WormBase: a modern Model Organism Information Resource

Harris, Todd W.; Arnaboldi, Valerio; Cain, Scott; Chan, Juancarlos; Chen, Wen J.; Cho, Jae‐Hyoung; Davis, Paul A.; Gao, Sibyl; Grove, Christian A.; Kishore, Ranjana; Lee, Raymond Y. N.; Müller, Hans‐Michael; Nakamura, Cecilia; Nuin, Paulo; Paulini, Michael; Raciti, Daniela; Rodgers, Faye H.; Russell, Matthew; Schindelman, Gary; Auken, Kimberly Van; Wang, Qinghua; Williams, Gary W.; Wright, Adam; Yook, Karen; Howe, Kevin; Schedl, Tim; Stein, Lincoln; Sternberg, Paul W.

doi:10.1093/nar/gkz920

Cited by 258 publications

(330 citation statements)

References 17 publications

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“…Raw reads were mapped to indexed transcriptomes using Kallisto version 0.46.0 (BRAY et al 2016) then total counts were rounded to the nearest integer and imported into R version 5.1.3 (R DEVELOPMENT CORE TEAM 2015) for analysis. We used all mRNA transcripts from D. melanogaster FlyBase release r6.30 (THURMOND et al 2019) and the longest transcripts from C. elegans WormBase release WBcel235 (HARRIS et al 2020) as references. We assessed differential expression of transcripts using DESeq2 (LOVE et al 2014).…”

Section: Gene Expression Quantificationmentioning

confidence: 99%

“…A handful of genes were significantly differentially expressed (in the same direction) in both flies and worms when comparing exposure to E. faecalis to Pseudomonas or Providencia (Table 1). Genes differentially expressed comparing infection with P. rettgeri to E. faecalis: ade2/pfas-1 was significantly Gram-positive biased after exposure and is a phosphoribosylformylglycinamidine synthase and is involved in purine synthesis and is expressed in the fat body in Drosophila and the intestines in Caenorhabditis (THURMOND et al 2019;HARRIS et al 2020). CG6218/W06B4.2 was gram-negative biased in both animals and is a N-acetylglucosamine kinase involved in carbohydrate phosphorylation and influences dauer lifespan in Caenorhabditis (XIE AND ROY 2012).…”

Section: We Measured Gene Expression After Four Different Treatmentsmentioning

confidence: 99%

“…Pseudomonas to E. faecalis: CG14210/Y40B1B.7 was Gram-positive biased in both animals but is poorly characterized and is an ortholog of the human CCDC86 gene (coiled-coil domain containing 86) which localizes to the nucleolus(THURMOND et al 2019;HARRIS et al 2020). NUCB1/nucb-1 was Gram-negative biased in both animals and is a nucleobindin protein involved in defense against Gram-negative bacteria in Drosophila(BERKEY et al 2009) and is expressed in the intestines of Caenorhabditis(HARRIS et al 2020).Galt/ZK1058.3 was Gram-positive biased in both animals is a galactose-1-phosphate uridylyltransferase associated with galactose homeostasis in Drosophila and without phenotypic data in Caenorhabditis(THURMOND et al 2019). In addition, Galt was upregulated in Drosophila after infection with Octosporea (a microsporidian that normally infects Daphnia)(ROXSTROM-LINDQUIST et al 2004).…”

mentioning

confidence: 99%

“…In addition, Galt was upregulated in Drosophila after infection with Octosporea (a microsporidian that normally infects Daphnia)(ROXSTROM-LINDQUIST et al 2004). Esyt2/esyt-2 was Gramnegative biased and is a synaptotagmin-like protein involved in lipid transport, among other things(THURMOND et al 2019;HARRIS et al 2020).…”

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confidence: 99%

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A comparative analysis ofCaenorhabditisandDrosophilatranscriptional changes in response to pathogen infection

Unckless

Lansdon

Ackley

2020

Preprint

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We analyzed transcriptomic data from C. elegans and D. melanogaster to compare the expression of orthologous pairs of genes in response to bacterial pathogens. Our results indicated that only a handful of genes that are orthologous between species are differentially expressed in response to pathogens, but that the pattern of expression was different when comparing one-to-one orthologs versus those that are restricted to one of the two organisms.These results suggest that, although broad patterns of susceptibility to bacterial pathogens are conserved, the regulatory framework by which the organisms fight pathogens is less well conserved. Further our results suggest a more complete analysis of the evolutionary changes in organismal responses to pathogens is required.Immune divergence in invertebrates 3 | P a g e Abstract Drosophila melanogaster and Caenorhabditis elegans are well-used invertebrate models for studying the innate immune system. The organisms are susceptible to bacterial pathogens that include Pseudomonas species, (entomophilia -Drosophila) or (aeruginosa -Caenorhabditis), E. faecalis and P. rettgeri, which are or are related to human pathogens. Further, the consequences of exposure to these pathogens, in terms of organismal survival, are roughly equivalent when compared. That is, worms and flies are more susceptible to infection by Pseudomonas than E. faecalis, whereas organismal survival on E. faecalis and P. rettgeri are roughly the same in both. To better understand how these organisms are coordinating their responses to these bacterial pathogens we examined transcriptomes in infected animals. We grouped our analysis based on protein orthology. Of the 3611 pairs analyzed, we found genes whose responses were conserved across the different species at a higher than expected rate for two of the three pathogens. Interestingly within the animals, genes with 1:1 orthologs between species behaved differently. Such genes were more likely to be expressed in D. melanogaster, and less likely to be expressed in C. elegans. From this analysis we found that the gene nucleobindin (nucb-1/NUCB1 in C. elegans and D. melanogaster, respectively) was upregulated in both species in response to Gram negative bacteria. We used RNAi to knock down nucb-1 and found the treated animals were more susceptible to infection by the Gram negative pathogen P. rettgeri than controls. These results provide insight into some of the conserved mechanisms of pathogen defense, but also suggest that these divergent organisms have evolved specific means to orchestrate the defense against pathogens.Immune divergence in invertebrates 4 | P a g e

