Directed evolution combined with synthetic biology strategies expedite semi-rational engineering of genes and genomes

Revolutionizing enzyme engineering through artificial intelligence and machine learning

The combinatorial space of an enzyme sequence has astronomical possibilities and exploring it with contemporary experimental techniques is arduous and often ineffective. Multi-target objectives such as concomitantly achieving improved selectivity, solubility and activity of an enzyme have narrow plausibility under approaches of restricted mutagenesis and combinatorial search. Traditional enzyme engineering approaches have a limited scope for complex optimization due to the requirement of a priori knowledge or experimental burden of screening huge protein libraries. The recent surge in high-throughput experimental methods including Next Generation Sequencing and automated screening has flooded the field of molecular biology with big-data, which requires us to re-think our concurrent approaches towards enzyme engineering. Artificial Intelligence (AI) and Machine Learning (ML) have great potential to revolutionize smart enzyme engineering without the explicit need for a complete understanding of the underlying molecular system. Here, we portray the role and position of AI techniques in the field of enzyme engineering along with their scope and limitations. In addition, we explain how the traditional approaches of directed evolution and rational design can be extended through AI tools. Recent successful examples of AI-assisted enzyme engineering projects and their deviation from traditional approaches are highlighted. A comprehensive picture of current challenges and future avenues for AI in enzyme engineering are also discussed.

Complete genome sequence of the Clostridium difficile LCL126

Clostridium difficile (C. difficile) is a kind of obligate anaerobic gram-positive Bacillus related with intestinal diseases and antibiotic treatment. In present study, the C. difficile genome was studied employing met genomic technology. Genome sequencing identified C. difficile LCL126 has total size of 4,301,949 bp with a 27.97% of GC content. Specifically, 4119 predicted coding genes, 188 repeat sequences, 13 prophages and 8 gene islands were detected. Additionally, gene function analysis aspect of the function annotation, effector, and virulence were concluded that total of 3367 cluster of orthologous groups of proteins genes and classified into 24 categories, while the most outstanding class was metabolic process (1533) and catalytic activity (1498). The carbohydrate-active enzymes have been detected 127 genes, pathogenicity analysis revealed that 133 reduced and 22 increased virulence (hypervirulence) genes, while 54 unaffected and 10 loss of pathogenicity genes were found. Furthermore, perform the visualization and methylation expression were revealed that the dominant types comprised m4C, m5C, and m6C with the number of 6989, 36,666, and 3534, respectively. Overall, whole genome sequence information of C. difficile LCL126 was obtained and functional prediction was revealed its possible toxicological potential genes existence.

Optimizing Calcium Detection Methods in Animal Systems: A Sandbox for Synthetic Biology

Since the 1970s, the emergence and expansion of novel methods for calcium ion (Ca2+) detection have found diverse applications in vitro and in vivo across a series of model animal systems. Matched with advances in fluorescence imaging techniques, the improvements in the functional range and stability of various calcium indicators have significantly enhanced more accurate study of intracellular Ca2+ dynamics and its effects on cell signaling, growth, differentiation, and regulation. Nonetheless, the current limitations broadly presented by organic calcium dyes, genetically encoded calcium indicators, and calcium-responsive nanoparticles suggest a potential path toward more rapid optimization by taking advantage of a synthetic biology approach. This engineering-oriented discipline applies principles of modularity and standardization to redesign and interrogate endogenous biological systems. This review will elucidate how novel synthetic biology technologies constructed for eukaryotic systems can offer a promising toolkit for interfacing with calcium signaling and overcoming barriers in order to accelerate the process of Ca2+ detection optimization.

Regulatory non-coding sRNAs in bacterial metabolic pathway engineering

Non-coding RNAs (ncRNAs) are versatile and powerful controllers of gene expression that have been increasingly linked to cellular metabolism and phenotype. In bacteria, identified and characterized ncRNAs range from trans-acting, multi-target small non-coding RNAs to dynamic, cis-encoded regulatory untranslated regions and riboswitches. These native regulators have inspired the design and construction of many synthetic RNA devices. In this work, we review the design, characterization, and impact of ncRNAs in engineering both native and exogenous metabolic pathways in bacteria. We also consider the opportunities afforded by recent high-throughput approaches for characterizing sRNA regulators and their corresponding networks to showcase their potential applications and impact in engineering bacterial metabolism.

DNA Assembly with the DATEL Method

Simple and reliable DNA assembly methods have become a critical technique in synthetic biology. Here, we present a protocol of the recently developed DATEL (scarless and sequence-independent DNA assembly method using thermostable exonuclease and ligase) method for the construction of genetic circuits and biological pathways from multiple DNA parts in one tube. DATEL is expected to be an applicable choice for both manual and automated high-throughput assembly of DNA fragments, which will greatly facilitate the rapid progress of synthetic biology and metabolic engineering.

