Massively Parallel Biophysical Analysis of CRISPR-Cas Complexes on Next Generation Sequencing Chips.

CRISPR-Cas nucleoproteins target foreign DNA via base pairing with a crRNA. However, a quantitative description of protein binding and nuclease activation at off-target DNA sequences remains elusive. Here, we describe a chip-hybridized association-mapping platform (CHAMP) that repurposes next-generation sequencing chips to simultaneously measure the interactions between proteins and ∼107 unique DNA sequences. Using CHAMP, we provide the first comprehensive survey of DNA recognition by a type I-E CRISPR-Cas (Cascade) complex and Cas3 nuclease. Analysis of mutated target sequences and human genomic DNA reveal that Cascade recognizes an extended protospacer adjacent motif (PAM). Cascade recognizes DNA with a surprising 3-nt periodicity. The identity of the PAM and the PAM-proximal nucleotides control Cas3 recruitment by releasing the Cse1 subunit. These findings are used to develop a model for the biophysical constraints governing off-target DNA binding. CHAMP provides a framework for high-throughput, quantitative analysis of protein-DNA interactions on synthetic and genomic DNA. PAPERCLIP.

Machine learning-aided engineering of hydrolases for PET depolymerization.

Plastic waste poses an ecological challenge1-3 and enzymatic degradation offers one, potentially green and scalable, route for polyesters waste recycling4. Poly(ethylene terephthalate) (PET) accounts for 12% of global solid waste5, and a circular carbon economy for PET is theoretically attainable through rapid enzymatic depolymerization followed by repolymerization or conversion/valorization into other products6-10. Application of PET hydrolases, however, has been hampered by their lack of robustness to pH and temperature ranges, slow reaction rates and inability to directly use untreated postconsumer plastics11. Here, we use a structure-based, machine learning algorithm to engineer a robust and active PET hydrolase. Our mutant and scaffold combination (FAST-PETase: functional, active, stable and tolerant PETase) contains five mutations compared to wild-type PETase (N233K/R224Q/S121E from prediction and D186H/R280A from scaffold) and shows superior PET-hydrolytic activity relative to both wild-type and engineered alternatives12 between 30 and 50 °C and a range of pH levels. We demonstrate that untreated, postconsumer-PET from 51 different thermoformed products can all be almost completely degraded by FAST-PETase in 1 week. FAST-PETase can also depolymerize untreated, amorphous portions of a commercial water bottle and an entire thermally pretreated water bottle at 50 ºC. Finally, we demonstrate a closed-loop PET recycling process by using FAST-PETase and resynthesizing PET from the recovered monomers. Collectively, our results demonstrate a viable route for enzymatic plastic recycling at the industrial scale.

Dynamic reorganization of metabolic enzymes into intracellular bodies.

Both focused and large-scale cell biological and biochemical studies have revealed that hundreds of metabolic enzymes across diverse organisms form large intracellular bodies. These proteinaceous bodies range in form from fibers and intracellular foci--such as those formed by enzymes of nitrogen and carbon utilization and of nucleotide biosynthesis--to high-density packings inside bacterial microcompartments and eukaryotic microbodies. Although many enzymes clearly form functional mega-assemblies, it is not yet clear for many recently discovered cases whether they represent functional entities, storage bodies, or aggregates. In this article, we survey intracellular protein bodies formed by metabolic enzymes, asking when and why such bodies form and what their formation implies for the functionality--and dysfunctionality--of the enzymes that comprise them. The panoply of intracellular protein bodies also raises interesting questions regarding their evolution and maintenance within cells. We speculate on models for how such structures form in the first place and why they may be inevitable.

UTexas Aptamer Database: the collection and long-term preservation of aptamer sequence information.

A growing interest in aptamer research, as evidenced by the increase in aptamer publications over the years, has led to calls for a go-to site for aptamer information. A comprehensive, publicly available aptamer dataset, which may be a repository for aptamer data, standardize aptamer reporting, and generate opportunities to expand current research in the field, could meet such a demand. There have been several attempts to create aptamer databases; however, most have been abandoned or removed entirely from public view. Inspired by previous efforts, we have published the UTexas Aptamer Database, https://sites.utexas.edu/aptamerdatabase, which includes a publicly available aptamer dataset and a searchable database containing a subset of all aptamer data collected to date (1990-2022). The dataset contains aptamer sequences, binding and selection information. The information is regularly reviewed internally to ensure accuracy and consistency across all entries. To support the continued curation and review of aptamer sequence information, we have implemented sustaining mechanisms, including researcher training protocols, an aptamer submission form, data stored separately from the database platform, and a growing team of researchers committed to updating the database. Currently, the UTexas Aptamer Database is the largest in terms of the number of aptamer sequences with 1,443 internally reviewed aptamer records.

