize modifications in the serum metabolome and to evaluate bioactive-bioactive and bioactive-food matrix interactions. DHA administration induces metabolome perturbation that is influenced by the food matrix and the co-presence of other bioactives. In particular, when co-administered with oat beta-glucan, DHA induces a strong rearrangement in the lipoprotein profile of the subjects. The observed modifications are consistent with clinical results and indicate that metabolomics represents a possible strategy to choose the most appropriate food matrices for bioactive enrichment

DHA-Induced Perturbation of Human Serum Metabolome. Role of the Food Matrix and Co-Administration of Oat β-glucan and Anthocyanins.

Docosahexaenoic acid (DHA) has been reported to have a positive impact on many diet-related disease risks, including metabolic syndrome. Although many DHA-enriched foods have been marketed, the impact of different food matrices on the effect of DHA is unknown. As well, the possibility to enhance DHA effectiveness through the co-administration of other bioactives has seldom been considered. We evaluated DHA effects on the serum metabolome administered to volunteers at risk of metabolic syndrome as an ingredient of three different foods. Foods were enriched with DHA alone or in combination with oat beta-glucan or anthocyanins and were administered to volunteers for 4 weeks. Serum samples collected at the beginning and end of the trial were analysed by NMR-based metabolomics. Multivariate and univariate statistical analyses were used to characterize modifications in the serum metabolome and to evaluate bioactive-bioactive and bioactive-food matrix interactions. DHA administration induces metabolome perturbation that is influenced by the food matrix and the co-presence of other bioactives. In particular, when co-administered with oat beta-glucan, DHA induces a strong rearrangement in the lipoprotein profile of the subjects. The observed modifications are consistent with clinical results and indicate that metabolomics represents a possible strategy to choose the most appropriate food matrices for bioactive enrichment