Polymicrobial communities often show complex patterns of metabolic and ecological interactions, yet our understanding of how the properties of communities emerge from the metabolic rules of species interactions is still limited. A central feature of metabolic interactions within microbial communities is ‘cross-feeding’, where one species or lineage consumes the metabolic by-products of another. Cross-feeding bacteria excrete and consume a wide range of metabolites and this sets the stage for diverse intra- and inter-specific metabolic interactions. In this thesis, I use ecological and evolutionary theory to address a number of critical questions posed by cross-feeding bacteria, with a particular focus on the role played by microbial metabolism in driving the emergence and dynamics of microbial interactions. First, I explore the conditions that favour the emergence and maintenance of cooperative cross-feeding and show that the evolutionary outcome depends strongly on the shape of the trade-off curves between the costs and benefits of cooperation. Second, I investigate the origins of cross-feeding interactions via single lineage diversification and derive new predictions on the physiological mechanisms that may explain the stable coexistence of a cross-feeding polymorphism that evolved from a single clone. Third, I investigate what are the ecological consequences of cross-feeding metabolic interactions and demonstrate theoretically that a simple mechanism of trade can generate a diverse array of ecological relationships. Furthermore, I show the importance of the metabolic by-product properties in determining the ecological outcome. Fourth, I investigate how metabolic constraints of individual species shape the emergent functional and structural relationships among species. I show that strong metabolic interdependence drives the emergence of mutualism, robust interspecific mixing, and increased community productivity. Furthermore, I show that these emergent community properties are driven by demographic feedbacks. In general, these findings support the idea that bridging microbial ecology and metabolism is a critical step toward a better understanding of the factors governing the emergence and dynamics of polymicrobial interactions.

The human gut microbiome is important for health and development, and understanding its functioning and dynamics are of great medical importance. The microbiome food web is largely characterized by chains of byproduct cross-feeding (where metabolites of one organism are used as nutrients for another), yet a recent study have shown that the average length of the chains are considerably shorter than what metabolic capabilities of present species allow for. Here, I use evolving populations of digital organisms to investigate if recurring perturbations are a potential constraint of byproduct cross-feeding chains. I evolved digital populations in an environment unconstrained by energy loss between trophic levels and then exposed them to a period of recurring perturbations, where a fraction of the population was removed at 100 random points in time. Perturbations caused a substantial decrease in cross-feeding chain length, with increased frequency as perturbation intensity increased. In some communities, effects persisted after the perturbation period had ended. Tracking evolution of resource use during and after the perturbation period revealed that organisms descending from long-chained ancestors often evolved a shorter chain, suggesting that they adapted to perturbations by losing the ability to consume low-level resources. The evolutionary loss of resource consumption could explain the persisting effects on cross-feeding chains. Though my study suggests that perturbations can limit the length of byproduct cross-feeding chains, further studies are necessary toconclude if effects remain in environments with a more realistic energy transfer between trophic levels.

The gut microbiome plays a vital role in human health. Disturbances of this microbial system is associated with diseases such as obesity and inflammatory bowel disease. In populations of microbial species, many organisms partake in byproduct cross-feeding interactions, where byproducts from one organism are consumed by other microbes. Using the digital evolution software Avida, I studied the effect of recurring perturbations and imperfect resource conversion on the evolution of byproduct cross-feeding chains in digital communities. To investigate the effect of perturbation and conversion rate on digital organisms, I evolved digital communities for 200,000 updates in an unperturbed environment that could hold 50 different resource types, each produced as a byproduct of consuming another resource. At 200,000 updates, 50 or 60 % of all organisms were removed at various intervals during periods of different lengths, with a conversion rate less than 100 % between resources in the byproduct chain. I found that 0.9 conversion rate caused communities to evolve longer cross-feeding chains. A conversion rate of 0.5 resulted in communities with much shorter chains, more similar in length to byproduct chains in the human gut. Perturbation events seem to affect chain length only under certain conditions when energy is lost between resources, for example when 60 % of all organisms were removed every 50th update on average. It appears that conversion loss makes digital communities more robust against the effects of perturbations, and that it might protect these communities from going extinct.

The benefits of human milk are well-known, as human milk provides optimal nutrition in facilitating the growth, health, and development of infants and children. There are circumstances when a mother’s breast milk may be unavailable due to maternal illness, insufficient milk supply, contraindications, or geographical barriers (Dempsey & Miletin, 2010). Global recommendations support the use of donor human milk in situations where a mother’s own breast milk is unavailable (World Health Organization, 2009). Due to the limited supply, the pasteurized product is allocated to high risk infants within the hospitalized setting (Human Milk Bank Association of North America, 2008). Based on the allocation priorities, many individuals are unable to access donor human milk. In response to the growing demands for donor human milk, Internet based organizations have facilitated peer to peer human milk sharing. Given the fact that sharing human milk has been practiced as a covert activity, there is a lack of prevalence data (Thorley, 2008). To date, minimal research has examined this phenomenon. The purpose of this study was to explore the description of sharing human milk utilizing an online commerce-free approach. Data was collected through semi-structured interviews with 13 research participants and analyzed using an inductive approach to qualitative content analysis. Qualitative content analysis was selected based on the recognition of the importance of obtaining a rich description when exploring this phenomenon. Outcomes generated from the research study resulted in emerging concepts and categories. The concepts from the data analysis consisted of the following: commitment to human milk; virtual nature of relationships; and making the private public. The identified categories include: 1) infant feeding practices; 2) experience with sharing human milk; 3) selection of donors or recipients; 4) relationships among donors and recipients sharing human milk; 5) shared doctrine; 6) use of the Internet to share human milk; and 7) informing health care professionals and others regarding sharing human milk. Findings generated from this study provide an increase in understanding of this phenomenon. The cultivated knowledge will assist health care professionals in working in partnership with families to ensure optimal outcomes. / Thesis (Master, Nursing) -- Queen's University, 2013-07-27 20:26:30.206

The human gut microbiome is a complex ecosystem with hundreds of species interacting with each other and the host. One function of the microbiome is to break down undigested nutrients into smaller nutrients, sometimes available for uptake by the host. The digestion of such macromolecules can involve several species where one feeds on another’s byproducts, forming a large cross-feeding network. The method of digital evolution can be of great aid in studying such complex ecosystems by creating models of the studied system. In this study, the digital evolution software Avida was used to study the effects of perturbations in the system on byproduct cross-feeding chain length. Intense perturbations were found to shorten the chain lengths in general whereas weaker perturbations had either a small or no effect. When perturbations ceased, most byproduct chains displayed recovery to lengths similar to the preperturbation lengths. This indicates that byproduct chain lengths may be kept short by common ecological mechanisms alone, explaining why very long chains are rarely observed while still theoretically possible.