Building blocks and blueprints for bacterial autolysins.

Bacteria utilize a wide variety of endogenous cell wall hydrolases, or autolysins, to remodel their cell walls during processes including cell division, biofilm formation, and programmed death. We here systematically investigate the composition of these enzymes in order to gain insights into their associated biological processes, potential ways to disrupt them via chemotherapeutics, and strategies by which they might be leveraged as recombinant antibacterial biotherapies. To do so, we developed LEDGOs (lytic enzyme domains grouped by organism), a pipeline to create and analyze databases of autolytic enzyme sequences, constituent domain annotations, and architectural patterns of multi-domain enzymes that integrate peptidoglycan binding and degrading functions. We applied LEDGOs to eight pathogenic bacteria, gram negatives Acinetobacter baumannii, Klebsiella pneumoniae, Neisseria gonorrhoeae, and Pseudomonas aeruginosa; and gram positives Clostridioides difficile, Enterococcus faecium, Staphylococcus aureus, and Streptococcus pneumoniae. Our analysis of the autolytic enzyme repertoires of these pathogens reveals commonalities and differences in their key domain building blocks and architectures, including correlations and preferred orders among domains in multi-domain enzymes, repetitions of homologous binding domains with potentially complementarity recognition modalities, and sequence similarity patterns indicative of potential divergence of functional specificity among related domains. We have further identified a variety of unannotated sequence regions within the lytic enzymes that may themselves contain new domains with important functions.

Electrostatic-Mediated Affinity Tuning of Lysostaphin Accelerates Bacterial Lysis Kinetics and Enhances In Vivo Efficacy.

Drug-resistant bacterial pathogens are a serious threat to global health, and antibacterial lysins are at the forefront of innovative treatments for these life-threatening infections. While lysins' general mechanism of action is well understood, the design principles that might enable engineering of performance-enhanced variants are still being formulated. Here, we report a detailed analysis of molecular determinants underlying the in vivo efficacy of lysostaphin, a canonical anti-MRSA (methicillin-resistant Staphylococcus aureus) lysin. Systematic analysis of bacterial binding, growth inhibition, lysis kinetics, and in vivo therapeutic efficacy revealed that binding affinity, and not inherent catalytic firepower, is the dominant driver of lysostaphin efficacy. This insight enabled electrostatic affinity tuning of lysostaphin to produce a single point mutant that manifested dramatically enhanced processivity and lysis kinetics and trended toward improved in vivo efficacy. More generally, these studies provide important insights into the complex relationships between lysin electrostatics, bacterial targeting, cell lysis efficiency, and in vivo efficacy. The lessons learned may enable engineering of other high-performance antibacterial biocatalysts.

Deimmunized Lysostaphin Synergizes with Small-Molecule Chemotherapies and Resensitizes Methicillin-Resistant Staphylococcus aureus to ß-Lactam Antibiotics.

There is an urgent need for novel agents to treat drug-resistant bacterial infections, such as multidrug-resistant Staphylococcus aureus (MRSA). Desirable properties for new antibiotics include high potency, narrow species selectivity, low propensity to elicit new resistance phenotypes, and synergy with standard-of-care (SOC) chemotherapies. Here, we describe analysis of the antibacterial potential exhibited by F12, an innovative anti-MRSA lysin that has been genetically engineered to evade detrimental antidrug immune responses in human patients. F12 possesses high potency and rapid onset of action, it has narrow selectivity against pathogenic staphylococci, and it manifests synergy with numerous SOC antibiotics. Additionally, resistance to F12 and ß-lactam antibiotics appears mutually exclusive, and, importantly, we provide evidence that F12 resensitizes normally resistant MRSA strains to ß-lactams both in vitro and in vivo These results suggest that combinations of F12 and SOC antibiotics are a promising new approach to treating refractory S. aureus infections.

Bioinformatics-driven discovery of novel Clostridioides difficile lysins and experimental comparison with highly active benchmarks.

