1. Descrição do Microscópio de Seguimento <ol><li> Uma placa de ágar é iluminado por uma fonte de luz de fibra e fotografada com uma câmara. Este sistema é montado em um estágio de translação X, Y. </li><li> A fase é movida por motores de passo padrão, os quais são ligados a um controlador de motor de passo. </li><li> O controlador e da câmara são ligados ao computador e controlados por programas personalizados escritos em LabVIEW. </li><li> A câmara capta as imagens da superfície de uma placa de ágar e identifica objetos escuros em um fundo claro. </li><li> A qualidade de imagem é ajustado de modo que o programa de computador pode quantificar objectos em tempo real. O ganho, o brilho, e a velocidade do obturador da câmara pode ser ajustado para proporcionar um objecto escuro sobre um fundo branco. </li><li> A marca de referência para o processo de calibração automática é feita por picar a superfície do agar com uma picareta verme. </li><li> A imagem, filtrada binário que é usado pelo programa de controle pode ser verificado. </li><li> O modoftware tem um recurso de auto-calibração que calcula a matriz de calibração movendo um objeto de teste a uma distância fixa. </li><li> Distâncias em pixels é calibrado para medidas tomadas pelo motor de passo pela matriz de calibração. </li><li> Após a calibração, o sistema está pronto para ir e não precisa ser recalibrado, a menos que a ampliação é alterada ou se a câmera é reposicionado. </li></ol> 2. Preparando Placas de Rastreamento e C. elegans para Rastreamento <ol><li> Um anel de cobre é utilizado para encurralar os vermes e mantê-los de migrar para a borda do prato. O cobre proporciona uma barreira química local e não afecta o movimento do sem-fim de outro modo para a duração da experiência (&lt;1 hora). Aqueça o primeiro anel, colocando-o sobre uma placa de aquecimento ou equivalente. </li><li> Anel lugar sobre uma placa de agar fresca (1,7% Agar Bacto, 0,25% de Bacto-peptona, 0,3% de NaCl, 1 mM de CaCl2, 1 mM MgSO4, 25 mM de tampão de fosfato de potássio, 5 ug / mlcolesterol) e pressione um pouco para incorporá-lo na superfície do ágar. </li><li> Escolha L4 fase ou vermes adultos jovens numa placa de ágar preenchido com algum buffer NGM (0,3% de NaCl, 1 mM de CaCl2, 1 mM MgSO4, 25 mM de tampão de fosfato de potássio), para lavá-los de resíduos de comida. Deixe os vermes nadar por alguns minutos. </li><li> Cuidadosamente coloque um único sem-fim na placa de controle, perto do centro do anel. E em seguida, coloque a placa sobre o rastreador worm. </li></ol> 3. Rastreamento Worm <ol><li> Execute o programa LabVIEW e selecionar as opções, se necessário (localização de imagens, tipos de imagens, medições, as configurações da câmera). </li><li> Usando o joystick mover o microscópio até que uma imagem do verme está no campo de visão (ecrã de computador). Pressione &quot;faixa&quot; para envolver o programa de rastreamento. </li><li> O programa de computador, na verdade, mede o movimento de uma imagens binárias filtradas conforme mostrado e pode fazer medições nesta imagem em tempo real </li><li> À réer rastrear uma reconstrução da trajectória global pode ser feito a partir dos movimentos de motores de passo, enquanto a forma muda locais do sem-fim pode ser vista em detalhe. </li></ol> 4. Análise de Dados <ol><li> Executar script skeletonizing (MATLAB) para parametrizar formas do verme. (Figura 2) </li><li> Calcule autovetores dos dados esqueletizadas. (Figura 3.4) </li><li> Figura 5 mostram. Leia legenda da figura ou resultados representativos. </li></ol>

