Cells swimming in confined environments are attracted by surfaces. We measure the steady-state distribution of smooth-swimming bacteria (Escherichia coli) between two glass plates. In agreement with earlier studies, we find a strong increase of the cell concentration at the boundaries. We demonstrate theoretically that hydrodynamic interactions of the swimming cells with solid surfaces lead to their reorientation in the direction parallel to the surfaces, as well as their attraction by the closest wall. A model is derived for the steady-state distribution of swimming cells, which compares favorably with our measurements. We exploit our data to estimate the flagellar propulsive force in swimming E. coli.

Although understanding of the olfactory system has progressed at the level of downstream receptor signaling and the wiring of olfactory neurons, the system remains poorly understood at the molecular level of the receptors and their interaction with and recognition of odorant ligands. The structure and functional mechanisms of these receptors still remain a tantalizing enigma, because numerous previous attempts at the large-scale production of functional olfactory receptors (ORs) have not been successful to date. To investigate the elusive biochemistry and molecular mechanisms of olfaction, we have developed a mammalian expression system for the large-scale production and purification of a functional OR protein in milligram quantities. Here, we report the study of human OR17-4 (hOR17-4) purified from a HEK293S tetracycline-inducible system. Scale-up of production yield was achieved through suspension culture in a bioreactor, which enabled the preparation of >10 mg of monomeric hOR17-4 receptor after immunoaffinity and size exclusion chromatography, with expression yields reaching 3 mg/L of culture medium. Several key post-translational modifications were identified using MS, and CD spectroscopy showed the receptor to be Ϸ50% ␣-helix, similar to other recently determined G protein-coupled receptor structures. Detergent-solubilized hOR17-4 specifically bound its known activating odorants lilial and floralozone in vitro, as measured by surface plasmon resonance. The hOR17-4 also recognized specific odorants in heterologous cells as determined by calcium ion mobilization. Our system is feasible for the production of large quantities of OR necessary for structural and functional analyses and research into OR biosensor devices. BiacoreA100 ͉ detergent screen ͉ fos-choline 14 ͉ G protein-coupled receptor purification ͉ membrane protein A nimal noses have evolved the ability to rapidly detect a seemingly infinite array of odors at minute concentrations. The basis of this sensitivity are the olfactory (smell) receptors, a large class of G protein-coupled receptors (GPCRs) that function together combinatorially to allow discrimination between a wide range of volatile and soluble molecules (1, 2). As GPCRs, all olfactory receptors (ORs) are integral membrane proteins with 7 predicted transmembrane domains. To date, crystal structures exist for only 5 GPCR proteins (3). Despite the fact that ORs represent the largest class of known membrane proteins, no detailed structure exists for any OR, because the major obstacle to structural and functional studies on membrane proteins is the notorious difficulty involved in expressing and purifying the large quantities of receptor protein sample required for techniques such as X-ray crystallography. The first crucial step to enable such pivotal biochemical and structural analyses is to engineer systems with the capacity to produce and purify milligram quantities of an OR. hOR17-4 (alternately known as OR1D2) is of particular interest because, in addition to olfactory neurons, it is exp...

Odorant cues are recognized by receptors expressed on olfactory sensory neurons, the primary sensory neurons of the olfactory epithelium. Odorant receptors typically obey the "one receptor, one neuron" rule, in which the receptive field of the olfactory neuron is determined by the singular odorant receptor that it expresses. Odor-evoked receptor activity across the population of olfactory neurons is then interpreted by the brain to identify the molecular nature of the odorant stimulus. In the present study, we characterized the properties of a C family G-protein-coupled receptor that, unlike most other odorant receptors, is expressed in a large population of microvillous sensory neurons in the zebrafish olfactory epithelium and the mouse vomeronasal organ. We found that this receptor, OlfCc1 in zebrafish and its murine ortholog Vmn2r1, is a calcium-dependent, low-sensitivity receptor specific for the hydrophobic amino acids isoleucine, leucine, and valine. Loss-of-function experiments in zebrafish embryos demonstrate that OlfCc1 is required for olfactory responses to a diverse mixture of polar, nonpolar, acidic, and basic amino acids. OlfCc1 was also found to promote localization of other OlfC receptor family members to the plasma membrane in heterologous cells. Together, these results suggest that the broadly expressed OlfCc1 is required for amino acid detection by the olfactory system and suggest that it plays a role in the function and/or intracellular trafficking of other olfactory and vomeronasal receptors with which it is coexpressed.

Everyday inductive reasoning draws on many kinds of knowledge, including knowledge about relationships between properties and knowledge about relationships between objects. Previous accounts of inductive reasoning generally focus on just one kind of knowledge: models of causal reasoning often focus on relationships between properties, and models of similarity-based reasoning often focus on similarity relationships between objects. We present a Bayesian model of inductive reasoning that incorporates both kinds of knowledge, and show that it accounts well for human inferences about the properties of biological species.

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Everyday inductive reasoning draws on many kinds of knowledge, including knowledge about relationships between properties and knowledge about relationships between objects. Previous accounts of inductive reasoning generally focus on just one kind of knowledge: models of causal reasoning often focus on relationships between properties, and models of similarity-based reasoning often focus on similarity relationships between objects. We present a Bayesian model of inductive reasoning that incorporates both kinds of knowledge, and show that it accounts well for human inferences about the properties of biological species.