DNAWorks: an automated method for designing oligonucleotides for PCR-based gene synthesis

Enhanced secretion through type 1 secretion system by grafting a calcium-binding sequence to modify the folding of cargo proteins

Extracellular secretion is a beneficial way to produce recombinant proteins at an industrial scale. Among bacterial secretion systems, the type 1 secretion system (T1SS) in Gram-negative bacteria is particularly attractive due to its simple architecture involving only three proteins and one-step translocation across both inner and outer membranes. However, proteins that fold rapidly within the cell often fail to pass through the narrow T1SS channel tunnel, limiting its industrial application. To address this limitation, we engineered a 10-amino-acid calcium-binding sequence (CBS) that disrupts proximal secondary structures through electrostatic repulsion at low Ca2+ concentrations, thereby inhibiting premature folding of target proteins in the cell. We demonstrated that CBS-grafted variants of three fast-folding proteins-mRFP1, RNase H1, and monobody-were efficiently secreted by Escherichia coli expressing the Serratia marcescens Lip T1SS as compared to their parental proteins. Remarkably, the CBS-grafted variants were fully active and structurally identical to the intracellularly produced parental proteins when isolated from culture supernatants. Furthermore, the removal of Ca2+ from CBS did not compromise the structure or function, indicating that the CBS-mediated calcium-dependent folding was irreversible. Our work will expand the utility of T1SS for secreting diverse proteins, paving the way for broader industrial applications.

Design and structure of overlapping regions in PCA via deep learning

Polymerase cycling assembly (PCA) stands out as the predominant method in the synthesis of kilobase-length DNA fragments. The design of overlapping regions is the core factor affecting the success rate of synthesis. However, there still exists DNA sequences that are challenging to design and construct in the genome synthesis. Here we proposed a deep learning model based on extensive synthesis data to discern latent sequence representations in overlapping regions with an AUPR of 0.805. Utilizing the model, we developed the SmartCut algorithm aimed at designing oligonucleotides and enhancing the success rate of PCA experiments. This algorithm was successfully applied to sequences with diverse synthesis constraints, 80.4 % of which were synthesized in a single round. We further discovered structure differences represented by major groove width, stagger, slide, and centroid distance between overlapping and non-overlapping regions, which elucidated the model's reasonableness through the lens of physical chemistry. This comprehensive approach facilitates streamlined and efficient investigations into the genome synthesis.

Large-scale discovery, analysis, and design of protein energy landscapes

All folded proteins continuously fluctuate between their low-energy native structures and higher energy conformations that can be partially or fully unfolded. These rare states influence protein function, interactions, aggregation, and immunogenicity, yet they remain far less understood than protein native states. Although native protein structures are now often predictable with impressive accuracy, conformational fluctuations and their energies remain largely invisible and unpredictable, and experimental challenges have prevented large-scale measurements that could improve machine learning and physics-based modeling. Here, we introduce a multiplexed experimental approach to analyze the energies of conformational fluctuations for hundreds of protein domains in parallel using intact protein hydrogen-deuterium exchange mass spectrometry. We analyzed 5,778 domains 28-64 amino acids in length, revealing hidden variation in conformational fluctuations even between sequences sharing the same fold and global folding stability. Site-resolved hydrogen exchange NMR analysis of 13 domains showed that these fluctuations often involve entire secondary structural elements with lower stability than the overall fold. Computational modeling of our domains identified structural features that correlated with the experimentally observed fluctuations, enabling us to design mutations that stabilized low-stability structural segments. Our dataset enables new machine learning-based analysis of protein energy landscapes, and our experimental approach promises to reveal these landscapes at unprecedented scale.

Robust enzyme discovery and engineering with deep learning using CataPro

Accurate prediction of enzyme kinetic parameters is crucial for enzyme exploration and modification. Existing models face the problem of either low accuracy or poor generalization ability due to overfitting. In this work, we first developed unbiased datasets to evaluate the actual performance of these methods and proposed a deep learning model, CataPro, based on pre-trained models and molecular fingerprints to predict turnover number (kcat), Michaelis constant (Km), and catalytic efficiency (kcat/Km). Compared with previous baseline models, CataPro demonstrates clearly enhanced accuracy and generalization ability on the unbiased datasets. In a representational enzyme mining project, by combining CataPro with traditional methods, we identified an enzyme (SsCSO) with 19.53 times increased activity compared to the initial enzyme (CSO2) and then successfully engineered it to improve its activity by 3.34 times. This reveals the high potential of CataPro as an effective tool for future enzyme discovery and modification.

Dsembler - DNA Assembly Designer: A Tool for Facilitating Assembly of Oligomers

Synthetic biology has garnered significant global interest owing to its diverse applications in bio-based production, biosensing, living therapeutics, and drug delivery. This heightened interest has increased the demand for novel protein synthesis methods and genome-scale assemblies. However, gene assembly from oligomers presents several challenges, including the risk of incorrect assembly between oligomers, self-annealing, and the potential for insertions or deletions resulting from misannealed oligomers. Dsembler (DNA Assembly Designer) is a web-based software application designed to assemble long DNA sequences. It provides a set of oligomers with optimal melting temperatures and GC overlap, which facilitates a commercially available oligomer pool service. By enhancing the accuracy of oligomer design, Dsembler has addressed critical challenges in synthetic biology and supported advancements in genetic engineering and molecular biology.

BAC-browser: the tool for synthetic biology

BACKGROUND

Currently, synthetic genomics is a rapidly developing field. Its main tasks, such as the design of synthetic sequences and the assembly of DNA sequences from synthetic oligonucleotides, require specialized software. In this article, we present a program with a graphical interface that allows non-bioinformatics to perform the tasks needed in synthetic genomics.

RESULTS

We developed BAC-browser v.2.1. It helps to design nucleotide sequences and features the following tools: generate nucleotide sequence from amino acid sequences using a codon frequency table for a specific organism, as well as visualization of restriction sites, GC composition, GC skew and secondary structure. To assemble DNA sequences, a fragmentation tool was created: regular breakdown into oligonucleotides of a certain length and breakdown into oligonucleotides with thermodynamic alignment. We demonstrate the possibility of DNA fragments assemblies designed in different modes of BAC-browser.

CONCLUSIONS

The BAC-browser has a large number of tools for working in the field of systemic genomics and is freely available at the link with a direct link https://sysbiomed.ru/upload/BAC-browser-2.1.zip .

Heat-sterilizable antibody mimics designed on the cold shock protein scaffold from hyperthermophile Thermotoga maritima

Antibodies and antibody mimics are extensively used in the pharmaceutical industry, where stringent safety standards are required. Implementing heat sterilization during or after the manufacturing process could help prevent contamination by viruses and bacteria. However, conventional antibodies and antibody mimics are not suitable for heat sterilization because they irreversibly denature at high temperatures. In this study, we focused on the refolding property of the cold shock protein from the hyperthermophile Thermotoga maritima (TmCSP), which denatures at elevated temperatures but regains its native structure upon re-cooling. We designed and constructed a mutant library of TmCSP in which amino acid residues in its three surface loops were diversified. From the library, mutant TmCSPs that bind to each of eight target proteins were selected by phage and yeast surface display methods. We confirmed that the secondary structure and binding affinity of all the selected mutants were restored after heat treatment followed by cooling. Additionally, freeze-drying did not impair their binding affinity. The crystal structure of a mutant TmCSP in complex with its target, the esterase from Alicyclobacillus acidocaldarius, revealed specific interactions between them. These results clearly demonstrate the feasibility of creating heat-sterilizable antibody mimics using TmCSP as a scaffold.