<ol>
	<li>Brenner, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+genetics+of+Caenorhabditis+elegans.">The genetics of Caenorhabditis elegans.</a> Genetics. 77 (1), 71-79 (1974).</li><li>de Bono, M., Maricq, A. V. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Neuronal+substrates+of+complex+behaviors+in+C.+elegans.">Neuronal substrates of complex behaviors in C. elegans.</a> Annu. Rev. Neurosci. (28), 451-501 (2005).</li><li>Pierce-Shimomura, J. T., Morse, T. M., Lockery, S. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+fundamental+role+of+pirouettes+in+Caenorhabditis+elegans+chemotaxis.">The fundamental role of pirouettes in Caenorhabditis elegans chemotaxis.</a> J. Neurosci. 19 (21), 9557-9569 (1999).</li><li>Gray, J. M., Hill, J. J., Bargmann, C. I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+circuit+for+navigation+in+Caenorhabditis+elegans.">A circuit for navigation in Caenorhabditis elegans.</a> Proc. Natl. Acad. Sci. U.S.A. 102 (9), 3184-3191 (2005).</li><li>Baek, J. H., Cosman, P., Feng, Z., Silver, J., Schafer, W. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Using+machine+vision+to+analyze+and+classify+Caenorhabditis+elegans+behavioral+phenotypes+quantitatively.">Using machine vision to analyze and classify Caenorhabditis elegans behavioral phenotypes quantitatively.</a> J. Neurosci. Methods. 118 (1), 9-21 (2002).</li><li>Stephens, G. J., Johnson-Kerner, B., Bialek, W., Ryu, W. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Dimensionality+and+Dynamics+in+the+Behavior+of+C.+elegans.">Dimensionality and Dynamics in the Behavior of C. elegans.</a> PLoS Comput. Biol. 4 (1), e1000028 (2008).</li><li>Stephens, G. J., Johnson-Kerner, B., Bialek, W., Ryu, W. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=From+modes+to+movement+in+the+behavior+of+C.+elegans.">From modes to movement in the behavior of C. elegans.</a> PLoS One. 5 (11), e13914 (2010).</li><li>Feng, Z., Cronin, C. J., Wittig, J. H., Sternberg, P. W., Schafer, W. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=An+imaging+system+for+standardized+quantitative+analysis+of+C.+elegans+behavior.">An imaging system for standardized quantitative analysis of C. elegans behavior.</a> BMC Bioinformatics. (5), 115 (2004).</li><li>Ramot, D., Johnson, B. E., Berry, T. L., Carnell, L., Goodman, M. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Parallel+Worm+Tracker:+A+Platform+for+Measuring+Average+Speed+and+Drug-Induced+Paralysis+in+Nematodes.">The Parallel Worm Tracker: A Platform for Measuring Average Speed and Drug-Induced Paralysis in Nematodes.</a> PLoS One. 3 (5), e2208 (2008).</li><li>Swierczek, N. A., Giles, A. C., Rankin, C. H., Kerr, R. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High-throughput+behavioral+analysis+in+C.+elegans.">High-throughput behavioral analysis in C. elegans.</a> Nat. Methods. 8 (7), 592-598 (2011).</li><li>Leifer, A. M., Fang-Yen, C., Gershow, M., Alkema, M. J., Samuel, A. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Optogenetic+manipulation+of+neural+activity+in+freely+moving+Caenorhabditis+elegans.">Optogenetic manipulation of neural activity in freely moving Caenorhabditis elegans.</a> Nat. Methods. 8 (2), 147-152 (2011).</li><li>Stirman, J. N., Crane, M. M., Husson, S. J., Wabnig, S., Schultheis, C., Gottschalk, A., Lu, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Real-time+multimodal+optical+control+of+neurons+and+muscles+in+freely+behaving+Caenorhabditis+elegans.">Real-time multimodal optical control of neurons and muscles in freely behaving Caenorhabditis elegans.</a> Nat. Methods. 8 (2), 153-158 (2011).</li><li>Ben Arous, J., Tanizawa, Y., Rabinowitch, I., Chatenay, D., Schafer, W. R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Automated+imaging+of+neuronal+activity+in+freely+behaving+Caenorhabditis+elegans.">Automated imaging of neuronal activity in freely behaving Caenorhabditis elegans.</a> J Neurosci Methods. 187 (2), 229-234 (2010).</li><li>Wittenburg, N., Baumeister, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Thermal+avoidance+in+Caenorhabditis+elegans:+an+approach+to+the+study+of+nociception.">Thermal avoidance in Caenorhabditis elegans: an approach to the study of nociception.</a> Proc. Natl. Acad. Sci. U.S.A. 96 (18), 10477-10482 (1999).</li></ol>

Não há conflitos de interesse declarados.

O estudo da locomoção e comportamento natural requer técnicas não-invasivas de rastreamento em parceria com técnicas de redução de dados. Aqui demonstramos um fácil de usar sistema de rastreamento que registra imagens detalhadas de C. elegans comportamento, uma vez que se arrasta na superfície de uma placa de agar. A quantidade de informação contida nestas imagens é vasto e de alta-dimensional, e por isso também têm desenvolvido métodos para reduzir a dimensionalidade dos dados em apenas quatro medidas fundamentais. Estas medidas são abrangentes e são fáceis de interpretar em relação ao comportamento worm. Para este trabalho nós mostramos que a transição entre os vermes para a frente e para trás, afirma preferencialmente em diferentes pontos do seu ciclo de ondulatória, uma medida que é difícil de fazer por olho. Este trabalho é complementar de sistemas de seguimento que foram desenvolvidos para medir o comportamento de vermes em baixa ampliação 8,9,10, e também para os sistemas que são capazes de medir ou modular a acti neuronalvity utilizando reagentes codificados geneticamente 11,12. Enquanto rastreamento único organismo é um poderoso método para quantificação de comportamento há algumas limitações da técnica. O primeiro é o facto de que o sistema controla apenas os organismos individuais de cada vez. Em comparação com rastreadores de câmera fixa, que são capazes de rastrear vários organismos 9,10, o rendimento do nosso tracker é baixo. No entanto, somos capazes de medir o comportamento do único organismo por períodos muito mais longos de tempo do que os trackers multi-sem-fim, que é importante para quantificar comportamentos muito tempo escala, tais como a fome, a postura de ovos, e alimentação. Além disso, o rastreador requer imagens que identifiquem claramente o verme do fundo. Isso nos impede de estudar movimentos sem-fim em ambientes que são visualmente desordenado ou muito complexo para o sistema de processamento de imagem para filtrar o worm. Este sistema é flexível e pode ser utilizado para outros tipos de behavirastreamento oral. Em vez de um ambiente homogêneo, o worm pode ser rastreado enquanto submetidos a espacial e temporal informação sensorial, semelhante a outros sistemas de rastreamento. Por exemplo, estímulo térmico pode ser aplicado através de laser de estímulo 7,14, ou informações químicas podem ser aplicados por meio de gradientes espaciais através do ágar 3. O sistema como um todo é flexível na concepção e pode ser usado com sistemas de rastreamento, tais como larvas de Drosophila.