Parallel molecular computation on digital data stored in DNA.

DNA is an incredibly dense storage medium for digital data. However, computing on the stored information is expensive and slow, requiring rounds of sequencing, in silico computation, and DNA synthesis. Prior work on accessing and modifying data using DNA hybridization or enzymatic reactions had limited computation capabilities. Inspired by the computational power of "DNA strand displacement," we augment DNA storage with "in-memory" molecular computation using strand displacement reactions to algorithmically modify data in a parallel manner. We show programs for binary counting and Turing universal cellular automaton Rule 110, the latter of which is, in principle, capable of implementing any computer algorithm. Information is stored in the nicks of DNA, and a secondary sequence-level encoding allows high-throughput sequencing-based readout. We conducted multiple rounds of computation on 4-bit data registers, as well as random access of data (selective access and erasure). We demonstrate that large strand displacement cascades with 244 distinct strand exchanges (sequential and in parallel) can use naturally occurring DNA sequence from M13 bacteriophage without stringent sequence design, which has the potential to improve the scale of computation and decrease cost. Our work merges DNA storage and DNA computing, setting the foundation of entirely molecular algorithms for parallel manipulation of digital information preserved in DNA.

Engineering a human P2X2 receptor with altered ligand selectivity in yeast.

P2X receptors are a family of ligand gated ion channels found in a range of eukaryotic species including humans but are not naturally present in the yeast Saccharomyces cerevisiae. We demonstrate the first recombinant expression and functional gating of the P2X2 receptor in baker's yeast. We leverage the yeast host for facile genetic screens of mutant P2X2 by performing site saturation mutagenesis at residues of interest, including SNPs implicated in deafness and at residues involved in native binding. Deep mutational analysis and rounds of genetic engineering yield mutant P2X2 F303Y A304W, which has altered ligand selectivity toward the ATP analog AMP-PNP. The F303Y A304W variant shows over 100-fold increased intracellular calcium amplitudes with AMP-PNP compared to the WT receptor and has a much lower desensitization rate. Since AMP-PNP does not naturally activate P2X receptors, the F303Y A304W P2X2 may be a starting point for downstream applications in chemogenetic cellular control. Interestingly, the A304W mutation selectively destabilizes the desensitized state, which may provide a mechanistic basis for receptor opening with suboptimal agonists. The yeast system represents an inexpensive, scalable platform for ion channel characterization and engineering by circumventing the more expensive and time-consuming methodologies involving mammalian hosts.

Kinetics of elementary steps in loop-mediated isothermal amplification (LAMP) show that strand invasion during initiation is rate-limiting.

Loop-mediated isothermal amplification (LAMP) has proven to be easier to implement than PCR for point-of-care diagnostic tests. However, the underlying mechanism of LAMP is complicated and the kinetics of the major steps in LAMP have not been fully elucidated, which prevents rational improvements in assay development. Here we present our work to characterize the kinetics of the elementary steps in LAMP and show that: (i) strand invasion / initiation is the rate-limiting step in the LAMP reaction; (ii) the loop primer plays an important role in accelerating the rate of initiation and does not function solely during the exponential amplification phase and (iii) strand displacement synthesis by Bst-LF polymerase is relatively fast (125 nt/s) and processive on both linear and hairpin templates, although with some interruptions on high GC content templates. Building on these data, we were able to develop a kinetic model that relates the individual kinetic experiments to the bulk LAMP reaction. The assays developed here provide important insights into the mechanism of LAMP, and the overall model should be crucial in engineering more sensitive and faster LAMP reactions. The kinetic methods we employ should likely prove useful with other isothermal DNA amplification methods.

Asymmetric Synthesis of α-Chloroamides via Photoenzymatic Hydroalkylation of Olefins.

