Description of microbial growth behaviour during the wash-out phase; determination of the maximum specific growth rate

Microbial interactions in theory and practice: when are measurements compatible with models?

Most predictive models of ecosystem dynamics are based on interactions between organisms: their influence on each other's growth and death. We review here how theoretical approaches are used to extract interaction measurements from experimental data in microbiology, particularly focusing on the generalised Lotka-Volterra (gLV) framework. Though widely used, we argue that the gLV model should be avoided for estimating interactions in batch culture - the most common, simplest and cheapest in vitro approach to culturing microbes. Fortunately, alternative approaches offer a way out of this conundrum. Firstly, on the experimental side, alternatives such as the serial-transfer and chemostat systems more closely match the theoretical assumptions of the gLV model. Secondly, on the theoretical side, explicit organism-environment interaction models can be used to study the dynamics of batch-culture systems. We hope that our recommendations will increase the tractability of microbial model systems for experimentalists and theoreticians alike.

The pyrite iron cycle catalyzed by Acidithiobacillus ferrooxidans

In this paper, we study a model of the biotic pyrite iron cycle catalyzed by bacteria Acidithiobacillus ferrooxidans, in mining activity sites waste dumps. Chemical reactions, reaction rates and the population growth model are mostly taken from the existing literature. Analysis of the corresponding dynamical system shows the existence of up to four non-trivial steady state solutions. The stability of the equilibria solutions is determined, finding up to two coexisting stable solutions. Two Hopf bifurcations and a region of parameter space in which there are stable periodic solutions are found. In addition, we find a homoclinic bifurcation which gives rise to a stable periodic orbit of large period. The existence of these stable oscillatory solutions gives a possible explanation for the oscillations of bacteria concentration and pH for the iron cycle, described in Jaynes et al. (Water Resour Res 20:233-242, 1984).

Modeling of bacterial growth; formulation and evaluation of a structured model

Models which consider changes in the composition of biomass in response to environmental changes are called Structured models. They provide a more comprehensive description of microbial behavior than unstructured models. Compared with the unstructured modeling efforts, very little has so far been done on the theory and practice of structured model building. In most of the works reported so far, no experimental data were provided, and hence no means of testing the proposed models were offered. Others only reported macroscopic response data and not the cellular composition. In an attempt to fill some of the gaps in this field, in this work, first the general formal approach to structured modeling is developed in matrix notation. Then, a simple two-compartmental model, i.e., a structured model describing the activity of the biomass with two variables, is described. The cell is divided into two fractions, one of which relates to the RNA fraction. The proposed model was then critically evaluated with experimental data, including the RNA data, obtained from fed-batch and continuous-culture experiments. The importance of using cellular structure data for model verification, i.e., RNA data in this case, is shown. Shortcomings and capabilities of the developed model are discussed.

Central carbon metabolism of Saccharomyces cerevisiae in anaerobic, oxygen-limited and fully aerobic steady-state conditions and following a shift to anaerobic conditions

Saccharomyces cerevisiae CEN.PK113-1A was grown in glucose-limited chemostat culture with 0%, 0.5%, 1.0%, 2.8% or 20.9% O2 in the inlet gas (D=0.10 h(-1), pH 5, 30 degrees C) to determine the effects of oxygen on 17 metabolites and 69 genes related to central carbon metabolism. The concentrations of tricarboxylic acid cycle (TCA) metabolites and all glycolytic metabolites except 2-phosphoglycerate+3-phosphoglycerate and phosphoenolpyruvate were higher in anaerobic than in fully aerobic conditions. Provision of only 0.5-1% O2 reduced the concentrations of most metabolites, as compared with anaerobic conditions. Transcription of most genes analyzed was reduced in 0%, 0.5% or 1.0% O2 relative to cells grown in 2.8% or 20.9% O2. Ethanol production was observed with 2.8% or less O2. After steady-state analysis in defined oxygen concentrations, the conditions were switched from aerobic to anaerobic. Metabolite and transcript levels were monitored for up to 96 h after the transition, and this showed that more than 30 h was required for the cells to fully adapt to anaerobiosis. Levels of metabolites of upper glycolysis and the TCA cycle increased following the transition to anaerobic conditions, whereas those of metabolites of lower glycolysis generally decreased. Gene regulation was more complex, with some genes showing transient upregulation or downregulation during the adaptation to anaerobic conditions.

2,4-Dichlorophenoxyacetic Acid (2,4-D) Utilization by Delftia acidovorans MC1 at Alkaline pH and in the Presence of Dichlorprop is Improved by Introduction of the tfdK Gene