Clostridioides difficile is the single most deadly bacterial pathogen in the United States, and its global prevalence and outsized health impacts underscore the need for more effective therapeutic options. Towards this goal, a novel group of modified peptidoglycan hydrolases with significant in vitro bactericidal activity have emerged as potential candidates for treating C. difficile infections (CDI). To date, discovery and development efforts directed at these CDI-specific lysins have been limited, and in particular there has been no systematic comparison of known or newly discovered lysin candidates. Here, we detail bioinformatics-driven discovery of six new anti-C. difficile lysins belonging to the amidase-3 family of enzymes, and we describe experimental comparison of their respective catalytic domains (CATs) with highly active CATs from the literature. Our quantitative analyses include metrics for expression level, inherent antibacterial activity, breadth of strain selectivity, killing of germinating spores, and structural and functional measures of thermal stability. Importantly, prior studies have not examined stability as a performance metric, and our results show that the panel of eight enzymes possess widely variable thermal denaturation temperatures and resistance to heat inactivation, including some enzymes that exhibit marginal stability at body temperature. Ultimately, no single enzyme dominated with respect to all performance measures, suggesting the need for a balanced assessment of lysin properties during efforts to find, engineer, and develop candidates with true clinical potential.

Computer-guided binding mode identification and affinity improvement of an LRR protein binder without structure determination.

Precise binding mode identification and subsequent affinity improvement without structure determination remain a challenge in the development of therapeutic proteins. However, relevant experimental techniques are generally quite costly, and purely computational methods have been unreliable. Here, we show that integrated computational and experimental epitope localization followed by full-atom energy minimization can yield an accurate complex model structure which ultimately enables effective affinity improvement and redesign of binding specificity. As proof-of-concept, we used a leucine-rich repeat (LRR) protein binder, called a repebody (Rb), that specifically recognizes human IgG1 (hIgG1). We performed computationally-guided identification of the Rb:hIgG1 binding mode and leveraged the resulting model to reengineer the Rb so as to significantly increase its binding affinity for hIgG1 as well as redesign its specificity toward multiple IgGs from other species. Experimental structure determination verified that our Rb:hIgG1 model closely matched the co-crystal structure. Using a benchmark of other LRR protein complexes, we further demonstrated that the present approach may be broadly applicable to proteins undergoing relatively small conformational changes upon target binding.

Computationally optimized deimmunization libraries yield highly mutated enzymes with low immunogenicity and enhanced activity.

Therapeutic proteins of wide-ranging function hold great promise for treating disease, but immune surveillance of these macromolecules can drive an antidrug immune response that compromises efficacy and even undermines safety. To eliminate widespread T-cell epitopes in any biotherapeutic and thereby mitigate this key source of detrimental immune recognition, we developed a Pareto optimal deimmunization library design algorithm that optimizes protein libraries to account for the simultaneous effects of combinations of mutations on both molecular function and epitope content. Active variants identified by high-throughput screening are thus inherently likely to be deimmunized. Functional screening of an optimized 10-site library (1,536 variants) of P99 ß-lactamase (P99ßL), a component of ADEPT cancer therapies, revealed that the population possessed high overall fitness, and comprehensive analysis of peptide-MHC II immunoreactivity showed the population possessed lower average immunogenic potential than the wild-type enzyme. Although similar functional screening of an optimized 30-site library (2.15 × 109 variants) revealed reduced population-wide fitness, numerous individual variants were found to have activity and stability better than the wild type despite bearing 13 or more deimmunizing mutations per enzyme. The immunogenic potential of one highly active and stable 14-mutation variant was assessed further using ex vivo cellular immunoassays, and the variant was found to silence T-cell activation in seven of the eight blood donors who responded strongly to wild-type P99ßL. In summary, our multiobjective library-design process readily identified large and mutually compatible sets of epitope-deleting mutations and produced highly active but aggressively deimmunized constructs in only one round of library screening.

DisruPPI: structure-based computational redesign algorithm for protein binding disruption.

