CoLiDe: Combinatorial Library Design tool for probing protein sequence space

GGAssembler: Precise and economical design and synthesis of combinatorial mutation libraries

Golden Gate assembly (GGA) can seamlessly generate full-length genes from DNA fragments. In principle, GGA could be used to design combinatorial mutation libraries for protein engineering, but creating accurate, complex, and cost-effective libraries has been challenging. We present GGAssembler, a graph-theoretical method for economical design of DNA fragments that assemble a combinatorial library that encodes any desired diversity. We used GGAssembler for one-pot in vitro assembly of camelid antibody libraries comprising >105 variants with DNA costs <0.007$ per variant and dropping significantly with increased library complexity. >93% of the desired variants were present in the assembly product and >99% were represented within the expected order of magnitude as verified by deep sequencing. The GGAssembler workflow is, therefore, an accurate approach for generating complex variant libraries that may drastically reduce costs and accelerate discovery and optimization of antibodies, enzymes and other proteins. The workflow is accessible through a Google Colab notebook at https://github.com/Fleishman-Lab/GGAssembler.

DeCOIL: Optimization of Degenerate Codon Libraries for Machine Learning-Assisted Protein Engineering

With advances in machine learning (ML)-assisted protein engineering, models based on data, biophysics, and natural evolution are being used to propose informed libraries of protein variants to explore. Synthesizing these libraries for experimental screens is a major bottleneck, as the cost of obtaining large numbers of exact gene sequences is often prohibitive. Degenerate codon (DC) libraries are a cost-effective alternative for generating combinatorial mutagenesis libraries where mutations are targeted to a handful of amino acid sites. However, existing computational methods to optimize DC libraries to include desired protein variants are not well suited to design libraries for ML-assisted protein engineering. To address these drawbacks, we present DEgenerate Codon Optimization for Informed Libraries (DeCOIL), a generalized method that directly optimizes DC libraries to be useful for protein engineering: to sample protein variants that are likely to have both high fitness and high diversity in the sequence search space. Using computational simulations and wet-lab experiments, we demonstrate that DeCOIL is effective across two specific case studies, with the potential to be applied to many other use cases. DeCOIL offers several advantages over existing methods, as it is direct, easy to use, generalizable, and scalable. With accompanying software (https://github.com/jsunn-y/DeCOIL), DeCOIL can be readily implemented to generate desired informed libraries.

Building the SynBio community in the Czech Republic from the bottom up: You get what you give

Given its highly innovative character and potential socioeconomic impact, Synthetic Biology is often ranked among prominent research areas and national research priorities in developed countries. The global evolution of this field is proceeding by leaps and bounds but its development at the level of individual states varies widely. Despite their current satisfactory economic status, the majority of 13, mostly post-communist, countries that entered the European Union family in and after 2004 (EU13) have long overlooked the blossoming of Synthetic Biology. Their prioritized lines of research have been directed elsewhere or "Synthetic Biology" did not become a widely accepted term to encompass their bioengineering and biotechnology domains. The Czech Republic is not an exception. The local SynBio mycelium already exists but is mainly built bottom-up through the activities of several academic labs, iGEM teams, and spin-off companies. In this article, we tell their individual stories and summarize the prerequisites that allowed their emergence in the Czech academic and business environment. In addition, we provide the reader with a brief overview of laboratories, research hubs, and companies that perform biotechnology and bioengineering-oriented research and that may be included in a notional "shadow SynBio community" but have not yet adopted Synthetic Biology as a unifying term for their ventures. We also map the current hindrances for a broader expansion of Synthetic Biology in the Czech Republic and suggest possible steps that should lead to the maturity of this fascinating research field in our country.

Modern and prebiotic amino acids support distinct structural profiles in proteins

The earliest proteins had to rely on amino acids available on early Earth before the biosynthetic pathways for more complex amino acids evolved. In extant proteins, a significant fraction of the 'late' amino acids (such as Arg, Lys, His, Cys, Trp and Tyr) belong to essential catalytic and structure-stabilizing residues. How (or if) early proteins could sustain an early biosphere has been a major puzzle. Here, we analysed two combinatorial protein libraries representing proxies of the available sequence space at two different evolutionary stages. The first is composed of the entire alphabet of 20 amino acids while the second one consists of only 10 residues (ASDGLIPTEV) representing a consensus view of plausibly available amino acids through prebiotic chemistry. We show that compact conformations resistant to proteolysis are surprisingly similarly abundant in both libraries. In addition, the early alphabet proteins are inherently more soluble and refoldable, independent of the general Hsp70 chaperone activity. By contrast, chaperones significantly increase the otherwise poor solubility of the modern alphabet proteins suggesting their coevolution with the amino acid repertoire. Our work indicates that while both early and modern amino acids are predisposed to supporting protein structure, they do so with different biophysical properties and via different mechanisms.

Sequencing the Origins of Life

One goal of origins of life research is to understand how primitive informational and catalytic biopolymers emerged and evolved. Recently, a number of sequencing techniques have been applied to analysis of replicating and evolving primitive biopolymer systems, providing a sequence-specific and high-resolution view of primitive chemical processes. Here, we review application of sequencing techniques to analysis of synthetic and primitive nucleic acids and polypeptides. This includes next-generation sequencing of primitive polymerization and evolution processes, followed by discussion of other novel biochemical techniques that could contribute to sequence analysis of primitive biopolymer driven chemical systems. Further application of sequencing to origins of life research, perhaps as a life detection technology, could provide insight into the origin and evolution of informational and catalytic biopolymers on early Earth or elsewhere.