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Section: Gene Expression Quantificationmentioning

confidence: 99%

Section: We Measured Gene Expression After Four Different Treatmentsmentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

confidence: 99%

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A comparative analysis ofCaenorhabditisandDrosophilatranscriptional changes in response to pathogen infection

Unckless

Lansdon

Ackley

2020

Preprint

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“…Two main variables in the design of our version of the CDK biosensor that could contribute to a lack of strong nuclear exclusion during G2 were the selection of promoter and/or the selection of fluorescent protein fused to DHB. To test these variables, we generated a new transgenic line expressing DHB under a different ribosomal promoter, rps-0, which, like rps-27 is ubiquitously expressed, though based on quantification of publicly available RNA-seq data, at approximately 25% (3722-4078 FPKM) that of rps-27 during the L3 and L4 stages (9019-13227 FPKM) (Celniker et al, 2009;Harris et al, 2019). Quantification of VPC division time-lapse data collected using rps-0>DHB::GFP revealed a higher peak value during G2: 1.37 ± 0.45 (n = 33; Figure 2B-D).…”

Section: Characterizing the Dynamic Range Of The C Elegans Cdk Biosementioning

confidence: 99%

Visualizing the metazoan proliferation-terminal differentiation decisionin vivo

Kohrman

Adikes

Martinez

et al. 2019

Preprint

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During organismal development, differential regulation of the cell cycle is critical to many cell biological processes, including cell fate specification and differentiation. While the mechanisms of cell cycle regulation are well studied, how control of the cell cycle is linked to differentiated cellular behavior remains poorly understood, mostly due to our inability to directly and precisely measure cell cycle state. In order to characterize cell cycle state live, we adapted a cyclindependent kinase (CDK) biosensor for in vivo use in the roundworm nematode, Caenorhabditis elegans. The CDK biosensor measures the cytoplasmic-to-nuclear localization of a portion of human DNA Helicase B (DHB) fused to a fluorescent protein to assess cell cycle state. The dynamic localization of DHB results from phosphorylation of the biosensor by CDKs, thereby allowing for quantitative assessment of cell cycle state. We demonstrate here the use of this biosensor to quantify lineage-specific differences between cycling cells and to examine the proliferation-differentiation decision. Unlike other live cell imaging tools (e.g., FUCCI), we show that DHB can be used to distinguish between actively cycling cells in the G1 phase of the cell cycle and terminally differentiated cells exited in G0. Thus, we provide here a new resource to study the control and timing of the metazoan cell cycle during cell fate specification and differentiation.

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Artificial intelligence for neurodegenerative experimental models

Marzi,

Schilder,

Nott

et al. 2023

Alzheimer's & Dementia

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INTRODUCTIONExperimental models are essential tools in neurodegenerative disease research. However, the translation of insights and drugs discovered in model systems has proven immensely challenging, marred by high failure rates in human clinical trials.METHODSHere we review the application of artificial intelligence (AI) and machine learning (ML) in experimental medicine for dementia research.RESULTSConsidering the specific challenges of reproducibility and translation between other species or model systems and human biology in preclinical dementia research, we highlight best practices and resources that can be leveraged to quantify and evaluate translatability. We then evaluate how AI and ML approaches could be applied to enhance both cross‐model reproducibility and translation to human biology, while sustaining biological interpretability.DISCUSSIONAI and ML approaches in experimental medicine remain in their infancy. However, they have great potential to strengthen preclinical research and translation if based upon adequate, robust, and reproducible experimental data.Highlights There are increasing applications of AI in experimental medicine. We identified issues in reproducibility, cross‐species translation, and data curation in the field. Our review highlights data resources and AI approaches as solutions. Multi‐omics analysis with AI offers exciting future possibilities in drug discovery.

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WormBase: a modern Model Organism Information Resource

Cited by 258 publications

References 17 publications

A comparative analysis ofCaenorhabditisandDrosophilatranscriptional changes in response to pathogen infection

A comparative analysis ofCaenorhabditisandDrosophilatranscriptional changes in response to pathogen infection

Visualizing the metazoan proliferation-terminal differentiation decisionin vivo

Artificial intelligence for neurodegenerative experimental models

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