Motivation: Disruption of protein-protein interactions can mitigate antibody recognition of therapeutic proteins, yield monomeric forms of oligomeric proteins, and elucidate signaling mechanisms, among other applications. While designing affinity-enhancing mutations remains generally quite challenging, both statistically and physically based computational methods can precisely identify affinity-reducing mutations. In order to leverage this ability to design variants of a target protein with disrupted interactions, we developed the DisruPPI protein design method (DISRUpting Protein-Protein Interactions) to optimize combinations of mutations simultaneously for both disruption and stability, so that incorporated disruptive mutations do not inadvertently affect the target protein adversely. Results: Two existing methods for predicting mutational effects on binding, FoldX and INT5, were demonstrated to be quite precise in selecting disruptive mutations from the SKEMPI and AB-Bind databases of experimentally determined changes in binding free energy. DisruPPI was implemented to use an INT5-based disruption score integrated with an AMBER-based stability assessment and was applied to disrupt protein interactions in a set of different targets representing diverse applications. In retrospective evaluation with three different case studies, comparison of DisruPPI-designed variants to published experimental data showed that DisruPPI was able to identify more diverse interaction-disrupting and stability-preserving variants more efficiently and effectively than previous approaches. In prospective application to an interaction between enhanced green fluorescent protein (EGFP) and a nanobody, DisruPPI was used to design five EGFP variants, all of which were shown to have significantly reduced nanobody binding while maintaining function and thermostability. This demonstrates that DisruPPI may be readily utilized for effective removal of known epitopes of therapeutically relevant proteins. Availability and implementation: DisruPPI is implemented in the EpiSweep package, freely available under an academic use license. Supplementary information: Supplementary data are available at Bioinformatics online.

Mapping the Pareto optimal design space for a functionally deimmunized biotherapeutic candidate.

The immunogenicity of biotherapeutics can bottleneck development pipelines and poses a barrier to widespread clinical application. As a result, there is a growing need for improved deimmunization technologies. We have recently described algorithms that simultaneously optimize proteins for both reduced T cell epitope content and high-level function. In silico analysis of this dual objective design space reveals that there is no single global optimum with respect to protein deimmunization. Instead, mutagenic epitope deletion yields a spectrum of designs that exhibit tradeoffs between immunogenic potential and molecular function. The leading edge of this design space is the Pareto frontier, i.e. the undominated variants for which no other single design exhibits better performance in both criteria. Here, the Pareto frontier of a therapeutic enzyme has been designed, constructed, and evaluated experimentally. Various measures of protein performance were found to map a functional sequence space that correlated well with computational predictions. These results represent the first systematic and rigorous assessment of the functional penalty that must be paid for pursuing progressively more deimmunized biotherapeutic candidates. Given this capacity to rapidly assess and design for tradeoffs between protein immunogenicity and functionality, these algorithms may prove useful in augmenting, accelerating, and de-risking experimental deimmunization efforts.

Effect of alginate microencapsulation on the catalytic efficiency and in vitro enzyme-prodrug therapeutic efficacy of cytosine deaminase and of recombinant E. coli expressing cytosine deaminase.

Cytosine deaminase (CD) catalyses the enzymatic conversion of the non-toxic prodrug 5-fluorocytosine (5-FC) to the potent chemotherapeutic form, 5-fluorouracil (5-FU). Intratumoral delivery of CD localises chemotherapy dose while reducing systemic toxicity. Encapsulation in biocompatible microcapsules immunoisolates CD and protects it from degradation. We report on the effect of alginate encapsulation on the catalytic and functional activity of isolated CD and recombinant E. coli engineered to express CD (E. coli(CD)). Alginate microcapsules containing either CD or Escherichia coli(CD) were prepared using ionotropic gelation. Conversion of 5-FC to 5-FU was quantitated in unencapsulated and encapsulated CD/E. coli(CD) using spectrophotometry, with a slower rate of conversion observed following encapsulation. Both encapsulated CD/5-FC and E. coli(CD)/5-FC resulted in cell kill and reduced proliferation of 9 L rat glioma cells, which was comparable to direct 5-FU treatment. Our results show that encapsulation preserves the therapeutic potential of CD and E. coli(CD) is equally effective for enzyme-prodrug therapy.

