Experimental strategies to improve drug-target identification in mass spectrometry-based thermal stability assays.

Mass spectrometry (MS)-based thermal stability assays have recently emerged as one of the most promising solutions for the identification of protein-ligand interactions. Here, we have investigated eight combinations of several recently introduced MS-based advancements, including the Phase-Constrained Spectral Deconvolution Method, Field Asymmetric Ion Mobility Spectrometry, and the implementation of a carrier sample as improved MS-based acquisition approaches for thermal stability assays (iMAATSA). We used intact Jurkat cells treated with a commercially available MEK inhibitor, followed by heat treatment, to prepare a set of unfractionated isobarically-labeled proof-of-concept samples to compare the performance of eight different iMAATSAs. Finally, the best-performing iMAATSA was compared to a conventional approach and evaluated in a fractionation experiment. Improvements of up to 82% and 86% were demonstrated in protein identifications and high-quality melting curves, respectively, over the conventional approach in the proof-of-concept study, while an approximately 12% improvement in melting curve comparisons was achieved in the fractionation experiment.

Publisher Correction: Fast, sensitive method for trisaccharide biomarker detection in mucopolysaccharidosis type 1.

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Fast, sensitive method for trisaccharide biomarker detection in mucopolysaccharidosis type 1.

Certain recessively inherited diseases result from an enzyme deficiency within lysosomes. In mucopolysaccharidoses (MPS), a defect in glycosaminoglycan (GAG) degradation leads to GAG accumulation followed by progressive organ and multiple system dysfunctions. Current methods of GAG analysis used to diagnose and monitor the diseases lack sensitivity and throughput. Here we report a LC-MS method with accurate metabolite mass analysis for identifying and quantifying biomarkers for MPS type I without the need for extensive sample preparation. The method revealed 225 LC-MS features that were >1000-fold enriched in urine, plasma and tissue extracts from untreated MPS I mice compared to MPS I mice treated with iduronidase to correct the disorder. Levels of several trisaccharides were elevated >10000-fold. To validate the clinical relevance of our method, we confirmed the presence of these biomarkers in urine, plasma and cerebrospinal fluid from MPS I patients and assessed changes in their levels after treatment.

Selection of plants for optimization of vegetative filter strips treating runoff from turfgrass.

Runoff from turf environments, such as golf courses, is of increasing concern due to the associated chemical contamination of lakes, reservoirs, rivers, and ground water. Pesticide runoff due to fungicides, herbicides, and insecticides used to maintain golf courses in acceptable playing condition is a particular concern. One possible approach to mitigate such contamination is through the implementation of effective vegetative filter strips (VFS) on golf courses and other recreational turf environments. The objective of the current study was to screen ten aesthetically acceptable plant species for their ability to remove four commonly-used and degradable pesticides: chlorpyrifos (CP), chlorothalonil (CT), pendimethalin (PE), and propiconazole (PR) from soil in a greenhouse setting, thus providing invaluable information as to the species composition that would be most efficacious for use in VFS surrounding turf environments. Our results revealed that blue flag iris (Iris versicolor) (76% CP, 94% CT, 48% PE, and 33% PR were lost from soil after 3 mo of plant growth), eastern gama grass (Tripsacum dactyloides) (47% CP, 95% CT, 17% PE, and 22% PR were lost from soil after 3 mo of plant growth), and big blue stem (Andropogon gerardii) (52% CP, 91% CT, 19% PE, and 30% PR were lost from soil after 3 mo of plant growth) were excellent candidates for the optimization of VFS as buffer zones abutting turf environments. Blue flag iris was most effective at removing selected pesticides from soil and had the highest aesthetic value of the plants tested.