Insertions and Deletions (Indels): A Missing Piece of the Protein Engineering Jigsaw

Indels allow antiviral proteins to evolve functional novelty inaccessible by missense mutations

Antiviral proteins often evolve rapidly at virus-binding interfaces to defend against new viruses. We investigated whether antiviral adaptation via missense mutations might face limits, which insertion or deletion mutations (indels) could overcome. Using high-throughput saturation missense mutagenesis, we identify one such case of a nearly insurmountable evolutionary challenge: the human anti-retroviral protein TRIM5α requires more than five missense mutations in its specificity-determining v1 loop to restrict a divergent simian immunodeficiency virus (SIV). However, through a novel saturating indel scanning methodology, we find that duplicating just one amino acid in v1 enables human TRIM5α to potently restrict SIV in a single evolutionary step. Moreover, natural primate TRIM5α v1 loops have evolved indels that confer novel antiviral specificities. Thus, indels enable antiviral proteins to overcome viral challenges otherwise inaccessible by missense mutations. Our findings reveal the potential of often-overlooked indel mutations in driving protein innovation.

Deep indel mutagenesis reveals the impact of amino acid insertions and deletions on protein stability and function

Amino acid insertions and deletions (indels) are an abundant class of genetic variants. However, compared to substitutions, the effects of indels on protein stability are not well understood. To better understand indels here we analyse new and existing large-scale deep indel mutagenesis (DIM) of structurally diverse proteins. The effects of indels on protein stability vary extensively among and within proteins and are not well predicted by existing computational methods. To address this shortcoming we present INDELi, a series of models that combine experimental or predicted substitution effects and secondary structure information to provide good prediction of the effects of indels on both protein stability and pathogenicity. Moreover, quantifying the effects of indels on protein-protein interactions suggests that insertions can be an important class of gain-of-function variants. Our results provide an overview of the impact of indels on proteins and a method to predict their effects genome-wide.

From duplication to fusion: Expanding Dayhoff's model of protein evolution

Dayhoff's hypothesis suggests that complex proteins emerged from simpler peptides or domains, which duplicated and fused to create more complex proteins and novel functions. These processes expanded and diversified the protein repertoire within organisms. Extensive studies and reviews over the past two decades have highlighted the impact of gene duplication on protein evolution. However, the role of fusion in this evolutionary narrative remains less understood. This perspective seeks to address this gap by emphasizing the role of fusion in evolution. Fusion is critical in determining the evolutionary fate of duplicated protomers, either preserving their ancestral function or evolving entirely new functions. It complements mutations, insertions, and deletions as evolutionary steps to enhance protein evolvability by expanding the capacity of the protein to explore new structural and functional space.

Automated Engineering Protein Dynamics via Loop Grafting: Improving Renilla Luciferase Catalysis

Engineering protein dynamics is a challenging and unsolved problem in protein design. Loop transplantation or loop grafting has been previously employed to transfer dynamic properties between proteins. We recently released a LoopGrafter Web server to execute the loop grafting task, employing eight computational tools and one database. The LoopGrafter method relies on the prediction of the local dynamic behavior of the elements to be transplanted and has successfully reconstructed previously engineered sequences. However, it was unclear whether catalytically competitive previously uncharacterized designs could be obtained by this method. Here, we address this question, showing how LoopGrafter generates viable loop-grafted chimeras of luciferases, how these chimeras encompass the activity of interest and unique kinetic properties, and how all this process is done fully automatically and agnostic of any previous knowledge. All constructed designs proved to be catalytically active, and the most active one improved the activity of the template enzyme by 4 orders of magnitude. The computational details and parameter optimization of the sequence pairing step of the LoopGrafter workflow are revealed. The optimized and experimentally validated loop grafting workflow available as a fully automated Web server represents a powerful approach for engineering catalytically efficient enzymes by modification of protein dynamics.

Systematic characterization of indel variants using a yeast-based protein folding sensor

Gene variants resulting in insertions or deletions of amino acid residues (indels) have important consequences for evolution and are often linked to disease, yet, compared to missense variants, the effects of indels are poorly understood and predicted. We developed a sensitive protein folding sensor based on the complementation of uracil auxotrophy in yeast by circular permutated orotate phosphoribosyltransferase (CPOP). The sensor reports on the folding of disease-linked missense variants and de-novo-designed proteins. Applying the folding sensor to a saturated library of single-residue indels in human dihydrofolate reductase (DHFR) revealed that most regions that tolerate indels are confined to internal loops, the termini, and a central α helix. Several indels are temperature sensitive, and folding is rescued upon binding to methotrexate. Rosetta and AlphaFold2 predictions correlate with the observed effects, suggesting that most indels destabilize the native fold and that these computational tools are useful for the classification of indels observed in population sequencing.

