MULTIPLEXED CHEMOSTAT SYSTEM FOR QUANTIFICATION OF BIODIVERSITY AND ECOSYSTEM FUNCTIONING IN ANAEROBIC DIGESTION

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Engineering microbial diversity-function experiments

As described earlier, anaerobic digestion involves complex and diverse microbial communities in a trophic chain with interactions, notably syntrophic interactions between syntrophs and archaeal communities. The proper functioning of anaerobic digestion depends on many environmental factors (temperature, pH, volatile fatty acids, etc.) but also on the microbial community diversity. And, applying constraints proved to be effective in changing and improving the balance of the system. Understanding and handling these constraints, or levers, can improve the system in a more favorable state and would enable to understand the underlying mechanisms of the diversity-function relationship. Therefore, in the following paragraphs, we will first discuss which parameters are important for handling complex microbial communities such as anaerobic digestion communities and in a second step we will see how to manipulate diversity to study diversity-function relationships.
The importance of the initial inoculum has been underlined not quite so often in the literature. In fact, the initial community structures are shaped with the different abiotic parameters and the divergence between communities can decrease over time. In some studies, microbial communities structures dynamic was found to be driven by deterministic patterns (Lin et al., 2017; Vanwonterghem et al., 2014a). Other studies operated different inocula and showed the importance of the initial inoculum for the operational stability (in methane production) and/or the digester resistance to disturbance (De Vrieze et al., 2014; Perrotta et al., 2017; Raposo et al., 2011). Despite similar operational conditions, evenness, diversity, phylogenetic structure and even product, microbial composition were clearly distinct between these inocula (Perrotta et al., 2017). Furthermore, the microbial structures were reproducible between inocula, as shown Figure 7 where the heat map represents the relative abundance of OTUs between the three inocula in triplicate.
There is a lot of white space here because there is a non-floating figure below. This happens also quite a lot in the printed version of the thesis (see page 27 or page 35, 69, 71 …). I do not know how to manage this well in Word. One way of doing it is – as a last step when the content is settled – to move text around manually. There must be a way in Word to do this nicer, I assume (long live LaTeX!).
In sum, the inoculum source matters for experimentation and although determinant phenomena can be observed, microbial structure cannot be expected to approximate. Specific interactions may already have been in place before and at the onset of inoculation. The specificity of inocula must therefore be taken into account for experimentation.
However, to be able to compare an inoculum performance in time-spaced experiments, two possibilities exist. (i) One inoculum can be sampled again in its environment at a different time. But we have seen the importance of initiating process and, furthermore, time differences of a sludge coming from a waste water treatment plan experience different constraints and show different microbial communities structure and efficiency (Valentin-Vargas et al., 2012). (ii) The other possibility of comparing an inoculum performance is to preserve this inoculum. Whether a preserved inoculum has the same functional and structural properties as a fresh inoculum have been experienced only a few times. Different temperatures, methods (encapsulation, drying and lyophilization) and cryoprotective agents can be used to preserve complex microbial communities for activity recovery. While Kerckhof et al. (2014) have found that activity of fecal communities were recovered after cryopreservation (Kerckhof et al., 2014), Hagen et al (2014) did not manage to recover methanogenic potential of two different inocula for any temperature conservation used (-20°C, 4°C, room temperature) (Hagen et al., 2015). Vogelsang et al. (1999) encapsulated nitrifiers communities into alginate beads and reactivated their activity between 40 to 60% into CSTR reactors after two or three months preservation at -80°C (Vogelsang et al., 1999). In the laboratory, it is admitted to preserve an inoculum at 35°C temperature for a maximum of one month to keep the microorganisms alive and at 4°C or room temperature for longer experiment. The large volumes of digestate are difficult to store at temperature -80°C, even with alginate beads where it would still take a certain number of beads to find the same concentration in the communities. Considering previous results of inocula particularities and preservation contingencies, carrying out tests at the same time is still preferable rather preservation or time-spaced experiments.
Other than inoculum itself, different biotic parameters can be applied on anaerobic digestion, as for example as bioaugmentation. The objective of bioaugmentation is to improve a process by introducing a pure, co-cultures or mixed cultures of microorganisms. Numerous studies have tested bioaugmentation on anaerobic digestion process. The increase of methane yield after bioaugmentation ranged from 120% to 0 and no evident parameter of succeeding or failing bioaugmentation was revealed (De Vrieze et al., 2016b). The experiment with 120% increase of methane yield has enriched biomass for propionate degradation. In this way, the authors managed to reduce the solid retention time for organic overload (Tale et al., 2011).
Another example of biotic parameter manipulation is synthetic biology. This expanding field can be described as the design of biological pathways, organisms or devices. Bell et al., (2005) build a synthetic community by adding 1 to 72 species and measure the respiration rate (Bell et al., 2005). Through this construction, they artificially increase the diversity and found a positive and decelerating relationship between bacterial diversity and the studied function. Therefore, synthetic approaches have better controlled of evenness, richness, perturbations effect and ecosystem function for diversity-function experiments (De Roy et al., 2014). However, even if synthetic ecosystems allow us to better understand the underlying mechanisms, testing and validating these systems reaction in vivo would endorse their utilization.
Tilman et al. (1994) performed an experiment to study the effect of plant biodiversity on ecosystem functioning (Tilman and Downing, 1994). They observed that the more diversity in an ecosystem, the greater the stability of the community is. Twenty years later, Bell et al. (2005) built synthetic communities and observed decelerating relationship between diversity and function (Bell et al., 2005). Creating interactions between organisms are influenced by different parameters, as seen before (operational conditions, perturbations and resilience, spatial organization, etc.). In batch reactors, Sierocinski et al., (2017), studied complex community coalescence and found that the more communities were mixed, the higher the performance of the process was by selecting the best performing taxa (Sierocinski et al., 2017).
Community assembly is proving to be an interesting parameter for the study of the functioning diversity relationship.

