Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1032130 | ENA |
REPOSITORIES: ENA
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Project description:Correspondence between evolution and development has been discussed for more than two centuries. Recent work reveals that phylogeny-ontogeny correlations are indeed present in developmental transcriptomes of eukaryotic clades with complex multicellularity. Nevertheless, it has been largely ignored that the pervasive presence of phylogeny-ontogeny correlations is likely a hallmark of development in eukaryotes. This perspective opens a possibility to look for similar parallelisms in biological settings where developmental logic and multicellular complexity are more obscure. For instance, it has been increasingly recognized that multicellular behavior underlies biofilm formation in bacteria. However, it remains unclear whether bacterial biofilm growth shares some basic principles with development in complex eukaryotes. Here we show that ontogeny of growing Bacillus subtilis biofilms recapitulates phylogeny at the expression level. Using finely resolved transcriptome and proteome profiles, we found that biofilm ontogeny correlates with the evolutionary measures. Early-stage biofilms expressed older and more conserved genes, while later-stage biofilms progressively used evolutionary younger and more diverged genes. Molecular and morphological signatures also revealed that biofilm growth is highly regulated and organized into discrete ontogenetic stages, similar to those of eukaryotic embryos. In conjunction this suggests that biofilm formation in Bacillus is a bona fide developmental process comparable to organismal development in animals, plants and fungi. Given that most cells on Earth reside in the form of biofilms and that biofilms represent the oldest known fossils, we anticipate that the widely-adopted vision of the first life as a single-cell and free-living organism needs rethinking.
2020-10-07 | PXD016656 | Pride
Project description:Genotyping studies suggest that there is genetic variability among P. gingivalis strains, however the extent of variability remains unclear, and the regions of variability have only partially been identified. We previously used heteroduplex analysis of the ribosomal operon intergenic spacer region (ISR) to type P. gingivalis strains in several diverse populations, identifying 6 predominant heteroduplex types and many minor ones. In addition we used ISR sequence analysis to determine the relatedness of P. gingivalis strains to one another, and demonstrated a link between ISR sequence phylogeny and the disease-associated phenotype of P. gingivalis strains. The availability of whole genome microarrays based on the genomic sequence of strain W83 has allowed a more comprehensive analysis of P. gingivalis strain variability, using the entire genome. The objectives of this study were to define the phylogeny of P. gingivalis strains using the entire genome, to compare the phylogeny based on genome content to the phylogeny based on a single locus (ISR), and to identify genes that are associated with the strongly disease-associated strain W83 that could be important for virulence. Keywords: Comparative genomic hybridization
2008-10-09 | GSE13128 | GEO
Project description:Variant antigens that are encoded by large multigene families play an important role in the adaptation and immune evasion of a wide range of pathogens. However, the study of their biological function is significantly hampered by the difficulty in controlling their expression in its cellular setting. The genomes of Plasmodium spp. encode a number of different multigene families that are thought to play a critical role for their survival. However, with the exception of the P. falciparum var genes very little is known about the biological roles of any of the other multigene families. Here we report a highly efficient genetic system to study variant antigens in Plasmodium spp. using the Selection Linked Integration method; we are able to activate the expression of a single member of a multigene of our choice using its endogenous promoter.
2020-07-03 | GSE152162 | GEO
Project description:Single-Cell Genotyping of Transcriptomes
| PRJNA483238 | ENA