Vrbanac A et al. (2017) Cell Host Microbe "An Elegan(t) Screen for Drug-Microbe Interactions."

Morton JT, Debelius JW, Knight R, Jiang L, Dorrestein P, Vrbanac A

[Cell Host Microbe, 2017]

Microbes affect drug responses, but mechanisms remain elusive. Two papers in Cell exploit C.elegans to infer anticancer drug mechanisms. Through high-throughput screens of drug-microbe-host interactions, Garcia-Gonzalez etal. (2017) and Scott etal. (2017) determine that bacterial metabolism underpins fluoropyrimidine cytotoxicity, providing a paradigm for unraveling bacterial mechanisms in drug metabolism.

Jose, Antony M. et al. (2009) International Worm Meeting "C. elegans tissues do not require RNA interference to generate and export silencing signals derived from expressed RNAs."

Hunter, Craig P., Garcia, Carlo, Jose, Antony M., Smith, Jessica J.

[International Worm Meeting, 2009]

Double-stranded RNA (dsRNA) triggers RNA interference (RNAi) to silence genes of matching sequence. RNAi-like mechanisms underlie key cellular processes such as heterochromatin formation, regulation of gene expression, and silencing of repetitive DNA. In some animals, when exogenous dsRNA is introduced into a cell, the resultant silencing is transported to other cells. However, numerous dsRNAs and hairpin RNAs (hpRNAs) are transcribed from animal genomes but whether expressed RNAs and endogenous RNAi-like mechanisms generate mobile silencing signals is unknown. Studies in C. elegans have shown that the conserved dsRNA channel Systemic RNAi Defective-1 (SID-1) is required for the import of transported silencing signals. We found that the efficient silencing of multicopy transgenes requires SID-1, suggesting that transgene silencing in one cell produces mobile silencing signals that function to initiate and/or maintain transgene silencing in another cell. Further, the tissue-specific expression of RNAi triggers resulted in the transport of silencing from all tested tissues to other tissues, consistent with expressed RNAi triggers generating mobile silencing signals. Although import through SID-1 suggests that mobile silencing signals are likely forms of dsRNA, their precise identity and biogenesis are unknown. We reasoned that proteins that act on dsRNA for RNAi within a cell may modify dsRNA or other dsRNA-derived RNAs to generate mobile silencing signals. Therefore, we examined the role of RNAi Defective-1 (RDE-1), an Argonaute protein required for RNAi in C. elegans, in the export of mobile silencing signals. In rde-1(-) animals, when gfp-dsRNA was expressed in the pharynx, no silencing of GFP expression was detected in either the pharynx or the body wall muscles. However, when rde-1(+) was expressed specifically in the body wall muscles of these animals, gfp expression was silenced only in that tissue. Consistent with the export of mobile silencing signals from an rde-1(-) pharynx, GFP expression in the pharynx remained unaffected. Thus, RNAi-mediated degradation of target mRNA is not required for the generation and export of mobile silencing signals derived from transgenically expressed RNAi triggers. We are systematically testing additional components and regulators of the RNAi pathway for possible roles in the generation of mobile silencing signals.

Torfeh E et al. (2019) Sci Rep "Monte-Carlo dosimetry and real-time imaging of targeted irradiation consequences in 2-cell stage Caenorhabditis elegans embryo."

Bourret S, Seznec H, Muggiolu G, Deves G, Incerti S, Vianna F, Torfeh E, Barberet P, Simon M

[Sci Rep, 2019]

Charged-particle microbeams (CPMs) provide a unique opportunity to investigate the effects of ionizing radiation on living biological specimens with a precise control of the delivered dose, i.e. the number of particles per cell. We describe a methodology to manipulate and micro-irradiate early stage C. elegans embryos at a specific phase of the cell division and with a controlled dose using a CPM. To validate this approach, we observe the radiation-induced damage, such as reduced cell mobility, incomplete cell division and the appearance of chromatin bridges during embryo development, in different strains expressing GFP-tagged proteins in situ after irradiation. In addition, as the dosimetry of such experiments cannot be extrapolated from random irradiations of cell populations, realistic three-dimensional models of 2 cell-stage embryo were imported into the Geant4 Monte-Carlo simulation toolkit. Using this method, we investigate the energy deposit in various chromatin condensation states during the cell division phases. The experimental approach coupled to Monte-Carlo simulations provides a way to selectively irradiate a single cell in a rapidly dividing multicellular model with a reproducible dose. This method opens the way to dose-effect investigations following targeted irradiation.

Berriz GF et al. (2003) Bioinformatics "Characterizing gene sets with FuncAssociate."