Protein deimmunization via structure-based design enables efficient epitope deletion at high mutational loads.

Anti-drug immune responses are a unique risk factor for biotherapeutics, and undesired immunogenicity can alter pharmacokinetics, compromise drug efficacy, and in some cases even threaten patient safety. To fully capitalize on the promise of biotherapeutics, more efficient and generally applicable protein deimmunization tools are needed. Mutagenic deletion of a protein's T cell epitopes is one powerful strategy to engineer immunotolerance, but deimmunizing mutations must maintain protein structure and function. Here, EpiSweep, a structure-based protein design and deimmunization algorithm, has been used to produce a panel of seven beta-lactamase drug candidates having 27-47% reductions in predicted epitope content. Despite bearing eight mutations each, all seven engineered enzymes maintained good stability and activity. At the same time, the variants exhibited dramatically reduced interaction with human class II major histocompatibility complex proteins, key regulators of anti-drug immune responses. When compared to 8-mutation designs generated with a sequence-based deimmunization algorithm, the structure-based designs retained greater thermostability and possessed fewer high affinity epitopes, the dominant drivers of anti-biotherapeutic immune responses. These experimental results validate the first structure-based deimmunization algorithm capable of mapping optimal biotherapeutic design space. By designing optimal mutations that reduce immunogenic potential while imparting favorable intramolecular interactions, broadly distributed epitopes may be simultaneously targeted using high mutational loads.

Discovery of novel S. aureus autolysins and molecular engineering to enhance bacteriolytic activity.

Staphylococcus aureus is a dangerous bacterial pathogen whose clinical impact has been amplified by the emergence and rapid spread of antibiotic resistance. In the search for more effective therapeutic strategies, great effort has been placed on the study and development of staphylolytic enzymes, which benefit from high potency activity toward drug-resistant strains, and a low inherent susceptibility to emergence of new resistance phenotypes. To date, the majority of therapeutic candidates have derived from either bacteriophage or environmental competitors of S. aureus. Little to no consideration has been given to cis-acting autolysins that represent key elements in the bacterium's endogenous cell wall maintenance and recycling machinery. In this study, five putative autolysins were cloned from the S. aureus genome, and their activities were evaluated. Four of these novel enzymes, or component domains thereof, demonstrated lytic activity toward live S. aureus cells, but their potencies were 10s to 1000s of times lower than that of the well-characterized therapeutic candidate lysostaphin. We hypothesized that their poor activities were due in part to suboptimal cell wall targeting associated with their native cell wall binding domains, and we sought to enhance their antibacterial potential via chimeragenesis with the peptidoglycan binding domain of lysostaphin. The most potent chimera exhibited a 140-fold increase in lytic rate, bringing it within 8-fold of lysostaphin. While this enzyme was sensitive to certain biologically relevant environmental factors and failed to exhibit a measurable minimal inhibitory concentration, it was able to kill lysostaphin-resistant S. aureus and ultimately proved active in lung surfactant. We conclude that the S. aureus proteome represents a rich and untapped reservoir of novel antibacterial enzymes, and we demonstrate enhanced bacteriolytic activity via improved cell wall targeting of autolysin catalytic domains.

Computationally driven deletion of broadly distributed T cell epitopes in a biotherapeutic candidate.

Biotherapeutics are subject to immune surveillance within the body, and anti-biotherapeutic immune responses can compromise drug efficacy and patient safety. Initial development of targeted antidrug immune memory is coordinated by T cell recognition of immunogenic subsequences, termed "T cell epitopes." Biotherapeutics may therefore be deimmunized by mutating key residues within cognate epitopes, but there exist complex trade-offs between immunogenicity, mutational load, and protein structure-function. Here, a protein deimmunization algorithm has been applied to P99 beta-lactamase, a component of antibody-directed enzyme prodrug therapies. The algorithm, integer programming for immunogenic proteins, seamlessly integrates computational prediction of T cell epitopes with both 1- and 2-body sequence potentials that assess protein tolerance to epitope-deleting mutations. Compared to previously deimmunized P99 variants, which bore only one or two mutations, the enzymes designed here contain 4-5 widely distributed substitutions. As a result, they exhibit broad reductions in major histocompatibility complex recognition. Despite their high mutational loads and markedly reduced immunoreactivity, all eight engineered variants possessed wild-type or better catalytic activity. Thus, the protein design algorithm is able to disrupt broadly distributed epitopes while maintaining protein function. As a result, this computational tool may prove useful in expanding the repertoire of next-generation biotherapeutics.