<table border="1"><tbody><tr><td> Nome da peça </td><td> Companhia </td><td> Número de catálogo </td><td> Comentários (opcional) </td></tr><tr><td> Câmera CCD </td><td> Basler </td><td> A601f </td><td></td></tr><tr><td> Lente </td><td> Edmund Optics </td><td> MMS série </td><td></td></tr><tr><td> Iluminação de fibra </td><td> Dolan Jenner </td><td> DC-950H </td><td></td></tr><tr><td> Estágio de tradução </td><td> Deltron </td><td> LS3-4 </td><td></td></tr><tr><td> Stepper Motor </td><td> EUA digitais </td><td> MS23C </td><td></td></tr><tr><td> Motor de passo de unidade </td><td> Lagartixa </td><td> G201 </td><td></td></tr><tr><td> Stepper controle motor </td><td> SimpleStep </td><td> SSXYZ </td><td></td></tr><tr><td></td><td></td><td></td><td> Todo o código de programação está disponível. Por favor, envie um e-mail pedido para o autor correspondente. </td></tr></tbody></table>

c. elegans tracking and behavioral measurement

Nós desenvolvemos técnicas de análise de instrumentação, processamento de imagem e os dados para quantificar o comportamento locomotor de C. elegans, uma vez que rastreia na superfície de uma placa de agar. Para o estudo da base genética, bioquímica, e neuronal de comportamento, C. elegans é um organismo ideal porque é geneticamente tratável, passível de microscopia, e mostra uma série de comportamentos complexos, incluindo táxis, aprendizagem, e 1,2 interação social. Análise comportamental, baseada em acompanhar os movimentos de vermes como eles rastejar sobre placas de agar foram particularmente úteis no estudo do comportamento sensorial 3, 4 locomoção, e fenotipagem geral mutacional 5. O nosso sistema funciona movendo o sistema de câmara de iluminação e como os vermes se arrasta em uma placa de agar estacionário, o que assegura que não haverá estímulo mecânico é transmitido para o sem-fim. O nosso sistema de rastreio é fácil de utilizar e inclui uma característica de calibração semi-automático. Um challenge de todos os sistemas de seguimento de vídeo é que gera uma quantidade enorme de dados que é intrinsecamente elevado dimensional. Nossa programas de processamento de imagem e análise de dados lidar com este desafio, reduzindo a forma vermes em um conjunto de componentes independentes, os quais de forma abrangente reconstruir o comportamento vermes como uma função de apenas 3-4 dimensões 6,7. Como um exemplo do processo mostra-se que o vírus entra e sai do seu estado de inversão de fase de uma forma específica.

