Biomedical subjects

Zhaoyang Feng

Publications and source records attributed to Zhaoyang Feng.

7 recordsLinked to original sources

PubMed2006

A C. elegans model of nicotine-dependent behavior: regulation by TRP-family channels.

Nicotine, the primary addictive substance in tobacco, induces profound behavioral responses in mammals, but the underlying genetic mechanisms are not well understood. Here we develop a C. elegans model of nicotine-dependent behavior. We show that worms exhibit behavioral responses to nicotine that parallel those observed in mammals, including acute response, tolerance, withdrawal, and sensitization. These nicotine responses require nicotinic acetylcholine receptor (nAChR) family genes that are known to mediate nicotine dependence in mammals, suggesting functional conservation of nAChRs in nicotine responses. Importantly, we find that mutant worms lacking TRPC (transient receptor potential canonical) channels are defective in their response to nicotine and that such a defect can be rescued by a human TRPC channel, revealing an unexpected role for TRPC channels in regulating nicotine-dependent behavior. Thus, C. elegans can be used to characterize known genes as well as to identify new genes regulating nicotine responses.

Amino Acid Sequence↗

PubMed2006

Anisotropy and corotation of galactic cosmic rays.

The intensity of Galactic cosmic rays is nearly isotropic because of the influence of magnetic fields in the Milky Way. Here, we present two-dimensional high-precision anisotropy measurement for energies from a few to several hundred teraelectronvolts (TeV), using the large data sample of the Tibet Air Shower Arrays. Besides revealing finer details of the known anisotropies, a new component of Galactic cosmic ray anisotropy in sidereal time is uncovered around the Cygnus region direction. For cosmic-ray energies up to a few hundred TeV, all components of anisotropies fade away, showing a corotation of Galactic cosmic rays with the local Galactic magnetic environment. These results have broad implications for a comprehensive understanding of cosmic rays, supernovae, magnetic fields, and heliospheric and Galactic dynamic environments.

Journal Article↗

PubMed2006

A C. elegans stretch receptor neuron revealed by a mechanosensitive TRP channel homologue.

The nematode Caenorhabditis elegans is commonly used as a genetic model organism for dissecting integration of the sensory and motor systems. Despite extensive genetic and behavioural analyses that have led to the identification of many genes and neural circuits involved in regulating C. elegans locomotion behaviour, it remains unclear whether and how somatosensory feedback modulates motor output during locomotion. In particular, no stretch receptors have been identified in C. elegans, raising the issue of whether stretch-receptor-mediated proprioception is used by C. elegans to regulate its locomotion behaviour. Here we have characterized TRP-4, the C. elegans homologue of the mechanosensitive TRPN channel. We show that trp-4 mutant worms bend their body abnormally, exhibiting a body posture distinct from that of wild-type worms during locomotion, suggesting that TRP-4 is involved in stretch-receptor-mediated proprioception. We show that TRP-4 acts in a single neuron, DVA, to mediate its function in proprioception, and that the activity of DVA can be stimulated by body stretch. DVA both positively and negatively modulates locomotion, providing a unique mechanism whereby a single neuron can fine-tune motor activity. Thus, DVA represents a stretch receptor neuron that regulates sensory-motor integration during C. elegans locomotion.

Animals↗

PubMed2006

Automated imaging of C. elegans behavior.

Automated systems for recording and analyzing behavior have many applications for the study of neurobiology in Caenorhabditis elegans. In particular, machine-based approaches allow for precise quantitative definitions of behavioral phenotypes that have traditionally been subjectively described by individual observers. Automated systems also facilitate the analysis of behaviors that occur over long time scales or are difficult to detect by eye. Here we describe the detailed methodology for the use of one recently described automated tracking system for C. elegans. These protocols make it possible to measure a wide range of parameters related to the morphology, body posture, and locomotion patterns of individual wild-type and mutant nematodes.

Algorithms↗

PubMed2004

An imaging system for standardized quantitative analysis of C. elegans behavior.

BACKGROUND: The nematode Caenorhabditis elegans is widely used for the genetic analysis of neuronal cell biology, development, and behavior. Because traditional methods for evaluating behavioral phenotypes are qualitative and imprecise, there is a need for tools that allow quantitation and standardization of C. elegans behavioral assays. RESULTS: Here we describe a tracking and imaging system for the automated analysis of C. elegans morphology and behavior. Using this system, it is possible to record the behavior of individual nematodes over long time periods and quantify 144 specific phenotypic parameters. CONCLUSIONS: These tools for phenotypic analysis will provide reliable, comprehensive scoring of a wide range of behavioral abnormalities, and will make it possible to standardize assays such that behavioral data from different labs can readily be compared. In addition, this system will facilitate high-throughput collection of phenotypic data that can ultimately be used to generate a comprehensive database of C. elegans phenotypic information. AVAILABILITY: The hardware configuration and software for the system are available from wschafer@ucsd.edu.

Animals↗

PubMed2004

Automatic tracking, feature extraction and classification of C elegans phenotypes.

This paper presents a method for automatic tracking of the head, tail, and entire body movement of the nematode Caenorhabditis elegans (C. elegans) using computer vision and digital image analysis techniques. The characteristics of the worm's movement, posture and texture information were extracted from a 5-min image sequence. A Random Forests classifier was then used to identify the worm type, and the features that best describe the data. A total of 1597 individual worm video sequences, representing wild type and 15 different mutant types, were analyzed. The average correct classification ratio, measured by out-of-bag (OOB) error rate, was 90.9%. The features that have most discrimination ability were also studied. The algorithm developed will be an essential part of a completely automated C. elegans tracking and identification system.

Algorithms↗

PubMed2002

Using machine vision to analyze and classify Caenorhabditis elegans behavioral phenotypes quantitatively.

Mutants with abnormal patterns of locomotion, also known as uncoordinated (Unc) mutants, have facilitated the genetic dissection of many important aspects of nervous system function and development in the nematode Caenorhabditis elegans. Although a large number of distinct classes of Unc mutants can be distinguished by an experienced observer, precise quantitative definitions of these classes have not been available. Here we describe a new approach for using automatically-acquired image data to quantify the locomotion patterns of wild-type and mutant worms. We designed an automated tracking and imaging system capable of following an individual animal for long time periods and saving a time-coded series of digital images representing its motion and body posture over the course of the recording. We have also devised methods for measuring specific features from these image data that can be used by the classification and regression tree classification algorithm to reliably identify the behavioral patterns of specific mutant types. Ultimately, these tools should make it possible to evaluate with quantitative precision the behavioral phenotypes of novel mutants, gene knockout lines, or pharmacological treatments.

Algorithms↗