Gene and protein sequence optimization for high-level production of fully active and aglycosylated lysostaphin in Pichia pastoris.

Lysostaphin represents a promising therapeutic agent for the treatment of staphylococcal infections, in particular those of methicillin-resistant Staphylococcus aureus (MRSA). However, conventional expression systems for the enzyme suffer from various limitations, and there remains a need for an efficient and cost-effective production process to facilitate clinical translation and the development of nonmedical applications. While Pichia pastoris is widely used for high-level production of recombinant proteins, there are two major barriers to the production of lysostaphin in this industrially relevant host: lack of expression from the wild-type lysostaphin gene and aberrant glycosylation of the wild-type protein sequence. The first barrier can be overcome with a synthetic gene incorporating improved codon usage and balanced A+T/G+C content, and the second barrier can be overcome by disrupting an N-linked glycosylation sequon using a broadened choice of mutations that yield aglyscosylated and fully active lysostaphin. The optimized lysostaphin variants could be produced at approximately 500 mg/liter in a small-scale bioreactor, and 50% of that material could be recovered at high purity with a simple 2-step purification. It is anticipated that this novel high-level expression system will bring down one of the major barriers to future development of biomedical, veterinary, and research applications of lysostaphin and its engineered variants.

A high-throughput screen for antibiotic drug discovery.

We describe an ultra-high-throughput screening platform enabling discovery and/or engineering of natural product antibiotics. The methodology involves creation of hydrogel-in-oil emulsions in which recombinant microorganisms are co-emulsified with bacterial pathogens; antibiotic activity is assayed by use of a fluorescent viability dye. We have successfully utilized both bulk emulsification and microfluidic technology for the generation of hydrogel microdroplets that are size-compatible with conventional flow cytometry. Hydrogel droplets are ∼25 pL in volume, and can be synthesized and sorted at rates exceeding 3,000 drops/s. Using this technique, we have achieved screening throughputs exceeding 5 million clones/day. Proof-of-concept experiments demonstrate efficient selection of antibiotic-secreting yeast from a vast excess of negative controls. In addition, we have successfully used this technique to screen a metagenomic library for secreted antibiotics that kill the human pathogen Staphylococcus aureus. Our results establish the practical utility of the screening platform, and we anticipate that the accessible nature of our methods will enable others seeking to identify and engineer the next generation of antibacterial biomolecules.

Alginate lyase exhibits catalysis-independent biofilm dispersion and antibiotic synergy.

More than 2 decades of study support the hypothesis that alginate lyases are promising therapeutic candidates for treating mucoid Pseudomonas aeruginosa infections. In particular, the enzymes' ability to degrade alginate, a key component of mucoid biofilm matrix, has been the presumed mechanism by which they disrupt biofilms and enhance antibiotic efficacy. The systematic studies reported here show that, in an in vitro model, alginate lyase dispersion of P. aeruginosa biofilms and enzyme synergy with tobramycin are completely decoupled from catalytic activity. In fact, equivalent antibiofilm effects can be achieved with bovine serum albumin or simple amino acids. These results provide new insights into potential mechanisms of alginate lyase therapeutic activity, and they should motivate a careful reexamination of the fundamental assumptions underlying interest in enzymatic biofilm dispersion.

Bioengineered lysozyme reduces bacterial burden and inflammation in a murine model of mucoid Pseudomonas aeruginosa lung infection.

