Genome manipulation by guide-directed Argonaute cleavage.

Many prokaryotic argonautes (pAgos) mediate DNA interference by using small DNA guides to cleave target DNA. A recent study shows that CbAgo, a pAgo from Clostridium butyricum, induces DNA interference between homologous sequences and generates double-stranded breaks (DSBs) in target DNAs. This mechanism enables the host to defend against invading DNAs such as plasmids and viruses. However, whether such a CbAgo-mediated DNA cleavage is mutagenic remains unexplored. Here we demonstrate that CbAgo, directed by plasmid-encoded guide sequences, can cleave genome target sites and induce chromosome recombination between downstream homologous sequences in Escherichia coli. The recombination rate correlates well with pAgo DNA cleavage activity and the mechanistic study suggests the recombination involves DSBs and RecBCD processing. In RecA-deficient E. coli strain, guide-directed CbAgo cleavage on chromosomes severely impairs cell growth, which can be utilized as counter-selection to assist Lambda-Red recombineering. These findings demonstrate the guide-directed cleavage of pAgo on the host genome is mutagenic and can lead to different outcomes according to the function of the host DNA repair machinery. We anticipate this novel DNA-guided interference to be useful in broader genetic manipulation. Our study also provides an in vivo assay to characterize or engineer pAgo DNA cleavage activity.

Protein stability engineering insights revealed by domain-wide comprehensive mutagenesis.

The accurate prediction of protein stability upon sequence mutation is an important but unsolved challenge in protein engineering. Large mutational datasets are required to train computational predictors, but traditional methods for collecting stability data are either low-throughput or measure protein stability indirectly. Here, we develop an automated method to generate thermodynamic stability data for nearly every single mutant in a small 56-residue protein. Analysis reveals that most single mutants have a neutral effect on stability, mutational sensitivity is largely governed by residue burial, and unexpectedly, hydrophobics are the best tolerated amino acid type. Correlating the output of various stability-prediction algorithms against our data shows that nearly all perform better on boundary and surface positions than for those in the core and are better at predicting large-to-small mutations than small-to-large ones. We show that the most stable variants in the single-mutant landscape are better identified using combinations of 2 prediction algorithms and including more algorithms can provide diminishing returns. In most cases, poor in silico predictions were tied to compositional differences between the data being analyzed and the datasets used to train the algorithm. Finally, we find that strategies to extract stabilities from high-throughput fitness data such as deep mutational scanning are promising and that data produced by these methods may be applicable toward training future stability-prediction tools.

Computational design of co-assembling protein-DNA nanowires.

Biomolecular self-assemblies are of great interest to nanotechnologists because of their functional versatility and their biocompatibility. Over the past decade, sophisticated single-component nanostructures composed exclusively of nucleic acids, peptides and proteins have been reported, and these nanostructures have been used in a wide range of applications, from drug delivery to molecular computing. Despite these successes, the development of hybrid co-assemblies of nucleic acids and proteins has remained elusive. Here we use computational protein design to create a protein-DNA co-assembling nanomaterial whose assembly is driven via non-covalent interactions. To achieve this, a homodimerization interface is engineered onto the Drosophila Engrailed homeodomain (ENH), allowing the dimerized protein complex to bind to two double-stranded DNA (dsDNA) molecules. By varying the arrangement of protein-binding sites on the dsDNA, an irregular bulk nanoparticle or a nanowire with single-molecule width can be spontaneously formed by mixing the protein and dsDNA building blocks. We characterize the protein-DNA nanowire using fluorescence microscopy, atomic force microscopy and X-ray crystallography, confirming that the nanowire is formed via the proposed mechanism. This work lays the foundation for the development of new classes of protein-DNA hybrid materials. Further applications can be explored by incorporating DNA origami, DNA aptamers and/or peptide epitopes into the protein-DNA framework presented here.

Monomerization of far-red fluorescent proteins.