Exemplo: Quando forrageamento, C. transições elegans de frente para reverter o movimento, muitas vezes realizando uma reorientação (ômega vez) antes de retornar ao estado de movimento para a frente. Quantificar essa transição é importante para entender os padrões de forrageamento de movimento e também no controle do worm motor. O poder de revelar detalhes sutis de comportamento locomoção pode ser visto através do nosso dispositivo rastreador. Como exemplo, vamos olhar para a frente para reverter e inverter de transmitir a transição através da captura de imagens de alta resolução de vermes rastejantes livremente sobre a placa de ágar para ~ 30 min. é executado. A análise Eigenmodos (Figura 3) que nos permite medir a fase de movimentos ondulatórios do verme. A medida de fase, por sua vez, permite-nos calcular a velocidade do sem-fim e para a frente para inverter transição (Figura 4). Traçando a probabilidade conjunta de velocidade do sem-fim e fase, podemos ver que a transition entre a frente e reverso probabilisticamente acontecer com uma fase preferencial (Figura 5a). Se separar a frente para reverter e inverter de transmitir transições e olhar para a probabilidade condicional de a fase do worm quando entra e sai de um evento de reversão, vemos que eles têm distribuições de fase distintas (Figura 5b, c). <img src="/files/ftp_upload/4094/4094fig1.jpg" alt="Figura 1" /> Figura 1. Seguimento microscópio. A amostra de um verme rastejante em uma placa de agar permanece estacionária, enquanto o sistema de imagem move-se para manter o sem-fim, no centro de visão. O sistema de imagem é construída em um estágio de tradução 2D impulsionado por motores de passo (3). Uma câmera CCD (Basler A601f) e lente (25mm de distância focal) imagens do verme abaixo (1) e uma luz de fibra óptica (Edmunds, modelo) acende-lo de cima (2). Um caseiro de passo controlador do motor utilizando uma simplesep controlador placa (SimpleStep; SSXYZ) controla o movimento do sistema de imagem. Um programa personalizado LabVIEW (National Instruments, Austin, TX, EUA), adquire e processa as imagens dos vermes, ao mesmo tempo, a comunicação com o controlador do motor para manter o sem-fim, no centro do campo. <img src="/files/ftp_upload/4094/4094fig2.jpg" alt="Figura 2" fo:content-width="5in" fo:src="/files/ftp_upload/4094/4094fig2highres.jpg" /> Figura 2. Processamento de imagens. (A) Worms movimentar, alterando a sua curvatura no tempo e no modo que as imagens processadas por vermes parametrização sua linha central. As imagens foram feitas pelo binário thesholding a imagem em escala de cinzento cru (b), e vermes individuais foram identificadas por filtragem objetos por tamanho (c). A distância entre o centro da massa do sem-fim e o centro da imagem e, em seguida, foi calculada a fase foi movido as distâncias adequadas para re-centralizar o worm. Estas distâncias de correção foram utilizados para calcular a trajetória do worm. A curvatura do perímetro verme foi utilizada para identificar a cauda (encurvada) e cabeça (máximo secundário). (D) As imagens foram então esqueletizada para localizar a linha central. (E) A curva resultante foi então então interpolados em 101 segmentos e o ângulo calculado entre os segmentos foi usado para parametrizar a curva. <a href="http://www.jove.com/files/ftp_upload/4094/4094fig2large.jpg" target="_blank">Clique aqui para ver maior figura</a> . <img src="/files/ftp_upload/4094/4094fig3.jpg" alt="Figura 3" fo:content-width="4.75in" fo:src="/files/ftp_upload/4094/4094fig3highres.jpg"/> Figura 3. Eigenmodos cálculo. Curvas fundamentais da forma verme foram calculadas usando a Análise de Componente Princípio 5. Cada curva de sem-fim está representada por uma soma linear dos autovetores (ou eigenworms), onde o<html> amplitude de cada componente é conhecido como o Eigenmodos (modo). Podemos quantificar o comportamento do verme medindo os primeiros 3 autovetores da forma sem-fim ao longo do tempo. <img src="/files/ftp_upload/4094/4094fig4.jpg" alt="Figura 4" fo:content-width="5in" fo:src="/files/ftp_upload/4094/4094fig4highres.jpg"/> Figura 4. Fase e velocidade. (A) A distribuição conjunta dos dois primeiros modos de ciclo limite. (B) A fase de posição sobre este ou ciclo limite correlaciona-se com a fase da posição do verme ondulatória. (C) Utilizando a velocidade de fase dos vermes para a frente e para trás, os movimentos podem ser quantificados. (D) A velocidade e direção ao longo desta ciclos limite indica a velocidade do worm. <a href="http://www.jove.com/files/ftp_upload/4094/4094fig4large.jpg" target="_blank">Clique aqui para ver maior figura</a> . 4094fig5.jpg &quot;alt =&quot; Figura 5 &quot;fo: conteúdo largura =&quot; 4in &quot;fo: src =&quot; files/ftp_upload/4094/4094fig5highres.jpg / &quot;/&gt; Figura 5. Fase de comutação dependente da velocidade. As transições entre os estados para a frente e reversa não ocorrem aleatoriamente ao longo do ciclo oscilatório. Eles (mas ainda estocasticamente) acontecem em fases específicas. (A) A distribuição conjunta da velocidade de fase e da velocidade indica claramente que os vermes sair e entrar no estado para a frente preferencialmente em fases específicas. (B) mostra um gráfico da fase condicionada à entrada para um evento de reversão. (C) mostra a fase condicionada à saída de um evento de reversão. A linha preta é a distribuição de ângulos de fase sem condicionamento em uma saída ou entrada.

Watch this Scientific Journal Video about C. elegans Tracking and Behavioral Measurement at JoVE.com

C. elegans Tracking and Behavioral Measurement

Temos desenvolvido um vídeo taxa de sistema de microscópio de rastreamento que pode gravar e quantificar<em&gt; C. elegans</em&gt; Comportamento de alta resolução e de alta velocidade. Também desenvolvemos métodos computacionais para reduzir a dimensionalidade das imagens sem-fim de um conjunto básico de medições que descrevem completamente a forma do sem-fim.

C. elegans Acompanhamento e Medição do Comportamento

We have developed instrumentation, image processing, and data analysis techniques to quantify the locomotory behavior of C. elegans as it crawls on the ...

c-elegans-tracking-and-behavioral-measurement

Nanyang Technological University

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JoVE Journal

Neuroscience

C. elegans Tracking and Behavioral Measurement

19.0K visualizações.  University of Toronto. Temos desenvolvido um vídeo taxa de sistema de microscópio de rastreamento que pode gravar e quantificar C. elegans Comportamento de alta resolução e de alta velocidade. Também desenvolvemos métodos computacionais para reduzir a dimensionalidade das imagens sem-fim de um conjunto básico de medições que descrevem completamente a forma do sem-fim.