Molecular Markers Specific for the Pseudomonadaceae Genera Provide Novel and Reliable Means for the Identification of Other Pseudomonas Strains/spp. Related to These Genera

Background/Objectives: Taxon-specific conserved signature indels (CSIs) exhibit a strong predictive ability of being found in other members of specific taxa/genera. Recently, multiple exclusively shared CSIs were identified for several newly described Pseudomonadaceae genera (viz. Aquipseudomonas, Atopomonas, Caenipseudomonas, Chryseomonas Ectopseudomonas, Geopseudomonas, Halopseudomonas, Metapseudomonas, Phytopseudomonas, Serpens, Stutzerimonas, Thiopseudomonas, and Zestomonas). This study examines the potential applications of these CSIs for identifying other Pseudomonas spp. (strains) related to these genera. Methods: This work utilized the AppIndels.com server, which uses information regarding the presence of known taxon-specific CSIs in a genome for predicting its taxonomic affiliation. For this purpose, sequence information for different CSIs specific for the Pseudomonadaceae species/genera were added to the server's database. Results: The AppIndels server was used to predict the taxonomic affiliation of 1972 genomes of unclassified Pseudomonas spp. (strains/isolates). Based upon finding a significant number of CSIs matching a specific taxon, the AppIndels server made positive predictions regarding the taxonomic affiliation of 299 examined genomes into the following clades/genera: Pseudomonas sensu stricto clade (46), Pseudomonas aeruginosa (64), Ectopseudomonas (46), Chryseomonas (32), Stutzerimonas (31), Metapseudomonas (22), Aquipseudomonas (21), Phytopseudomonas (17), Halopseudomonas (9), Geopseudomonas (4), Thiopseudomonas (3), Serpens (2), and Caenipseudomonas and Zestomonas (1 each). Phylogenetic studies confirmed that the taxonomic predictions by the server were 100% accurate. Conclusions: Our results demonstrate that the CSIs specific for Pseudomonadaceae species/genera, in conjunction with the AppIndels server, provides a novel and useful tool for identifying other species/strains affiliated with these species/genera. Phylogenetic studies suggest that many examined Pseudomonas strains constitute novel species in the indicated genera.

Crispant analysis in zebrafish as a tool for rapid functional screening of disease-causing genes for bone fragility

Heritable fragile bone disorders (FBDs), ranging from multifactorial to rare monogenic conditions, are characterized by an elevated fracture risk. Validating causative genes and understanding their mechanisms remain challenging. We assessed a semi-high throughput zebrafish screening platform for rapid in vivo functional testing of candidate FBD genes. Six genes linked to severe recessive osteogenesis imperfecta (OI) and four associated with bone mineral density (BMD) from genome-wide association studies were analyzed. Using CRISPR/Cas9-based crispant screening in F0 mosaic founder zebrafish, Next-generation sequencing confirmed high indel efficiency (mean 88%), mimicking stable knock-out models. Skeletal phenotyping at 7, 14, and 90 days post-fertilization (dpf) using microscopy, Alizarin Red S staining, and microCT was performed. Larval crispants showed variable osteoblast and mineralization phenotypes, while adult crispants displayed consistent skeletal defects, including malformed neural and haemal arches, vertebral fractures and fusions, and altered bone volume and density. In addition, aldh7a1 and mbtps2 crispants experienced increased mortality due to severe skeletal deformities. RT-qPCR revealed differential expression of osteogenic markers bglap and col1a1a, highlighting their biomarker potential. Our results establish zebrafish crispant screening as a robust tool for FBD gene validation, combining skeletal and molecular analyses across developmental stages to uncover novel insights into gene functions in bone biology.

Selection of a promiscuous minimalist cAMP phosphodiesterase from a library of de novo designed proteins

The ability of unevolved amino acid sequences to become biological catalysts was key to the emergence of life on Earth. However, billions of years of evolution separate complex modern enzymes from their simpler early ancestors. To probe how unevolved sequences can develop new functions, we use ultrahigh-throughput droplet microfluidics to screen for phosphoesterase activity amidst a library of more than one million sequences based on a de novo designed 4-helix bundle. Characterization of hits revealed that acquisition of function involved a large jump in sequence space enriching for truncations that removed >40% of the protein chain. Biophysical characterization of a catalytically active truncated protein revealed that it dimerizes into an α-helical structure, with the gain of function accompanied by increased structural dynamics. The identified phosphodiesterase is a manganese-dependent metalloenzyme that hydrolyses a range of phosphodiesters. It is most active towards cyclic AMP, with a rate acceleration of ~109 and a catalytic proficiency of >1014 M-1, comparable to larger enzymes shaped by billions of years of evolution.