Accurate de novo design of heterochiral protein-protein interactions

Abiotic D-proteins that selectively bind to natural L-proteins have gained significant biotechnological interest. However, the underlying structural principles governing such heterochiral protein-protein interactions remain largely unknown. In this study, we present the de novo design of D-proteins consisting of 50-65 residues, aiming to target specific surface regions of L-proteins or L-peptides. Our designer D-protein binders exhibit nanomolar affinity toward an artificial L-peptide, as well as two naturally occurring proteins of therapeutic significance: the D5 domain of human tropomyosin receptor kinase A (TrkA) and human interleukin-6 (IL-6). Notably, these D-protein binders demonstrate high enantiomeric specificity and target specificity. In cell-based experiments, designer D-protein binders effectively inhibited the downstream signaling of TrkA and IL-6 with high potency. Moreover, these binders exhibited remarkable thermal stability and resistance to protease degradation. Crystal structure of the designed heterochiral D-protein-L-peptide complex, obtained at a resolution of 2.0 Å, closely resembled the design model, indicating that the computational method employed is highly accurate. Furthermore, the crystal structure provides valuable information regarding the interactions between helical L-peptides and D-proteins, particularly elucidating a novel mode of heterochiral helix-helix interactions. Leveraging the design of D-proteins specifically targeting L-peptides or L-proteins opens up avenues for systematic exploration of the mirror-image protein universe, paving the way for a diverse range of applications.

De novo design of mini-protein binders broadly neutralizing Clostridioides difficile toxin B variants

Clostridioides difficile toxin B (TcdB) is the key virulence factor accounting for C. difficile infection-associated symptoms. Effectively neutralizing different TcdB variants with a universal solution poses a significant challenge. Here we present the de novo design and characterization of pan-specific mini-protein binders against major TcdB subtypes. Our design successfully binds to the first receptor binding interface (RBI-1) of the varied TcdB subtypes, exhibiting affinities ranging from 20 pM to 10 nM. The cryo-electron microscopy (cryo-EM) structures of the mini protein binder in complex with TcdB1 and TcdB4 are consistent with the computational design models. The engineered and evolved variants of the mini-protein binder and chondroitin sulfate proteoglycan 4 (CSPG4), another natural receptor that binds to the second RBI (RBI-2) of TcdB, better neutralize major TcdB variants both in cells and in vivo, as demonstrated by the colon-loop assay using female mice. Our findings provide valuable starting points for the development of therapeutics targeting C. difficile infections (CDI).

Challenges and Solutions for Leave-One-Out Biosensor Design in the Context of a Rugged Fitness Landscape

The leave-one-out (LOO) green fluorescent protein (GFP) approach to biosensor design combines computational protein design with split protein reconstitution. LOO-GFPs reversibly fold and gain fluorescence upon encountering the target peptide, which can be redefined by computational design of the LOO site. Such an approach can be used to create reusable biosensors for the early detection of emerging biological threats. Enlightening biophysical inferences for nine LOO-GFP biosensor libraries are presented, with target sequences from dengue, influenza, or HIV, replacing beta strands 7, 8, or 11. An initially low hit rate was traced to components of the energy function, manifesting in the over-rewarding of over-tight side chain packing. Also, screening by colony picking required a low library complexity, but designing a biosensor against a peptide of at least 12 residues requires a high-complexity library. This double-bind was solved using a "piecemeal" iterative design strategy. Also, designed LOO-GFPs fluoresced in the unbound state due to unwanted dimerization, but this was solved by fusing a fully functional prototype LOO-GFP to a fiber-forming protein, Drosophila ultrabithorax, creating a biosensor fiber. One influenza hemagglutinin biosensor is characterized here in detail, showing a shifted excitation/emission spectrum, a micromolar affinity for the target peptide, and an unexpected photo-switching ability.

Enhancing catalytic efficiency of Bacillus subtilis laccase BsCotA through active site pocket design

BsCotA laccase is a promising candidate for industrial application due to its excellent thermal stability. In this research, our objective was to enhance the catalytic efficiency of BsCotA by modifying the active site pocket. We utilized a strategy combining the diversity design of the active site pocket with molecular docking screening, which resulted in selecting five variants for characterization. All five variants proved functional, with four demonstrating improved turnover rates. The most effective variants exhibited a remarkable 7.7-fold increase in catalytic efficiency, evolved from 1.54 × 105 M-1 s-1 to 1.18 × 106 M-1 s-1, without any stability loss. To investigate the underlying molecular mechanisms, we conducted a comprehensive structural analysis of our variants. The analysis suggested that substituting Leu386 with aromatic residues could enhance BsCotA's ability to accommodate the 2,2'-azino-di-(3-ethylbenzothiazoline)-6-sulfonate (ABTS) substrate. However, the inclusion of charged residues, G323D and G417H, into the active site pocket reduced kcat. Ultimately, our research contributes to a deeper understanding of the role played by residues in the laccases' active site pocket, while successfully demonstrating a method to lift the catalytic efficiency of BsCotA. KEY POINTS: • Active site pocket design that enhanced BsCotA laccase efficiency • 7.7-fold improved in catalytic rate • All tested variants retain thermal stability.

Gene synthesis design: a pythonic approach

Researchers often need to synthesize genes of interest in this era of synthetic biology. Gene synthesis by PCR assembly of multiple DNA fragments is a quick and economical method that is widely applied. Up to now, there have been a few software solutions for designing fragments in gene synthesis. However, some of these software solutions use programming languages that are not popular now, other software products are commercial or require users to visit servers. In this study, we propose a Python program to design DNA fragments for gene synthesis. The algorithm is designed to meet the experimental needs. Also, the source code with detailed annotation is freely available for all users. Furthermore, the feasibility of the algorithm and the program is validated by experiments. Our program can be useful for the design of gene synthesis in the labs and help the study of gene structure and function.

Binding and sensing diverse small molecules using shape-complementary pseudocycles

We describe an approach for designing high-affinity small molecule-binding proteins poised for downstream sensing. We use deep learning-generated pseudocycles with repeating structural units surrounding central binding pockets with widely varying shapes that depend on the geometry and number of the repeat units. We dock small molecules of interest into the most shape complementary of these pseudocycles, design the interaction surfaces for high binding affinity, and experimentally screen to identify designs with the highest affinity. We obtain binders to four diverse molecules, including the polar and flexible methotrexate and thyroxine. Taking advantage of the modular repeat structure and central binding pockets, we construct chemically induced dimerization systems and low-noise nanopore sensors by splitting designs into domains that reassemble upon ligand addition.

