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To create bacterial transcription "circuits" for biotechnology, one approach is to recombine natural transcription factors, promoters, and operators. Additional novel functions can be engineered from existing transcription factors such as the E. coli AraC transcriptional activator, for which binding to DNA is modulated by binding L-arabinose. Here, we engineered chimeric AraC/XylS transcription activators that recognized ara DNA binding sites and responded to varied effector ligands. The first step, identifying domain boundaries in the natural homologs, was challenging because (i) no full-length, dimeric structures were available and (ii) extremely low sequence identities (≤10%) among homologs precluded traditional assemblies of sequence alignments. Thus, to identify domains, we built and aligned structural models of the natural proteins. The designed chimeric activators were assessed for function, which was then further improved by random mutagenesis. Several mutational variants were identified for an XylS•AraC chimera that responded to benzoate; two enhanced activation to near that of wild-type AraC. For an RhaR•AraC chimera, a variant with five additional substitutions enabled transcriptional activation in response to rhamnose. These five changes were dispersed across the protein structure, and combinatorial experiments testing subsets of substitutions showed significant non-additivity. Combined, the structure modeling and epistasis suggest that the common AraC/XylS structural scaffold is highly interconnected, with complex intra-protein and inter-domain communication pathways enabling allosteric regulation. At the same time, the observed epistasis and the low sequence identities of the natural homologs suggest that the structural scaffold and function of transcriptional regulation are nevertheless highly accommodating of amino acid changes., (© 2021 Wiley Periodicals LLC.)

Understanding how each residue position contributes to protein function has been a long-standing goal in protein science. Substitution studies have historically focused on conserved protein positions. However, substitutions of nonconserved positions can also modify function. Indeed, we recently identified nonconserved positions that have large substitution effects in human liver pyruvate kinase (hLPYK), including altered allosteric coupling. To facilitate a comparison of which characteristics determine when a nonconserved position does vs does not contribute to function, the goal of the current work was to identify neutral positions in hLPYK. However, existing hLPYK data showed that three features commonly associated with neutral positions-high sequence entropy, high surface exposure, and alanine scanning-lacked the sensitivity needed to guide experimental studies. We used multiple evolutionary patterns identified in a sequence alignment of the PYK family to identify which positions were least patterned, reasoning that these were most likely to be neutral. Nine positions were tested with a total of 117 amino acid substitutions. Although exploring all potential functions is not feasible for any protein, five parameters associated with substrate/effector affinities and allosteric coupling were measured for hLPYK variants. For each position, the aggregate functional outcomes of all variants were used to quantify a "neutrality" score. Three positions showed perfect neutral scores for all five parameters. Furthermore, the nine positions showed larger neutral scores than 17 positions located near allosteric binding sites. Thus, our strategy successfully enriched the dataset for positions with neutral and modest substitutions., (© 2020 Wiley Periodicals LLC.)

Human mutations often cause amino acid changes (variants) that can alter protein function or stability. Some variants fall at protein positions that experimentally exhibit "rheostatic" mutation outcomes (different amino acid substitutions lead to a range of functional outcomes). In ongoing studies of rheostat positions, we encountered the need to aggregate experimental results from multiple variants, to describe the overall roles of individual positions. Here, we present "RheoScale" which generates quantitative scores to discriminate rheostat positions from those with "toggle" (most substitutions abolish function) or "neutral" (most substitutions have wild-type function) outcomes. RheoScale scores facilitate correlations of experimental data (such as binding affinity or stability) with structural and bioinformatic analyses. The RheoScale calculator is encoded into a Microsoft Excel workbook and an R script. Example analyses are shown for three model protein systems, including one assessed via deep mutational scanning. The RheoScale calculator quickly and efficiently provided quantitative descriptions that were in good agreement with prior qualitative observations. As an example application, scores were compared to the example proteins' structures; strong rheostat positions tended to occur in dynamic locations. In the future, RheoScale scores can be easily integrated into computational studies to facilitate improved algorithms for predicting outcomes of human variants., (© 2018 Wiley Periodicals, Inc.)

As proteins evolve, amino acid positions key to protein structure or function are subject to mutational constraints. These positions can be detected by analyzing sequence families for amino acid conservation or for coevolution between pairs of positions. Coevolutionary scores are usually rank-ordered and thresholded to reveal the top pairwise scores, but they also can be treated as weighted networks. Here, we used network analyses to bypass a major complication of coevolution studies: For a given sequence alignment, alternative algorithms usually identify different, top pairwise scores. We reconciled results from five commonly-used, mathematically divergent algorithms (ELSC, McBASC, OMES, SCA, and ZNMI), using the LacI/GalR and 1,6-bisphosphate aldolase protein families as models. Calculations used unthresholded coevolution scores from which column-specific properties such as sequence entropy and random noise were subtracted; "central" positions were identified by calculating various network centrality scores. When compared among algorithms, network centrality methods, particularly eigenvector centrality, showed markedly better agreement than comparisons of the top pairwise scores. Positions with large centrality scores occurred at key structural locations and/or were functionally sensitive to mutations. Further, the top central positions often differed from those with top pairwise coevolution scores: instead of a few strong scores, central positions often had multiple, moderate scores. We conclude that eigenvector centrality calculations reveal a robust evolutionary pattern of constraints-detectable by divergent algorithms--that occur at key protein locations. Finally, we discuss the fact that multiple patterns coexist in evolutionary data that, together, give rise to emergent protein functions., (© 2015 Wiley Periodicals, Inc.)