Optimal phylogenetic reconstruction of insertion and deletion events

MOTIVATION

Insertions and deletions (indels) influence the genetic code in fundamentally distinct ways from substitutions, significantly impacting gene product structure and function. Despite their influence, the evolutionary history of indels is often neglected in phylogenetic tree inference and ancestral sequence reconstruction, hindering efforts to comprehend biological diversity determinants and engineer variants for medical and industrial applications.

RESULTS

We frame determining the optimal history of indel events as a single Mixed-Integer Programming (MIP) problem, across all branch points in a phylogenetic tree adhering to topological constraints, and all sites implied by a given set of aligned, extant sequences. By disentangling the impact on ancestral sequences at each branch point, this approach identifies the minimal indel events that jointly explain the diversity in sequences mapped to the tips of that tree. MIP can recover alternate optimal indel histories, if available. We evaluated MIP for indel inference on a dataset comprising 15 real phylogenetic trees associated with protein families ranging from 165 to 2000 extant sequences, and on 60 synthetic trees at comparable scales of data and reflecting realistic rates of mutation. Across relevant metrics, MIP outperformed alternative parsimony-based approaches and reported the fewest indel events, on par or below their occurrence in synthetic datasets. MIP offers a rational justification for indel patterns in extant sequences; importantly, it uniquely identifies global optima on complex protein data sets without making unrealistic assumptions of independence or evolutionary underpinnings, promising a deeper understanding of molecular evolution and aiding novel protein design.

AVAILABILITY AND IMPLEMENTATION

The implementation is available via GitHub at https://github.com/santule/indelmip.

Indels allow antiviral proteins to evolve functional novelty inaccessible by missense mutations

Antiviral proteins often evolve rapidly at virus-binding interfaces to defend against new viruses. We investigated whether antiviral adaptation via missense mutations might face limits, which insertion or deletion mutations (indels) could overcome. We report one such case of a nearly insurmountable evolutionary challenge: the human anti-retroviral protein TRIM5α requires more than five missense mutations in its specificity-determining v1 loop to restrict a divergent simian immunodeficiency virus (SIV). However, duplicating just one amino acid in v1 enables human TRIM5α to potently restrict SIV in a single evolutionary step. Moreover, natural primate TRIM5α v1 loops have evolved indels that confer novel antiviral specificities. Thus, indels enable antiviral proteins to overcome viral challenges inaccessible by missense mutations, revealing the potential of these often-overlooked mutations in driving protein innovation.

Remote loop evolution reveals a complex biological function for chitinase enzymes beyond the active site

Loops are small secondary structural elements that play a crucial role in the emergence of new enzyme functions. However, the evolutionary molecular mechanisms how proteins acquire these loop elements and obtain new function is poorly understood. To address this question, we study glycoside hydrolase family 19 (GH19) chitinase-an essential enzyme family for pathogen degradation in plants. By revealing the evolutionary history and loops appearance of GH19 chitinase, we discover that one loop which is remote from the catalytic site, is necessary to acquire the new antifungal activity. We demonstrate that this remote loop directly accesses the fungal cell wall, and surprisingly, it needs to adopt a defined structure supported by long-range intramolecular interactions to perform its function. Our findings prove that nature applies this strategy at the molecular level to achieve a complex biological function while maintaining the original activity in the catalytic pocket, suggesting an alternative way to design new enzyme function.

Persistent homology reveals strong phylogenetic signal in 3D protein structures

Changes that occur in proteins over time provide a phylogenetic signal that can be used to decipher their evolutionary history and the relationships between organisms. Sequence comparison is the most common way to access this phylogenetic signal, while those based on 3D structure comparisons are still in their infancy. In this study, we propose an effective approach based on Persistent Homology Theory (PH) to extract the phylogenetic information contained in protein structures. PH provides efficient and robust algorithms for extracting and comparing geometric features from noisy datasets at different spatial resolutions. PH has a growing number of applications in the life sciences, including the study of proteins (e.g. classification, folding). However, it has never been used to study the phylogenetic signal they may contain. Here, using 518 protein families, representing 22,940 protein sequences and structures, from 10 major taxonomic groups, we show that distances calculated with PH from protein structures correlate strongly with phylogenetic distances calculated from protein sequences, at both small and large evolutionary scales. We test several methods for calculating PH distances and propose some refinements to improve their relevance for addressing evolutionary questions. This work opens up new perspectives in evolutionary biology by proposing an efficient way to access the phylogenetic signal contained in protein structures, as well as future developments of topological analysis in the life sciences.