Anthozoa-class red fluorescent proteins (RFPs) are frequently used as biological markers, with far-red (λem ∼ 600-700 nm) emitting variants sought for whole-animal imaging because biological tissues are more permeable to light in this range. A barrier to the use of naturally occurring RFP variants as molecular markers is that all are tetrameric, which is not ideal for cell biological applications. Efforts to engineer monomeric RFPs have typically produced dimmer and blue-shifted variants because the chromophore is sensitive to small structural perturbations. In fact, despite much effort, only four native RFPs have been successfully monomerized, leaving the majority of RFP biodiversity untapped in biomarker development. Here we report the generation of monomeric variants of HcRed and mCardinal, both far-red dimers, and describe a comprehensive methodology for the monomerization of red-shifted oligomeric RFPs. Among the resultant variants is mKelly1 (emission maximum, λem = 656 nm), which, along with the recently reported mGarnet2 [Matela G, et al. (2017) Chem Commun (Camb) 53:979-982], forms a class of bright, monomeric, far-red FPs.

Precision is essential for efficient catalysis in an evolved Kemp eliminase.

Linus Pauling established the conceptual framework for understanding and mimicking enzymes more than six decades ago. The notion that enzymes selectively stabilize the rate-limiting transition state of the catalysed reaction relative to the bound ground state reduces the problem of design to one of molecular recognition. Nevertheless, past attempts to capitalize on this idea, for example by using transition state analogues to elicit antibodies with catalytic activities, have generally failed to deliver true enzymatic rates. The advent of computational design approaches, combined with directed evolution, has provided an opportunity to revisit this problem. Starting from a computationally designed catalyst for the Kemp elimination--a well-studied model system for proton transfer from carbon--we show that an artificial enzyme can be evolved that accelerates an elementary chemical reaction 6 × 10(8)-fold, approaching the exceptional efficiency of highly optimized natural enzymes such as triosephosphate isomerase. A 1.09 Å resolution crystal structure of the evolved enzyme indicates that familiar catalytic strategies such as shape complementarity and precisely placed catalytic groups can be successfully harnessed to afford such high rate accelerations, making us optimistic about the prospects of designing more sophisticated catalysts.

Computational design and experimental verification of a symmetric protein homodimer.

Homodimers are the most common type of protein assembly in nature and have distinct features compared with heterodimers and higher order oligomers. Understanding homodimer interactions at the atomic level is critical both for elucidating their biological mechanisms of action and for accurate modeling of complexes of unknown structure. Computation-based design of novel protein-protein interfaces can serve as a bottom-up method to further our understanding of protein interactions. Previous studies have demonstrated that the de novo design of homodimers can be achieved to atomic-level accuracy by ß-strand assembly or through metal-mediated interactions. Here, we report the design and experimental characterization of a α-helix-mediated homodimer with C2 symmetry based on a monomeric Drosophila engrailed homeodomain scaffold. A solution NMR structure shows that the homodimer exhibits parallel helical packing similar to the design model. Because the mutations leading to dimer formation resulted in poor thermostability of the system, design success was facilitated by the introduction of independent thermostabilizing mutations into the scaffold. This two-step design approach, function and stabilization, is likely to be generally applicable, especially if the desired scaffold is of low thermostability.

Accuracy of the ABC/2 Score for Intracerebral Hemorrhage: Systematic Review and Analysis of MISTIE, CLEAR-IVH, and CLEAR III.