Vídeo: C. elegans Tracking and Behavioral Measurement

Assaying &beta;-amyloid Toxicity using a Transgenic C. elegans Model

Accumulation of the &beta;-amyloid peptide (A&beta;) is generally believed to be central to the induction of Alzheimer's disease, but the relevant mechanism(s) of toxicity are still unclear. A&beta; is also deposited intramuscularly in Inclusion Body Myositis, a severe human myopathy. The intensely studied nematode worm Caenorhabditis elegans can be transgenically engineered to express human A&beta;. Depending on the tissue or timing of A&beta; expression, transgenic worms can have readily measurable phenotypes that serve as a read-out of A&beta; toxicity. For example, transgenic worms with pan-neuronal A&beta; expression have defects is associative learning (Dosanjh et al. 2009), while transgenic worms with constitutive muscle-specific expression show a progressive, age-dependent paralysis phenotype (Link, 1995; Cohen et al. 2006). One particularly useful C. elegans model employs a temperature-sensitive mutation in the mRNA surveillance system to engineer temperature-inducible muscle expression of an A&beta; transgene, resulting in a reproducible paralysis phenotype upon temperature upshift (Link et al. 2003). Treatments that counter A&beta; toxicity in this model [e.g., expression of a protective transgene (Hassan et al. 2009) or exposure to Ginkgo biloba extracts (Wu et al. 2006)] reproducibly alter the rate of paralysis induced by temperature upshift of these transgenic worms. Here we describe our protocol for measuring the rate of paralysis in this transgenic C. elegans model, with particular attention to experimental variables that can influence this measurement.

Assaying &#946;-amyloid Toxicity using a Transgenic C. elegans Model

The intensely studied nematode worm Caenorhabditis elegans can be transgenically engineered to express the human &beta;-amyloid peptide (A&beta;). Induced expression of A&beta; in C. elegans muscle leads to a rapid, reproducible paralysis phenotype that can be used to monitor treatments that modulate A&beta; toxicity.

Assaying Toxicidade β-amilóide utilizando um transgênico C. elegans Modelo

Accumulation of the &beta;-amyloid peptide (A&beta;) is generally believed to be central to the induction of Alzheimer's disease, but the relevant ...

Neurociência

C. elegans Positive Butanone Learning, Short-term, and Long-term Associative Memory Assays

The memory of experiences and learned information is critical for organisms to make choices that aid their survival. C. elegans navigates its environment through neuron-specific detection of food and chemical odors1, 2, and can associate nutritive states with chemical odors3, temperature4, and the pathogenicity of a food source5.
Here, we describe assays of C. elegans associative learning and short- and long-term associative memory. We modified an aversive olfactory learning paradigm6 to instead produce a positive response; the assay involves starving ~400 worms, then feeding the worms in the presence of the AWC neuron-sensed volatile chemoattractant butanone at a concentration that elicits a low chemotactic index (similar to Toroyama et al.7). A standard population chemotaxis assay1 tests the worms' attraction to the odorant immediately or minutes to hours after conditioning.
After conditioning, wild-type animals' chemotaxis to butanone increases ~0.6 Chemotaxis Index units, its "Learning Index". Associative learning is dependent on the presence of both food and butanone during training. Pairing food and butanone for a single conditioning period ("massed training") produces short-term associative memory that lasts ~2 hours. Multiple conditioning periods with rest periods between ("spaced training") yields long-term associative memory (&lt;40 hours), and is dependent on the cAMP Response Element Binding protein (CREB),6 a transcription factor required for long-term memory across species.8
Our protocol also includes image analysis methods for quick and accurate determination of chemotaxis indices. High-contrast images of animals on chemotaxis assay plates are captured and analyzed by worm counting software in MatLab. The software corrects for uneven background using a morphological tophat transformation.9 Otsu's method is then used to determine a threshold to separate worms from the background.10 Very small particles are removed automatically and larger non-worm regions (plate edges or agar punches) are removed by manual selection. The software then estimates the size of single worm by ignoring regions that are above a specified maximum size and taking the median size of the remaining regions. The number of worms is then estimated by dividing the total area identified as occupied by worms by the estimated size of a single worm.
We have found that learning and short- and long-term memory can be distinguished, and that these processes share similar key molecules with higher organisms.6,8 Our assays can quickly test novel candidate genes or molecules that affect learning and short- or long-term memory in C. elegans that are relevant across species.

C. elegans Positive Butanone Learning, Short-term, and Long-term Associative Memory Assays

Here we describe methods to test C. elegans associative learning and short- and long-term associative memory. These population assays employ the worms abilities to chemotax toward volatile odorants, and form positive associations upon pairing food with the chemoattractant butanone. Increasing the number of conditioning periods induces long-term memory.

C. elegans Aprender Butanona Positivo, de curto prazo e de longo prazo Ensaios Memória Associativa

The memory of experiences and learned information is critical for organisms to make choices that aid their survival. C. elegans navigates its environment ...

In vivo Laser Axotomy in C. elegans

Neurons communicate with other cells via axons and dendrites, slender membrane extensions that contain pre- or post-synaptic specializations. If a neuron is damaged by injury or disease, it may regenerate. Cell-intrinsic and extrinsic factors influence the ability of a neuron to regenerate and restore function. Recently, the nematode C. elegans has emerged as an excellent model organism to identify genes and signaling pathways that influence the regeneration of neurons1-6. The main way to initiate neuronal regeneration in C. elegans is laser-mediated cutting, or axotomy. During axotomy, a fluorescently-labeled neuronal process is severed using high-energy pulses. Initially, neuronal regeneration in C. elegans was examined using an amplified femtosecond laser5. However, subsequent regeneration studies have shown that a conventional pulsed laser can be used to accurately sever neurons in vivo and elicit a similar regenerative response1,3,7.
We present a protocol for performing in vivo laser axotomy in the worm using a MicroPoint pulsed laser, a turnkey system that is readily available and that has been widely used for targeted cell ablation. We describe aligning the laser, mounting the worms, cutting specific neurons, and assessing subsequent regeneration. The system provides the ability to cut large numbers of neurons in multiple worms during one experiment. Thus, laser axotomy as described herein is an efficient system for initiating and analyzing the process of regeneration.

