Computation-guided optimization of split protein systems.

Splitting bioactive proteins into conditionally reconstituting fragments is a powerful strategy for building tools to study and control biological systems. However, split proteins often exhibit a high propensity to reconstitute, even without the conditional trigger, limiting their utility. Current approaches for tuning reconstitution propensity are laborious, context-specific or often ineffective. Here, we report a computational design strategy grounded in fundamental protein biophysics to guide experimental evaluation of a sparse set of mutants to identify an optimal functional window. We hypothesized that testing a limited set of mutants would direct subsequent mutagenesis efforts by predicting desirable mutant combinations from a vast mutational landscape. This strategy varies the degree of interfacial destabilization while preserving stability and catalytic activity. We validate our method by solving two distinct split protein design challenges, generating both design and mechanistic insights. This new technology will streamline the generation and use of split protein systems for diverse applications.

Functional plasticity and evolutionary adaptation of allosteric regulation.

Allostery is a fundamental regulatory mechanism of protein function. Despite notable advances, understanding the molecular determinants of allostery remains an elusive goal. Our current knowledge of allostery is principally shaped by a structure-centric view, which makes it difficult to understand the decentralized character of allostery. We present a function-centric approach using deep mutational scanning to elucidate the molecular basis and underlying functional landscape of allostery. We show that allosteric signaling exhibits a high degree of functional plasticity and redundancy through myriad mutational pathways. Residues critical for allosteric signaling are surprisingly poorly conserved while those required for structural integrity are highly conserved, suggesting evolutionary pressure to preserve fold over function. Our results suggest multiple solutions to the thermodynamic conditions of cooperativity, in contrast to the common view of a finely tuned allosteric residue network maintained under selection.

Rugged fitness landscapes minimize promiscuity in the evolution of transcriptional repressors.

How a protein's function influences the shape of its fitness landscape, smooth or rugged, is a fundamental question in evolutionary biochemistry. Smooth landscapes arise when incremental mutational steps lead to a progressive change in function, as commonly seen in enzymes and binding proteins. On the other hand, rugged landscapes are poorly understood because of the inherent unpredictability of how sequence changes affect function. Here, we experimentally characterize the entire sequence phylogeny, comprising 1,158 extant and ancestral sequences, of the DNA-binding domain (DBD) of the LacI/GalR transcriptional repressor family. Our analysis revealed an extremely rugged landscape with rapid switching of specificity, even between adjacent nodes. Further, the ruggedness arises due to the necessity of the repressor to simultaneously evolve specificity for asymmetric operators and disfavors potentially adverse regulatory crosstalk. Our study provides fundamental insight into evolutionary, molecular, and biophysical rules of genetic regulation through the lens of fitness landscapes.

Deep metagenomic mining reveals bacteriophage sequence motifs driving host specificity.

Bacteriophages can adapt to new hosts by altering sequence motifs through recombination or convergent evolution. Where such motifs exist and what fitness advantage they confer remains largely unknown. We report a new method, Bacteriophage Library Informed Sequence Scoring (BLISS), to discover sequence motifs in metagenomic datasets governing phage activity. BLISS uses experimental deep mutational scanning data to create sequence profiles to enable deep mining of metagenomes for functional motifs which are otherwise invisible to searches. We experimentally tested 10,073 BLISS-derived sequence motifs for the receptor-binding protein of the T7 phage. The screen revealed hundreds of T7 variants with novel host specificity with functional motifs sourced from distant families besides other major phyla. Position, substitution and location preferences on T7 dictated different specificities. To demonstrate therapeutic utility, we engineered highly active T7 variants against urinary tract pathogens. BLISS is a powerful tool to unlock the functional potential encoded in phage metagenomes.

Mapping the functional landscape of the receptor binding domain of T7 bacteriophage by deep mutational scanning.

The interaction between a bacteriophage and its host is mediated by the phage's receptor binding protein (RBP). Despite its fundamental role in governing phage activity and host range, molecular rules of RBP function remain a mystery. Here, we systematically dissect the functional role of every residue in the tip domain of T7 phage RBP (1660 variants) by developing a high-throughput, locus-specific, phage engineering method. This rich dataset allowed us to cross compare functional profiles across hosts to precisely identify regions of functional importance, many of which were previously unknown. Substitution patterns showed host-specific differences in position and physicochemical properties of mutations, revealing molecular adaptation to individual hosts. We discovered gain-of-function variants against resistant hosts and host-constricting variants that eliminated certain hosts. To demonstrate therapeutic utility, we engineered highly active T7 variants against a urinary tract pathogen. Our approach presents a generalized framework for characterizing sequence-function relationships in many phage-bacterial systems.

Bacteria can cause diseases, but they also battle their own microscopic enemies: a group of viruses known as bacteriophages. For instance, the T7 bacteriophage preys on various strains of Escherichia coli, a type of bacteria often found in the human gut. While many E. coli strains are inoffensive or even beneficial to human health, some can be deadly. Finding a way to kill harmful strains while sparing the helpful ones would be a helpful addition to the medicine toolkit. Bacteriophages identify and interact with their specific target through a structure known as the receptor binding protein, or RBP. However, it is still unclear exactly how RBP helps the viruses recognize which type of bacteria to infect. Here, Huss et al. set to map out and modify this structure in T7 bacteriophage so the virus is more efficient and specific about which strain of E. coli it kills. First, the role of each building block in the tip of RBP was meticulously dissected; this generated the knowledge required to genetically engineer a large number of different T7 bacteriophages, each with a slightly variation in their RBP. These viruses were then exposed to various strains of bacteria. Monitoring the bacteriophages that survived and multiplied the most after infecting different strains of E. coli revealed which RBP building blocks are important for efficiency and specificity. This was then confirmed by engineering highly active T7 bacteriophage variants against an E. coli strain that causes urinary tract infections. These findings demonstrate that even small changes to the bacteriophages can make a big difference to their ability to infect their preys. The approaches developed by Huss et al. help to understand exactly how the RBP allows a virus to infect a specific type of bacteria; this could one day pave the way for new therapies that harness those viruses to fight increasingly resistant bacterial infections.