High-Throughput Profiling of Caenorhabditis elegans Starvation-Responsive microRNAs

MicroRNAs (miRNAs) are non-coding RNAs of ~22 nucleotides in length that regulate gene expression by interfering with the stability and translation of mRNAs. Their expression is regulated during development, under a wide variety of stress conditions and in several pathological processes. In nature, animals often face feast or famine conditions. We observed that subjecting early L4 larvae from Caenorhabditis elegans to a 12-hr starvation period produced worms that are thinner and shorter than well-fed animals, with a decreased lipid accumulation, diminished progeny, reduced gonad size, and an increased lifespan. Our objective was to identify which of the 302 known miRNAs of C. elegans changed their expression under starvation conditions as compared to well-fed worms by means of deep sequencing in early L4 larvae. Our results indicate that 13 miRNAs (miR-34-3p, the family of miR-35-3p to miR-41-3p, miR-39-5p, miR-41-5p, miR-240-5p, miR-246-3p and miR-4813-5p) were upregulated, while 2 miRNAs (let-7-3p and miR-85-5p) were downregulated in 12-hr starved vs. well-fed early L4 larvae. Some of the predicted targets of the miRNAs that changed their expression in starvation conditions are involved in metabolic or developmental process. In particular, miRNAs of the miR-35 family were upregulated 6–20 fold upon starvation. Additionally, we showed that the expression of gld-1, important in oogenesis, a validated target of miR-35-3p, was downregulated when the expression of miR-35-3p was upregulated. The expression of another reported target, the cell cycle regulator lin-23, was unchanged during starvation. This study represents a starting point for a more comprehensive understanding of the role of miRNAs during starvation in C. elegans.     

Survival rates of mutant genes under artificial selection using individual and family information

We have used diffusion and branching process methods to investigate fixation rates, probabilities of survival per generation, and times to fixation of mutant genes under different selection methods incorporating individual and family information. Diffusion approximations fit well to simulated results even for large selection coefficients. Methods that give much weight to family information, such as BLUP evaluation which is widely used in animal breeding, reduce fixation rates of mutant genes because of the reduced effective population sizes. In general, it is observed that even mutants with relatively small heterozygous effects (say 0.1 phenotypic standard deviation) are practically ‘safe’ (i.e. their probability of loss from one generation to the next is smaller than, say, 10%) after just a few generations, typically less than 10. For methods of selection with larger effective size, such as within-family selection, the mutant is ‘safe’ in the population somewhat earlier but eventual fixation takes a longer time. Finally we evaluate the amount by which the use of marker assisted selection reduces the fixation probability of newly arisen mutants.     

S-adenosylmethionine decarboxylase from Leishmania donovani. Molecular, genetic, and biochemical characterization of null mutants and overproducers.

The polyamine biosynthetic enzyme, S-adenosylmethionine decarboxylase (ADOMETDC) has been advanced as a potential target for antiparasitic chemotherapy. To investigate the importance of this protein in a model parasite, the gene encoding ADOMETDC has been cloned and sequenced from Leishmania donovani. The Delta adometdc null mutants were created in the insect vector form of the parasite by double targeted gene replacement. The Delta adometdc strains were incapable of growth in medium without polyamines; however, auxotrophy could be rescued by spermidine but not by putrescine, spermine, or methylthioadenosine. Incubation of Delta adometdc parasites in medium lacking polyamines resulted in a drastic increase of putrescine and glutathione levels with a concomitant decrease in the amounts of spermidine and the spermidine-containing thiol trypanothione. Parasites transfected with an episomal ADOMETDC construct were created in both wild type and Delta adometdc parasites. ADOMETDC overexpression abrogated polyamine auxotrophy in the Delta adometdc L. donovani. In addition, ADOMETDC overproduction in wild type parasites alleviated the toxic effects of 5'-(((Z)-4-amino-2-butenyl)methylamino)-5'-deoxyadenosine (MDL 73811), but not pentamidine, berenil, or methylglyoxyl bis(guanylhydrazone), all inhibitors of ADOMETDC activities in vitro. The molecular, biochemical, and genetic characterization of ADOMETDC establishes that it is essential in L. donovani promastigotes and a potential target for therapeutic validation.     

Localization of thymostimulin in mammalian thymuses: comparative evaluation

An anti-thymostimulin (TS) serum was tested on rabbit, guinea-pig, lamb and pig thymuses to study the localization of the hormonal factor. The immuno-peroxidase method, with some modifications, was applied to tissue fixed in Bouin's or in Bouin-PAF liquids and embedded in paraffin wax. Immuno-reactivity was shown in reticulo-epithelial cells in the cortex, in the medulla and in the external cells of the Hassall's corpuscles. The intensity of the immuno-reaction is stronger in pig thymus, whereas in lamb, rabbit and guinea-pig thymuses it is more uniform and pale, but to varying degrees. Comparison with the localization of TS in thymuses of other mammals and man and the problem of species-specificity were discussed.     

Comparing multiple correspondence and principal component analyses with biomechanical signals. Example with turning the steering wheel

The purpose of this article is to compare Principal Component Analysis (PCA) and a much less used method, i.e. MCA (Multiple Correspondence Analysis) with data being first changed into membership values to fuzzy space windows. For such a comparison, data from an experimental study about turning the steering wheel is used. In a didactic perspective, this article only considers one multidimensional signal with 5 components: 3 linked to the steering wheel angle and hand positions and 2 to hand effort variables. A discussion weighs out the pros and the cons of both methods with criteria such as the possibility to show complex relational phenomena, the analysis/computing time or the information loss inherent to the averaging stage (in the perspective to analyze several hundreds of large multidimensional signals).