Photoenzymatic intermolecular hydroalkylations of olefins are highly enantioselective for chiral centers formed during radical termination but poorly selective for centers set in the C-C bond-forming event. Here, we report the evolution of a flavin-dependent "ene"-reductase to catalyze the coupling of α,α-dichloroamides with alkenes to afford α-chloroamides in good yield with excellent chemo- and stereoselectivity. These products can serve as linchpins in the synthesis of pharmaceutically valuable motifs. Mechanistic studies indicate that radical formation occurs by exciting a charge-transfer complex templated by the protein. Precise control over the orientation of molecules within the charge-transfer complex potentially accounts for the observed stereoselectivity. The work expands the types of motifs that can be prepared using photoenzymatic catalysis.

Using fungible biosensors to evolve improved alkaloid biosyntheses.

A key bottleneck in the microbial production of therapeutic plant metabolites is identifying enzymes that can improve yield. The facile identification of genetically encoded biosensors can overcome this limitation and become part of a general method for engineering scaled production. We have developed a combined screening and selection approach that quickly refines the affinities and specificities of generalist transcription factors; using RamR as a starting point, we evolve highly specific (>100-fold preference) and sensitive (half-maximum effective concentration (EC50) < 30 µM) biosensors for the alkaloids tetrahydropapaverine, papaverine, glaucine, rotundine and noscapine. High-resolution structures reveal multiple evolutionary avenues for the malleable effector-binding site and the creation of new pockets for different chemical moieties. These sensors further enabled the evolution of a streamlined pathway for tetrahydropapaverine, a precursor to four modern pharmaceuticals, collapsing multiple methylation steps into a single evolved enzyme. Our methods for evolving biosensors enable the rapid engineering of pathways for therapeutic alkaloids.

A synthetic genetic edge detection program.

Edge detection is a signal processing algorithm common in artificial intelligence and image recognition programs. We have constructed a genetically encoded edge detection algorithm that programs an isogenic community of E. coli to sense an image of light, communicate to identify the light-dark edges, and visually present the result of the computation. The algorithm is implemented using multiple genetic circuits. An engineered light sensor enables cells to distinguish between light and dark regions. In the dark, cells produce a diffusible chemical signal that diffuses into light regions. Genetic logic gates are used so that only cells that sense light and the diffusible signal produce a positive output. A mathematical model constructed from first principles and parameterized with experimental measurements of the component circuits predicts the performance of the complete program. Quantitatively accurate models will facilitate the engineering of more complex biological behaviors and inform bottom-up studies of natural genetic regulatory networks.

A Humanized CB1R Yeast Biosensor Enables Facile Screening of Cannabinoid Compounds.

Yeast expression of human G-protein-coupled receptors (GPCRs) can be used as a biosensor platform for the detection of pharmaceuticals. Cannabinoid receptor type 1 (CB1R) is of particular interest, given the cornucopia of natural and synthetic cannabinoids being explored as therapeutics. We show for the first time that engineering the N-terminus of CB1R allows for efficient signal transduction in yeast, and that engineering the sterol composition of the yeast membrane modulates its performance. Using an engineered cannabinoid biosensor, we demonstrate that large libraries of synthetic cannabinoids and terpenes can be quickly screened to elucidate known and novel structure-activity relationships. The biosensor strains offer a ready platform for evaluating the activity of new synthetic cannabinoids, monitoring drugs of abuse, and developing therapeutic molecules.

Improved Bst DNA Polymerase Variants Derived via a Machine Learning Approach.

The DNA polymerase I from Geobacillus stearothermophilus (also known as Bst DNAP) is widely used in isothermal amplification reactions, where its strand displacement ability is prized. More robust versions of this enzyme should be enabled for diagnostic applications, especially for carrying out higher temperature reactions that might proceed more quickly. To this end, we appended a short fusion domain from the actin-binding protein villin that improved both stability and purification of the enzyme. In parallel, we have developed a machine learning algorithm that assesses the relative fit of individual amino acids to their chemical microenvironments at any position in a protein and applied this algorithm to predict sequence substitutions in Bst DNAP. The top predicted variants had greatly improved thermotolerance (heating prior to assay), and upon combination, the mutations showed additive thermostability, with denaturation temperatures up to 2.5 °C higher than the parental enzyme. The increased thermostability of the enzyme allowed faster loop-mediated isothermal amplification assays to be carried out at 73 °C, where both Bst DNAP and its improved commercial counterpart Bst 2.0 are inactivated. Overall, this is one of the first examples of the application of machine learning approaches to the thermostabilization of an enzyme.

Peptide Macrocyclization Guided by Reversible Covalent Templating.