Machine Learning-Guided Protein Engineering

Recent progress in engineering highly promising biocatalysts has increasingly involved machine learning methods. These methods leverage existing experimental and simulation data to aid in the discovery and annotation of promising enzymes, as well as in suggesting beneficial mutations for improving known targets. The field of machine learning for protein engineering is gathering steam, driven by recent success stories and notable progress in other areas. It already encompasses ambitious tasks such as understanding and predicting protein structure and function, catalytic efficiency, enantioselectivity, protein dynamics, stability, solubility, aggregation, and more. Nonetheless, the field is still evolving, with many challenges to overcome and questions to address. In this Perspective, we provide an overview of ongoing trends in this domain, highlight recent case studies, and examine the current limitations of machine learning-based methods. We emphasize the crucial importance of thorough experimental validation of emerging models before their use for rational protein design. We present our opinions on the fundamental problems and outline the potential directions for future research.

A cellular selection identifies elongated flavodoxins that support electron transfer to sulfite reductase

Flavodoxins (Flds) mediate the flux of electrons between oxidoreductases in diverse metabolic pathways. To investigate whether Flds can support electron transfer to a sulfite reductase (SIR) that evolved to couple with a ferredoxin, we evaluated the ability of Flds to transfer electrons from a ferredoxin-NADP reductase (FNR) to a ferredoxin-dependent SIR using growth complementation of an Escherichia coli strain with a sulfur metabolism defect. We show that Flds from cyanobacteria complement this growth defect when coexpressed with an FNR and an SIR that evolved to couple with a plant ferredoxin. When we evaluated the effect of peptide insertion on Fld-mediated electron transfer, we observed a sensitivity to insertions within regions predicted to be proximal to the cofactor and partner binding sites, while a high insertion tolerance was detected within loops distal from the cofactor and within regions of helices and sheets that are proximal to those loops. Bioinformatic analysis showed that natural Fld sequence variability predicts a large fraction of the motifs that tolerate insertion of the octapeptide SGRPGSLS. These results represent the first evidence that Flds can support electron transfer to assimilatory SIRs, and they suggest that the pattern of insertion tolerance is influenced by interactions with oxidoreductase partners.

Molecular determinants of protein evolvability

The plethora of biological functions that sustain life is rooted in the remarkable evolvability of proteins. An emerging view highlights the importance of a protein's initial state in dictating evolutionary success. A deeper comprehension of the mechanisms that govern the evolvability of these initial states can provide invaluable insights into protein evolution. In this review, we describe several molecular determinants of protein evolvability, unveiled by experimental evolution and ancestral sequence reconstruction studies. We further discuss how genetic variation and epistasis can promote or constrain functional innovation and suggest putative underlying mechanisms. By establishing a clear framework for these determinants, we provide potential indicators enabling the forecast of suitable evolutionary starting points and delineate molecular mechanisms in need of deeper exploration.

Base editor screens for in situ mutational scanning at scale

A fundamental challenge in biology is understanding the molecular details of protein function. How mutations alter protein activity, regulation, and response to drugs is of critical importance to human health. Recent years have seen the emergence of pooled base editor screens for in situ mutational scanning: the interrogation of protein sequence-function relationships by directly perturbing endogenous proteins in live cells. These studies have revealed the effects of disease-associated mutations, discovered novel drug resistance mechanisms, and generated biochemical insights into protein function. Here, we discuss how this "base editor scanning" approach has been applied to diverse biological questions, compare it with alternative techniques, and describe the emerging challenges that must be addressed to maximize its utility. Given its broad applicability toward profiling mutations across the proteome, base editor scanning promises to revolutionize the investigation of proteins in their native contexts.

Mind the gap

Amino acid deletions are high-risk, high-reward mutations, yet structural consequences are poorly understood. In this issue of Structure, Woods et al. (2023) individually deleted 65 residues from a small α-helical protein, structurally assayed the 17 soluble variants, and developed a computational model of deletion solubility combining Rosetta and AlphaFold2.

Epistatic Effects Between Amino Acid Insertions and Substitutions Mediate Toxin resistance of Vertebrate Na+,K+-ATPases

The recurrent evolution of resistance to cardiotonic steroids (CTS) across diverse animals most frequently involves convergent amino acid substitutions in the H1-H2 extracellular loop of Na+,K+-ATPase (NKA). Previous work revealed that hystricognath rodents (e.g., chinchilla) and pterocliform birds (sandgrouse) have convergently evolved amino acid insertions in the H1-H2 loop, but their functional significance was not known. Using protein engineering, we show that these insertions have distinct effects on CTS resistance in homologs of each of the two species that strongly depend on intramolecular interactions with other residues. Removing the insertion in the chinchilla NKA unexpectedly increases CTS resistance and decreases NKA activity. In the sandgrouse NKA, the amino acid insertion and substitution Q111R both contribute to an augmented CTS resistance without compromising ATPase activity levels. Molecular docking simulations provide additional insight into the biophysical mechanisms responsible for the context-specific mutational effects on CTS insensitivity of the enzyme. Our results highlight the diversity of genetic substrates that underlie CTS insensitivity in vertebrate NKA and reveal how amino acid insertions can alter the phenotypic effects of point mutations at key sites in the same protein domain.