Dataset Information

Identifying and quantifying two ligand-binding sites while imaging native human membrane receptors by AFM.

ABSTRACT: A current challenge in life sciences is to image cell membrane receptors while characterizing their specific interactions with various ligands. Addressing this issue has been hampered by the lack of suitable nanoscopic methods. Here we address this challenge and introduce multifunctional high-resolution atomic force microscopy (AFM) to image human protease-activated receptors (PAR1) in the functionally important lipid membrane and to simultaneously localize and quantify their binding to two different ligands. Therefore, we introduce the surface chemistry to bifunctionalize AFM tips with the native receptor-activating peptide and a tris-N-nitrilotriacetic acid (tris-NTA) group binding to a His10-tag engineered to PAR1. We further introduce ways to discern between the binding of both ligands to different receptor sites while imaging native PAR1s. Surface chemistry and nanoscopic method are applicable to a range of biological systems in vitro and in vivo and to concurrently detect and localize multiple ligand-binding sites at single receptor resolution.

SUBMITTER: Pfreundschuh M

PROVIDER: S-EPMC4660198 | biostudies-literature | 2015 Nov

REPOSITORIES: biostudies-literature

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Identifying and quantifying two ligand-binding sites while imaging native human membrane receptors by AFM.

Pfreundschuh Moritz M Alsteens David D Wieneke Ralph R Zhang Cheng C Coughlin Shaun R SR Tampé Robert R Kobilka Brian K BK Müller Daniel J DJ

Nature communications 20151112

A current challenge in life sciences is to image cell membrane receptors while characterizing their specific interactions with various ligands. Addressing this issue has been hampered by the lack of suitable nanoscopic methods. Here we address this challenge and introduce multifunctional high-resolution atomic force microscopy (AFM) to image human protease-activated receptors (PAR1) in the functionally important lipid membrane and to simultaneously localize and quantify their binding to two diff ...[more]

PMID: 26561004

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Project description:BackgroundBark beetles are major pests of conifer forests, and their behavior is primarily mediated via olfaction. Targeting the odorant receptors (ORs) may thus provide avenues towards improved pest control. Such an approach requires information on the function of ORs and their interactions with ligands, which is also essential for understanding the functional evolution of these receptors. Hence, we aimed to identify a high-quality complement of ORs from the destructive spruce bark beetle Ips typographus (Coleoptera, Curculionidae, Scolytinae) and analyze their antennal expression and phylogenetic relationships with ORs from other beetles. Using 68 biologically relevant test compounds, we next aimed to functionally characterize ecologically important ORs, using two systems for heterologous expression. Our final aim was to gain insight into the ligand-OR interaction of the functionally characterized ORs, using a combination of computational and experimental methods.ResultsWe annotated 73 ORs from an antennal transcriptome of I. typographus and report the functional characterization of two ORs (ItypOR46 and ItypOR49), which are responsive to single enantiomers of the common bark beetle pheromone compounds ipsenol and ipsdienol, respectively. Their responses and antennal expression correlate with the specificities, localizations, and/or abundances of olfactory sensory neurons detecting these enantiomers. We use homology modeling and molecular docking to predict their binding sites. Our models reveal a likely binding cleft lined with residues that previously have been shown to affect the responses of insect ORs. Within this cleft, the active ligands are predicted to specifically interact with residues Tyr84 and Thr205 in ItypOR46. The suggested importance of these residues in the activation by ipsenol is experimentally supported through site-directed mutagenesis and functional testing, and hydrogen bonding appears key in pheromone binding.ConclusionsThe emerging insight into ligand binding in the two characterized ItypORs has a general importance for our understanding of the molecular and functional evolution of the insect OR gene family. Due to the ecological importance of the characterized receptors and widespread use of ipsenol and ipsdienol in bark beetle chemical communication, these ORs should be evaluated for their potential use in pest control and biosensors to detect bark beetle infestations.

Project description:BackgroundSpecies distribution models are often used to characterize a species' native range climate, so as to identify sites elsewhere in the world that may be climatically similar and therefore at risk of invasion by the species. This endeavor provoked intense public controversy over recent attempts to model areas at risk of invasion by the Indian Python (Python molurus). We evaluated a number of MaxEnt models on this species to assess MaxEnt's utility for vertebrate climate matching.Methodology/principal findingsOverall, we found MaxEnt models to be very sensitive to modeling choices and selection of input localities and background regions. As used, MaxEnt invoked minimal protections against data dredging, multi-collinearity of explanatory axes, and overfitting. As used, MaxEnt endeavored to identify a single ideal climate, whereas different climatic considerations may determine range boundaries in different parts of the native range. MaxEnt was extremely sensitive to both the choice of background locations for the python, and to selection of presence points: inclusion of just four erroneous localities was responsible for Pyron et al.'s conclusion that no additional portions of the U.S. mainland were at risk of python invasion. When used with default settings, MaxEnt overfit the realized climate space, identifying models with about 60 parameters, about five times the number of parameters justifiable when optimized on the basis of Akaike's Information Criterion.Conclusions/significanceWhen used with default settings, MaxEnt may not be an appropriate vehicle for identifying all sites at risk of colonization. Model instability and dearth of protections against overfitting, multi-collinearity, and data dredging may combine with a failure to distinguish fundamental from realized climate envelopes to produce models of limited utility. A priori identification of biologically realistic model structure, combined with computational protections against these statistical problems, may produce more robust models of invasion risk.

Dataset Information

Identifying and quantifying two ligand-binding sites while imaging native human membrane receptors by AFM.

Publications

Identifying and quantifying two ligand-binding sites while imaging native human membrane receptors by AFM.

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