A combination of recent advancements in molecular recording devices and sequencing technologies has made it possible to generate lineage tracing data on the order of thousands of cells. Dynamic lineage recorders are able to generate random, heritable mutations which accumulate continuously on the timescale of developmental processes; this genetic information is then recovered using single-cell RNA sequencing. These data have the potential to hold rich phylogenetic information due to the irreversible nature of the editing process, a key feature of the employed CRISPR-based systems that deviates from traditional assumptions about molecular mutation processes. Recent technologies have furthermore made it possible for mutations to be acquired sequentially. Understanding the information content of these recorders remains an open area of investigation. Here, we model a sequentially-edited recording system and analyse the experimental conditions over which exact phylogenetic reconstruction occurs with high probability. We find, using simulation and theory, explicit parameter regimes over which simple and efficient distance-based reconstruction methods can accurately resolve the cellular phylogeny. We furthermore illustrate how our theoretical results could be used to help inform experimental design.

Bacterial lineages are relatively short-lived on geological timescales, according to phylogenetic analyses, implying that bacterial extinction occurs at high rates. Since the vast majority of bacteria live in large populations in oceans and soils, many well-studied extinction mechanisms, such as demographic or environmental stochasticity, seem unlikely to drive this pattern. We outline mechanisms for the extinction of large bacterial populations, and discuss the emergence of a new virus as a possible cause of extinction. We use deterministic and stochastic models to characterise the persistence of a bacterial population, demonstrating that when resistance to a new virus does not emerge, large populations are more likely to go extinct than small populations, which contrasts with classically studied extinction mechanisms. When they go extinct, large populations also reach extinction more quickly. When phage-resistant bacteria appear, extinction is rare but its probability increases with population size in some parameter regimes. We also quantify bacterial extinction in spatially distinct subpopulations. We conclude that large bacterial populations are robust to many extinction mechanisms, and typically evolve resistance to new phages, as observed empirically. For bacterial lineages that have gone extinct, however, the failure to evolve resistance to a novel phage is a likely underlying mechanism.