De novo assembly and next-generation sequencing to analyse full-length gene variants from codon-barcoded libraries

Perspectives on improving crop Rubisco by directed evolution

Rubisco catalyses the entry of almost all CO2 into the biosphere and is often the rate-limiting step in plant photosynthesis and growth. Its notoriety as the most abundant protein on Earth stems from the slow and error-prone catalytic properties that require plants, cyanobacteria, algae and photosynthetic bacteria to produce it in high amounts. Efforts to improve the CO2-fixing properties of plant Rubisco has been spurred on by the discovery of more effective isoforms in some algae with the potential to significantly improve crop productivity. Incompatibilities between the protein folding machinery of leaf and algae chloroplasts have, so far, prevented efforts to transplant these more effective Rubisco variants into plants. There is therefore increasing interest in improving Rubisco catalysis by directed (laboratory) evolution. Here we review the advances being made in, and the ongoing challenges with, improving the solubility and/or carboxylation activity of differing non-plant Rubisco lineages. We provide perspectives on new opportunities for the directed evolution of crop Rubiscos and the existing plant transformation capabilities available to evaluate the extent to which Rubisco activity improvements can benefit agricultural productivity.

Deep mutational scan of a drug efflux pump reveals its structure-function landscape

Drug efflux is a common resistance mechanism found in bacteria and cancer cells, but studies providing comprehensive functional insights are scarce. In this study, we performed deep mutational scanning (DMS) on the bacterial ABC transporter EfrCD to determine the drug efflux activity profile of more than 1,430 single variants. These systematic measurements revealed that the introduction of negative charges at different locations within the large substrate binding pocket results in strongly increased efflux activity toward positively charged ethidium, whereas additional aromatic residues did not display the same effect. Data analysis in the context of an inward-facing cryogenic electron microscopy structure of EfrCD uncovered a high-affinity binding site, which releases bound drugs through a peristaltic transport mechanism as the transporter transits to its outward-facing conformation. Finally, we identified substitutions resulting in rapid Hoechst influx without affecting the efflux activity for ethidium and daunorubicin. Hence, single mutations can convert EfrCD into a drug-specific ABC importer.

Three-dimensional structure-guided evolution of a ribosome with tethered subunits

RNA-based macromolecular machines, such as the ribosome, have functional parts reliant on structural interactions spanning sequence-distant regions. These features limit evolutionary exploration of mutant libraries and confound three-dimensional structure-guided design. To address these challenges, we describe Evolink (evolution and linkage), a method that enables high-throughput evolution of sequence-distant regions in large macromolecular machines, and library design guided by computational RNA modeling to enable exploration of structurally stable designs. Using Evolink, we evolved a tethered ribosome with a 58% increased activity in orthogonal protein translation and a 97% improvement in doubling times in SQ171 cells compared to a previously developed tethered ribosome, and reveal new permissible sequences in a pair of ribosomal helices with previously explored biological function. The Evolink approach may enable enhanced engineering of macromolecular machines for new and improved functions for synthetic biology.

Purification of multiplex oligonucleotide libraries by synthesis and selection

Complex oligonucleotide (oligo) libraries are essential materials for diverse applications in synthetic biology, pharmaceutical production, nanotechnology and DNA-based data storage. However, the error rates in synthesizing complex oligo libraries can be substantial, leading to increment in cost and labor for the applications. As most synthesis errors arise from faulty insertions and deletions, we developed a length-based method with single-base resolution for purification of complex libraries containing oligos of identical or different lengths. Our method-purification of multiplex oligonucleotide libraries by synthesis and selection-can be performed either step-by-step manually or using a next-generation sequencer. When applied to a digital data-encoded library containing oligos of identical length, the method increased the purity of full-length oligos from 83% to 97%. We also show that libraries encoding the complementarity-determining region H3 with three different lengths (with an empirically achieved diversity >10⁶) can be simultaneously purified in one pot, increasing the in-frame oligo fraction from 49.6% to 83.5%.

Bridging non-overlapping reads illuminates high-order epistasis between distal protein sites in a GPCR

Epistasis emerges when the effects of an amino acid depend on the identities of interacting residues. This phenomenon shapes fitness landscapes, which have the power to reveal evolutionary paths and inform evolution of desired functions. However, there is a need for easily implemented, high-throughput methods to capture epistasis particularly at distal sites. Here, we combine deep mutational scanning (DMS) with a straightforward data processing step to bridge reads in distal sites within genes (BRIDGE). We use BRIDGE, which matches non-overlapping reads to their cognate templates, to uncover prevalent epistasis within the binding pocket of a human G protein-coupled receptor (GPCR) yielding variants with 4-fold greater affinity to a target ligand. The greatest functional improvements in our screen result from distal substitutions and substitutions that are deleterious alone. Our results corroborate findings of mutational tolerance in GPCRs, even in conserved motifs, but reveal inherent constraints restricting tolerated substitutions due to epistasis.

Epistasis effects among amino acids at distal sites within binding pockets can have important impacts on protein fitness landscapes. Here the authors present BRIDGE, which matches non-overlapping sequence reads with their cognate DNA templates.

Advancing Personalized Medicine Through the Application of Whole Exome Sequencing and Big Data Analytics

There is a growing attention toward personalized medicine. This is led by a fundamental shift from the ‘one size fits all’ paradigm for treatment of patients with conditions or predisposition to diseases, to one that embraces novel approaches, such as tailored target therapies, to achieve the best possible outcomes. Driven by these, several national and international genome projects have been initiated to reap the benefits of personalized medicine. Exome and targeted sequencing provide a balance between cost and benefit, in contrast to whole genome sequencing (WGS). Whole exome sequencing (WES) targets approximately 3% of the whole genome, which is the basis for protein-coding genes. Nonetheless, it has the characteristics of big data in large deployment. Herein, the application of WES and its relevance in advancing personalized medicine is reviewed. WES is mapped to Big Data “10 Vs” and the resulting challenges discussed. Application of existing biological databases and bioinformatics tools to address the bottleneck in data processing and analysis are presented, including the need for new generation big data analytics for the multi-omics challenges of personalized medicine. This includes the incorporation of artificial intelligence (AI) in the clinical utility landscape of genomic information, and future consideration to create a new frontier toward advancing the field of personalized medicine.

Deep sequencing methods for protein engineering and design

The advent of next-generation sequencing (NGS) has revolutionized protein science, and the development of complementary methods enabling NGS-driven protein engineering have followed. In general, these experiments address the functional consequences of thousands of protein variants in a massively parallel manner using genotype-phenotype linked high-throughput functional screens followed by DNA counting via deep sequencing. We highlight the use of information rich datasets to engineer protein molecular recognition. Examples include the creation of multiple dual-affinity Fabs targeting structurally dissimilar epitopes and engineering of a broad germline-targeted anti-HIV-1 immunogen. Additionally, we highlight the generation of enzyme fitness landscapes for conducting fundamental studies of protein behavior and evolution. We conclude with discussion of technological advances.