A new model in which the maximum microbial specific growth rate (max) is described as a function of pH and temperature is presented. The seven parameters of this model are the three cardinal pH parameters (the pH below which no growth occurs, the pH above which no growth occurs, and the pH at which the max is optimal), the three cardinal temperature parameters (the temperature below which no growth occurs, the temperature above which no growth occurs, and the temperature at which the max is optimal), and the specific growth rate at the optimum temperature and optimum pH. The model is a combination of the cardinal temperature model with inflection and the cardinal pH model (CPM). The CPM was compared with the models of Wijtzes et al. and Zwietering et al. by using previously published data sets. The models were compared on the basis of the usual criteria (simplicity, biological significance and minimum number of parameters, applicability, quality of fit, minimum structural correlations, and ease of initial parameter estimation), and our results justified the choice of the CPM. Our combined model was constructed by using the hypothesis that the temperature and pH effects on the max are independent. An analysis of this new model with an Escherichia coli O157:H7 data set showed that there was a good correspondence between observed and calculated max values. The potential and convenience of the model are discussed.

Growth rates and lag times of Listeria monocytogenes at 4 and 8°C were compared in dairy products (milk, cream, and cheese), minced beef, and smoked salmon. Results showed that an increase in incubation temperature from 4 to 8°C leads to a significant decrease in time required to reach a given bacterial population density. The decreases were about 50% on cheese surfaces, 60 to 65% in milk and cream, and 75 to 80% in minced beef and smoked salmon. Consequences on the shelf life of chilled products are discussed on the basis of a simple and general linear relationship between the relative decrease in shelf life and generation time. This relationship was experimentally highlighted and theoretically demonstrated.

Soil bacteria function in the three‐dimensional space in heterogeneous soil complex and their activities depend in part on encountering substrates at the microbial scale. The bacterial density per gram of soil, which is generally measured, does not indicate if bacteria are all in the same location or spread throughout the soil complex. We characterized spatial distribution for how dispersed or aggregated nitrifiers (NH+4 and NO−2 oxidizers) were at a submillimeter scale. The spatial approach was based on the relationship, obtained experimentally, between the percentage of microsamples (50–500 μm diam.) harboring nitrifiers and the volume of the microsamples. The smallest sample size (50‐μm diam.) was considered as an approximation of microhabitat. The simulated spatial pattern of NO−2 oxidizer microhabitats in soil were compared with experimental data. The simulated pattern of NO−2 oxidizer distribution suggested that microhabitats averaged seven NO−2 oxidizers and occurred in preferentially colonized patches that had about a 250‐μm diam. These were randomly distributed and occupied 5.5% of the soil volume. They were functionally connected through microporosity and hence diffusion processes probably controlled the spatial distribution of nirifiers. The nitrifier spatial pattern enabled efficient nitrification because NH+4 and NO−2 oxidizers were near one another. The results showed the potential of our method to study spatial distribution of bacteria at the microhabitat scale.

Background The recent rise in cultivation-independent genome sequencing has provided key material to explore uncharted branches of the Tree of Life. This has been particularly spectacular concerning the Archaea, projecting them at the center stage as prominently relevant to understand early stages in evolution and the emergence of fundamental metabolisms as well as the origin of eukaryotes. Yet, resolving deep divergences remains a challenging task due to well-known tree-reconstruction artefacts and biases in extracting robust ancient phylogenetic signal, notably when analyzing data sets including the three Domains of Life. Among the various strategies aimed at mitigating these problems, divide-and-conquer approaches remain poorly explored, and have been primarily based on reconciliation among single gene trees which however notoriously lack ancient phylogenetic signal. Results We analyzed sub-sets of full supermatrices covering the whole Tree of Life with specific taxonomic sampling to robustly resolve different parts of the archaeal phylogeny in light of their current diversity. Our results strongly support the existence and early emergence of two main clades, Cluster I and Cluster II, which we name Ouranosarchaea and Gaiarchaea, and we clarify the placement of important novel archaeal lineages within these two clades. However, the monophyly and branching of the fast evolving nanosized DPANN members remains unclear and worth of further study. Conclusions We inferred a well resolved rooted phylogeny of the Archaea that includes all recently described phyla of high taxonomic rank. This phylogeny represents a valuable reference to study the evolutionary events associated to the early steps of the diversification of the archaeal domain. Beyond the specifics of archaeal phylogeny, our results demonstrate the power of divide-and-conquer approaches to resolve deep phylogenetic relationships, which should be applied to progressively resolve the entire Tree of Life.