In vivo Laser Axotomy in C. elegans

A protocol to cut neurons in C. elegans with a MicroPoint pulsed laser is presented. We describe setting up the system, immobilizing worms, and severing labeled neurons. Advantages include a relatively low-cost system and the ability to sever neuronal processes or ablate cells in vivo.

In vivo Laser axotomia em C. elegans

Neurons communicate with other cells via axons and dendrites, slender membrane extensions that contain pre- or post-synaptic specializations. If a neuron ...

Automated Quantification of Synaptic Fluorescence in C. elegans

Synapse strength refers to the amplitude of postsynaptic responses to presynaptic neurotransmitter release events, and has a major impact on overall neural circuit function. Synapse strength critically depends on the abundance of neurotransmitter receptors clustered at synaptic sites on the postsynaptic membrane. Receptor levels are established developmentally, and can be altered by receptor trafficking between surface-localized, subsynaptic, and intracellular pools, representing important mechanisms of synaptic plasticity and neuromodulation. Rigorous methods to quantify synaptically-localized neurotransmitter receptor abundance are essential to study synaptic development and plasticity. Fluorescence microscopy is an optimal approach because it preserves spatial information, distinguishing synaptic from non-synaptic pools, and discriminating among receptor populations localized to different types of synapses. The genetic model organism Caenorhabditis elegans is particularly well suited for these studies due to the small size and relative simplicity of its nervous system, its transparency, and the availability of powerful genetic techniques, allowing examination of native synapses in intact animals.
Here we present a method for quantifying fluorescently-labeled synaptic neurotransmitter receptors in C. elegans. Its key feature is the automated identification and analysis of individual synapses in three dimensions in multi-plane confocal microscope output files, tabulating position, volume, fluorescence intensity, and total fluorescence for each synapse. This approach has two principal advantages over manual analysis of z-plane projections of confocal data. First, because every plane of the confocal data set is included, no data are lost through z-plane projection, typically based on pixel intensity averages or maxima. Second, identification of synapses is automated, but can be inspected by the experimenter as the data analysis proceeds, allowing fast and accurate extraction of data from large numbers of synapses. Hundreds to thousands of synapses per sample can easily be obtained, producing large data sets to maximize statistical power. Considerations for preparing C. elegans for analysis, and performing confocal imaging to minimize variability between animals within treatment groups are also discussed. Although developed to analyze C. elegans postsynaptic receptors, this method is generally useful for any type of synaptically-localized protein, or indeed, any fluorescence signal that is localized to discrete clusters, puncta, or organelles.
The procedure is performed in three steps: 1) preparation of samples, 2) confocal imaging, and 3) image analysis. Steps 1 and 2 are specific to C. elegans, while step 3 is generally applicable to any punctate fluorescence signal in confocal micrographs.

Automated Quantification of Synaptic Fluorescence in C. elegans

The abundance of neurotransmitter receptors clustered at synapses strongly influences synaptic strength. This method quantifies fluorescently-labeled neurotransmitter receptors in three dimensions with single-synapse resolution in C. elegans, allowing hundreds of synapses to be rapidly characterized within a single sample without distortions introduced by z-plane projection.

Quantificação automatizada de fluorescência em Synaptic<em&gt; C. elegans</em

Synapse strength refers to the amplitude of postsynaptic responses to presynaptic neurotransmitter release events, and has a major impact on overall ...

A Molecular Readout of Long-term Olfactory Adaptation in C. elegans

During sustained stimulation most sensory neurons will adapt their response by decreasing their sensitivity to the signal. The adaptation response helps shape attention and also protects cells from over-stimulation. Adaptation within the olfactory circuit of C. elegans was first described by Colbert and Bargmann1,2. Here, the authors defined parameters of the olfactory adaptation paradigm, which they used to design a genetic screen to isolate mutants defective in their ability to adapt to volatile odors sensed by the Amphid Wing cells type C (AWC) sensory neurons. When wildtype C. elegans animals are exposed to an attractive AWC-sensed odor3 for 30 min they will adapt their responsiveness to the odor and will then ignore the adapting odor in a chemotaxis behavioral assay for ~1 hr. When wildtype C. elegans animals are exposed to an attractive AWC-sensed odor for ~1 hr they will then ignore the adapting odor in a chemotaxis behavioral assay for ~3 hr. These two phases of olfactory adaptation in C. elegans were described as short-term olfactory adaptation (induced after 30 min odor exposure), and long-term olfactory adaptation (induced after 60 min odor exposure). Later work from L'Etoile et al.,4 uncovered a Protein Kinase G (PKG) called EGL-4 that is required for both the short-term and long-term olfactory adaptation in AWC neurons. The EGL-4 protein contains a nuclear localization sequence that is necessary for long-term olfactory adaptation responses but dispensable for short-term olfactory adaptation responses in the AWC4. By tagging EGL-4 with a green fluorescent protein, it was possible to visualize the localization of EGL-4 in the AWC during prolonged odor exposure. Using this fully functional GFP-tagged EGL-4 (GFP::EGL-4) molecule we have been able to develop a molecular readout of long-term olfactory adaptation in the AWC5. Using this molecular readout of olfactory adaptation we have been able to perform both forward and reverse genetic screens to identify mutant animals that exhibit defective subcellular localization patterns of GFP::EGL-4 in the AWC6,7. Here we describe: 1) the construction of GFP::EGL-4 expressing animals; 2) the protocol for cultivation of animals for long-term odor-induced nuclear translocation assays; and 3) the scoring of the long-term odor-induced nuclear translocation event and recovery (re-sensitization) from the nuclear GFP::EGL-4 state.