Scarless assembly of unphosphorylated DNA fragments with a simplified DATEL method

Efficient assembly of multiple DNA fragments is a pivotal technology for synthetic biology. A scarless and sequence-independent DNA assembly method (DATEL) using thermal exonucleases has been developed recently. Here, we present a simplified DATEL (sDATEL) for efficient assembly of unphosphorylated DNA fragments with low cost. The sDATEL method is only dependent on Taq DNA polymerase and Taq DNA ligase. After optimizing the committed parameters of the reaction system such as pH and the concentration of Mg²⁺ and NAD+, the assembly efficiency was increased by 32-fold. To further improve the assembly capacity, the number of thermal cycles was optimized, resulting in successful assembly 4 unphosphorylated DNA fragments with an accuracy of 75%. sDATEL could be a desirable method for routine manual and automated assembly.

Diversification and enrichment of clinical biomaterials inspired by Darwinian evolution

Regenerative medicine and biomaterials design are driven by biomimicry. There is the essential requirement to emulate human cell, tissue, organ and physiological complexity to ensure long-lasting clinical success. Biomimicry projects for biomaterials innovation can be re-invigorated with evolutionary insights and perspectives, since Darwinian evolution is the original dynamic process for biological organisation and complexity. Many existing human inspired regenerative biomaterials (defined as a nature generated, nature derived and nature mimicking structure, produced within a biological system, which can deputise for, or replace human tissues for which it closely matches) are without important elements of biological complexity such as, hierarchy and autonomous actions. It is possible to engineer these essential elements into clinical biomaterials via bioinspired implementation of concepts, processes and mechanisms played out during Darwinian evolution; mechanisms such as, directed, computational, accelerated evolutions and artificial selection contrived in the laboratory. These dynamos for innovation can be used during biomaterials fabrication, but also to choose optimal designs in the regeneration process. Further evolutionary information can help at the design stage; gleaned from the historical evolution of material adaptations compared across phylogenies to changes in their environment and habitats. Taken together, harnessing evolutionary mechanisms and evolutionary pathways, leading to ideal adaptations, will eventually provide a new class of Darwinian and evolutionary biomaterials. This will provide bioengineers with a more diversified and more efficient innovation tool for biomaterial design, synthesis and function than currently achieved with synthetic materials chemistry programmes and rational based materials design approach, which require reasoned logic. It will also inject further creativity, diversity and richness into the biomedical technologies that we make. All of which are based on biological principles. Such evolution-inspired biomaterials have the potential to generate innovative solutions, which match with existing bioengineering problems, in vital areas of clinical materials translation that include tissue engineering, gene delivery, drug delivery, immunity modulation, and scar-less wound healing.

STATEMENT OF SIGNIFICANCE

Evolution by natural selection is a powerful generator of innovations in molecular, materials and structures. Man has influenced evolution for thousands of years, to create new breeds of farm animals and crop plants, but now molecular and materials can be molded in the same way. Biological molecules and simple structures can be evolved, literally in the laboratory. Furthermore, they are re-designed via lessons learnt from evolutionary history. Through a 3-step process to (1) create variants in material building blocks, (2) screen the variants with beneficial traits/properties and (3) select and support their self-assembly into usable materials, improvements in design and performance can emerge. By introducing biological molecules and small organisms into this process, it is possible to make increasingly diversified, sophisticated and clinically relevant materials for multiple roles in biomedicine.

Production of novel NaN3-resistant creatine amidinohydrolase in recombinant Escherichia coli

Creatinase (creatine amidinohydrolase), an important medical enzyme, has been used for clinical diagnosis of renal function because of its high substrate specificity. Recently, we successfully cloned a NaN3-resistant creatinase encoding gene from Arthrobacter nicotianae. By optimizing the cultivation process, we realized its high-level expression in Escherichia coli. In this addendum, production of this NaN3-resistant creatinase in E. coli and future research were further discussed.

Combinatorial Evolution of Enzymes and Synthetic Pathways Using One-Step PCR

DNA engineering is the fundamental motive driving the rapid development of modern biotechnology. Here, we present a versatile evolution method termed "rapidly efficient combinatorial oligonucleotides for directed evolution" (RECODE) for rapidly introducing multiple combinatorial mutations to the target DNA by combined action of a thermostable high-fidelity DNA polymerase and a thermostable DNA Ligase in one reaction system. By applying this method, we rapidly constructed a variant library of the rpoS promoters (with activity of 8-460%), generated a novel heparinase from the highly specific leech hyaluronidase (with more than 30 mutant residues) and optimized the heme biosynthetic pathway by combinatorial evolution of regulatory elements and pathway enzymes (2500 ± 120 mg L(-1) with 20-fold increase). The simple RECODE method enabled researchers the unparalleled ability to efficiently create diverse mutant libraries for rapid evolution and optimization of enzymes and synthetic pathways.