Vaccine design and development: Exploring the interface with computational biology and AI

Computational biology involves applying computer science and informatics techniques in biology to understand complex biological data. It allows us to collect, connect, and analyze biological data at a large scale and build predictive models. In the twenty first century, computational resources along with Artificial Intelligence (AI) have been widely used in various fields of biological sciences such as biochemistry, structural biology, immunology, microbiology, and genomics to handle massive data for decision-making, including in applications such as drug design and vaccine development, one of the major areas of focus for human and animal welfare. The knowledge of available computational resources and AI-enabled tools in vaccine design and development can improve our ability to conduct cutting-edge research. Therefore, this review article aims to summarize important computational resources and AI-based tools. Further, the article discusses the various applications and limitations of AI tools in vaccine development.

Postbiotic-based recombinant receptor activator of NF-κB ligand enhanced oral vaccine efficiency in chicken

Functional M cells are differentiated by receptor activator of NF-κB ligand (RANKL) and capture of luminal antigens to initiate immune responses. We aimed to use postbiotic-based recombinant chicken RANKL (cRANKL) to promote M cell differentiation and test the efficacy of oral vaccines. Chicks were divided into three groups that were administered phosphate-buffered saline (PBS), cell extracts of wild-type Lactococcus lactis subsp. lactis IL1403 (WT_CE), or cell extracts of recombinant L. lactis expressing cRANKL (cRANKL_CE). The expression of the M cell marker was measured, and the gut microbiome was profiled. The efficiency of the infectious bursal disease (IBD) vaccine was tested after 12 consecutive days of administering cRANKL_CE. The chickens that were administered cRANKL_CE (p = 0.038) had significantly higher Annexin A5 (ANXA5) mRNA expression levels than those in the PBS group (PBS vs. WT_CE, p = 0.657). In the gut microbiome analysis, no significant changes were observed. However, the relative abundance of Escherichia-Shigella was negatively correlated (r =  - 0.43, p = 0.019) with ANXA5 mRNA expression in Peyer's patches. cRANKL_CE/IBD (p = 0.018) had significantly higher IBD-specific faecal IgA levels than PBS/IBD (PBS/IBD vs. WT_CE/IBD, p = 0.217). Postbiotic-based recombinant cRANKL effectively improved the expression of M cell markers and the efficiency of oral vaccines. No significant changes were observed in the gut microbiome after administration of postbiotic-based recombinant cRANKL. This strategy can be used for the development of feed additives and adjuvants. KEY POINTS: • Postbiotic-based recombinant cRANKL enhanced the expression of ANXA5 in chicken. • The relative abundance of Escherichia-Shigella was negatively correlated with ANXA5 expression. • Postbiotic-based recombinant cRANKL effectively improved the efficiency of oral vaccine.

Recombinant multiepitope proteins expressed in Escherichia coli cells and their potential for immunodiagnosis

Recombinant multiepitope proteins (RMPs) are a promising alternative for application in diagnostic tests and, given their wide application in the most diverse diseases, this review article aims to survey the use of these antigens for diagnosis, as well as discuss the main points surrounding these antigens. RMPs usually consisting of linear, immunodominant, and phylogenetically conserved epitopes, has been applied in the experimental diagnosis of various human and animal diseases, such as leishmaniasis, brucellosis, cysticercosis, Chagas disease, hepatitis, leptospirosis, leprosy, filariasis, schistosomiasis, dengue, and COVID-19. The synthetic genes for these epitopes are joined to code a single RMP, either with spacers or fused, with different biochemical properties. The epitopes' high density within the RMPs contributes to a high degree of sensitivity and specificity. The RMPs can also sidestep the need for multiple peptide synthesis or multiple recombinant proteins, reducing costs and enhancing the standardization conditions for immunoassays. Methods such as bioinformatics and circular dichroism have been widely applied in the development of new RMPs, helping to guide their construction and better understand their structure. Several RMPs have been expressed, mainly using the Escherichia coli expression system, highlighting the importance of these cells in the biotechnological field. In fact, technological advances in this area, offering a wide range of different strains to be used, make these cells the most widely used expression platform. RMPs have been experimentally used to diagnose a broad range of illnesses in the laboratory, suggesting they could also be useful for accurate diagnoses commercially. On this point, the RMP method offers a tempting substitute for the production of promising antigens used to assemble commercial diagnostic kits.

POSoligo software for in vitro gene synthesis

Oligonucleotide synthesis is vital for molecular experiments. Bioinformatics has been employed to create various algorithmic tools for the in vitro synthesis of nucleotides. The main approach to synthesizing long-chain DNA molecules involves linking short-chain oligonucleotides through ligase chain reaction (LCR) and polymerase chain reaction (PCR). Short-chain DNA molecules have low mutation rates, while LCR requires complementary interfaces at both ends of the two nucleic acid molecules or may alter the conformation of the nucleotide chain, leading to termination of amplification. Therefore, molecular melting temperature, length, and specificity must be considered during experimental design. POSoligo is a specialized offline tool for nucleotide fragment synthesis. It optimizes the oligonucleotide length and specificity based on input single-stranded DNA, producing multiple contiguous long strands (COS) and short patch strands (POS) with complementary ends. This process ensures free 5'- and 3'-ends during oligonucleotide synthesis, preventing secondary structure formation and ensuring specific binding between COS and POS without relying on stabilizing the complementary strands based on Tm values. POSoligo was used to synthesize the linear RBD sequence of SARS-CoV-2 using only one DNA strand, several POSs for LCR ligation, and two pairs of primers for PCR amplification in a time- and cost-effective manner.

An Integer Linear Programming Model to Optimize Coding DNA Sequences By Joint Control of Transcript Indicators

A Coding DNA Sequence (CDS) is a fraction of DNA whose nucleotides are grouped into consecutive triplets called codons, each one encoding an amino acid. Because most amino acids can be encoded by more than one codon, the same amino acid chain can be obtained by a very large number of different CDSs. These synonymous CDSs show different features that, also depending on the organism the transcript is expressed in, could affect translational efficiency and yield. The identification of optimal CDSs with respect to given transcript indicators is in general a challenging task, but it has been observed in recent literature that integer linear programming (ILP) can be a very flexible and efficient way to achieve it. In this article, we add evidence to this observation by proposing a new ILP model that simultaneously optimizes different well-grounded indicators. With this model, we efficiently find solutions that dominate those returned by six existing codon optimization heuristics.

Storage-D: A user-friendly platform that enables practical and personalized DNA data storage

Deoxyribonucleic acid (DNA) has been suggested as a very promising medium for data storage in recent years. Although numerous studies have advocated for DNA data storage, its practical application remains obscure and there is a lack of a user-oriented platform. Here, we developed a DNA data storage platform, named Storage-D, which allows users to convert their data into DNA sequences of any length and vice versa by selecting algorithms, error-correction, random-access, and codec pin strategies in terms of their own choice. It incorporates a newly designed "Wukong" algorithm, which provides over 20 trillion codec pins for data privacy use. This algorithm can also control GC content to the selected standard, as well as adjust the homopolymer run length to a defined level, while maintaining a high coding potential of ~1.98 bis/nt, allowing it to outperform previous algorithms. By connecting to a commercial DNA synthesis and sequencing platform with "Storage-D," we successfully stored "Diagnosis and treatment protocol for COVID-19 patients" into 200 nt oligo pools in vitro, and 500 bp genes in vivo which replicated in both normal and extreme bacteria. Together, this platform allows for practical and personalized DNA data storage, potentially with a wide range of applications.