Growth of Delftia acidovorans MC1 on 2,4-dichlorophenoxyacetic acid (2,4-D) and on racemic 2-(2,4-dichlorophenoxy)propanoic acid ((RS)-2,4-DP) was studied in the perspective of an extension of the strain's degradation capacity at alkaline pH. At pH 6.8 the strain grew on 2,4-D at a maximum rate (mu max) of 0.158 h(-1). The half-maximum rate-associated substrate concentration (Ks) was 45 microM. At pH 8.5 mu max was only 0.05 h(-1) and the substrate affinity was mucher lower than at pH 6.8. The initial attack of 2,4-D was not the limiting step at pH 8.5 as was seen from high dioxygenase activity in cells grown at this pH. High stationary 2,4-D concentrations and the fact that mu max with dichlorprop was around 0.2 h(-1) at both pHs rather pointed at limited 2,4-D uptake at pH 8.5. Introduction of tfdK from D. acidovorans P4a by conjugation, coding for a 2,4-D-specific transporter resulted in improved growth on 2,4-D at pH 8.5 with mu max of 0.147 h(-1) and Ks of 267 microM. Experiments with labeled substrates showed significantly enhanced 2,4-D uptake by the transconjugant TK62. This is taken as an indication of expression of the tfdK gene and proper function of the transporter. The uncoupler carbonylcyanide m-chlorophenylhydrazone (CCCP) reduced the influx of 2,4-D. At a concentration of 195 microM 2,4-D, the effect amounted to 90% and 50%, respectively, with TK62 and MC1. Cloning of tfdK also improved the utilization of 2,4-D in the presence of (RS)-2,4-DP. Simultaneous and almost complete degradation of both compounds occurred in TK62 up to D = 0.23 h(-1) at pH 6.8 and up to D = 0.2 h(-1) at pH 8.5. In contrast, MC1 left 2,4-D largely unutilized even at low dilution rates when growing on herbicide mixtures at pH 8.5.

Rhodotorulic acid production by Rhodotorula mucilaginosa

Rhodotorula mucilaginosa produces the siderophore rhodotorulic acid (RA) when grown in iron-limited conditions. R. mucilaginosa grew at rates between 0.10 and 0.19 h(-1) in iron-restricted conditions, depending on the carbon source, and at 0.23 h(-1) in iron-sufficient conditions. In bioreactors inoculated with iron-starved pre-cultures, initial specific growth rates in batch culture were dependent on the iron concentration. The critical dilution rate (Dcrit, at which steady state cultures cannot be sustained) in continuous cultures was also dependent on the iron concentration and was lower than mu(max) in batch culture. Sucrose was the best carbon source for RA production [287+/-11 micromol (g biomass)(-1)] and production could be further increased by supplementing the medium with the precursors acetate [460+/-13 micromol (g biomass)(-1)], ornithine [376+/-6 micromol (g biomass)(-1)], or both [539+/-15 micromol (g biomass)(-1)]. Citric acid was an effective suppresser of RA production. RA was produced in a growth rate dependent manner and was optimally produced at pH 6.5.

Effect of temperature and pH onCandida blankii in chemostat culture

The growth characteristics ofCandida blankii as a function of temperature and pH in a simulated bagasse hemicellulose hydrolysate were determined in chemostat culture. The highest maximum specific growth rate of 0.44h(-1) was reached at 38°C and at pH 5.5, with a sharp decrease in growth rate on either side of this temperature. Growth occurred at 46°C but not at 48°C. The protein and cell yields varied little below 40°C and the respective values were 0.22 and 0.5 g/g at 38°C. At the lower pH values, a severe linear decrease in cell and protein yields occurred, whereas a small increase in these yields at decreasing pH values was found when acetic acid was omitted from the medium. In the presence of acetic acid, a very sharp decrease in the growth rate at pH values below pH 4.5 was noted, despite the very low residual acetic acid concentrations, of less than 50 mg/l, in the culture.

Complementation of the Saccharomyces cerevisiae srb1-1 mutation: an autoselection system for stable plasmid maintenance

The autonomously replicating plasmid YEpSS1, containing the S. cerevisiae SOD1 and SRB1 genes, was highly unstable in a wild-type strain. When transformed into a fragile srb1-1 mutant host, the same plasmid displayed different characteristics depending on the growth medium used. Both batch and continuous culture experiments demonstrated that the plasmid was very unstable when the transformed strain SLU15 was grown in the presence of an osmotic stabiliser (10% w/v sorbitol). However, in the absence of the osmoticum, nearly 100% of the cells retained the plasmid and produced the Sod1 protein after 80 generations of growth.

Heritable damage to yeast caused by transformation

The introduction of plasmid DNA into yeast by transformation or electroporation, but not by cytoduction, results in the induction of a slow growth phenotype. This phenotype is inherited as a dominant Mendelian trait, which is only exhibited in the absence of the native 2 mu nuclear DNA plasmid of yeast. The use of recombinant DNA technology in yeast, therefore, does not necessarily manipulate the genome in a precise and completely defined way.

Stability of a cloned gene in yeast grown in chemostat culture

A study has been made of the stability of LEU2, a cloned chromosomal gene of Saccharomyces cerevisiae, when reintroduced into yeast on a number of plasmid vectors which permit a chromosomal or episomal location for the gene in either high or low copy number. Glucose-limited continuous culture was employed to ensure that there was no selection for the inserted gene. Both the rate of segregation of plasmid minus cells and the effect of the plasmid on host growth rate were found to determine plasmid stability which, in many cases, could be predicted by simple mathematical models. The presence or absence of the endogenous 2 mu plasmid of yeast was found to have an important influence on the stability of 2 mu-based vectors. This led to the discovery that, for the host strain used, the presence of 2 mu sequences represented a selective advantage for the cells.