BACKGROUND AND PURPOSE: The ABC/2 score estimates intracerebral hemorrhage (ICH) volume, yet validations have been limited by small samples and inappropriate outcome measures. We determined accuracy of the ABC/2 score calculated at a specialized reading center (RC-ABC) or local site (site-ABC) versus the reference-standard computed tomography-based planimetry (CTP). METHODS: In Minimally Invasive Surgery Plus Recombinant Tissue-Type Plasminogen Activator for Intracerebral Hemorrhage Evacuation-II (MISTIE-II), Clot Lysis Evaluation of Accelerated Resolution of Intraventricular Hemorrhage (CLEAR-IVH) and CLEAR-III trials. ICH volume was prospectively calculated by CTP, RC-ABC, and site-ABC. Agreement between CTP and ABC/2 was defined as an absolute difference up to 5 mL and relative difference within 20%. Determinants of ABC/2 accuracy were assessed by logistic regression. RESULTS: In 4369 scans from 507 patients, CTP was more strongly correlated with RC-ABC (r(2)=0.93) than with site-ABC (r(2)=0.87). Although RC-ABC overestimated CTP-based volume on average (RC-ABC, 15.2 cm(3); CTP, 12.7 cm3), agreement was reasonable when categorized into mild, moderate, and severe ICH (κ=0.75; P<0.001). This was consistent with overestimation of ICH volume in 6 of 8 previous studies. Agreement with CTP was greater for RC-ABC (84% within 5 mL; 48% of scans within 20%) than for site-ABC (81% within 5 mL; 41% within 20%). RC-ABC had moderate accuracy for detecting ≥5 mL change in CTP volume between consecutive scans (sensitivity, 0.76; specificity, 0.86) and was more accurate with smaller ICH, thalamic hemorrhage, and homogeneous clots. CONCLUSIONS: ABC/2 scores at local or central sites are sufficiently accurate to categorize ICH volume and assess eligibility for the CLEAR-III and MISTIE III studies and moderately accurate for change in ICH volume. However, accuracy decreases with large, irregular, or lobar clots. CLINICAL TRIAL REGISTRATION: URL: http://www.clinicaltrials.gov. Unique identifier: MISTIE-II NCT00224770; CLEAR-III NCT00784134.

Iterative approach to computational enzyme design.

A general approach for the computational design of enzymes to catalyze arbitrary reactions is a goal at the forefront of the field of protein design. Recently, computationally designed enzymes have been produced for three chemical reactions through the synthesis and screening of a large number of variants. Here, we present an iterative approach that has led to the development of the most catalytically efficient computationally designed enzyme for the Kemp elimination to date. Previously established computational techniques were used to generate an initial design, HG-1, which was catalytically inactive. Analysis of HG-1 with molecular dynamics simulations (MD) and X-ray crystallography indicated that the inactivity might be due to bound waters and high flexibility of residues within the active site. This analysis guided changes to our design procedure, moved the design deeper into the interior of the protein, and resulted in an active Kemp eliminase, HG-2. The cocrystal structure of this enzyme with a transition state analog (TSA) revealed that the TSA was bound in the active site, interacted with the intended catalytic base in a catalytically relevant manner, but was flipped relative to the design model. MD analysis of HG-2 led to an additional point mutation, HG-3, that produced a further threefold improvement in activity. This iterative approach to computational enzyme design, including detailed MD and structural analysis of both active and inactive designs, promises a more complete understanding of the underlying principles of enzymatic catalysis and furthers progress toward reliably producing active enzymes.

Designed oligomers of cyanovirin-N show enhanced HIV neutralization.

Cyanovirin-N (CV-N) is a small, cyanobacterial lectin that neutralizes many enveloped viruses, including human immunodeficiency virus type I (HIV-1). This antiviral activity is attributed to two homologous carbohydrate binding sites that specifically bind high mannose glycosylation present on envelope glycoproteins such as HIV-1 gp120. We created obligate CV-N oligomers to determine whether increasing the number of binding sites has an effect on viral neutralization. A tandem repeat of two CV-N molecules (CVN(2)) increased HIV-1 neutralization activity by up to 18-fold compared to wild-type CV-N. In addition, the CVN(2) variants showed extensive cross-clade reactivity and were often more potent than broadly neutralizing anti-HIV antibodies. The improvement in activity and broad cross-strain HIV neutralization exhibited by these molecules holds promise for the future therapeutic utility of these and other engineered CV-N variants.

Direct visualization reveals dynamics of a transient intermediate during protein assembly.

Interactions between proteins underlie numerous biological functions. Theoretical work suggests that protein interactions initiate with formation of transient intermediates that subsequently relax to specific, stable complexes. However, the nature and roles of these transient intermediates have remained elusive. Here, we characterized the global structure, dynamics, and stability of a transient, on-pathway intermediate during complex assembly between the Signal Recognition Particle (SRP) and its receptor. We show that this intermediate has overlapping but distinct interaction interfaces from that of the final complex, and it is stabilized by long-range electrostatic interactions. A wide distribution of conformations is explored by the intermediate; this distribution becomes more restricted in the final complex and is further regulated by the cargo of SRP. These results suggest a funnel-shaped energy landscape for protein interactions, and they provide a framework for understanding the role of transient intermediates in protein assembly and biological regulation.