Structure of methyltransferase RedM that forms the dimethylpyrrolinium of the bisindole reductasporine

Bisindoles are biologically active natural products that arise from the oxidative dimerization of two molecules of l-tryptophan. In bacterial bisindole pathways, a core set of transformations is followed by the action of diverse tailoring enzymes that catalyze reactions that lead to diverse bisindole products. Among bisindoles, reductasporine is distinct due to its dimethylpyrrolinium structure. Its previously reported biosynthetic gene cluster encodes two unique tailoring enzymes, the imine reductase RedE and the dimethyltransferase RedM, which were shown to produce reductasporine from a common bisindole intermediate in recombinant E. coli. To gain more insight into the unique tailoring enzymes in reductasporine assembly, we reconstituted the biosynthetic pathway to reductasporine in vitro and then solved the 1.7 Å resolution structure of RedM. Our work reveals RedM adopts a variety of conformational changes with distinct open and closed conformations, and site-directed mutagenesis alongside sequence analysis identifies important active site residues. Finally, our work sets the stage for understanding how RedM evolved to react with a pyrrolinium scaffold and may enable the development of new dimethyltransferase catalysts.

De novo design of diverse small molecule binders and sensors using Shape Complementary Pseudocycles

A general method for designing proteins to bind and sense any small molecule of interest would be widely useful. Due to the small number of atoms to interact with, binding to small molecules with high affinity requires highly shape complementary pockets, and transducing binding events into signals is challenging. Here we describe an integrated deep learning and energy based approach for designing high shape complementarity binders to small molecules that are poised for downstream sensing applications. We employ deep learning generated psuedocycles with repeating structural units surrounding central pockets; depending on the geometry of the structural unit and repeat number, these pockets span wide ranges of sizes and shapes. For a small molecule target of interest, we extensively sample high shape complementarity pseudocycles to generate large numbers of customized potential binding pockets; the ligand binding poses and the interacting interfaces are then optimized for high affinity binding. We computationally design binders to four diverse molecules, including for the first time polar flexible molecules such as methotrexate and thyroxine, which are expressed at high levels and have nanomolar affinities straight out of the computer. Co-crystal structures are nearly identical to the design models. Taking advantage of the modular repeating structure of pseudocycles and central location of the binding pockets, we constructed low noise nanopore sensors and chemically induced dimerization systems by splitting the binders into domains which assemble into the original pseudocycle pocket upon target molecule addition.

New insights into the substrate specificity of cholesterol oxidases for more aware application

Cholesterol oxidases (ChOxes) are enzymes that catalyze the oxidation of cholesterol to cholest-4-en-3-one. These enzymes find wide applications across various diagnostic and industrial settings. In addition, as a pathogenic factor of several bacteria, they have significant clinical implications. The current classification system for ChOxes is based on the type of bond connecting FAD to the apoenzyme, which does not adequately illustrate the enzymatic and structural characteristics of these proteins. In this study, we have adopted an integrative approach, combining evolutionary analysis, classic enzymatic techniques and computational approaches, to elucidate the distinct features of four various ChOxes from Rhodococcus sp. (RCO), Cromobacterium sp. (CCO), Pseudomonas aeruginosa (PCO) and Burkhoderia cepacia (BCO). Comparative and evolutionary analysis of substrate-binding domain (SBD) and FAD-binding domain (FBD) helped to reveal the origin of ChOxes. We discovered that all forms of ChOxes had a common ancestor and that the structural differences evolved later during divergence. Further examination of amino acid variations revealed SBD as a more variable compared to FBD independently of FAD coupling mechanism. Revealed differences in amino acid positions turned out to be critical in determining common for ChOxes properties and those that account for the individual differences in substrate specificity. A novel look with the help of chemical descriptors on found distinct features were sufficient to attempt an alternative classification system aimed at application approach. While univocal characteristics necessary to establish such a system remain elusive, we were able to demonstrate the substrate and protein features that explain the differences in substrate profile.

Fusion crystallization reveals the behavior of both the 1TEL crystallization chaperone and the TNK1 UBA domain

Human thirty-eight-negative kinase-1 (TNK1) is implicated in cancer progression. The TNK1 ubiquitin-associated (UBA) domain binds polyubiquitin and plays a regulatory role in TNK1 activity and stability. No experimentally determined molecular structure of this unusual UBA domain is available. We fused the UBA domain to the 1TEL variant of the translocation ETS leukemia protein sterile alpha motif (TELSAM) crystallization chaperone and obtained crystals diffracting as far as 1.53 Å. GG and GSGG linkers allowed the UBA to reproducibly find a productive binding mode against its host 1TEL polymer and crystallize at protein concentrations as low as 0.2 mg/mL. Our studies support a mechanism of 1TEL fusion crystallization and show that 1TEL fusion crystals require fewer crystal contacts than traditional protein crystals. Modeling and experimental validation suggest the UBA domain may be selective for both the length and linkages of polyubiquitin chains.

Bacterial production of recombinant contraceptive vaccine antigen from CatSper displayed on a human papilloma virus-like particle

CatSper is a voltage dependent calcium ion channel present in the principal piece of sperm tail. It plays a crucial role in sperm hyperactivated motility and so in fertilization. Extracellular loops of mouse sperm CatSper were used to develop a vaccine to achieve protection from pregnancy. These loops were inserted at one of the three hypervariable regions of Human Papilloma Virus (HPV) capsid protein (L1). Recombinant vaccines were expressed in E.coli as inclusion body (IB), purified, refolded and assembled into virus-like particles (VLP) in vitro, and adsorbed on alum. Four vaccine candidates were tested in Balb/C mice. All the constructs proved immunogenic, one showed contraceptive efficacy. This recombinant contraceptive vaccine is a non-hormonal intervention and is expected to give long-acting protection from undesired pregnancies.

GIFTdb: a useful gene database for plant fruit traits improving

Fruit traits are critical determinants of plant fitness, resource diversity, productive and quality. Gene regulatory networks in plants play an essential role in determining fruit traits, such as fruit size, yield, firmness, aroma and other important features. Many research studies have focused on elucidating the associated signaling pathways and gene interaction mechanism to better utilize gene resources for regulating fruit traits. However, the availability of specific database of genes related to fruit traits for use by the plant research community remains limited. To address this limitation, we developed the Gene Improvements for Fruit Trait Database (GIFTdb, http://giftdb.agroda.cn). GIFTdb contains 35 365 genes, including 896 derived from the FR database 1.0, 305 derived from 30 882 articles from 2014 to 2021, 236 derived from the Universal Protein Resource (UniProt) database, and 33 928 identified through homology analysis. The database supports several aided analysis tools, including signal transduction pathways, gene ontology terms, protein-protein interactions, DNAWorks, Basic Local Alignment Search Tool (BLAST), and Protein Subcellular Localization Prediction (WoLF PSORT). To provide information about genes currently unsupported in GIFTdb, potential fruit trait-related genes can be searched based on homology with the supported genes. GIFTdb can provide valuable assistance in determining the function of fruit trait-related genes, such as MYB306-like, by conducting a straightforward search. We believe that GIFTdb will be a valuable resource for researchers working on gene function annotation and molecular breeding to improve fruit traits.

