Biology subjects

Bahl, C. D.

Publications and source records attributed to Bahl, C. D..

8 recordsLinked to original sources

bioRxiv2026

MPNN-guided redesign of PET hydrolases with enhanced catalytic activity below the PET glass transition temperature

Enzymatic depolymerization of polyethylene terephthalate (PET) presents a sustainable route for plastic circularity, but its industrial viability is disadvantaged by the need for thermostable enzymes active under mild, energy-efficient conditions. While Polyester Hydrolase Leipzig 7 (PHL7, also known as PES-H1) rapidly degrades amorphous PET near the glass transition temperature of this polymer (~65{degrees}C), its poor protein expression, inactivation above 60{degrees}C and slow depolymerization below 60{degrees}C limits its practical application. Here, we employ ProteinMPNN and LigandMPNN, structural and evolutionary information, to redesign the sequence of PHL7 and improve protein expression, thermostability and activity. We identified 2/36 experimentally tested variants (D5, D11) with enhanced PET depolymerization at 50{degrees}C, achieving the same efficiency as PHL7 at 70{degrees}C but with a shifted product profile, favoring mono-(2-hydroxyethyl) terephthalate (MHET) over terephthalate. Molecular dynamics revealed that these redesigns exhibit enhanced flexibility in active site regions, providing a mechanistic understanding of their low-temperature catalysis. These variants enable a potential route to resynthesize virgin PET via MHET polycondensation, offering an efficient circular economy pathway.

bioengineering↗

bioRxiv2024

Molecular basis for the transcriptional regulation of an epoxide-based virulence circuit in Pseudomonas aeruginosa

The opportunistic pathogen Pseudomonas aeruginosa infects cystic fibrosis (CF) patient airways and produces a virulence factor Cif that is associated with worse outcomes. Cif is an epoxide hydrolase that reduces cell-surface abundance of the cystic fibrosis transmembrane conductance regulator (CFTR) and sabotages pro-resolving signals. Its expression is regulated by a divergently transcribed TetR family transcriptional repressor. CifR represents the first reported epoxide-sensing bacterial transcriptional regulator, but neither its interaction with cognate operator sequences nor the mechanism of activation has been investigated. Using biochemical and structural approaches, we uncovered the molecular mechanisms controlling this complex virulence operon. We present here the first molecular structures of CifR alone and in complex with operator DNA, resolved in a single crystal lattice. Significant conformational changes between these two structures suggest how CifR regulates the expression of the virulence gene cif. Interactions between the N-terminal extension of CifR with the DNA minor groove of the operator play a significant role in the operator recognition of CifR. We also determined that cysteine residue Cys107 is critical for epoxide sensing and DNA release. These results offer new insights into the stereochemical regulation of an epoxide-based virulence circuit in a critically important clinical pathogen.

biochemistry↗

bioRxiv2023

Simultaneous enhancement of multiple functional properties using evolution-informed protein design

Designing optimized proteins is important for a range of practical applications. Protein design is a rapidly developing field that would benefit from approaches that enable many changes in the amino acid primary sequence, rather than a small number of mutations, while maintaining structure and enhancing function. Homologous protein sequences contain extensive information about various protein properties and activities that have emerged over billions of years of evolution. Evolutionary models of sequence co-variation, derived from a set of homologous sequences, have proven effective in a range of applications including structure determination and mutation effect prediction. In this work we apply one of these models (EVcouplings) to computationally design highly divergent variants of the model protein TEM-1 {beta}-lactamase, and characterize these designs experimentally using multiple biochemical and biophysical assays. Nearly all designed variants were functional, including one with 84 mutations from the nearest natural homolog. Surprisingly, all functional designs had large increases in thermostability and most had a broadening of available substrates. These property enhancements occurred while maintaining a nearly identical structure to the wild type enzyme. Collectively, this work demonstrates that evolutionary models of sequence co-variation (1) are able to capture complex epistatic interactions that successfully guide large sequence departures from natural contexts, and (2) can be applied to generate functional diversity useful for many applications in protein design.

