Biology subjects

Gaszek, I. K.

Publications and source records attributed to Gaszek, I. K..

4 recordsLinked to original sources

bioRxiv2025

Saturation mutagenesis map of generalist versus specialist adaptations of β-lactamase to novel antibiotics

The evolution of {beta}-lactamase proteins is shaped by the need to maintain enzymatic activity against previously prevalent {beta}-lactam antibiotics while expanding substrate range against new classes of antibiotics. Using saturation mutagenesis and sequence-barcoding-based quantification, we comprehensively mapped the response of the fitness landscape of TEM-1 {beta}-lactamase, which evolved against penicillin-class antibiotics, to mutational perturbations against six diverse {beta}-lactam antibiotics. This systematic panel of antibiotic substrates, including representatives from penicillin, cephalosporin, and monobactam classes, allowed us to classify resistance mutations into two categories. Generalist mutations conferred resistance to multiple antibiotics and were consistently restricted to three positions critical for substrate recognition and catalytic function R164, G238, and E240. These substitutions produced broad spectrum resistance through mechanisms such as expansion of the active site and improved substrate accommodation. In contrast, specialist mutations conferred resistance to only a single antibiotic and exhibited much wider positional diversity. Ceftazidime selection yielded the greatest number of distinct specialist mutations, which were frequently found in flexible or peripheral regions including the omega loop. One especially unexpected finding was the identification of the E166P variant. E166 is a catalytic residue required for deacylation during hydrolysis, and substitutions at this site are generally assumed to abolish function. However, E166P conferred a significant increase in ceftazidime resistance despite eliminating activity against penicillins. Molecular dynamics simulations and mutational analysis revealed that the E166P mutant employs an alternative catalytic mechanism, involving residue N132, rather than the canonical pathway. Together, our findings reveal, at the molecular level, how specialist mutations open up a wide range of diverse and idiosyncratic solutions at the expense of generalizability. These insights may inform strategic design of antibiotic administration protocols to systematically lower pathogenic evolvability.

evolutionary biology↗

bioRxiv2025

Higher-order epistasis drives evolutionary unpredictability toward novel antibiotic resistance

The rapid evolution of extended-spectrum {beta}-lactamases (ESBLs) represents a global health threat, undermining the efficacy of {beta}-lactams, the most extensively used antibiotic class. To elucidate the evolutionary dynamics underlying {beta}-lactam resistance, we constructed a comprehensive combinatorial mutant library comprising all 55,296 possible TEM-1 {beta}-lactamase variants integrating 18 clinically observed mutations across 13 key residues. Over eight million empirical fitness measurements were obtained under selection pressure with both a native antibiotic substrate (ampicillin) and a novel antibiotic (aztreonam), establishing the largest experimentally determined fitness landscape for antibiotic resistance to date. Through graph-theoretic and epistatic analyses, we discovered that selection with ampicillin resulted in weak epistasis, with mutants rarely surpassing the fitness of the wild-type enzyme. Conversely, aztreonam selection elicited extensive higher-order epistasis, generating a rugged fitness landscape characterized by increased phenotypic unpredictability. Interpretable machine-learning analyses identified context-dependent epistatic interactions necessary for achieving high-level aztreonam resistance. Further evolutionary statistical analyses, including direct coupling analysis and latent generative landscapes, showed that top-performing TEM-1 variants consistently adhered to conserved epistatic patterns found in naturally occurring {beta}-lactamases. Our findings demonstrate that higher-order epistasis critically shapes fitness landscape ruggedness when enzymes adapt to novel substrates, whereas adaptations to native substrates exhibit predictably smoother landscapes. This integrated experimental and computational framework provides a foundation for predictive evolutionary pharmacology, enabling assessments of newly developed {beta}-lactams or emerging {beta}-lactamase variants for their potential contribution to ESBL evolution. Importantly, incorporating graph-theoretically informed evolutionary constraints can strategically disrupt evolutionary pathways, presenting a viable approach to mitigate the rise of antibiotic resistance.

evolutionary biology↗

bioRxiv2024

Elucidating TolC Protein Dynamics: Structural Shifts Facilitate Efflux Mediated β-lactam Resistance

Efflux-mediated {beta}-lactam resistance represents a significant public health challenge, limiting the efficacy of various {beta}-lactam antibiotics against numerous clinically relevant pathogenic bacteria. Structural and functional analyses have revealed that the efflux protein TolC in several Gram-negative bacteria serves as a conduit for antibiotics, bacteriocins, and phages, affecting bacterial susceptibility and virulence. In this study, we conducted a comprehensive examination of the efflux of {beta}-lactam drugs mediated by TolC, employing extensive experimental and computational analyses. Our computational investigations into the molecular dynamics of drug-free TolC revealed critical unidirectional movements of the trimeric TolC and identified residues significantly involved in TolC opening. To corroborate these findings, we performed a whole-gene-saturation mutagenesis assay, systematically mutating each residue of TolC to 19 other amino acids and measuring the fitness effects of these mutations under {beta}-lactam-induced selection. The {beta}-lactams oxacillin, piperacillin, and carbenicillin were selected for this study because they are effluxed by the AcrAB-TolC complex with varying efficiencies. This approach clarified the similarities and differences in the efflux processes of the three {beta}-lactam antibiotics through the trimeric TolC. Further analysis of TolCs efflux mechanism for these {beta}-lactam antibiotics via steered molecular dynamics simulations revealed the existence of general and drug-specific mechanisms employed by TolC. We identified key positions at the periplasmic entry of TolC whose altered dynamics influence long-range efflux motions as allosteric modulators. Our findings provide valuable insights into the structural dynamics of TolC, establishing a foundation for understanding the key mechanisms behind multidrug resistance and principles for designing new antibiotics and antibiotic derivatives capable of circumventing the bacterial efflux mechanism.

biophysics↗

bioRxiv2018

High-order epistasis in catalytic power of dihydrofolate reductase gives rise to a rugged fitness landscape in the presence of trimethoprim selection

Evolutionary fitness landscapes of certain antibiotic target enzymes have been comprehensively mapped showing strong high order epistasis between mutations, but understanding these effects at the biochemical and molecular levels remained open. Here, we carried out an extensive experimental and computational study to quantitatively understand the evolutionary dynamics of Escherichia coli dihydrofolate reductase (DHFR) enzyme in the presence of trimethoprim induced selection. Biochemical and structural characterization of resistance-conferring mutations targeting a total of ten residues spanning the substrate binding pocket of DHFR revealed distinct resistance mechanisms. Next, we experimentally measured biochemical parameters (Km, Ki, and kcat) for a mutant library carrying all possible combinations of six resistance-conferring DHFR mutations and quantified epistatic interactions between them. We found that the epistasis between DHFR mutations is high-order for catalytic power of DHFR (kcat and Km), but less prevalent for trimethoprim affinity (Ki). Taken together our data provide a concrete illustration of how epistatic coupling at the level of biochemical parameters can give rise to complex fitness landscapes, and suggest new strategies for developing mutant specific inhibitors.

evolutionary biology↗