A novel protein purification scheme based on salt inducible self-assembling peptides

BACKGROUND

Protein purification remains a critical need for biosciences and biotechnology. It frequently requires multiple rounds of chromatographic steps that are expensive and time-consuming. Our lab previously reported a cleavable self-aggregating tag (cSAT) scheme for streamlined protein expression and purification. The tag consists of a self-assembling peptide (SAP) and a controllable self-cleaving intein. The SAP drives the target protein into an active aggregate, then by intein-mediated cleavage, the target protein is released. Here we report a novel cSAT scheme in which the self-assembling peptide is replaced with a salt inducible self-assembling peptide. This allows a target protein to be expressed first in the soluble form, and the addition of salt then drives the target protein into the aggregated form, followed by cleavage and release.

RESULTS

In this study, we used MpA (MKQLEDKIEELLSKAAMKQLEDKIEELLSK) as a second class of self-assembling peptide in the cSAT scheme. This scheme utilizes low salt concentration to keep the fusion protein soluble, while eliminating insoluble cellular matters by centrifugation. Salt then triggers MpA-mediated self-aggregation of the fusion, removing soluble background host cell proteins. Finally, intein-mediated cleavage releases the target protein into solution. As a proof-of-concept, we successfully purified four proteins and peptides (human growth hormone, 22.1 kDa; LCB3, 7.7 kDa; SpyCatcherΔN-ELP-SpyCatcherΔN, 26.2 kDa; and xylanase, 45.3 kDa) with yields ranging from 12 to 87 mg/L. This was comparable to the classical His-tag method both in yield and purity (72-97%), but without the His-tag. By using a further two-step column purification process that included ion-exchange chromatography and size-exclusion chromatography, the purity was increased to over 99%.

CONCLUSION

Our results demonstrate that a salt-inducible self-assembling peptide can serve as a controllable aggregating tag, which might be advantageous in applications where soluble expression of the target protein is preferred. This work also demonstrates the potential and advantages of utilizing salt inducible self-assembling peptides for protein separation.

Computational design of sequence-specific DNA-binding proteins

Sequence-specific DNA-binding proteins (DBPs) play critical roles in biology and biotechnology, and there has been considerable interest in the engineering of DBPs with new or altered specificities for genome editing and other applications. While there has been some success in reprogramming naturally occurring DBPs using selection methods, the computational design of new DBPs that recognize arbitrary target sites remains an outstanding challenge. We describe a computational method for the design of small DBPs that recognize specific target sequences through interactions with bases in the major groove, and employ this method in conjunction with experimental screening to generate binders for 5 distinct DNA targets. These binders exhibit specificity closely matching the computational models for the target DNA sequences at as many as 6 base positions and affinities as low as 30-100 nM. The crystal structure of a designed DBP-target site complex is in close agreement with the design model, highlighting the accuracy of the design method. The designed DBPs function in both Escherichia coli and mammalian cells to repress and activate transcription of neighboring genes. Our method is a substantial step towards a general route to small and hence readily deliverable sequence-specific DBPs for gene regulation and editing.

Mega-scale experimental analysis of protein folding stability in biology and design

Advances in DNA sequencing and machine learning are providing insights into protein sequences and structures on an enormous scale1. However, the energetics driving folding are invisible in these structures and remain largely unknown2. The hidden thermodynamics of folding can drive disease3,4, shape protein evolution5-7 and guide protein engineering8-10, and new approaches are needed to reveal these thermodynamics for every sequence and structure. Here we present cDNA display proteolysis, a method for measuring thermodynamic folding stability for up to 900,000 protein domains in a one-week experiment. From 1.8 million measurements in total, we curated a set of around 776,000 high-quality folding stabilities covering all single amino acid variants and selected double mutants of 331 natural and 148 de novo designed protein domains 40-72 amino acids in length. Using this extensive dataset, we quantified (1) environmental factors influencing amino acid fitness, (2) thermodynamic couplings (including unexpected interactions) between protein sites, and (3) the global divergence between evolutionary amino acid usage and protein folding stability. We also examined how our approach could identify stability determinants in designed proteins and evaluate design methods. The cDNA display proteolysis method is fast, accurate and uniquely scalable, and promises to reveal the quantitative rules for how amino acid sequences encode folding stability.

An Inferred Ancestral CotA Laccase with Improved Expression and Kinetic Efficiency

Laccases are widely used in industrial production due to their broad substrate availability and environmentally friendly nature. However, the pursuit of laccases with superior stability and increased heterogeneous expression to meet industry demands appears to be an ongoing challenge. To address this challenge, we resurrected five ancestral sequences of laccase BsCotA and their homologues. All five variants were successfully expressed in soluble and functional forms with improved expression levels in Escherichia coli. Among the five variants, three exhibited higher catalytic rates, thermal stabilities, and acidic stabilities. Notably, AncCotA2, the best-performing variant, displayed a k_cat/K_M of 7.5 × 10⁵ M^-1·s^-1, 5.2-fold higher than that of the wild-type BsCotA, an improved thermo- and acidic stability, and better dye decolorization ability. This study provides a laccase variant with high application potential and presents a new starting point for future enzyme engineering.

Fusion crystallization reveals the behavior of both the 1TEL crystallization chaperone and the TNK1 UBA domain

Human thirty-eight-negative kinase-1 (TNK1) is implicated in cancer progression. The TNK1-UBA domain binds polyubiquitin and plays a regulatory role in TNK1 activity and stability. Sequence analysis suggests an unusual architecture for the TNK1 UBA domain, but an experimentally-validated molecular structure is undetermined. To gain insight into TNK1 regulation, we fused the UBA domain to the 1TEL crystallization chaperone and obtained crystals diffracting as far as 1.53 Å. A 1TEL search model enabled solution of the X-ray phases. GG and GSGG linkers allowed the UBA to reproducibly find a productive binding mode against its host 1TEL polymer and to crystallize at protein concentrations as low as 0.1 mg/mL. Our studies support a mechanism of TELSAM fusion crystallization and show that TELSAM fusion crystals require fewer crystal contacts than traditional protein crystals. Modeling and experimental validation suggest the UBA domain may be selective for both the length and linkages of polyubiquitin chains.

Decreasing the flexibility of the TELSAM-target protein linker and omitting the cleavable fusion tag improves crystal order and diffraction limits

TELSAM crystallization promises to become a revolutionary tool for the facile crystallization of proteins. TELSAM can increase the rate of crystallization and form crystals at low protein concentrations without direct contact between TELSAM polymers and, in some cases, with very minimal crystal contacts overall (Nawarathnage et al ., 2022). To further understand and characterize TELSAM-mediated crystallization, we sought to understand the requirements for the composition of the linker between TELSAM and the fused target protein. We evaluated four different linkers Ala-Ala, Ala-Val, Thr-Val, and Thr-Thr, between 1TEL and the human CMG2 vWa domain. We compared the number of successful crystallization conditions, the number of crystals, the average and best diffraction resolution, and the refinement parameters for the above constructs. We also tested the effect of the fusion protein SUMO on crystallization. We discovered that rigidification of the linker improved diffraction resolution, likely by decreasing the number of possible orientations of the vWa domains in the crystal, and that omitting the SUMO domain from the construct also improved the diffraction resolution.