synthetic biology↗

bioRxiv2021

Growing Glycans in Rosetta: Accurate de novo glycan modeling, density fitting, and rational sequon design

Carbohydrates and glycoproteins modulate key biological functions. Computational approaches inform function to aid in carbohydrate structure prediction, structure determination, and design. However, experimental structure determination of sugar polymers is notoriously difficult as glycans can sample a wide range of low energy conformations, thus limiting the study of glycan-mediated molecular interactions. In this work, we expanded the RosettaCarbohydrate framework, developed and benchmarked effective tools for glycan modeling and design, and extended the Rosetta software suite to better aid in structural analysis and benchmarking tasks through the SimpleMetrics framework. We developed a glycan-modeling algorithm, GlycanTreeModeler, that computationally builds glycans layer-by-layer, using adaptive kernel density estimates (KDE) of common glycan conformations derived from data in the Protein Data Bank (PDB) and from quantum mechanics (QM) calculations. After a rigorous optimization of kinematic and energetic considerations to improve near-native sampling enrichment and decoy discrimination, GlycanTreeModeler was benchmarked on a test set of diverse glycan structures, or "trees". Structures predicted by GlycanTreeModeler agreed with native structures at high accuracy for both de novo modeling and experimental density-guided building. GlycanTreeModeler algorithms and associated tools were employed to design de novo glycan trees into a protein nanoparticle vaccine that are able to direct the immune response by shielding regions of the scaffold from antibody recognition. This work will inform glycoprotein model prediction, aid in both X-ray and electron microscopy density solutions and refinement, and help lead the way towards a new era of computational glycobiology.

molecular biology↗

bioRxiv2021

Humoral immune responses against seasonal coronaviruses predict efficiency of SARS-CoV-2 spike targeting, FcγR activation, and corresponding COVID-19 disease severity

Despite SARS-CoV-2 being a "novel" coronavirus, several studies suggest that detection of anti-spike IgG early in infection may be attributable to the amplification of humoral memory responses against seasonal hCoVs in severe COVID-19 patients. In this study, we examined this concept by characterizing anti-spike IgG from a cohort of non-hospitalized convalescent individuals with a spectrum of COVID-19 severity. We observed that anti-spike IgG levels positively correlated with disease severity, higher IgG cross-reactivity against betacoronaviruses (SARS-CoV-1 and OC43), and higher levels of proinflammatory Fc gamma receptor 2a and 3a (Fc{gamma}R2a & Fc{gamma}R3a) activation. In examining the levels of IgG targeting betacoronavirus conserved and immunodominant epitopes versus disease severity, we observed a positive correlation with the levels of IgG targeting the conserved S2FP region, and an inverse correlation with two conserved epitopes around the heptad repeat (HR) 2 region. In comparing the levels of IgG targeting non-conserved epitopes, we observed that only one of three non-conserved immunodominant epitopes correlated with disease severity. Notably, the levels of IgG targeting the receptor binding domain (RBD) were inversely correlated with severity. Importantly, targeting of the RBD and HR2 regions have both been shown to mediate SARS-CoV-2 neutralization. These findings show that, aside from antibody (Ab) targeting of the RBD region, humoral memory responses against seasonal betacoronaviruses are potentially an important factor in dictating COVID-19 severity, with anti-HR2-dominant Ab profiles representing protective memory responses, while an anti-S2FP dominant Ab profiles indicate deleterious recall responses. Though these profiles are masked in whole antigen profiling, these analyses suggest that distinct Ab memory responses are detectable with epitope targeting analysis. These findings have important implications for predicting severity of SARS-CoV-2 infections (primary and reinfections), and may predict vaccine efficacy in subpopulations with different dominant antibody epitope profiles.

microbiology↗

bioRxiv2021

Ensuring scientific reproducibility in bio-macromolecular modeling via extensive, automated benchmarks

