92B05 General biology and biomathematics
Refine
Has Fulltext
- yes (2)
Document Type
- Doctoral Thesis (2)
Language
- English (2)
Is part of the Bibliography
- yes (2)
Keywords
- ACD6 (1)
- Anpassung (1)
- Antibiotika (1)
- Arabidopsis (1)
- Dialel (1)
- Erbe (1)
- Nekrose (1)
- Pharmakodynamik (1)
- Stoffwechsel (1)
- Variation (1)
Institute
Plants are unable to move away from unwanted environments and therefore have to locally adapt to changing conditions. Arabidopsis thaliana (Arabidopsis), a model organism in plant biology, has been able to rapidly colonize a wide spectrum of environments with different biotic and abiotic challenges. In recent years, natural variation in Arabidopsis has shown to be an excellent resource to study genes underlying adaptive traits and hybridization’s impact on natural diversity. Studies on Arabidopsis hybrids have provided information on the genetic basis of hybrid incompatibilities and heterosis, as well as inheritance patterns in hybrids. However, previous studies have focused mainly on global accessions and yet much remains to be known about variation happening within a local growth habitat. In my PhD, I investigated the impact of heterozygosity at a local collection site of Arabidopsis and its role in local adaptation. I focused on two different projects, both including hybrids among Arabidopsis individuals collected around Tübingen in Southern Germany. The first project sought to understand the impact of hybridization on metabolism and growth within a local Arabidopsis collection site. For this, the inheritance patterns in primary and secondary metabolism, together with rosette size of full diallel crosses among seven parents originating from Southern Germany were analyzed. In comparison to primary metabolites, compounds from secondary metabolism were more variable and showed pronounced non-additive inheritance patterns. In addition, defense metabolites, mainly glucosinolates, displayed the highest degree of variation from the midparent values and were positively correlated with a proxy for plant size.
In the second project, the role of ACCELERATED CELL DEATH 6 (ACD6) in the defense response pathway of Arabidopsis necrotic hybrids was further characterized. Allelic interactions of ACD6 have been previously linked to hybrid necrosis, both among global and local Arabidopsis accessions. Hence, I characterized the early metabolic and ionic changes induced by ACD6, together with marker gene expression assays of physiological responses linked to its activation. An upregulation of simple sugars and metabolites linked to non-enzymatic antioxidants and the TCA cycle were detected, together with putrescine and acids linked to abiotic stress responses. Senescence was found to be induced earlier in necrotic hybrids and cytoplasmic calcium signaling was unaffected in response to temperature. In parallel, GFP-tagged constructs of ACD6 were developed.
This work therefore gave novel insights on the role of heterozygosity in natural variation and adaptation and expanded our current knowledge on the physiological and molecular responses associated with ACD6 activation.
Mathematical models of bacterial growth have been successfully applied to study the relationship between antibiotic drug exposure and the antibacterial effect. Since these models typically lack a representation of cellular processes and cell physiology, the mechanistic integration of drug action is not possible on the cellular level. The cellular mechanisms of drug action, however, are particularly relevant for the prediction, analysis and understanding of interactions between antibiotics. Interactions are also studied experimentally, however, a lacking consent on the experimental protocol hinders direct comparison of results. As a consequence, contradictory classifications as additive, synergistic or antagonistic are reported in literature.
In the present thesis we developed a novel mathematical model for bacterial growth that integrates cell-level processes into the population growth level. The scope of the model is to predict bacterial growth under antimicrobial perturbation by multiple antibiotics in vitro.
To this end, we combined cell-level data from literature with population growth data for Bacillus subtilis, Escherichia coli and Staphylococcus aureus. The cell-level data described growth-determining characteristics of a reference cell, including the ribosomal concentration and efficiency. The population growth data comprised extensive time-kill curves for clinically relevant antibiotics (tetracycline, chloramphenicol, vancomycin, meropenem, linezolid, including dual combinations).
The new cell-level approach allowed for the first time to simultaneously describe single and combined effects of the aforementioned antibiotics for different experimental protocols, in particular different growth phases (lag and exponential phase). Consideration of ribosomal dynamics and persisting sub-populations explained the decreased potency of linezolid on cultures in the lag phase compared to exponential phase cultures. The model captured growth rate dependent killing and auto-inhibition of meropenem and - also for vancomycin exposure - regrowth of the bacterial cultures due to adaptive resistance development. Stochastic interaction surface analysis demonstrated the pronounced antagonism between meropenem and linezolid to be robust against variation in the growth phase and pharmacodynamic endpoint definition, but sensitive to a change in the experimental duration.
Furthermore, the developed approach included a detailed representation of the bacterial cell-cycle. We used this representation to describe septation dynamics during the transition of a bacterial culture from the exponential to stationary growth phase. Resulting from a new mechanistic understanding of transition processes, we explained the lag time between the increase in cell number and bacterial biomass during the transition from the lag to exponential growth phase. Furthermore, our model reproduces the increased intracellular RNA mass fraction during long term exposure of bacteria to chloramphenicol.
In summary, we contribute a new approach to disentangle the impact of drug effects, assay readout and experimental protocol on antibiotic interactions. In the absence of a consensus on the corresponding experimental protocols, this disentanglement is key to translate information between heterogeneous experiments and also ultimately to the clinical setting.