Synopsis

We demonstrate that the TELSAM protein crystallization chaperone can enable facile protein crystallization and high-resolution structure determination. We provide evidence to support the use of short but flexible linkers between TELSAM and the protein of interest and to support the avoidance of cleavable purification tags in TELSAM-fusion constructs.

Improving de novo protein binder design with deep learning

Recently it has become possible to de novo design high affinity protein binding proteins from target structural information alone. There is, however, considerable room for improvement as the overall design success rate is low. Here, we explore the augmentation of energy-based protein binder design using deep learning. We find that using AlphaFold2 or RoseTTAFold to assess the probability that a designed sequence adopts the designed monomer structure, and the probability that this structure binds the target as designed, increases design success rates nearly 10-fold. We find further that sequence design using ProteinMPNN rather than Rosetta considerably increases computational efficiency.

Mirror proteorhodopsins

Proteorhodopsins (PRs), bacterial light-driven outward proton pumps comprise the first discovered and largest family of rhodopsins, they play a significant role in life on the Earth. A big remaining mystery was that up-to-date there was no described bacterial rhodopsins pumping protons at acidic pH despite the fact that bacteria live in different pH environment. Here we describe conceptually new bacterial rhodopsins which are operating as outward proton pumps at acidic pH. A comprehensive function-structure study of a representative of a new clade of proton pumping rhodopsins which we name "mirror proteorhodopsins", from Sphingomonas paucimobilis (SpaR) shows cavity/gate architecture of the proton translocation pathway rather resembling channelrhodopsins than the known rhodopsin proton pumps. Another unique property of mirror proteorhodopsins is that proton pumping is inhibited by a millimolar concentration of zinc. We also show that mirror proteorhodopsins are extensively represented in opportunistic multidrug resistant human pathogens, plant growth-promoting and zinc solubilizing bacteria. They may be of optogenetic interest.

Cloning and Molecular Characterization of the Recombinant CVB4E2 Immunogenic Viral Protein (rVP1), as a Potential Subunit Protein for Vaccine and Immunodiagnostic Reagent Candidate

The aim of the present study was, first, to clone the VP1 gene of the human coxsackievirus B4 strain E2 (CVB4E2) in the prokaryotic pUC19 plasmid expression vector then to compare it with the structural capsid proteins of the same strain using bioinformatic tools. PCR colony amplification followed through a restriction digestion analysis and sequencing process which affirmed the success of the cloning process. SDS-PAGE and Western Blotting were used to characterize the purified recombinant viral protein expressed in bacteria cells. The BLASTN tool revealed that the nucleotide sequence of the recombinant VP1 (rVP1) expressed by pUC19 highly matched the target nucleotide sequence of the diabetogenic CVB4E2 strain. Secondary structure and three-dimension structure prediction suggested that rVP1, such as wild-type VP1, is chiefly composed of random coils and a high percentage of exposed amino acids. Linear B-cell epitope prediction showed that several antigenic epitopes are likely present in rVP1 and CVB4E2 VP1 capsid protein. Additionally, phosphorylation site prediction revealed that both proteins may affect the signal transduction of host cells and can be involved in virus virulence. The present work highlights the usefulness of cloning and bioinformatics characterizations for gene investigation. Furthermore, the collected data are helpful for future experimental research related to the development of immunodiagnostic reagents and subunit vaccines based on the expression of immunogenic viral capsid proteins.

Generation of Functional-RNA Arrays by In Vitro Transcription and In Situ RNA Capture for the Detection of RNA-RNA Interactions

RNA performs a wide variety of vital cellular functions. These functions typically require interactions with other biological macromolecules, often as part of an intricate communication network. High-throughput techniques capable of analyzing RNA-based interactions are therefore essential. Functional-RNA arrays address this need, providing the capability of performing hundreds of miniature assays in parallel. Here we describe a method to generate functional-RNA arrays using in vitro transcription of a DNA template array and in situ RNA capture. We also suggest how functional-RNA arrays could be applied to investigating RNA-RNA interactions.

Heterologous Expression of Recombinant Human Cytochrome P450 (CYP) in Escherichia coli: N-Terminal Modification, Expression, Isolation, Purification, and Reconstitution

Cytochrome P450 (CYP) enzymes play important roles in metabolising endogenous and xenobiotic substances. Characterisations of human CYP proteins have been advanced with the rapid development of molecular technology that allows heterologous expression of human CYPs. Among several hosts, bacteria systems such as Escherichia coli (E. coli) have been widely used thanks to their ease of use, high level of protein yields, and affordable maintenance costs. However, the levels of expression in E. coli reported in the literature sometimes differ significantly. This paper aims to review several contributing factors, including N-terminal modifications, co-expression with a chaperon, selections of vectors and E. coli strains, bacteria culture and protein expression conditions, bacteria membrane preparations, CYP protein solubilizations, CYP protein purifications, and reconstitution of CYP catalytic systems. The common factors that would most likely lead to high expression of CYPs were identified and summarised. Nevertheless, each factor may still require careful evaluation for individual CYP isoforms to achieve a maximal expression level and catalytic activity. Recombinant E. coli systems have been evidenced as a useful tool in obtaining the ideal level of human CYP proteins, which ultimately allows for subsequent characterisations of structures and functions.

Implementing computational methods in tandem with synonymous gene recoding for therapeutic development

Synonymous gene recoding, the substitution of synonymous variants into the genetic sequence, has been used to overcome many production limitations in therapeutic development. However, the safety and efficacy of recoded therapeutics can be difficult to evaluate because synonymous codon substitutions can result in subtle, yet impactful changes in protein features and require sensitive methods for detection. Given that computational approaches have made significant leaps in recent years, we propose that machine-learning (ML) tools may be leveraged to assess gene-recoded therapeutics and foresee an opportunity to adapt codon contexts to enhance some powerful existing tools. Here, we examine how synonymous gene recoding has been used to address challenges in therapeutic development, explain the biological mechanisms underlying its effects, and explore the application of computational platforms to improve the surveillance of functional variants in therapeutic design.

Inhibition of a malaria host-pathogen interaction by a computationally designed inhibitor

Malaria is a substantial global health burden with 229 million cases in 2019 and 450,000 deaths annually. Plasmodium vivax is the most widespread malaria-causing parasite putting 2.5 billion people at risk of infection. P. vivax has a dormant liver stage and therefore can exist for long periods undetected. Its blood-stage can cause severe reactions and hospitalization. Few treatment and detection options are available for this pathogen. A unique characteristic of P. vivax is that it depends on the Duffy antigen/receptor for chemokines (DARC) on the surface of host red blood cells for invasion. P. vivax employs the Duffy binding protein (DBP) to bind to DARC. We first de novo designed a three helical bundle scaffolding database which was screened via protease digestions for stability. Protease-resistant scaffolds highlighted thresholds for stability, which we utilized for selecting DARC mimetics that we subsequentially designed through grafting and redesign of these scaffolds. The optimized design small helical protein disrupts the DBP:DARC interaction. The inhibitor blocks the receptor binding site on DBP and thus forms a strong foundation for a therapeutic that will inhibit reticulocyte infection and prevent the pathogenesis of P. vivax malaria.

