טכניון מכון טכנולוגי לישראל
הטכניון מכון טכנולוגי לישראל - בית הספר ללימודי מוסמכים  
Ph.D Thesis
Ph.D StudentRuss Dor
SubjectBacterial Response to Multitude of Effectors, in Nature
and in the Lab
DepartmentDepartment of Biology
Supervisors Professor Roy Kishony
Professor Oded Beja
Full Thesis textFull thesis text - English Version


Abstract

From natural ecology to clinical therapy, cells are often exposed to mixtures of multiple stresses. Those stressors affect the prosperity and survival of individual species and the structure of whole communities. In this work, I study how the combination of multiple drugs affect the growth of individual species and how members of multiple species communities are distributed across spatial niches in the natural multi-stressor environment of soil. In the first project, we asked what is the null expectation for the combined effect of drug combinations. Two competing null models are used to predict the combined effect of drugs: response additivity (Bliss) and dosage additivity (Loewe). Noting that these models diverge with increased number of drugs, we contrast their predictions with measurements of Escherichia coli growth under combinations of up to 10 different antibiotics. We find that as the number of drugs increases, Bliss maintains accuracy while Loewe systematically loses its predictive power. The total dosage required for growth inhibition, which Loewe predicts should be fixed, steadily increases with the number of drugs, following a square root scaling. This scaling is explained by an approximation to Bliss where dosages of independent drugs add up as orthogonal vectors rather than linearly as in Loewe. The rejection of dosage additivity in favor of effect additivity and dosage orthogonality provides a framework for understanding how multiple drugs and stressors add up in nature and suggests that many-drug therapies may require higher dosages than classically anticipated. In the second project, we zoomed out to an entire community and asked what governs the abundance of microbial species across microhabitats in natural soil communities. The soil is heavily populated by diverse microbial species. While community composition and behavior are well described at the metacommunity level, less is known about the way this community is distributed across small microhabitats. We developed a method to map the population of small soil aggregates using metagenomic amplicon sequencing of the 16S rRNA gene often used as a phylogenetic marker. We found that the relative abundance of individual species are distributed lognormally across aggregates. Combined with a model of dispersal and growth, which is affected by multitude of stressors, this log normality rejects the possibility that each species is limited by different metabolic niche. Instead, these results are consistent with the species abundance being dominated by interspecies competition for resources, occurring independently on each single soil aggregate. Interestingly, as most species are rare any two species rarely co-occur on the same aggregate and the long normal distribution of each given species stems from competition with different set of competitors on each aggregate. To examine if pairwise competitions re-occur across the aggregates we measured the correlations between the abundance of species. Our findings highlight the importance of studying the soil microbiome at small spatial scale and enhance our understanding of the forces govern the assembly of soil microbial communities. Together the two projects combine the use of mathematical tools, high throughput measurements and computation to address biological questions and provide new insights that promote our understanding in the fields of drug combinations and microbial ecology.