Systems-Level Modelling of Microbial Communities

Theory and Practice

Aarthi Ravikrishnan, Karthik Raman

• Publisher: CRC Press
• Year: 2018
• Print ISBN: 9781138596719
• eBook ISBN: 9780429946066
• Topic: Computer Science
• Subtopic: Programming Games
• Index: Computer Science

Systems-Level Modelling of Microbial Communities: Theory and Practice introduces various aspects of modelling microbial communities and presents a detailed overview of the computational methods which have been developed in this area. This book is aimed at researchers in the field of computational/systems biology as well as biologists/experimentalists studying microbial communities, who are keen on embracing the concepts of computational modelling. The primary focus of this book is on methods for modelling interactions between micro-organisms in a community, with special emphasis on constraint-based and network-based modelling techniques. A brief overview of population- and agent-based modelling is also presented. Lastly, it covers the experimental methods to understand microbial communities, and provides an outlook on how the field may evolve in the coming years.

CHAPTER 1

Introduction to microbial communities

Micro-organisms are ubiquitous, yet rarely function as independent entities, and thrive in communities. Landscapes of microbial communities are enormous and display astounding capabilities to perform composite actions. The dynamic and complex interactions between microbes play significant roles in shaping community assemblies. Microbial communities are inarguably the preeminent friends and foes of human beings, influencing human health and disease, as well as the biosphere itself.

Interactions in microbial communities can be broadly classified into beneficial, neutral or harmful, which determine the spatio-temporal arrangement of the micro-organisms [1]. Such complex interactions help microbes inhabit different niches, which otherwise would not have been possible. For instance, in the biofilm formed on the surface of the teeth, the initial colonisers bind to the salivary pellicle receptors, followed by the later colonisers, which attach to the receptors of initial microorganisms [2].

Microbial communities have also evoked a lot of interest for metabolic engineering. Owing to the diversity in the metabolic capabilities of the constituent micro-organisms, microbial communities are emerging as a viable alternative to single organisms. Naturally occurring microbial consortia have been explored for several applications such as wastewater treatment, food fermentations and bioremediation. Further, many of the beneficial associations between micro-organisms have been leveraged in multiple industrial applications, where co-cultures of organisms with diverse metabolic capabilities have been used. In addition, metabolic interactions between microbes have been synthetically induced by introducing heterologous pathways and transporters. These transporters serve as a gateway for interactions between the micro-organisms [3].

Due to the advantages discussed above and the amenability of microbial communities to manipulations,there is a burgeoning interest in applying these communities for biotechnological applications, despite the associated practical difficulties. Further, to better understand microbial communities, several modelling techniques have been developed, each of which provides a different perspective. In this chapter, we shine a spotlight on the basic concepts underlying microbial communities and discuss examples elucidating the importance of microbial communities.

1.1 MODES OF INTERACTION IN COMMUNITIES

Micro-organisms in a community tend to interact with each other through various means. These interactions can be broadly classified into different categories, based on the nature of interactions. One such type of interaction is mutualism, where all the organisms benefit each other. A classic example of mutualism includes syntrophy, where there is a cross-feeding of the nutrients between the micro-organisms in a community. Such cross-feeding of nutrients has been commonly observed in nature, especially in anaerobic marine environments and under extreme conditions of temperature and pH [4].

Syntrophic associations have also been demonstrated in the laboratory, where two organisms — Desulfovibrio vulgaris Hilden- borough and Methanococcus maripaludis S2 — were co-cultivated in a medium containing lactate [5]. Further, this co-culture system was also modelled to understand the mutualistic interactions [6]. In another example, it was shown that strains of Methanobacillus omelianskii, which are the most abundant organisms in sewage sludge, show cross-feeding tendencies when grown on ethanol [7].

In another type of interaction, commensalism, one of the organisms derives benefit, while there is no effect on the other organisms in the community. Such an interaction is most commonly found in co-cultivation of lactic acid bacteria (LAB) and propionic acid bacteria (PAB), where the lactic acid produced by the former serves as the carbon source for the latter. The LAB, however, does not derive any benefit from the presence of PAB [8]. In the human gut, although the organisms are often referred to as commensals, the relationship between the gut microbiome and the host is predominantly mutualistic [9].