Sampling of structure and sequence space of small protein folds

Nature only samples a small fraction of the sequence space that can fold into stable proteins. Furthermore, small structural variations in a single fold, sometimes only a few amino acids, can define a protein's molecular function. Hence, to design proteins with novel functionalities, such as molecular recognition, methods to control and sample shape diversity are necessary. To explore this space, we developed and experimentally validated a computational platform that can design a wide variety of small protein folds while sampling shape diversity. We designed and evaluated stability of about 30,000 de novo protein designs of eight different folds. Among these designs, about 6,200 stable proteins were identified, including some predicted to have a first-of-its-kind minimalized thioredoxin fold. Obtained data revealed protein folding rules for structural features such as helix-connecting loops. Beyond serving as a resource for protein engineering, this massive and diverse dataset also provides training data for machine learning. We developed an accurate classifier to predict the stability of our designed proteins. The methods and the wide range of protein shapes provide a basis for designing new protein functions without compromising stability.

A depth-first search algorithm for oligonucleotide design in gene assembly

When synthesizing a gene with a long DNA sequence, it is usually necessary to divide it into several fragments. Based on these fragments, a set of oligonucleotides for gene assembly is produced. Each oligonucleotide is synthesized separately by the chemical reaction, and then the obtained oligonucleotides are assembled into the full gene sequence, in a specific environment, by polymerase chain reaction (PCR) or ligase chain reaction (LCR). In this paper, an effective and efficient algorithm to divide long genes into oligonucleotide sets is presented. First, according to the length of the overlapping oligonucleotide region, the long DNA sequence to be synthesized is divided into fragments of approximately equal length. Second, the length of these fragments is iterated to dynamically optimize the length of the overlapping regions to reduce melting temperature fluctuations. Then, the improved depth-first search algorithm is used according to the design principle of pruning optimization to obtain a uniform set of oligonucleotides with very close melting temperatures. This will decrease the errors in gene assembly with PCR or LCR. Lastly, the oligonucleotides that have homologous melting temperatures needed for PCR-based synthesis and two-step assembly of the target gene are deduced and outputted.

Functional Expression of the Recombinant Spike Receptor Binding Domain of SARS-CoV-2 Omicron in the Periplasm of Escherichia coli

A new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant known as Omicron has caused a rapid increase in recent global patients with coronavirus infectious disease 2019 (COVID-19). To overcome the COVID-19 Omicron variant, production of a recombinant spike receptor binding domain (RBD) is vital for developing a subunit vaccine or a neutralizing antibody. Although bacterial expression has many advantages in the production of recombinant proteins, the spike RBD expressed in a bacterial system experiences a folding problem related to disulfide bond formation. In this study, the soluble Omicron RBD was obtained by a disulfide isomerase-assisted periplasmic expression system in Escherichia coli. The Omicron RBD purified from E. coli was very well recognized by anti-SARS-CoV-2 antibodies, sotrovimab (S309), and CR3022, which were previously reported to bind to various SARS-CoV-2 variants. In addition, the kinetic parameters of the purified Omicron RBD upon binding to the human angiotensin-converting enzyme 2 (ACE2) were similar to those of the Omicron RBD produced in the mammalian expression system. These results suggest that an E. coli expression system would be suitable to produce functional and correctly folded spike RBDs of the next emerging SARS-CoV-2 variants quickly and inexpensively.

Oral Administration of Mice with Cell Extracts of Recombinant Lactococcus lactis IL1403 Expressing Mouse Receptor Activator of NF-kB Ligand (RANKL)

Receptor activator of NF-kB ligand (RANKL) is known to play a major role in bone metabolism and the immune system, and its recombinant form has been expressed in bacterial systems for research since the last two decades. However, most of these recombinant forms are used after purification or directly using living cells. Here, there were cell extracts of recombinant Lactococcus lactis expressing mouse RANKL (mRANKL) used to evaluate its biological activity in mice. Mice were divided into three groups that were fed phosphate-buffered saline (PBS), wild-type L. lactis IL1403 (WT_CE), and recombinant L. lactis expressing mRANKL (mRANKL_CE). The small intestinal transcriptome and fecal microbiome were then profiled. The biological activity of mRANKL_CE was confirmed by studying RANK-RANKL signaling in vitro and in vivo. For small intestinal transcriptome, differentially expressed genes (DEGs) were identified in the mRANKL_CE group, and no DEGs were found in the WT_CE group. In the PBS vs. mRANKL_CE gene enrichment analysis, upregulated genes were enriched for heat shock protein binding, regulation of bone resorption, and calcium ion binding. In the gut microbiome analysis, there were no critical changes among the three groups. However, Lactobacillus and Sphingomonas were more abundant in the mRANKL_CE group than in the other two groups. Our results indicate that cell extracts of mRANKL_CE can play an effective role without a significant impact on the intestine. This strategy may be useful for the development of protein drugs.

Generalized Approach towards Secretion-Based Protein Production via Neutralization of Secretion-Preventing Cationic Substrate Residues

Many heterologous proteins can be secreted by bacterial ATP-binding cassette (ABC) transporters, provided that they are fused with the C-terminal signal sequence, but some proteins are not secretable even though they carry the right signal sequence. The invention of a method to secrete these non-secretable proteins would be valuable both for understanding the secretory physiology of ABC transporters and for industrial applications. Herein, we postulate that cationic “supercharged” regions within the target substrate protein block the secretion by ABC transporters. We also suggest that the secretion of such substrate proteins can be rescued by neutralizing those cationic supercharged regions via structure-preserving point mutageneses. Surface-protruding, non-structural cationic amino acids within the cationic supercharged regions were replaced by anionic or neutral hydrophilic amino acids, reducing the cationic charge density. The examples of rescued secretions we provide include the spike protein of SARS-CoV-2, glutathione-S-transferase, streptavidin, lipase, tyrosinase, cutinase, growth factors, etc. In summary, our study provides a method to predict the secretability and a tool to rescue the secretion by correcting the secretion-blocking regions, making a significant step in understanding the physiological properties of ABC transporter-dependent protein secretion and laying the foundation for the development of a secretion-based protein-producing platform.

Optimal Design of Synthetic DNA Sequences Without Unwanted Binding Sites

Synthesizing DNA molecules by design has become an essential tool in molecular biology and is expected to become ubiquitous in the coming decade. Successful design of a synthetic DNA molecule often requires satisfying multiple objectives, some of which may conflict with others. One particularly important objective is the elimination of unwanted protein binding sites, which may interfere with the desired function of the synthesized molecule. While most design tools offer this fundamental capability, they do not follow a systematic approach that guarantees elimination of all unwanted sites whenever a feasible solution exists. Furthermore, the algorithms these tools use (when published) are often quite naive and inefficient. We present a formal description of the binding site elimination problem and suggest several efficient algorithms that eliminate unwanted patterns with minimum interference to the desired function of the synthesized sequence. These algorithms are simple, efficient, and flexible and, therefore, can be easily incorporated in all existing DNA design tools, enhancing their design capabilities.