A Molecular Readout of Long-term Olfactory Adaptation in C. elegans

Here we describe a molecular readout of long-term olfactory adaptation in Caenorhabditis elegans. The Protein Kinase G, EGL-4, is necessary for stable adaptation responses in the primary sensory neuron pair called AWC. During prolonged odor exposure EGL-4 translocates from the cytosol to nucleus of the AWC.

A Leitura Molecular de adaptação a longo prazo olfativa em<em&gt; C. elegans</em

During sustained stimulation most sensory neurons will adapt their response by decreasing their sensitivity to the signal. The adaptation response helps ...

Hippocampal Insulin Microinjection and In vivo Microdialysis During Spatial Memory Testing

Glucose metabolism is a useful marker for local neural activity, forming the basis of methods such as 2-deoxyglucose and functional magnetic resonance imaging. However, use of such methods in animal models requires anesthesia and hence both alters the brain state and prevents behavioral measures. An alternative method is the use of in vivo microdialysis to take continuous measurement of brain extracellular fluid concentrations of glucose, lactate, and related metabolites in awake, unrestrained animals. This technique is especially useful when combined with tasks designed to rely on specific brain regions and/or acute pharmacological manipulation; for example, hippocampal measurements during a spatial working memory task (spontaneous alternation) show a dip in extracellular glucose and rise in lactate that are suggestive of enhanced glycolysis1-3,4-5, and intrahippocampal insulin administration both improves memory and increases hippocampal glycolysis6. Substances such as insulin can be delivered to the hippocampus via the same microdialysis probe used to measure metabolites. The use of spontaneous alternation as a measure of hippocampal function is designed to avoid any confound from stressful motivators (e.g. footshock), restraint, or rewards (e.g. food), all of which can alter both task performance and metabolism; this task also provides a measure of motor activity that permits control for nonspecific effects of treatment. Combined, these methods permit direct measurement of the neurochemical and metabolic variables regulating behavior.

Hippocampal Insulin Microinjection and In vivo Microdialysis During Spatial Memory Testing

Modulation of hippocampally-dependent spatial working memory by direct intrahippocampal microinjection, accompanied and followed by in vivo microdialysis for metabolites in conscious, behaving animals.

Microinjeção insulina hipocampal e<em&gt; Em vivo</em&gt; Microdiálise Durante um teste de memória espacial

Glucose metabolism is a useful marker for local neural activity, forming the basis of methods such as 2-deoxyglucose and functional magnetic resonance ...

A Method for High Fidelity Optogenetic Control of Individual Pyramidal Neurons In vivo

Optogenetic methods have emerged as a powerful tool for elucidating neural circuit activity underlying a diverse set of behaviors across a broad range of species. Optogenetic tools of microbial origin consist of light-sensitive membrane proteins that are able to activate (e.g., channelrhodopsin-2, ChR2) or silence (e.g., halorhodopsin, NpHR) neural activity ingenetically-defined cell types over behaviorally-relevant timescales. We first demonstrate a simple approach for adeno-associated virus-mediated delivery of ChR2 and NpHR transgenes to the dorsal subiculum and prelimbic region of the prefrontal cortex in rat. Because ChR2 and NpHR are genetically targetable, we describe the use of this technology to control the electrical activity of specific populations of neurons (i.e., pyramidal neurons) embedded in heterogeneous tissue with high temporal precision. We describe herein the hardware, custom software user interface, and procedures that allow for simultaneous light delivery and electrical recording from transduced pyramidal neurons in an anesthetized in vivo preparation. These light-responsive tools provide the opportunity for identifying the causal contributions of different cell types to information processing and behavior.

A Method for High Fidelity Optogenetic Control of Individual Pyramidal Neurons In vivo

The recent development of neuroscience tools that combine genetics and optics, termed "optogenetics", enables control over neural circuit activity with an unprecedented level of spatial and temporal resolution. Here we provide a protocol for integrating in vivo recording with optogenetic manipulation of genetically-defined subsets of prefrontal cortical and subicular pyramidal neurons.

Um Método para High Fidelity Optogenetic Controle de Individual Piramidal neurônios<em&gt; In vivo</em

Optogenetic methods  have emerged as a powerful tool for elucidating neural circuit activity  underlying a diverse set of behaviors across a broad range ...