The creation of complementary products via templating is a hallmark feature of nucleic acid replication. Outside of nucleic acid-like molecules, the templated synthesis of a hetero-complementary copy is still rare. Herein we describe one cycle of templated synthesis that creates homomeric macrocyclic peptides guided by linear instructing strands. This strategy utilizes hydrazone formation to pre-organize peptide oligomeric monomers along the template on a solid support resin, and microwave-assisted peptide synthesis to couple monomers and cyclize the strands. With a flexible templating strand, we can alter the size of the complementary macrocycle products by increasing the length and number of the binding peptide oligomers, showing the potential to precisely tune the size of macrocyclic products. For the smaller macrocyclic peptides, the products can be released via hydrolysis and characterized by ESI-MS.

How a B family DNA polymerase has been evolved to copy RNA.

We report here crystal structures of a reverse transcriptase RTX, which was evolved in vitro from the B family polymerase KOD, in complex with either a DNA duplex or an RNA-DNA hybrid. Compared with the apo, binary, and ternary complex structures of the original KOD polymerase, the 16 substitutions that result in the function of copying RNA to DNA do not change the overall protein structure. Only six substitutions occur at the substrate-binding surface, and the others change domain-domain interfaces in the polymerase to enable RNA-DNA hybrid binding and reverse transcription. Most notably, F587L at the Palm and Thumb interface stabilizes the open and apo conformation of the Thumb. The intrinsically flexible Thumb domain seems to play a major role in accommodating the RNA-DNA hybrid product distal to the active site. This is reminiscent of naturally occurring RNA-dependent DNA polymerases, including telomerase, which have a dramatically augmented Thumb domain, and of reverse transcriptase, which extends its Thumb with the RNase H domain.

Integrated Top-Down and Bottom-Up Mass Spectrometry for Characterization of Diselenide Bridging Patterns of Synthetic Selenoproteins.

With the rapid acceleration in the design and development of new biotherapeutics, ensuring consistent quality and understanding degradation pathways remain paramount, requiring an array of analytical methods including mass spectrometry. The incorporation of non-canonical amino acids, such as for synthetic selenoproteins, creates additional challenges. A comprehensive strategy to characterize selenoproteins should serve dual purposes of providing sequence confirmation and mapping of selenocysteine bridge locations and the identification of unanticipated side products. In the present study, a combined approach exploiting the benefits of both top-down and bottom-up mass spectrometry was developed. Both electron-transfer/higher-energy collision dissociation and 213 nm ultraviolet photodissociation were utilized to provide complementary information, allowing high quality characterization, localization of diselenide bridges for complex proteins, and the identification of previously unreported selenoprotein dimers.

Systematic Review of Aptamer Sequence Reporting in the Literature Reveals Widespread Unexplained Sequence Alterations.

Aptamers have been the subject of more than 144 000 papers to date. However, there has been a growing concern that discrepancies in the reporting of aptamer research limit the reliability of these reagents for research and other applications. These observations noting inconsistencies in the use of our RNA antilysozyme aptamer served as an impetus for our systematic review of the reporting of aptamer sequences in the literature. Our detailed examination of the literature citing the RNA antilysozyme aptamer revealed that 93% of the 61 publications reviewed reported unexplained altered sequences with 96% of those using DNA variants. The 10 most cited aptamers were examined using a standardized methodology in order to categorize the extent to which the sequences themselves and altered sequences were adequately described in the literature. Our review of 780 aptamer publications spanned decades, multiple journals, and research groups and revealed that 41% of the papers reported unexplained sequence alterations or omitted sequences. We identified 10 common categories of sequence alterations including deletions, substitutions, and additions, among others. Overall, our findings can be used as a starting point for building better practices in author submissions and publication standards, elevating the rigor and reproducibility of aptamer research.

Site-specific 5-hydroxytryptophan incorporation into apolipoprotein A-I impairs cholesterol efflux activity and high-density lipoprotein biogenesis.