Divergent binding mode for a protozoan BRC repeat to RAD51

Interaction of BRCA2 through ca. 30 amino acid residue motifs, BRC repeats, with RAD51 is a conserved feature of the double-strand DNA break repair by homologous recombination in eukaryotes. In humans the binding of the eight BRC repeats is defined by two sequence motifs, FxxA and LFDE, interacting with distinct sites on RAD51. Little is known of the interaction of BRC repeats in other species, especially in protozoans, where variable number of BRC repeats are found in BRCA2 proteins. Here, we have studied in detail the interactions of the two BRC repeats in Leishmania infantum BRCA2 with RAD51. We show LiBRC1 is a high-affinity repeat and determine the crystal structure of its complex with LiRAD51. Using truncation mutagenesis of the LiBRC1 repeat, we demonstrate that high affinity binding is maintained in the absence of an LFDE-like motif and suggest compensatory structural features. These observations point towards a divergent evolution of BRC repeats, where a common FxxA-binding ancestor evolved additional contacts for affinity maturation and fine-tuning.

Intron-Encoded Domain of Herstatin, An Autoinhibitor of Human Epidermal Growth Factor Receptors, Is Intrinsically Disordered

Human epidermal growth factor receptors (HER/ERBB) form dimers that promote cell proliferation, migration, and differentiation, but overexpression of HER proteins results in cancer. Consequently, inhibitors of HER dimerization may function as effective antitumor drugs. An alternatively spliced variant of HER2, called herstatin, is an autoinhibitor of HER proteins, and the intron 8-encoded 79-residue domain of herstatin, called Int8, binds HER family receptors even in isolation. However, the structure of Int8 remains poorly understood. Here, we revealed by circular dichroism, NMR, small-angle X-ray scattering, and structure prediction that isolated Int8 is largely disordered but has a residual helical structure. The radius of gyration of Int8 was almost the same as that of fully unfolded states, although the conformational ensemble of Int8 was less flexible than random coils. These results demonstrate that Int8 is intrinsically disordered. Thus, Int8 is an interesting example of an intrinsically disordered region with tumor-suppressive activity encoded by an intron. Furthermore, we show that the R371I mutant of Int8, which is defective in binding to HER2, is prone to aggregation, providing a rationale for the loss of function.

Design of protein-binding proteins from the target structure alone

The design of proteins that bind to a specific site on the surface of a target protein using no information other than the three-dimensional structure of the target remains a challenge1-5. Here we describe a general solution to this problem that starts with a broad exploration of the vast space of possible binding modes to a selected region of a protein surface, and then intensifies the search in the vicinity of the most promising binding modes. We demonstrate the broad applicability of this approach through the de novo design of binding proteins to 12 diverse protein targets with different shapes and surface properties. Biophysical characterization shows that the binders, which are all smaller than 65 amino acids, are hyperstable and, following experimental optimization, bind their targets with nanomolar to picomolar affinities. We succeeded in solving crystal structures of five of the binder-target complexes, and all five closely match the corresponding computational design models. Experimental data on nearly half a million computational designs and hundreds of thousands of point mutants provide detailed feedback on the strengths and limitations of the method and of our current understanding of protein-protein interactions, and should guide improvements of both. Our approach enables the targeted design of binders to sites of interest on a wide variety of proteins for therapeutic and diagnostic applications.

Oral Immunization of Mice with Cell Extracts from Recombinant Lactococcus lactis Expressing SARS-CoV-2 Spike Protein

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread all over the world and became a pandemic that named coronavirus disease-2019 (COVID-19). At present, several intramuscular vaccines have been successfully developed and mass vaccination has progressed in many countries. The aim of the study is to develop and examine an oral vaccine against COVID-19 with recombinant Lactococcus lactis IL1403, a strain of lactic acid bacteria, expressing SARS-CoV-2 spike (S) protein receptor-binding domain (RBD) S1 subunit as an immunizing antigen. PBS or cell extracts from recombinant L. lactis were orally administered into mice (control VS treatment), and formation of antigen-specific antibodies and changes in the gut microbiome were analyzed. Intracellular antigen was detected, but its secretion was not successful. After immunization, antigen-specific serum IgG and fecal IgA levels were 1.5-fold (P = 0.002) and 1.4-fold (P = 0.016) higher in the immunized mice (treatment) than control, respectively. Gut microbiome profiles were clearly separated between the two groups when analyzed for beta diversity with overall similarity. At the genus level, while Coprococcus (P = 0.036) and unclassified genus of Ruminococcaceae (P = 0.037) in treatment were more abundant than control, rc4-4 (P = 0.013) and Stenotrophomonas (P = 0.021) were less abundant. Our results indicate that cell extract containing SARS-CoV-2 antigen can induce mice to produce antigen-specific antibodies without overall changes in the gut microbiome. This strategy may be useful for the development of other oral viral vaccines.

Heterologous prime-boost vaccination based on Polymorphic protein D protects against intravaginal Chlamydia trachomatis infection in mice

The control of the worldwide spread of sexually transmitted Chlamydia trachomatis (Ct) infection urgently demands the development of a preventive vaccine. In this work, we designed a vaccine based on a fragment of polymorphic protein D (FPmpD) that proved to be immunogenic enough to generate a robust systemic and mucosal IgG humoral immune response in two strains of mice. We used a heterologous prime-boost strategy, including simultaneous systemic and mucosal administration routes. The high titers of anti-PmpD antibodies elicited by this immunization scheme did not affect murine fertility. We tested the vaccine in a mouse model of Ct intravaginal infection. Anti-PmpD antibodies displayed potent neutralizing activity in vitro and protective effects in uterine tissues in vivo. Notably, the humoral immune response of PmpD-vaccinated mice was faster and stronger than the primary immune response of non-vaccinated mice when exposed to Ct. FPmpD-based vaccine effectively reduced Ct shedding into cervicovaginal fluids, bacterial burden at the genitourinary tract, and overall infectivity. Hence, the FPmpD-based vaccine might constitute an efficient tool to protect against Ct intravaginal infection and decrease the infection spreading.

An Integrated Algorithm for Designing Oligodeoxynucleotides for Gene Synthesis

The design and construction of large synthetic genes can be a slow, difficult, and confusing process, especially in the key step of oligodeoxynucleotide design. Herein we present an integrated algorithm to design oligonucleotide sets for gene synthesis by both ligase chain reaction and polymerase chain reaction. It offers much flexibility with no constraints on the gene to be synthesized. Firstly, it divides the long-input DNA sequence by a greedy algorithm based on the length of the oligodeoxynucleotide overlap region. Secondly, it tunes the length of the overlap region iteratively in an attempt to minimize the melting temperature variance of overlap. Thirdly, dynamic programming algorithm is used to achieve the uniform melting temperature of the oligodeoxynucleotide overlaps. Finally, the oligodeoxynucleotides with homologous melting temperature necessary for ligase chain reaction-based or two-step assembly PCR-based synthesis of the desired gene are outputted.