Other types can be broadly categorised under harmful interactions, where either one or all of the organisms are negatively affected. Parasitism is one such form of interaction, where there is a benefit for one organism (parasite) at the cost of the other (host). Such an interaction is most commonly observed between bacteria–bacteriophage or between any predator and prey [10]. In the other type of interaction, amensalism, one of the organisms is harmed, while the other derives no benefit from the interaction. Such interactions are most commonly observed in food fermentations, especially those involving lactic acid bacteria [11], where the end products reduce the pH of the fermentation medium, detrimentally affecting the other organisms in the community. Competition is one other type of interaction, where the organisms compete with each other for space and resources.

In general, while microbial communities are used for any application, positive or beneficial interactions are generally leveraged, so that the joint metabolic capabilities of the microorganisms can be fully explored.

Key Interactions

• Mutualism (+/+): All organisms in the community are benefited

• Commensalism (+/0): Only one organism is benefited, others derive no benefit

• Amensalism (-/0): One organism derives no benefit while the others are harmed

• Competition (-/-): All the organisms compete for same resources, and the community comes to harm

• Parasitism (-/+): Only one organism is benefited, others are harmed

In the next sections, we mention a few examples of well- known naturally existing microbial communities and also describe a few studies where synthetic microbial communities have been used for biotechnological applications.

1.2 NATURAL MICROBIAL COMMUNITIES

Several microbial communities are known to inhabit different natural habitats, such as the soil, the human oral cavity and the gut. In many communities, micro-organisms act in tandem, carrying out a specific function, while in a few other cases, such as communities in biofilms, there is a sequential progression or succession of micro-organisms. The naturally existing microbial communities have implications for multiple processes, ranging from the digestion of human milk oligosaccharides [12] to the regulation of global biogeochemical cycles [13]. Microbial communities also play important roles in the progression of several human diseases, including diabetes mellitus and atherosclerosis [14]. In this section, we describe a few important naturally existing microbial communities, and the roles played by the micro-organisms therein.

1.2.1 Gut microbiota

The human gut is known to be inhabited by a distinctive community of micro-organisms. The composition of the human gut microbiota is known to vary at different stages of the lifecycle. These variations are influenced by several factors such as perinatal colonisation, diet, host susceptibility, exposure to antibiotics and other environmental exposures [15]. Several studies [16,17] have shown that the composition of the gut microbiota is primarily influenced by the mode of birth and the type of diet. These studies have reported that the gut of infants born via vaginal delivery is dominated by Lactobacillus and Prevotella species, while those born via Caesarean delivery have abundant Clostridium, Staphylococcus,Propionobacterium and Corynebacterium species [16]. Moreover, the development of these micro-organisms in the gut of infants depends on the mode of feeding — in breastfed infants, it was shown that a few species of Bifidobacterium such as B. infantis, B. breve, B. adolescentis, B. longum and B. bifidum are abundant, in comparison to formula-fed infants, who had higher levels of B. longum [17].

Since the organisms in the gut are involved in a plethora of functions, there has been an emerging interest in analysing and understanding the gut microbiota. Specifically, many studies focus on the interplay of organisms and other factors such as lifestyle and dietary intake [18]. The gut microbiota often aid in the conversion of indigestible dietary polysaccharides to short- chain fatty acids such as acetate, propionate and butyrate, which are then absorbed by the human host cells [19]. Other prominent functions of the gut micro-organisms include the development of immune system, metabolism of drug and xenobiotics, as well as protection from resident pathogens [20].

Recent advances in gene sequencing technologies combined with modelling techniques have enabled the understanding of these microbial communities and also their interactions. Specifically, metabolic modelling of microbial communities has gained a lot of traction [21,22] partly due to an increase in the availability of genomic data. Further, to gather more profound insights into the metabolic capabilities of the gut, genome-scale metabolic reconstructions have been developed for several gut microbiota [23]. More details on the genome-scale modelling of gut microbial communities can be found in refs. [24,25].

1.2.2 Soil microbiota

Soil is inhabited by different types of microbial communities, which help in carbon sequestration and maintaining the fertility of the soil. The micro-organisms in the soil also regulate the biogeochemical cycles [26] and play an important role in several processes such as decomposition of organic matter found in forest soils [27].

The soil has different horizons, or layers, ea...

Table of contents

• Cover
• Half Title
• Title Page
• Copyright Page
• Dedication
• Table of Contents
• Preface
• CHAPTER 1 ■ Introduction to microbial communities
• CHAPTER 2 ■ Network-based modelling of microbial communities
• CHAPTER 3 ■ Population- and agent-based modelling of microbial communities
• CHAPTER 4 ■ Constraint-based modelling of microbial communities
• CHAPTER 5 ■ Experimental techniques to understand microbial interactions
• CHAPTER 6 ■ Outlook
• Bibliography
• Index