Interactive computational and experimental approaches improve the sensitivity of periplasmic binding protein-based nicotine biosensors for measurements in biofluids.

We developed fluorescent protein sensors for nicotine with improved sensitivity. For iNicSnFR12 at pH 7.4, the proportionality constant for ΔF/F0 vs [nicotine] (δ-slope, 2.7 µM-1) is 6.1-fold higher than the previously reported iNicSnFR3a. The activated state of iNicSnFR12 has a fluorescence quantum yield of at least 0.6. We measured similar dose-response relations for the nicotine-induced absorbance increase and fluorescence increase, suggesting that the absorbance increase leads to the fluorescence increase via the previously described nicotine-induced conformational change, the "candle snuffer" mechanism. Molecular dynamics (MD) simulations identified a binding pose for nicotine, previously indeterminate from experimental data. MD simulations also showed that Helix 4 of the periplasmic binding protein (PBP) domain appears tilted in iNicSnFR12 relative to iNicSnFR3a, likely altering allosteric network(s) that link the ligand binding site to the fluorophore. In thermal melt experiments, nicotine stabilized the PBP of the tested iNicSnFR variants. iNicSnFR12 resolved nicotine in diluted mouse and human serum at 100 nM, the peak [nicotine] that occurs during smoking or vaping, and possibly at the decreasing levels during intervals between sessions. NicSnFR12 was also partially activated by unidentified endogenous ligand(s) in biofluids. Improved iNicSnFR12 variants could become the molecular sensors in continuous nicotine monitors for animal and human biofluids.

Interactive computational and experimental approaches improve the sensitivity of periplasmic binding protein-based nicotine biosensors for measurements in biofluids.

We developed fluorescent protein sensors for nicotine with improved sensitivity. For iNicSnFR12 at pH 7.4, the proportionality constant for ∆F/F0vs [nicotine] (δ-slope, 2.7 µM-1) is 6.1-fold higher than the previously reported iNicSnFR3a. The activated state of iNicSnFR12 has a fluorescence quantum yield of at least 0.6. We measured similar dose-response relations for the nicotine-induced absorbance increase and fluorescence increase, suggesting that the absorbance increase leads to the fluorescence increase via the previously described nicotine-induced conformational change, the 'candle snuffer' mechanism. Molecular dynamics (MD) simulations identified a binding pose for nicotine, previously indeterminate from experimental data. MD simulations also showed that Helix 4 of the periplasmic binding protein (PBP) domain appears tilted in iNicSnFR12 relative to iNicSnFR3a, likely altering allosteric network(s) that link the ligand binding site to the fluorophore. In thermal melt experiments, nicotine stabilized the PBP of the tested iNicSnFR variants. iNicSnFR12 resolved nicotine in diluted mouse and human serum at 100 nM, the peak [nicotine] that occurs during smoking or vaping, and possibly at the decreasing levels during intervals between sessions. NicSnFR12 was also partially activated by unidentified endogenous ligand(s) in biofluids. Improved iNicSnFR12 variants could become the molecular sensors in continuous nicotine monitors for animal and human biofluids.

GRID: a high-resolution protein structure refinement algorithm.