In vivo Neuronal Calcium Imaging in C. elegans

The nematode worm C. elegans is an ideal model organism for relatively simple, low cost neuronal imaging in vivo. Its small transparent body and simple, well-characterized nervous system allows identification and fluorescence imaging of any neuron within the intact animal. Simple immobilization techniques with minimal impact on the animal's physiology allow extended time-lapse imaging. The development of genetically-encoded calcium sensitive fluorophores such as cameleon 1 and GCaMP 2 allow in vivo imaging of neuronal calcium relating both cell physiology and neuronal activity. Numerous transgenic strains expressing these fluorophores in specific neurons are readily available or can be constructed using well-established techniques. Here, we describe detailed procedures for measuring calcium dynamics within a single neuron in vivo using both GCaMP and cameleon. We discuss advantages and disadvantages of both as well as various methods of sample preparation (animal immobilization) and image analysis. Finally, we present results from two experiments: 1) Using GCaMP to measure the sensory response of a specific neuron to an external electrical field and 2) Using cameleon to measure the physiological calcium response of a neuron to traumatic laser damage. Calcium imaging techniques such as these are used extensively in C. elegans and have been extended to measurements in freely moving animals, multiple neurons simultaneously and comparison across genetic backgrounds. C. elegans presents a robust and flexible system for in vivo neuronal imaging with advantages over other model systems in technical simplicity and cost.

In vivo Neuronal Calcium Imaging in C. elegans

With its small transparent body, well-documented neuroanatomy and a host of amenable genetic techniques and reagents, C. elegans makes an ideal model organism for in vivo neuronal imaging using relatively simple, low-cost techniques. Here we describe single neuron imaging within intact adult animals using genetically encoded fluorescent calcium indicators.

Na imagem cálcio vivo Neuronal em C. elegans

The nematode worm C. elegans is an ideal model organism  for relatively simple, low cost neuronal imaging in vivo. Its small transparent body and simple, ...

Long-term Behavioral Tracking of Freely Swimming Weakly Electric Fish

Long-term behavioral tracking can capture and quantify natural animal behaviors, including those occurring infrequently. Behaviors such as exploration and social interactions can be best studied by observing unrestrained, freely behaving animals. Weakly electric fish (WEF) display readily observable exploratory and social behaviors by emitting electric organ discharge (EOD). Here, we describe three effective techniques to synchronously measure the EOD, body position, and posture of a free-swimming WEF for an extended period of time. First, we describe the construction of an experimental tank inside of an isolation chamber designed to block external sources of sensory stimuli such as light, sound, and vibration. The aquarium was partitioned to accommodate four test specimens, and automated gates remotely control the animals&#39; access to the central arena. Second, we describe a precise and reliable real-time EOD timing measurement method from freely swimming WEF. Signal distortions caused by the animal&#39;s body movements are corrected by spatial averaging and temporal processing stages. Third, we describe an underwater near-infrared imaging setup to observe unperturbed nocturnal animal behaviors. Infrared light pulses were used to synchronize the timing between the video and the physiological signal over a long recording duration. Our automated tracking software measures the animal&#39;s body position and posture reliably in an aquatic scene. In combination, these techniques enable long term observation of spontaneous behavior of freely swimming weakly electric fish in a reliable and precise manner. We believe our method can be similarly applied to the study of other aquatic animals by relating their physiological signals with exploratory or social behaviors.

We describe a set of techniques for studying spontaneous behavior of freely swimming weakly electric fish over an extended period of time, by synchronously measuring the animal&#39;s electric organ discharge timing, body position and posture both accurately and reliably in a specially designed aquarium tank inside a sensory isolation chamber.

Longo prazo Behavioral Rastreamento de Livremente Natação fracamente elétrico dos peixes

Long-term behavioral tracking can capture and quantify natural animal behaviors, including those occurring infrequently. Behaviors such as exploration and ...

Visualizing Neuroblast Cytokinesis During C. elegans Embryogenesis

This protocol describes the use of fluorescence microscopy to image dividing cells within developing Caenorhabditis elegans embryos. In particular, this protocol focuses on how to image dividing neuroblasts, which are found underneath the epidermal cells and may be important for epidermal morphogenesis. Tissue formation is crucial for metazoan development&#160;and relies on external cues from neighboring tissues. C. elegans is an excellent model organism to study tissue morphogenesis in vivo due to its transparency and simple organization, making its tissues easy to study via microscopy. Ventral enclosure is the process where the ventral surface of the embryo is covered by a single layer of epithelial cells. This event is thought to be facilitated by the underlying neuroblasts, which provide chemical guidance cues to mediate migration of the overlying epithelial cells. However, the neuroblasts are highly proliferative and also may act as a mechanical substrate for the ventral epidermal cells. Studies using this experimental protocol could uncover the importance of intercellular communication during tissue formation, and could be used to reveal the roles of genes involved in cell division within developing tissues.

Visualizing Neuroblast Cytokinesis During C. elegans Embryogenesis

This protocol describes how to image dividing cells within a tissue in Caenorhabditis elegans embryos. While several protocols describe how to image cell division in the early embryo, this protocol describes how to image cell division within a developing tissue during mid late embryogenesis.

Visualizando neuroblasto Cytokinesis Durante<em&gt; C. elegans</em&gt; Embriogênese

This protocol describes the use of fluorescence microscopy to image dividing cells within developing Caenorhabditis elegans embryos. In particular, this ...