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Opasic, L.

Publications and source records attributed to Opasic, L..

2 recordsLinked to original sources

Embryo-like features in developing Bacillus subtilis biofilms

Correspondence between evolution and development has been discussed for more than two centuries1. Recent work reveals that phylogeny-ontogeny correlations are indeed present in developmental transcriptomes of eukaryotic clades with complex multicellularity2-10. Nevertheless, it has been largely ignored that the pervasive presence of phylogeny-ontogeny correlations is a hallmark of development in eukaryotes6, 10-12. This perspective opens a possibility to look for similar parallelisms in biological settings where developmental logic and multicellular complexity are more obscure13-16. For instance, it has been increasingly recognized that multicellular behaviour underlies biofilm formation in bacteria13, 14, 17-19. However, it remains unclear whether bacterial biofilm growth shares some basic principles with development in complex eukaryotes14-16, 18, 20. Here we show that the ontogeny of growing Bacillus subtilis biofilms recapitulates phylogeny at the expression level. Using time-resolved transcriptome and proteome profiles, we found that biofilm ontogeny correlates with the evolutionary measures, in a way that evolutionary younger and more diverged genes were increasingly expressed towards later timepoints of biofilm growth. Molecular and morphological signatures also revealed that biofilm growth is highly regulated and organized into discrete ontogenetic stages, analogous to those of eukaryotic embryos11, 21. Together, 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 biofilms22 and that biofilms represent the oldest known fossils23, we anticipate that the widely-adopted vision of the first life as a single-cell and free-living organism needs rethinking.

evolutionary biology↗

How many samples are needed to infer truly clonal mutations from heterogenous tumours?

BackgroundModern cancer treatment strategies aim to target tumour specific genetic (or epigenetic) alterations. Treatment response improves if these alterations are clonal, i.e. present in all cancer cells within tumours. However, the identification of truly clonal alterations is impaired by the tremendous intra-tumour genetic heterogeneity and unavoidable sampling biases.\n\nMethodsHere, we investigate the underlying causes of these spatial sampling biases and how the distribution and sizes of biopsies in sampling protocols can be optimized to minimize such biases.\n\nResultsWe find that in the ideal case, less than a handful of samples can be enough to infer truly clonal mutations. The frequency of the largest sub-clone at diagnosis is the main factor determining the accuracy of truncal mutation estimation in structured tumours. If the first sub-clone is dominating the tumour, higher spatial dispersion of samples and larger sample size can increase the accuracy of the estimation. In such an improved sampling scheme, fewer samples will enable the detection of truly clonal alterations with the same probability.\n\nConclusionsTaking spatial tumour structure into account will decrease the probability to misclassify a sub-clonal mutation as clonal and promises better informed treatment decisions.

cancer biology↗