The energy-based refinement of protein structures generated by fold prediction algorithms to atomic-level accuracy remains a major challenge in structural biology. Energy-based refinement is mainly dependent on two components: (1) sufficiently accurate force fields, and (2) efficient conformational space search algorithms. Focusing on the latter, we developed a high-resolution refinement algorithm called GRID. It takes a three-dimensional protein structure as input and, using an all-atom force field, attempts to improve the energy of the structure by systematically perturbing backbone dihedrals and side-chain rotamer conformations. We compare GRID to Backrub, a stochastic algorithm that has been shown to predict a significant fraction of the conformational changes that occur with point mutations. We applied GRID and Backrub to 10 high-resolution (≤ 2.8 Å) crystal structures from the Protein Data Bank and measured the energy improvements obtained and the computation times required to achieve them. GRID resulted in energy improvements that were significantly better than those attained by Backrub while expending about the same amount of computational resources. GRID resulted in relaxed structures that had slightly higher backbone RMSDs compared to Backrub relative to the starting crystal structures. The average RMSD was 0.25 ± 0.02 Å for GRID versus 0.14 ± 0.04 Å for Backrub. These relatively minor deviations indicate that both algorithms generate structures that retain their original topologies, as expected given the nature of the algorithms.

Experimental library screening demonstrates the successful application of computational protein design to large structural ensembles.

The stability, activity, and solubility of a protein sequence are determined by a delicate balance of molecular interactions in a variety of conformational states. Even so, most computational protein design methods model sequences in the context of a single native conformation. Simulations that model the native state as an ensemble have been mostly neglected due to the lack of sufficiently powerful optimization algorithms for multistate design. Here, we have applied our multistate design algorithm to study the potential utility of various forms of input structural data for design. To facilitate a more thorough analysis, we developed new methods for the design and high-throughput stability determination of combinatorial mutation libraries based on protein design calculations. The application of these methods to the core design of a small model system produced many variants with improved thermodynamic stability and showed that multistate design methods can be readily applied to large structural ensembles. We found that exhaustive screening of our designed libraries helped to clarify several sources of simulation error that would have otherwise been difficult to ascertain. Interestingly, the lack of correlation between our simulated and experimentally measured stability values shows clearly that a design procedure need not reproduce experimental data exactly to achieve success. This surprising result suggests potentially fruitful directions for the improvement of computational protein design technology.

Generation of longer emission wavelength red fluorescent proteins using computationally designed libraries.

The longer emission wavelengths of red fluorescent proteins (RFPs) make them attractive for whole-animal imaging because cells are more transparent to red light. Although several useful RFPs have been developed using directed evolution, the quest for further red-shifted and improved RFPs continues. Herein, we report a structure-based rational design approach to red-shift the fluorescence emission of RFPs. We applied a combined computational and experimental approach that uses computational protein design as an in silico prescreen to generate focused combinatorial libraries of mCherry mutants. The computational procedure helped us identify residues that could fulfill interactions hypothesized to cause red-shifts without destabilizing the protein fold. These interactions include stabilization of the excited state through H-bonding to the acylimine oxygen atom, destabilization of the ground state by hydrophobic packing around the charged phenolate, and stabilization of the excited state by a π-stacking interaction. Our methodology allowed us to identify three mCherry mutants (mRojoA, mRojoB, and mRouge) that display emission wavelengths > 630 nm, representing red-shifts of 20-26 nm. Moreover, our approach required the experimental screening of a total of ∼5,000 clones, a number several orders of magnitude smaller than those previously used to achieve comparable red-shifts. Additionally, crystal structures of mRojoA and mRouge allowed us to verify fulfillment of the interactions hypothesized to cause red-shifts, supporting their contribution to the observed red-shifts.

Evaluating and optimizing computational protein design force fields using fixed composition-based negative design.

An accurate force field is essential to computational protein design and protein fold prediction studies. Proper force field tuning is problematic, however, due in part to the incomplete modeling of the unfolded state. Here, we evaluate and optimize a protein design force field by constraining the amino acid composition of the designed sequences to that of a well behaved model protein. According to the random energy model, unfolded state energies are dependent only on amino acid composition and not the specific arrangement of amino acids. Therefore, energy discrepancies between computational predictions and experimental results, for sequences of identical composition, can be directly attributed to flaws in the force field's ability to properly account for folded state sequence energies. This aspect of fixed composition design allows for force field optimization by focusing solely on the interactions in the folded state. Several rounds of fixed composition optimization of the 56-residue beta1 domain of protein G yielded force field parameters with significantly greater predictive power: Optimized sequences exhibited higher wild-type sequence identity in critical regions of the structure, and the wild-type sequence showed an improved Z-score. Experimental studies revealed a designed 24-fold mutant to be stably folded with a melting temperature similar to that of the wild-type protein. Sequence designs using engrailed homeodomain as a scaffold produced similar results, suggesting the tuned force field parameters were not specific to protein G.