Berriz GF, King OD, Bryant B, Roth FP, Sander C

[Bioinformatics, 2003]

SUMMARY: FuncAssociate is a web-based tool to help researchers use Gene Ontology attributes to characterize large sets of genes derived from experiment. Distinguishing features of FuncAssociate include the ability to handle ranked input lists, and a Monte Carlo simulation approach that is more appropriate to determine significance than other methods, such as Bonferroni or idk p-value correction. FuncAssociate currently supports 10 organisms (Vibrio cholerae, Shewanella oneidensis, Saccharomyces cerevisiae, Schizosaccharomyces pombe, Arabidopsis thaliana, Caenorhaebditis elegans, Drosophila melanogaster, Mus musculus, Rattus norvegicus and Homo sapiens). AVAILABILITY: FuncAssociate is freely accessible at http://llama.med.harvard.edu/Software.html. Source code (in Perl and C) is freely available to academic users ''as is''.

Fan LY et al. (2017) Data Brief "Dataset of the human homologues and orthologues of lipid-metabolic genes identified as DAF-16 targets their roles in lipid and energy metabolism."

Fan LY, Lam EW, Saavedra-Garcia P

[Data Brief, 2017]

The data presented in this article are related to the review article entitled 'Unravelling the role of fatty acid metabolism in cancer through the FOXO3-FOXM1 axis' (Saavedra-Garcia et al., 2017) [24]. Here, we have matched the DAF-16/FOXO3 downstream genes with their respective human orthologues and reviewed the roles of these targeted genes in FA metabolism. The list of genes listed in this article are precisely selected from literature reviews based on their functions in mammalian FA metabolism. The nematode Caenorhabditis elegans gene orthologues of the genes are obtained from WormBase, the online biological database of C. elegans. This dataset has not been uploaded to a public repository yet.

Hong F et al. (2006) Biometrics "Functional hierarchical models for identifying genes with different time-course expression profiles."

Hong F, Li H

[Biometrics, 2006]

Time-course studies of gene expression are essential in biomedical research to understand biological phenomena that evolve in a temporal fashion. We introduce a functional hierarchical model for detecting temporally differentially expressed (TDE) genes between two experimental conditions for cross-sectional designs, where the gene expression profiles are treated as functional data and modeled by basis function expansions. A Monte Carlo EM algorithm was developed for estimating both the gene-specific parameters and the hyperparameters in the second level of modeling. We use a direct posterior probability approach to bound the rate of false discovery at a pre-specified level and evaluate the methods by simulations and application to microarray time-course gene expression data on Caenorhabditis elegans developmental processes. Simulation results suggested that the procedure performs better than the two-way ANOVA in identifying TDE genes, resulting in both higher sensitivity and specificity. Genes identified from the C. elegans developmental data set show clear patterns of changes between the two experimental conditions.

Barbieri, Sofia et al. (2021) International Worm Meeting "The dynamic partnered dance between PLK-1 and MEX-5: interpreting gradient formation with computational modelling."

Gotta, Monica, Barbieri, Sofia, Griffin, Erik E., Nurni Ravi, Aparna

[International Worm Meeting, 2021]

In C. elegans embryos, PLK-1 is pivotal for cell division and it orchestrates polarity establishment together with its binding partner, MEX-5. To achieve this, their localization/activity must be precisely regulated. MEX-5 enrichment at the anterior cytoplasm results from a change in its diffusivity following uneven phosphorylation along the embryo axis. We know PLK-1 relocalization to the anterior depends on MEX-5. However, the biological and physical mechanisms behind the dynamics of this protein are still poorly described. To address this, PLK-1 and MEX-5 gradient formation was measured in two CRISPR strains and significant discrepancies were revealed between the two proteins in terms of: 1) gradient steepness, as PLK-1 forms a less steep gradient compared to MEX-5; 2) dynamics, with PLK-1 gradient establishment delayed and slower; 3) diffusivity, as PLK-1 diffusion coefficient does not correspond to MEX-5's one from anterior to posterior. To shed light on PLK-1 dynamics, and how it is intertwined to MEX-5, we developed a novel Monte Carlo simulation framework able to recreate the protein motions in the C. elegans one-cell embryo. Thanks to our computational approach, we were able to postulate on the biological mechanisms behind MEX-5 and PLK-1 dynamics during the whole cell division, from early embryos to the steady-state before cytokinesis. The simulations succeed in reproducing PLK-1 gradient formation, in agreement with experimental measurements, if: 1) PLK-1 binds to phosphorylated MEX-5; 2) the binding is triggered after a defined time delay; 3) PLK-1 dynamically interacts with MEX-5, leading to a continuous replenishment of a pool of unbound PLK-1. The Monte Carlo framework we propose can eventually be applied to other polarity-related factors or mutants in which polarization is perturbed, to understand if it can be traced back to a failure in PLK-1 localization. Finally, conditions where gradient formation is altered, like after stress, can be simulated.

