What is microbial dormancy?

Life can be stressful. One way to deal with stress is to simply wait it out. Microbes do this by entering a state of reduced activity and increased resistance commonly called 'dormancy'. But what is dormancy? Different scientific disciplines emphasize distinct traits and phenotypic ranges in defining dormancy for their microbial species and system-specific questions of interest. Here, we propose a unified definition of microbial dormancy, using a broad framework to place earlier discipline-specific definitions in a new context. We then discuss how this new definition and framework may improve our ability to investigate dormancy using multi-omics tools. Finally, we leverage our framework to discuss the diversity of genomic mechanisms for dormancy in an extreme environment that challenges easy definitions - the permafrost.

The "comfort timing" strategy: a potential pathway for the cultivation of uncultured microorganisms and a possible adaptation for environmental colonisation

Efforts to isolate uncultured microorganisms over the last century and a half, as well as the advanced 'omics' technologies developed over the last three decades, have greatly increased the knowledge and resources of microbiology. However, many cellular functions such as growth remain unknown in most of the microbial diversity identified through genomic sequences from environmental samples, as evidenced by the increasingly precise observations of the phenomenon known as the 'great plate count anomaly'. Faced with the many microbial cells recalcitrant to cultivation present in environmental samples, Epstein proposed the 'scout' model, characterised by a dominance of dormant cells whose awakening would be strictly stochastic. Unfortunately, this hypothesis leaves few exploitable possibilities for microbial cultivation. This review proposes that many microorganisms follow the 'comfort timing' strategy, characterised by an exit from dormancy responding to a set of environmental conditions close to optimal for growth. This 'comfort timing' strategy offers the possibility of designing culture processes that could isolate a larger proportion of uncultured microorganisms. Two methods are briefly proposed in this article. In addition, the advantages of dormancy, of the 'scout' model and of the 'comfort timing' strategy for survival under difficult conditions, but also for colonisation of environments, are discussed.

Changes in the Size of the Active Microbial Pool Explain Short-Term Soil Respiratory Responses to Temperature and Moisture

Heterotrophic respiration contributes a substantial fraction of the carbon flux from soil to atmosphere, and responds strongly to environmental conditions. However, the mechanisms through which short-term changes in environmental conditions affect microbial respiration still remain unclear. Microorganisms cope with adverse environmental conditions by transitioning into and out of dormancy, a state in which they minimize rates of metabolism and respiration. These transitions are poorly characterized in soil and are generally omitted from decomposition models. Most current approaches to model microbial control over soil CO2 production relate responses to total microbial biomass (TMB) and do not differentiate between microorganisms in active and dormant physiological states. Indeed, few data for active microbial biomass (AMB) exist with which to compare model output. Here, we tested the hypothesis that differences in soil microbial respiration rates across various environmental conditions are more closely related to differences in AMB (e.g., due to activation of dormant microorganisms) than in TMB. We measured basal respiration (SBR) of soil incubated for a week at two temperatures (24 and 33°C) and two moisture levels (10 and 20% soil dry weight [SDW]), and then determined TMB, AMB, microbial specific growth rate, and the lag time before microbial growth (t lag ) using the Substrate-Induced Growth Response (SIGR) method. As expected, SBR was more strongly correlated with AMB than with TMB. This relationship indicated that each g active biomass C contributed ~0.04 g CO2-C h(-1) of SBR. TMB responded very little to short-term changes in temperature and soil moisture and did not explain differences in SBR among the treatments. Maximum specific growth rate did not respond to environmental conditions, suggesting that the dominant microbial populations remained similar. However, warmer temperatures and increased soil moisture both reduced t lag , indicating that favorable abiotic conditions activated soil microorganisms. We conclude that soil respiratory responses to short-term changes in environmental conditions are better explained by changes in AMB than in TMB. These results suggest that decomposition models that explicitly represent microbial carbon pools should take into account the active microbial pool, and researchers should be cautious in comparing modeled microbial pool sizes with measurements of TMB.