Towards functional molecular fingerprints

Abstract

One of the most important challenges in microbial ecology is to determine the ecological function of dominant microbial populations in their environment. In this paper we propose a generic method coupling fingerprinting and mathematical tools to achieve the functional assigning of bacteria detected in microbial consortia. This approach was tested on a nitrification bioprocess where two functions carried out by two different communities could be clearly distinguished. The mathematical theory of observers of dynamical systems has been used to design a dynamic estimator of the active biomass concentration of each functional community from the available measurements on nitrifying performance. Then, the combination of phylotypes obtained by fingerprinting that best approximated the estimated trajectories of each functional biomass was selected through a random optimization method. By this way, a nitritation or nitratation function was assigned to each phylotype detected in the ecosystem by means of functional molecular fingerprints. The results obtained by this approach were successfully compared with the information obtained from 16S rDNA identification. This original approach can be used on any biosystem involving n successive cascading bioreactions performed by n communities.

Species Coexistence in Nitrifying Chemostats: A Model of Microbial Interactions

“…Except for some well-identified periods, the experiment was run in duplicate and both chemostats behaved similarly. For this reason, in the present study we concentrate on the results obtained from only one device (the chemostat denoted as "chemostat B" in [31]). The main results of this monitoring-on average over the 525 days of experiments-were (i) 40% of the total biomass was represented by the most abundant AOB; (ii) the most abundant NOB represented less than 10% of the total biomass; (iii) the two most abundant AOB and the two most abundant NOB represented more than 55% of the total biomass.…”

“…However, it is not what is observed in practice (cf. the data we use from [31]: we will come back on these data later on but it will be clearly shown that the dynamics of AOB1 and AOB2, and of NOB1 and NOB2, are significantly different). Now, with different growth rates and again no interactions, the competitive exclusion principle applies and coexistence is simply not possible.…”

“…The parameters of model #1, optimized to match experimental data in [31] are recalled in Table 1. The identification of microbial interactions was done with the help of the model #2 described by Equation (3).…”

“…As suggested in [31], they are supposed to be Monod functions and are thus written as µ A (S 1 ) = µ max1…”

“…In the same way, some studies have explained coexistence in chemostats by the heterogeneity of the medium or by variations in solid retention times [8] while others have considered abundances) of the bacteria present in the chemostat were made by Single Strand Conformation Polymorphism. In a previous work, using an original mathematical approach, a functional community assignation (i.e., in AOB or NOB community) was performed for each phylotype detected in the chemostat [30,31]. In the present work, a microbial interaction model is optimized on the kinetics of the two most abundant phylotypes of each functional community.…”