The spread of drug-resistant bacterial pathogens is a growing global concern and has prompted an effort to explore potential adjuvant and alternative therapies derived from nature's repertoire of bactericidal proteins and peptides. In humans, the airway surface liquid layer is a rich source of antibiotics, and lysozyme represents one of the most abundant and effective antimicrobial components of airway secretions. Human lysozyme is active against both Gram-positive and Gram-negative bacteria, acting through several mechanisms, including catalytic degradation of cell wall peptidoglycan and subsequent bacterial lysis. In the infected lung, however, lysozyme's dense cationic character can result in sequestration and inhibition by polyanions associated with airway inflammation. As a result, the efficacy of the native enzyme may be compromised in the infected and inflamed lung. To address this limitation, we previously constructed a charge-engineered variant of human lysozyme that was less prone to electrostatic-mediated inhibition in vitro. Here, we employ a murine model to show that this engineered enzyme is superior to wild-type human lysozyme as a treatment for mucoid Pseudomonas aeruginosa lung infections. The engineered enzyme effectively decreases the bacterial burden and reduces markers of inflammation and lung injury. Importantly, we found no evidence of acute toxicity or allergic hypersensitivity upon repeated administration of the engineered biotherapeutic. Thus, the charge-engineered lysozyme represents an interesting therapeutic candidate for P. aeruginosa lung infections.

Structure-based redesign of proteins for minimal T-cell epitope content.

The protein universe displays a wealth of therapeutically relevant activities, but T-cell driven immune responses to non-"self" biological agents present a major impediment to harnessing the full diversity of these molecular functions. Mutagenic T-cell epitope deletion seeks to mitigate the immune response, but can typically address only a small number of epitopes. Here, we pursue a "bottom-up" approach that redesigns an entire protein to remain native-like but contain few if any immunogenic epitopes. We do so by extending the Rosetta flexible-backbone protein design software with an epitope scoring mechanism and appropriate constraints. The method is benchmarked with a diverse panel of proteins and applied to three targets of therapeutic interest. We show that the deimmunized designs indeed have minimal predicted epitope content and are native-like in terms of various quality measures, and moreover that they display levels of native sequence recovery comparable to those of non-deimmunized designs.

Functional Deimmunization of Botulinum Neurotoxin Protease Domain via Computationally Driven Library Design and Ultrahigh-Throughput Screening.

Botulinum neurotoxin serotype A (BoNT/A) is a widely used cosmetic agent that also has diverse therapeutic applications; however, adverse antidrug immune responses and associated loss of efficacy have been reported in clinical uses. Here, we describe computational design and ultrahigh-throughput screening of a massive BoNT/A light-chain (BoNT/A-LC) library optimized for reduced T cell epitope content and thereby dampened immunogenicity. We developed a functional assay based on bacterial co-expression of BoNT/A-LC library members with a Förster resonance energy transfer (FRET) sensor for BoNT/A-LC enzymatic activity, and we employed high-speed fluorescence-activated cell sorting (FACS) to identify numerous computationally designed variants having wild-type-like enzyme kinetics. Many of these variants exhibited decreased immunogenicity in humanized HLA transgenic mice and manifested in vivo paralytic activity when incorporated into full-length toxin. One variant achieved near-wild-type paralytic potency and a 300% reduction in antidrug antibody response in vivo. Thus, we have achieved a striking level of BoNT/A-LC functional deimmunization by combining computational library design and ultrahigh-throughput screening. This strategy holds promise for deimmunizing other biologics with complex superstructures and mechanisms of action.

Nonclassical antagonism between human lysozyme and AMPs against Pseudomonas aeruginosa.

Combinations of human lysozyme (hLYS) and antimicrobial peptides (AMPs) are known to exhibit either additive or synergistic activity, and as a result, they have therapeutic potential for persistent and antibiotic-resistant infections. We examined hLYS activity against Pseudomonas aeruginosa when combined with six different AMPs. In contrast to prior reports, we discovered that some therapeutically relevant AMPs manifest striking antagonistic interactions with hLYS across particular concentration ranges. We further found that the synthetic AMP Tet009 can inhibit hLYS-mediated bacterial lysis. To the best of our knowledge, these results represent the first observations of antagonism between hLYS and AMPs, and they advise that future development of lytic enzyme and AMP combination therapies considers the potential for antagonistic interactions.