Each year vast international resources are wasted on irreproducible research. The scientific community has been slow to adopt standard software engineering practices, despite the increases in high-dimensional data, complexities of workflows, and computational environments. Here we show how scientific software applications can be created in a reproducible manner when simple design goals for reproducibility are met. We describe the implementation of a test server framework and 40 scientific benchmarks, covering numerous applications in Rosetta bio-macromolecular modeling. High performance computing cluster integration allows these benchmarks to run continuously and automatically. Detailed protocol captures are useful for developers and users of Rosetta and other macromolecular modeling tools. The framework and design concepts presented here are valuable for developers and users of any type of scientific software and for the scientific community to create reproducible methods. Specific examples highlight the utility of this framework and the comprehensive documentation illustrates the ease of adding new tests in a matter of hours.

bioinformatics↗

bioRxiv2021

Biochemical and Structural Characterization of Two Cif-Like Epoxide Hydrolases from Burkholderia cenocepacia

Epoxide hydrolases catalyze the conversion of epoxides to vicinal diols in a range of cellular processes such as signaling, detoxification, and virulence. These enzymes typically utilize a pair of tyrosine residues to orient the substrate epoxide ring in the active site and stabilize the hydrolysis intermediate. A new subclass of epoxide hydrolases that utilize a histidine in place of one of the tyrosines was established with the discovery of the CFTR Inhibitory Factor (Cif) from Pseudomonas aeruginosa. Although the presence of such Cif-like epoxide hydrolases was predicted in other opportunistic pathogens based on sequence analyses, only Cif and its homologue aCif from Acinetobacter nosocomialis have been characterized. Here we report the biochemical and structural characteristics of Cfl1 and Cfl2, two Cif-like epoxide hydrolases from Burkholderia cenocepacia. Cfl1 is able to hydrolyze xenobiotic as well as biological epoxides that might be encountered in the environment or during infection. In contrast, Cfl2 shows very low activity against a diverse set of epoxides. The crystal structures of the two proteins reveal quaternary structures that build on the well-known dimeric assembly of the /{beta} hydrolase domain, but broaden our understanding of the structural diversity encoded in novel oligomer interfaces. Analysis of the interfaces reveals both similarities and key differences in sequence conservation between the two assemblies, and between the canonical dimer and the novel oligomer interfaces of each assembly. Finally, we discuss the effects of these higher-order assemblies on the intra-monomer flexibility of Cfl1 and Cfl2 and their possible roles in regulating enzymatic activity.

biochemistry↗

bioRxiv2020

The evolution of non-motif selectivity determinants in Monosiga brevicollis PDZ domains

The evolution of signaling pathways is complex and well-studied. In particular, the emergence of animal multicellularity had a major impact on protein-protein interactions and signaling systems in eukaryotic cells. However, choanoflagellates, our closest non-metazoan ancestor, contain a number of closely related signaling and trafficking proteins and domains. In addition, because choanoflagellates can adopt a rosette-/multicellular-like state, a lot can be gained by comparing proteins involved in choanoflagellate and human signaling pathways. Here, we look at how selectivity determinants evolved in the PDZ domain. There are over 250 PDZ domains in the human proteome, which are involved in critical protein-protein interactions that result in large multimolecular complexes, e.g., in the postsynaptic density of neuronal synapses. Binding of C-terminal sequences by PDZ domains is often transient and recognition typically involves 6 residues or less, with only 2 residues specifying the binding motif. We solved high resolution crystal structures of Monosiga brevicollis PDZ domains homologous to human Dlg1 PDZ2, Dlg1 PDZ3, GIPC, and SHANK1 PDZ domains to investigate if the non-motif preferences are conserved, despite hundreds of millions of years of evolution. We also calculated binding affinities for GIPC, SHANK1, and SNX27 PDZ domains from M. brevicollis. Overall, we found that peptide selectivity is conserved between these two disparate organisms, with one exception, mbDLG-3. In addition, we identify 178 PDZ domains in the M. brevicollis proteome, including 11 new sequences, which we verified using Rosetta and homology modeling. Overall, our results provide novel insight into signaling pathways in the choanoflagellate organism.

biochemistry↗