Apolipoprotein A-I (apoA-I) is the major protein constituent of high-density lipoprotein (HDL) and a target of myeloperoxidase-dependent oxidation in the artery wall. In atherosclerotic lesions, apoA-I exhibits marked oxidative modifications at multiple sites, including Trp72 Site-specific mutagenesis studies have suggested, but have not conclusively shown, that oxidative modification of Trp72 of apoA-I impairs many atheroprotective properties of this lipoprotein. Herein, we used genetic code expansion technology with an engineered Saccharomyces cerevisiae tryptophanyl tRNA-synthetase (Trp-RS):suppressor tRNA pair to insert the noncanonical amino acid 5-hydroxytryptophan (5-OHTrp) at position 72 in recombinant human apoA-I and confirmed site-specific incorporation utilizing MS. In functional characterization studies, 5-OHTrp72 apoA-I (compared with WT apoA-I) exhibited reduced ABC subfamily A member 1 (ABCA1)-dependent cholesterol acceptor activity in vitro (41.73 ± 6.57% inhibition; p < 0.01). Additionally, 5-OHTrp72 apoA-I displayed increased activation and stabilization of paraoxonase 1 (PON1) activity (µmol/min/mg) when compared with WT apoA-I and comparable PON1 activation/stabilization compared with reconstituted HDL (WT apoA-I, 1.92 ± 0.04; 5-OHTrp72 apoA-I, 2.35 ± 0.0; and HDL, 2.33 ± 0.1; p < 0.001, p < 0.001, and p < 0.001, respectively). Following injection into apoA-I-deficient mice, 5-OHTrp72 apoA-I reached plasma levels comparable with those of native apoA-I yet exhibited significantly reduced (48%; p < 0.01) lipidation and evidence of HDL biogenesis. Collectively, these findings unequivocally reveal that site-specific oxidative modification of apoA-I via 5-OHTrp at Trp72 impairs cholesterol efflux and the rate-limiting step of HDL biogenesis both in vitro and in vivo.

Pattern Generation with Nucleic Acid Chemical Reaction Networks.

Biological and biochemical systems are manifestations of chemical reaction networks (CRNs). The ability to design and engineer such networks may allow the construction of artificial systems that are as complex as those seen in biology, opening the way to translational possibilities including adaptive materials. One venue for progress is the design of autonomous systems capable of pattern generation; however many synthetic CRNs, such as the Belousov-Zhabotinsky reaction, cannot be rewired to encode more complex interactions and thus lack the capacity for more detailed engineering algorithms. In contrast, DNA is an information-rich molecule with predictable and reliable base-pairing interactions and well-studied kinetics, and the use of DNA has greatly enabled the rational design of much more complex synthetic CRNs. Recent advances in the DNA computing field include circuits for pattern transformation, an example of self-organization. An arsenal of tools for designing DNA circuits to implement various CRNs has been developed by DNA nanotechnologists, including software to reliably program strand-displacement nucleic acid circuits. In addition, DNA walkers can be used to create CRNs with controlled diffusivity, while DNA gels similarly represent a new medium for implementing CRNs that may ultimately lead to the development of smart materials. As we will argue, future endeavors in nucleic acid-based pattern generation will be most greatly advanced by harnessing well-known enzymatic processes to serve as generators and amplifiers. Once nucleic acid computing tools are further developed to expedite the design process of pattern generation, we anticipate a transition from proof-of-concept curiosities to application-driven inquiries.

Selection of self-priming molecular replicators.

Self-priming amplification of oligonucleotides is possible based on foldback of 3' ends, self-priming, and concatemerization, especially in the presence of phosphorothioate linkages. Such a simple replicative mechanism may have led to the accumulation of specific replicators at or near the origin of life. To determine how early replicators may have competed with one another, we have carried out selections with phosphorothiolated hairpins appended to a short random sequence library (N10). Upon the addition of deoxynucleoside triphosphates and a polymerase, concatemers quickly formed, and those random sequences that templated the insertion of purines, especially during initiation, quickly predominated. Over several serial transfers, particular sequences accumulated, and in isolation these were shown to outcompete less efficient replicators.

Retrons and their applications in genome engineering.

Precision genome editing technologies have transformed modern biology. These technologies have arisen from the redirection of natural biological machinery, such as bacteriophage lambda proteins for recombineering and CRISPR nucleases for eliciting site-specific double-strand breaks. Less well-known is a widely distributed class of bacterial retroelements, retrons, that employ specialized reverse transcriptases to produce noncoding intracellular DNAs. Retrons' natural function and mechanism of genetic transmission have remained enigmatic. However, recent studies have harnessed their ability to produce DNA in situ for genome editing and evolution. This review describes retron biology and function in both natural and synthetic contexts. We also highlight areas that require further study to advance retron-based precision genome editing platforms.