Concomitant with the genomic era, many bioinformatics programs have been developed to identify functionally important positions from sequence alignments of protein families. To evaluate these analyses, many have used the LacI/GalR family and determined whether positions predicted to be "important" are validated by published experiments. However, we previously noted that predictions do not identify all of the experimentally important positions present in the linker regions of these homologs. In an attempt to reconcile these differences, we corrected and expanded the LacI/GalR sequence set commonly used in sequence/function analyses. Next, a variety of analyses were carried out (1) for the entire LacI/GalR sequence set and (2) for a subset of homologs with functionally-important "YxPxxxAxxL" motifs in their linkers. This strategy was devised to determine whether predictions could be improved by knowledge-based sequence sorting and-for some analyses-did increase the number of linker positions identified. However, two functionally important linker positions were not reliably identified by any analysis. Finally, we compared the new predictions to all known experimental data for E. coli LacI and three homologous linkers. From these, we estimate that >50% of positions are important to the functions of the LacI/GalR homologs. In corollary, neutral positions might occur less frequently and might be easier to detect in sequence analyses. Although analyses have successfully guided mutations that partially exchange protein functions, a better experimental understanding of the sequence/function relationships in protein families would be helpful for uncovering the remaining rules used by nature to evolve new protein functions., (Copyright © 2011 Wiley-Liss, Inc.)

In protein families, conserved residues often contribute to a common general function, such as DNA-binding. However, unique attributes for each homolog (e.g. recognition of alternative DNA sequences) must arise from variation in other functionally-important positions. The locations of these "specificity determinant" positions are obscured amongst the background of varied residues that do not make significant contributions to either structure or function. To isolate specificity determinants, a number of bioinformatics algorithms have been developed. When applied to the LacI/GalR family of transcription regulators, several specificity determinants are predicted in the 18 amino acids that link the DNA-binding and regulatory domains. However, results from alternative algorithms are only in partial agreement with each other. Here, we experimentally evaluate these predictions using an engineered repressor comprising the LacI DNA-binding domain, the LacI linker, and the GalR regulatory domain (LLhG). "Wild-type" LLhG has altered DNA specificity and weaker lacO(1) repression compared to LacI or a similar LacI:PurR chimera. Next, predictions of linker specificity determinants were tested, using amino acid substitution and in vivo repression assays to assess functional change. In LLhG, all predicted sites are specificity determinants, as well as three sites not predicted by any algorithm. Strategies are suggested for diminishing the number of false negative predictions. Finally, individual substitutions at LLhG specificity determinants exhibited a broad range of functional changes that are not predicted by bioinformatics algorithms. Results suggest that some variants have altered affinity for DNA, some have altered allosteric response, and some appear to have changed specificity for alternative DNA ligands.

Homologue function can be differentiated by changing residues that affect binding sites or long-range interactions. LacI and PurR are two proteins that represent the LacI/GalR family (>500 members) of bacterial transcription regulators. All members have distinct DNA-binding and regulatory domains linked by approximately 18 amino acids. Each homologue has specificity for different DNA and regulatory effector ligands; LacI and PurR also exhibit differences in allosteric communication between DNA and effector binding sites. A comparative study of LacI and PurR suggested that alterations in the interface between the regulatory domain and linker are important for differentiating their functions. Four residues (equivalent to LacI positions 48, 55, 58, and 61) appear particularly important for creating a unique interface and were predicted to be necessary for allosteric regulation. However, nearby residues in the linker interact with DNA ligand. Thus, differences observed in interactions between linker and regulatory domain may be the cause of altered function or an effect of the two proteins binding different DNA ligands. To separate these possibilities, we created a chimeric protein with the LacI DNA-binding domain/linker and the PurR regulatory domain (LLhP). If the interface requires homologue-specific interactions in order to propagate the signal from effector binding, then LLhP repression should not be allosterically regulated by effector binding. Experiments show that LLhP is capable of repression from lacO1 and, contrary to expectation, allosteric response is intact. Further, restoring the potential for PurR-like interactions via substitutions in the LLhP linker tends to diminish repression. These effects are especially pronounced for residues 58 and 61. Clearly, binding affinity of LLhP for the lacO1 DNA site is sensitive to long-range changes in the linker. This result also raises the possibility that mutations at positions 58 and 61 co-evolved with changes in the DNA-binding site. In addition, repression measured in the absence and presence of effector ligand shows that allosteric response increases for several LLhP variants with substitutions at positions 48 and 55. Thus, while side chain variation at these sites does not generally dictate the presence or absence of allostery, the nature of the amino acid can modulate the response to effector., (2007 Wiley-Liss, Inc.)