READ  Machine learning basics 

Community assembly

A community is an assemblage of populations that could be defined by their productivity (metabolites, etc.), their species identity and abundance, the diversity and the trophic interactions, bottom-up (nutrient control) and top-down (predation).
Community assembly is driven by different parameters: dispersal, genetic diversification, selection and ecological drift (Vellend, 2010). Dispersal and diversification are the dynamics that generate or introduce new taxa, whereas selection and drifts imply abundance changes. The hypothetical mechanisms driving the community assembly have been based on the contrasting perspectives of the stochastic neutral models and the deterministic niche paradigm. The neutral hypothesis (Hubbell, 2001) implies random organisms dynamics, whereas the deterministic niche paradigm suggests selection processes via abiotic parameters and species interactions.
Applied to microbial communities, some studies found only one mechanism implied (Sloan et al., 2006; Vanwonterghem et al., 2014a), whereas others have suggested that both stochastic and determinism forces act on the populations (Caruso et al., 2011; Dumbrell et al., 2010; Stegen et al., 2012; Van Der Gast et al., 2008). In these works, perturbations and abiotic parameters would drive niches-selection processes and the patchwork environment would favor stochastic events to occur.
Environmental perturbations affect the microbial community in terms of composition and function. However, microbial communities may be resilient or resistant to these changes (Allison and Martiny, 2008; Shade et al., 2012).

Thesis objectives

Different microbial populations are involved in the anaerobic digestion process, yet their dynamic are not well understood. To study community assembly processes and to understand the dynamics of microbial communities, assembly experiments can be performed at the scale of the whole community by artificially controlling parameters, like dispersal or selection by tuning environmental factors.

Table of contents :

1 INTRODUCTION
2 LITERATURE REVIEW
2.1 MICROBIAL COMMUNITIES IN THE ANAEROBIC DIGESTION PROCESS
2.1.1 The different steps of anaerobic digestion
2.1.2 Abiotic parameters influencing anaerobic digestion
2.2 MOLECULAR TOOL TO STUDY MICROBIAL COMMUNITIES IN THE ANAEROBIC DIGESTION PROCESS
2.3 MICROBIAL DIVERSITY AND STRUCTURE
2.3.1 Concept of microbial diversity
2.3.2 Diversity measurements
2.3.3 Community distances
2.4 MICROBIAL INTERACTIONS
2.5 MICROBIAL DIVERSITY AND ECOSYSTEMS FUNCTION
2.5.1 Relationship between microbial diversity and ecosystems function
2.5.2 Engineering microbial diversity-function experiments
2.6 COMMUNITY ASSEMBLY
3 THESIS OBJECTIVES
4 MATERIAL AND METHODS
4.1 INOCULUM AND SUBSTRATE CHOICE
4.2 DESIGN OF LAMACS
4.3 PRESSURE DATA ANALYSIS
4.4 ANALYTICAL METHODS
4.4.1 Biochemical analyses
4.4.2 Biological analyses
4.5 BIOMASS PREPARATION AND INOCULATION
4.6 STATISTICAL ANALYSES
4.7 SUMMARY OF EXPERIMENTS PERFORMED
5 MULTIPLEXED CHEMOSTAT SYSTEM FOR QUANTIFICATION OF BIODIVERSITY AND ECOSYSTEM FUNCTIONING IN ANAEROBIC DIGESTION
5.1 ABSTRACT
5.2 INTRODUCTION
5.3 RESULTS
5.3.1 Range of operating conditions of the multiplexed chemostats
5.3.2 Sensitivity of performance measurement
5.3.3 Long-term operation of the multiplexed chemostats
5.4 DISCUSSION
5.5 ADDITIONAL DATA
6 SUBSTRATE AND INOCULUM CHOICE AFFECT ASSEMBLY OF FUNCTIONALLY REDUNDANT ANAEROBIC COMMUNITIES
6.1 INTRODUCTION
6.2 RESULTS
6.2.1 Reactor operation
6.2.2 Influence of substrate and community assembly on ecosystem functioning
6.2.3 Relating microbial diversity to ecosystem functioning
6.2.4 Relating microbial community structures to ecosystem functioning
6.2.5 Coalescence of mixed communities
6.3 DISCUSSION
6.4 CONCLUSION
6.5 ADDITIONAL DATA
7 GENERAL CONCLUSION
8 PERSPECTIVES
9 REFERENCES

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