The Distribution of Bacterial Doubling Times in the Wild

Abstract

Generation time varies widely across organisms and is an important factor in the life cycle, life history and evolution of organisms. Although the doubling time (DT), has been estimated for many bacteria in the lab, it is nearly impossible to directly measure it in the natural environment. However, an estimate can be obtained by measuring the rate at which bacteria accumulate mutations per year in the wild and the rate at which they mutate per generation in the lab. If we assume the mutation rate per generation is the same in the wild and in the lab, and that all mutations in the wild are neutral, an assumption that we show is not very important, then an estimate of the DT can be obtained by dividing the latter by the former. We estimate the DT for four species of bacteria for which we have both an accumulation and a mutation rate estimate. We also infer the distribution of DTs across all bacteria from the distribution of the accumulation and mutation rates. Both analyses suggest that DTs for bacteria in the wild are substantially greater than those in the lab, that they vary by orders of magnitude between different species of bacteria and that a substantial fraction of bacteria double very slowly in the wild.

CRISPR-based herd immunity can limit phage epidemics in bacterial populations

“…We show that herd immunity can occur in phage-bacterial communities and that it strongly depends on bacterial growth rates and spatial population structure. Average growth rates of bacteria in the wild have been estimated as substantially slower than in the laboratory (generation time is 7.4 fold longer [ Gibson et al, 2017 ]), a condition that we have shown to facilitate herd immunity. Furthermore, bacterial populations in the wild are also highly structured, as bacteria readily form micro-colonies or biofilms ( Hall-Stoodley et al, 2004 ) and grow in spatially heterogeneous environments such as soil or the vertebrate gut ( Fierer and Jackson, 2006 ), a second condition we have shown to facilitate herd immunity.…”

Long identical sequences found in multiple bacterial genomes reveal frequent and widespread exchange of genetic material between distant species

“…Assuming a mutation rate µ of 10 −9 per bp and per generation, this results in a detection horizon of t ML ≈ 10 6 generations. Assuming a mean generation time in the wild of about 10 hours [28], this corresponds to approximately 1000 years. That is to say, we estimate that the HGT events we detect date back to the past 1000 years.…”

Evolution of chemotactic hitchhiking

“…We interpret the race duration as the average distance between chemoattractant patches or the decay time of transient chemoattractant concentrations. Chemogradients are chosen along with growth rates given from empiric data (Blackburn et al ., 1998; Gibson et al ., 2018). (c) For microbes to swim, they must do work against friction.…”

“…We therefore assume microbes pay a metabolic cost proportional to the square of their run speed and take run speed to be heritable. (d) The microbial growth rate at a given location depends on the chemoattractant concentration at that location, in accordance with empiric data (Gibson et al ., 2018; Monod, 1949). (e) When two microbes collide, they either stick or not stick depending on the stickiness trait of the microbes.…”