It is known that bacterial populations could quickly adapt to antibiotic treatments by becoming tolerant and resistant to the drug. Recently, adaptive laboratory evolution (ALE) has proven to be a useful strategy to generate mutants that are adapted to different treatment conditions, and opens up a new avenue for studying antibiotic tolerance and resistance, since it is robust and can be highly parallelized, generating numerous mutants in a short time. Besides, this kind of laboratory evolution protocol mimics how bacteria evolved in clinical patients. Combining it with proteomics, one can cross-compare multiple resistant and tolerant strains that evolved from the same ancestor to study their differential adaptation strategies, resulting in more protein candidates associated wit...[ Read more ]

It is known that bacterial populations could quickly adapt to antibiotic treatments by becoming tolerant and resistant to the drug. Recently, adaptive laboratory evolution (ALE) has proven to be a useful strategy to generate mutants that are adapted to different treatment conditions, and opens up a new avenue for studying antibiotic tolerance and resistance, since it is robust and can be highly parallelized, generating numerous mutants in a short time. Besides, this kind of laboratory evolution protocol mimics how bacteria evolved in clinical patients. Combining it with proteomics, one can cross-compare multiple resistant and tolerant strains that evolved from the same ancestor to study their differential adaptation strategies, resulting in more protein candidates associated with tolerance. This can be a viable roadmap to mapping the “tolerome”, the collection of genes/proteins that are important for tolerance. This information will be of tremendous clinical value because it has become increasingly recognized that tolerance accelerates the evolution of resistance, and diagnostic tools and suitable therapy for combatting tolerance will also be key to preventing resistance development.

In the 2^nd Chapter, we subjected E. coli populations to ALE using different antibiotics from different classes (β-lactam, aminoglycoside, and fluoroquinolone), generating three evolved populations with distinct mutations and tolerance mechanisms (Evo3A, Evo3C, Evo3P). Using proteomics, we cross-compared the proteome profile of the three tolerant populations to obtain the key players in their tolerance phenotype. Six protein candidates with similar expression profiles across the three evolved populations were obtained, which were GrcA, NuoF, CysP, AhpF, RaiA, and ribosome recycling factor (RRF). The importance of these proteins on antibiotic tolerance was validated through gene knockout assay. In the 3^rd Chapter, we followed up on one of the evolved populations from ampicillin treatment, Evo3A. Through time-course proteomics, we showed that xvii the tolerant population employed an activated SOS response and a suppression of ROS generation, along with other metabolic adjustments. In addition, Evo3A mutants also filamented extensively when exposed to ampicillin, ostensibly a mechanism to evade the antibiotic’s effect.

In the second part of our study, we switched gear to study a more clinically relevant pathogen, methicillin-resistant S. aureus (MRSA). In the 4^th Chapter, we used ALE with different drug combination schemes and showed that differences in the treatment conditions can lead to different tolerance/resistance phenotypes. Two weeks of intermittent daptomycin (DAP) treatment led to a DAP-tolerant strain with a point mutation 9 base-pairs upstream pgsA gene, while two weeks of DAP and rifampin (RIF) treatment led to a DAP-resistant strain with a mutation in the mprF gene which has been previously observed in clinical isolates. Remarkably, adding RIF to the treatment regime after one week of DAP treatment led to reduced tolerance through an additional mutation in the pta gene. By performing comparative proteomics of the three evolved strains with different phenotypes, we observed that the resistant strains were less perturbed by antibiotic treatment, whereas the tolerant strains exhibited a far more complicated response, with a large number of differentially regulated processes including reduced ribosomal proteins and phosphorelay sensor kinase activity, increased tryptophan synthase activity, and cell wall modulation. In the 5^th Chapter, we employed ALE by treating parallel MRSA populations in different growth phases to hunt for novel tolerance and resistance mutations and explored their evolutionary dynamics. We generated multiple resistant and tolerant strains bearing single point mutations in different genes governing their tolerance/resistance phenotypes. In addition, we found out that tolerance mutation appeared first in the population, but was then invaded by the resistant mutant. Through competition experiments on the emerging mutants, we showed that the final population genotype and phenotype heavily depend on the survival advantages conferred by the tolerance/resistance mutations during antibiotic treatment. In the 6^th Chapter, we followed up on 3 resistant and 3 tolerant mutants that evolved from the same ancestor from Chapter 5, and performed a comprehensive proteomics analysis to study and cross-compare these MRSA strains with distinct daptomycin tolerance/resistance phenotypes. We observed that the strain with the highest tolerance level compared to the others has the most different proteome and response to antibiotic treatment, resembling those observed in persister cells. Through cross-comparison analysis and gene overexpression assay, we found the key proteins that play important roles in each of the tolerance and resistance phenotypes. Moreover, we also showed that while the resistant strains have peptidoglycan changes and a more positive surface charge to directly repel daptomycin, the tolerant strains possessed other cell wall changes that do not involve the peptidoglycan nor alterations of the surface charge. In the 7^th Chapter, we further investigated the effect of population bottlenecks in the development of tolerance/resistance in MRSA populations under daptomycin treatment. We observed that although tolerance development is slower under bottlenecking conditions, the populations finally attained tolerance mutation in the yycH gene, and additional mutations in yycI and several other genes led to an even higher tolerance level. Through proteomics, we showed that the yycH and yycI mutations led to the loss-of-function of the protein, down-regulated the WalRK two-component system, and the downstream players including the autolysin Atl and amidase Sle1 that are important for cell wall metabolism.

In the last part of our study, we focused on finding and characterizing novel therapeutic agents that could kill MRSA cells and eradicate their biofilms. Through bioassay-guided isolation, our collaborators have identified elasnin as a promising compound for the eradication of MRSA biofilms. In the 8^th Chapter, we found out that in addition to its remarkable anti-biofilm properties, elasnin also has antibacterial activity and can kill growing MRSA planktonic cells. Through in xix vitro laboratory evolution, we found out that populations repetitively treated with elasnin consistently attained a mutation in a putative phosphate transport regulator, and the evolved strains exhibited increased elasnin tolerance, reduced growth rate, loss of pigmentation, and increased intracellular phosphate (P_i) and polyphosphate levels. Through multi-omic analysis, we uncovered the affected processes on the WT and tolerant MRSA planktonic cells following elasnin treatment. In the 9^th Chapter, we discovered that elasnin has superior activity in eradicating the biofilm of a clinically observed daptomycin-resistant MRSA strain. Proteomics analysis revealed that this superior activity is due to the lower expression of key proteins that play a role in pathogenesis and cell adhesion in the daptomycin-resistant strain, leading to weaker biofilm development.

Altogether, we developed an experimental method to study antibiotic persistence and tolerance of E. coli model organism bacteria by high-throughput proteomics (Chapter 2 and 3), elucidated the key players and processes involved in antibiotic tolerance and resistance of MRSA pathogen towards different treatment conditions (Chapter 4, 5, 6, and 7), and characterized elasnin as a novel compound for the eradication of MRSA and decipher its mode of action (Chapter 8 and 9).