Comparative systems biology of lactic acid bacteria (SYSMOLAB2; Teusink-Westerhoff)

Molecular and genomics approaches have contributed greatly to our understanding of living organisms. They have also led to a number of surprises. One is the fact that organisms that appear to be highly different are rather similar in terms of their molecules. In fact, many of the molecular components of humans are similar to components of worms and even bacteria. Even closer similarities have been found between bacterial species that differ greatly between themselves, e.g. in how they interact with human beings (see below). Whilst this has been helping Science discover how molecules behave, it also presents us with a great paradox: for sure, humans and worms differ dramatically in almost anything that is important. A recent development in the sciences, called Systems Biology, recognizes that the functioning of living organisms is also determined by the interactions between their components, just like the scoring by a football player is not just determined by that player himself, but often more by how the rest of the team has cooperated to deliver the ball to her at the right moment. Here we propose to test our hypothesis that most of the differences between organisms derives from differences in the interactions between their components. Four strongly related organisms will be compared, i.e. one that produces our cheese, one that is a fecal contaminant of food, one that causes sore throats and worse, and one that is a food additive promoting digestion. The networks in each of the four bacteria will be unraveled, the flow of carbon and energy through those networks will be determined, and the extent to which the bacteria are able to adjust their networks to altered environments will be measured. The results will be assembled into computer models that should then reproduce the behaviour of the bacteria. It will be examined whether and how these computer versions of the organisms explain the differences in the extent to which they cause disease or function as organisms that help produce our food. These explanations of the functional differences will then be tested experimentally. The work by an international consortium with the Manchester part engaged in much of the computer modelling, will not only help us in finding resolutions of the above-mentioned paradox, but it will also demonstrate the power of strong interactions between mathematical and experimental biology approaches to big questions of Life. The experience gained, as well as the models themselves, should be useful much more widely for helping understand the molecular basis of Life, of health and of disease.

SysMO-LAB2 aims to extend and further develop comparative systems biology approaches to understand similarities and differences in fermentation behaviour of four Lactic Acid Bacteria (LAB). Lactococcus lactis, used in dairy food applications; Enterococcus faecalis, a major (fecal) contaminant of food and water as well as a contributor to food fermentation, and Streptococcus pyogenes, an important human pathogen, will continue to be studied. The fourth organism, Lactobacillus plantarum provides an important extension to the LABs in SysMO-LAB1 and has been chosen as a well characterized representative of the lactobacilli, an industrially important group of LAB. L. plantarum is associated with human health (probiotic) and is a versatile LAB found in very many different niches. From our results in SysMO-LAB1, we concluded that our comparative analysis should be extended to be able to fully understand the phenotypic differences observed. This relates to effects of amino acid metabolism and the ability to explicitly model changes in enzyme levels. Moreover, we want to make use of the increasing number of sequenced strains of the same species, and use our models to explain the enormous diversity in acidification rates in such strains. This specific application of comparative systems biology is of tremendous importance to the biotech industry and medicine, and will blend comparative systems biology with comparative genomics, while harvesting on the opportunities provided by the latest developments in sequence technology. Thus, our aims are to extend our comparative systems biology activities: 1. vertically, by incorporating the multi-level regulation of enzymes in primary metabolism and by explicit modelling of PTS-mediated glucose signalling (i.e. make enzyme levels internal variables of the model, not input parameters) and 2. horizontally, by extending the regulatory boundaries of the system to include the effects of amino acid metabolism.

1) Who will benefit from this research? This research will investigate four species of lactic acid bacteria. One of these (L. lactis) is used in the preparation of certain dairy foods. Another one (S. pyogenes) is a human pathogen causing severe throat infections. Yet another one, E. faecalis, a fecal contaminant of food and water, also contributes to food fermentation, whereas L. plantarum has probiotic activity and is used commercially for this purpose. The human makes use of some of these species in their living form but needs to prevent the other species from contaminating. Rather than using antibiotics and antibiotic resistant strains, one should use the organisms under conditions that favour the desired species whilst selecting strongly against the other. This project examines the differences between the four organisms in terms of their own food-processing and regulatory, intracellular networks. It will thereby contribute to: 1. defining conditions for the preparation of food that increase food safety (i.e. decreases the risk of contamination with pathogens). 2. defining conditions for the preparation of food with mixtures of microorganisms that enhance taste 3. define conditions of food and eating, such that when swallowed it does not promote the growth of the more pathogenic species in the throat or the intestines. 4. understanding how L. plantarum acts probiotically and how its activity can be varied by providing optimized conditions, e.g. in terms of food for its human host. The food and food-transport industry will benefit from items 1 and 2. The food preparation industry ('biological restaurants') could benefit from the progress on item 2. Item 3 could be useful for the medical sector. Item 4 will be important for the new industry that promotes probiotic foods. Because of the increased use of computation, also the software and hardware industries will benefit. The general public may benefit from this research by being enabled to understand that not all bacteria are 'bad', and more specifically that quite similar bacteria can be good versus bad for the human, also depending on the context (E. faecalis). We may also demonstrate that rather than being like magic, this is something that can be understood by computer modelling. The whole project is also a model system to study the more general question to what extent differences in networking of essentially the same molecules can produce entirely different functionalities. This general issue is relevant for the understanding of the difference between tumor cells and their normal parental cells. It is also important in the context of metabolic engineering and synthetic biology, by enabling one to understand to what extent can one make a network produce other molecules or respond differently, by changing the networking of its molecules. Here the project may serve the academic community interested in metabolic engineering and tumour biology. 2) How will they benefit from this research? They will benefit as suggested above. In addition, the food industry and the newer industry that aims to produce more probiotic mixtures of bacteria and food, may benefit from the experiment-based models that this project will produce. These models should enable them to calculate new possible mixtures. They may also suggest ways in which the microbial ecosystem of these probiotics can be kept under control by implementing certain conditions. 3) What will be done during the course of the grant to ensure that they have the opportunity to benefit from this research? This is described in the impact plan.