Microbiome for Mars: surveying microbiome connections to healthcare with implications for long-duration human spaceflight, virtual workshop, July 13, 2020.

The inaugural "Microbiome for Mars" virtual workshop took place on July 13, 2020. This event assembled leaders in microbiome research and development to discuss their work and how it may relate to long-duration human space travel. The conference focused on surveying current microbiome research, future endeavors, and how this growing field could broadly impact human health and space exploration. This report summarizes each speaker's presentation in the order presented at the workshop.

An efficient algorithm for multistate protein design based on FASTER.

Most of the methods that have been developed for computational protein design involve the selection of side-chain conformations in the context of a single, fixed main-chain structure. In contrast, multistate design (MSD) methods allow sequence selection to be driven by the energetic contributions of multiple structural or chemical states simultaneously. This methodology is expected to be useful when the design target is an ensemble of related states rather than a single structure, or when a protein sequence must assume several distinct conformations to function. MSD can also be used with explicit negative design to suggest sequences with altered structural, binding, or catalytic specificity. We report implementation details of an efficient multistate design optimization algorithm based on FASTER (MSD-FASTER). We subjected the algorithm to a battery of computational tests and found it to be generally applicable to various multistate design problems; designs with a large number of states and many designed positions are completely feasible. A direct comparison of MSD-FASTER and multistate design Monte Carlo indicated that MSD-FASTER discovers low-energy sequences much more consistently. MSD-FASTER likely performs better because amino acid substitutions are chosen on an energetic basis rather than randomly, and because multiple substitutions are applied together. Through its greater efficiency, MSD-FASTER should allow protein designers to test experimentally better-scoring sequences, and thus accelerate progress in the development of improved scoring functions and models for computational protein design.

Blue fluorescent proteins with enhanced brightness and photostability from a structurally targeted library.

The utility of blue fluorescent protein (BFP) has been limited by its low quantum yield and rapid photobleaching. A library targeting residues neighboring the chromophore yielded a variant with enhanced quantum yield (0.55 versus 0.34), reduced pH sensitivity and a 40-fold increase in photobleaching half-life. This BFP, named Azurite, is well expressed in bacterial and mammalian cells and extends the palette of fluorescent proteins that can be used for imaging.

Attempts to develop an enzyme converting DHIV to KIV.

Dihydroxy-acid dehydratase (DHAD) catalyzes the dehydration of R-2,3-dihydroxyisovalerate (DHIV) to 2-ketoisovalerate (KIV) using an Fe-S cluster as a cofactor, which is sensitive to oxidation and expensive to synthesize. In contrast, sugar acid dehydratases catalyze the same chemical reactions using a magnesium ion. Here, we attempted to substitute the high-cost DHAD with a cost-efficient engineered sugar acid dehydratase using computational protein design (CPD). First, we tried without success to modify the binding pocket of a sugar acid dehydratase to accommodate the smaller, more hydrophobic DHIV. Then, we used a chemically activated substrate analog to react with sugar acid dehydratases or other enolase superfamily enzymes. Mandelate racemase from Pseudomonas putida (PpManR) and the putative sugar acid dehydratase from Salmonella typhimurium (StPutD) showed beta-elimination activity towards chlorolactate (CLD). CPD combined with medium-throughput selection improved the PpManR kcat/KM for CLD by four-fold. However, these enzyme variants did not show dehydration activity towards DHIV. Lastly, assuming phosphorylation could also be a good activation mechanism, we found that mevalonate-3-kinase (M3K) from Picrophilus torridus (PtM3K) exhibited adenosine triphosphate (ATP) hydrolysis activity when mixed with DHIV, indicating phosphorylation activity towards DHIV. Engineering PpManR or StPutD to accept 3-phospho-DHIV as a substrate was performed, but no variants with the desired activity were obtained.