RESUMEN
Laser electrospray mass spectrometry (LEMS) with offline classification is used to discriminate plant tissues at atmospheric pressure using an intense (10(13) W cm(-2)), nonresonant (800 nm) femtosecond laser pulse to vaporize cellular content for subsequent mass analysis. The tissue content of the plant within the 0.05 mm(2) laser interaction region is vaporized into the electrospray plume where the molecules are ionized prior to transfer into the mass spectrometer. The measurements for a flower petal, leaf, and stem of an impatiens plant reveal mass spectral signatures that enable discrimination as performed using a compressive linear classifier. The statistical analysis of the plant tissue samples reveals reproducibility of the data for replicate tissue samples and within a single tissue sample. A similar degree of discrimination was achieved for the green and white regions of aphelandra squarrosa (zebra plant) leaves.
Asunto(s)
Acanthaceae/química , Acanthaceae/citología , Impatiens/química , Impatiens/citología , Rayos Láser , Espectrometría de Masas/métodos , Componentes Aéreos de las Plantas/química , Componentes Aéreos de las Plantas/citología , Reproducibilidad de los Resultados , Factores de TiempoRESUMEN
Polycystic kidney disease (PKD) is a common human genetic disease with severe medical consequences. Although it is appreciated that the cilium plays a central role in PKD, the underlying mechanism for PKD remains poorly understood and no effective treatment is available. In zebrafish, kidney cyst formation is closely associated with laterality defects and body curvature. To discover potential drug candidates and dissect signaling pathways that interact with ciliary signals, we performed a chemical modifier screen for the two phenotypes using zebrafish pkd2(hi4166) and ift172(hi2211) models. pkd2 is a causal gene for autosomal dominant PKD and ift172 is essential for building and maintaining the cilium. We identified trichostatin A (TSA), a pan-HDAC (histone deacetylase) inhibitor, as a compound that affected both body curvature and laterality. Further analysis verified that TSA inhibited cyst formation in pkd2 knockdown animals. Moreover, we demonstrated that inhibiting class I HDACs, either by valproic acid (VPA), a class I specific HDAC inhibitor structurally unrelated to TSA, or by knocking down hdac1, suppressed kidney cyst formation and body curvature caused by pkd2 deficiency. Finally, we show that VPA was able to reduce the progression of cyst formation and slow the decline of kidney function in a mouse ADPKD model. Together, these data suggest body curvature may be used as a surrogate marker for kidney cyst formation in large-scale high-throughput screens in zebrafish. More importantly, our results also reveal a critical role for HDACs in PKD pathogenesis and point to HDAC inhibitors as drug candidates for PKD treatment.
Asunto(s)
Modelos Animales de Enfermedad , Inhibidores de Histona Desacetilasas/farmacología , Enfermedades Renales Poliquísticas/tratamiento farmacológico , Animales , Técnicas de Silenciamiento del Gen , Genes Dominantes , Inhibidores de Histona Desacetilasas/uso terapéutico , Histona Desacetilasas/genética , Ácidos Hidroxámicos/farmacología , Ácidos Hidroxámicos/uso terapéutico , Fenotipo , Enfermedades Renales Poliquísticas/genética , Ácido Valproico/farmacología , Ácido Valproico/uso terapéutico , Pez CebraRESUMEN
We describe a trainable system for analyzing videos of developing C. elegans embryos. The system automatically detects, segments, and locates cells and nuclei in microscopic images. The system was designed as the central component of a fully automated phenotyping system. The system contains three modules 1) a convolutional network trained to classify each pixel into five categories: cell wall, cytoplasm, nucleus membrane, nucleus, outside medium; 2) an energy-based model, which cleans up the output of the convolutional network by learning local consistency constraints that must be satisfied by label images; 3) a set of elastic models of the embryo at various stages of development that are matched to the label images.
Asunto(s)
Inteligencia Artificial , Caenorhabditis elegans/anatomía & histología , Caenorhabditis elegans/embriología , Interpretación de Imagen Asistida por Computador/métodos , Microscopía de Contraste de Fase/métodos , Microscopía por Video/métodos , Reconocimiento de Normas Patrones Automatizadas/métodos , Fenotipo , Algoritmos , Animales , Caenorhabditis elegans/clasificación , Caenorhabditis elegans/crecimiento & desarrollo , Embrión no Mamífero/citología , Desarrollo Fetal/fisiología , Aumento de la Imagen/métodos , Reproducibilidad de los Resultados , Sensibilidad y EspecificidadRESUMEN
Various biological processes exhibit characteristics that vary dramatically in response to different input conditions or changes in the history of the process itself. One of the examples studied here, the Ras-PKC-mitogen-activated protein kinase (MAPK) bistable pathway, follows two distinct dynamics (modes) depending on duration and strength of EGF stimulus. Similar examples are found in the behavior of the cell cycle and the immune system. A classification methodology, based on time-frequency analysis, was developed and tested on these systems to understand global behavior of biological processes. Contrary to most traditionally used statistical and spectral methods, our approach captures complex functional relations between parts of the systems in a simple way. The resulting algorithms are capable of analyzing and classifying sets of time-series data obtained from in vivo or in vitro experiments, or in silico simulation of biological processes. The method was found to be considerably stable under stochastic noise perturbation and, therefore, suitable for the analysis of real experimental data.
Asunto(s)
Algoritmos , Ciclo Celular/fisiología , Inmunidad/fisiología , Modelos Teóricos , Transducción de Señal/fisiología , Biología de Sistemas , Proteínas Quinasas Activadas por Mitógenos/metabolismo , Proteína Quinasa C/metabolismo , Factores de Tiempo , Proteínas ras/metabolismoRESUMEN
We used a maskless photolithography method to produce DNA oligonucleotide microarrays with unique probe sequences tiled throughout the genome of Drosophila melanogaster and across predicted splice junctions. RNA expression of protein coding and nonprotein coding sequences was determined for each major stage of the life cycle, including adult males and females. We detected transcriptional activity for 93% of annotated genes and RNA expression for 41% of the probes in intronic and intergenic sequences. Comparison to genome-wide RNA interference data and to gene annotations revealed distinguishable levels of expression for different classes of genes and higher levels of expression for genes with essential cellular functions. Differential splicing was observed in about 40% of predicted genes, and 5440 previously unknown splice forms were detected. Genes within conserved regions of synteny with D. pseudoobscura had highly correlated expression; these regions ranged in length from 10 to 900 kilobase pairs. The expressed intergenic and intronic sequences are more likely to be evolutionarily conserved than nonexpressed ones, and about 15% of them appear to be developmentally regulated. Our results provide a draft expression map for the entire nonrepetitive genome, which reveals a much more extensive and diverse set of expressed sequences than was previously predicted.