Dengg M. et al. (2006) European Worm Meeting "Using Caenorhabditis elegans to Study Cellular Responses to Endogenous DNA Damage"

Boulton S., Nilsen H., Garcia-Muse T., Dengg M.

[European Worm Meeting, 2006]

Dengg, M. 1, Garcia-Muse, T.2, Boulton, S.2, and Nilsen, H1 DNA repair pathways and intracellular signalling cascades contribute to DNA damage response (DDR) mechanisms that determine cellular responses to DNA damage. C.elegans has been used successfully to study DDR in response to DNA damage induced by physical or chemical agents. Whether DDR is activated in response to the most abundant forms of DNA damage, arising spontaneously through the reaction of water and reactive oxygen species with DNA, is poorly understood. Compared with treatment with physical or chemical DNA damaging agents, the study of DDR in response to endogenous lesions must overcome technical problems with respect to inducing sufficiently high levels of DNA lesions to allow studies of downstream responses. We have exploited RNA interference (RNAi) technology in C.elegans to modulate dUTP pools in order to achieve incorporation of uracil above background levels. Here, we present data describing the phenotypical consequences of increased incorporation of uracil into DNA. The role of DNA repair and DNA damage checkpoints in activating DNA damage response pathways in response to uracil will be presented.

Rivas E et al. (2000) Bioinformatics "Secondary structure alone is generally not statistically significant for the detection of noncoding RNAs."

Rivas E, Eddy SR

[Bioinformatics, 2000]

MOTIVATION: Several results in the literature suggest that biologically interesting RNAs have secondary structures that are more stable than expected by chance. Based on these observations, we developed a scanning algorithm for detecting noncoding RNA genes in genome sequences, using a fully probabilistic version of the Zuker minimum-energy folding algorithm. RESULTS: Preliminary results were encouraging, but certain anomalies led us to do a carefully controlled investigation of this class of methods. Ultimately, our results argue that for the probabilistic model there is indeed a statistical effect, but it comes mostly from local base-composition bias and not from RNA secondary structure. For the thermodynamic implementation (which evaluates statistical significance by doing Monte Carlo shuffling in fixed-length sequence windows, thus eliminating the base-composition effect) the signals for noncoding RNAs are still usually indistinguishable from noise, especially when certain statistical artifacts resulting from local base-composition inhomogeneity are taken into account. We conclude that although a distinct, stable secondary structure is undoubtedly important in most noncoding RNAs, the stability of most noncoding RNA secondary structures is not sufficiently different from the predicted stability of a random sequence to be useful as a general genefinding approach.

Wu Y et al. (2024) Brief Bioinform "Reconstruction of gene regulatory networks for Caenorhabditis elegans using tree-shaped gene expression data."

Hu J, Wu Y, Zhou D

[Brief Bioinform, 2024]

Constructing gene regulatory networks is a widely adopted approach for investigating gene regulation, offering diverse applications in biology and medicine. A great deal of research focuses on using time series data or single-cell RNA-sequencing data to infer gene regulatory networks. However, such gene expression data lack either cellular or temporal information. Fortunately, the advent of time-lapse confocal laser microscopy enables biologists to obtain tree-shaped gene expression data of Caenorhabditis elegans, achieving both cellular and temporal resolution. Although such tree-shaped data provide abundant knowledge, they pose challenges like non-pairwise time series, laying the inaccuracy of downstream analysis. To address this issue, a comprehensive framework for data integration and a novel Bayesian approach based on Boolean network with time delay are proposed. The pre-screening process and Markov Chain Monte Carlo algorithm are applied to obtain the parameter estimates. Simulation studies show that our method outperforms existing Boolean network inference algorithms. Leveraging the proposed approach, gene regulatory networks for five subtrees are reconstructed based on the real tree-shaped datatsets of Caenorhabditis elegans, where some gene regulatory relationships confirmed in previous genetic studies are recovered. Also, heterogeneity of regulatory relationships in different cell lineage subtrees is detected. Furthermore, the exploration of potential gene regulatory relationships that bear importance in human diseases is undertaken. All source code is available at the GitHub repository https://github.com/edawu11/BBTD.git.