Coupling a Live Cell Directed Evolution Assay with Coevolutionary Landscapes to Engineer an Improved Fluorescent Rhodopsin Chloride Sensor

Illuminating anions in biology with genetically encoded fluorescent biosensors

Anions are critical to all life forms. Anions can be absorbed as nutrients or biosynthesized. Anions shape a spectrum of fundamental biological processes at the organismal, cellular, and subcellular scales. Genetically encoded fluorescent biosensors can capture anions in action across time and space dimensions with microscopy. The firsts of such technologies were reported more than 20 years for monoatomic chloride and polyatomic cAMP anions. However, the recent boom of anion biosensors illuminates the unknowns and opportunities that remain for toolmakers and end users to meet across the aisle to spur innovations in biosensor designs and applications for discovery anion biology. In this review, we will canvas progress made over the last three years for biologically relevant anions that are classified as halides, oxyanions, carboxylates, and nucleotides.

State-of-the-art in engineering small molecule biosensors and their applications in metabolic engineering

Genetically encoded biosensors are crucial for enhancing our understanding of how molecules regulate biological systems. Small molecule biosensors, in particular, help us understand the interaction between chemicals and biological processes. They also accelerate metabolic engineering by increasing screening throughput and eliminating the need for sample preparation through traditional chemical analysis. Additionally, they offer significantly higher spatial and temporal resolution in cellular analyte measurements. In this review, we discuss recent progress in in vivo biosensors and control systems-biosensor-based controllers-for metabolic engineering. We also specifically explore protein-based biosensors that utilize less commonly exploited signaling mechanisms, such as protein stability and induced degradation, compared to more prevalent transcription factor and allosteric regulation mechanism. We propose that these lesser-used mechanisms will be significant for engineering eukaryotic systems and slower-growing prokaryotic systems where protein turnover may facilitate more rapid and reliable measurement and regulation of the current cellular state. Lastly, we emphasize the utilization of cutting-edge and state-of-the-art techniques in the development of protein-based biosensors, achieved through rational design, directed evolution, and collaborative approaches.

Unlocking chloride sensing in the red at physiological pH with a fluorescent rhodopsin-based host

Chloride is a vital ion for all forms of life. Protein-based fluorescent biosensors can enable researchers to visualize chloride in cells but remain underdeveloped. Here, we demonstrate how a single point mutation in an engineered microbial rhodopsin results in ChloRED-1-CFP. This membrane-bound host is a far-red emitting, ratiometric sensor that provides a reversible readout of chloride in live bacteria at physiological pH, setting the stage to investigate the roles of chloride in diverse biological contexts.

Rational Design of the β-Bulge Gate in a Green Fluorescent Protein Accelerates the Kinetics of Sulfate Sensing

Detection of anions in complex aqueous media is a fundamental challenge with practical utility that can be addressed by supramolecular chemistry. Biomolecular hosts such as proteins can be used and adapted as an alternative to synthetic hosts. Here, we report how the mutagenesis of the β-bulge residues (D137 and W138) in mNeonGreen, a bright, monomeric fluorescent protein, unlocks and tunes the anion preference at physiological pH for sulfate, resulting in the turn-off sensor SulfOFF-1. This unprecedented sensing arises from an enhancement in the kinetics of binding, largely driven by position 138. In line with these data, molecular dynamics (MD) simulations capture how the coordinated entry and gating of sulfate into the β-barrel is eliminated upon mutagenesis to facilitate binding and fluorescence quenching.

Latent generative landscapes as maps of functional diversity in protein sequence space

Variational autoencoders are unsupervised learning models with generative capabilities, when applied to protein data, they classify sequences by phylogeny and generate de novo sequences which preserve statistical properties of protein composition. While previous studies focus on clustering and generative features, here, we evaluate the underlying latent manifold in which sequence information is embedded. To investigate properties of the latent manifold, we utilize direct coupling analysis and a Potts Hamiltonian model to construct a latent generative landscape. We showcase how this landscape captures phylogenetic groupings, functional and fitness properties of several systems including Globins, β-lactamases, ion channels, and transcription factors. We provide support on how the landscape helps us understand the effects of sequence variability observed in experimental data and provides insights on directed and natural protein evolution. We propose that combining generative properties and functional predictive power of variational autoencoders and coevolutionary analysis could be beneficial in applications for protein engineering and design.

Efficient polyethylene terephthalate degradation at moderate temperature: a protein engineering study of LC-cutinase highlights the key role of residue 243

Enzymatic degradation of poly(ethylene terephthalate) (PET) is becoming a reality because of the identification of novel PET-hydrolysing enzymes (PHEs) and the engineering of evolved enzyme variants. Here, improved variants of leaf-branch compost cutinase (LCC), a thermostable enzyme isolated by a metagenomic approach, were generated by a semi-rational protein engineering approach. Starting from a deleted LCC form lacking the secretion signal (ΔLCC), single and double variants possessing a higher activity on PET were isolated. The single-point F243T ΔLCC variant partially (~ 67%) depolymerized amorphous PET film producing ~ 21.9 mm of products after 27 h of reaction at 72 °C. The S101N/F243T ΔLCC double variant reached a further increase in activity on PET. Notably, for both single and double variants the highest conversion yield was obtained at 55 °C. Kinetics studies and molecular dynamics simulations support that a slight decreased affinity for PET is responsible for the superior degradation performance of the S101N/F243T variant and that this stems from a slightly higher flexibility of the active site region close to position 243. Furthermore, our findings question the need for a high reaction temperature for PET degradation, at least for LCC: at ≥ 70 °C, the conversion of amorphous PET into a more crystalline polymer, resistant to enzymatic hydrolysis, is favoured. The evolved S101N/F243T ΔLCC variant is able to depolymerize fully 1.3 g of untreated postconsumer PET waste in ≤ 3 days at 55 °C (using 1.25 mg of enzyme only), this making PET enzymatic degradation by engineering LCC a more ecofriendly and sustainable process.

Discovery of a monomeric green fluorescent protein sensor for chloride by structure-guided bioinformatics

Chloride is an essential anion for all forms of life. Beyond electrolyte balance, an increasing body of evidence points to new roles for chloride in normal physiology and disease. Over the last two decades, this understanding has been advanced by chloride-sensitive fluorescent proteins for imaging applications in living cells. To our surprise, these sensors have primarily been engineered from the green fluorescent protein (GFP) found in the jellyfish Aequorea victoria. However, the GFP family has a rich sequence space that could already encode for new sensors with desired properties, thereby minimizing protein engineering efforts and accelerating biological applications. To efficiently sample this space, we present and validate a stepwise bioinformatics strategy focused first on the chloride binding pocket and second on a monomeric oligomerization state. Using this, we identified GFPxm163 from GFPxm found in the jellyfish Aequorea macrodactyla. In vitro characterization shows that the binding of chloride as well as bromide, iodide, and nitrate rapidly tunes the ground state chromophore equilibrium from the phenolate to the phenol state generating a pH-dependent, turn-off fluorescence response. Furthermore, live-cell fluorescence microscopy reveals that GFPxm163 provides a reversible, yet indirect readout of chloride transport via iodide exchange. With this demonstration, we anticipate that the pairing of bioinformatics with protein engineering methods will provide an efficient methodology to discover and design new chloride-sensitive fluorescent proteins for cellular applications.